Spatiotemporal variability of maximum precipitation altitude and precipitation gradients in global mountain basins

Accurate precipitation data is a crucial input for hydrological models, yet precipitation datasets in alpine regions are too coarse to be used for regional hydrological research. The Maximum Precipitation Altitude (MPA) and precipitation gradient are key indicators for revealing the complex interactions between topography and precipitation, and they play an essential role in understanding precipitation distribution in mountainous regions. Based on the Integrated Multi–satellitE Retrievals for Global Precipitation Measurement (IMERG) dataset, this study calculated the MPA and precipitation gradients for 858 major global mountain basins. In addition, we discussed spatiotemporal characteristics of MPAs and precipitation gradients across four representative mountain ranges—the Alps, Andes, Rocky Mountains, and Tibetan Plateau. The results showed that the MPAs among different mountain ranges exhibit substantial spatiotemporal variability. Temporally, MPAs are strongly influenced by seasonal and monsoonal variations in both the Northern and Southern Hemispheres. Spatially, the mean MPAs are 1094.8 m in the Alps, 2644.9 m in the Andes, 2122.6 m in the Rocky Mountains, and 3913.6 m on the Tibetan Plateau, indicating that higher MPAs tend to be associated with lower water vapor. Regarding precipitation gradients, the average annual gradient is positive below the MPA (43.32 mm/100 m) but becomes negative above the MPA (−11.48 mm/100 m). Furthermore, MPAs show positive correlations with wind speed and the lifting condensation level (LCL), but negative correlations with precipitation frequency, precipitation intensity, specific humidity, and the angle between wind direction and slope aspect. These findings provide new insights into the spatial heterogeneity of precipitation in mountainous environments and offer valuable guidance for improving hydrological and climate modeling in complex terrain.