In this investigation, we center on assessing the derived precipitation data. The results highlight the efficacy of TROPICS in capturing the dynamics, spatial distribution, and seasonal patterns of precipitation. For instance, the 2021 Hurricane Ida landfall and its precipitation patterns are distinctly depicted by TROPICS. TROPICS consistently exhibits a well-distributed precipitation across CONUS when compared to Stage IV data. In addition to case studies, we perform a quantitative approach and compare TROPICS with other precipitation datasets, including N20 ATMS, GPM DPR, GMI, and Stage IV. This is conducted through collocating observations from TROPICS and these alternate products. Statistics and metrics such as the correlation coefficients and root mean square errors (RMSE) are analyzed. Specifically, when contrasted with GMI as a reference, TROPICS' rainfall yields a correlation coefficient of 0.5 and an RMSE of 2.0 mm/h, while N20 ATMS shows figures of 0.61 correlation and 1.5 mm/h RMSE. For Graupel water path (GWP), TROPICS records a correlation of 0.52 and an RMSE of 0.53 kg/m², in contrast to N20 ATMS, which demonstrates a correlation of 0.56 and an RMSE of 0.47 kg/m². Regarding Cloud liquid water (CLW), the metrics stand at 0.5 correlation and 0.08 mm for TROPICS, with N20 ATMS having 0.71 correlation and 0.07 mm, respectively. When compared against GPM DPR rainfall, TROPICS exhibits a correlation of 0.31 and an RMSE of 2.97 mm/h, whereas ATMS scores 0.41 correlation and 3.14 mm/h RMSE. Noteworthy is a marginal degradation in precipitation retrieval over land than over the ocean. This preliminary analysis underscores the value of the TROPICS mission for precipitation measurement and demonstrates the successful integration of TROPICS processing capability within the MiRS retrieval algorithm framework.
Reference: Yang J. X., Y. K. Lee, C. Grassotti, K. Garrett, Q. Liu, W. Blackwell, R. Vincent Leslie, T. Greenwald, R. Bennartz, S. Braun, Atmospheric Humidity and Temperature Sounding from CubeSat TROPICS Mission: Early Performance Evaluation with MiRS, Remote Sensing of Environment, 2023.

