Investigating Representation Errors in Inversions of Satellite CO 2 Retrievals

Investigating Representation Errors in

Inversions of Satellite CO2 Retrievals

K.D. Corbin, A.S. Denning, N.C. Parazoo

Department of Atmospheric ScienceColorado State University

Transcom Meeting - Purdue UniversityApril 24-27, 2007


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)


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

Calculating Clear-Sky Errors at CO2 Towers


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]


NEE Clear-Sky Bias at Tower Sites

[Corbin and Denning, 2006]

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


SiB2-RAMS Case DescriptionsNorth America South America

97 K

M450 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

Emulatedsatellite

track


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


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


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

WLEF Tapajos


2003 PCTM Comparisons to Observations

Clear-sky bias from PCTM at tower locations match observed errors reasonably well


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


Annual Mean Clear-Sky Errors by Latitude

Clear-sky errors larger in NH Underestimation of mean in sub-tropics


Seasonal Clear-Sky Errors in PCTM

Magnitude of errors varies with season


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


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


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

Documents

Investigating Representation Errors in Inversions of Satellite CO 2 Retrievals