An Algorithm for the Constraining of Radiative Transfer Calculations to CERES-Observed Broadband Top-of-Atmosphere Irradiance

Abstract

Abstract NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project is responsible for operation and data processing of observations from scanning radiometers on board the Tropical Rainfall Measuring Mission (TRMM), Terra, Aqua, and Suomi National Polar-Orbiting Partnership (NPP) satellites. The clouds and radiative swath (CRS) CERES data product contains irradiances computed using a radiative transfer model for nearly all CERES footprints in addition to top-of-atmosphere (TOA) irradiances derived from observed radiances by CERES instruments. This paper describes a method to constrain computed irradiances by CERES-derived TOA irradiances using Lagrangian multipliers. Radiative transfer model inputs include profiles of atmospheric temperature, humidity, aerosols and ozone, surface temperature and albedo, and up to two sets of cloud properties for a CERES footprint. Those inputs are adjusted depending on predefined uncertainties to match computed TOA and CERES-derived TOA irradiance. Because CERES instantaneous irradiances for an individual footprint also include uncertainties, primarily due to the conversion of radiance to irradiance using anisotropic directional models, the degree of the constraint depends on CERES-derived TOA irradiance as well. As a result of adjustment, TOA computed-minus-observed standard deviations are reduced from 8 to 4 W m−2 for longwave irradiance and from 15 to 6 W m−2 for shortwave irradiance. While agreement of computed TOA with CERES-derived irradiances improves, comparisons with surface observations show that model constrainment to the TOA does not reduce computation bias error at the surface. After constrainment, shortwave down at the surface has an increased bias (standard deviation) of 1% (0.5%) and longwave increases by 0.2% (0.1%). Clear-sky changes are negligible.