Yu-wen Chen | Engineering Papers

NASA NTRSDate not supplied

Reducing OCO-2 regional biases through novel 3D cloud, albedo, and meteorology estimation

This ROSES project tests the addition of novel 3D cloud, albedo fine structure, temperature and water vapor profile to the OCO-2 retrieved system. All new parameters have been added to the ReFRACtor / TROPESS system for testing. Currently, we are comparing 3d-cloud retrievals from OCO-2 radiances to the MODIS-derived EAR3T cloud properties. The water and temperature profile retrievals have been implemented and result in improved XCO2 comparisons to TCCON, and now are implementing principal-component analysis (PCA) to reduce the number of parameters added. We are also studying ECOSTRESS spectral library, AVIRIS-ng, OCO-2 spectral residuals, and albedo retrievals with additional parameters to determine the appropriate characterization of albedo. We find that the current albedo parametrization (2nd order polynomial) is adequate for ocean and vegetation, but not adequate for soil and rock observations.

Reducing OCO-2↗

NASA NTRSDate not supplied

Direct 3d-Cloud Estimates From Oco-2 Radiances

3d-clouds effects result from scattering from clouds outside the field of view. These effects have previously been shown to result in a bias in estimate of carbon dioxide on the order of 0.4 ppm for good quality, bias-corrected OCO-2 observations affected by 3d-clouds (Massie et al., 2021). In this paper we directly retrieve 3d-clouds from OCO-2 synthetic and actual radiances utilizing a spectral parametrization of 3d-clouds (Schmidt et al., 2023). We find that retrieving 3d-clouds results in improves carbon dioxide estimates affected by 3d-clouds but increases carbon dioxide scatter for scenes not affected by 3d-clouds. We also find a spectral residual pattern when 3d-cloud effects are present but not retrieved that can be used to identify scenes impacted by 3d-clouds.

Susan S Kulawik↗