|Abstract or Summary
- Extreme, flood-producing precipitation events in mountains threaten human life and local and national economies. In the Himalayas, scarce meteorological data historically limited understanding of the underlying processes driving extreme events. However, the capacity to observe, measure and quantify precipitation on regional scales has increased tremendously over the last three decades with the increasing prevalence of remotely-sensed data. While remotely-sensed precipitation can add essential information for understanding local hydrology, the spatial and temporal scales of the observations may result in biases based on the types of events that can be captured by the data. We analyze one of the recent remotely-sensed precipitation datasets, collected by the Tropical Rainfall Measuring Mission (TRMM), to better understand the spatial and temporal context of storm processes that generate flood disasters in high mountain environments. The objectives of this study are to 1) analyze the spatial distribution of extreme rainfall and convection across the mountain systems of the western Himalayan region, 2) investigate the deviations between remotely-sensed and ground-based precipitation observations across the orography, and 3) examine the sub-grid heterogeneity of remotely-sensed precipitation observations. First, we provide evidence of significant deviations between the mean and variance of extreme rainfall and convective intensities across mountain systems, which may produce variable over and underestimations of precipitation across the landscape. Extreme rainfall values are highest across the Lower Himalaya where synoptic weather systems are more prevalent, whereas extreme convective intensities are significantly higher across the Inner Himalaya. Second, we identify that deviations between extreme precipitation values measured by TRMM and GBO stations reverse with increasing topography, indicating that both rainfall regime and valley-ridge rainfall distributions vary with elevation and relief. Third, we identify large sub-grid differences in the variance of the extreme rainfall distributions within a single TRMM pixel, underscoring the complexities of bias correction of gridded rainfall measurements using GBO stations. Our findings support the hypothesis that storm regimes vary with the orography, uniquely affecting the measurement of remotely-sensed precipitation.