![Page 1: C. Sweeney 1, A. Karion, D.W.Guenther 1, S. E. Wolter 1, D. Neff 1, P.M. Lang 2, M.J. Heller 1, T. Conway 2, E.J. Dlugokencky 2, P. Novelli 2, L. Bruhwiler](https://reader035.vdocuments.net/reader035/viewer/2022070402/56649f265503460f94c3dc30/html5/thumbnails/1.jpg)
C. Sweeney1, A. Karion, D.W.Guenther1, S. E. Wolter1, D. Neff1, P.M. Lang2, M.J. Heller1, T. Conway2, E.J. Dlugokencky2, P. Novelli2, L.
Bruhwiler2, A. Hirsch1, A. Jacobson1, J. Miller1 G. Petron1, S. Montzka2 and K.A. Masarie2
1CIRES, University of Colorado, Boulder, CO2NOAA/ESRL, Boulder, CO
NOAA/ESRL Carbon Cycle Group aircraft profile measurements – Non CO2 gases
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Aircraft Data
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Making Annual Climatology
Original data Original data – detrended
Making an Annual Climatology
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West East Transect
HAA
THD
NHA
OIL
•West coast sites lagged by one month
•West coast show well mixed throughout column relative to east coast
CAR
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The Arctic Footprint
Boundary LayerFree TroposphereCourtesy of Adam Hirsch
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Arctic CO2/CH4 Correlation
Residual of profile means show extremely good correlations in Arctic.
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Boundary Layer
Free Troposphere
HAA
NHASCA
CMA
Boundary Layer Enhancement
of CH4
•Significant enhancement in the boundary layer suggesting a year round flux
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Midwest Sites
THD NHA
CAR
Midwest enhancement
of N2O
•Significant enhancement of N2O in boundary layer in croplands of the Midwestern US
Courtesy of Eric Kort (GEIA N2O fluxes)
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Arctic CO2/CO Correlation
Residual s of profile means for CO2 and CO correlates well suggesting that large scale transport is driving winter time high.
PFA
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Fre
e T
ropo
sph
ere
Bou
nda
ry L
ayer
HAA
HAA
CAR
CAR
NHA
OIL
NHA
OIL
Boundary layer CO
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What do we do with the data?
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Kriging interpolation – 850 mbar
Crovoisier et al., in review
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Direct Carbon Budgeting Approach
Surface CO2 fluxes (Fsurf)
Out
Exchanges with the upper atmosphere
(convection, advection)
h
u
n
verticalVSsurf t
CdV
tdSF
nu.
Edges ConvectionVolume
nu.
nu.Crovoisier et al., 2006
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Crovoisier et al., in review
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Surface flux acting on transport (A) Concentration
Forward ModelForward Model
Regression of data c onto basis
set A.
Inverse ModelInverse Model
CA
)(1 CA
CCC
Measurement
Background
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Forward Model
ATransport
Flux
Foot print – one month Flux prior (GEIA)
= C’Concentration
anomally
Courtesy of Eric Kort
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Regions
Obs.(Flasks/profiles)
Particle concentration (BL)
Regions
=C’
p
[CH4] Flux
A
IRegions
ppT
pCT PCCPCCJ )()(
Foot print – one month
Courtesy of Eric Kort
Flux prior (GEIA)
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Inversion Model for aircraft profiles using a LPDM
Advantage:1. Monthly fluxes for each region 2.Ability to use sparse measurement field by treating each profile as an independent observation assuming that monthly fluxes have not changed over the last 5 years.3.Evaluate spatial distribution of fluxes (region to region)Disadvantage1.Requires a background concentration2.It will be tricky to define regions that are truly independent.3.Number of regions will be limited by the limited number of profiles per month (10 profiles x 18 sites)
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Conclusions
• The last 5 years of aircraft profiles not only tell us about transport but suggest distribution of many sources/sinks for CO2, CO, SF6, N2O and CH4.
• The aircraft profiles offer an independent estimate of regional scale fluxes.
• This is a new dataset which needs to be exercised by good science!