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!