Changes in the precipitation regime highly influence the hydrological budget. Paired with the outstanding topography of the Himalaya, these changes might have severe impacts on the vulnerability of the environment and population in the vicinity of the mountain range. In order to reduce this vulnerability, management strategies for agriculture and natural hazards have to be adapted to those changes. Therefore, the spatial and temporal variability of precipitation in trans-Himalayan catchments was investigated in this study based on precipitation estimates from the APHRODITE, TRMM (V6)3B42 and the CRU TS 4.0 gridded datasets. The Mann-Kendall test and the Sens slope estimator were used to determine the significance and magnitude of annual and seasonal monotonic trends on three different spatial levels. Spatial downscaling was performed to identify the areas which are most affected. To detect possible change point years, Pettitts test and the Cumulative Deviations test were used. Furthermore, wettest and driest decades as well as the extreme precipitation years were calculated for the study period and compared with the trend development. The trend detection revealed three major clusters of changing precipitation, namely a drying trend in the north-western Himalaya, a wetting trend in the central Himalaya and a strong drying trend in the front of the Bhutanese Himalaya. While declining monsoon activity in summer was the main influencer to the precipitation decrease in Bhutan, winter and pre-monsoon rainfall contributed most to the increasing rainfall trends in the Center. The receding frequency of Western Disturbances in the post-monsoon and winter season causes the drying trend in the north-west. Change points in the precipitation regime were detected for the drying areas in the early 1970s (NW) and the early 1980s respectively (SE). The occurrence of wettest/driest decades and extreme precipitation years agrees with the trend development. From the data sources, the APHRODITE appears to be the most reliable gridded dataset in the Himalayan region.