Presentation Information
[U16-P06]Advances in precipitation climate information from long-term spaceborne radar data and insights into statistical gaps
*Masafumi Hirose1 (1.Meijo University)
Keywords:
Spaceborne precipitation radar,Regional Uncertainty,Spatio-temporal variation
Satellite precipitation observations have continuously collected data under diverse conditions, capturing a wide range of spatiotemporal variations. This has enabled the development of high-accuracy, high-resolution precipitation climate information derived from spaceborne precipitation radar data, as well as high-temporal-resolution, gridded precipitation datasets based on multiple sensors. Studies that combine these advantages have also emerged. These long-term datasets reduce sampling errors across various statistics and have increasingly shown that precipitation variability and associated retrieval uncertainties are closely linked to region-specific environmental conditions and observational characteristics. Moreover, these datasets suggest that understanding rare events and localized features is essential for interpreting broad-scale, long-term statistics. This study presents results based on long-term observational data from 1998 to 2025 obtained by the Ku-band precipitation radars onboard the Tropical Rainfall Measuring Mission satellite and the Global Precipitation Measurement core observatory. The enhanced sampling coverage has clarified the spatial distribution of systematic errors and terrain-dependent biases. Examples include the effect of heavy rainfall samples on the spatial consistency of precipitation climate values, characteristic vertical precipitation distributions appearing under specific environmental conditions, retrieval uncertainties and regional variability related to weak precipitation at small horizontal and vertical scales, and climatological statistics of precipitation systems associated with tropical cyclones. Analyses of seasonal variations in diurnal cycles and other conditional means indicate that the benefits of increased sampling remain notable, even after a quarter-century. Investigating time-series information requires evaluating observation-related errors arising from sensor sensitivity and orbital changes; this study attempted to reduce this effect. Re-evaluating past data based on statistics from high-sensitivity satellite radars will be necessary in the future. This work aims to contribute to ongoing efforts to build long-term datasets that bridge these gaps, while also understanding the detectability of diverse precipitation phenomena.