Estimating Regional Sources and Sinks of CO 2 Using GOSAT XCO 2

Estimating Regional Sources and Sinks of CO 2 Using GOSAT XCO 2 Feng Deng Dylan Jones Daven Henze Nicolas Bousserez Kevin Bowman Joshua Fisher Ray Nassar IWGGMS-9 YokohamaJapan May 2013 1

XCO 2 Observations ACOS-GOSAT b29 XCO2 for July 2009 - Dec 2010 to quantify monthly fluxes in 2010 Conducted three difference XCO2 inversions using high-gain data: RUN A: XCO2 screened by selecting only data with ΔP < 5 hpa RUN B: XCO2 bias corrected following the approach of Wunch et al 2011 RUN C: XCO2 bias corrected using estimated fitting coefficients from Wunch et al 2011 Use the GEOS-Chem 4-dimensional variational 4D-var data assimilation system to solve for monthly fluxes at the 4 5 resolution of the model using an 18-month assimilation window 1 July 2009 31 December 2010 XCO 2 in RUN_B and RUN_C are similar Both RUN_C and RUN_B are lower than RUN_A in summer in the subtropics and higher in winter in the extratropics 2

Inversion Results: Annual Fluxes 2010 Global Mean fluxes RUN_A: 379 Pg C RUN_B: 402 Pg C RUN_C: 411 PgC 3

Annual Mean Regional Flux Estimates Boreal Tropical South America South America Northern Africa The$three$XCO 2 $inversions$produce$very$different$es5mates$for$boreal$north$america$temperate$north$ America$and$temperate$South$America With$the$pressure$filtering$Run_A$the$GOSAT$XCO 2 $suggests$a$source$of$about$05$pg$c$for$temperate$north$ America$whereas$RUN_B$and$RUN_C$suggest$a$sink The$three$XCO 2 $based$es5mates$are$consistent$for$tropical$south$america$northern$africa$temperate$eurasia$ and$europe Southern Africa Boreal Eurasia Eurasia Tropical Asia Australia Europe 4

/0-1230456 7036" /0-1230456 8329306-3 Monthly Mean Regional Flux Estimates "& Global$mean$es5mates$are$similar$for$all$three$XCO 2$inversions $ %& $ %& /0-1 "& European$ﬂuxes$are$consistent$across$the$3$XCO 2$inversions$and$with$ the$mpiubgc$ﬂux$data$product 45 "? 6 789:89 The$stronger$uptake$in$RUN_B$and$RUN_C$in$May$and$June$in$ "> ;<12=3 $North$America$results$in$an$underes5mate$of$XCO 2$at$ & Lamont - 45 6 789:89 "$ ;<12=3 - /0-1 - - :#093 /0-1230456 7036" :#06;46 7036" /0-1230456 8329306-3 "& "& "$ /0-1 /0-1 45 $ %& $ %9 - - - 45 45 6 789:89 6 789:89 ;<12=3 "> 6 789:89;<12=3 "> ;<12=3 & "> /0-1 /0-1 "? ;<12=3 "? 45 6 789:89 "? $ %9 & "? "> &" &# & /0-1 RUN_A 45 # /0 6 789:89 # - EF &# & /0-1 "" "$ 2 "C4D$B"$B &$ "" - - "$ "? 6 789:89 $"> RUN_C 45 ;<12=3 :#06;46 7036" 2 $B"$B &% $%& - &$ $%& - &% :#093 $ %9 2 $>"$> 2 "?4@$>"$> AB 12-"345 65 789 :;<=>?5 @?<?A 12-"34 56789:; <:7:= &" ;<12=3 # # & $ /0-5

Uncertainty Reduction on Monthly Regional Flux Estimates Maximumuncertaintyreduc0on 50%forTropicalSouthAmerica Intheextratropicsthelargest uncertaintyreduc0onwas obtainedforthenorth Americanfluxes0mates Minimumuncertaintyreduc0onin Europeinwinter Globe Europe Australia Tropical Asia Eurasia Boreal Eurasia Southern Africa Northern Africa South America Tropical South America Boreal 6

Regional Sensitivity Analysis The modeled CO 2 profile fx is transformed to match the instrument sensitivity using the observation operator XCO 2 m = XCO 2 a j h j a j f x y a j where x = surface CO 2 fluxes and ya = GOSAT a priori profile Europe and Asia CO 2 Fluxes dxco 2 m dx df x = h j a j dx j j Produce influence functions Jacobians for North America Europe and temperate Asia The total flux for each region was scaled to yield a CO 2 source of 1 Pg C/month In each source region CO 2 was emitted for 1 month and the model was allowed to transport the emitted CO 2 for an additional 3 months after the fluxes were turned off The modeled fields were sampled along the GOSAT orbit and transformed with the averaging kernels and pressure weights 7

Regional Jacobians Jan Jan 2010 n XCO2 Sensitivity European XCO2 Sensitivity ppm/pg C ppm/pg C Asia XCO2 Sensitivity Sensi0vitywithrespecttoJanuaryfluxesin January Weak$sensi5vity$to$European$fluxes$in$Jan$due$to$limited$ observa5onal$coverage$at$highula5tudes ppm/pg C 8

Regional Jacobians April April 2010 n XCO2 Sensitivity European XCO2 Sensitivity ppm/pg C ppm/pg C Asia XCO2 Sensitivity Sensi0vitywithrespecttoAprilfluxesinApril Greater$sensi5vity$to$European$fluxes$in$April$due$to$beXer$ observa5onal$coverage$at$highula5tudes ppm/pg C 9

Regional Jacobians April May 2010 n XCO2 Sensitivity European XCO2 Sensitivity ppm/pg C ppm/pg C Asia XCO2 Sensitivity Sensi0vitywithrespecttoAprilfluxesinMay Observa5ons$over$Europe$in$May$provide$greater$ sensi5vity$to$north$american$fluxes$in$april$than$ observa5ons$over$north$america ppm/pg C 10

Estimating Transit Times for Continental Emissions Receptor regions for pulse experiment Eastern Pacific North America Atlantic Europe Siberia Asia Simulate the transit times using a narrower pulse: For the 3 continental regions Europe Asia emit a pulse of 1 Pg C for 1 day and transport the emitted CO 2 for an additional 3 months after the fluxes were turned off Look at the distribution of the 3 tracers across each of the 6 receptor regions 11

Transit Times to the Middle Troposphere ~5 km 006 005 n Receptor Europe Asia Atlantic Ocean Receptor European Receptor 004 003 002 001 000 006 005 004 20 40 60 80 Time Days Siberian Receptor Europe Asia 20 40 60 80 Time Days Asian Receptor 20 40 60 80 Time Days Eastern Pacific Receptor 003 002 001 000 20 40 60 80 Time Days 20 40 60 80 Time Days 20 40 60 80 Time Days On timescales of 1-2 weeks n fluxes are influenced mainly by observations across North America and Eurasia n fluxes are strongly influenced by long-range transport and would be more sensitive to regional biases in the XCO2 data European fluxes influenced mainly by observations in Eurasia on short timescales week European fluxes are less sensitive to long-range transport 12

Summary Residual biases in the XCO 2 data are a challenge for the regional flux estimates Regional flux estimate must be interpreted with care The inversion significantly increased the uptake in the northern extratropics to correct for the underestimate of the seasonal cycle in our a priori fluxes n fluxes are strongly influenced by long-range transport The flux estimates should be more sensitive to spatially varying biases in the observations and to model transport errors European fluxes are influenced mainly by observations in Eurasia on short timescales The flux estimate are less sensitive to biases in the observations outside of Europe and to model transport errors Because of the observational coverage of GOSAT the inversion is most sensitive to North American fluxes in the northern extratropics Better observational coverage is critical including data over the oceans to capture the continental export TheworkhasbeensupportedbytheNa0onalAeronau0csandSpaceAdministra0ontheNaturalScienceandEngineering ResearchCouncilofCanadaandtheCanadianSpaceAgency 13

Inversion Configuration Use the GEOS-Chem 4-dimensional variational 4D-var data assimilation system to solve for monthly fluxes at the 4 5 resolution of the model using an 18-month assimilation window 1 July 2009 31 December 2010 Initial conditions obtained by assimilating surface flask data from Jan 2007 to July 2009 and scaling a posteriori CO 2 field for 1 July 2009 to remove the global mean bias relative to the XCO 2 datasets; The initial bias was 024% 027% and 027% for RUN_A RUN_B and RUN_C respectively Assume a priori and observation error covariance matrices are diagonal Prior Fluxes Fossil fuel emissions Andres et al 2011; Biomass Burning GFEDv3; Biofuel emissions Yevich and Logan 2003 Shipping emissions Corbett and Koehler 2003 2004; Endresen et al 2004 2007; Aviation emissions Friedl 1997; Kim et al 2007; Wilkerson et al 2010; Chemical source of CO 2 Nassar et al 2010 Ocean-atmosphere CO 2 flux Takahashi et al 2009 Gross primary productivity GPP and total ecosystem respiration TER specified from BEPS Chen et al 1999; Deng & Chen 2011 assuming a balanced biosphere 14