Ice/Snow Surface Temperature Retrieval From Chinese FY-3D MERSI-II Data: Algorithm and Preliminary Validation

Abstract

Ice/snow surface temperature (I/SST) is an essential parameter in many research fields such as the climate change, energy, and matter balance of the South pole regions. Recently, many algorithms have been developed for various satellite observations to derive the I/SST. However, rare studies focus on accurate I/SST retrieval from the observations of Chinese MEdium Resolution Spectral Imager II (MERSI-II) instrument onboard the FY-3D satellite with the spatial resolution of 250 m and temporal resolution of about five days, which just bridges the specifications of the Aqua-MODerate-resolution Imaging Spectroradiometer (MODIS) (1000-m pixel size and 0.5-day revisit cycle) and Landsat-Thermal InfraRed Sensor (TIRS) (100-m pixel size and 16-day revisit cycle) instruments. In this study, a new method with correction of striping noise and consideration of angular emissivity effect is developed for the MERSI-II data to accurately retrieve the I/SST. The performance of the proposed method is assessed by using both MODIS product and ground I/SST measurements. The results show that the FY-3D I/SST retrieval accuracy is comparable to the MODIS product, with a discrepancy of < 1.6 K. Ground-based validation reveals that the proposed method could be used to accurately retrieve the I/SST with a root-mean-square error (RMSE) of < 1.5 K. Overall, this study proposes a method for accurate I/SST retrieval from the FY-3D MERSI-II data with the pixel size of 250 m, implying the possibilities in improving the spatio-temporal resolutions of the current I/SST products. Moreover, the proposed method is also helpful to improve our understandings of the polar regions.