Publications

Li, HP; Liu, HL; Duan, MZ; Deng, XB; Zhang, SL (2022). Estimation of Air Temperature under Cloudy Conditions Using Satellite-Based Cloud Products. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 19, 1001705.

Abstract
This letter presents a novel method fir instantaneous air temperature under cloudy conditions (T-a,T-cloudy) estimation using satellite-derived cloud top temperature (CTT), cloud top height (CTH), and Global Forecast System (GFS) forecasts. The radiosonde profiles were used to analyze the relationship between T-a,T-cloudy and CTT, CTH. The results showed that it is feasible to estimate T-a,T-cloudy using CTT and CTH, especially for low and middle cloud conditions. Linear and neural network (NN)-based T-a,T-cloudy estimation models were constructed and validated using the Visible Infrared Imaging Radiometer Suite (VIIRS) CTT, CTH, and GFS T-air for summer 2017 and 2018. The NN model performs better than the linear model, and GFS T-air can obviously improve the accuracy of T-a,T-cloudy estimation. The correlation coefficient (R), root-mean-square error (RMSE), and bias of the NN model with GFS T-air were 0.953, 1.950 degrees C, and -0.030 degrees C, respectively. The estimation model performed better under low and warm clouds than high and cold cloud conditions.

DOI:
10.1109/LGRS.2021.3057170

ISSN:
1558-0571