Snow sublimation is a loss of water from the snowpack to the atmosphere. So far, snow sublimation has remained unquantified in the Himalaya, prohibiting a full understanding of the water balance and glacier mass balance. Hence, we measured surface latent heat fluxes with an eddy covariance system on Yala Glacier (5,350 m a.s.l) in the Nepalese Himalaya to quantify the role snow sublimation plays in the water and glacier mass budget. Observations reveal that cumulative sublimation is 32 mm for a 32-day period from October to November 2016, which is high compared to observations in other regions in the world. Multiple turbulent flux parameterizations were subsequently tested against this observed sublimation. The bulk-aerodynamic method offered the best performance, and we subsequently used this method to estimate cumulative sublimation and evaporation at the location of the eddy covariance system for the 2016-2017 winter season, which is 125 and 9 mm respectively. This is equivalent to 21% of the annual snowfall. In addition, the spatial variation of total daily sublimation over Yala Glacier was simulated with the bulk-aerodynamic method for a humid and non-humid day. Required spatial fields of meteorological variables were obtained from high-resolution WRF simulations of the region in combination with field observations. The cumulative daily sublimation at the location of the eddy covariance system equals the simulated sublimation averaged over the entire glacier. Therefore, this location appears to be representative for Yala Glacier sublimation. The spatial distribution of sublimation is primarily controlled by wind speed. Close to the ridge of Yala Glacier cumulative daily sublimation is a factor 1.7 higher than at the location of the eddy covariance system, whereas it is a factor 0.8 lower at the snout of the glacier. This illustrates that the fraction of snowfall returned to the atmosphere may be much higher than 21% at wind-exposed locations. This is a considerable loss of water and illustrates the importance and need to account for sublimation in future hydrological and mass balance studies in the Himalaya.

Frequently used gridded meteorological datasets poorly represent precipitation in the Himalayas because of their relatively low spatial resolution and the associated representation of the complex topography. Dynamical downscaling using high-resolution atmospheric models may improve the accuracy and quality of the precipitation fields. However, most physical parameterization schemes are designed for a spatial resolution coarser than 1 km. In this study the Weather Research and Forecasting (WRF) Model is used to determine which resolution is required to most accurately simulate monsoon and winter precipitation, 2-m temperature, and wind fields in the Nepalese Himalayas. Four model nests are set up with spatial resolutions of 25, 5, 1, and 0.5 km, respectively, and a typical 10-day period in summer and winter in 2014 are simulated. The model output is compared with observational data obtained from automatic weather stations, pluviometers, and tipping buckets in the Langtang catchment. Results show that, despite issues with the quality of the observational data due to undercatch of snowfall, the highest resolution of 500 m does provide the best match with the observations and gives the most plausible spatial distribution of precipitation. The quality of the wind and temperature fields is also improved, whereby the cold temperature bias is decreased. Our results further elucidate the performance of WRF at high resolution and demonstrate the importance of accurate surface boundary conditions and spinup time for simulating precipitation. Furthermore, they suggest that future modeling studies of High Mountain Asia should consider a subkilometer grid for accurately estimating local meteorological variability.

Many glaciers in the northwest of High Mountain Asia (HMA) show an almost zero or positive mass balance, despite the global trend of melting glaciers. This phenomenon is often referred to as the “Karakoram anomaly,” although strongest positive mass balances can be found in the Kunlun Shan mountain range, northeast of the Karakoram. Using a regional climate model, in combination with a moisture‐tracking model, we show that the increase in irrigation intensity in the lowlands surrounding HMA, particularly in the Tarim basin, can locally counter the effects of global warming on glaciers in Kunlun Shan, and parts of Pamir and northern Tibet, through an increase in summer snowfall and decrease in net radiance. Irrigation can thus affect the regional climate in a way that favors glacier growth, and future projections of glacier melt, which may impact millions of inhabitants surrounding HMA, will need to take into account predicted changes in irrigation intensity.

There is strong variation in glacier mass balances in High Mountain Asia. Particularly interesting is the fact that glaciers are in equilibrium or even gaining mass in the Karakoram and Kunlun Shan ranges, which is in sharp contrast with the negative mass balances in the rest of High Mountain Asia. To understand this difference, an in-depth understanding of the meteorological drivers of the glacier mass balance is required. In this study, two catchments in contrasting climatic regions, one in the central Himalaya (Langtang) and one in the Karakoram (Shimshal), are modeled at 1 km grid spacing with the numerical atmospheric model WRF for the period of 2011-2013. Our results show that the accumulation and melt dynamics of both regions differ due to contrasting meteorological conditions. In Shimshal, 92% of the annual precipitation falls in the form of snow, in contrast with 42% in Langtang. In addition, 80% of the total snow falls above an altitude of 5000 m a.s.l, compared with 35% in Langtang. Another prominent contrast is that most of the annual snowfall falls between December and May (71%), compared with 52% in Langtang. The melt regimes are also different, with 41% less energy available for melt in Shimshal. The melt in the Karakoram is controlled by net shortwave radiation (r = 0.79 ± 0.01) through the relatively low glacier albedo in summer, while net longwave radiation (clouds) dominates the energy balance in the Langtang region (r = 0.76 ± 0.02). High amounts of snowfall and low melt rates result in a simulated positive glacier surface mass balance in Shimshal (+0.31 ± 0.06 m w.e. year −1) for the study period, while little snowfall, and high melt rates lead to a negative mass balance in Langtang (−0.40 ± 0.09 m w.e. year −1). The melt in Shimshal is highly variable between years, and is especially sensitive to summer snow events that reset the surface albedo. We conclude that understanding glacier mass balance anomalies requires quantification and insight into subtle shifts in the energy balance and accumulation regimes at high altitude and that the sensitivity of glaciers to climate change is regionally variable.

Abstract. Glaciers in High Mountain Asia (HMA) provide an important water resource for communities downstream, and they are markedly impacted by global warming, yet there is a lack of understanding of the observed glacier mass balances and their spatial variability. In particular, the glaciers in the western Kunlun Shan and Karakoram (WKSK) ranges show neutral to positive mass balances despite global warming. Using models of the regional climate and glacier mass balance, we reproduce the observed patterns of glacier mass balance in High Mountain Asia of the last decades within uncertainties. We show that low temperature sensitivities of glaciers and an increase in snowfall, for a large part caused by increases in evapotranspiration from irrigated agriculture, result in positive mass balances in the WKSK. The pattern of mass balances in High Mountain Asia can thus be understood from the combination of changes in climatic forcing and glacier properties, with an important role for irrigated agriculture.