As a mountainous country, Nepal is most susceptible to precipitation extremes and related hazards, including severe floods, landslides and droughts that cause huge losses of life and property, impact the Himalayan environment, and hinder the socioeconomic development of the country. Given that the countrywide assessment of such extremes is still lacking, we present a comprehensive picture of prevailing precipitation extremes observed across Nepal. First, we present the spatial distribution of daily extreme precipitation indices as defined by the Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI) from 210 stations over the period of 1981–2010. Then, we analyze the temporal changes in the computed extremes from 76 stations, featuring long-term continuous records for the period of 1970–2012, by applying a non-parametric Mann−Kendall test to identify the existence of a trend and Sen’s slope method to calculate the true magnitude of this trend. Further, the local trends in precipitation extremes have been tested for their field significance over the distinct physio-geographical regions of Nepal, such as the lowlands, middle mountains and hills and high mountains in the west (WL, WM and WH, respectively), and likewise, in central (CL, CM and CH) and eastern (EL, EM and EH) Nepal. Our results suggest that the spatial patterns of high-intensity precipitation extremes are quite different to that of annual or monsoonal precipitation. Lowlands (Terai and Siwaliks) that feature relatively low precipitation and less wet days (rainy days) are exposed to high-intensity precipitation extremes. Our trend analysis suggests that the pre-monsoonal precipitation is significantly increasing over the lowlands and CH, while monsoonal precipitation is increasing in WM and CH and decreasing in CM, CL and EL. On the other hand, post-monsoonal precipitation is significantly decreasing across all of Nepal while winter precipitation is decreasing only over the WM region. Both high-intensity precipitation extremes and annual precipitation trends feature east−west contrast, suggesting significant increase over the WM and CH region but decrease over the EM and CM regions. Further, a significant positive trend in the number of consecutive dry days but significant negative trend in the number of wet (rainy) days are observed over the whole of Nepal, implying the prolongation of the dry spell across the country. Overall, the intensification of different precipitation indices over distinct parts of the country indicates region-specific risks of floods, landslides and droughts. The presented findings, in combination with population and environmental pressures, can support in devising the adequate region-specific adaptation strategies for different sectors and in improving the livelihood of the rural communities in Nepal.

In this paper we assess the snow cover and its dynamics for the western river basins of the Indus River system (IRS) and their sub-basins located in Afghanistan, China, India and Pakistan for the period 2001–2012. First, we validate the Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products from Terra (MOD10A1) and Aqua (MYD10A1) against the Landsat Thematic Mapper/Enhanced Thematic Mapper plus (TM/ETM+) data set, and then improve them for clouds by applying a validated non-spectral cloud removal technique. The improved snow product has been analysed on a seasonal and annual basis against different topographic parameters (aspect, elevation and slope). Our results show a decreasing tendency for the annual average snow cover for the westerlies-influenced basins (upper Indus basin (UIB), Astore, Hunza, Shigar and Shyok) and an increasing tendency for the monsoon-influenced basins (Jhelum, Kabul, Swat and Gilgit). Seasonal average snow cover decreases during winter and autumn, and increases during spring and summer, which is consistent with the observed cooling and warming trends during the respective seasons. Sub-basins at relatively higher latitudes/altitudes show higher variability than basins at lower latitudes/middle altitudes. Northeastern and northwestern aspects feature greater snow cover. The mean end-of-summer regional snow line altitude (SLA) zones range from 3000 to 5000 m a.s.l. for all basins. Our analysis provides an indication of a descending end-of-summer regional SLA zone for most of the studied basins, which is significant for the Shyok and Kabul basins, thus indicating a change in their water resources. Such results are consistent with the observed hydro-climatic data, recently collected local perceptions and glacier mass balances for the investigated period within the UIB. Moreover, our analysis shows a significant correlation between winter season snow cover and the North Atlantic Oscillation (NAO) index of the previous autumn. Similarly, the inter-annual variability of spring season snow cover and spring season precipitation explains well the inter-annual variability of the summer season discharge from most of the basins. These findings indicate some potential for the seasonal stream flow forecast in the region, suggesting snow cover as a possible predictor.

Largely depending on the meltwater from the Hindukush–Karakoram–Himalaya, withdrawals from the upper Indus Basin (UIB) contribute half of the surface water availability in Pakistan, indispensable for agricultural production systems, industrial and domestic use, and hydropower generation. Despite such importance, a comprehensive assessment of prevailing state of relevant climatic variables determining the water availability is largely missing. Against this background, this study assesses the trends in maximum, minimum and mean temperatures, diurnal temperature range and precipitation from 18 stations (1250–4500 m a.s.l.) for their overlapping period of record (1995–2012) and, separately, from six stations of their long-term record (1961–2012). For this, a Mann–Kendall test on serially independent time series is applied to detect the existence of a trend, while its true slope is estimated using the Sen's slope method. Further, locally identified climatic trends are statistically assessed for their spatial-scale significance within 10 identified subregions of the UIB, and the spatially (field-) significant climatic trends are then qualitatively compared with the trends in discharge out of corresponding subregions. Over the recent period (1995–2012), we find warming and drying of spring (field-significant in March) and increasing early melt season discharge from most of the subregions, likely due to a rapid snowmelt. In stark contrast, most of the subregions feature a field-significant cooling within the monsoon period (particularly in July and September), which coincides well with the main glacier melt season. Hence, a decreasing or weakly increasing discharge is observed from the corresponding subregions during mid- to late melt season (particularly in July). Such tendencies, being largely consistent with the long-term trends (1961–2012), most likely indicate dominance of the nival but suppression of the glacial melt regime, altering overall hydrology of the UIB in future. These findings, though constrained by sparse and short observations, largely contribute in understanding the UIB melt runoff dynamics and address the hydroclimatic explanation of the Karakoram Anomaly.

Two new indicators of rainfall seasonality based on information entropy, the relative entropy (RE) and the dimensionless seasonality index (DSI), together with the mean annual rainfall, are evaluated on a global scale for recently updated precipitation gridded datasets and for historical simulations from coupled atmosphere–ocean general circulation models. The RE provides a measure of the number of wet months and, for precipitation regimes featuring a distinct wet and dry season, it is directly related to the duration of the wet season. The DSI combines the rainfall intensity with its degree of seasonality and it is an indicator of the extent of the global monsoon region. We show that the RE and the DSI are fairly independent of the time resolution of the precipitation data, thereby allowing objective metrics for model intercomparison and ranking. Regions with different precipitation regimes are classified and characterized in terms of RE and DSI. Comparison of different land observational datasets reveals substantial difference in their local representation of seasonality. It is shown that two-dimensional maps of RE provide an easy way to compare rainfall seasonality from various datasets and to determine areas of interest. Models participating to the Coupled Model Intercomparison Project platform, Phase 5, consistently overestimate the RE over tropical Latin America and underestimate it in West Africa, western Mexico and East Asia. It is demonstrated that positive RE biases in a general circulation model are associated with excessively peaked monthly precipitation fractions, too large during the wet months and too small in the months preceding and following the wet season; negative biases are instead due, in most cases, to an excess of rainfall during the premonsoonal months.