Investigating Representation Errors in Inversions of Satellite CO 2 Retrievals

1. Investigating Representation Errors in Inversions of Satellite CO2 Retrievals K.D. Corbin, A.S. Denning, N.C. Parazoo Department of Atmospheric Science Colorado State University Transcom Meeting - Purdue University April 24-27, 2007

2. Motivation • OCO and GOSAT will retrieve total column XCO2 measurements beginning late 2008 • Inverse modelers will use these measurements to help identify CO2 sources and sinks • Using space borne XCO2 to represent a transport model grid-cell may introduce sampling errors into inversions • XCO2 measurements will only represent clear conditions • Investigate sampling errors using continuous data, a regional cloud-resolving model (SiB-RAMS), and a global transport model (PCTM) Transcom Meeting - Purdue University April 24-27, 2007

3. Calculating Clear-Sky Errors at CO2 Towers • CO2 continuous data from 3 towers: • WLEF: 1995-2003 • Harvard Forest: 1993-2002 • Tapajos (km67): 2002-2005 • Mid-day means from 1100-1600 LST • Created clear-sky subset • Ranked PAR measurements from all years at each site • Selected 20% of days per month with highest PAR • Fit separate harmonic functions to clear-sky subset and entire time-series • Subtracted fits: CO2 fitCLEAR - CO2 fitTOTAL Transcom Meeting - Purdue University April 24-27, 2007

4. Clear-Sky Bias at Continuous CO2 Tower Sites • CO2 lower on clear days than on average • Temperate sites have greatest bias in winter • Tropical site shows biggest difference in rainy season [Corbin and Denning, 2006] Transcom Meeting - Purdue University April 24-27, 2007

5. NEE Clear-Sky Bias at Tower Sites • In mid-lats, enhanced uptake on clear days during summer, but negligible winter errors • In tropics, enhanced uptake year-round on clear days • NEE bias cannot account for CO2 errors [Corbin and Denning, 2006] Transcom Meeting - Purdue University April 24-27, 2007

6. SiB2-RAMS Case Descriptions North America South America Emulated satellite track 97 KM 450 KM • August 11-21, 2001 • 3 frontal passages • August 1-16, 2001 • Dry season - calm conditions • Bulk microphysical parameterization to simulate clouds and precipitation explicitly Transcom Meeting - Purdue University April 24-27, 2007

7. Spatial Representation Errors using SiB-RAMS [Corbin et al., 2007] • Errors are unbiased and generally less than 0.5 ppm • Spatial errors increase with domain heterogeneity and size Transcom Meeting - Purdue University April 24-27, 2007

8. Clear-Sky Temporal Errors using SiB-RAMS [Corbin et al., 2007] • Large errors at both sites • Biased errors at temperate site due to CO2 anomalies associated with frontal systems that are masked by clouds Transcom Meeting - Purdue University April 24-27, 2007

9. Clear-Sky Errors using PCTM • Global 2003 simulation • 1.25o longitude x 1.0o latitude • Calculated clear-sky CO2 error for each land grid-cell • Used daytime mean total column CO2 concentrations • Created clear-sky subset using downward shortwave radiation • Fit 2 harmonics to clear-sky and total data • Subtracted FitCLEAR - FitTOTAL Tapajos WLEF Transcom Meeting - Purdue University April 24-27, 2007

10. 2003 PCTM Comparisons to Observations Clear-sky bias from PCTM at tower locations match observed errors reasonably well Transcom Meeting - Purdue University April 24-27, 2007

11. Annual Mean Clear-Sky Errors in PCTM • Errors vary regionally with spatially coherent patterns • Underestimation of CO2 in South America and Alaska • Overestimation of CO2 in Asia Transcom Meeting - Purdue University April 24-27, 2007

12. Annual Mean Clear-Sky Errors by Latitude • Clear-sky errors larger in NH • Underestimation of mean in sub-tropics Transcom Meeting - Purdue University April 24-27, 2007

13. Seasonal Clear-Sky Errors in PCTM • Magnitude of errors varies with season Transcom Meeting - Purdue University April 24-27, 2007

14. Seasonal Clear-Sky Errors by Latitude • Large underestimation of CO2 in NH land during winter • Overestimation of CO2 in NH summer • Underestimation of CO2 in SH spring Transcom Meeting - Purdue University April 24-27, 2007

15. Conclusions • Spatial representation errors are small (< 0.5 ppm) • Clear-sky (temporal) sampling errors are large and vary seasonally and regionally • Satellite XCO2 cannot be used to represent temporal averages • Transport must be modeled accurately and sampled at same time/location as satellite Transcom Meeting - Purdue University April 24-27, 2007

16. Acknowledgements • Thanks to Steve Wofsy for the Tapajos Forest (km67) and Harvard Forest tower data and Ken Davis for the data from WLEF • Funding by NASA Earth System Science Fellowship 53-1970, NASA Contract NNG04GQ15H SUPP2, and NASA Subcontract (via Purdue University) 521-0438-01 Transcom Meeting - Purdue University April 24-27, 2007