Method for geostationary satellite thermal infrared data simulation from polar-orbiting MODIS sensors

Abstract

Simulation of thermal images plays an important role in the pre-evaluation of the data acquisition characteristics of sensors. This work addressed an operational method for the time-series thermal infrared (TIR) data of geostationary satellite simulated from polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS) sensors based on Radiative Transfer Model (RTM) under cloud-free conditions. The data procedure, including the land surface emissivity (LSE), time-series land surface temperature (LST), time-series atmospheric parameters, sensor performance, can be described as follows. Firstly, MODIS LST product filtering rules are developed due to its data quality. Then, a Diurnal Temperature Cycle (DTC) model with four parameters is used to acquire the time-series LSTs. The spatial and spectral matching method are adopted from MODIS LST&LSE product. A temporal interpolation method is used to obtain the time-series atmospheric parameters from the atmospheric profile provided by European Centre for Medium-Range Weather Forecasts (ECMWF). Then, the time-series TIR data at sensors were modeled using this method. Compared with the time-series TOA brightness temperature of MSG/ SEVIRI geostationary satellite, the results show that the modeling accuracy is achieved with root mean square errors (RMSEs) 2.39K, 2.81K, 1.06K, and 1.29K at MODIS overpass times, and the mean and RMSE are -0.09K and 1.61K for all cloud-free pixels at the UTC time spanning from 08:00 to 05:00, which can be well reconstruct the time-series real scenes using the proposed method.