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Advanced radiative transfer modeling system developed for satellite data assimilation and remote sensing applications.

Authors :
Yang, Jun
Ding, Shouguo
Dong, Peiming
Bi, Lei
Yi, Bingqi
Source :
Journal of Quantitative Spectroscopy & Radiative Transfer. Aug2020, Vol. 251, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

• An advanced radiative transfer modeling system has been developed for satellite data assimilation and remote sensing applications. • It focuses on the radiative transfer components for applications to Fengyun satellites. • The accuracy is validated against other model results and the measurements. An advanced radiative transfer modeling system (ARMS) has been developed for satellite data assimilation and remote sensing applications. It inherits the capability of other fast radiative transfer models developed mainly for US and European satellite programs but focuses on the radiative transfer components that are specific for the assimilation of the Fengyun satellites and those sensors not included in existing models. The ARMS forward operator includes a fast transmittance module, a new particle absorption and scattering look-up table, surface emissivity and polarimetric radiative transfer solver. The particle optical properties of aerosols and ice clouds are calculated based on a super-spheroidal T-matrix model. The polarimetric two-stream approximation is adopted as the preferred solver to simulate the Stokes vector and their Jacobians. The simulations of ARMS are compared with those of other models and observations of Fengyun satellites, respectively. The comparison shows close agreement between ARMS and other existing fast radiative transfer models. Therefore, ARMS has robust simulation capabilities for existing satellite sensors. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00224073
Volume :
251
Database :
Academic Search Index
Journal :
Journal of Quantitative Spectroscopy & Radiative Transfer
Publication Type :
Academic Journal
Accession number :
143801100
Full Text :
https://doi.org/10.1016/j.jqsrt.2020.107043