status and overview of ipwgof ipwg–related precipitation
TRANSCRIPT
Status and Overview of IPWG relatedof IPWG–related
Precipitation Data SetsPrecipitation Data Sets
Chris Kiddand many many others…and many, many others…
NASA WetNet: Tallahassee c.1989NASA WetNet: Tallahassee c.1989
IPWG#5, Hamburg, 11-15 October 2010
NASA WetNet PIP-1 Bristol c.1991NASA WetNet PIP 1 Bristol c.1991
IPWG#5, Hamburg, 11-15 October 2010
GPCP AIP-3 Shinfield Park c.1993
IPWG#5, Hamburg, 11-15 October 2010
IPWG#4 CMA Beijing 2008IPWG#4 CMA Beijing 2008
IPWG#5, Hamburg, 11-15 October 2010
History of precipitation 19601959 Vanguard 2
1960 TIROS-1
observation capabilities1970
1966 ATS-1
1970 1974 SMS-1
1978 SMMR1980 1983 NOAA-8
1987 SSM/I
1990
1997 TRMM
1988 WetNet1990 PIP-11989 AIP-1
20002003 SSM/IS
2002 MSG
C
1998 AMSU1993 PIP-21996 PIP-3
1991 AIP-21994 AIP-3
2001 IPWG
20102010 Megha-Tropiques
2006 Cloudsat2001 IPWG2004 PEHRPP
2020
2013 GPM
2010 Megha Tropiques
2018 PPM
IPWG#5, Hamburg, 11-15 October 2010
Meteorological Earth Observing SystemGOES-13
GOES-E(USA)75° W.
GOES-W135° W.
100° W.
850 km
ОMETEOSAT-9(EUMETSAT)
0° E. 35800 km
МЕТЕОR(RUSSIA)
METOP(EUMETSAT)
DMSP
GOES-9144°E
DMSP
DMSP(USA)
MTSAT(JAPAN)
140° E.
(USA)
FY-2METEOSAT-8
3.4° E.
FY-1(CHINA)NOAA
(USA)
METEOSAT-7
FY-2(CHINA)
105° E.
(USA)
METEOSAT 774° E.
ELECTRO(RUSSIA)
76° E.METEOSAT-6
67.5° E.
Observation availabilityy
Region Availability Cycle (current) Res.*Region Availability Cycle (current) Res.
Visible Since start of satellite era
Geostationary, 15/30 minsPolar orbiters, 6-hourly
250 m+, y
Infrared Shortly after start of Geostationary, 15/30 mins 1 km+satellite era~ calibrated since 1979
Polar orbiters, 6-hourly
Passive Microwave
Experimental 1972/1975Uncalibrated since 1978Calibrated since 1987
Polar orbiters, 6-hourly+ Low Earth orbiter (TMI)
4 km+
Active Microwave(radar)
13.8 GHz since 199794 GHz since 2006
Low Earth Orbiter (PR)Polar orbiter (Cloudsat)
4 km1.5 km
* Resolutions vary greatly with scan angle, frequency, sensor, etc.y g y g q y
IPWG#5, Hamburg, 11-15 October 2010
Satellite retrieval of precipitationp pVisible (including near IR)
R fl t l d t ti ( i• Reflectance, cloud top properties (size, phase)
I f dInfrared• Thermal emission – cloud top
temperatures → height
Passive Microwave• Natural emissions from surface and• Natural emissions from surface and
precipitation (emission and scattering)
A ti MiActive Microwave• Backscatter from precipitation particles
Note: Observations are not direct measurements
IPWG#5, Hamburg, 11-15 October 2010
Observations to Products
ClimatologyData inputs Resolutionsti /
Agriculture/crops
Obs
Re P
Visibletime/space
M thl / l Agriculture/cropsser
etri
rod
Infrared
Monthly/seasonalClimate resolution
Meteorologyvat
iev
duct
Passive MW
Hydrology
ion
als
ts
Active MWInstantaneous
ss Instantaneous
Full resolution
Model outputs
IPWG#5, Hamburg, 11-15 October 2010
Vis/IR and microwave retrievalsVis/IR and microwave retrievalsMicrowave methodologiesVisible/IR methodologies
Visible: Albedo, thickness
nIR: Particle size/type
Emission from hydrometeors over radiometrically ‘cold’ backgrounds
S tt i b h d tthIR: Cloud top temperatures/height Scattering by hydrometeors over radiometrically ‘warm’ backgrounds
Visible/IR techniques Microwave techniquesEmpirical techniques:
f fThresholding of cloud-top
( ) Use of surface observations to calibrate microwave observationsPhysical techniques:
temperatures (cold clouds=rain)
Cold cloud durationPhysical techniques:Radiative Transfer Modelling of MW energy through the atmosphere. Baysian techniques use of a priori
Empirical calibration of thIRMulti-spectral analysis
Baysian techniques – use of a prioridata bases of hydrometeor profiles derived from Cloud Radiation Models.
Neural Networks
IPWG#5, Hamburg, 11-15 October 2010
Vis/IR & microwave combined techniquesVis/IR & microwave combined techniquesVis/IR Microwave (active/passive)
☺ Rationale: Observations more directly related to hydrometeors
Rationale: Observation of cloud top properties (temperature/size) but indirect ☺
☺(temperature/size), but indirect
Observations: Frequent observations (30mins); Good
Observations: Infrequent observations (2/sat/day); Poor
☺☺
observations (30mins); Good spatial resolution (1-4 km)
observations (2/sat/day); Poor spatial resolution (5-25 km) ☺
Combine directness of MW observations with the resolution/frequency of IR observations
Calibration of Vis/IR-derived Advect microwave estimates f fproperties with microwave
observationswith information from IR
observations
IPWG#5, Hamburg, 11-15 October 2010
PM-calibrated IR products
2015 2045 2215 2245 0945 10152145TIME
LEO
H HH H H H
O
M M M
GEO
ainf
all
timat
eR
aes
t
M = match between LEO+GEO observations H = GEO-only observationsJoe Turk NRL/JPL
Result: Improved rainfall estimates every 30 minutes
IPWG#5, Hamburg, 11-15 October 2010
Advection/Morphing productsp g p12 May 2003MSG – SSMI
study
Wind vectors derived from MSG 15 minutes data(simple correlation match)
PMW estimates advected using MSG i d t 0745 0930(simple correlation match) MSG wind vectors: 0745-0930
Basis of ‘CMORPH’ and GSMaP techniquesuses forwards and backward propagation of PM rainfalluses forwards and backward propagation of PM rainfall
IPWG#5, Hamburg, 11-15 October 2010
“Global” Estimates
All products have advantages and disadvantagesAll products have advantages and disadvantages
IPWG#5, Hamburg, 11-15 October 2010
Satellite – gauge data sets
Algorithm Input data Space/time Areal coverage/ Update Latency Producer
Publicly available, quasi-operational, quasi-global, multi-sensor satellite-gauge precipitation estimates
g g
Algorithm Input data Space/time scales
Areal coverage/ start date
Update frequency
Latency Producer
GPCP Version 2.1 Satellite-Gauge (SG)
GPCP-OPI, gauge 1/79-6/87, 12/87 SSM/I-AGPI (IR), gauge, TOVS 7/87 4/05 except
2.5˚/monthly Global/1979 Monthly 3 months NASA/GSFC 613.1 (Adler & Huffman)
TOVS 7/87-4/05 except 12/87, AIRS 5/05-present
TRMM Plus Other Data (3B43 Version 6)
TCI-TMI, TCI-SSM/I, TCI-AMSR-E, TCI-AMSU, MW-VAR (IR), gauge
0.25°/monthly Global – 50°N-S/Jan 1998
Monthly 1 week NASA/GSFC PPS (Adler & Huffman)
CMAP OPI SSM/I GPI MSU 2 5˚/monthly Global/1979 Seasonal 3 months NOAA/NWS CPCCMAP OPI, SSM/I, GPI, MSU, gauge, model
2.5 /monthly Global/1979 Seasonal 3 months NOAA/NWS CPC (Xie)
GPCP pentad (Version 1.1)
OPI, SSM/I, GPI, MSU, gauge, GPCP monthly
2.5˚/5-day Global/1979 Seasonal 3 months NOAA/NWS CPC (Xie)
GPCP One-D D il
SSM/I-TMPI (IR), GPCP thl
1˚/daily Global – 50˚N-50˚S/O t b 1997
Monthly 3 months NASA/GSFC 613.1 (H ff )Degree Daily
(Version 1.1) monthly 50˚S/October 1997 (Huffman)
TRMM Plus Other Satellites (3B42 Version 6)
TCI-TMI, TCI-SSM/I, TCI-AMSR-E, TCI-AMSU, MW-VAR (IR), V.6 3B43
0.25°/3-hourly Global – 50°N-S/Jan 1998
Monthly 1 week NASA/GSFC PPS (Adler & Huffman)
f G O SS / / f / (?) O / S C CAfrican GPI, NOAA SSM/I, gauge 10 km/daily Africa/April 2000(?) Daily 6 hours NOAA/NWS CPC (Xie)
South Asian GPI, NOAA SSM/I, gauge 10 km/daily South Asia/April 2001
Daily 6 hours NOAA/NWS CPC (Xie)
CAMS/OPI CMAP-OPI, gauge 2.5˚/daily Global/1979 Monthly 6 hours NOAA/NWS CPC (Xie)
Mostly daily-monthly, 10km-250km
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
Multi-Satellite data setsPublicly available, quasi-operational, quasi-global, multi-satellite precipitation estimates
Algorithm Input data Space/time scales
Areal coverage/ start date
Update frequency
Latency Producer
TRMM Real-Time HQ (3B40RT)
TMI, TMI-SSM/I, TMI-AMSR-E, TMI-AMSU
0.25˚/3-hourly Global – 70˚N-S/ Feb. 2005
3 hours 9 hours NASA/GSFC PPS (Adler & Huffman)
TRMM Real-Time MW-VAR 0.25˚/hourly Global – 50˚N-S/ 1 hour 9 hours NASA/GSFC PPSTRMM Real Time VAR (3B41RT)
MW VAR 0.25 /hourly Global 50 N S/ Feb. 2005
1 hour 9 hours NASA/GSFC PPS (Adler & Huffman)
TRMM Real-Time HQVAR (3B42RT)
HQ, MW-VAR 0.25˚/3-hourly Global – 50˚N-S/ Feb. 2005
3 hours 9 hours NASA/GSFC PPS (Adler & Huffman)
NRL Real TIme SSM/I-cal PMM (IR) 0.25˚/hourly Global – 40˚N-S/ July 2000
Hourly 3 hours NRL Monterey (Turk)July 2000 (Turk)
TCI (3G68) PR, TMI 0.5˚/hourly
Global – 35°N-S/ Dec. 1997
Daily 4 days NASA/GSFC PPS (Haddad)
TOVS HIRS, MSU 1°/daily Global/1979-April 2005
Daily 1 month NASA/GSFC 610 (Susskind)
AIRS AIRS di tt i l th/ bit Gl b l/M 2002 D il 1 d NASA/GSFC 610AIRS AIRS sounding rettrievals swath/orbit segments
Global/May 2002 Daily 1 day NASA/GSFC 610 (Susskind)
CMORPH TMI, AMSR-E, SSM/I, AMSU, IR vectors
0.08°/30-min 50°N-S/2000 Daily 18 hours NOAA/CPC (Xie)
GSMaP-MWR TMI, AMSR-E, AMSR, 0.25°/hourly, 60°N-S/1998-2006 – – JAXA (Aonashi & SSM/I daily,montjhly Kubota)
GSMaP-MVK+ TMI, AMSR-E, AMSR, SSM/I, IR vectors
0.1°/hourly 60°N-S/2003-2006 – – JAXA (Ushio)
GSMaP-NRT TMI, AMSR-E, SSM/I, IR vectors
0.1°/hourly 60°N-S/Oct. 2007 1 hour 4 hours JAXA (Kachi & Kubota)
Mostly hourly-daily, 10km-100km
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
Single sensor products
Algorithm Input data Space/time scales
Areal coverage/ start date
Update frequency
Latency Producer
Publicly available, quasi-operational, quasi-global, single-sensor precipitation estimates
scales start date frequencyGoddard Profiling Algorithm (3G68)
TMI 0.5˚/hourly Global – 37°N-S/Dec. 1997
Daily 4 days NASA/GSFC PPS (Kummerow)
TRMM PR Precip (3G68)
PR 0.5˚/hourly Global – 37°N-S/Dec. 1997
Daily 4 days NASA/GSFC PPS (Iguchi)
GPROF SSM/I 0 5˚/ bit Gl b l 70°N S/ M thl 1 th C l St t U iGPROF SSM/I 0.5˚/orbit segments
Global – 70°N-S/ Jan. 1998
Monthly 1 month Colo. State Univ. (Kummerow)
RSS TMI,AMSR-E,SSM/I, QSCAT
pixel/orbit;1°/ 12-hr;0.5°/ pentad,monthly
Global Ocean – 82°N-S/1988-2007
pending pending HOAPS/Univ. of Hamburg, MPI (Klepp,Andersson)
HOAPS SSM/I 0.25°/1-,3-, 7-day;monthly
Global Ocean – 70°N-S/July 1987
1-,3-,7day; monthly
1 day, then 15 days
RSS (Wentz)
Chang-Chiu-WIlheit Statistical
TMI 5°/monthly Global ocean – 40°N-S/Jan. 1998
Monthly 1 week NASA/GSFC TSDIS (Chiu)
Chang-Chiu- SSM/I 2.5°/monthly Global ocean – Monthly 1 month Chinese U. of Hong gWilheit Statistical
y60°N-S/July 1987
y gKong (Chiu)
NESDIS/ FNMOC Scattering index
SSM/I 0.25˚/daily 1.0˚/pentad, mon 2.5˚/pentad, mon
Global/July 1987 Daily 6 hours NESDIS ORA (Ferraro)
NESDIS AMSU 0 25˚/daily Global/2000 Daily 4 hours NESDIS ORANESDIS High Frequency
AMSU 0.25 /daily1.0˚/pentad, mon 2.5˚/pentad, mon
Global/2000 Daily 4 hours NESDIS ORA (Weng and Ferraro)
GPI GEO-IR, LEO-IR in GEO gaps
2.5°/pentad Global – 40˚N-S 1986–March 1997
N/A N/A NOAA/NWS CPC (Xie)
GEO LEO IR 1°/3 hourly Global 40˚N S Monthly 1 Week NOAA/NWS CPC GEO-, LEO-IR 1°/3-hourly Global – 40 N-S Oct. 1996
Monthly 1 Week NOAA/NWS CPC (Xie)
OPI AVHRR 2.5˚/daily Global/1979 Daily 1 day NOAA/NWS CPC (Xie)
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
Gauge-based precipitation analyses
Publicly available, quasi-operational, quasi-global, gauge precipitation analyses
Gauge based precipitation analyses
y , q p , q g , g g p p yAlgorithm Input data Space/time
scales Areal coverage/ start date
Update frequency
Latency Producer
GPCC Gauge – Version 2 “Full
~60,000 gauges (climatology anomaly)
0.5°,1˚,2.5°/ monthly
Global/1901-2007 Occasional – DWD GPCC (Rudolf)Version 2 Full
Analysis” (climatology-anomaly) monthly (Rudolf)
GPCC Gauge – “Monitoring”
~8,000 gauges (climatology-anomaly)
1˚,2.5°/monthly Global/2007 Monthly 3 months DWD GPCC (Rudolf)
GHCN+CAMS Gauge
~3,800 gauges (SPHEREMAP)
2.5°/monthly Global/1979 Monthly 1 week NOAA/NWS CPC (Xie)Gauge (SPHEREMAP) (Xie)
CRU Gauge ~20,000 gauges (anomaly analysis)
0.5°/monthly Global/1901 Occasional – U. East Anglia (New and Viner)
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
EXAMPLES: GPCP V.2.1 SG climatology for 1979-2008
Note ITCZ, dry subtropical highs, mid-latitude storm tracksPrecipitation is concentrated around maritime continentp
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
Local linear trend in GPCP V.2.1 SG, 1979-2007 (29 years)
Regionally coherent trends do exist0 7 /d/d d li t d 29 l ll• >0.7 mm/d/decade linear trend over 29 years, locally
• the pattern appears to be driven by increases in ENSO frequency • data set inhomogeneities require careful examination
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
Model vs satelliteF
ECM
WF
2RT
3B4
3-hourly precipitation accumulations for 1 June 2007
Clear differences between identification (or definition) of precipitation
IPWG#5, Hamburg, 11-15 October 2010
High resolution climatologiesHigh resolution climatologiesTRMM PR data: 11 years (1997→) at ~5 km resolution.
fall
all
e of
rain
f
Rainfall shows significant local al
rain
fa
curr
ence
gvariability linked with relief.
nnua
l tot
OccAn
IPWG#5, Hamburg, 11-15 October 2010
IPWG Inter-comparison regionsp gNear real-time intercomparison of model & satellite estimates vs radar/gauge
IPWG#5, Hamburg, 11-15 October 2010
Space-time dependency3-hour
Space-time dependencyAt full resolution the ‘accuracy’ of
day
At full resolution the accuracy of estimated rain is low; averaging over time and space improves the picture
5-day
Month
VAR vs. HQ (mm/hr) Feb. 2002 30°N-S
Fine-scale data allows users to decide the averaging strategy
Huffman 2/10IPWG#5, Hamburg, 11-15 October 2010
Satellite error propagation in flood prediction700 700)
400
500
600
700
e (m
3 /s)
radar 1kmSREM2D KIDD 4km
400
500
600
700
e (m
3 /s)
radar 1kmSREM2D 3B42
1200
km
2
Anagnostou& Hossain:
100
200
300
Dis
char
ge
0
100
200
300
Dis
char
ge
higl
ione
(
0 20 40 60 80 100 120 140 1600
Time (hrs)
0 20 40 60 80 100 120 140 1600
Time (hrs)
Bac
ch
200
250 radar 1kmSREM2D KIDD 4km
200
250 radar 1kmSREM2D 3B42
2 )
50
100
150
Dis
char
ge (m
3 /s)
50
100
150
Dis
char
ge (m
3 /s)
a (1
16 k
m2
0 20 40 60 80 100 120 140 1600
Time (hrs)
0 20 40 60 80 100 120 140 160
0
Time (hrs)
Posi
naPMIR: 4km/30min 3B42RT: 1deg/3hr
High:57.9
0.5 km 1 km 2 km 4 km 8 km 16 kmLow:1.6A li ti l ti iti lApplications are resolution critical
IPWG#5, Hamburg, 11-15 October 2010
High latitude precipitationHigh latitude precipitation
Validation instrumentation at high latitudes to observe and
measure precipitationmeasure precipitation
IPWG#5, Hamburg, 11-15 October 2010
Sounding MW techniques
07:35183-WSLC
snowfall
183-WSL
snowfall
10:55 09:15 07:3509:15
183-WSLC
Use of AMSU 183GHz: capable of retrieving
NIMROD22 November 2008183-WSLC
10:55
p gprecipitation (rain and snow) over cold backgrounds 22 November 2008backgrounds
Vincenzo Levizanni, ISAC
IPWG#5, Hamburg, 11-15 October 2010
Summaryy• Wide range of techniques and algorithms exist• Estimates available from monthly/2.5° to 15min/4km• Validation results show good correlations, although
seasonally dependent (poor cold-season performance)
F t h llFuture challenges• Future missions will advance satellite precipitation retrievals
through improved sensors and sampling
• Extensions of retrievals of precipitation at higher latitudes is p p gchallenging:- Light intensity, low-level, frozen precipitation- Surface background contamination- Monitoring changes critical for climate studies
IPWG#5, Hamburg, 11-15 October 2010