scholarly journals Variations and changes in snow depth at meteorological stations Barentsburg and Hornsund (Spitsbergen)

2017 ◽  
Vol 58 (75pt1) ◽  
pp. 11-20 ◽  
Author(s):  
Marzena Osuch ◽  
Tomasz Wawrzyniak
Keyword(s):  
Snow Cover ◽  
Interannual Variability ◽  
Trend Analysis ◽  
Air Temperature ◽  
Snow Depth ◽  
Moving Average ◽  
Onset Date ◽  
The Novel ◽  
Temperature And Precipitation ◽  
Snow Cover Duration

ABSTRACTIn this study, seasonality and interannual variability of snow depth at two stations (Hornsund and Barentsburg) located in western Spitsbergen are investigated. For this purpose, the novel Moving Average over Shifting Horizon method combined with trend estimation was used. The Hornsund and Barentsburg stations exhibit similar snow depth trends during early autumn and late spring when statistically significant decreases were estimated at both stations (for August 1984–July 2016). In the remaining period, there are differences in outcomes between stations. The results for Barentsburg from October till the end of May are characterised by the lack of a trend while at Hornsund decreases of snow depth were estimated. The largest changes occur in May when the snow depth was at its maximum. Differences in the estimated tendencies were explained with the help of a trend analysis for air temperature and precipitation. An analysis of maximum snow depth, snow onset date, snow disappearance date and snow-cover duration is included. The results of the assessment depend on the location, with a lack of statistically significant changes in Barentsburg, and later snow onset date, shorter duration and decrease of maximum depth in Hornsund.

scholarly journals Variations of snow cover in the source regions of the Yangtze and Yellow Rivers in China between 1960 and 1999

2007 ◽  
Vol 53 (182) ◽  
pp. 420-426 ◽  
Author(s):  
Yang Jianping ◽  
Ding Yongjian ◽  
Liu Shiyin ◽  
Liu Jun Feng
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Monthly Precipitation ◽  
Measured Temperature ◽  
Annual Maximum ◽  
Study Region ◽  
Source Regions ◽  
Precipitation Decrease ◽  
Snow Cover Duration

AbstractVariations in annual maximum and accumulated snow depths, snow-cover duration, precipitation and air temperature have been analyzed using daily snow depth, monthly air temperature and monthly precipitation data from 1960 to 1999 from six meteorological stations in the source regions of the Yangtze and Yellow Rivers in China. Annual maximum snow depth, snow-cover duration and precipitation increased by ~0.23, ~0.06 and ~0.05% a–1, respectively, during the study period, while annual accumulated snow depth increased by ~2.4% a–1. Annual mean air temperature increased by ~0.6°C over the study period. An unusually heavy snow cover in 1985 coincided with historically low air temperatures. Data from Tuotuohe and Qingshuihe meteorological stations are used to examine inter-station variability. The annual maximum and accumulated snow depths increased by ~0.35 and ~10.6% a–1 at Tuotuohe, and by ~0.42 and ~2.3%a–1 at Qingshuihe. However, from the late 1980s until 1999 the climate in the study region has become warmer and drier. The precipitation decrease in the 1990s (and not the rapid rise in measured temperature) is thought to be the primary cause of the decrease in snow depth in those years.

scholarly journals Trends and regime shifts in climatic conditions and river runoff in Estonia during 1951–2015

2017 ◽  
Vol 8 (4) ◽  
pp. 963-976 ◽  
Author(s):  
Jaak Jaagus ◽  
Mait Sepp ◽  
Toomas Tamm ◽  
Arvo Järvet ◽  
Kiira Mõisja
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
Atmospheric Circulation ◽  
Air Temperature ◽  
Large Scale ◽  
Regime Shifts ◽  
The Arctic ◽  
Dry Period ◽  
Snow Cover Duration ◽  
Large Scale Atmospheric Circulation

Abstract. Time series of monthly, seasonal and annual mean air temperature, precipitation, snow cover duration and specific runoff of rivers in Estonia are analysed for detecting of trends and regime shifts during 1951–2015. Trend analysis is realised using the Mann–Kendall test and regime shifts are detected with the Rodionov test (sequential t-test analysis of regime shifts). The results from Estonia are related to trends and regime shifts in time series of indices of large-scale atmospheric circulation. Annual mean air temperature has significantly increased at all 12 stations by 0.3–0.4 K decade−1. The warming trend was detected in all seasons but with the higher magnitude in spring and winter. Snow cover duration has decreased in Estonia by 3–4 days decade−1. Changes in precipitation are not clear and uniform due to their very high spatial and temporal variability. The most significant increase in precipitation was observed during the cold half-year, from November to March and also in June. A time series of specific runoff measured at 21 stations had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 L s−1 km−2 decade−1, while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May have notably decreased indicating the shift of the runoff maximum to the earlier time, i.e. from April to March. Air temperature, precipitation, snow cover duration and specific runoff of rivers are highly correlated in winter determined by the large-scale atmospheric circulation. Correlation coefficients between the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) indices reflecting the intensity of westerlies, and the studied variables were 0.5–0.8. The main result of the analysis of regime shifts was the detection of coherent shifts for air temperature, snow cover duration and specific runoff in the late 1980s, mostly since the winter of 1988/1989, which are, in turn, synchronous with the shifts in winter circulation. For example, runoff abruptly increased in January, February and March but decreased in April. Regime shifts in annual specific runoff correspond to the alternation of wet and dry periods. A dry period started in 1964 or 1963, a wet period in 1978 and the next dry period at the beginning of the 21st century.

Comparison of snow cover characteristics according to weather stations and ERA 5-Land reanalysis in the Perm region

2021 ◽  
Vol 2 ◽  
pp. 95-110
Author(s):  
A.D., Kryuchkov ◽  
◽  
N.A Kalinin ◽  
Keyword(s):  
Snow Cover ◽  
Interannual Variability ◽  
Seasonal Variability ◽  
Snow Depth ◽  
Reanalysis Data ◽  
Error Distribution ◽  
Current Version ◽  
Weather Stations ◽  
Perm Region

Comparison of snow cover characteristics according to weather stations and ERA 5-Land reanalysis in the Perm region / Kryuchkov A.D., Kalinin N.A. // Hydrometeorological Research and Forecasting, 2021, no. 2 (380), pp. 95-110. The consistency of information on the snow depth contained in the ERA 5-Land reanalysis with data of weather stations of the Perm region is analyzed. The study is performed for the period from October 1990 to May 2020. It is shown that the interannual variability of the snow cover is generally successfully reflected by the current version of the reanalysis. Data on the snow availability are more accurately reproduced during the period of formation of the snow cover than during its melt. The performed calculations demonstrate a systematic overestimation of the snow depth in the ERA 5-Land reanalysis relative to the actual observations and a predominantly meridional error distribution on the territory of the Perm region. The maximum values in the seasonal variability of the snow cover occur earlier in the reanalysis than in the actual observations. Keywords: snow cover, reanalysis, weather stations, seasonal variability, interannual variability

scholarly journals Estimating the weight of a snow cover using only meteorological factors

1993 ◽  
Vol 18 ◽  
pp. 190-192
Author(s):  
Kenji Shinojima ◽  
Hiroshi Harada
Keyword(s):  
Snow Cover ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Moving Average ◽  
Data Acquisition System ◽  
Degree Days ◽  
Forest Product Research Institute ◽  
Temperature And Precipitation ◽  
Using Data

We compute the weight of the snow cover as a function of the daily quantity of precipitation and daily melting using only data from the Automated Meteorological Data Acquisition System (AMeDAS), which is used widely in Japan. The correlation between long-term measurements and meteorological data in AMeDAS factors was computed by statistical methods from the Forestry and Forest Product Research Institute, Tokamachi Experiment Station, in Niigata Prefecture, using data for 11 winter seasons (1977–87). The daily quantity of melting is expressed with a three-day moving average of degree days. The coefficient of correlation between the daily groups of each value of the 1323 days during the 11 winter seasons was 0.986 with a standard deviation of ±590 Ν m−2. Thus, if air temperature and precipitation can be obtained for an area, the weight of the snow cover can be estimated with confidence.

scholarly journals Estimating the weight of a snow cover using only meteorological factors

1993 ◽  
Vol 18 ◽  
pp. 190-192
Author(s):  
Kenji Shinojima ◽  
Hiroshi Harada
Keyword(s):  
Snow Cover ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Moving Average ◽  
Data Acquisition System ◽  
Degree Days ◽  
Forest Product Research Institute ◽  
Temperature And Precipitation ◽  
Using Data

We compute the weight of the snow cover as a function of the daily quantity of precipitation and daily melting using only data from the Automated Meteorological Data Acquisition System (AMeDAS), which is used widely in Japan. The correlation between long-term measurements and meteorological data in AMeDAS factors was computed by statistical methods from the Forestry and Forest Product Research Institute, Tokamachi Experiment Station, in Niigata Prefecture, using data for 11 winter seasons (1977–87).The daily quantity of melting is expressed with a three-day moving average of degree days. The coefficient of correlation between the daily groups of each value of the 1323 days during the 11 winter seasons was 0.986 with a standard deviation of ±590 Ν m−2. Thus, if air temperature and precipitation can be obtained for an area, the weight of the snow cover can be estimated with confidence.

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 Changes in Snow Depth, Snow Cover Duration, and Potential Snowmaking Conditions in Austria, 1961–2020—A Model Based Approach

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1330
Author(s):  
Marc Olefs ◽  
Roland Koch ◽  
Wolfgang Schöner ◽  
Thomas Marke
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Climate Impact ◽  
Physically Based ◽  
Spatially Distributed ◽  
Direct Interpretation ◽  
H 26 ◽  
Natural Snow ◽  
Snow Cover Duration ◽  
Snow Conditions

We used the spatially distributed and physically based snow cover model SNOWGRID-CL to derive daily grids of natural snow conditions and snowmaking potential at a spatial resolution of 1 × 1 km for Austria for the period 1961–2020 validated against homogenized long-term snow observations. Meteorological driving data consists of recently created gridded observation-based datasets of air temperature, precipitation, and evapotranspiration at the same resolution that takes into account the high variability of these variables in complex terrain. Calculated changes reveal a decrease in the mean seasonal (November–April) snow depth (HS), snow cover duration (SCD), and potential snowmaking hours (SP) of 0.15 m, 42 days, and 85 h (26%), respectively, on average over Austria over the period 1961/62–2019/20. Results indicate a clear altitude dependence of the relative reductions (−75% to −5% (HS) and −55% to 0% (SCD)). Detected changes are induced by major shifts of HS in the 1970s and late 1980s. Due to heterogeneous snowmaking infrastructures, the results are not suitable for direct interpretation towards snow reliability of individual Austrian skiing resorts but highly relevant for all activities strongly dependent on natural snow as well as for projections of future snow conditions and climate impact research.

scholarly journals On the Role of Snow Cover in Depressing Air Temperature

2008 ◽  
Vol 47 (7) ◽  
pp. 2008-2022 ◽  
Author(s):  
Thomas L. Mote
Keyword(s):  
Boundary Layer ◽  
North America ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Cloud Cover ◽  
Effect Of Temperature ◽  
Temperature Changes ◽  
Temperature Depression

Abstract This study empirically examines the role of snow depth on the depression of air temperature after controlling for effect of temperature changes above the boundary layer. In addition, this study examines the role of cloud cover, solar elevation angle, and maximum snow-covered albedo on the temperature depression due to snow cover. The work uses a new dataset of daily, gridded snow depth, snowfall, and maximum and minimum temperatures for North America from 1960 to 2000 in conjunction with 850-hPa temperature data for the same period from the NCEP–NCAR reanalysis, version 1. The 850-hPa temperatures are used as a control to remove the effect of temperature changes above the boundary layer on surface air temperatures. Findings from an analysis of variance demonstrate that snow cover can result in daily maximum (minimum) temperature depressions on average of 4.5°C (2.6°C) for snow depths greater than 10 cm over the grasslands of central North America, but temperature depressions average only 1.2°C (1.1°C) overall. The temperature depression of snow cover is shown to be reduced by increased cloud cover and decreased maximum albedo, which is indicative of denser forest cover. The role of snow melting on temperature depression is further explored by comparing days with maximum temperatures above or below freezing.

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.

scholarly journals How much can we save? Impact of different emission scenarios on future snow cover in the Alps

2017 ◽  
Vol 11 (1) ◽  
pp. 517-529 ◽  
Author(s):  
Christoph Marty ◽  
Sebastian Schlögl ◽  
Mathias Bavay ◽  
Michael Lehning
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Swiss Alps ◽  
Small Scale ◽  
Emission Scenarios ◽  
Scenario Period ◽  
Temperature And Precipitation ◽  
Elevation Zone ◽  
Time Periods ◽  
Intervention Scenario

Abstract. This study focuses on an assessment of the future snow depth for two larger Alpine catchments. Automatic weather station data from two diverse regions in the Swiss Alps have been used as input for the Alpine3D surface process model to compute the snow cover at a 200 m horizontal resolution for the reference period (1999–2012). Future temperature and precipitation changes have been computed from 20 downscaled GCM-RCM chains for three different emission scenarios, including one intervention scenario (2 °C target) and for three future time periods (2020–2049, 2045–2074, 2070–2099). By applying simple daily change values to measured time series of temperature and precipitation, small-scale climate scenarios have been calculated for the median estimate and extreme changes. The projections reveal a decrease in snow depth for all elevations, time periods and emission scenarios. The non-intervention scenarios demonstrate a decrease of about 50 % even for elevations above 3000 m. The most affected elevation zone for climate change is located below 1200 m, where the simulations show almost no snow towards the end of the century. Depending on the emission scenario and elevation zone the winter season starts half a month to 1 month later and ends 1 to 3 months earlier in this last scenario period. The resulting snow cover changes may be roughly equivalent to an elevation shift of 500–800 or 700–1000 m for the two non-intervention emission scenarios. At the end of the century the number of snow days may be more than halved at an elevation of around 1500 m and only 0–2 snow days are predicted in the lowlands. The results for the intervention scenario reveal no differences for the first scenario period but clearly demonstrate a stabilization thereafter, comprising much lower snow cover reductions towards the end of the century (ca. 30 % instead of 70 %).

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