Local-scale variability of seasonal mean and extreme values of in situ snow depth and snowfall measurements

Daily measurements of snow depth and snowfall can vary strongly over short distances. However, it is not clear if there is a seasonal dependence in these variations and how they impact common snow climate indicators based on mean values, as well as estimated return levels of extreme events based on maximum values. To analyse the impacts of local-scale variations we compiled a unique set of parallel snow measurements from the Swiss Alps consisting of 30 station pairs with up to 77 years of parallel data. Station pairs are usually located in the same villages (or within 3 km horizontal and 150 m vertical distances). Investigated snow climate indicators include average snow depth, maximum snow depth, sum of new snow, days with snow on the ground, days with snowfall, and snow onset and disappearance dates, which are calculated for various seasons (December to February (DJF), November to April (NDJFMA), and March to April (MA)). We computed relative and absolute error metrics for all these indicators at each station pair to demonstrate the potential variability. We found the largest relative inter-pair differences for all indicators in spring (MA) and the smallest in DJF. Furthermore, there is hardly any difference between DJF and NDJFMA, which show median variations of less than 5 % for all indicators. Local-scale variability ranges between less than 24 % (DJF) and less than 43 % (MA) for all indicators and 75 % of all station pairs. The highest percentage (90 %) of station pairs with variability of less than 15 % is observed for days with snow on the ground. The lowest percentage (30 %) of station pairs with variability of less than 15 % is observed for average snow depth. Median differences of snow disappearance dates are rather small (3 d) and similar to the ones found for snow onset dates (2 d). An analysis of potential sunshine duration could not explain the higher variabilities in spring. To analyse the impact of local-scale variations on the estimation of extreme events, 50-year return levels were quantified for maximum snow depth and maximum 3 d new snow sum, which are often used for avalanche prevention measures. The found return levels are within each other's 95 % confidence intervals for all (but three) station pairs, revealing no striking differences. The findings serve as an important basis for our understanding of variabilities of commonly used snow indicators and extremal indices. Knowledge about such variabilities in combination with break-detection methods is the groundwork in view of any homogenization efforts regarding snow time series.

Analysis of moose-vehicle collisions countermeasures in northern climates

This research investigates the reliability of two measures intended to reduce moose-vehicle collisions (MVCs): continuous lighting and clearing/grubbing of roadway corridors. Individual analyses and a combined regression analysis were conducted to measure the effects of several combinations of variables on MVC rates, including clearing and grubbing, continuous lighting, clearing without grubbing, moose population, precipitation, snowfall, and maximum snow depth. Nine corridor improvement projects were analyzed based on the variables present. In previous studies, it has been hypothesized that MVC rates are influenced by environmental conditions such as snowfall and daylight. The Alaska Department of Transportation and Public Facilities (DOT&PF) has performed many studies on MVCs along several corridors. Some corridors showed a significant drop in the number of MVCs after the installation of continuous lighting. The results show there is a consistent drop in MVCs after clearing and grubbing, with the exception of one corridor. The combined clearing/grubbing and continuous lighting projects also resulted in a consistent drop in MVCs. The projects with clearing and grubbing as a component had varying trends in MVCs, which may indicate that DOT&PF Maintenance and Operations performed clearing of re-vegetated areas, or that older growth is less of an attractant for moose.

Local-scale uncertainty of seasonal mean and extreme values of in-situ snow depth and snow fall measurements

Measurements of snow depth and snowfall on the daily scale can vary strongly over short distances. However, it is not clear if there is a seasonal dependence in these variations and how they impact common snow climate indicators based on mean values, as well as estimated return levels of extreme events based on maximum values. To analyse the impacts of local-scale variations we compiled a unique set of parallel snow measurements from the Swiss Alps consisting of 30 station pairs with up to 77 years of parallel data. Station pairs are mostly located in the same villages (or within 3 km horizontal and 150 m vertical distances). Investigated snow climate indicators include average snow depth, maximum snow depth, sum of new snow, days with snow on the ground, days with snowfall as well as snow onset and disappearance dates, which are calculated for various seasons (December to February (DFJ), November to April (NDJFMA), and March to April (MA)). We computed relative and absolute error metrics for all these indicators at each station pair to demonstrate the potential uncertainty. We found the largest relative inter-pair differences for all indicators in spring (MA) and the smallest in DJF. Furthermore, there is hardly any difference between DJF and NDJFMA which show median uncertainties of less than 5 % for all indicators. Local-scale uncertainty ranges between less than 24 % (DJF) and less than 43 % (MA) for all indicators and 75 % of all station pairs. Highest (lowest) percentage of station pairs with uncertainty less than 15 % is observed for days with snow on the ground with 90 % (average snow depth, 30 %). Median differences of snow disappearance dates are rather small (three days) and similar to the ones found for snow onset dates (two days). An analysis of potential sunshine duration could not explain the higher uncertainties in spring. To analyse the impact of local-scale variations on the estimation of extreme events, 50-year return levels were quantified for maximum snow depth and maximum 3-day new snow sum, which are often used for prevention measures. The found return levels are within each other’s 95 % confidence intervals for all (but two) station pairs, revealing no striking differences. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and extremal indices. Knowledge about such uncertainties in combination with break-detection methods is the groundwork in view of any homogenization efforts regarding snow time series.

Spring freshet on East European plain: changes in drivers and conditions during last three decades

<p>Over the past 20 years, the climate on the East European plain tends to be significantly warmer and drier. Winters became shorter and spring freshet’s conditions have been changed significantly. Maximum snow depth was the most important factor of spring freshet formation 30 years ago, but nowadays it has no significance at all and main factor today is melt water losses on infiltration and evaporation.</p><p>We registered a decrease in the period of stable snow accumulation (on average by 20% in the southern and southwestern parts of the East European Plain) because of the increase in winter temperatures. More often during first part of winter snow cover disappeared totally. The number of thaws and their duration at the end of the winter also increase and this leads to earlier and more prolonged melting of the snow pack. In these conditions, an extremely low spring freshet is formed. Our studies show that with the condition of an equal maximum snow depth the slow snowmelt forms the spring freshet up to 4 times less in volume than the fast melting.</p><p>Soil moisture also plays an important role in the melt water losses. The most part of the East European Plain is characterized by a decrease in soil moisture in late autumn, which indicates increased losses during snow melting period.</p><p>Still, the most significant changes in the structure of the factors of spring freshet formation are common to the southern and southwestern parts of the East European Plain. In the northern part, conservative factors still dominate, although this area is characterized by the significant increase in winter temperatures.</p><p>The study was supported by Russian Science Foundation Proj. №19-77-10032</p>

Snow cover variations across China from 1951–2018

Based on a snow depth dataset retrieved from meteorological stations, this experiment explored snow indices, including snow depth (SD), snow covered days (SCDs), and snow phenology variations, across China from 1951 to 2018. The results indicated that the snow cover in China exhibits regional differences. The annual mean SD tended to increase, and the increases in mean and maximum snow depth were 0.04 cm and 0.1 cm per decade, respectively. SCDs tended to increase by approximately 0.5 days per decade. The significant increases were concentrated at latitudes higher than 40° N, especially in Northeast China. However, in the Tibetan Plateau, the SD and SCDs tended to decrease but not significantly. Regarding the snow phenology variations, the snow duration days in China decreased, and 25.2 % of the meteorological stations showed significant decreasing trends. This result was mainly caused by the postponement of the snow onset date and the advancement of the snow end date. Geographical and meteorological factors are closely related to snow cover, especially the change in temperature, which will lead to significant changes in snow depth and phenology.

Wind Tunnel Tests of Wind-Induced Snow Distribution for Cubes with Holes

The nonuniform distribution of snow around structures with holes is extremely unfavorable for structural safety, and the mechanism of wind-snow interaction between adjacent structures with holes needs to be explored. Therefore, a wind tunnel simulation was performed, in which quartz particles with an average particle size of 0.14 mm as snow particles were used, and cubes with dimensions of 100 mm × 100 mm × 100 mm each containing a hole with the size of 20 mm × 20 mm were employed as structures. Firstly, the quality of a small low-speed wind tunnel flow field was tested, and then the effects of hole orientation (hole located on the windward side, leeward side, and other vertical sides) and absence of holes on the surface of a single cube were studied. Furthermore, the effects of different hole locations (respectant position, opposite position, and dislocation) and relative spacing (50 mm, 100 mm, and 150 mm) on the surfaces of two cubes and the snow distribution around them were investigated. It was concluded that the presence and location of hole had a great influence on snow distribution around cubes. Snow distribution was favorable when hole was located on the other vertical sides of the test specimen. The most unfavorable snow distribution was obtained when the holes on the two-holed sides of the cubes were respectant with a maximum snow depth coefficient of 1.4. A significant difference was observed in the snow depths of two sides of cubes when holes were dislocated. When two holes were respectant, surrounding snow depth was decreased, and the maximum snow depth on model surface area was increased with the increase of spacing. Wind tunnel tests on holed cubes provided a reference for the prediction of snow load distribution of typical structures with holes.

Tree-Ring Response to Snow Cover and Reconstruction of Century annual Maximum Snow Depth for Northern Tianshan Mountains, China

Heavy snowfall and extreme snow depth cause serious losses of human life and property in the northern Tianshan Mountains almost every winter. Snow cover is an important indicator of climate change. In this study, we developed five tree-ring-width chronologies of Schrenk spruce (Picea schrenkiana Fisch. et Mey) from the northern Tianshan Mountains using standard dendrochronological methods. Correlation analyses indicated that radial growth of trees in the northern Tianshan Mountains is positively affected by annual maximum snow depth. This relationship was validated and models of annual maximum snow depth back to the 18th century were developed. The reconstruction explains 48.3% of the variance in the instrumental temperature records during the 1958/59–2003/04 calibration periods. It indicates that quasi-periodic changes exist on 2.0–4.0-yr, 5.3-yr, 14.0-yr, and 36.0-yr scales. The reconstructed series shows that maximum snow depth exhibits obvious stages change, the periods characterized by lower maximum snow depth were 1809/10–1840/41, 1873/74–1893/94, 1909/10–1929/30, 1964/65–1981/82, and the periods characterized by higher maximum snow depth were 1841/42–1872/73, 1894/95–1908/09, 1930/31–1963/64, and 1982/83–present. The lower period of annual maximum snow depth during the 1920s–1930s is consistent with the severe drought that occurred at this time in northern China. From the 1970s to the present, the maximum snow depth has increased clearly with the change to a warmer and wetter climate in Xinjiang. The reconstruction sheds new light on snow cover variability and change in a region where the climate history for the past several centuries is poorly understood.