LAUSR

Accurate information on the thermal structures of tropical cyclones (TCs) is essential for monitoring and forecasting their intensity and location. In this study, a scene-dependent 1-D variation (SD1DVAR) algorithm is developed to retrieve atmospheric temperature and moisture profiles under all-weather conditions. In SD1DVAR, the background and observation error matrix varies according to the scattering intensity. Especially, the observation error matrix increases in precipitating atmospheres due to a larger uncertainty in the forward operator. With the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) satellite, SD1DVAR can retrieve better thermal structures in the storm life cycle than NOAA Microwave Integrated Retrieval System (MIRS). Comparing with the aircraft dropsonde observations, the temperature and humidity errors from SD1DVAR are about 3 K and 20%, respectively, whereas those from MIRS are around 4 K–5 K and 30%, respectively. SD1DVAR is also applied for Microwave Temperature Sounder (MWTS) and Microwave Humidity Sounder (MWHS) onboard FengYun-3D (FY-3D) satellite. The MWTS and MWHS data sets are first combined into a single Comprehensive MicroWave Suite (CMWS) data stream and then used to retrieve the hurricane thermal structures. It is shown that the hurricane structure from CMWS is very similar to that from ATMS. However, due to the availability of 118-GHz measurements from the CMWS, the hurricane temperature vertical structure is better resolved, and the humidity error is also reduced by about 5%.