Climate change impacts on NATURAL SYSTEMS AND PATTERNS 2.2 SNOW COVER |
Type of knowledge |
Results and interpretation |
Observation and analysis methods |
References |
| Reconstructions | Swiss Alps: During the Holocene, a period following the short cold event of the recent Dryas (since 10 000 BP), is the end of the rapid glacier retreat in thePre Alpine valleys end and the beginning of the actual climate. During the Preboreal period, the lower limit of snow occurrence (altitude limit above which the winter snow cover on a plane surface does not melt during summer) rise from 2000m a.s.l to 2600 a.s.l. The beginning of the recent Atlantic (since 6000 BP) is associated with a temperature rise, inducing a 200m rise in altitude of the upper limit of the forest and of the lower limit of the snow cover. |
Lateltin & al. 1997 - R: PNR31 | |
Italian Alps - Northern Apenines: |
Bibliographic synthesis | Pellegrini & al 1998 in Bertolini & al 2004 - A | |
|
Observations |
Swiss
Alps (low altitude): Reduction of snow cover by 3-4 weeks during the late 80’s and the early 90’s. |
Reduction
in the duration of snow cover documented in the low altitude zones of
the Swiss Alps Using satellite imagery. |
Baumgartner & Apfl 1994 in Bravard 2006 - P |
Swiss
Alps: Beniston (1997) has correlated thick snow cover and long duration in the Swiss Alps with high NAO index because during these episodes, winter temperatures shift toward higher values (« the frequency of temperatures exceeding the freezing point is more than doubled above 1000 m, thus enhancing the potential for early snowmelt »). |
Beniston, 1997 in Bravard 2006 - P | ||
| Eastern
Switzerland:
The snow depth shows a great short-term variability and a marked long-term fluctuation. The low values from 1925-1934 are obvious. This period is not correlated with high winter temperatures, in contrast to the low values around 1990. The snow coverage (number of days with more than 20cm of snow) shows a similar pattern to the snow depth. The variability is rather small at the beginning of the century and increases afterwards. |
The winter climate was primarily investigated at Davos. A 96 year continuous time series is available. |
Schneebeli & al. 1997 - A | |
Swiss Alps: No significant statistical trend or periodicity for the parameters analysed during the 20th century. No marked change in the distribution of extreme snowfall events. |
Day by day parameter (temperature, precipitations, cloud cover, wind direction and force, new snow (snow falling for 3 days), height and duration of snow cover) for three meteorological stations: Davos; Bever and Andermatt. |
Bader & Kunz 2000a - R : PNR31 | |
Bernese Alps: Snow depth and duration have decreased since the beginning of the century. Years without any snow or only small snow depth have not yet been recorded at elevations as high as 2000 m above sea level, although this has been observed at low to medium elevations (< 1,200 m) in the late 1980s and early 1990s (Beniston, 1997). |
Keller & al 2000 - A | ||
Chartreuse massif (French Alps): |
Etchevers & Martin 2002 - P | ||
| Swiss
Alps: The greatest snow abundance occurs for cold / moist winters in the both observed sites of Chateau d'Oex ad Arosa, while the least abundance is associated with warm winter in Arosa. Warm and moist winter at medium elevation is associated with the fall of precipitation in the form of rain rather than snow. Hence the extent of the winter snow pack is rapidly reduced. At higher elevation, warm/moist winters lead to greater snow accumulaton. At higher elevations, on the other hand, the warm-moist winter mode leads to greater total snow accumulation than the warm-dry mode, but does not offset the negative influence of the higher temperatures compared to cold winters. It can also be seen that the duration of the snow season is strongly modulated by the various combinations of temperature and precipitation, the longest being related to the cold-moist winter mode, the shortest to the warm modes (dry at high elevations and moist at low elevations). The longest duration of the snow season is related to the cold/moist winter mode, the shortest to the warm modes (dry at high elevation and moist at low elevation). There is a non-linear increase in seasonal snow accumulation for a linear increase in snow duration. For example, in the case of wetter-than-average winters, an increase in snow duration by 60 days, from 30 to 90 days is accompanied on average by a rise in snow accumulation of 225 cm, from 50 to 275 cm. The same increase of 60 days, but from 240 to 300 days, results in an average additional accumulation of 315 cm, from 960 to 1275 cm. |
Field observation from 18 meteorological stations representative of Swiss climate. These stations have altitudinal range from 317m asl to 2500m asl and with data covering the 1931-2000 period. Calcul of the correlation coefficients between the DJF Average Minimum Temperature and the Sesonal Snow Accumulation (r = 0.85 and r = 0.72). The data for wetter-than-average and drier-than-average winters have been disaggregated. Calcul of the corelation coefficient for the regression lines (r = 0.96). |
Beniston & al. 2003a - A | |
Swiss
Alps: At the low elevation site of Château d'Oex, the snow depth is reduced by 45% between the 1960s and the 1990s. But there is a high interannual variability, e.g. the duration ranged from 10 days during the 1961-1962 winter to 110 days the next winter. During the same time interval, the Davos site experienced a loss of 12% of the snow depth (reduction of average total accumulation from 330cm to 288cm). These trends are inversed at the high elevation site of Säntis with an enhancement of snow depth of 35% (increase from 1590 cm for the 1960's to 2475 cm for the 1990s). On the overall, the length of the snow season tended to decrease at most location since the early 1970's. Since the mid 1980's and up till today, the lenght of the snow season and the snow amount at Arosa, based on a 20 cm treshold, have been reduced by 2-3 weeks as a result of unusually high and persistent pressure over the Alps. This shift remains within the ± 2 weeks (duration occurs between end of November toward mid-May). The situation of today is similar to the situation in the early 1930's. There is a strong linear relation between snow duration and snow height for the 18 stations studied (r = 0.97). Large scale forcing, rather than just local or regional factors, plays a dominant role in controling the timing and amount of snow in the Alps. |
Beniston & al. 2003b - A | ||
Swiss Alps: Average snow depth Looking at the relative deviation of the 10-year mean of HS compared with the long-term mean, it can be assumed that the 1930s had generally below-average snow (except in the south) and the 1940s had above-average snow at lower altitudes, whereas the higher altitudes show slightly negative deviations from the long-term mean. After the 1950s, with mostly below-average snow, three decades with plenty of snow follow, and the last decade, the 1990s, is, throughout, clearly below average. During the 1990s, when stations at low levels had clearly below-average snow and the higher the stations were, the more they approached average conditions. Rather the opposite is the case during the snowy 1960s, 1970s and 1980s, with low areas showing slight tendencies to higher relative values than high-altitude stations. It is striking that five winters of the last decade (1990-99) are within the 11 least snowy winters of the past 69 years, and 1989 also belongs to this group. Looking at the annual relative deviation from the long-term mean, averaged over all stations, very typical are the large year-to-year variations. In more than 60% of all cases the direction towards increasing or decreasing snow changes from year to year. Clusters of successive years with above-average snow can be found in the late 1960s and with short interruptions from the late 1970s till the mid 1980s. Accumulations of years with below-average snow are recorded in the late 1940s, late 1950s till early 1960s, early 1970s and from the late 1980s through most of the 1990s. Whereas R1-R3 and R5 behave very similarly, R4 and R7 have some distinctive deviations, and R6 has its own line completely. In addition to regional variations, trends are not uniformly distributed with altitude. Since the 1930s, for the entire Swiss Alps and the whole winter period, high elevations (> 1600 m a.s.l.) show a very slight increase culminating in the early 1960s, followed by a 20-year period remaining on this high level and then a gradual decrease towards the end of the century ending somewhat below the initial start-up level. On the other hand, low elevations (< 1000 m a.s.l.) show much more variability: a very snowy period during the 1940s is followed by the lean 1950s, then again the snowy 1960s, about average 1970s and after a final climax in the early 1980s a marked drop towards unprecedented low values during the 1990s. Duration of continuous snow cover Time series of the duration of snow cover (d0) reveal large variability for different stations, regions and altitudes. The general pattern for d0 is that high stations (> 1600 m a.s.l.) and low stations (< 1000 m a.s.l.) are fairly constant over the last 70 years, whereas at mid altitudes (about 1000-1600 m a.s.l.) a strong increase culminating in the early 1980s was followed by a marked decrease towards the end of the century. This is found for absolute values; looking at relative deviations from the long-term mean reveals a slightly different picture. As for the HS winter mean, the decreasing trend since the early 1980s gets more pronounced from high- to low-altitude stations and looks near identical. At low elevations, small and hardly visible absolute trends obviously turn into large and noticeable relative changes. Altogether, b0 is fairly constant over the last 70 years. On the other hand, e0 shows a clearer trend towards earlier snow melting during the 1980s and 1990s. This implies that the generally shorter duration of snow cover is mainly caused by earlier snow melting than later first snowfalls. |
A maximum number of consistent long-term snow series was selected all over the Swiss Alps, divided into seven snow climatological regions (R1-R7) and including the adjacent forelands. R1-R3: North Slope, R4 and R7: the interior areas of the Alps, R5: Grisons and R6: South Slope. The analyses are based on daily, manually measured snow depth (HS) and new snow (HN) data from the observational networks. Only consistent long-term (> 25 years) stations within the period of 1931-99 were considered. This results in a total of 140 HS stations and 120 HN stations. The mean seasonal snow depth from 1 November to 30 April is analysed. Apart from the whole winter, two-monthly part seasons have been studied. Duration (d0), beginning (b0) and final dates (e0) of snow cover are examined. Only the time period during which the ground was continuously covered with snow (HS > 0 cm) is considered. The same parameters are also determined for higher HS thresholds greater than 20, 30, 50 and 70 cm (d20-d70, b20-b70, e20-e70). Trends on daily new snowfall are analysed for long-term changes. The seasonal sum of daily HN correlates (r = 0.88) with the mean seasonal snow depth and thus shows very similar trends to the HS mean. Therefore, the HN sum is not discussed further here. |
Laternser & Schneebeli 2003 - A | |
Switzerland:
Under 1300m a.s.l, the snow cover duration decreased significantly. |
Scherrer & al. 2004 in Frei & Widmer 2007 - E | ||
| French and Swiss
Alps: If the solid precipitations are quite stable, it is important to note that the snow cover changed a lot at low and mid elevation sites (roughly under 1800m) whereas for the high elevation sites, no trend has been detected. At the Météo France experimental site of "Col de Porte" (1360m) in the Chartreuse massif, measurements clearly show a decrease of both height and duration of the snow cover: between 1960 and 2004, the mean height decreased regularly from 116 cm to 54 cm. |
Météo-France data for the "Col de Porte". | Ancey 2005 - E | |
Swiss
Alps: The amount and duration of snow cover on the alpine foreland have significantly reduced in the last quarter of the 20th century compared to previous decades (reduction of the ground snow cover from 43 to 22 days per winter in Bern, 15 to 3 days per winter in Lugano between the 1960s and the 1990s). |
Beniston 2005a - A | ||
Southern
Germany: The winter cover allows conclusions to be drawn about changes in the characteristics of winter periods. The trend towards winters with less snowfall with less lasting snow cover is definitely apparent. Up to moderate altitudes the durations decrease markedly in general. In the observed period, however, some regional distinctive features can be seen. In the eastern part of the Alps and the Bavarian Forest the decrease in the lower altitudes is from 20 % to 30 %. This trend weakens with increasing altitude and reverses (positive trend) on higher ground. In the Upper-Rhine plain and the western declivity of the Black Forest the duration of snow cover decreases approx. 50 % and more on lower ground and decreases at moderate altitudes to 10 to 20%. In the higher regions mean values under 10 % are observed. Here, too, the trend weakens with increasing altitude. However, only in isolated cases are values observed where the trend is reversed. At lower and moderate altitudes the number of days with snow cover has decreased markedly: • approx. 30 – 50% in lower regions (< approx. 300 m above sea level), • approx. 10 – 20% at moderate altitudes (between 300 and 800 m above sea level), • less than 10% on high ground, or in some cases even increasing at higher altitudes (> approx. 800 m above sea level). |
The parameters snow cover period, snow cover time, longest snow cover period (winter cover), start of the maximum snow cover height, constancy of snow cover, conservation of winter cover and maximum water equivalent values are best suited to describe the snow cover conditions and the water reserves stored in the snow cover. All the snow cover parameters mentioned correlate strictly with the elevation of the ground. Study period: 1951/52 - 1995/96 [Framework: KLIWA Project] |
Hennegriff & al 2006 - A | |
Alps: Since 1950, the snow fall limit rise more than 100m in altitude. |
Seiler 2006 - P* | ||
Northern
Italy: In 2003-2006 period, winter snow accumulation was 40 % below normal conditions (1959-2002 mean values) at Lago Valsoera weather station (2440 m, Gran Paradiso range). |
Cat-Berro & Mercalli 2007 - P | ||
Switzerland: Currently in Einsiedeln (PreAlps, 882 m a.s.l.), the number of days with snow per winter half of the year is reduced by 20 days compare to 50 years ago. Since the mid-1950s, the number of days with snow decreased in numerous low elevation ski resorts (below 1200 or 1300 m a.s.l.). On the other hand, no unambiguous trend has been detected for resorts located over 1500 or 1600 m . In low elevation resorts, the sums of fresh snow heights also tend to decrease, as at Gsteig (Bernese Oberland). In Mürren, a resort located in the same area but at higher elevation, the sums of fresh snow heights rather increased. In addition to the rise of the snowfall limit, one can also observe a shift in time of snowfalls, which occur later during winter. In Mürren, for example, since 1954 one can observe a progressive decrease of the snow cover thickness at Christmas. |
Bibliographic review | North & al. 2007 - R: OFEV | |
World: Data from satellite monitoring from 1966 to 2005 show that mean monthly snow-cover extent in the Northern Hemisphere is decreasing at a rate of 1.3 per cent per decade. For the calendar year of 2006 average snow-cover extent was 24.9 million km2, which is 0.6 million km2 less than the 37-year average. In the Northern Hemisphere, spring and summer show the strongest decreases in snow-cover extent. Satellite observations of snow-cover extent show a decreasing trend in the Northern Hemisphere for every month except November and December, with the most significant decreasing trends during May to August (Brodzik et al., 2006). The average Northern Hemisphere snow-cover extent for March and April decreased by 7.5 ± 3.5 % from 1922-2005 (Lemke et al., 2007). |
Bibliographic review | UNEP 2007 - R | |
Swiss Alps: For new snow sums and snow depths 3 well separated patterns of variability were identified. The first (uniform) pattern explains >50% of total variance and the spatial pattern is almost uniform over the entire Swiss area with exception of the southern Alps, where the loading is small. The second (north–south) pattern (explaining ~15% of total variance) shows a north–south dipole with positive (negative) loadings on the northern (southern) slopes of the Alps. The third (low–high) pattern (explaining ~9% of total variance) shows positive loadings at low altitude stations, negative loadings at high altitude stations and a weak, decreasing trend. New snow sum anomalies of the leading pattern are primarily related to seasonal precipitation anomalies. Snow day sum leading pattern anomalies on the other hand are primarily related to seasonal temperature anomalies and only weakly to precipitation anomalies, as melt processes are almost linearly related to seasonal temperature (e.g. Ohmura 2001). New snow sums are only influenced by processes during snow accumulation (i.e. during snowfall events). Evidently these can be described reasonably by seasonal precipitation sums. On the other hand, the leading snow day variability is influenced by processes that control snow accumulation and ablation, which are highly related to seasonal temperature. The north–south snow pattern, which explains most of snow variability in southern Switzerland, correlates excellently with southern Alpine precipitation. The low–high snow pattern correlates well with local temperature. Also the large-scale flow explains substantial amounts of variance in the Swiss Alpine snow pattern data. The leading pattern of snow variability is primarily linked with a low (high) pressure anomaly pattern centred over central and southeastern Europe. It bears some resemblance to the third pattern of European sea level pressure variability (BLO) often referred to as Euro-Atlantic blocking (D'Andrea et al. 1998, Scherrer et al. 2006). The second (north–south) snow pattern is mainly influenced by the East Atlantic anomaly pattern. Only the low–high snow pattern variability, which explains substantial amounts of interannual snow variance at low-lying stations, is primarily linked with the interannual variability of the NAO. The authors find several indications that this low–high pattern could be related to ongoing climate change. It shows no similarity with known precipitation patterns, is strongly linked with the increase of the 0°C isotherm, exhibits a negative trend, and its correlation with NAO decreases from near zero to a highly significant negative value towards the end of the 20th century. |
Quality-checked December–January–February (DJF) data from Alpine and close foreland stations in the period from 1958–1999 were considered. Three seasonal snow variables were computed from daily data: averaged snow depths, cumulated new snow sums and the number of snow days (days with snow depth = 5 cm). In total 89 new snow sum and 110 snow depth stations were used in the analysis. The station altitudes range from 275 to 2540 m a.s.l. with the highest station density between 1250 and 1750 m a.s.l. For most snow measurement sites local temperature and precipitation values are not available. In these cases seasonal mean temperature and precipitation values were linearly interpolated to the snow station coordinates and altitudes (Scherrer et al. 2004, Begert et al. 2005). Mean sea level pressure data from the ECMWF reanalysis project ERA-40 dataset (Uppala et al. 2005) was used to determine patterns of largescale flow. Unrotated Principle Component Analysis (PCA) (Preisendorfer 1988) was applied to determine the major patterns of seasonal mean snow variability. The resulting spatial loadings are called Empirical Orthogonal Functions (EOFs) hereafter. The temporal scores are principal components (PCs) below. PCA was also conducted to determine the major patterns of the local temperature and precipitation at the snow stations and large-scale flow variability (sea level pressure) in the Euro-Atlantic sector. Standard statistical techniques such as Pearson correlation analysis and stepwise multiple linear models were used to relate local variables such as snow, temperature and precipitation with Euro-Atlantic scale flow fields (Junge & Stephenson 2003). Significance levels were determined using a Monte-Carlo approach of first order auto-regressive (AR1) processes to mimic the redness of the processes investigated. |
Scherrer & Appenzeller 2006 - A | |
Alps: Numerous studies have been carried out in the Alps and a lot of them are coherent. A strong decrease of snow cover has been observed during the second half of the 20th century and is explained by the concomitant increase of air temperature (generally, there is no precipitation trend). This decrease is obvious for medium altitude, but less evident for high altitude (where measurements are also less usual). |
Etchevers 2007 - C1 | ||
|
Modeling |
Swiss
Alps: An average increase of 4°C in temperatures, forecasted by several regional models for this area of Europe, would reduce the volume of snow by 50% in the Swiss Alps. For every 1°C increase in temperature, the snow line will rise by about 150 m so that “regions where snowfall is the current norm will increasingly experience precipitation in the form of rain. » |
Beniston 1997 in Bravard 2006 - P | |
Northern
French Alps: According to the scenario of Météo France (Martin & Durand, 1998), assuming an increase in temperature of +1.8 C°, at an elevation of 1,500 m, the average length of snow cover, presently comprised between 160 and 180 days in the Northern French Alps, could decrease down to 125-135 days. In the Southern Alps, it could decrease from 130-100 down to 80-55 days/yr. This means one month less of snow cover that today (SAFRAN-CROCUS snow model, in French ARPEGE GCM - Team Climate Modelling and Global Change). |
Martin & Durand 1998 in Bravard 2006 - P | ||
French
Alps: According to the climate change scenarios, the snow coverage is modified (especially at middle elevation). In the PT scenario, the snow cover duration is diminished by 30-40 days a-1 at 1500 m. At high elevation (3000 m), changes are small and snow coverage can be considered stable. |
SCM is used to simulate the snow coverage. |
Martin & al 2001 - A | |
| French Alps: With the SAFRAN/CROCUS model, the impact of global warming of 1.8°C on snow cover at high elevation sites (above 2500m asl) should remain low: delayed onset of snow cover, slightly faster melting of the snow cover (decrease of the snow cover duration on a dozen days per year) and a light decrease of the snow height. Under this 2500m altitude, the cold season will decrease and even disappear around 1800-2000m asl (the mean temperature can compensate the simulated warming of +1.8°C). At medium altitude (1500m a.s.l), snow cover duration should decrease by one month (from 5 to 4 months duration). The snow height should decrease by around 40cm in the Northern Alps (from 1m to 60cm) and of around 20 cm in the Southern Alps (from 40 to 20 cm). In the French Alps, the impact of global warming of +1.8°C on the snow cover (SAFRAN/MODCOU/CROCUS model, coupled with the ISBA surface scheme) should be more pronounced for medium and low altitudes. Snow cover duration should decrease by 45 days (+/-15) at 1000m a.s.l, and by 35 days (+/-10) at 3000m a.s.l. The mean snow height should be reduced by between 20 and 30cm, depending on the altitude. Above 2500m a.s.l, snow cover duration should decrease slightly (around a dozen days per year), as well as snow height. But around 1500m a.s.l, the mean snow cover duration should decrease by a month in (from 5 to 4 months of duration). Snow height should decrease by around 40cm in the Northern Alps (from 1m to 60cm) and by around 20 cm in the Southern Alps (from 40 to 20 cm). The Isère river catchments area would experience a decrease in maximum snow accumulation of between 30 and 50% with a quasi-complete disappearance during the summer season. The impacts of climate change on snow cover in the Haute Durance river catchments are similar, with a lesser reduction due to the lower altitude. In both cases, snow cover will tend to decrease and the nival characteristic of the river catchments tend to soften |
A first method uses the SAFRAN and CROCUS tools. The Crocus model calculates the snow cover evolution (thickness, stratigraphy…) for each mountain range every 300m elevation (from 900 to 3600 m) for 6 orientations (N, E, SE, S, SW, W) and 3 slopes (0, 20 and 40°). The Safran analysis system supplies all the available meteorological data, as well as numeric model outputs. A simple scenario (uniform 1.8°C temperature increase) was chosen. The study carried out a comparison between results of a reference simulation (1980 decade) and results of a simulation with the temperature increase (Martin et al.,1994). The second method uses the SAFRAN tools for the meteorological parameter analysis, the hydrological model MODCOU integrating the surface scheme ISBA and a simplified snow module inspired by CROCUS. These tools were validated on the Rhone river watershed, before being used in a climatic scenario (GICC-Rhône project). Six different “2*CO2” scenarios were used to estimate the impact of climate change on snow hydrology of certain watershed with snow dominant pattern. Four models were used among which two supplied scenarios with low (LR) and high (HR) resolution. |
Etchevers & Martin 2002 - P | |
French Alps: The ratio of solid precipitation over total precipitation decreases significantly over the Rhone basin (-21%), particularly for low and medium altitude watersheds, and the duration of the snow cover reduces. The snow pack is strongly reduced in the southern part of the Alps, the maximum snow water equivalent (SWE) and snow cover duration diminish by 50%. In the northern Alps, the SWE reduction is weaker (-20%). The snow pack anomalies strongly depend on the elevation and are significant below 1000 m. The mean snow depth diminishes by 25 cm under 2000 m (-31%) but only by 16 cm at 3000 m (-11%). The contrast is particularly strong between 1500 and 2400 m. The reduction of the snow cover lifetime is 50 days (-26%) under 2000 m versus 40 days (-3%) at 3000 m. |
Etchevers & al. 2002 - A | ||
Swiss
Alps: Under changing climatic conditions, the separation into different winters modes can be used as an indication of the type of snow cover that could be expected in the future, by analogy with current conditions. Examples are given in the study: A rise in temperature of over 5°C at Arosa and a 40% reduction in precipitation leads to a switch from the cold/moist to the warm/dry modes, leading to a reduction of 54 days in snow cover and almost a 50% reduction in the seasonal snow accumulation. For an equivalent rise in temperature and reduction in precipitation at the lower site of Chateau d’Oex, there is a reduction of over 100 days of snow cover, from 125 days to 22 days, and an 80% reduction in snow cover. The sensitivity of snow cover to warming is greater for dryer-than-average winters than for wetter-than-average winters. The volume of snow cover remains maximum at 2000 m for both + 2°C and + 4°C scenario ; the reduction in volume corresponds to 10% per degree of warming. The snow cover duration is reduced of 15-20 days per degree of warming. The shortening of the snow season concerns more the end (spring), rather than the beginning (autumn), so that it should be expected that snow melt would intervene much earlier in the season than under current conditions. |
Scenario HIRHAM 4, GRENBLS model for snow cover reaction (GRound ENergy
Balance for naturaL Surfaces). |
Beniston & al. 2003a - A | |
Alps: Large scale forcing, rather than just local or regional factors, plays a dominant role in controlling the timing and amount of snow in the Alps. |
Beniston & al. 2003b - A | ||
Thur and upper Ticino river basins (Swiss Alps): For the Thur and Ticino basins, the 17-scenario projections revealed a decrease in the annual mean snowwater equivalent (SWE) between 73% (Thur basin) and 69% (Ticino basin) as compared with the control run. Averaged over the winter period (DJF), SWE was calculated to diminish by 68% (26 mm) in the Thur basin and by 57% (66 mm) in the Ticino basin. The lifetime of continuous snow cover was shortened by about 1 to 3 months, while the snow-line was raised by some 300 to 600 m. The occurrence of snow-free conditions (SWE < 1 mm) was advanced by about 5 to 8 weaks in spring, as opposed to a postponement of only about 1 to 3 weaks for the begin of the snow season. In both basins, large differences across the scenario members occurred in particular during the spring season. |
Possible future changes in the natural water budget relative to the 1981-2000 (Thur) and 1991-2000 (Ticino) baselines were investigated by driving the distributed catchment model WaSiM-ETH with a set of 23 regional climate scenarios for monthly mean temperature (T) and precipitation (P). The scenarios referred to 2081-2100 and were constructed by applying a statistical-downscaling technique to outputs from 7 global climate models. |
Jasper & al. 2004 - A | |
French Alps: |
Evaluation of global climate change with a “2*CO2” scenario and 4 models of atmospheric circulation (low and high resolution). Hydrological modeling and determination of 6 scenarios combining observed climatic variables (data resulting from 131 stations distributed in the watershed for the 1981-1997 period) with simulated anomalies for temperature and precipitation. Application of climate forcing scenarios to 5 different hydrological models (Modcou, ISBA-Modcou, Marthe, CEQUEAU, Ecomag) covering the French part of the Rhone river watershed. |
GICC Rhône 2005 - R | |
World/Alps: Climate models project significant decreases in snow cover by the end of this century, with reductions of 60 to 80 % in snow water equivalent (depth of water resulting from snow melt) in most mid-latitude regions. The largest decreases are projected over Europe, while simulated increases are seen in the Canadian Arctic and Siberia. Climate model projections indicate that the Alps and Pyrenees will experience warmer winters with possible increases in precipitation (Marinucci et al., 1995), which will raise snow lines, reduce overall snow cover, and decrease summer runoff. |
Bibliographic review | UNEP 2007 - R | |
|
Hypothesis |
Alps:
An increase of temperature of 2-3°C by the year 2050 would adversely affect low altitude (below 1,200-1,500 m). Warmer winters will bring less snow at these altitudes, and snow will melt faster. |
Abegg and Froesch 1994 in Bravard 2006 - P | |
Alps: The hypothesis of less snowy Alps in the future is still valid, even after the 1999 winter. When more humidity is "injected" in the atmosphere because of global warming, it is normal that, despite the warming trend, when there is a North-West pattern with North or South blockings, abundant snow falls may occur in the Alps some years. |
ProClim 1999 - E | ||
World: In most temperate mountain regions, the snow pack is close to its melting point, so it is very sensitive to changes in temperature. As warming progresses in the future, current regions of snow precipitation increasingly will experience precipitation in the form of rain. For every 1°C increase in temperature, the snowline rises by about 150 m; as a result, less snow will accumulate at low elevations than today, although there could be greater snow accumulation above the freezing level because of increased precipitation in some regions. The timing of stream flow therefore alters significantly. At higher altitudes, most of the precipitation continues to fall as snow, so the distribution of flow through the year is altered little. In areas where snowfall currently is marginal, snow may cease to occur. |
IPCC 2001 - R | ||
French Alps: The possible increase of winter precipitations in the French Alps may partially counterbalance the snow deficits at medium altitude; this change in the precipitation amount should not influence the snow cover duration, which is primarily governed by the melting process |
Etchevers & Martin 2002 - P | ||
|
World:
For every °C increase in temperature, the snowline will rise by about 150 m. |
Beniston 2003 - R | ||
| Swiss
Alps: An average warming of 4°C for the period 2071-2100 (simulation from the PRUDENCE project) suggests that snow volume in the Swiss Alps may respond by reduction of at least 90% at altitude close to 1000m asl, by 45-60% at 2000m asl, and 30-40% at 3000m asl. The duration of snow cover may be sharply reduced in warmer climate, with a termination of the season 50-60 days earlier at high elevation (above 2000-2500m asl) and 110-130 days earlier at medium elevation (close to 1000m asl). Reduction in snow-cover duration of 15-20 days for each degree of wintertime warming can be expected. |
Beniston & al. 2003a - A | ||
Swiss Alps: The study suggests a strong domination of the temperature on snow duration. Small shifts of winter mean minimum temperature may lead to substantial change in the length of the snow cover season. |
Beniston & al. 2003b - A | ||
French and Swiss Alps: It is likely that for low elevation sites, the snow cover decrease trend may continue and even accelerate in the next years. |
Ancey 2005 - E | ||
Wold: A common aerosol found in the atmosphere over many regions of the earth is black carbon. This substance absorbs sunlight. It is scrubbed from the atmosphere by precipitation and, because it is ubiquitous, is likely to end up in the snow and ice fields of the planet. There it could decrease the surface albedo, causing the snow/ice to absorb solar energy more readily and thereby melt sooner. Measurements of black carbon amounts and its budgets are only now being made. By whatever means, darkening the surface of a snow/ice field will enhance melt rates. It seems that proper inclusion of aerosols in global climate models will increase early melting of snow packs and, especially, glaciers and sea ice. Properly represented aerosols in climate models will apparently also work together with increasing temperature to reduce snow/ice in regions where heavy air pollution exists (for example, China, the western USA and Europe). |
Barnett & al. 2005 - A | ||
France: A net decrease of snow cover duration, especially in the Southern Alps and in Pyrenees (-30 % to -40 %), is expected (MIES, 2000). |
ONERC 2005 - R | ||
| Alps
/ South Germany: One can expect up to 50% decrease of the snow cover in winter for 700-1000 m altitude sites because of temperature rise and precipitation seasonal shifts. |
Seiler 2006 - P* | ||
World: |
IPCC 2007 - R (SP) | ||
Switzerland: By 2050, the snow line could rise by 350 m (OcCC, 2007). Above 2000 m a.s.l., snow amounts should rather increase in the future (OcCC/ProClim, 2007). |
Bibliographic review | North & al. 2007 - R: OFEV |
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Legend of bibliographical
references:
- * : study taken into account in WP7.
- A : Article (Peer reviewed publication)
- C : Comment
- E : Scientific study (unpublished)
- P : Proceedings
- R : Report
- Re : Experience Feedback
- T : Thesis
- W : Website