Retrieval of Tropical Cyclone Sea-Level Pressure Fields From the MWTS-2 and MWHS-2 Onboard the FengYun-3D Satellite

Accurate sea level pressure (SLP) data are critical for the forecasting and monitoring of tropical cyclones (TCs). Previous studies have explored SLP retrieval for TCs using passive microwave observations in a single oxygen band (60 or 118 GHz). Leveraging the Fengyun-3 (FY-3) satellite’s capability to simultaneously observe radiation in both 60 and 118 GHz bands, this study proposes a neural network-based algorithm to retrieve TC SLP fields from combined observations of brightness temperature (TB) and warm TB anomalies in both frequency bands. Application studies were carried out using the joint observations from the Microwave Temperature Sounder-2 (MWTS-2) and Microwave Humidity Sounder-2 (MWHS-2) onboard the FY-3D satellite. Optimal frequency channels for the SLP retrieval were selected based on an information content analysis. SLP retrievals within the TC core regions (within a 2° radius from the centers) were compared with SLP data from the Global Data Assimilation System Final Analysis (GDAS/FNL). The results showed root mean square errors (RMSEs) of 2.78 hPa for tropical depressions and storms, 4.23 hPa for hurricanes or typhoons, and 6.15 hPa for major hurricanes or severe typhoons. Retrievals were also compared with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> observations, and the corresponding RMSEs were 3.82, 4.86, and 5.14 hPa, respectively. Furthermore, comparative experiments between the new algorithm and the previous algorithm that used only observations from a single oxygen band demonstrated that the new algorithm provides more comprehensive SLP information and achieves higher accuracy.