Spatial and temporal variabilities of maximum snow depth in the Northern and Central Kazakhstan

2019 ◽  
Vol 12 (11) ◽  
Author(s):  
Marat Moldakhmetov ◽  
Lyazzat Makhmudova ◽  
Zhanara Zhanabayeva ◽  
Alina Kumeiko ◽  
Mohammad Daud Hamidi ◽  
...  
Keyword(s):  
Snow Depth ◽  
Maximum Snow Depth

Variation of snow, winter precipitation and winter air temperature during the last century at Nagaoka, Japan

1996 ◽  
Vol 42 (140) ◽  
pp. 136-140 ◽  
Author(s):  
Tsutomu Nakamura ◽  
Masujiro Shimizu
Keyword(s):  
Air Temperature ◽  
Snow Depth ◽  
Moving Average ◽  
Winter Precipitation ◽  
Statistical Correlation ◽  
Past Century ◽  
Temperature Deviation ◽  
Linear Rate ◽  
The Past ◽  
Maximum Snow Depth

AbstractReduced amounts of snow in the eight winters from 1986-87 to 1993-94 at Nagaoka, Japan, seem to be due to a winter air-temprature rise. The winter air temprature has shown cyclic varition gradual increase in the past 100years. The linear rate of the temperature rise in the past century was calculated as 1.35°C per 100 years. Both the maximum Snow depth and winter precipitation showed an inversely positive correlation with winter mean air temperature, The square of the statistical correlation coefficient r2was calculated as 0.321 and 0.107. respectively. Statistically smoothed curves or the maximum snow depth and winter precipitation showed maximum values in 1940, Fluctuations in deviation of the maximum Snow depth showed smaller values than in precipitation. The minimum winter mean air temperature obtained from a 10 year moving average curve was found in 1942, and the deviation fom the climatic mean changed from negative to positive in 1949. The change in sign or the temperature deviation and the increase of the deviation may be attributable to global warming.

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

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Xintong Jiang ◽  
Zhixiang Yin ◽  
Hanbo Cui
Keyword(s):  
Wind Tunnel ◽  
Snow Depth ◽  
Structural Safety ◽  
Windward Side ◽  
Leeward Side ◽  
Wind Tunnel Tests ◽  
Maximum Snow Depth ◽  
Adjacent Structures ◽  
Significant Difference ◽  
Snow Distribution

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.

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

2021 ◽  
Author(s):  
Moritz Buchmann ◽  
Michael Begert ◽  
Stefan Brönnimann ◽  
Christoph Marty
Keyword(s):  
Extreme Events ◽  
Snow Depth ◽  
Extreme Values ◽  
Local Scale ◽  
Swiss Alps ◽  
Scale Uncertainty ◽  
Return Levels ◽  
Maximum Snow Depth ◽  
Climate Indicators ◽  
The Impact

Abstract. 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

2021 ◽  
Author(s):  
Maxim Kharlamov ◽  
Maria Kireeva ◽  
Natalia Varentsova
Keyword(s):  
Soil Moisture ◽  
Snow Depth ◽  
Snow Accumulation ◽  
East European Plain ◽  
Water Losses ◽  
East European ◽  
Maximum Snow Depth ◽  
Winter Temperatures ◽  
Melt Water ◽  
Spring Freshet

<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>

Variation of snow, winter precipitation and winter air temperature during the last century at Nagaoka, Japan

1996 ◽  
Vol 42 (140) ◽  
pp. 136-140 ◽  
Author(s):  
Tsutomu Nakamura ◽  
Masujiro Shimizu
Keyword(s):  
Air Temperature ◽  
Snow Depth ◽  
Moving Average ◽  
Winter Precipitation ◽  
Statistical Correlation ◽  
Past Century ◽  
Temperature Deviation ◽  
Linear Rate ◽  
The Past ◽  
Maximum Snow Depth

AbstractReduced amounts of snow in the eight winters from 1986-87 to 1993-94 at Nagaoka, Japan, seem to be due to a winter air-temprature rise. The winter air temprature has shown cyclic varition gradual increase in the past 100years. The linear rate of the temperature rise in the past century was calculated as 1.35°C per 100 years. Both the maximum Snow depth and winter precipitation showed an inversely positive correlation with winter mean air temperature, The square of the statistical correlation coefficient r2 was calculated as 0.321 and 0.107. respectively. Statistically smoothed curves or the maximum snow depth and winter precipitation showed maximum values in 1940, Fluctuations in deviation of the maximum Snow depth showed smaller values than in precipitation. The minimum winter mean air temperature obtained from a 10 year moving average curve was found in 1942, and the deviation fom the climatic mean changed from negative to positive in 1949. The change in sign or the temperature deviation and the increase of the deviation may be attributable to global warming.

Sign in / Sign up

Export Citation Format

Share Document