GHG-CCI. 4 th CCI Co-location Meeting 4-6 Feb 2014, ESA ESRIN. CCI Integration Meeting, ECMWF, March 2011

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1 GHG-CCI 4 th CCI Co-location Meeting 4-6 Feb 2014, ESA ESRIN CCI Integration Meeting, ECMWF, March 2011 Phase 1 results: Climate Research Perspective Michael Buchwitz Institute of Environmental Physics (IUP) University of Bremen, Germany and the GHG-CCI project team

2 GHG-CCI: Key documents PVIR v2.0 for CRDP#1 CAR v1.1 for CRDP#1 Available from -> Documents And several peer-reviewed & other publications: See -> Publications 2

3 Smoothly varying (increasing) emissions, but Carbon budget & related issues Global Carbon Project (GCP) Le Quéré et al., 2013 Emissions Atmospheric growth Highly variable CO 2 atmospheric growth rate or airborn fraction due to variable & not wellunderstood land sink!? Ocean sink Land sink: derived indirectly from reported / estimated emissions and accurate but sparse observations complex and not well understood important for climate prediction Land sink 3

4 CO 2 & methane time series Carbon dioxide (CO 2 ): Increase: ~2 ppm/yr (interannual variations not well understood -> biosphere) Burning of fossil fuels! Methane (CH 4 ): Unexpected increase since 2007 with ~6-9 ppb/yr Anthropogenic? Wetlands? 4

5 SCIAMACHY/BESD XCO

6 SCIA WFMD&BESD CO 2 : Terrestrial carbon sink Inter-annual variability of CO 2 growth rate vs Temperature Schneising et al., ACP, 2014 Inter-annual variability of CO 2 seasonal cycle amplitude vs Temperature Terrestrial carbon uptake variability correlated with / driven by near-surface temperature changes: SCIAMACHY: / 0.32 ppm /yr /K -> approx /- 0.7 GtC /yr /K CarbonTracker vs. SCIAMACHY: Good agreement Less carbon uptake (= higher atmospheric growth rate) in warmer years 6

7 Constraining climate models via observed CO 2 & temperature Cox et al., Nature, 2013 Obervations: Atmospheric CO 2 growth rate vs. temperature -> Tropics: +53 +/- 17 GtC / K Unconstrained climate models Observational constraint Slope: 5.1 +/- 0.9 GtC /yr /K Carbon storage Direct C effect Climate effect (γ<0 -> pos. feedback!) 7

8 First global regional-scale CO 2 surface fluxes from GOSAT/RemoTeC Basu et al., ACP, 2013 Chevallier et al., GRL, 2011: TCCON-only inversion Consistent with flask-only but larger uncertainties Adding GOSAT: Natural fluxes only as fossil fuel emissions prescribed Shift of terrestrial net carbon uptake from tropics to (northern) extra tropics But: 1 year only, still bias issues (e.g., land/ocean), NAM trsam trasi EUR 8

9 CO 2 flux inversions using different satellite data products and models Chevallier et al., CARv1.1, 2013 TransCom regions (land only) LMDZ-19 LMDZ-39 CAR v1.1: Inverted annual carbon budgets (natural fluxes only) Ø Year: 2010 Ø Data: GHG-CCI CRDP#1 Ø Models: LMDZ 19 & 39 (levels) Ø Inversion method: Chevallier et al., 2005 Preliminary conclusions from initial analysis of GHG-CCI CRDP#1: Ø Carbon budgets not always consistent with independent data (e.g., from the CarboEurope synthesis) Ø Sensitivity to the choice of the L2 product Ø Sensitivity to the choice of the transport model 9

10 CO 2 flux inversions using different satellite data products and models Chevallier et al., GRL (accepted article), 2014 Goal: Regional natural CO 2 fluxes for yr Method: 3 inversion methods (2x LSCE (LMDZ 19&39), 1x Univ. Edinburgh (UoE)) CO 2 surface obs. & 2 GOSAT satellite XCO 2 products: GHG-CCI UoL OCFP v4 NASA ACOS v3.3 Key conclusions: Regional flux time series: Good agreement for phase but NOT amplitude Annual regional fluxes: Not realistic for all regions, e.g., Europe: inferred sink significantly too large To be improved: Inversion method incl. prior fluxes and transport models, satellite data (biases to be further reduced) 10

11 GHG-CCI CAR: CCDAS Carbon Cycle Data Assimilation System (CCDAS) CAR, v1.1: Initial assessment by FastOpt (T. Kaminski and M. Scholze) using the reported (reliable) uncertainties as given in the CRDP#1 SCIAMACHY BESD (SCIAMACHY) and EMMA (SCIAMACHY and GOSAT merged) XCO 2 products Approach: Optimization of biosphere model parameters Adventage w.r.t. direct flux inversion: May lead to improved biosphere models -> Better climate prediction Assessed target quantities: regional Net Primary Production (NPP) regional heterotrophic RESpiration (RES) regional Net Ecosystem Production (NEP) Findings: Very high uncertainty reduction: > 50% at model grid scale > 70% for aggregated regions To be assessed: impact of biases Potential for high uncertainty reduction of NEP even when using only 1 year of SCIAMACHY XCO 2 0% 50% 100% Prior: Scholze et al., 2007 Model: BETHY-TM3 CAR v1.1 11

12 XCO 2 : Comparison with Models SCIA NOAA/CT JFM AMJ MPI-BGC LSCE/MACC Model data: F. Chevallier, LSCE; C. Rödenbeck, MPI-BGC; NOAA JAS OND Who is right and who is wrong? Assessment ongoing 12

13 SCIAMACHY XCO 2 vs Models TransCom regions Europe Best agreement?:??? 13

14 SCIAMACHY XCO 2 vs Models TransCom regions Tropical Asia Best agreement?: LSCE/MACC? 14

15 SCIAMACHY XCO 2 vs Models TransCom regions Southern Africa Outlier?: LSCE/MACC? 15

16 SCIAMACHY XCO 2 vs Models TransCom regions South American Tropical Best agreement?:??? 16

17 SCIAMACHY XCO 2 vs Models (All models adjusted to high-quality surface CO 2 observations) JFM SCIA NOAA/CT MPI-BGC LSCE/MACC Best agreement?: LSCE/MACC? +/- 8 ppm 17

18 SCIAMACHY XCO 2 vs Models (All models adjusted to high-quality surface CO 2 observations) OND SCIA NOAA/CT MPI-BGC LSCE/MACC Outlier?: LSCE/MACC? +/- 8 ppm 18

19 Methane Natural gas Coal mining Wetlands Rice Ruminants Wastewater Energy Landfills Termites Hydrates 19

20 SCIAMACHY: Renewed methane growth Schneising et al., 2011 NH (~0-60 o ) Tropics NH Tropics Frankenberg et al., 2011 Findings: Increase ~7-9 ppb/yr ( %/yr) ( relative to ) Mainly tropics & NH mid latitudes No local / regional hot spot found Analysis complicated by detector degradation 20

21 SCIAMACHY & NOAA/flasks: Renewed methane growth Bergamaschi et al., 2013 Total emissions Anthropogenic Wetlands 2007 Findings: Methane emissions : TgCH 4 /yr higher compared to Atmospheric increase : on average ~6+/-1 ppb/yr ( %/yr) (relative to ; update of global means from Dlugokencky et al., 2009) Where?: Mainly tropics & NH mid latitudes, no significant trend for arctic latitudes Reason for increase: Mainly increasing anthropogenic emissions Interannual variations: Mainly wetlands & biomass burning 21

22 SCIAMACHY & NOAA/flasks: Renewed methane growth Houweling et al., ACPD, 2013 In our inversions, the observed transition to increasing CH 4 mixing ratios in 2007 is attributed mostly to the tropics. The difference in global emissions between a two year period before and after July 2006 amounts to Tg/yr. Within the tropical band an important contribution is found from South East Asia, although the associated posterior flux uncertainties are too large to identify the emissions from growing Asian economies as the main cause. Therefore our results are also consistent with a scenario of coincident increases in emissions from tropical wetlands. 22

23 Renewed methane growth: Anthropogenic or wetlands? Kirschke, Bousquet, Ciais, et al.,

24 GOSAT/UoL-PR CH 4 : Regional surface fluxes Fraser et al., ACP, 2013 First GOSAT methane emissions published in peerreviewed journal derived using GHG-CCI XCH 4 Kirschke, Bousquet, Ciais, et al., Global Methan Budget

25 Many thanks for your attention! GHG-CCI Carbon dioxide GHG-CCI Methane 25