The Significance of Fast Radiative Transfer for Hyperspectral SWIR XCO2 Retrievals

Abstract

Fast radiative transfer (RT) methods are commonplace in most algorithms which retrieve the column-averaged dry-mole fraction of carbon dioxide (XCO2) in the Earth’s atmosphere. These methods are required to keep the computational effort at a manageable level and to allow for operational processing of tens of thousands of measurements per day. Without utilizing any fast RT method, the involved computation times would be one to two orders of magnitude larger. In this study, we investigate three established methods within the same retrieval algorithm, and for the first time, analyze the impact of the fast RT method while keeping every other aspect of the algorithm the same. We perform XCO2 retrievals on measurements from the OCO-2 instrument and apply quality filters and parametric bias correction. We find that the central 50% of scene-by-scene differences in XCO2 between retrieval sets, after threshold filtering and bias correction, that use different fast RT methods, are less than 0.40 ppm for land scenes, and less than 0.11 ppm for ocean scenes. Significant regional differences larger than 0.3 ppm are observed and further studies with larger samples and regional-scale subsets need to be undertaken to fully understand the impact on applications that utilize space-based XCO2.

Monitoring Greenhouse Gases from Space

“…IAPCAS retrieves XCO 2 together with aerosol, and other variables, using the Optimal Estimation Method (OEM) by iteratively analysing and optimizing the spectrum residual between the simulation and the satellite measurement. The University of Leicester (UoL-FP) algorithm is a full-physics retrieval algorithm, based on the Optimal Estimation method, originally developed for the NASA OCO mission but has since been applied to many other missions, including GOSAT and OCO-2 [24,25]. The UoL-FP and IAPCAS are based on the same retrieval principles (namely, Optimal Estimation), but they employ independent and different implementations of aerosols and radiative transfer solvers and use different retrieval setups.…”