Abstract
ABSTRACT Estimating total precipitable water vapour (TPWV) from advanced microwave scanning radiometer 2 (AMSR2) measurements with reasonable accuracy is challenging. Therefore, this study aims to improve the AMSR2 TPWV algorithm using metaheuristic algorithms for the first time. Radiosonde observations of six stations in the western part of Iran during 2020 were used as reference data. Moderate Resolution Imaging Spectroradiometer (MODIS) products, including land surface temperature and cloud mask, were used in the TPWV extracting algorithm and in selecting clear-sky days, respectively. Five metaheuristic methods – genetic algorithm (GA), particle swarm optimization (PSO), grey wolf optimizer (GWO), whale optimization algorithm (WOA), and bat algorithm (BA) – were used, due to the ability of metaheuristic methods in modelling complicated issues such as AMSR2 TPWV estimation. The WOA, GWO, and PSO showed the best performance. Therefore, metaheuristic algorithms can be used to improve the AMSR2 TPWV algorithm with reasonable performance on a local scale.
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