Mitigation of satellite OCO-2 CO2biases in the vicinity of clouds with 3D calculations using the Education and Research 3D Radiative Transfer Toolbox (EaR3T)

Abstract

Accurate and continuous measurements of atmospheric carbon dioxide (CO2) are essential for climate change research and monitoring of emission reduction efforts. NASA's Orbiting Carbon Observatory (OCO-2 and 3) satellites have been deployed to infer the column-averaged CO2 dry-air mixing ratio (XCO2) from passive spectroscopy, with a designed uncertainty of less than 1 ppm for the regional average. This accuracy is often not met in cloudy regions because clouds in the vicinity of a footprint introduce biases in the XCO2 retrievals. These arise from limitations in the one-dimensional (1D) forward radiative transfer (RT) model, which does not capture the spectral radiance perturbations introduced by clouds adjacent to a clear footprint. Our paper introduces a three-dimensional (3D) RT pipeline to explicitly account for these effects in real-world satellite observations. This is done by ingesting collocated imagery and reanalysis products to calculate the cloud-induced perturbations at the footprint level. To make that computationally feasible, a simple approximation for their spectral dependence is used. The calculated perturbations are then used to reverse (undo) the cloud vicinity effects at the radiance level, at which point the standard 1D OCO-2 retrieval code can be applied without modifications. For two cases over land, we demonstrate that this approach indeed reduces the XCO2 anomalies near clouds. We also characterize the dependence of the XCO2 footprint-level bias on the distance from clouds and other key scene parameters, such as surface reflectance. Although this dependence may be specific to cloud type, aerosols, and other factors, we illustrate how it could be parameterized to bypass our physics-based 3D-RT pipeline for use in an operational framework. In the future, we intend to explore this possibility by applying our tool to a variety of scenes over land and ocean.