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Analysis of 3D cloud effects in OCO-2 XCO2 retrievals

Massie, S., H. Cronk, A. Merrelli, C. O'Dell, K. S. Schmidt, H. Chen, and D. Baker (2021), Analysis of 3D cloud effects in OCO-2 XCO2 retrievals, Atmos. Meas. Tech., 14, 1475-1499, doi:10.5194/amt-14-1475-2021.
Abstract: 

The presence of 3D cloud radiative effects in OCO-2 retrievals is demonstrated from an analysis of 2014– 2019 OCO-2 XCO2 raw retrievals, bias-corrected XCO2bc data, ground-based Total Carbon Column Observation Network (TCCON) XCO2, and Moderate Resolution Imaging Spectroradiometer (MODIS) cloud and radiance fields. In approximate terms, 40 % (quality flag – QF = 0, land or ocean) and 73 % (QF = 1, land or ocean) of the observations are within 4 km of clouds. 3D radiative transfer calculations indicate that 3D cloud radiative perturbations at this cloud distance, for an isolated low-altitude cloud, are larger in absolute value than those due to a 1 ppm increase in CO2 . OCO-2 measurements are therefore susceptible to 3D cloud effects. Four 3D cloud metrics, based upon MODIS radiance and cloud fields as well as stand-alone OCO-2 measurements, relate XCO2bc–TCCON averages to 3D cloud effects. This analysis indicates that the operational bias correction has a nonzero residual 3D cloud bias for both QF = 0 and QF = 1 data. XCO2bc–TCCON averages at small cloud distances differ from those at large cloud distances by −0.4 and −2.2 ppm for the QF = 0 and QF = 1 data over the ocean. Mitigation of 3D cloud biases with a table lookup technique, which utilizes the nearest cloud distance (Distkm) and spatial radiance heterogeneity (CSNoiseRatio) 3D metrics, reduces QF = 1 ocean and land XCO2bc–TCCON averages from −1 ppm to near ±0.2 ppm. The ocean QF = 1 XCO2bc–TCCON averages can be reduced to the 0.5 ppm level if 60 % (70 %) of the QF = 1 data points are utilized by applying Distkm (CSNoiseRatio) metrics in a data screening process. Over land the QF = 1 XCO2bc–TCCON averages are reduced to the 0.5 (0.8) ppm level if 65 % (63 %) of the data points are utilized by applying Diastkm (CSNoiseRatio) data screening. The addition of more terms to the linear regression equations used in the current bias correction processing without data screening, however, did not introduce an appreciable improvement in the standard deviations of the XCO2bc–TCCON statistics.

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Research Program: 
Atmospheric Composition