Retrieval of Global Total Precipitable Water from FY-3D MWHS-II Data

Total Precipitable Water (TPW) is a key variable of atmospheres, and its spatiotemporal distribution is of great importance in global climate change. This paper addresses the TPW retrieval over both sea and land surfaces from the data acquired by the Microwave Humidity Sounder II (MWHS-II) on Fengyun 3D (FY-3D) satellite. First, Back Propagation neural network (BPNN) algorithms are developed with the spatiotemporal matching samples of the MWHS-II data versus the fifth-generation European Centre for Medium-Range Weather Forecast (ECMWF) atmospheric reanalysis (ERA5) data. Then, the TPWs between 65°S and 65°N over both sea and land surfaces are retrieved from FY-3D MWHS-II data in 2022. Finally, the TPWs retrieved in this work are validated with the radiosonde TPWs over both sea and land surfaces, and they are also compared to the F18 Special Sensor Microwave Imager Sounder (SSMIS) TPWs over sea surfaces. The results indicate that the BPNN algorithms developed in this work are valid and accurate. The mean error (ME), the root mean square error (RMSE) and mean absolute error (MAE) of the TPWs retrieved in this work against the radiosonde TPWs are -1.17 mm, 3.46 mm and 2.63 mm over sea surfaces, respectively, and they are -0.80 mm, 4.04 mm and 3.13 mm over land surfaces, respectively. The TPWs retrieved in this work are much more accurate than the F18 SMMIS TPWs.