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

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.

Download Full-text

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

Annals of Glaciology ◽

10.1017/aog.2017.20 ◽

2017 ◽

Vol 58 (75pt1) ◽

pp. 11-20 ◽

Cited By ~ 7

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.

Download Full-text

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

Earth System Dynamics ◽

10.5194/esd-8-963-2017 ◽

2017 ◽

Vol 8 (4) ◽

pp. 963-976 ◽

Cited By ~ 15

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.

Download Full-text

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

Atmosphere ◽

10.3390/atmos11121330 ◽

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.

Download Full-text

On the Role of Snow Cover in Depressing Air Temperature

Journal of Applied Meteorology and Climatology ◽

10.1175/2007jamc1823.1 ◽

2008 ◽

Vol 47 (7) ◽

pp. 2008-2022 ◽

Cited By ~ 32

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.

Download Full-text

Regional pattern of annual snow cover duration in the Greater Alpine Region (2000 – 2018)

10.5194/egusphere-egu2020-4863 ◽

2020 ◽

Author(s):

Markus Hrachowitz ◽

Stefan Fugger ◽

Karsten Schulz

Keyword(s):

Snow Cover ◽

Regional Differences ◽

Climatic Variability ◽

Alpine Region ◽

Annual Number ◽

Point Scale ◽

Study Region ◽

The North ◽

Upward Shift ◽

Snow Cover Duration

This study analyses regional differences in annual snow cover duration as quantified by the annual number of days with snow cover (Dsc) and investigates differences in sensitivity of Dsc to climatic variability across the Greater Alpine Region over the 2000-2018 period. MODIS snow cover data were used to estimate Dsc based on the Regional Snowline Elevation (RSLE) method, a spatial filter technique for large-scale cloud cover reduction.Dsc over the study period closely follows the relief, with a mean Dsc of ~10&#8211;60 days at elevations of 500 m that increase to about 100&#8211;150 days at 1500m. South of the main alpine ridge, Dsc is, at the same elevation, consistently lower than north of it with differences of &#916;Dsc&#160; ~25&#8211;50 days. Similarly, the eastern part of the study region experiences longer snow cover duration than the western part. This difference is particularly pronounced at elevations below 1500m where &#916;Dsc ~25 days. Throughout the study period, a general upward shift of the RSLE was observed for most parts of the Greater Alpine Region. This upward shift, characterized by later onset of snow accumulation (&#8710;Dstart ~14&#8211;30 d) and earlier melt-out at the end of the snow season (&#8710;Dend ~10&#8211;20 d), translates into reductions of the annual number of snow-covered days by up to &#916;Dsc = -46 days over the study period. The data suggest that, in particular, low-elevation&#160; (< 600m.a.s.l.) regions in the north-eastern part of the Greater Alpine Region, as well as elevations between 1400 and 2000 m in the north-western part of the study region experienced the most pronounced reductions of Dsc., whereas &#916;Dsc remained very limited south of the main Alpine ridge. The spatially integrated MODIS-derived estimates of Dsc correspond well with Dsc estimates derived from longer-term point-scale observations at >500 ground station observations across the region. In the majority of regions, the temporal evolution of Dsc over the 2000-2018 study period also reflects the longer-term Dsc trends as estimated from these point-scale observations (1970-2014). This provides supporting evidence that the widespread decline of Dsc across the Greater Alpine Region as estimated based on MODIS data is largely not caused by isolated short-term climatic variability but coincides with multi-decadal fluctuations. A comparison of the sensitivities of Dsc to climatic variability indicates that neither mean winter temperatures Tw nor annual solid precipitation totals Ps, are consistent first order controls on Dsc across&#160; elevations and regions. Rather, the data highlight the importance of the interaction between the two variables: depending on the respective sensitivities of Dsc to changes in either variable, Tw or Ps, respectively, the interplay between them can reinforce or largely off-set potential effects on Dsc in different regions in the Greater Alpine Region. The regional differences in &#916;Dsc with a less pronounced decline south of the main Alpine ridge are largely a consequence of this interplay: while Tw evolved similarly North and South of the Alpine ridge, many southern regions, unlike the northern regions, experienced an increase in Ps that offsets the effects of positive temperature trends.

Download Full-text

Simulation of Northern Eurasian Local Snow Depth, Mass, and Density Using a Detailed Snowpack Model and Meteorological Reanalyses

Journal of Hydrometeorology ◽

10.1175/jhm-d-12-012.1 ◽

2013 ◽

Vol 14 (1) ◽

pp. 203-219 ◽

Cited By ~ 79

Author(s):

Eric Brun ◽

Vincent Vionnet ◽

Aaron Boone ◽

Bertrand Decharme ◽

Yannick Peings ◽

...

Keyword(s):

Snow Cover ◽

Land Surface ◽

Snow Depth ◽

Snow Water Equivalent ◽

Land Surface Model ◽

Northern Eurasia ◽

Surface Model ◽

Monthly Precipitation ◽

Blowing Snow ◽

Snow Water

Abstract The Crocus snowpack model within the Interactions between Soil–Biosphere–Atmosphere (ISBA) land surface model was run over northern Eurasia from 1979 to 1993, using forcing data extracted from hydrometeorological datasets and meteorological reanalyses. Simulated snow depth, snow water equivalent, and density over open fields were compared with local observations from over 1000 monitoring sites, available either once a day or three times per month. The best performance is obtained with European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim). Provided blowing snow sublimation is taken into account, the simulations show a small bias and high correlations in terms of snow depth, snow water equivalent, and density. Local snow cover durations as well as the onset and vanishing dates of continuous snow cover are also well reproduced. A major result is that the overall performance of the simulations is very similar to the performance of existing gridded snow products, which, in contrast, assimilate local snow depth observations. Soil temperature at 20-cm depth is reasonably well simulated. The methodology developed in this study is an efficient way to evaluate different meteorological datasets, especially in terms of snow precipitation. It reveals that the temporal disaggregation of monthly precipitation in the hydrometeorological dataset from Princeton University significantly impacts the rain–snow partitioning, deteriorating the simulation of the onset of snow cover as well as snow depth throughout the cold season.

Download Full-text

How is snow cover in global mountain area changing? Detection of snow cover and snow phenology changes by using MODIS imagery over 2000 - 2018

10.5194/egusphere-egu2020-20482 ◽

2020 ◽

Author(s):

Claudia Notarnicola

Keyword(s):

Snow Cover ◽

Northern Hemisphere ◽

Air Temperature ◽

Lower Latitude ◽

Snow Melt ◽

Snow Cover Area ◽

Mountain Areas ◽

Snow Albedo ◽

Modis Imagery ◽

Snow Cover Duration

Mountain areas have raised a lot of attention in the past years, as they are considered sentinel of climate changes. Quantification of snow cover changes and related phenology in global mountain areas can have multiple implications on water resources, ecosystem services, tourism, and energy production [1]. Up to now, several studies have investigated snow cover changes at continental scale and there are several indications of snow cover decline over the Northern Hemisphere [2, 3], despite no study has analyzed snow behavior specifically in mountain areas at global level. In this context, this study investigates the changes in the main snow cover parameters (snow cover area, snow cover duration, snow onset and snow melt) over global mountain areas from 2000 to 2018.To proper monitor the evolution of snow changes at global mountain areas and interlinkages with meteorological drivers (air temperature, snowfall), automatic procedures were developed based on MODIS imagery in global mountain areas over the period 2000-2018 by exploiting Google Earth Engine where the whole time series of MODIS is available at a global scale. MODIS snow cover products have the highest resolution available, 500 m, and with daily global acquisitions. From MODIS snow cover areas (MOD10v6), snow phenology parameters were derived, namely snow cover duration, snow onset and snow melt. Together with snow cover and phenology changes, snow albedo changes were assessed, especially in relation to snow onset and melt variability.The results of the trend analysis carried with Man-Kendall statistics indicate that around 78% of the global mountain areas present a snow decline. In average, snow cover duration has decreased up to 43 days, and a snow cover area up to 13%. Significant snow cover duration changes can be linked in 58% of the areas to both delayed snow onset, and advanced melt. Few areas show positive changes, mainly during winter time and located in the Northern Hemisphere.Considering the relationship with meteorological parameters and albedo, air temperature is detected as the main driver for snow onset and melt, while a mixed effect of air temperature and precipitation dominates the winter season. Moreover, snowmelt timing is strongly related to significant changes in snow albedo during March and April in the Northern Hemisphere. Regarding snow onset changes, it has been detected a latitude amplification for the dependency con air temperature, indicating that the sensitivity of snow onset on temperature changes is amplified going from higher to lower latitude.&#160;References[1] Barnett, T.P., Adam J.C., Lettenmaier D.P. Potential impact of a warming climate on water availability in snow-dominated regions, Nature 438 (2005).[2] Bormann, K. J., Brown, R. D., Derksen, C., Painter, T. H. Estimating snow-cover trends from space, Nat. Clim. Change&#160;8,&#160;924&#8211;928 (2018).[3] Ye. K. H., & Wu, R. G. Autumn snow cover variability over northern Eurasia and roles of atmospheric circulation. Adv. Atmos. Sci. 34(7), 847&#8211;858 (2017) doi: 10.1007/s00376-017-6287-z.

Download Full-text

New categories for the climatic division of snowy areas in Japan

Annals of Glaciology ◽

10.3189/1998aog26-1-131-137 ◽

1998 ◽

Vol 26 ◽

pp. 131-137 ◽

Cited By ~ 3

Author(s):

Masaaki Ishizaka

Keyword(s):

Temperature Gradient ◽

Snow Cover ◽

Air Temperature ◽

Snow Depth ◽

Winter Season ◽

Critical Values ◽

Absolute Value ◽

Mean Temperature ◽

Wet Snow ◽

The Absolute

New categories for the climatic division of snowy areas according to their snow-cover character in mid-winter are proposed. They are a wet-snow region, a dry-snow region, an intermediate snow region and a depth-hoar region. The wet-snow region is defined as the region in which every layer of deposited snow is wet due to percolation of snowmelt water throughout the winter. In contrast, areas in which the snow cover is dry, at least in the coldest period of the winter season, are classified into two categories, that is the dry-snow region and the depth-hoar region. In the latter region, the small snow depth and low air temperature induce development of depth hoar. The intermediate snow region was introduced to indicate an intermediate character between the dry-snow and wet-snow regions. From the climatic dataset calculated by the Japanese Meteorological Agency and from snow surveys, it has been found that in snowy areas, which have a climatic monthly mean temperature in January (Tjan) higher than 0.3°C, snow would be expected to be wet throughout the winter and, in areas that have Tjan, lower than −1.1°C, to be dry at least in the coldest period. Snow covers, where Tjan is between these two values, are expected to have intermediate characters. Therefore, these temperatures are supposed to be critical values among the wet, dry and intermediate snow regions. The criterion that separates the depth-hoar region from the dry-snow areas was found to be given by a climatic mean temperature gradient. This value lies between 10 and 12°Cm−1, which is derived by dividing the absolute value of the average of the climatic monthly mean air temperature, which is always below 0°C, by the average of the monthly maximum snow depth during January and February.

Download Full-text

New categories for the climatic division of snowy areas in Japan

Annals of Glaciology ◽

10.1017/s0260305500014695 ◽

1998 ◽

Vol 26 ◽

pp. 131-137 ◽

Cited By ~ 4

Author(s):

Masaaki Ishizaka

Keyword(s):

Temperature Gradient ◽

Snow Cover ◽

Air Temperature ◽

Snow Depth ◽

Winter Season ◽

Critical Values ◽

Absolute Value ◽

Mean Temperature ◽

Wet Snow ◽

The Absolute

New categories for the climatic division of snowy areas according to their snow-cover character in mid-winter are proposed. They are a wet-snow region, a dry-snow region, an intermediate snow region and a depth-hoar region. The wet-snow region is defined as the region in which every layer of deposited snow is wet due to percolation of snowmelt water throughout the winter. In contrast, areas in which the snow cover is dry, at least in the coldest period of the winter season, are classified into two categories, that is the dry-snow region and the depth-hoar region. In the latter region, the small snow depth and low air temperature induce development of depth hoar. The intermediate snow region was introduced to indicate an intermediate character between the dry-snow and wet-snow regions. From the climatic dataset calculated by the Japanese Meteorological Agency and from snow surveys, it has been found that in snowy areas, which have a climatic monthly mean temperature in January (Tjan ) higher than 0.3°C, snow would be expected to be wet throughout the winter and, in areas that have Tjan, lower than −1.1°C, to be dry at least in the coldest period. Snow covers, where Tjan is between these two values, are expected to have intermediate characters. Therefore, these temperatures are supposed to be critical values among the wet, dry and intermediate snow regions. The criterion that separates the depth-hoar region from the dry-snow areas was found to be given by a climatic mean temperature gradient. This value lies between 10 and 12°Cm−1, which is derived by dividing the absolute value of the average of the climatic monthly mean air temperature, which is always below 0°C, by the average of the monthly maximum snow depth during January and February.

Download Full-text

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

10.5194/esd-2017-24 ◽

2017 ◽

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 trends and regime shifts during 1951–2015. Trend analysis is performed 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 12 observed stations by 0.3–0.4 K per decade. 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 per decade. 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. Time series of specific runoff measured at 21 stations has had significant seasonal changes during the study period. Winter values have increased by 0.4–0.9 l/s per km2 per decade while stronger changes are typical for western Estonia and weaker changes for eastern Estonia. At the same time, specific runoff in April and May has notably decreased indicating the shift of the runoff maximum to earlier time, i.e. from April to March. All meteorological and hydrological variables 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 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 the annual specific runoff correspond to the alternation of wet and dry periods. A dry period started since 1964 or 1963, a wet period since 1978 and the next dry period since the beginning of the 21st century.

Download Full-text