Abstract
This study applies the Advanced Radiative Transfer Modeling System (ARMS), which was developed to accelerate the uses of Fengyun satellite data in weather, climate, and environmental applications in China, to characterize the biases of seven infrared (IR) bands of the Advanced Geosynchronous Radiation Imager (AGRI) onboard the Chinese geostationary meteorological satellite, Fengyun–4A. The AGRI data are quality controlled to eliminate the observations affected by clouds and contaminated by stray lights during the mid–night from 1600 to 1800 UTC during spring and autumn. The mean biases, computed from AGRI IR observations and ARMS simulations from the National Center for Environmental Prediction (NCEP) Final analysis data (FNL) as input, are within −0.7–1.1 K (0.12–0.75 K) for all seven IR bands over the oceans (land) under clear–sky conditions. The biases show seasonal variation in spatial distributions at bands 11–13, as well as a strong dependence on scene temperatures at bands 8–14 and on satellite zenith angles at absorption bands 9, 10, and 14. The discrepancies between biases estimated using FNL and the European Center for Medium–Range Weather Forecasts Reanalysis–5 (ERA5) are also discussed. The biases from water vapor absorption bands 9 and 10, estimated using ERA5 over ocean, are smaller than those from FNL. Such discrepancies arise from the fact that the FNL data are colder (wetter) than the ERA5 in the middle troposphere (upper–troposphere).
Highlights
Advanced Geosynchronous Radiation Imager (AGRI) biases are estimated by the differences between the AGRI observations and Advanced Radiative Transfer Modeling System (ARMS) simulations with the Final analysis data (FNL) dataset as input (OMBFNL )
The FNL dataset was utilized as input for ARMS
AGRI data around mid–night before and after the vernal and autumnal equinoxes were removed due to brightness temperature anomalies at band 8 caused by the stray light contamination
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. The intercomparison is limited to equatorial regions in which the coincident, co–angled, and collocated measurements can be found [15] Another way is to compare observations to the radiative transfer model simulations from Numerical Weather. (ERA5) data as input to the RTTOV model in order to calculate and analyze the biases of the AGRI seven 4 km–resolution IR bands. The bias characteristics of AGRI IR bands derived from a radiative transfer model other than RTTOV, such as ARMS, have not been investigated so far. The National Center for Environmental Prediction (NCEP) Final analysis data (FNL) is used as input to the ARMS model to generate AGRI radiance simulations.
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