scholarly journals Snowfall and snow cover evolution in the Eastern Pre-Pyrenees (NE Iberian Peninsula)

2021 ◽  
Author(s):  
J. Bonsoms ◽  
F. Salvador-Franch ◽  
M. Oliva
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Winter Season ◽  
Teleconnection Pattern ◽  
Data Series ◽  
Weather Types ◽  
The North ◽  
Spatio Temporal ◽  
Snow Cover Duration ◽  
Snow Precipitation

Snow cover has significant impacts on geoecological dynamics as well as on socio-economical systems. An accurate quantification of snow precipitation patterns in mountain regions is needed to better understand the spatio-temporal implications of snow cover. The objective of this work is to characterize the patterns of solid precipitation and snow cover in two high Mediterranean massifs. To this purpose, we analyse instrumental data series of snowfall and snow depth of Port del Comte (2316 m a.s.l.) and Cadí-Nord (2134 m). Both stations are situated in the eastern Pre-Pyrenees and include 14 consecutive snow seasons from November to May, allowing to (i) explore the dependence of the main drivers of snowpack: temperature and snowfall; (ii) find out the most frequent circulation weather types associated with high intensity snowfall events, and finally (iii) investigate the role of the North Atlantic Oceanic (NAO) teleconnection pattern explaining snow cover evolution during the winter season. Data show that snowfall is controlled by similar weather types in both stations that resulted in similar snowfall averages: 205 cm and 258 cm at Port del Comte and Cadí-Nord, respectively. Nevertheless, local factors interfere with the amount of snow depth recorded, which is moderately different between stations. Whereas Cadí-Nord records a seasonal mean of 66 cm, Port del Comte records a smaller quantity of 25 cm with a high interannual and seasonal variability. In fact, snowfall recurrence, snow amount or duration in the ground is considerably variable among years (CV20). In these stations, snow cover duration is determined by the precipitation in the form of snow falling during the previous months. Snowfalls in moderate to severe episodes (15 cm in 24 h) are mainly driven by Atlantic flows, mostly from NW. In addition, NAO pattern is negatively correlated with snowfall in November and December months (R-0.50), showing a weaker and not statistically significant correlation during the rest of the winter season.

scholarly journals Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China

2016 ◽  
Vol 10 (5) ◽  
pp. 2453-2463 ◽  
Author(s):  
Xiaodong Huang ◽  
Jie Deng ◽  
Xiaofang Ma ◽  
Yunlong Wang ◽  
Qisheng Feng ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Snow Depth ◽  
Winter Season ◽  
Remote Sensing Data ◽  
Microwave Remote Sensing ◽  
The Tibetan Plateau ◽  
Optical Remote Sensing ◽  
The North ◽  
The Mean

Abstract. By combining optical remote sensing snow cover products with passive microwave remote sensing snow depth (SD) data, we produced a MODIS (Moderate Resolution Imaging Spectroradiometer) cloudless binary snow cover product and a 500 m snow depth product. The temporal and spatial variations of snow cover from December 2000 to November 2014 in China were analyzed. The results indicate that, over the past 14 years, (1) the mean snow-covered area (SCA) in China was 11.3 % annually and 27 % in the winter season, with the mean SCA decreasing in summer and winter seasons, increasing in spring and fall seasons, and not much change annually; (2) the snow-covered days (SCDs) showed an increase in winter, spring, and fall, and annually, whereas they showed a decrease in summer; (3) the average SD decreased in winter, summer, and fall, while it increased in spring and annually; (4) the spatial distributions of SD and SCD were highly correlated seasonally and annually; and (5) the regional differences in the variation of snow cover in China were significant. Overall, the SCD and SD increased significantly in south and northeast China, and decreased significantly in the north of Xinjiang province. The SCD and SD increased on the southwest edge and in the southeast part of the Tibetan Plateau, whereas it decreased in the north and northwest regions.

scholarly journals Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 307
Author(s):  
Chi Zhang ◽  
Naixia Mou ◽  
Jiqiang Niu ◽  
Lingxian Zhang ◽  
Feng Liu
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Feedback Effect ◽  
Effect Of Temperature ◽  
The Tibetan Plateau ◽  
Reanalysis Dataset ◽  
Spatio Temporal ◽  
The Impact ◽  
Main Factor

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade−1, p = 0.81) and SCD (s = −2.3 d decade−1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.

scholarly journals Changes in Snow Storage in the Upper Hron River Basin (Slovakia)

2014 ◽  
Vol 10 (2) ◽  
pp. 145-160
Author(s):  
Katarína Kotríková ◽  
Kamila Hlavčová ◽  
Róbert Fencík
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Satellite Images ◽  
Snow Water Equivalent ◽  
Winter Season ◽  
Kendall Test ◽  
Measured Data ◽  
Time Step ◽  
Snow Storage ◽  
Snow Water

Abstract An evaluation of changes in the snow cover in mountainous basins in Slovakia and a validation of MODIS satellite images are provided in this paper. An analysis of the changes in snow cover was given by evaluating changes in the snow depth, the duration of the snow cover, and the simulated snow water equivalent in a daily time step using a conceptual hydrological rainfall-runoff model with lumped parameters. These values were compared with the available measured data at climate stations. The changes in the snow cover and the simulated snow water equivalent were estimated by trend analysis; its significance was tested using the Mann-Kendall test. Also, the satellite images were compared with the available measured data. From the results, it is possible to see a decrease in the snow depth and the snow water equivalent from 1961-2010 in all the months of the winter season, and significant decreasing trends were indicated in the months of December, January and February

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 Reanalysis of 47 Years of Climate in the French Alps (1958–2005): Climatology and Trends for Snow Cover

2009 ◽  
Vol 48 (12) ◽  
pp. 2487-2512 ◽  
Author(s):  
Yves Durand ◽  
Gérald Giraud ◽  
Martin Laternser ◽  
Pierre Etchevers ◽  
Laurent Mérindol ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Depth ◽  
Numerical Models ◽  
High Elevation ◽  
Climatic Conditions ◽  
Spatial And Temporal Variability ◽  
The South ◽  
French Alps ◽  
Mountainous Regions ◽  
The North

Abstract Since the early 1990s, Météo-France has used an automatic system combining three numerical models to simulate meteorological parameters, snow cover stratigraphy, and avalanche risk at various altitudes, aspects, and slopes for a number of mountainous regions (massifs) in the French Alps and the Pyrenees. This Système d’Analyse Fournissant des Renseignements Atmosphériques à la Neige (SAFRAN)–Crocus–Modèle Expert de Prévision du Risque d’Avalanche (MEPRA) model chain (SCM), usually applied to operational daily avalanche forecasting, is here used for retrospective snow and climate analysis. For this study, the SCM chain used both meteorological observations and guess fields mainly issued from the newly reanalyzed atmospheric model 40-yr ECMWF Re-Analysis (ERA-40) data and ran on an hourly basis over a period starting in the winter of 1958/59 until recent past winters. Snow observations were finally used for validation, and the results presented here concern only the main climatic features of the alpine modeled snowfields at different spatial and temporal scales. The main results obtained confirm the very significant spatial and temporal variability of the modeled snowfields with regard to certain key parameters such as those describing ground coverage or snow depth. Snow patterns in the French Alps are characterized by a marked declining gradient from the northwestern foothills to the southeastern interior regions. This applies mainly to both depths and durations, which exhibit a maximal latitudinal variation at 1500 m of about 60 days, decreasing strongly with the altitude. Enhanced at low elevations, snow depth shows a mainly negative temporal variation over the study period, especially in the north and during late winters, while the south exhibits more smoothed features. The number of days with snow on the ground shows also a significant general signal of decrease at low and midelevation, but this signal is weaker in the south than in the north and less visible at high elevation. Even if a statistically significant test cannot be performed for all elevations and areas, the temporal decrease is present in all the studied quantities. Concerning snow duration, this general decrease can also be interpreted as a sharp variation of the mean values at the end of the 1980s, inducing a step effect in its time series rather than a constant negative temporal trend. The results have also been interpreted in terms of potential for a viable ski industry, especially in the southern areas, and for different changing climatic conditions. Presently, French downhill ski resorts are economically viable from a range of about 1200 m MSL in the northern foothills to 2000 m in the south, but future prospects are uncertain. In addition, no clear and direct relationship between the North Atlantic Oscillation (NAO) or the ENSO indexes and the studied snow parameters could be established in this study.

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

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

<p>This study analyses regional differences in annual snow cover duration as quantified by the annual number of days with snow cover (D<sub>sc</sub>) and investigates differences in sensitivity of D<sub>sc</sub> to climatic variability across the Greater Alpine Region over the 2000-2018 period. MODIS snow cover data were used to estimate D<sub>sc</sub> based on the Regional Snowline Elevation (RSLE) method, a spatial filter technique for large-scale cloud cover reduction.</p><p>D<sub>sc</sub> over the study period closely follows the relief, with a mean D<sub>sc</sub> of ~10–60 days at elevations of 500 m that increase to about 100–150 days at 1500m. South of the main alpine ridge, D<sub>sc</sub> is, at the same elevation, consistently lower than north of it with differences of ΔD<sub>sc</sub>  ~25–50 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 ΔD<sub>sc</sub> ~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 (∆D<sub>start</sub> ~14–30 d) and earlier melt-out at the end of the snow season (∆D<sub>end</sub> ~10–20 d), translates into reductions of the annual number of snow-covered days by up to ΔD<sub>sc</sub> = -46 days over the study period. The data suggest that, in particular, low-elevation  (< 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 D<sub>sc</sub>., whereas ΔD<sub>sc</sub> remained very limited south of the main Alpine ridge. The spatially integrated MODIS-derived estimates of D<sub>sc</sub> correspond well with D<sub>sc</sub> 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 D<sub>sc</sub> over the 2000-2018 study period also reflects the longer-term D<sub>sc</sub> trends as estimated from these point-scale observations (1970-2014). This provides supporting evidence that the widespread decline of D<sub>sc</sub> 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 D<sub>sc</sub> to climatic variability indicates that neither mean winter temperatures T<sub>w</sub> nor annual solid precipitation totals P<sub>s</sub>, are consistent first order controls on D<sub>sc</sub> across  elevations and regions. Rather, the data highlight the importance of the interaction between the two variables: depending on the respective sensitivities of D<sub>sc</sub> to changes in either variable, T<sub>w</sub> or P<sub>s</sub>, respectively, the interplay between them can reinforce or largely off-set potential effects on D<sub>sc</sub> in different regions in the Greater Alpine Region. The regional differences in ΔD<sub>sc</sub> with a less pronounced decline south of the main Alpine ridge are largely a consequence of this interplay: while T<sub>w</sub> evolved similarly North and South of the Alpine ridge, many southern regions, unlike the northern regions, experienced an increase in P<sub>s</sub> that offsets the effects of positive temperature trends.</p>

scholarly journals Processes governing snow ablation in alpine terrain – detailed measurements from the Canadian Rockies

2020 ◽  
Vol 24 (1) ◽  
pp. 143-157 ◽  
Author(s):  
Michael Schirmer ◽  
John W. Pomeroy
Keyword(s):  
High Resolution ◽  
Snow Cover ◽  
Spatial Correlation ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Initial Distribution ◽  
Aerial Photographs ◽  
Slope Aspect ◽  
Spatial Correlations ◽  
The North

Abstract. The spatial distribution of snow water equivalent (SWE) and melt are important for estimating areal melt rates and snow-cover depletion (SCD) dynamics but are rarely measured in detail during the late ablation period. This study contributes results from high-resolution observations made using large numbers of sequential aerial photographs taken from an unmanned aerial vehicle on an alpine ridge in the Fortress Mountain Snow Laboratory in the Canadian Rocky Mountains from May to July in 2015. Using structure-from-motion and thresholding techniques, spatial maps of snow depth, snow cover and differences in snow depth (dHS) during ablation were generated in very high resolution as proxies for spatial SWE, spatial ablation rates and SCD. The results indicate that the initial distribution of snow depth was highly variable due to overwinter snow redistribution; thus, the subsequent distribution of dHS was also variable due to albedo, slope/aspect and other unaccountable differences. However, the initial distribution of snow depth was 5 times more variable than that of the subsequent dHS values, which varied by a factor of 2 between the north and south aspects. dHS patterns were somewhat spatially persistent over time but had an insubstantial impact on SCD curves, which were overwhelmingly governed by the initial distribution of snow depth. The reason for this is that only a weak spatial correlation developed between the initial snow depth and dHS. Previous research has shown that spatial correlations between SWE and ablation rates can strongly influence SCD curves. Reasons for the lack of a correlation in this study area were analysed and a generalisation to other regions was discussed. The following questions were posed: what is needed for a large spatial correlation between initial snow depth and dHS? When should snow depth and dHS be taken into account to correctly model SCD? The findings of this study suggest that hydrological and atmospheric models need to incorporate realistic distributions of SWE, melt energy and cold content; therefore, they must account for realistic correlations (i.e. not too large or too small) between SWE and melt in order to accurately model SCD.

scholarly journals Short-period variability in snow cover duration in the north of Eurasia in modern climate conditions from MODIS data

2017 ◽  
Vol 14 (5) ◽  
pp. 223-238
Author(s):  
T.B. Titkova ◽  
◽  
L.M. Kitaev ◽  
V.V. Vinogradova ◽  
◽  
...  
Keyword(s):  
Snow Cover ◽  
Climate Conditions ◽  
Modis Data ◽  
Period Variability ◽  
The North ◽  
Short Period ◽  
Snow Cover Duration

scholarly journals Impact of Eurasian autumn snow on the winter North Atlantic Oscillation in seasonal forecasts of the 20<sup>th</sup> century

2021 ◽  
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann
Keyword(s):  
North Atlantic Oscillation ◽  
Snow Cover ◽  
North Atlantic ◽  
Climate Model ◽  
Winter Season ◽  
Reanalysis Data ◽  
Causal Connection ◽  
Seasonal Forecasts ◽  
The North ◽  
The North Atlantic Oscillation

Abstract. As the leading climate mode of wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Eurasian cryosphere as a possible predictor for the wintertime NAO. However, missing correlation between snow cover and wintertime NAO in climate model experiments and strong non-stationarity of this link in reanalysis data is questioning the causality of this relationship. Here we use the large ensemble of Atmospheric Seasonal Forecasts of the 20th Century (ASF-20C) with the European Centre for Medium-Range Weather Forecasts model, focusing on the winter season. Besides the main 110-year ensemble of 51 members, we investigate a second, perturbed ensemble of 21 members where initial (November) land conditions over the Northern Hemisphere are swapped from neighboring years. The Eurasian snow/NAO linkage is examined in terms of a longitudinal snow depth dipole across Eurasia. Subsampling the perturbed forecast ensemble and contrasting members with high and low initial snow dipole conditions, we found that their composite difference indicates more negative NAO states in the following winter (DJF) after positive west to east snow cover gradients at the beginning of November. Surface and atmospheric forecast anomalies through the troposphere and stratosphere associated with the anomalous positive snow dipole consist of colder early winter surface temperatures over Eastern Eurasia, an enhanced Ural ridge and increased vertical energy fluxes into the stratosphere, with a subsequent negative NAO-like signature in the troposphere. We thus confirm the existence of a causal connection between autumn snow patterns and subsequent winter circulation in the ASF-20C forecasting system.

scholarly journals New categories for the climatic division of snowy areas in Japan

1998 ◽  
Vol 26 ◽  
pp. 131-137 ◽  
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.

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