current state of radiation belt modeling: successes and...
TRANSCRIPT
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
Current state of Radiation Belt Modeling
Successes and ChallengesR Friedel13 Yue Chen13 G Cunningham13 S Morley1
J Lichtenberger2 Lilla Juhasz2
4th Asia Oceania Space Weather Alliance Workshop
Jeju Republic of Korea Oct 24-27 2016
Friedel - 13h30 Keynote 2 Oct 26 2016 LA-UR-27986
1Los Alamos National Laboratory Los Alamos USA 2Eoumltvoumls University Budapest Hungary 6New Mexico Consortium Los Alamos USA
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Motivation
Background ndash why 3D diffusion codes
Inputs needed for 3D diffusion codes
ndash Initial State
ndash Chorus Hiss EMIC (pitch angleenergy diffusion)
ndash ULF (radial diffusion)
ndash Outer boundary (Magnetopause)
ndash Background electron density
ndash Low energy boundary (Oct 2012 event)
Nowcast to Forecast
DREAM-RT RBSP AE9 Comparison
Contents
Slide 2
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Focus of this talk is on energetic (~MeV) electron
radiation belt modeling
This population is the cause of deep dielectric
charging and contributes to overall dose
The region to be covered is from geosynchronous to
low-Earth orbit
We ask the question
What currently are the main limitations in modeling this
population in the Earthrsquos Radiation Belts
Motivation
Slide 3
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundResults from Reeves et al 2003
Slide 4
Difficulty in understanding dynamics of system Wide range of responses for similar geomagnetic storms ndash Increase Decrease Shift of peak No change -are all possible responses
Many processes operate simultaneously that cannot be separated observationally
Response thought to be result of a delicate balance of loss transport and internal energization processes
Acceleration and loss of relativistic electrons during geomagnetic storms GD Reeves KL McAdams RHW Friedel TP OBrien
Geophysical Research Letters 30 (10)
451 Citations ()
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Quick QuestionWhy canrsquot current models reproduce the observed dynamics
Slide 5
We have a range of quite sophisticated modelling approaches for the inner radiation belts that include transport acceleration and losses Whatrsquos missing
I would hold that our current models DO include the major physical processes but that we are driving these models with broad statistical inputs (DLL wave statistics driving DEE and Dαα simple background density models) and badly constrained boundary conditions
Simply Average inputs in -gt average behaviour out
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 6
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion Simple lifetimes to model pitch angle diffusion loss
2 RAM-type drift physics codes Uses DLL in static fields or calculates drifts in self consistent magnetic and electric fields Simple lifetimes to model pitch angle diffusion loss Uses DEE and Dαα + cross terms) with statistic wave amplitudes or with calculated growth
rates -gt wave amplitudes
3 MHD codes with particle tracers Radial diffusion from self-consistent fields Traced particles use DEE and Dαα with statistic wave amplitudes
4 Hybrid codes Can treat self-consistent EMIC whistler growth amp interaction Limited coupling to global codes
5 PIC codes Once these do the global magnetosphere we may all be able to go homehellip Prohibitive computational needs
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 7
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion
Likely to be the only candidate for an operational MeV radiation belt model
for the foreseeable future eg
Salammbocirc (ONERA)
SpaceCastSpaceStorm (BAS)
VERB (UCLA)
DREAM3D (LANL)
hellip
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Motivation
Background ndash why 3D diffusion codes
Inputs needed for 3D diffusion codes
ndash Initial State
ndash Chorus Hiss EMIC (pitch angleenergy diffusion)
ndash ULF (radial diffusion)
ndash Outer boundary (Magnetopause)
ndash Background electron density
ndash Low energy boundary (Oct 2012 event)
Nowcast to Forecast
DREAM-RT RBSP AE9 Comparison
Contents
Slide 2
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Focus of this talk is on energetic (~MeV) electron
radiation belt modeling
This population is the cause of deep dielectric
charging and contributes to overall dose
The region to be covered is from geosynchronous to
low-Earth orbit
We ask the question
What currently are the main limitations in modeling this
population in the Earthrsquos Radiation Belts
Motivation
Slide 3
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundResults from Reeves et al 2003
Slide 4
Difficulty in understanding dynamics of system Wide range of responses for similar geomagnetic storms ndash Increase Decrease Shift of peak No change -are all possible responses
Many processes operate simultaneously that cannot be separated observationally
Response thought to be result of a delicate balance of loss transport and internal energization processes
Acceleration and loss of relativistic electrons during geomagnetic storms GD Reeves KL McAdams RHW Friedel TP OBrien
Geophysical Research Letters 30 (10)
451 Citations ()
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Quick QuestionWhy canrsquot current models reproduce the observed dynamics
Slide 5
We have a range of quite sophisticated modelling approaches for the inner radiation belts that include transport acceleration and losses Whatrsquos missing
I would hold that our current models DO include the major physical processes but that we are driving these models with broad statistical inputs (DLL wave statistics driving DEE and Dαα simple background density models) and badly constrained boundary conditions
Simply Average inputs in -gt average behaviour out
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 6
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion Simple lifetimes to model pitch angle diffusion loss
2 RAM-type drift physics codes Uses DLL in static fields or calculates drifts in self consistent magnetic and electric fields Simple lifetimes to model pitch angle diffusion loss Uses DEE and Dαα + cross terms) with statistic wave amplitudes or with calculated growth
rates -gt wave amplitudes
3 MHD codes with particle tracers Radial diffusion from self-consistent fields Traced particles use DEE and Dαα with statistic wave amplitudes
4 Hybrid codes Can treat self-consistent EMIC whistler growth amp interaction Limited coupling to global codes
5 PIC codes Once these do the global magnetosphere we may all be able to go homehellip Prohibitive computational needs
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 7
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion
Likely to be the only candidate for an operational MeV radiation belt model
for the foreseeable future eg
Salammbocirc (ONERA)
SpaceCastSpaceStorm (BAS)
VERB (UCLA)
DREAM3D (LANL)
hellip
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Focus of this talk is on energetic (~MeV) electron
radiation belt modeling
This population is the cause of deep dielectric
charging and contributes to overall dose
The region to be covered is from geosynchronous to
low-Earth orbit
We ask the question
What currently are the main limitations in modeling this
population in the Earthrsquos Radiation Belts
Motivation
Slide 3
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundResults from Reeves et al 2003
Slide 4
Difficulty in understanding dynamics of system Wide range of responses for similar geomagnetic storms ndash Increase Decrease Shift of peak No change -are all possible responses
Many processes operate simultaneously that cannot be separated observationally
Response thought to be result of a delicate balance of loss transport and internal energization processes
Acceleration and loss of relativistic electrons during geomagnetic storms GD Reeves KL McAdams RHW Friedel TP OBrien
Geophysical Research Letters 30 (10)
451 Citations ()
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Quick QuestionWhy canrsquot current models reproduce the observed dynamics
Slide 5
We have a range of quite sophisticated modelling approaches for the inner radiation belts that include transport acceleration and losses Whatrsquos missing
I would hold that our current models DO include the major physical processes but that we are driving these models with broad statistical inputs (DLL wave statistics driving DEE and Dαα simple background density models) and badly constrained boundary conditions
Simply Average inputs in -gt average behaviour out
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 6
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion Simple lifetimes to model pitch angle diffusion loss
2 RAM-type drift physics codes Uses DLL in static fields or calculates drifts in self consistent magnetic and electric fields Simple lifetimes to model pitch angle diffusion loss Uses DEE and Dαα + cross terms) with statistic wave amplitudes or with calculated growth
rates -gt wave amplitudes
3 MHD codes with particle tracers Radial diffusion from self-consistent fields Traced particles use DEE and Dαα with statistic wave amplitudes
4 Hybrid codes Can treat self-consistent EMIC whistler growth amp interaction Limited coupling to global codes
5 PIC codes Once these do the global magnetosphere we may all be able to go homehellip Prohibitive computational needs
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 7
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion
Likely to be the only candidate for an operational MeV radiation belt model
for the foreseeable future eg
Salammbocirc (ONERA)
SpaceCastSpaceStorm (BAS)
VERB (UCLA)
DREAM3D (LANL)
hellip
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundResults from Reeves et al 2003
Slide 4
Difficulty in understanding dynamics of system Wide range of responses for similar geomagnetic storms ndash Increase Decrease Shift of peak No change -are all possible responses
Many processes operate simultaneously that cannot be separated observationally
Response thought to be result of a delicate balance of loss transport and internal energization processes
Acceleration and loss of relativistic electrons during geomagnetic storms GD Reeves KL McAdams RHW Friedel TP OBrien
Geophysical Research Letters 30 (10)
451 Citations ()
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Quick QuestionWhy canrsquot current models reproduce the observed dynamics
Slide 5
We have a range of quite sophisticated modelling approaches for the inner radiation belts that include transport acceleration and losses Whatrsquos missing
I would hold that our current models DO include the major physical processes but that we are driving these models with broad statistical inputs (DLL wave statistics driving DEE and Dαα simple background density models) and badly constrained boundary conditions
Simply Average inputs in -gt average behaviour out
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 6
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion Simple lifetimes to model pitch angle diffusion loss
2 RAM-type drift physics codes Uses DLL in static fields or calculates drifts in self consistent magnetic and electric fields Simple lifetimes to model pitch angle diffusion loss Uses DEE and Dαα + cross terms) with statistic wave amplitudes or with calculated growth
rates -gt wave amplitudes
3 MHD codes with particle tracers Radial diffusion from self-consistent fields Traced particles use DEE and Dαα with statistic wave amplitudes
4 Hybrid codes Can treat self-consistent EMIC whistler growth amp interaction Limited coupling to global codes
5 PIC codes Once these do the global magnetosphere we may all be able to go homehellip Prohibitive computational needs
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 7
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion
Likely to be the only candidate for an operational MeV radiation belt model
for the foreseeable future eg
Salammbocirc (ONERA)
SpaceCastSpaceStorm (BAS)
VERB (UCLA)
DREAM3D (LANL)
hellip
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Quick QuestionWhy canrsquot current models reproduce the observed dynamics
Slide 5
We have a range of quite sophisticated modelling approaches for the inner radiation belts that include transport acceleration and losses Whatrsquos missing
I would hold that our current models DO include the major physical processes but that we are driving these models with broad statistical inputs (DLL wave statistics driving DEE and Dαα simple background density models) and badly constrained boundary conditions
Simply Average inputs in -gt average behaviour out
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 6
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion Simple lifetimes to model pitch angle diffusion loss
2 RAM-type drift physics codes Uses DLL in static fields or calculates drifts in self consistent magnetic and electric fields Simple lifetimes to model pitch angle diffusion loss Uses DEE and Dαα + cross terms) with statistic wave amplitudes or with calculated growth
rates -gt wave amplitudes
3 MHD codes with particle tracers Radial diffusion from self-consistent fields Traced particles use DEE and Dαα with statistic wave amplitudes
4 Hybrid codes Can treat self-consistent EMIC whistler growth amp interaction Limited coupling to global codes
5 PIC codes Once these do the global magnetosphere we may all be able to go homehellip Prohibitive computational needs
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 7
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion
Likely to be the only candidate for an operational MeV radiation belt model
for the foreseeable future eg
Salammbocirc (ONERA)
SpaceCastSpaceStorm (BAS)
VERB (UCLA)
DREAM3D (LANL)
hellip
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 6
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion Simple lifetimes to model pitch angle diffusion loss
2 RAM-type drift physics codes Uses DLL in static fields or calculates drifts in self consistent magnetic and electric fields Simple lifetimes to model pitch angle diffusion loss Uses DEE and Dαα + cross terms) with statistic wave amplitudes or with calculated growth
rates -gt wave amplitudes
3 MHD codes with particle tracers Radial diffusion from self-consistent fields Traced particles use DEE and Dαα with statistic wave amplitudes
4 Hybrid codes Can treat self-consistent EMIC whistler growth amp interaction Limited coupling to global codes
5 PIC codes Once these do the global magnetosphere we may all be able to go homehellip Prohibitive computational needs
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 7
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion
Likely to be the only candidate for an operational MeV radiation belt model
for the foreseeable future eg
Salammbocirc (ONERA)
SpaceCastSpaceStorm (BAS)
VERB (UCLA)
DREAM3D (LANL)
hellip
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundInner Radiation Belt Modeling Approaches
Slide 7
Main classes of models
1 Diffusion models based on Fokker-Planck Equation Uses diffusion coefficients to model the effects of waves on radial pitch angle energy
and cross diffusion
Likely to be the only candidate for an operational MeV radiation belt model
for the foreseeable future eg
Salammbocirc (ONERA)
SpaceCastSpaceStorm (BAS)
VERB (UCLA)
DREAM3D (LANL)
hellip
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
BackgroundDiffusion coefficient calculation (Glauert Summers Albert)
Slide 8
Wave particle interaction diffusion coefficient calculations based on quasi-linear theory are computationally expensive and the community has spent a lot of effort to perform these calculations with varying degrees of approximations
For the waves
- First order resonances only
- Parallel propagation of waves only
- Assumed k-distribution of waves (guided by data)
- Assumed frequency distribution of waves (guided by data)
- Fixed K-distribution along field lines
- No feedback of particles on waves no damping
- Currently parameterized by wave power only
For background environmental conditions
- Dipole magnetic field- Advanced dynamic field
models- Simple background
density models- Simple ion composition
models
For global wave power distribution
- We do not have global in-situ wave data
- Simple statistics based on geomagnetic activity indices
- Assumes instantaneous MLT distribution = statistical MLT distribution
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
The biggest uncertainty in ANY forward modeling comes from
the fidelity of the initial state (eg DREAM G Reeves LANL)
Ongoing KSWC LANL NOAA collaboration to run a version of real-
time dream at KSWC Initially with GOES data later RBSP beacon data
Initial State
Slide 9
Data
Assimilation
Model
GEO amp GPS amp
Polar
Observations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMICWave Models ndash Model grid and distribution in one bin
Slide 10
L-shell [3 12] in step of 2
Local Time [0 24] hr in step of 1 hr
Mag Latitude Ranges [0 10] [10 25] [25
35] and gt35 deg
AE ranges lt100nT [100 300] nT and
gt300nT
Example Chorus Wave Model
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Statistical wave inputs for the calculation of diffusion coefficients are
not adequate
Use of operational LEO observations as Chorus proxy
Chorus Hiss EMIC
Slide 11
Glo
ba
l time
-d
ep
en
de
nt c
ho
rus
ma
ps
from
low
-E
arth
-o
rbit e
lec
tron
pre
cip
itatio
n a
nd
Va
n A
llen
Pro
be
s d
ata
Che
n Y
et a
l Ge
op
hysic
al R
ese
arc
h L
ette
rs 2
01
4 F
eb
16
Vo
l41
(3)
Similar work
Constructing the global distribution of chorus wave intensity using measurements of electrons
by the POES satellites and waves by the Van Allen Probes
Li W et al Geophysical Research Letters 2013 Vol40(17)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Chorus Hiss EMIC
Slide 12
bull Estimate in-situ wave distribution and properties from ground based
VLF measurements
bull Huge availability of ground based data eg ADWANET
Ground based
observations as
proxies
Need research to
establish transfer
functions between
ground
observations and
in-situ waves
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Radial diffusion is one of
the major physical process
in the radiation belt yet
there is little agreement on
the best way to obtain it
Ground based global ULF
measurements offer the
only viable route for
obtaining ongoing time-
varying DLL
Plot from ldquoULF wave derived radiation belt
radial diffusion coefficientsrdquo JGR Ozeke at
al 2012
ULF
Slide 13
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
For 3D diffusion codes the last closed drift shell is the outer
boundary for trapped electrons
The last closed drift shell can be calculated by establishing the
largest possible L from magnetic field models
Outer boundary
Slide 14
Plot from ldquoL neural
networks from
different magnetic field
models and their
applicability Y Yu et
al JGR 2012
LANL freely available
from
wwwlanlstarlanlgov
(Josef Koller)
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Needed in the calculation
of all diffusion coefficients
ldquoNowcastrdquo of the
plasmasphere density
possible using ground
based inputs (whistlers
field line resonances
together with a data
assimilative code
(PLASMON FP7 project J
Lichtenberger)
Background electron density
Slide 15
Modeled electron lifetimes from Hiss
C Jeffery LANL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analyses of whistlersvirtual (whistler) trace transformation [Lichtenberger JGR 2009]
Whistler Nose frequency
related to equatorial electron
density and density profile
along field line
log10 neq=A + BsdotL
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Automated analysis of field line resonancesCross phase method FLRINV [Berube et al 2003]
Example of automated detection of resonance frequency ndash
example of continuous detection over ~12 hours from
European EMMA chain of magnetometer stations
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
3D diffusion codes treat electrons dominated by magnetic
field drifts (E gt 100keV)
100 keV at low L has plasmasheet origin of 1-10keV particles
that are not provided by the model
Models need this lower energy boundary at all L at all times
Typically this boundary is specified ONCE in the initial state
Specifying a 1-10keV source at the outer boundary Radial
diffusion is not adequate for their transport
Results from W Tu et al ldquoEvent-specific chorus wave and
electron seed population models in DREAM3D using the Van
Allen Probes Geophys Res Lett 2014
Low energy boundary
Slide 18
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Low energy boundary from VLF- a new ground-based approach Lilla Juhaz ELTE
Slide 19
Energetic electron density estimation from whistler-mode chorus emissions
Omura Y Y Katoh and D Summers (2008) Theory and simulation of the generation of whistler-mode chorus J Geophys Res 113
Omura Y and D Nunn (2011) Triggering process of whistler mode chorus emissions in the magnetosphere J Geophys Res 116
Studies on generation of whistler-mode chorus revealed two important relations
bull There is a simple relation between the frequency sweep rate of chorus
emissions and the wave amplitude at the equator
bull The wave amplitude is close to the ldquooptimal amplituderdquo that is proportional to
the density of the energetic electrons
In-situ measurements (ie at the equator) are rare Ground based VLF receivers
are able to detect chorus but need to take propagation effects into account
Themis D
dawn
6RE
equator
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 20
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM3D Simulation of the
Oct 2012 event
Slide 21
3L
4
5
6RD only
Last closed drift shell
3
L
4
5
6
7
9
11
10-6
10-7
10-8
10-9
L
TS045
10-10
PSD data micro=2000 MeVG K=01 G12Re
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
10-6
10-7
10-8
10-9
10-10
bull Modeling the enhancementndash Event-specific chorus waves
ndash Realistic source population
(100s keV)
3
L
4
5
6 10-6
10-7
10-8
10-9
10-10
RD+chorus +Seed
micro=88 MeVG
K=01 G12Re
3
L
4
5
6
RD only
Oct 6 Oct 7 Oct 8 Oct 9
2012
Oct 10 Oct 11
electron flux data
100
102
104
106
108L=42 αeq=50o
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
High quality science grade data are rare and NOT useful
for operations (CRRES -gt RBSP 22 year gap )
ldquoOperationalrdquo data (LANL GEO Galileo GPS etc) while
plentiful may not to be publically available
Some operational assets may have ldquoassuredrdquo availability
(GOES POESJPSS)
Suggestions for future operational data providers
ndash Other models
ndash Cubesat constellation
Path Forward
Slide 22
ndash Ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Path Forward
Slide 23
ndash Ground based data
~$1M = one Cubesat
~$20K = One VLF Mag Ground Station
50 Ground Stations for the price of one Cubesat
So where should we invest
Invest in the research needed to relate high quality in situ
data to corresponding ground based data
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
As shown here specification of the required
boundary conditions and inputs required is non
trivial even in the presence of some data
How to do this in a forecast mode
Additional research needed to set up proxy
relationships for all the inputs tying them back to
Kp Dst Solar Wind data from L1 - which
ultimately need to rely on ldquogoodrdquo future
predictions of conditions at L1
Nowcast to forecast
Slide 24
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
DREAM-RT ndash Processing Chart
LANL-KSWC collaboration
Slide 25
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV
Operated by Los Alamos National Security LLC for the US Department of Energys NNSA
UNCLASSIFIED
4th Asia Oceania Space Weather Alliance Workshop - Jeju Republic of Korea Oct 24-27 2016
Slide 26
DREAM-RT1994-084 LANL-01A LANL-04A
Flux 15 MeV
RBSP-A MagEIS
Flux 15 MeV
January 2014
AE-9
Flux 15 MeV