Improving Overland Precipitation Retrieval with Brightness Temperature Temporal Variation

Abstract

Abstract Current microwave precipitation retrieval algorithms utilize the instantaneous brightness temperature (TB) to estimate precipitation rate. This study presents a new idea that can be used to improve existing algorithms: using TB temporal variation from the microwave radiometer constellation. As a proof of concept, microwave observations from eight polar-orbiting satellites are utilized to derive . Results show that correlates more strongly with precipitation rate than the instantaneous TB. Particularly, the correlation with precipitation rate improved to −0.6 by using over the Rocky Mountains and north of 45°N, while the correlation is only −0.1 by using TB. The underlying reason is that largely eliminates the negative influence from snow-covered land, which frequently is misidentified as precipitation. Another reason is that is less affected by environmental variation (e.g., temperature, water vapor). Further analysis shows that the magnitude of the correlation between and precipitation rate is dependent on the satellite revisit frequency. Finally, it is shown that the retrieval results from are superior to that from TB, with the largest improvement in winter. Additionally, the retrieved precipitation rate over snow-covered regions by only using at 89 GHz agrees well with the ground radar observations, which opens new opportunities to retrieve precipitation in high latitudes for sensors with the highest frequency at ~89 GHz. This study implies that a geostationary microwave radiometer can significantly improve precipitation retrieval performance. It also highlights the importance of maintaining the current passive microwave satellite constellation.