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Net radiation is a key component of surface radiation balance and has a strong influence on hydrological processes via evapotranspiration. In this study, daily average net radiation (Rnmean) for all-sky conditions was investigated as a function of the estimated daily average global radiation (GRmean) during the summers of 2011 and 2012 (128 days total) in the Sugnugur Valley of Northern Mongolia. We present a simple alternative remote sensing approach that considers factors such as topography, cloud fraction, cloud optical thickness and surface albedo. First, a geometric model for the simulation of daily average global radiation (GRCS:mean) for clear-sky conditions was applied on a daily basis. It considers topographical effects, such as slope, azimuth and elevation. GRmean was then derived for all-sky conditions by coupling the averaged atmospheric products of MODIS. Finally, Rnmean was obtained as a function of the simulated GRmean using the linear regression parameters found at a permanent observation site. The results were validated with the data from a nearby temporary observation site. The root mean square errors (RMSE) were 44 and 52 Wm−2 for GRmean and 18 and 25 Wm−2 for Rnmean at the two different sites. This methodology requires few observations and offers a simple means for estimating GRmean with high spatial (30 m) and temporal (daily) resolution under any sky conditions in the absence of ground measurements. Furthermore, Rnmean can be modeled from the simulated GRmean at regional or watershed scales where ground observations exist at one site at least. [ABSTRACT FROM AUTHOR]

High topographic heterogeneity and complex mechanisms between the atmosphere and the ground create unique hydro-climatic processes over mountainous regions. Based on in situ observations, we present the spatial variability of ground surface temperature (GST) in the Khentii Mountains of northern Mongolia, which is situated at the southern fringe of the Eurasian permafrost zone. Changes in the hydrothermal regime of the active layer were investigated in association with changing climate and wildfire effects. The results reveal that the GST tends to increase continuously since 2011 in both thawing and freezing seasons, and varies significantly within a short horizontal distance, particularly during the thawing season. Extreme weather events, such as drought and heavy snowfall, amplify the increase in the ground temperature and deepen the seasonal thawing depth. The fire-induced loss in organic layer resulted in a greater heat penetration deeper into the ground and unbalanced the moisture distribution. Overall, the thawing depth is greater by >1.7 m under severely burned forest, compared to unburned forest. Given that about 30% of the boreal forest was affected by wildfire in the study area, the ground thermal regime changed considerably. The findings suggest that the combination of regional temperature rise and more frequent extreme weather and wildfire events in the region triggers permafrost degradation and alters the hydrothermal regime in the future. [ABSTRACT FROM AUTHOR]

Livestock production is a socioeconomic linchpin in Mongolia and is affected by large-scale livestock die-offs. Colloquially known as dzuds, these die-offs are driven by anomalous climatic events, including extreme cold temperatures, extended snow cover duration (SCD) and drought. As average temperatures across Mongolia have increased at roughly twice the global rate, we hypothesized that increasing cold season surface melt including soil freeze/thaw (FT), snowmelt, and icing events associated with regional warming have become increasingly important drivers of dzud events as they can reduce pasture productivity and inhibit access to grazing. Here, we use daily brightness temperature (Tb) observations to identify anomalous surface melt and icing events across Mongolia from 2003–2016 and their contribution to dzuds relative to other climatic drivers, including winter temperatures, SCD, and drought. We find a positive relationship between surface melt and icing events and livestock mortality during the fall in southern Mongolia and during the spring in the central and western regions. Further, anomalous seasonal surface melt and icing events explain 17–34% of the total variance in annual livestock mortality, with cold temperatures as the leading contributor of dzuds (20–37%). Summer drought showed the greatest explanatory power (43%) but overall had less statistically significant relationships relative to winter temperatures. Our results indicate that surface melt and icing events will become an increasingly important driver of dzuds as annual temperatures and livestock populations are projected to increase in Mongolia. [ABSTRACT FROM AUTHOR]

Knowledge of the snow cover dynamics in mountains of the semi-arid regions on Earth is essential for an improved understanding of the hydrological regime and for human water supply in a water scarce environment. In the semi-arid Sugnugur headwater catchment (in the Khentii Mountains, northern Mongolia), a spatial analysis of seasonal snow cover duration (SCD) was achieved on a 30 m grid by integrating the spatial resolution of Landsat-7, Landsat-8 and Sentinel-2A images with the daily temporal resolution of MODIS snow products (2000-2017). Validation was achieved using in situ measurements from winter field campaigns and spatially distributed surface temperature recordings. We found a mean increase of SCD with altitude at approximately +6 days/100m. However, no altitude-dependent changes in snow depth could be observed during the field campaigns. The southern exposed valley slopes are either snow free or covered by intermittent snow throughout the winter months due to high sublimation rates and prevailing wind. The estimated mean SCD ranges from 124 in the lower parts of the catchment to 226 days on the mountain peaks, with a mean underestimation of 12-13 days. Snow onset and melt dates exhibited large inter-annual variability, but no significant trend in the seasonal SCD was evident. Our method supports the better quantification of snow melt rates and thus water availability in this semi-arid environment. It can be applied to high-resolution snow mapping in similar mountainous regions. [ABSTRACT FROM AUTHOR]