Modelling of snowmelt runoff across the Himalayan Region

The Snowmelt-Runoff Model (SRM) was used to evaluate the impact of climate change on hydrological aspects of Lidder River Catchment of the Himalayan Region. It was observed that the river has an average discharge of 1082.49 cusecs. The coefficient of determination (R2) was varies in the range 0.90-0.95 during model validation period (2013-2018).The average coefficient of determination 0.926 and average seasonal volume difference (Dv) was obtained (-) 0.83%. The snow melt runoff harvested water can be used to bring 10 per cent more area under irrigation and water use efficiency which can be increased to an extent of 12-15 per cent for sustainable agriculture production in the Himalayan Region.

A comparison of hydrological models with different level of complexity in Alpine regions in the context of climate change

This study compares the ability of two degree-day models (Poli-Hydro and a degree-day implementation of Alpine3D) and one full energy-balance melt model (Alpine3D) to predict the discharge on two partly glacierized Alpine catchments of different size and intensity of exploitation, under present conditions and climate change as projected at the end of the century. For present climate, the magnitude of snow melt predicted by Poli-Hydro is sensibly lower than the one predicted by the other melt schemes, and the melting season is delayed by one month. This difference can be explained by the combined effect of the reduced complexity of the melting scheme and the reduced computational temporal resolution. The degree-day implementation of Alpine3D reproduces a melt season closer to the one obtained with its full solver; in fact, the onset of the degree-day mode still depends upon the full energy-balance solver, thus not bringing any particular benefit in terms of inputs and computational load, unlike with Poli-Hydro. Under climate change conditions, Alpine3D is more sensitive than Poli-Hydro, reproducing discharge curves and volumes shifted by one month earlier as a consequence of the earlier onset of snow melt. Despite their benefits, the coarser temporal computational resolution and the fixed monthly degree-days of simpler melt models like Poli-Hydro make them controversial to use for climate change applications with respect to energy-balance ones. Nevertheless, under strong river regulation, the influence of calibration might even overshadow the benefits of a full energy-balance scheme.

Amplification of Annual and Diurnal Cycles of Alpine Lightning

The response of lightning to a changing climate is not fully understood. Historic trends of proxies known for fostering convective environments suggest an increase of lightning over large parts of Europe. Since lightning results from the interaction of processes on many scales, as many of these processes as possible must be considered for a comprehensive answer. Recent achievements of decade-long seamless lightning measurements and hourly reanalyses of atmospheric conditions including cloud micro-physics combined with flexible regression techniques have made a reliable reconstruction of lightning down to its seasonally varying diurnal cycle feasible. To include a large variety of land-cover, topographical and atmospheric circulation conditions, the European Eastern Alps and their surroundings are our reconstruction region over a period of four decades. The most intense changes occurred over the high Alps where lightning activity doubled in the past decade compared to the 1980s. There, the lightning season reaches a higher maximum and starts one month earlier, likely due to the earlier snow melt. Diurnally, the peak is up to 50% stronger with more lightning strikes in the afternoon and evening hours. Signals along the southern and northern alpine rim are similar but weaker whereas the flatlands north of the Alps have no significant trend.

Why super sandstorm 2021 in North China

Severe sandstorms reoccurred in the spring of 2021 after absence for more than 10 years in North China. The dust source area, located in Mongolia, suffered destructive cooling and warming in early and late winter which loosened the land. Lacked precipitation, excessive snow melt, and strong evaporation resulted in dry soil and exiguous spring vegetation. A super-strong Mongolian cyclone developed on the bare and loose ground, and easily blew and transported large amounts of sand particles into North China. Furthermore, the top-ranking anomalies of sea ice shift in the Barents and Kara Sea and the sea surface temperatures in east Pacific and northwest Atlantic were identified to induce the aforementioned tremendous climate anomalies in dust source area. Analyses, based on large-ensemble CMIP6, yield identical results as the reanalysis data. Thus, the climate variabilities at different latitudes and synoptic disturbances jointly facilitated the strongest spring sandstorm over the recent decade.

Monitoring the Level of the Air Contamination by Chemical Elements Impoundment in the Snow Melt of the Snow Blanket

The research on the snow blanket pollution in Chita and its environs has been conducted to determine 29 chemical elements in the snow melt. It has been revealed that there is a direct causality between the pollution degree of the snow aqueous phase and the level of air pollution in the technogenesis environment. While comparing some indicators of chemical elements content and their compounds in snow melt, a critical concentration in the reference sites has been identified. It has been noted that the standard ratios compliance for this phase in the conjoint backgrounds is not always realistic, requires the MPC indicators development for the snow under technogenic impact and consideration of natural geochemical conditions and climatic factors.

The seasonal dynamics of a High Arctic plant - visitor network: temporal observations and responses to delayed snow melt

Plant - visitor food webs provide important insights into species interactions, and more information about their seasonal dynamics is vital to understanding the resilience of species to external pressures. Studies of Arctic networks can also improve our understanding of species responses to the pressures of climate change. This study provides the first description of a plant – insect visitor network in Svalbard, a High Arctic archipelago already experiencing the consequences of climate change. A subset of the network was collected from experimental plots where the snow melt date was delayed with snow fences. The deep snow plots delayed flowering and we expected this to disrupt plant-visitor interactions compared to ambient snow conditions. However, the composition of flowers and insect visitors were similar between regimes, and the network tracked patterns of overall flowering phenology. Nevertheless, the deep snow significantly reduced the average overlap between flower availability and insect activity, reducing the probability of an interaction. We suggest that at a landscape scale, Arctic pollinators will benefit from patchy changes to snow melt that maintain heterogeneity in the timing of flowering but changes that increase homogeneity in snowmelt across the landscape may negatively impact some species.