Precipitation is the most important variable in the climate system and the dominant driver of land surface hydrologic conditions. Rain gauge measurement provides precipitation estimates on the ground surface; however, these measurements are sparse, especially in the high-elevation areas of Nepal. Reanalysis datasets are the potential alternative for precipitation measurement, although it must be evaluated and validated before use. This study evaluates the performance of second-generation Modern-ERA Retrospective analysis for Research and Applications (MERRA-2) datasets with the 141-gauge observations from Nepal between 2000 and 2018 on monthly, seasonal, and annual timescales. Different statistical measures based on the Correlation Coefficient (R), Mean Bias (MB), Root-Mean-Square Error (RMSE), and Nash–Sutcliffe efficiency (NSE) were adopted to determine the performance of both MERRA-2 datasets. The results revealed that gauge calibrated (MERRA-C) underestimated, whereas model-only (MERRA-NC) overestimated the observed seasonal cycle of precipitation. However, both datasets were able to reproduce seasonal precipitation cycle with a high correlation (R ≥ 0.95), as revealed by observation. MERRA-C datasets showed a more consistent spatial performance (higher R-value) to the observed datasets than MERRA-NC, while MERRA-NC is more reasonable to estimate precipitation amount (lower MB) across the country. Both MERRA-2 datasets performed better in winter, post-monsoon, and pre-monsoon than in summer monsoon. Moreover, MERRA-NC overestimated the observed precipitation in mid and high-elevation areas, whereas MERRA-C severely underestimated at most of the stations throughout all seasons. Among both datasets, MERRA-C was only able to reproduce the observed elevation dependency pattern. Furthermore, uncertainties in MERRA-2 precipitation products mentioned above are still worthy of attention by data developers and users.

Drought influences agriculture, hydrology, ecology and socio‐economic systems globally. As agriculture is the primary source for livelihoods and contributes to ~27% of Nepalʼs total gross domestic product, it is essential to understand the impact of drought on maize and wheat crop yields to minimize the drought‐related risks. This study presents insights about agricultural drought across Nepal during 1987–2017 using the Standardized Precipitation Evapotranspiration Index (SPEI). The temporal evolution of SPEI time series has revealed frequent occurrences of drought episodes during the cropping cycle of summer maize and winter wheat crops. Moreover, the turning point of the drought was detected in 2000 (1987–2000, 2001–2017) in different regions. The averaged frequency for the SPEIs (1, 3, 6 and 12) of drought years for summer maize (winter wheat) in the western, central and eastern regions increased by 13% (12.5%), 6% (7.5%) and 7% (8%), respectively, from 1987–2000 to 2001–2017. The relationship between Standardized Yield Residual Series, the detrended SPEI at 1–12 lags and soil moisture was observed for both crops. The most correlated crop growth period for summer maize and winter wheat was the sowing and growing period, respectively, indicating the sensitive period of water deficit. Besides, the correlation performed in the two sub‐periods (1987–2000 and 2001–2017) shows that drought impacts increased in the western and central regions, whereas they substantially decreased in the eastern region during the cropping period of summer maize. However, the drought sensitivity for winter wheat was decreased in the western region but significantly increased in the central and eastern regions of Nepal. The results of this study provide important information useful for policymakers in monitoring and mitigating the drought‐related risks on maize and wheat crops in Nepal.

Chir pine (Pinus roxburghii Sarg.) is a common tree species with ecological and economic importance across the subtropical forests of the central Himalayas. However, little is known about its growth response to the recent warming and drying trends observed in this region. Here, we developed a 268-year-long ring-width chronology (1743–2010) from western Nepal to investigate its growth response to climate. Based on nearby available meteorological records, growth was positively correlated with winter (November to February; r = 0.39, p < 0.05) as well as March to April (r = 0.67, p < 0.001) precipitation. Growth also showed a strong positive correlation with the sum of precipitation from November of the previous year to April of the current year (r = 0.65, p < 0.001). In contrast, a negative relationship with the mean temperature in March to April (r = −0.48, p < 0.05) suggests the influence of warming-induced evapotranspiration on tree growth. Spring droughts lasting 4–6 months constrain Chir pine growth. These results are supported by the synchronization between droughts and very narrow or locally missing rings. Warming and drying tendencies during winter and spring will reduce forest growth and resilience and make Chir pine forests more vulnerable and at higher risk of growth decline and dieback.

Nepal is located on the southern slope of the Central Himalayas and has experienced frequent droughts in the past. In this study, we used an ensemble of 13 biased corrected models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to assess the future drought conditions over Nepal under three shared socioeconomic pathways (SSP126, SSP245, and SSP585) using the Standardized Precipitation Evapotranspiration Index (SPEI) at annual timescale. The monthly correlation between observed and CMIP6-simulated historical SPEI is 0.23 (p < 0.01), which indicates the CMIP6 model ensemble can simulate the drought characteristics over Nepal. In the future period (2020–2100), the duration and severity of droughts are projected to increase with higher emission scenarios, especially for SSP585. Our results indicate enhanced drought intensity under SSP126, whereas, under SSP245, the drought frequency will be slightly higher. The drought frequency is projected to increase in the early future (2020–2060), decreasing in the late future (2061–2100) under all SSP scenarios. The results further indicate more prolonged and severe droughts in the early future under SSP585 as compared to SSP126 and SSP245. The findings of the present study can help drought mitigation as well as long-term adaptation strategies over Nepal.

Changes in precipitation and temperature, especially in the Himalayan region, will have repercussions for socio-economic conditions in the future. Thus, this study aimed to understand the climatic trend and changes in one of the Himalayan River basins, i.e., Gandaki River Basin (GRB), Nepal. In particular, we analysed the historical (1985–2014) and projected (2015–2100) precipitation and temperature trend and their extremes using observation and 13 bias-corrected Coupled Model Intercomparison Project phase 6 (CMIP6) datasets. Additionally, the relationship between extreme precipitation/temperature indices and ocean-atmospheric circulation patterns were also analysed. The results showed an increasing trend of precipitation amount and temperature at annual and seasonal scales with the highest upward trend for precipitation in monsoon season and temperature in winter season. Among nine precipitation indices analysed, the wet extremes are projected to increase in all Shared Socioeconomic Pathways (SSP) scenarios; with the highest increment of high-intensity related extremes (R10 mm and R20 mm). In contrast, dry spells will decline in the distant-future (2075–2100) as compared to near (2015–2044) and mid-future (2045–2074). Further, increment in temperature trend resulted in a decrease in cold related temperature extremes and an increase in warm related extremes. Furthermore, it was observed that the changes in precipitation and temperature extremes over GRB were influenced by large-scale ocean-atmospheric circulation patterns. The Atlantic Multidecadal Oscillation (AMO), Sea Surface Temperature (SST) and Southern Oscillation Index (SOI) were found to have a major role in driving precipitation extremes while AMO, SST and Pacific Decadal Oscillation (PDO) have strong influence on temperature extremes. The results of this study will be useful for better understanding the implications of historical and future changes in precipitation and temperature and their extremes over the GRB.