Accurate precipitation measurement is crucial for weather forecasting and hydrological modeling. Tropical Rainfall Measuring Mission (TRMM) 3B42V7 satellite precipitation product offers an opportunity to monitor precipitation at high spatiotemporal resolution. However, it has several inherent errors related to observation, instrument, and rainfall retrieval algorithms. It is, therefore, essential to validate it with ground‐based measurements. We divide the region into different elevation ranges and compare 3B42V7 with India Meteorological Department gauge‐based measurements, so as to observe the behavior of satellite at different altitudes. This paper evaluates error characteristics of 3B42V7 using continuous and categorical validation schemes. The analysis reveals 3100 m altitude as the breakpoint for the satellite overestimating and underestimating rainfall amount for elevation ranges below and above it, respectively. It gives a poor positive correlation of ~0.23 between individual rainfall events, though the correlation improves (~0.67) for areal‐averaged precipitation values. 3B42V7 also underestimates the frequency of actual rainfall events and is not very good at identifying correct rain and no‐rain events with the overall accuracy of ~66%. Conclusively, the satellite exhibits comparatively better performance for 1000–2000 m elevations but exacerbates over higher‐altitude regions. Further, we assess its capability for very heavy rainfall events using three percentile thresholds. The low‐magnitude bias for 98th and 99th percentiles and high‐magnitude bias for 99.99th percentile imply that 3B42V7 may not be suitable for the study of very heavy rainfall events. On the basis of these findings, it is recommended to improve satellite precipitation retrieval algorithms by incorporating topographical and local climatic factors into consideration.

Using remotely sensed Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall and topographic data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM), the impact of oroghraphical aspects such as topography, spatial variability of elevation and altitude of apexes are examined to investigate capacious summer monsoon rainfall over the Western Ghats (WG) of India. TRMM 3B42 v7 rainfall data is validated with Indian Meteorological Department (IMD) gridded rainfall data at 0.5 ∘ resolution over the WG. The analysis of spatial pattern of monsoon rainfall with orography of the WG ascertains that the grade of orographic precipitation depends mainly on topography of the mountain barrier followed by steepness of windward side slope and altitude of the mountain. Longer and broader, i.e. cascaded topography, elevated summits and gradually increasing slopes impel the enhancement in precipitation. Comparing topography of various states of the WG, it has been observed that windward side of Karnataka receives intense rainfall in the WG during summer monsoon. It has been observed that the rainfall is enhanced before the peak of the mountain and confined up to the height about 800 m over the WG. In addition to this, the spatial distribution of heavy and very heavy rainfall events in the last 14 years has also been explored. Heavy and very heavy rain events on this hilly terrain are categorized with a threshold of precipitation (R) in the range 150 > R > 120 mm day −1 and exceeding 150 mm day −1 using probability distribution of TRMM 3B42 v7 rainfall. The areas which are prone to heavy precipitation are identified. The study would help policy makers to manage the hazard scenario and, to improve weather predictions on mountainous terrain of the WG.

Using remotely sensed Tropical Rainfall Measuring Mission (TRMM) 3B42 version 7 precipitation data, an investigation on extreme rainfall events (EREs) during the monsoon season has been conducted over the Northwest Himalaya (NWH) for the period of 1998–2013. The satellite precipitation data have been validated with gridded rain gauge data prepared by India Meteorological Department (IMD) using standard statistical measures. A strong positive correlation of 0.88 is found between both, supporting the use of 3B42 V7 for the study of rainfall over the region. The EREs have been identified using three indices corresponding to 98th, 99th, and 99.99th percentiles of the rainfall distribution over the region. The 98th and 99th percentile thresholds are suggested to be considered as extreme and very extreme events respectively whereas 99.99th percentile may correspond to the cloudburst events. The parametric t‐test results indicate a significant increasing trend of the frequency of EREs whereas non‐parametric Mann‐Kendall test results yield no significant trend of EREs over the study region. As the sample size is small, therefore the significance of these results may not be ascertained. The elevation exhibits strong inverse relation with frequency and intensity of EREs over the NWH. A strong negative correlation of ∼0.8 and a poor negative correlation of ∼0.48 are obtained between the elevation and frequency of extremes exceeding 98th and 99th percentiles, and frequency of the cloudburst events, respectively. Whereas, elevation shows strong negative correlations of −0.85, −0.84, and −0.81 with rainfall intensities associated with 98th, 99th, and 99.99th percentiles, respectively. The plains and foothills of the NWH region experience the highest frequency of EREs. However, the peaks of the highest frequency of events are also observed at different elevation ranges at state‐level analysis. This study is a contribution to the on‐going research of extreme events over the mountainous terrain including disaster management study.

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