scholarly journals Estimate Average Annual Maximum Snow Depth with the Temperature and the Amount of Precipitation of the Mesh Normal Climatic Data in Toyama Prefecture, Japan

2018 ◽  
Vol 100 (5) ◽  
pp. 174-177
Author(s):  
Hideharu Aiura ◽  
Haruki Nakajima ◽  
Megumi Ishida
Keyword(s):  
Snow Depth ◽  
Climatic Data ◽  
Annual Maximum ◽  
Maximum Snow Depth

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

2016 ◽  
Vol 43 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Li Qin ◽  
Yujiang Yuan ◽  
Ruibo Zhang ◽  
Wenshou Wei ◽  
Shulong Yu ◽  
...  
Keyword(s):  
Snow Cover ◽  
Tree Ring ◽  
Snow Depth ◽  
Tianshan Mountains ◽  
Severe Drought ◽  
Annual Maximum ◽  
Climate History ◽  
Important Indicator ◽  
Maximum Snow Depth ◽  
Northern Tianshan

Abstract 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.

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 NOAA’s 1981–2010 U.S. Climate Normals: Monthly Precipitation, Snowfall, and Snow Depth

2013 ◽  
Vol 52 (11) ◽  
pp. 2377-2395 ◽  
Author(s):  
Imke Durre ◽  
Michael F. Squires ◽  
Russell S. Vose ◽  
Xungang Yin ◽  
Anthony Arguez ◽  
...  
Keyword(s):  
United States ◽  
Pacific Northwest ◽  
Great Plains ◽  
Snow Depth ◽  
State Of The Art ◽  
The United States ◽  
Climatic Data ◽  
Monthly Precipitation ◽  
National Climatic Data Center ◽  
The Caribbean

AbstractThe 1981–2010 “U.S. Climate Normals” released by the National Oceanic and Atmospheric Administration’s (NOAA) National Climatic Data Center include a suite of monthly, seasonal, and annual statistics that are based on precipitation, snowfall, and snow-depth measurements. This paper describes the procedures used to calculate the average totals, frequencies of occurrence, and percentiles that constitute these normals. All parameters were calculated from a single, state-of-the-art dataset of daily observations, taking care to produce normals that were as representative as possible of the full 1981–2010 period, even when the underlying data records were incomplete. In the resulting product, average precipitation totals are available at approximately 9300 stations across the United States and parts of the Caribbean Sea and Pacific Ocean islands. Snowfall and snow-depth statistics are provided for approximately 5300 of those stations, as compared with several hundred stations in the 1971–2000 normals. The 1981–2010 statistics exhibit the familiar climatological patterns across the contiguous United States. When compared with the same calculations for 1971–2000, the later period is characterized by a smaller number of days with snow on the ground and less total annual snowfall across much of the contiguous United States; wetter conditions over much of the Great Plains, Midwest, and northern California; and drier conditions over much of the Southeast and Pacific Northwest. These differences are a reflection of the removal of the 1970s and the addition of the 2000s to the 30-yr-normals period as part of this latest revision of the normals.

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.

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