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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
Aircraft Data
Making Annual Climatology
Original data Original data – detrended
Making an Annual Climatology
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
The Arctic Footprint
Boundary LayerFree TroposphereCourtesy of Adam Hirsch
Arctic CO2/CH4 Correlation
Residual of profile means show extremely good correlations in Arctic.
Boundary Layer
Free Troposphere
HAA
NHASCA
CMA
Boundary Layer Enhancement
of CH4
•Significant enhancement in the boundary layer suggesting a year round flux
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)
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
Fre
e T
ropo
sph
ere
Bou
nda
ry L
ayer
HAA
HAA
CAR
CAR
NHA
OIL
NHA
OIL
Boundary layer CO
What do we do with the data?
Kriging interpolation – 850 mbar
Crovoisier et al., in review
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
Crovoisier et al., in review
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
Forward Model
ATransport
Flux
Foot print – one month Flux prior (GEIA)
= C’Concentration
anomally
Courtesy of Eric Kort
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)
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)
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!