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Sensitivity of Alpine snow cover to European temperature
International Journal of Climatology
Abstract
The number of days with snow cover at 268 Alpine climate stations in the winters of 1961–2000 has been investigated with respect to the mean winter temperature over Europe. The corresponding description, originally developed for Austria and recently applied to Switzerland, consists in fitting a logistic curve to the observed data. The slope of this curve, originally the hyperbolic tangent function, is interpreted as the sensitivity of the snow duration-temperature relationship.
Here we first demonstrate with a physical-statistical model that the proper logistic curve is not the hyperbolic tangent, but the error function, generated through the pdf of the fluctuating temperature; the slope of this curve is inversely proportional to the standard deviation of temperature. Since the station temperature used for this local model is on a scale much too small for global climate models, we simulate, secondly, the temperature with the concept of the Alpine temperature: It is the spatial Taylor expansion of the seasonal European temperature in vertical and horizontal directions. This improved model yields, for the same Austrian and Swiss data, both a better fit and a slightly smaller sensitivity of the snow-temperature curve than the original hyperbolic model.
Thirdly we apply our improved model to a considerably larger Alpine data set comprising also data from France, Germany, Italy and Slovenia and find a sensitivity of about − 0.33 ( ± 0.03) per degree warming. It is representative for the entire Alpine region and corresponds to a maximum reduction of the snow cover of 30 days in winter at a height of 700 m for 1° European warming. The implication is that the relation between the natural fluctuations of winter snow duration and European temperature may be an estimate for a trend of snow duration in case of a future European temperature trend. Copyright
... La durée du manteau neigeux est ainsi très sensible à l'évolution de la température de l'air (Hantel & Hirtl-Wielke 2007), notamment au printemps (Hantel et al. 2000;Wielke et al. 2004), ce qui est donc aussi le cas pour sa date de démarrage à l'automne, sa date de fonte au printemps, ou encore à l'inverse, la durée sans présence de neige au sol en été ( Figure 3). À moyenne altitude, les études de Rebetez (1996), Bednorz (2004) et Schöner et al. (2019 indiquent que cette sensibilité du manteau neigeux existe également en hiver, puisque des températures de l'air plus élevées pendant cette saison ont pu être mises en relation avec un manteau neigeux moins épais. ...
... Acquaotta et al. 2015;Rebetez & Reinhard 2008). Warmer temperatures were shown to be the major cause of the shorter snow cover duration in the European Alps(Hantel & Hirtl-Wielke 2007;Scherrer et al. 2004;Serquet et al. 2011). In fact, the reduction of the snow cover duration can be caused either by accelerated snowmelt due to warmer temperatures in spring(Rixen et al. 2012;Wielke et al. 2004) and/or reduced snowfalls during the winter season(Marty & Blanchet 2012;Scherrer et al. 2013). ...
RÉSUMÉ
Les régions de montagne sont des zones particulièrement exposées aux variations du climat. L’augmentation significative des températures de l’air observée au cours du XXe siècle dans les Alpes a eu des répercussions notables sur l’évolution spatiale et temporelle du manteau neigeux, engendrant d’importantes modifications au niveau des écosystèmes, des cycles hydrologiques ou encore des activités économiques humaines. Dans ce contexte de réchauffement de l’air, il est important de développer les connaissances actuelles sur la variabilité du manteau neigeux alpin, afin de mieux appréhender les conséquences de ces changements sur l’environnement direct. Cette thèse de doctorat a pour objectif d’étudier la relation entre le changement climatique de ces dernières décennies (1970-2016) et l’évolution temporelle du manteau neigeux continu dans les Alpes suisses au-delà de 1100 m d’altitude, ainsi que l’influence de cette couverture neigeuse sur le risque d’exposition au gel des plantes alpines au moment du démarrage de leur croissance après la fonte des neiges.
L’analyse portée sur l’évolution temporelle (1970-2015) des principales caractéristiques annuelles du manteau neigeux continu (épaisseur, durée, saisonnalité) entre 1100 et 2500 m d’altitude dans les Alpes suisses dévoile un recul généralisé de la couverture neigeuse au cours de cette période, que ce soit dans son épaisseur ou dans sa durée et quel que soit l’altitude, la zone géographique examinée ou les conditions climatiques locales. L’étude montre notamment que la durée du manteau neigeux continu s’est réduite en moyenne de 38 jours entre 1970 et 2015 et que cette réduction est plus particulièrement attribuable à une date de fonte des neiges de plus en plus précoce au printemps (-26 jours), plutôt qu’à un début d’enneigement continu plus tardif à l’automne (+12 jours).
La combinaison entre une date de fonte des neiges de plus en plus précoce avec une forte dépendance du démarrage de la croissance des plantes alpines à celle-ci, pose la question d’un éventuel risque accru d’exposition au gel de ces plantes, à une période où celles-ci y sont particulièrement vulnérables. L’analyse du risque d’exposition au gel de ces plantes lors de leur période de début de croissance illustre l’existence d’une solide relation entre la date de fonte des neiges et la fréquence ou l’intensité de gel lors des jours avoisinant cette période. En effet, il est observé en moyenne que plus la fonte des neiges est précoce, plus les fréquences et intensités de gel augmentent au cours de la période de démarrage de la croissance des plantes alpines et ce, quelle que soit l’altitude (1418-2950 m), la zone géographique ou encore la période temporelle analysée (1998-2016 ou 1970-2016) dans les Alpes suisses. Néanmoins, avec une augmentation moyenne des températures de l’air printanières de 0,6°C par décennie entre 1970 et 2016 dans les zones alpines et subalpines, aucun changement significatif n’a été observé dans le même temps quant à la fréquence ou à l’intensité de gel pendant cette période de début de croissance. Ce réchauffement a permis de contrebalancer les effets d’un déneigement du sol plus précoce, en décalant au même rythme les dernières occurrences de gel et le démarrage de la croissance des plantes alpines, limitant ainsi leur risque d’exposition au gel au cours de leur période de début de croissance.
L’ensemble des analyses menées dans cette thèse démontrent l’importance de la saisonnalité du manteau neigeux sur le démarrage de la croissance des plantes alpines, ainsi qu’une grande homogénéité spatiale des résultats à travers les Alpes suisses. En effet, qu’il s’agisse de l’évolution du manteau neigeux ou du risque d’exposition au gel tardif pour les plantes alpines, les résultats de ce travail se retrouvent sans distinction significative à travers l’ensemble du gradient d’altitude représentant les étages alpins et subalpins, au sein de zones géographiques diverses et éloignées ainsi que dans des conditions climatiques locales variées, indiquant qu’il s’agit de phénomènes d’ampleur supérieure à celle des Alpes suisses.
Mots-clés : Alpes suisses, Fonte des neiges, Gel tardif, Manteau neigeux, Plantes alpines, Réchauffement climatique
ABSTRACT
Mountain regions are particularly exposed to climate change. The significant increase of air temperatures observed during the XXth century in the Alps had strong impacts on the spatial and temporal variability of snow cover, causing major changes on ecosystems, hydrological cycles or human economic activities. In this context of global warming, it is important to improve knowledge on snowpack variability in order to better understand the consequences of these changes on the surrounding environment. This PhD thesis aims to explore the relationship between recent climate change (1970-2016) and the temporal evolution of continuous snowpack in the Swiss Alps over 1100 m asl, as well as the influence of this snowpack on the risk of frost exposure for alpine plants during their most vulnerable period to frost, i.e. at the beginning of their growth period shortly after the time of snowmelt.
The analysis of the main annual characteristics of the continuous snow cover (thickness, duration, seasonality) from 1100 to 2500 m asl in the Swiss Alps over the 1970-2015 period reveal a general decline of the snowpack, whether for its depth or its duration and irrespective of elevation, geographical location or local climatic conditions. This study also demonstrate that the snow cover duration has been shortened at all sites on average by 38 days between 1970 and 2015 and that this shortening is mainly driven by an earlier time of snowmelt (-26 days) rather than a later time of snow onset (+12 days).
The combination between an earlier time of snowmelt and a strong dependence of the beginning of growth of alpine plants to this snowmelt raises the question of a potential higher risk of frost exposure for these plants, during a period when they are particularly vulnerable to freezing events. The analysis of the risk of frost exposure for alpine plants during the beginning of their growth period illustrate the existence of a strong relationship between the time of snowmelt and the frequency or intensity of freezing events during the days surrounding this vulnerability period for plants. On average, an early time of snowmelt generally leads to an increasing frequency and intensity of frost during the vulnerable period for alpine plants, irrespective of elevation (1418-2950 m), geographical location or the temporal period analyzed (1998-2016 or 1970-2016) in the Swiss Alps. However, with an average spring air temperature increase of 0,6°C decade-1 between 1970 and 2016 in alpine and subalpine regions, the frequency and intensity of frost during the vulnerable period for alpine plants remained unchanged. This warming allowed a compensatory effect of an earlier time of snowmelt by shifting the last occurrence of frost and the beginning of alpine plants growth period to a same extent, thus limiting their exposure to late frost events during the beginning of their growth period.
All analyses conducted in this PhD thesis demonstrate the importance of snowpack seasonality on alpine plants growth period, as well as a strong spatial homogeneity of the results over the Swiss Alps. Whether for the snowpack evolution or the risk of exposure to late frost events for alpine plants, results may indeed be found without any significant distinction across all elevations, various geographical locations and a large panel of local climatic conditions, indicating that they could be extended beyond the Swiss Alps.
Keywords: Swiss Alps, Time of snowmelt, Late frost, Snow cover, Alpine plants, Global warming
... Despite the high year-to-year variability, a negative and nearly identical trend of AAR values is observed over the two study periods (1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) for the three glaciers (from -0.06 to -0.08). Such trends were also found before 1998 [60] and are in line with a temperature increase since 1979 at the climate station in Vent (0.07 °C /year) [58] and a general decrease of SC in the Alps [61,62]. ...
... Despite the high year-to-year variability, a negative and nearly identical trend of AAR values is observed over the two study periods (1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) for the three glaciers (from −0.06 to −0.08). Such trends were also found before 1998 [60] and are in line with a temperature increase since 1979 at the climate station in Vent (0.07 • C /year) [58] and a general decrease of SC in the Alps [61,62]. ...
Mapping snow cover (SC) on glaciers at the end of the ablation period provides a possibility to rapidly obtain a proxy for their equilibrium line altitude (ELA) which in turn is a metric for the mass balance. Satellite determination of glacier snow cover, derived over large regions, can reveal its spatial variability and temporal trends. Accordingly, snow mapping on glaciers has been widely applied using several satellite sensors. However, as glacier ice originates from compressed snow, both have very similar spectral properties and standard methods to map snow struggle to distinguish snow on glaciers. Hence, most studies applied manual delineation of snow extent on glaciers. Here we present an automated tool, named ‘ASMAG’ (automated snow mapping on glaciers), to map SC on glaciers and derive the related snow line altitude (SLA) for individual glaciers using multi-temporal Landsat satellite imagery and a digital elevation model (DEM). The method has been developed using the example of the Ötztal Alps, where an evaluation of the method is possible using field-based observations of the annual equilibrium line altitude (ELA) and the accumulation area ratio (AAR) measured for three glaciers for more than 30 years. The tool automatically selects a threshold to map snow on glaciers and robustly calculates the SLA based on the frequency distribution of elevation bins with more than 50% SC. The accuracy of the SC mapping was about 90% and the SLA was determined successfully in 80% of all cases with a mean uncertainty of ±19 m. When cloud-free scenes close to the date of the highest snowline are available, a good to very good agreement of SC ratios (SCR)/SLA with field data of AAR/ELA are obtained, otherwise values are systematically higher/lower as useful images were often acquired too early in the summer season. However, glacier specific differences are still well captured. Snow mapping on glaciers is impeded by clouds and their shadows or when fresh snow is covering the glaciers, so that more frequent image acquisitions (as now provided by Sentinel-2) would improve results.
... 1. Introduction 1.1. Context among others, are supported by satellite data and ground measurements, which reveal a consistent trend towards shorter snow seasons and reduced snow depths [10]. This increase in temperature and the reduction in snow cover have various implications on different industries, one of them being the Swiss winter tourism industry, which is being hit especially hard. ...
The ongoing effects of climate change have led to a rise in global temperature, significantly reducing snow cover and resulting in the abandonment of numerous ski areas across Switzerland. As a result, many ski lifts have been decommissioned and left to deteriorate due to lenient local regulations. To address this issue, this paper presents a case study approach to repurposing steel trusses from abandoned ski lifts for a new structural application within the building industry. The design, sourcing, and construction of a new load-supporting column are described, focusing on reusing the ski lift steel trusses as a whole, without dismantling them into their components. After collection, these elements are adapted to comply with current building standards. By pouring out the hollow structure with the recently developed building material Cleancrete ©, a new load-bearing structure is developed. A comprehensive life cycle assessment (LCA) demonstrates the environmental performance of the steel-Cleancrete hybrid construction, which achieves a global warming potential (GWP) of 536.58 kg CO 2-eq. In comparison, alternative designs using wood and concrete exhibited GWP values of 679.45 kg CO 2-eq, +26.6%, and 1593.72 kg CO 2-eq, +197.02%, respectively. These findings suggest that repurposing abandoned ski lift structures can significantly contribute to sustainable building practices, waste reduction, and the promotion of circular economy principles. The process outlined in this paper holds potential for future applications, particularly in the reuse of other steel components, ensuring continued circularity even as the supply of ski lift structures may dwindle.
... Linking snow drought information to agriculture systems holds particular signi cance in crop-producing countries, where the impacts of snow drought can propagate globally through trade networks and exacerbate food insecurity 16 . Snow exhibits signi cant sensitivity to different levels of future warming [44][45][46] . For this reason, snow droughts are projected to become increasingly frequent 8 due to warming winters, with escalating impacts on crop growth (Fig .3). ...
The global crop ecosystem is critically dependent on snow availability, which has diminished in numerous snow-dependent regions due to increasing snow droughts associated with warmer winters. However, our understanding of crop yield sensitivity to snow droughts and how this sensitivity evolves remains limited. In this study, we find that from 1960 to 2020, approximately 51% of winter wheat croplands have experienced a significant increase (5.3−6.7% per year) in the frequency of snow droughts. To assess the sensitivity of winter wheat yield to snow droughts, we utilized explainable machine learning, gridded yield datasets, and the standardized snow water equivalent index (SWEI) from 1982 to 2016. Our findings reveal a positive association between yield anomalies and SWEI under snow drought conditions and a significant increase in the sensitivity of yield to SWEI over 24% of Northern Hemisphere winter wheat croplands. Additionally, enhanced accumulation of growing degree days, increased vapor pressure deficit (VPD), a slight decrease in total precipitation, and increased heavy rainfall are identified as dominant factors amplifying yield sensitivity to snow droughts. These findings highlight an increasing vulnerability of crop systems to snow droughts over the past three decades, which is crucial for informing risk management and adaptation of agriculture to a warming future with less snow.
... The changes in the depth of snow cover and the number of days with snow on the Gąsienicowa Glade in the Tatra Mountains correspond to the general developments taking place in the Alps, but also in other high mountain ranges in the world (e.g., Beniston et al., 2018;Brown & Petkova, 2007;Durand et al., 2009;Fontrodona Bach et al., 2018;Hantel & Hirtl-Wielke, 2007;Klein et al., 2016;Laternser & Schneebeli, 2003;Marty & Blanchet, 2011;Marty & Meister, 2012;Mote et al., 2005;Notarnicola, 2020;Räisänen, 2008). The decrease in the number of days with snow cover in the Gąsienicowa Glade in the Tatra Mountains is mainly due to the increase in temperature in the winter and spring months. ...
The oldest meteorological station in the Polish Tatra Mountains is that on the Gąsienicowa Glade (1520 m). In this study, two series of observations for the years 1927–1938 and 1947–2020 are presented for the number of days with snow cover higher than 1 cm (SCD—from 142 to 228 days), maximum snow depth (HSmax—from 43 to 271 cm) and average snow depth (HSmean—from 10 to 93 cm). For the remaining meteorological parameters discussed in this article, the observation series is slightly shorter. From 1927 to 2020, the number of days with snow cover show downward trends (SCD—from nearly 200 days in 1927/1928 to about 175 days in 2019/2020). The decrease in the values of SCD discussed is due to an increase in air temperature and an upward trend in the percentage of the number days with rain over the number of days with snowfall. The increase in mean air temperature started in the 1980s. The strongest temperature trends were recorded in spring (TG in June—from 8.2°C in 1927 to 10.0°C in 2020) and in summer (TG in August—from 9.7°C in 1927 to 12.0°C in 2020). The last two decades, in particular, are exceptional for the Tatra Mountains, both in terms of air temperature, days with snow cover, maximum and mean snow depth. Since the beginning of observations in the Gąsienicowa Glade, no such strong decade‐long increases in temperature and decreases in the number of days with snow cover and in maximum and mean snow depth have been recorded. The observed trends in days with snow cover and maximum and mean snow depth in the Tatras are similar to those observed in studies conducted in the Alps.
... Several studies have shown that higher air temperature is the main reason for shorter SC duration in the Alps (Hantel & Hirtl-Wielke, 2007; Mor an-Tejeda, L opez-Moreno, Scherrer et al., 2004;Serquet et al., 2011Serquet et al., , 2013 or the Pyrenees (Mor an-Tejeda, Herrera, et al., 2013), among others. In fact, the shortened duration of SC may be due to either accelerated snowmelt due to higher temperatures in spring (Klein et al., 2016;Wielke et al., 2004) and/or reduced snowfall during the winter season (Marty & Blanchet, 2012;Marty & Meister, 2012;Scherrer et al., 2013;Serquet et al., 2011Serquet et al., , 2013. ...
This article discusses the reasons for shortening snow cover duration in the Western Sudetes, considering local changes in: air temperature; amount and type of precipitation; sunshine duration and atmospheric circulation leading to changes in the number of days with snow cover and its depth; and its start and end dates. All factors were linked to the exposure and relief of the study area. The analysis was made for the winter seasons (Nov–Apr) 1961/1962–2020/2021. It was found that the primary reasons for the shortening of snow cover duration in the Western Sudetes are: a multi‐year increase in air temperature and sunshine duration; changes in precipitation patterns—a decrease in the proportion of solid precipitation, changes in atmospheric circulation—including an increase in anticyclonic circulation types with sunny weather, especially in April (snow cover disappears in most of the elevation profile of the Sudetes); and less cyclonic weather types. The above factors synergistically affect the lower snow depth, and fewer days with solid precipitation, which promotes its faster spring ablation. In the subsequent 30 years (climatological norms), there is a successive shortening in its duration. On the snow cover start dates, there are no clear trends in the direction and rate of change. On end dates, negative trends are observed, in most cases statistically significant. The rate of change for the end dates of snow cover is about twice as high as the start dates. The rate of decline in snow cover is higher at stations at similar altitudes with northern macro‐exposure than southern. The results correspond with other studies from Europe and the world on the earlier disappearance of snow cover. They confirm the successive global warming and shortening snow cover duration, especially evident in the last few decades.
... The surface temperature has a main influence on the hydrological cycle, particularly in the mountain cryosphere, where the water supply is dominated by melting snow or ice [16][17][18][19] . For glacier and snow melting runoff modeling, the lapse rate is the key parameter, which would have a direct impact on the simulated accuracy of hydrological processes in ungauged basins [20][21][22] . ...
As a key parameter of hydrological process modeling, the near-surface air temperature lapse rate reflects the vertical changes in air temperature characteristics in alpine basins but often lacks the support of sufficient ground observation data. This study estimated the lapse rate of the Lhasa River Basin (LRB) from the monthly air temperature dataset (2001–2015), which was derived based on good relationships between the observed air temperature at eight gauged stations and the corresponding gridded land surface temperature of MODIS. The estimated annual average air temperature lapse rate was approximately 0.62 °C/100 m. The monthly lapse rate in different years varied seasonally in the range of 0.45–0.8 °C/100 m; the maximum was in May, and the relatively low value occurred from September to January. The snow cover in the zones with relatively low altitudes showed seasonal variation, which was consistent with the air temperature variation. Permanent snow cover appeared in the area above 5000 m and expanded with increasing elevation.
... While these studies are invaluable to inform on ecological mechanisms underpinning ecological changes, their paucity precludes tracking complex, non-linear responses along topographical, geomorphological and climate gradients. For example, winter snow duration-which is widely acknowledged as a key driver of vegetation dynamics-for the time being shows decreased sensitivity to global warming at elevations above 2000 m (Hantel & Hirtl-Wielke, 2007;Schoener et al., 2019). Another issue is the over-representation of high summits in plot-based surveys, considering that the area they cover represents a minute fraction of above-treeline habitats. ...
The long-term increase in satellite-based proxies of vegetation cover is a well-documented response of seasonally snow-covered ecosystems to climate warming. However, observed greening trends are far from uniform, and substantial uncertainty remains concerning the underlying causes of this spatial variability. Here, we processed surface reflectance of the moderate resolution imaging spectroradiometer (MODIS) to investigate trends and drivers of changes in the annual peak values of the Normalized Difference Vegetation Index (NDVI). Our study focuses on above-treeline ecosystems in the European Alps. NDVI changes in these ecosystems are highly sensitive to land cover and biomass changes and are marginally affected by anthropogenic disturbances. We observed widespread greening for the 2000–2020 period, a pattern that is consistent with the overall increase in summer temperature. At the local scale, the spatial variability of greening was mainly due to the preferential response of north-facing slopes between 1900 and 2400 m. Using high-resolution imagery, we noticed that the presence of screes and outcrops locally magnified this response. At the regional scale, we identified hotspots of greening where vegetation cover is sparser than expected given the elevation and exposure. Most of these hotspots experienced delayed snow melt and green-up dates in recent years. We conclude that the ongoing greening in the Alps primarily reflects the high responsiveness of sparsely vegetated ecosystems that are able to benefit the most from temperature and water-related habitat amelioration above treeline.
... At low elevation, snowmelt occurred earlier during our study period, as found by Klein et al., 2016 [even though the effect is larger in our study site with an advancement of 1.6 days/year than in Klein et al., 2016, −0.5 (−0.7; −0.3) days/year since 1970 for stations under 1,500 m asl], which lead to the advancement trend of frog breeding phenology. At high elevation, however, we observed a delay in snowmelt in our study area and years, which is consistent with certain studies demonstrating decreased sensitivity of snow cover duration to climate warming above 2,000 m (Hantel and Hirtl-Wielke, 2007;Schoener et al., 2019). Consistent with the strong relationship between snowmelt and frog spawning, we observed a delay of frog breeding phenology at the high elevation sites. ...
The alarming decline of amphibians around the world calls for complementary studies to better understand their responses to climate change. In mountain environments, water resources linked to snowmelt play a major role in allowing amphibians to complete tadpole metamorphosis. As snow cover duration has significantly decreased since the 1970s, amphibian populations could be strongly impacted by climate warming, and even more in high elevation sites where air temperatures are increasing at a higher rate than at low elevation. In this context, we investigated common frog (Rana temporaria) breeding phenology at two different elevations and explored the threats that this species faces in a climate change context. Our objectives were to understand how environmental variables influence the timing of breeding phenology of the common frog, and explore the threats that amphibians face in the context of climate change in mountain areas. To address these questions, we collected 11 years (2009–2019) of data on egg-spawning date, tadpole development stages, snowmelt date, air temperature, rainfall and drying up of wetland pools at ∼1,300 and ∼1,900 m a.s.l. in the French Alps. We found an advancement of the egg-spawning date and snowmelt date at low elevation but a delay at high elevations for both variables. Our results demonstrated a strong positive relationship between egg-spawning date and snowmelt date at both elevations. We also observed that the risk of frost exposure increased faster at high elevation as egg-spawning date advanced than at low elevation, and that drying up of wetland pools led to tadpole mortality at the high elevation site. Within the context of climate change, egg-spawning date is expected to happen earlier in the future and eggs and tadpoles of common frogs may face higher risk of frost exposure, while wetland drying may lead to higher larval mortality. However, population dynamics studies are needed to test these hypotheses and to assess impacts at the population level. Our results highlight climate-related threats to common frog populations in mountain environments, but additional research should be conducted to forecast how climate change may benefit or harm amphibian populations, and inform conservation and land management plans in the future.
... Warming air temperatures have decreased the volume, extent, and persistence of winter snowpack in the Alps (Hantel and Hirtl-Wielke, 2007;Beniston, 2012) and the Sierra Nevada (NASA, 2015), changing the form of precipitation that dominates mountain hydrology from snow and ice to rainfall, and increasing the variability of stream discharge (IPCC, 2014). Streamflow projections for a representative watershed in the northern Rocky Mountains (United States) show peak streamflows occurring 1-2 months earlier as winter snowpack declines (Gould et al., 2016). ...
For millennia, humans have deliberately altered the geomorphology of the world's mountains to obtain resources, create transportation routes, and develop infrastructure for economic, agricultural, recreational, and spiritual activities. Road building, agriculture, mining, logging, dams, environmental restoration efforts, and other actions influence geomorphic forms and processes in planned and in unintended ways, including accelerated soil erosion and mass wasting. Such impacts can persist for millennia, alter regional fluvial systems, and catalyze change downstream. Climate change extends anthropogenic impacts throughout the world and creates new hazards, such as glacial lake outburst floods and massive rockfalls, that require further intervention and mitigation measures.
... Accordingly, Serquet et al. (2013) discovered a negative trend in the ratio of snowfall to total precipitation days over 1961-2008 across Switzerland in winter and spring, which indicates that a liquid precipitation has become more frequent. In the Alps, the recent surface warming and the associated circulation changes, with a shift towards a predominantly positive phase of the North Atlantic Oscillation (Zampieri et al., 2013), have largely concurred to the general reduction of snowfall observed in the past decades (Hantel and Hirtl-Wielke,-2007;Serquet et al., 2011). Accordingly, Déry and Brown (2007), observed monthly mean snow cover extent and air temperature over the Northern Hemisphere are strongly anti-correlated, especially in April-June, when extensive snow cover is accompanied with strong solar activity. ...
The emergence of decreasing trends in snowfall frequency and snow depth highlights the challenges arising from shifts in snow regimes. In particular, snow‐dependent southern Europe regions may be negatively impacted by such changes. Snow regimes strongly influence the water availability in reservoirs and groundwater. This study presents the world's longest series of monthly snowfall (fresh snow depth, snow days per year, days with snow on the ground) for the Parma Observatory, northern Italy (44°48′N and 10°19′E) between 1777 and 2018. These datasets were collected over the centuries using early rain gauges and recently, SIAP tipping bucket models. Sources of inhomogeneity were identified and analysed through the study of metadata and of nonparametric tests on datasets. Homogenized time series were obtained after correcting the observed snowfall data for the instruments response and localization characteristics, for the observing practices with the help of the standard normal homogeneity tests. The Buishand and the Mann–Kendall tests were further applied to check the correction and detect possible monotonic trends. Over the study period, days per year of snow decreased after the change point detected in 1897, in association with a rise in surface air temperature (including a distinct urban warming trend). In this study high numbers of snowy days per year (hereafter referred as snowfall frequency) and snow depth values during the latest phase of the LIA at Parma are consistent with a cycle of minimum solar activity, suggesting that enhanced, solar‐induced blocking activity dominated, with the arrival into the Mediterranean of large cold air masses developing over Siberia and northern Europe. Over the last century, snow appears to have resonance‐like characteristics as similar trends were observed over the Northern Hemisphere, where the extent of the snow cover has been reported to markedly decline in the transition spring and autumn seasons.
... A reduction in the total amount of snow and also snow cover duration since the mid-1980s was detected and mainly attributed to warmer temperatures in the European Alps (Hantel and Hirtl-Wielke, 2007;Scherrer et al., 2004;Serquet et al., 2011). Impacts were particularly evident at elevations below 1200 m (Beniston, 2006). ...
Understanding the temporal and spatial variability of river discharge of alpine hydrological systems is of particular interest due to their relevance for water uses including water provisioning, hydropower production and touristic activities. Streamflow variability is highly heterogeneous both in time and space due to several reasons, such as a differentiated response to climate change, differences in catchment morphology and geographic location. Therefore, catchment classification for these systems is challenging. A suitable tool to determine the crucial scales of variability of a non-stationary time series is wavelet transform. In this work, we compute the wavelet coherence between fifty selected gauging stations located within the Inn River catchment to classify them by runoff behavior, focusing only on long term variability, between one and eight years scales. This choice allows us to filter out the effect of local meteorological patterns and the effects of hydropower production. In addition, we decompose the streamflow signals in three levels (256 days, three years, six years) using Discrete Wavelet Transform to further understand the detected alterations in the streamflow signal. Three main runoff behaviors (referred as three classes) are found at the yearly scale. Focusing on two-four years scales a loss of coherence between time series located at different elevations becomes significant in the 1980s. Prior to 1980 we detect four different behaviors, while after 1980 we detect eleven different classes. At larger scales the stations are clustered in four classes. Our analysis highlights that catchment classification may depend on the scale of the analyzed signal and it may vary both in time and space. This research contributes to the development of new methods for catchment classification, which is highly relevant for many hydrological applications such as prediction in ungauged basins, model parameterization, understanding the potential impact of environmental and climatic changes, and transferring information from gauged catchments to the ungauged ones.
... The phase of precipitation is also projected to change due to the increase in temperature, especially in mid-latitude mountainous regions, where a shortening of the period with temperatures below 0 • C is expected, as well as a vertical shift of the limit between solid and liquid precipitation, leading to a reduction in the number of solid precipitation events (Diaz et al., 2003;IPCC, 2013;Wang et al., 2014). In the case of the Alpine regions, during the last decades the proportion between the number of snowfall days to the number of rainfall days has experienced a downward trend connected to increasing temperatures (Hantel and Hirtl-Wielke, 2007;Marty, 2008), with a stronger decrease in the lower elevation areas, close to the freezing level (Scherrer et al., 2004;Serquet et al., 2011). The change from solid to liquid precipitation leads to changes in the distribution of snow cover, mountain glacier areas (IPCC, 2013) and in freshwater discharge (Dyurgerov and Carter, 2006;Beniston and Stoffel, 2016;Würzer et al., 2016), favoring the reduction of the freshwater storage capacity and the increase of risks of winter and spring flooding (Knowles et al., 2001). ...
Solid precipitation plays an important role in the Earth's climate system, as well as for the maintenance of ecosystems and the development of human society. The large uncertainty in precipitation estimates and the discrepancies within climate model projections make this component of the hydrological cycle important as a research topic. Remote sensing allows to monitor precipitation and clouds in regions where in-situ observations are scarce and scattered, but with limited temporal resolution and a blind zone close to the ground level for spaceborne sensors, and limited visibility in the lower atmosphere in complex terrain for ground-based radars. The objectives of this dissertation are the following: 1) to characterize cloud and precipitation in Antarctica, detecting the presence of supercooled liquid and ice particles near the ground level using a ground-based 532-nm depolarization lidar; 2) to characterize the vertical structure of the precipitation in two contrasted but important regions of the cryosphere, Antarctica and the Alps, in the low troposphere using ground-based radars.In this study, a cloud and precipitation hydrometeor detection method is proposed using lidar data, complemented with a K-band micro rain radar (MRR) to improve the detection of precipitation, both instruments deployed at the Dumont d'Urville (DDU) station in East Antarctica. A method based on lidar depolarization and attenuated backscattering coefficient and the use of k-means clustering is developed for the particle classification. The classification of cloud and precipitation particles provides the vertical distribution of supercooled liquid water, as well as planar oriented ice and randomly oriented ice particles. The comparison between ground-based and satellite-derived classifications shows consistent patterns for the vertical distribution of supercooled liquid water in clouds.The vertical structure of precipitation near the surface is analyzed using the Doppler moments derived from three MRR profiles at DDU, the Princess Elisabeth (PE) station, at the interior of East Antarctica, and at the Col de Porte (CDP) station, in the French Alps. These analyses demonstrate that local climate plays an important role in the vertical structure of the precipitation. In Antarctica, the strong katabatic winds blowing from the high plateau down to the coast decrease the radar reflectivity factor near the surface due to the sublimation of the snowfall particles. Doppler moments also provide rich information to understand precipitation processes, such as aggregation and riming, as observed at DDU and CDP.The results also show that in the interior of the Antarctic continent a significant part (47%) of the precipitation profiles completely sublimate before reaching the surface, due to the dry atmospheric conditions, while in the coast of Antarctica it corresponds to about the third part (36%). In the Alps, this percentage is reduced to 15%. The major occurrence of particle sublimation is observed below the altitude where CloudSat profiles are contaminated by ground clutter. Therefore, this phenomenon cannot be fully captured from space with the current generation of sensors.This dissertation contributes to the study of the vertical structure of snowfall in the low troposphere, useful for the evaluation of precipitation remote sensing products, which may have severe limitations in the vicinity of the surface.
... Investigation showed that a logistic (non-linear) regression function was more appropriate than linear regression, and this yielded a distinctive sigmoidal relationship for the two variables ( Figure 4), plotting snow cover duration as a fraction of the snow year (i.e. total cover of 1.0 = 243 days). This logistic function also seemed to be invariant with time and is consistent with a similar analysis from the Alps (Hantel and Hirtl-Wielke, 2007). This suggests a general relationship that can then form a useful basis from which to map and contextualise snow cover change for both uplands and lowlands. ...
Recent research on snow cover patterns over recent decades is reviewed for GB. Interpretation for upland areas is complicated by data availability issues. Nevertheless, two distinct features can be highlighted. Firstly, a general relationship of average yearly snow cover duration with mean temperature. This relationship is apparently non‐linear indicating that snow cover duration is especially sensitive to a defined mean temperature range. Secondly, that snow cover can be rather variable from year to year, or over multi‐year phases. This variability has been related to the frequency of synoptic‐scale atmospheric circulation patterns including the North Atlantic Oscillation. These two features are used to contextualise recent and likely future trends in snow cover. It is suggested that there may be different patterns of variability in some mountain areas compared to the adjacent lowlands. This is associated with combined effects of temperature and precipitation during exposure to different air masses. Suggestions are made for improving snow cover observations to further investigate these issues.
... Furthermore, model validation could only be performed for Switzerland since the SWE reference data were restricted to that area. Nevertheless, Hantel and Hirtl-Wielke [33] have shown that snow cover sensitivities are similar throughout the whole Alps. Hence, we assume that the results from our model validation are transferable to an Alpine-wide range, given that the topography of Switzerland covers nearly the whole Alpine elevation range. ...
The recent development of high-resolution climate models offers a promising approach in improving the simulation of precipitation, clouds and temperature. However, higher grid spacing is also a promising feature to improve the simulation of snow cover. In particular, it provides a refined representation of topography and allows for an explicit simulation of convective precipitation processes. In this study we analyze the snow cover in a set of decade-long high-resolution climate simulation with horizontal grid spacing of 2.2 km over the greater Alpine region. Results are compared against observations and lower resolution models (12 and 50 km), which use parameterized convection. The simulations are integrated using the COSMO (Consortium for Small-Scale Modeling) model. The evaluation of snow water equivalent (SWE) in the simulation of present-day climate, driven by the ERA-Interim reanalysis, against an observational dataset, reveals that the high-resolution simulation clearly outperforms simulations with grid spacing of 12 and 50 km. The latter simulations underestimate the cumulative amount of SWE over Switzerland over the whole annual cycle by 33% (12 km simulation) and 56% (50 km simulation) while the high-resolution simulation shows a spatially and temporally averaged difference of less than 1%. Scenario simulations driven by GCM MPI-ESM-LR (2081-2090 RCP8.5 vs. 1991-2000) reveal a strong decrease of SWE over the Alps, consistent with previous studies. Previous studies had found that the relative decrease becomes gradually smaller with elevation, but this finding was limited to low and intermediate altitudes (as a 12 km simulation resolves the topography up to 2500 m). In the current study we find that the height gradient reverses sign, and relative reductions in snow cover increases above 3000 m asl, where important parts of the cryosphere are present. In addition, the simulations project a transition from permanent to seasonal snow cover at high altitudes, with potentially important impacts to Alpine permafrost. This transition and the more pronounced decline of SWE emphasize the value of the higher grid spacing. Overall, we show that high-resolution climate models offer a promising approach in improving the simulation of snow cover in Alpine terrain.
... One of the most widespread impacts of the increasing mean air temperature at the global scale is the cryosphere shrinkage, which is especially evidenced by the ongoing prevalent trends of increasing ice-melting rates and negative glacier mass balances in high mountain environments (Fountain et al. 2012;Huss et al. 2017), the extensive glacier front retreats, and the increasing frequency of glacier extinctions. Additionally, the annual number of days with snow cover is generally decreasing at high latitudes (e.g., Dye and Tucker 2003) and at high altitudes in the Alps (e.g., Hantel and Lucia-Maria 2007;Marty et al. 2017). Thus, this decrease in snow cover also contributes to changes in the hydrological cycle in mountain catchments in terms of thaw anticipation, high glacier ablation rates, and higher water discharges in the glacier streams. ...
The tree-ring stable carbon and oxygen isotope chronologies from two forest sites located in the Forni Glacier forefield (Italy)—one along the glacier stream (GL) and the other toward the valley slope (SL)—were analyzed with the aim of disentangling the precipitation and glacier meltwater inputs in source water δ¹⁸O, as reflected by the tree-ring cellulose δ¹⁸O. The cellulose δ¹⁸O from the GL trees has a negative correlation with winter and summer temperatures, whereas the cellulose δ¹⁸O from the SL trees has a positive correlation with precipitation δ¹⁸O. The isotopic signature of the source water at the GL site is also influenced by waters of glacial origin, as confirmed by the ¹⁸O-depleted glacier meltwater inputs (GMWI_δ¹⁸O) estimated by means of an isotope model. The GMWI_δ¹⁸O values are consistent with the mean difference measured between the δ¹⁸O in the glacier stream and in the precipitation and the winter and summer temperature explains up to 37 percent of the GMWI_δ¹⁸O variance. Our results show an increasing influence of glacier meltwater throughout the past decade for the GL site. Our analysis opens new opportunities to reconstruct changes in water regimes of the glacier streams by means of the tree-ring cellulose δ¹⁸O.
... By contrast, statistical methods infer such relations from 6 observation data. Temperature data in the Alps have been used empirically to evaluate the sensitivity of snow 7 cover to recent and future warming (Hantel et al. 2000;Hantel and Hirtl-Wielke 2007). Similarly, joint 8 temperature/precipitation distributions have been used as proxies for frequency of synoptic weather patterns 9 and thus to infer relative snowiness of winters in the Swiss Alps (e.g. ...
Snow cover is an important indicator of climate change but constraints on observational data quality can limit interpretation of spatial and temporal variability, especially in mountain areas. This issue was addressed using archived data from the Snow Survey of Great Britain to infer key climate relationships which were then used to reference larger‐scale patterns of change. Data analysis using nonlinear (logistic) regression showed average changes in yearly snow cover were strongly related to mean temperature rather than precipitation values. Inferred change shows long‐term decline in average yearly snow cover with greatest declines in some mountain areas, notably in northern England, that can be related to their position on the most temperature‐sensitive segment of the logistic curve. Further declines in snow cover were projected in the future: a central ensemble projection from HadRM3 climate model showed average yearly snow cover predominantly confined to Great Britain mountain areas by the 2050s. However, inter‐annual variability means some years can deviate significantly from average snow cover patterns. Site‐based analysis showed this variability has distinctive geographical variations and different influences for mountains compared to adjacent valleys. Comparison of inter‐annual variability with Lamb weather‐type frequency and North Atlantic Oscillation index shows the influence of large‐scale airflow patterns on snow cover duration. Most notable is the role of northwesterly and northerly flows in explaining snowy years on mountains exposed to that direction, compared to influence of easterly flows at lower levels. Future changes will therefore depend on dominant annual/decadal circulation patterns in addition to long‐term declines from climate warming.
... Greening and browning dynamics in alpine study areas have received substantially less attention than in Arctic and sub-Arctic regions, where multiple field and remote sensing-based studies indicate widespread patterns of recent greening, mostly caused by shrub expansion into tundra (Tape et al 2006. However, there are a number of reasons to expect temporal trends in NDVI in the context of the European Alps, including recent increases in air temperature above the global average increase (Beniston 2005, decreases in snow cover duration (Durand et al 2009b, Hantel andHirt-Wielke 2007), glacier retreat and ensuing plant colonization (Cannone et al 2008), tree line rise and forest expansion (Améztegui et al 2010, Carlson et al 2014, observed increases in species richness plant diversity observed on European summits , Kammer et al 2007 and shifts in alpine land use practices . ...
Les prairies supra-forestières sont des écosystèmes bien représentés dans les milieux de montagne et qui s’avèrent vulnérables aux changements climatiques et aux modalités d’utilisation des terres. Dans ce contexte, l’objectif principal de cette thèse a été d’évaluer l’effet des forçages climatiques et du pastoralisme sur la végétation des prairies supra-forestières à différentes échelles spatio-temporelles. En particulier, nous avons cherché à comprendre les réponses des prairies à la variabilité interannuelle du climat (température et précipitation), aux tendances sur le long terme (réchauffement) et aux évènements extrêmes (vagues de chaleur et sécheresses) ; ainsi qu’aux modalités de la gestion pastorale (charges et calendriers de pâturage). Pour cela, nous avons réalisé des analyses sur un nombre de métriques phénologiques, météorologiques et pastorales. Les premières, dérivées principalement de l’indice de différence normalisée de la végétation (NDVI) à partir d’images satellite de moyenne (MODIS) et de haute résolution (Landsat et SPOT), ainsi que des données acquises au sol à la volée et en continu sur cinq alpages. Les deuxièmes, calculées à partir des ré-analyses du modèle climatique SAFRAN de Météo-France. Les troisièmes, estimées à partir des données des Enquêtes Pastorales régionales (1996-1997 et 2012-2014), et des cahiers d’alpage du dispositif Alpages Sentinelles. Concernant la végétation des prairies supra-forestières, nos résultats mettent en évidence : (i) des tendances au verdissement assez généralisées, (ii) des tolérances plus importantes aux vagues de chaleur qu’aux périodes de sécheresse estivales, (iii) des sensibilités plus importantes aux facteurs climatiques qu’aux pressions de pâturage, (iv) des réponses légères mais positives aux modalités de gestion pastoral, et (v) un potentiel de repousse en fin de saison. L’originalité de nos résultats a été de montrer l’existence de relations plus fortes entre les facteurs climatiques et la végétation des prairies, qu’entre cette dernière et le pâturage. Ils ont également éclairé les apports de l’utilisation de la télédétection dans l’étude de ces milieux.
... As mountain ecosystems are tightly controlled by altitudinal gradients, the effect of climate change is more pronounced here than in the lowlands (Fagre et al. 2007). In general, significant changes to the snowfall and snow-cover pattern, seasonal variation (duration) of snow and winter warming episodes have been reported from all over the world (Hantel and Hirtl-Wielke 2007;Gottfried et al. 2011;Gobiet et al. 2014). Carrion (2002) describes how mountains all over the planet in general witnessed a near-complete shift of dominant vegetation patterns in the Mid-Holocene, and observes that local level transitional changes to vegetation due to climatic forcing can occur at decadal scales. ...
This article analyzes the complex challenges for environmental sustainability of mountain destinations through a case study of the Shiroumadake District of North Japan Alps. The area is known for its scenic peaks including Mount Shirouma, powdery winter snow and the rich variety of alpine wildflowers in summer. However the area has a long history of human habitation and visitation; and its emergence as one of the most famous mountain resorts of Japan has resulted in significant ongoing visitor impact on the landscape. Currently a general warming trend and change of snow conditions threaten this area. The case study adopted a qualitative method based on interviews and content analysis to gain important insight on the complex interrelationship between the biophysical (geological, geomorphological, ecological) and social (mainly tourism) aspects of the area. It was found that while climate change is keenly perceived by local stakeholders due to its threat on livelihoods; anthropogenic fragmentation of geo-ecological connectivity and its transformation over time are poorly understood. Standard management decisions favor stabilization of key geomorphic processes that have shaped the dynamic environment through perpetual change at least since the Holocene deglaciation; such human actions fragment ecological resilience of the place. The article posits that the understanding of the past and key natural change pathways is of critical importance for sustainable future of mountain destinations, and recommends downscaling of economic activities such as large-scale tourism for reducing the level of anthropogenic impact.
... Within the context of global climate change [1,5], temperature rise in the European Alps has been pronounced and accompanied by rising snow lines and earlier melt-out dates [6,7]. Recent studies show that a continuous winter snow pack is becoming increasingly rare in Alpine catchments below 1200 m above sea level (a.s.l.) [8], although snow cover duration above 2000 m a.s.l. has been shown to be less sensitive to changes in air temperature [9]. Over the last few decades, observational studies of mountain vegetation have demonstrated rising tree lines in the Alps and Pyrenees in response to climate warming and land abandonment [10,11] as well as increasing species richness on Europe's temperate alpine summits [12]. ...
The central aim of this thesis is to contribute to current understanding of environmental drivers of plant diversity and productivity as well as of recent changes in vegetation structure in a temperate alpine context, the French Alps. My approach draws on methods from remote sensing and plant ecology by combining plot-based measures of plant diversity and climate data with high-resolution imagery. Chapter I demonstrates the importance of quantifying snow cover duration for predicting patterns of plant taxonomic and functional diversity, and also highlights the ongoing challenge of modeling spatial gross primary productivity dynamics in alpine landscapes. In Chapter II, I explore the utility of satellite imagery for quantifying environmental conditions experienced by alpine plant communities, and further show how metrics of snow cover duration and peak productivity can be used to differentiate habitat for dominant alpine plant communities. I also explore how functional diversity mediates NDVI responses to highly contrasting snow years. Chapter III provides new evidence of recent shifts occurring in high-elevation plant communities in the French Alps in response to climate and land-use change. Analysis of the forest-grassland ecotone in the Vercors Regional Park shows a strong dynamic of forest expansion in response to overall climate warming and local shifts in grazing-related land-use practices, which supports findings from other studies conducted elsewhere in the Alps and Pyrenees. In the second part of Chapter III, for the first time I present evidence of greening dynamics in a protected area of the French Alps, the Ecrins National Park. I propose that a decrease in snow cover duration and pronounced warming occurring in the 1980s likely contributed to increased canopy productivity in high alpine contexts, and are driving long-term greening in the absence of land-use change. Taken collectively, rather than pushing a specific aspect alpine ecology forward, my work helps to fill out our working knowledge of alpine plant communities and serves to solidify a number of field-based observations by carrying out robust spatial analyses.
... Greening and browning dynamics in alpine study areas have received substantially less attention than in Arctic and sub-Arctic regions, where multiple field and remote sensing-based studies indicate widespread patterns of recent greening, mostly caused by shrub expansion into tundra (Tape et al 2006, Myers-Smith et al 2011. However, there are a number of reasons to expect temporal trends in NDVI in the context of the European Alps, including recent increases in air temperature above the global average increase (Beniston 2005, Durand et al 2009a, decreases in snow cover duration (Durand et al 2009b, Hantel andHirt-Wielke 2007), glacier retreat and ensuing plant colonization (Cannone et al 2008), tree line rise and forest expansion (Améztegui et al 2010, Carlson et al 2014, observed increases in species richness plant diversity observed on European summits (Pauli et al 2012, Kammer et al 2007 and shifts in alpine land use practices (Gartzia et al 2016). ...
We combined imagery from multiple sources (MODIS, Landsat-5, 7, 8) with land cover data to test for long-term (1984-2015) greening or browning trends of vegetation in a temperate alpine area, the Ecrins National Park, in the context of recent climate change and domestic grazing practices. We showed that over half (56%) of the Ecrins National Park displayed significant increases in peak normalized difference vegetation index (NDVI max) over the last 16 years (2000-2015). Importantly, the highest proportional increases in NDVI max occurred in rocky habitats at high elevations (> 2500 m a.s.l.). While spatial agreement in the direction of change in NDVI max as detected by MODIS and Landsat was high (76% overlap), correlations between log-response ratio values were of moderate strength (approx. 0.3). In the context of above treeline habitats, we found that proportional increases in NDVI max were higher between 1984 and 2000 than between 2000 and 2015, suggesting a slowing of greening dynamics during the recent decade. The timing of accelerated greening prior to 2000 coincided with a pronounced increase in the amount of snow-free growing degree-days that occurred during the 1980s and 1990s. In the case of grasslands and low-shrub habitats, we did not find evidence for a negative effect of grazing on greening trends, possibly due to the low grazing intensity typically found in the study area. We propose that the emergence of a longer and warmer growing season enabled high-elevation plant communities to produce more biomass, and also allowed for plant colonization of habitats previously characterized by long-lasting snow cover. Increasing plant productivity in an alpine context has potential implications for biodiversity trajectories and for ecosystem services in mountain landscapes. The presented evidence for long-term greening trends in a representative region of the European Alps provides the basis for further research on mechanisms of greening in alpine landscapes.
... The seasonal pattern of warming would play a critical role in determining the kind of new situations that ecosystem experience. For instance, summer and autumn warming may lead to seasonal water limitation; spring warming to early snowmelt (Moran-Tejeda et al. 2014) and upward shift of the snow line in spring; winter warming to episodic events of melting (Gobiet et al. 2014) and shorter snow duration (Hantel and Hirtl-Wielke 2007); summer snowline uplift to a reduced nival belt (Gottfried et al. 2011), and so on. In general, the shift from snow to rain may have amplifying consequences for the hydrological cycle and the natural processes depending on it (Morán-Tejeda et al. 2017). ...
The high mountains have retained a noticeable degree of wilderness even in the most populated regions of the planet. This is the reason why many nature reserves have been established in these landscapes. Currently, climate change and long-range transport of contaminants are affecting those protected areas, and thus conservation priorities may be challenged by these new pressures. In fact, many high mountains hold a legacy of on-site past human activities (e.g., pasturing, forestry, mining), which in some areas may partially persist, even increase, whereas in others are substituted by new uses (e.g., tourism, mountain sport). Therefore, high mountain nature reserves face a challenging future. The conservation goals have to be revised. Former alternative paradigms respectively based on the preservation of wilderness or a traditional cultural landscape will be insufficient. Indeed, global change provides new goals for the high mountain conservation areas as suitable places where to study the nature’s response in the absence of, or combined with, other local pressures. Different branches of sciences may contribute to inform about the changes; however, conservation is ultimately a societal endeavour and thus their goals must be linked to the social demand for a fair society in a sustainable planet. As an added-value to this task, the high mountains hold a large amount of symbolism.
... Temperature is a principal factor influencing snowfall and snowmelt (Karl et al., 1993;Hantel and Hirtl-Wielke, 2007;McCabe and Wolock, 2010) and in turn the snow-covered area and snow mass. In general, snow tends to decrease in response to surface warming (Karl et al., 1993;Dai et al., 2012). ...
Snow change over the Tibetan Plateau may exert a large influence on climate variability in the surrounding regions. However, the characteristics of snow changes at different time scales and the factors for these changes are still not clear. The present study documents linear trends in snow cover and snow water equivalent over the Tibetan Plateau and their relationship to surface air temperature changes during 1979–2006 based on satellite data. The long-term snow variations display a remarkable regional difference and an obvious seasonal dependence. A significant decreasing trend is observed in the western part for snow cover and snow water equivalent in summer and fall and in the southern part for snow cover in all the four seasons. A significant increasing trend is identified in the central-eastern part for snow cover in fall, winter, and spring and in the eastern and far western parts for snow water equivalent in winter and spring. The relationship between snow and surface air temperature changes features regional disparity. The temperature increase is accompanied by snow cover decrease in the southern and western parts, but by snow cover and snow water equivalent increase in the central-eastern part. The reasons for the snow changes vary with the season. The increase in snowmelt following the temperature increase may be the reason for the snow cover decrease in the western and southern parts in summer. The snowfall change induced by vertical motion change appears to be a factor for the snow water equivalent increase in the far western part and the snow cover decrease in the southern part in winter. The increase in snowfall induced by the increase in atmospheric moisture following the temperature increase and the enhanced upward motion may contribute to the snow increase in the eastern part in winter.
... Several approaches, such as the analog method, search for relationships between observed large-scale predictors (generally from reanalyses) and observed local-scale predictands (Vrac et al., 2007a;Dayon et al., 2015). In contrast, model output statistics approaches calibrate model outputs against observations, with various levels of complexity, such as 45 scaling methods (linear scaling, local intensity scaling, variance scaling, ...), delta-change methods (e.g.,Abegg et al., 2007;Hantel and Hirtl-Wielke, 2007;Schmucki et al., 2014) and distribution mapping methods (e.g.,Boe et al., 2007;Déqué, 2007;Gobiet et al., 2015;Olsson et al., 2015). The latter include quantile mapping, which is considered as an efficient and easy to implement adjustment method (Themeßl et al., 2011;Teutschbein and Seibert, 2012;Maurer and Pierce, 2014;50 Gobiet et al., 2015). ...
We introduce the method ADAMONT v1.0 to adjust and disaggregate daily climate projections from a regional climate model (RCM)
using an observational dataset at hourly time resolution. The method uses a refined quantile mapping approach for statistical adjustment and
an analogous method for sub-daily disaggregation. The method ultimately produces adjusted hourly time series of temperature,
precipitation, wind speed, humidity, and short- and longwave radiation, which can in turn be used to force any energy balance land
surface model. While the method is generic and can be employed for any appropriate observation time series, here we focus on the
description and evaluation of the method in the French mountainous regions. The observational dataset used here is the SAFRAN
meteorological reanalysis, which covers the entire French Alps split into 23 massifs, within which meteorological conditions are
provided for several 300 m elevation bands. In order to evaluate the skills of the method itself, it is applied to the
ALADIN-Climate v5 RCM using the ERA-Interim reanalysis as boundary conditions, for the time period from 1980 to 2010. Results of the
ADAMONT method are compared to the SAFRAN reanalysis itself. Various evaluation criteria are used for temperature and precipitation but
also snow depth, which is computed by the SURFEX/ISBA-Crocus model using the meteorological driving data from either the adjusted RCM
data or the SAFRAN reanalysis itself. The evaluation addresses in particular the time transferability of the method (using various
learning/application time periods), the impact of the RCM grid point selection procedure for each massif/altitude band configuration,
and the intervariable consistency of the adjusted meteorological data generated by the method. Results show that the performance of
the method is satisfactory, with similar or even better evaluation metrics than alternative methods. However, results for air
temperature are generally better than for precipitation. Results in terms of snow depth are satisfactory, which can be viewed as
indicating a reasonably good intervariable consistency of the meteorological data produced by the method. In terms of temporal
transferability (evaluated over time periods of 15 years only), results depend on the learning period. In terms of RCM grid point
selection technique, the use of a complex RCM grid points selection technique, taking into account horizontal but also altitudinal
proximity to SAFRAN massif centre points/altitude couples, generally degrades evaluation metrics for high altitudes compared to
a simpler grid point selection method based on horizontal distance.
... Different modelling studies have focused on assessing the impact of climate change on snow cover and extent in different mountains of the world (López-Moreno et al., 2009Bavay et al., 2009Bavay et al., , 2013Lafaysse et al., 2014;Piazza et al., 2014). They also assessed the relationship between the SST, surface air temperature and the large-scale atmospheric variability and snow cover over different regions (Ye and Bao, 2001;Scherrer et al., 2004;Hantel and Hirtl-Wielke, 2007;Seager et al., 2010). However, many discrepancies exist among these models, especially in terms of local snow response to different SST forcings (Ma and Xie, 2013). ...
The end-of-century projection of the snowfall characteristics over the Alps region is studied using the 50-km resolution atmospheric global climate model, HiRAM (high-resolution atmospheric model). The model is forced by three different patterns of projections in the sea surface temperature (SST) in order to assess the sensitivity of snowfall characteristics to theses patterns. It is found that the mean snowfall intensity and frequency is poorly affected by the differences in SST forcing. However, the projections of heavy snowfall events strongly depend on the SST scenario. The changes in temperature and frequency of precipitation and freezing days over the Alps were investigated. We found that these variables did not exhibit a clear dependence to the SST scenario and could not explain the differences observed in snowfall projections. Changes in the moisture transport from the Atlantic Ocean to Europe were found significantly different between each scenario and are assumed to be the main factor affecting the projections of snowfalls, by providing more or less moisture supply.
... Spatio-temporal analysis of altitudinal vegetation shifts, for example, was investigated by Diaz-Varela et al. (2007), while Gottfried et al. (2011) demonstrated the coincidence of the alpine-nival ecotone with the summer snow line. The winter snow line varies considerably under the influence of European temperature fluctuations (Hantel and Hirtl-Wielke, 2007), is located at an average altitude of 640 m and is characterized by an upward shift of approximately 120 m per°C climate warming . ...
Although the European Alps are one of the most investigated regions worldwide, maps depicting climate change by means of climate classification are still not-existent. To contribute to this topic, a time series of very high resolution (30 arc-seconds) maps of the well-known Köppen-Geiger climate classification is presented. The maps cover the greater Alpine region located within the geographical domain of 4 to 19 degrees longitude and 43 to 49 degrees latitude. Gridded monthly data were selected to compile climate maps within this region. Observations for the period 1800–2010 were taken from the historical instrumental climatological surface time series of the greater Alpine region, HISTALP. Projected climate data for the period 2011–2100 were taken, as an example, from the Rossby Centre regional atmospheric model RCA4. Temperature fields were spatially disaggregated by applying the observed seasonal cycle of the environmental lapse rate. The main results of this study are, therefore, 366 observed and predicted (two scenarios) very high resolution Köppen-Geiger climate maps of the greater Alpine region covering the period 1800–2100. Digital data, as well as animated maps, showing the shift of the climate zones are provided on the following website http://koeppen-geiger.vu-wien.ac.at. Furthermore, the relationship between the Köppen-Geiger climate classification and the altitudinal belts of the Alps is demonstrated by calculating the boundaries of the climate zones, i.e. the deciduous forest line, the mixed forest line, the forest and tree line (timber line) and the snow line. The mean altitude of the potential timber line in the greater Alpine region, for example, was calculated to be 1730 m by the end of the 19th century, 1880 m by the end of the 20th century and to lie between 2120 and 2820 m by the end of the 21st century. The latter altitudes were projected for the greenhouse gas scenarios RCP 2.6 (best case) and RCP 8.5 (worst case). The altitude of the timber line (and the other boundaries of the altitudinal belts) is generally higher in the Western Alps, showing a clear west-east slope.
... Such impacts cannot be addressed using delta-change methods, which by definition apply fixed changes to an ob-105 served time series conserving its statistical persistence properties and seasonality (e.g. Abegg et al., 2007;Hantel and Hirtl-Wielke, 2007;Schmucki et al., 2014) although this could evolve significantly under changed climate conditions. ...
We introduce a method – called ADAMONT (ADAptation of RCM outputs to MOuNTain regions) v1.0 – to downscale and adjust daily climate projections from a regional climate model against a regional reanalysis of hourly meteorological conditions using quantile mapping. The method produces adjusted hourly time series of temperature, precipitation, wind speed, humidity, and short- and longwave radiation, which can in turn be used to force any energy balance land surface model. The ADAMONT method is evaluated through its application to the ALADIN-Climate v5 RCM forced by the ERA-Interim reanalysis, compared to the SAFRAN reanalysis, used as the pseudo-observation database covering the entire French Alps split into 23 massifs within which meteorological conditions are provided for several elevation bands separated by 300 m altitude. Different evaluation criteria are analysed for temperature, precipitation, but also snow depth, which is computed by the SURFEX/ISBA-Crocus model using the meteorological driving data generated using this method. The impact of the learning period and of the method used to select neighbouring RCM grid points for each SAFRAN massif/altitude configuration is tested. The performance of the method is satisfying, with similar or even better evaluation metrics than previous literature findings. Results for temperature are generally better than for precipitation. Snow depth yields good results, which can be viewed as indicating a reasonably good inter-variable consistency of the meteorological data produced by the method. The temporal transferability of the method is assessed through the comparison of results obtained using different learning periods, and shows that the method is sensitive to the period considered due to the empirical treatment of values beyond the 99.5 th quantile. The use of a complex RCM grid points selection technique taking into account horizontal but also altitudinal proximity to SAFRAN massif centroids/altitude couples generally degrades evaluation metrics for high altitudes, compared to a simpler 2-dimensional proximity selection technique.
... This rapid warming was also observed in the European Alps (Marty 2008) and has been particularly pronounced in spring (Acquaotta et al. 2015;Rebetez and Reinhard 2008). Warmer temperatures were shown to be the major cause of the shorter snow cover duration in the European Alps (Hantel and Hirtl-Wielke 2007;Scherrer et al. 2004;Serquet et al. 2011). In fact, the reduction of the snow cover duration can be caused either by accelerated snowmelt due to warmer temperatures in spring (Rixen et al. 2012;Wielke et al. 2004) and/or reduced snowfalls during the winter season (Marty and Blanchet 2012;Scherrer et al. 2013). ...
Global warming has strong impacts on snow cover, which in turn affects ecosystems, hydrological regimes and winter tourism. Only a few long-term snow series are available worldwide, especially at high elevation. Here, we analyzed several snowpack characteristics over the period 1970–2015 at eleven meteorological stations, spanning elevations from 1139 to 2540 m asl in the Swiss Alps. Snow cover duration has significantly shortened at all sites, on average by 8.9 days decade−1. This shortening was largely driven by earlier snowmelt (on average 5.8 days decade−1) and partly by later snow onset but the latter was significant in only ~30 % of the stations. On average, the snow season now starts 12 days later and ends 26 days earlier than in 1970. Overall, the annual maximum snow depth has declined from 3.9 to 10.6 % decade−1 and was reached 7.8 ± 0.4 to 12.0 ± 0.4 days decade−1 earlier, though these trends hide a high inter-annual and decadal variability. The number of days with snow on the ground has also significantly decreased at all elevations, in all regions and for all thresholds from 1 to 100 cm. Overall, our results demonstrate a marked decline in all snowpack parameters, irrespective of elevation and region, and whether for drier or wetter locations, with a pronounced shift of the snowmelt in spring, in connection with reinforced warming during this season.
... To proceed in the comparison, neural com-5 puted snow cover thickness values have been binarized setting euristically the threshold to value of 5 cm. This value is a threshold commonly used to define the days with snow on the ground (snow duration) (Hantel and Hirtl-Wielke, 2007). Comparison results have been organized in a confusion matrix in which classes considered are presence and absence of snow. ...
This work investigates learning and generalisation capabilities of radial basis function networks (RBFN) used to solve snow cover thickness estimation model as regression and classification. The model is based on a minimal set of climatic and topographic data collected from a limited number of stations located in the Italian Central Alps. Several experiments have been conceived and conducted adopting different evaluation indexes in both regression and classification tasks. The snow cover thickness estimation by RBFN has been proved a valuable tool able to deal with several critical aspects arising from the specific experimental context.
... Approaches able to conduct such analyses are covering different spatial and temporal scales and a wide range of complexity. Global and regional climate models (GCMs and RCMs) are increasingly used for driving snow models which can be then used for deriving trends in the annual snow water equivalent (SWE) distribution (Dankers and Christensen 2005;Hantel and Hirtl-Wielke 2007;Mellander et al. 2007;Merritt et al. 2006;Rasmus et al. 2004;Uhlmann et al. 2009). RCMs and especially GCMs are usually working on scales from 10? km, which limits their capabilities in view of local impact analysis. ...
Snow cover dynamics in alpine regions play a crucial role in view of the water balance of head water catchments. The temporal storage of water in form of snow and ice leads to a decoupling of precipitation and runoff. Changes in the volume and the temporal dynamics of the snow storage lead to modified runoff regimes and can influence the frequency of low flow events and floods. For a better estimation of the possible range and direction of future changes, projection runs can be realized by using process-based models. In this study, the Cold Regions Hydrological Modelling platform (CRHM) is used to compile such a model for simulating the snow cover development within research catchment Zugspitze (RCZ; 11.4 km2/Germany). Therefore, the catchment is divided into four hydrological response units (HRUs), able to cover the physiographic characteristics in four elevation zones. The model is evaluated over snow depth measurements. The range of variability within and differences between the HRUs are analyzed, and future projections (2001–2100) are performed on the basis of three different WETTREG realizations. It could be shown that CRHM is able to reproduce the snow cover dynamics very well and that the ongoing climate change does have an identifiable influence on the average extent and size of the snow storage. Furthermore, it could be shown that variations in snow cover dynamics within the RCZ are strongly connected to NAO.
... Within the context of global climate change [1,5], temperature rise in the European Alps has been pronounced and accompanied by rising snow lines and earlier melt-out dates [6,7]. Recent studies show that a continuous winter snow pack is becoming increasingly rare in Alpine catchments below 1200 m above sea level (a.s.l.) [8], although snow cover duration above 2000 m a.s.l. has been shown to be less sensitive to changes in air temperature [9]. Over the last few decades, observational studies of mountain vegetation have demonstrated rising tree lines in the Alps and Pyrenees in response to climate warming and land abandonment [10,11] as well as increasing species richness on Europe's temperate alpine summits [12]. ...
We investigated snow cover dynamics using time series of moderate (MODIS) to high (SPOT-4/5, Landsat-8) spatial resolution satellite imagery in a 3700 km2 region of the southwestern French Alps. Our study was carried out in the context of the SPOT (Take 5) Experiment initiated by the Centre National d’Etudes Spatiales (CNES), with the aim of exploring the utility of high spatial and temporal resolution multispectral satellite imagery for snow cover mapping and applicationsin alpine ecology. Our three objectives were: (i) to validate remote sensing observations of first snow free day derived from the Normalized Difference Snow Index (NDSI) relative to ground-based measurements; (ii) to generate regional-scale maps of first snow free day and peak standing biomass derived from the Normalized Difference Vegetation Index (NDVI); and (iii) to examine the usefulness of these maps for habitat mapping of herbaceous vegetation communities above the tree line. Imagery showed strong agreement with ground-based measurements of snow melt-out date, although R
2 was higher for SPOT and Landsat time series (0.92) than for MODIS (0.79). Uncertainty surrounding
estimates of first snow free day was lower in the case of MODIS, however (˘3 days as compared to ˘9 days for SPOT and Landsat), emphasizing the importance of high temporal as well as high spatial resolution for capturing local differences in snow cover duration. The main floristic differences between plant communities were clearly visible in a two-dimensional habitat template defined by the first snow free day and NDVI at peak standing biomass, and these differences were accentuated when axes were derived from high spatial resolution imagery. Our work demonstrates the enhanced potential of high spatial and temporal resolution multispectral imagery for quantifying snow cover duration and plant phenology in temperate mountain regions, and opens new avenues to examine to what extent plant community diversity and functioning are controlled by snow cover duration.
... Mountain snowpacks are expected to accumulate less snow in response to warming air temperatures as the fraction of precipitation that falls as snow decreases (e.g. Abatzoglou, 2011;Abatzaglou et al., 2014;Groisman et al., 2004;Hamlet et al., 2005;Hantel and Hirtl-Wielke, 2007;Knowles et al., 2006;Lettenmaier and Gan, 1990;Luce et al., 2014a;Mote, 2006;Mote et al., 2005;Mote, 2003;Pierce et al., 2008;Woods, 2009). ...
Path analyses of historical streamflow data from the Pacific Northwest indicate that the precipitation amount has been the dominant control on the magnitude of low streamflow extremes compared to the air temperature-affected timing of snowmelt runoff. The relative sensitivities of low streamflow to precipitation and temperature changes have important implications for adaptation planning because global circulation models produce relatively robust estimates of air temperature changes but have large uncertainties in projected precipitation amounts in the Pacific Northwest. Quantile regression analyses indicate that low streamflow extremes from the majority of catchments in this study have declined from 1948 to 2013, which may significantly affect terrestrial and aquatic ecosystems, and water resource management. Trends in the 25th percentile of mean annual streamflow have declined and the center of timing has occurred earlier. We quantify the relative influences of total precipitation and air temperature on the annual low streamflow extremes from 42 stream gauges using mean annual streamflow as a proxy for precipitation amount effects and streamflow center of timing as a proxy for temperature effects on low flow metrics, including 7q10 summer (the minimum 7-day flow during summer with a 10-year return probability), mean August, mean September, mean summer, 7q10 winter, and mean winter flow metrics. These methods have the benefit of using only readily available streamflow data, which makes our results robust against systematic errors in high elevation distributed precipitation data. Winter low flow metrics are weakly tied to both mean annual streamflow and center of timing.
... However, snow cover sensitivity to precipitation and temperature changes is highly related to topographic features such as elevation, aspect and terrain shading. For example, snow duration at mid and low altitudes has shown to be more susceptible to temperature increases in the twentieth century (Laternser and Schneebeli 2003;Beniston et al. 2003a;Scherrer et al. 2004;Wielke et al. 2004;Hantel and Hirtl-Wielke 2007;Hantel and Maurer 2011). Similarly, climate projections in Alpine areas expect a reduction of maximum snow water equivalent (Beniston et al. 2003b;Martin and Etchevers 2005;Bavay et al. 2009;Brown and Mote 2009), changes in the accumulation timing (Beniston et al. 2003b;Bavay et al. 2009) and a shortening of the snow cover season (Beniston et al. 2003a) affecting especially mid and low elevations (see Gobiet et al. (2013) for an up-to-date review). ...
Snow cover maps from Earth Observation (EO) satellites are valuable datasets containing large-scale information on snow cover extent, snow cover distribution and snow cover duration. In evaluating the performances of Regional Climate Models, EO data can be a valid piece of information alternative to in-situ measurements, which require a dense network of stations covering the entire altitudinal range and techniques for interpolating the values. In this context, MODIS snow products play a leading role providing several types of snow cover maps with high spatial and temporal resolutions. Here, we assess snow cover outputs of a high resolution Regional Climate Model (RCM) using MODIS maps of snow covered area over the Po river basin, northern Italy. The dataset consists of 9 years of MODIS data (2003–2011) cleaned from cloud cover by means of a cloud removal procedure. The maps have 500 m spatial resolution and daily temporal resolution. The RCM considered is COSMO-CLM, run at 0.0715° resolution (about 8 km) and coupled with the soil module TERRA_ML. The ERA-Interim reanalyses are used as initial and boundary conditions. The results show a good agreement between observed and simulated snow cover duration and extension. COSMO-CLM is able to reproduce the inter-annual variabilities of snow cover features as well as the seasonal trend of snow cover duration and extension. Limitations emerge when the RCM simulates the progressive depletion of the snow cover in spring. Simulated snowmelt occurs faster than the observed one. Then, we investigate the influence of the spatial resolution of the climate model. The simulation at 0.0715° (about 8 km) is compared to a simulation performed at 0.125° (about 14 km). The comparison highlights the benefits provided by the higher spatial resolution in the accumulation season, reflecting the improvements obtained in temperature and precipitation fields.
... The effects of climate change will impact all ecosystems from the plant species to the microorganism community. An increase in temperature which exceeds the global average has been reported in the Alpine region (Rebetez and Reinhard 2008), and its consequences can be seen in glacier retreat and changes in snow-cover duration (Hantel and Hirtl-Wielke 2007). Plant species growing at high altitude will Communicated by Z. Kaya ...
Alpine regions represent an interesting biome for studying local adaptation in forest trees. Strong genetic differentiation is expected along elevational gradients in spite of extensive gene flow. We sampled 18 and 20 natural populations of Pinus cembra and Pinus mugo, in two subregions and four elevational gradients. To investigate the effects of elevation on genetic diversity and adaptation, 768 and 1152 single nucleotide polymorphisms (SNPs) were genotyped in P. cembra and P. mugo. We found low but significant genetic differentiation among populations in both species. To discover outliers, we applied Bayesian simulation and hierarchical island model analyses. A larger number of outliers were found using the first method. Some SNPs were detected with both analyses: one SNP in P. cembra and three in P. mugo when using two subregions and four SNPs in P. cembra and one in P. mugo when using four elevational gradients. The association between environmental and genetic variation was tested with Bayesian simulation (Bayenv) and a latent factor mixed model (LFMM). The first method, using all populations, detected 6 and 20 SNPs associated to temperature in P. cembra and in P. mugo, respectively, 3 SNPs associated to precipitation in P. cembra, and 14 SNPs to elevation in P. mugo. The LFMM found a higher number of SNPs associated to temperature in P. mugo than in P. cembra (37 vs. 27), with a stronger association with maximum temperature (April–June). In P. cembra, the majority of associations (51 SNPs) were found with precipitation (January–March). Five SNPs in common between species were found on genes potentially involved in plant response to abiotic stress. Using these results, we confirmed that temperature was an important driver of adaptive potential for each species so that continued changes to global temperatures will likely involve continued adaptation as ranges shift upwards.
Global climate change gives rise to changing spatial patterns of snow and ice, especially over mountain blocks where orographic and synoptic circulation effects play significant roles in creating patterns of precipitation and glacier development. The presence of snow and ice results in heat balance changes and other land surface feedbacks that have implications for patterns of mountain glacier retreat and the dynamics of mountain geomorphic systems. This study considers the sensitivity of the mountain cryosphere (snow, ice, permafrost) to global climate change, and the implications of this sensitivity analysis for evaluating mountain surface stability, geomorphic change and the generation of mountain geohazards. Consideration of these issues is informed by evidence from case studies reported in the literature and by field observations of mountain system dynamics worldwide. Results show that ‘sensitivity’ to climate forcing has been interpreted and defined in different ways in mountain snow, ice and permafrost systems, with respect to properties such as albedo, mass balance or rapidity of system change. There are also significant spatial differences in sensitivity between different mountain blocks for snow, ice and permafrost, and these regions are therefore likely to follow different trajectories of geomorphic change in response to climate forcing, related to their physiographic properties and the extent of cryospheric coverage. Within glaciated mountains in particular, the relative timing of different geomorphic events, and the interplay between slope, glacier front and proglacial sediment sources and environments, may vary depending on glacier size, geomorphic setting and microclimate. By contrast, responses to permafrost warming (increased surface instability and mass movements) and changes in snow patterns (avalanche risk, floods) may have quite different spatial and temporal patterns and influenced by different environmental controls. An integrated evolutionary model for mountain system development under a changing cryosphere is proposed, highlighting the critical role of energy balance as a forcing factor that then triggers downstream mountain system responses. This suggests that different elements of mountain systems exhibit different sensitivities, and furthermore that these sensitivities change over time and space through the period of anthropogenic global warming and paraglacial relaxation.
Ice is critical within the Earth system in its role in modifying land surface albedo and therefore Earth's radiative heat balance. While many studies have examined cryospheric impacts on heat balance (sensitivity), these results vary significantly, depending on model setup. This study examines the climate sensitivity of different elements of Earth's cryospheric system, as revealed in the literature, and seeks explanation for the radiative behavior of these different elements through examining the different properties and dynamics of these elements. Thus, an understanding of cryospheric sensitivity is set within an Earth systems context. This allow for a better understanding of equilibrium rather than transient climate sensitivity, especially under global climate change.
This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region.
Recommendations for resource managers
• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.
Straipsnyje vertinami palydovinės informacijos apie teritorijos padengtumą sniegu trūkių užpildymo metodai. Buvo naudojami dviejų NASA palydovų Terra ir Aqua bei Lietuvos meteorologijos stočių tinklui priklausančių stočių sniego dangos duomenys 2013–2016 m. spalio–balandžio mėnesiais. Naudojant du skirtingus būdus (pirmyn ir atgal) buvo užpildyti palydovinių sniego dangos duomenų sekų trūkiai, atsirandantys dėl ištisinio debesuotumo. Gauti dydžiai palyginti su Lietuvos meteorologijos stotyse nustatytu dienų su sniego danga skaičiumi. Analizuojamu 2013–2016 m. laikotarpiu šaltojo sezono mėnesiais palydovinių duomenų trūkiai sudarė 60 % nuo bendro dienų skaičiaus. 2013–2016 m. žiemomis vidutinis dienų su sniego danga skaičius Lietuvos meteorologijos stotyse buvo 47. Remiantis Terra palydovo duomenis, šis dydis buvo 44 dienos, o pagal Aqua perduotą informaciją – 55 dienos. Kiek didesnis dienų su sniego danga skaičius nustatytas trūkius užpildžius pirmyn metodu, tačiau skirtumas yra nedidelis ir abiejų palydovų duomenys neviršija vienos dienos. Vidutiniškai sezoninis dienų su sniego danga skaičius, nustatytas remiantis palydovų duomenimis, nuo išmatuoto atskirose meteorologijos stotyse skiriasi 9 dienomis pagal Terra ir 13 dienų pagal Aqua palydovo duomenis. Dažni atodrėkiai, sniego dangos fragmentacija ir didelis debesuotumas lėmė nemažus skirtumus tarp palydovinės bei meteorologijos stočių informacijos.
The Alps play a vital role in the water supply of the region through the rivers Danube, Rhine, Po and Rhone while they are crucial to the ecosystem. Over the past two centuries, we witnessed the temperature to increase by +2 degrees, which is approximately three times higher than the global average. Under this study, the Alps are analyzed using regional climatic models for possible projections in order to understand the climatic changes impact on the water cycle, particularly on runoff. The scenario is based on assumptions of future greenhouse gases emissions. The regional model results show the consistent warming trend in the last 30-year span: temperature in winter may increase by 3 to 4.5°C and summers by 4 to 5.5°C. The precipitation regime may also be altered: increasing about 10-50% in winter and decreasing about 30-60% in summer. The changes in the amount of precipitation are not uninformed. Differences are observed particularly between the North West and South East part of the Alps. Due to the projected changes in alpine rainfall and temperature patterns, the seasonality of alpine flow regime will also be altered: massive rise will occur in winter and a significant reduction in summer. The typical low flow period during winter will also be shifted to late summer and autumn.
Purpose
This paper examines the impact of global warming and climate change on skiing by assessing the costs that ski resorts would have to bear in order to address the lack of snow. In this way new development models can be hypothesized for the regional economy in the Aosta Valley, territory located in the West Alps whose economy is largely based on winter tourism.
Design/methodology/approach
Starting with a literature review regarding global warming and its effects on the Alps, a methodology of analysis has been implemented in order to assess the relative weaknesses of ski resorts. Additional costs in adaptation strategies have been considered in the light of a major choice ski resorts must face: investing or not. For this analysis, four scenarios of global warming have been taken into consideration.
Findings
The lack of snow due to a rise in temperatures will have a big impact on regional ski resorts and will seriously threaten the economy of small lateral valleys. In this scenario, it is important to think about reorganizing the regional ski supply by focusing on stations with better economic results and those strategically well located. In this way, we can safeguard winter tourism in the region and preserve skiing by concentrating costs only in those resorts that are also able to bear new cost adaptation strategies.
Originality/value
The value of this paper is its estimation of the future impact of a rise in the average temperature in regional ski resorts. This impact is assessed in relation to concerns about the reduction of the skiing area and the new costs that ski companies will need to bear. The paper also proposes a new model for the reorganization of the ski supply in the Aosta Valley.
We introduce the method ADAMONT v1.0 to adjust and disaggregate daily climate projections from a regional climate model (RCM) using an observational dataset at hourly time resolution. The method uses a refined quantile mapping approach for statistical adjustment and an analogous method for sub-daily disaggregation. The method ultimately produces adjusted hourly time series of temperature, precipitation, wind speed, humidity, and short- and longwave radiation, which can in turn be used to force any energy balance land surface model. While the method is generic and can be employed for any appropriate observation time series, here we focus on the description and evaluation of the method in the French mountainous regions. The observational dataset used here is the SAFRAN meteorological reanalysis, which covers the entire French Alps split into 23 massifs, within which meteorological conditions are provided for several 300 m elevation bands. In order to evaluate the skills of the method itself, it is applied to the ALADIN-Climate v5 RCM using the ERA-Interim reanalysis as boundary conditions, for the time period from 1980 to 2010. Results of the ADAMONT method are compared to the SAFRAN reanalysis itself. Various evaluation criteria are used for temperature and precipitation but also snow depth, which is computed by the SURFEX/ISBA-Crocus model using the meteorological driving data from either the adjusted RCM data or the SAFRAN reanalysis itself. The evaluation addresses in particular the time transferability of the method (using various learning/application time periods), the impact of the RCM grid point selection procedure for each massif/altitude band configuration, and the intervariable consistency of the adjusted meteorological data generated by the method. Results show that the performance of the method is satisfactory, with similar or even better evaluation metrics than alternative methods. However, results for air temperature are generally better than for precipitation. Results in terms of snow depth are satisfactory, which can be viewed as indicating a reasonably good intervariable consistency of the meteorological data produced by the method. In terms of temporal transferability (evaluated over time periods of 15 years only), results depend on the learning period. In terms of RCM grid point selection technique, the use of a complex RCM grid points selection technique, taking into account horizontal but also altitudinal proximity to SAFRAN massif centre points/altitude couples, generally degrades evaluation metrics for high altitudes compared to a simpler grid point selection method based on horizontal distance.
The topographical heterogeneity of mountain landscapes and the associated species turnover over short distances should prompt us to examine the relationships between climate and mountain plant distribution at a much finer scale than is commonly done. Here, I focused on the root zone temperature experienced by low-stature perennial-dominated plant communities of temperate mountains, which are seasonally covered by snow. Based on the analysis of multi-annual recordings of ground temperatures across a broad spectrum of plant communities, I propose a habitat template using Growing Degree Days (GDD) and Freezing Degree Days (FDD). These two indices summarize soil thermal conditions experienced during the favorable and the unfavorable period for growth. This heuristic framework allows refining our working hypotheses on the range shifts of mountain plants in response to recent and future climate change. Regional trends in climate variables controlling GDD and FDD indicate that the combination of earlier snow melt-out and higher summer temperatures have led to an overall increase in GDD over the last decades. However the persistence of cold episodes in spring and in fall along with the shorter snow coverage suggest that the positive effect of an extended growing season might be counteracted by the detrimental effects of increasing FDD. I thus hypothesize (i) a local-scale, downward shift of plant species along mesotopographical gradients, with marked species infilling in sparsely vegetated, long-lasting snow patches that contain vacant niches and (ii) a watershed-scale upward shift of subalpine species inhabiting south-exposed grasslands and able to cope with moderate FDD. This perspective challenges the simplistic view of an overall range shift of mountain plants along elevational gradients and calls for the improvement of models of snow cover dynamics and root zone temperature to draw up realistic scenarios of mountain vegetation changes under a warmer climate.
Study region: The hydropower reservoir of Gigerwald is located in the alpine valley Calfeisental in eastern Switzerland. The lake is fed by runoff from rain, snow melt and ice melt from a few small glaciers, as well as by water collected in a neighbouring valley.
Study focus: Water resources in the Alps are projected to undergo substantial changes in the coming decades. It is therefore essential to explore climate change impacts in catchments with hydropower facilities. We present a multi-dataset calibration (MDC) using discharge, snowcover data and glacier mass balances for an ensemble of hydrological simulations performed using the Hydrologiska Byråns Vattenbalansavdelning (HBV)-light model. The objective is to predict the future changes in hydrological processes in the catchment and to assess the benefits of a MDC compared to a traditional calibration to discharge only.
New hydrological insights for the region: We found that the annual runoff dynamics will undergo significant changes with more runoff in winter and less in summer by shifting parts of the summer melt runoff to an earlier peak in spring. We furthermore found that the MDC reduces the uncertainty in the projections of glacial runoff and leads to a different distribution of runoff throughout the year than if calibrated to discharge only. We therefore argue that MDC leads to more consistent model results by representing the runoff generation processes more realistically.
In the French South of the Alps the temperatures are going to increase during XXIth century. To know to what extent this reheating will echo in fine spatial scale locally on every ski slopes, this article suggests studying the evolution of the height of the isotherm 0°C between 1961-1990, 2021-2050 and 2071-2100 according to the scenarios A1B, B1 and A2. By means of the climatic outputs of ALADIN-Climat at 12 km of resolution a step of downscaling statistics based on the multiple regression allows to simulate the temperatures at 25 m of resolution. The results show a clear rise of 250 to 350 m of height of the isotherm 0°C for monthly mean temperatures from December till March for half of the century and until 600 m for the end of the Century. MOTS-CLES : modélisation climatique, descente d'échelle statistique, températures moyennes mensuelles, stations de ski.
Changes to the North American (NA) snow packs for 1979-2004 were detected from snow water equivalent (SWE) retrieved from SMMR and SSM/I passive microwave data using the non-parametric Kendall's test. In NA, about 30% decreasing trends in SWE for 1979-2004 are statistically significant, or about three times more than significant increasing trends of SWE. Significant decreasing trends in SWE are more extensive in Canada than in the USA. The overall mean trend magnitudes are about -0.4 to -0.5 mm/year, which translates to an overall reduction of snow depth of about 5-6 cm in 26 years. From detected increasing (decreasing) trends of gridded temperature (precipitation) based on the North American Regional Reanalysis (NARR) and the University of Delaware data set for NA, and their respective correlations with SWE data, it seems that the extensive decreasing trends in SWE detected mainly in Canada are caused more by increasing temperatures than by decreasing precipitation.
In a previous study Pons et al. (Clim Res 54(3):197–207, 2010. doi:10.3354/cr01117g) reported a significant decreasing trend of snowfall occurrence in the Northern Iberian Peninsula since the mid 70s. The study was based on observations of annual snowfall frequency (measured as the annual number of snowfall days NSD) from a network of 33 stations ranging from 60 to 1350 m. In the present work we analyze the skill of Regional Climate Models (RCMs) to reproduce this trend for the period 1961–2000 (using both reanalysis- and historical GCM-driven boundary conditions) and the trend and the associated uncertainty of the regional future projections obtained under the A1B scenario for the first half of the twenty-first century. In particular, we consider the regional simulation dataset from the EU-funded ENSEMBLES project, consisting of thirteen state-of-the-art RCMs run at 25 km resolution over Europe. While ERA40 severely underestimates both the mean NSD and its observed trend (−2.2 days/decade), the corresponding RCM simulations driven by the reanalysis appropriately capture the interannual variability and trends of the observed NSD (trends ranging from −3.4 to −0.7, −2.1 days/decade for the ensemble mean). The results driven by the GCM historical runs are quite variable, with trends ranging from −8.5 to 0.2 days/decade (−1.5 days/decade for the ensemble mean), and the greatest uncertainty by far being associated with the particular GCM used. Finally, the trends for the future 2011–2050 A1B runs are more consistent and significant, ranging in this case from −3.7 to −0.5 days/decade (−2.0 days/decade for the ensemble mean), indicating a future significant decreasing trend. These trends are mainly determined by the increasing temperatures, as indicated by the interannual correlation between temperature and NSD (−0.63 in the observations), which is preserved in both ERA40- and GCM-driven simulations.
Daily snow water equivalent records from the snowpack telemetry archive are used to assess spatiotemporal characteristics of large snowfall events over the montane western United States. The largest mean annual (leading) events are found in the Pacific Northwest and Sierra Nevada. The mean leading event lasting up to 72 hours typically accounts for 10-23% of the water equivalent of annual snowfall, with the largest contribution in the Arizona/New Mexico sector. For most of the West, snowfall events in the top quartile of station distributions are most common during midwinter, but those for the Rocky Mountain states and Utah are more common during late winter or spring. Colorado also shows a secondary peak in large events during November. Large midwinter snowfall events in the marine sectors, Idaho, and Arizona/New Mexico are spatially coherent in that when observed at one station, they tend to occur at surrounding stations. Large events are less spatially coherent for drier inland regions. When annual snowfall is anomalously positive, there tends to be an increase in the number of snow days as well as a shift in the distributions toward the larger event sizes. Opposite relationships are observed for negative annual snowfall anomalies. These findings are in accord with recent studies using lower elevation data, demonstrating that the probability of extreme precipitation events is altered during El Nino or La Nina conditions.
The Climate Change 2001 volumes of the Third Assessment Report of the IPCC provide the most comprehensive assessment of climate change since its second report, Climate Change 1995. This Synthesis Report gives a comprehensive summary of the main points of the three separate volumes of the Report: The Scientific Basis; Impacts, Adaptation, and Vulnerability; and Mitigation.
Nivo-meteorological data from six daily recording stations located in the Italian Alps (three in the Piedmont Region, to the West, and three in the Dolomites, to the East), operating since 1991 and representative for quite large areas, have been analysed in order to point out nivometric regimes. The data gathered were also used to infer time and space distribution of parameters (thickness of snow cover, wind intensity, air humidity, amount of liquid precipitation and daily minimum, average and maximum air temperature) affecting skiability, and therefore influencing the touristic potential of alpine area.
German
Zur Bestimmung von nivometrischen Regimes wurden Schneedaten analysiert, die seit 1991 an sechs alpinen Stationen in Italien (drei westliche im Piedmont, und drei östliche in den Dolomiten) gemessen werden und jeweils relativ große Gebiete repräsentieren. Die gesammelten Daten wurden außerdem verwendet, um die raum-zeitliche Verteilung von Parametern zu charakterisieren, die die Schneebedingungen beeinflussen (Dicke der Schneedecke, Windstärke, Luftfeuchte, Flüssig-Niederschlagsmenge und die täglichen Minimum-, Maximum- und Durchschnittstemperaturen). Diese Variablen sind mitbestimmend für die Wintersportbedingungen und damit für das touristische Potential.
The seasonal snow cover fluctuates from year to year both in amount and duration. These fluctuations are mainly due to climate noise. The relation between the observed duration of snow cover, temperature and station height has been studied quantitatively. A statistical model that has been originally developed for estimating the sensitivity over Austria has been thoroughly tested before it has been applied to the Swiss data. The records of 59 Swiss stations between 273 and 3580 m above sea level for the years 1961 to 1990 have been used in order to estimate the sensitivity of the snow cover duration to possible climate changes. We assume that the number of snow days N at a station depends on the seasonal mean European Temperature T. As sensitivity we define s = dn=dT with n = N=N0 the relative duration of snow cover. We expect that s is small for stations at low levels ('never snow') as well as for stations at very high levels ('always snow'). At intermediate levels where many skiing areas are located the sensitivity is relatively large. For the interpolation of this relationship any logistic function can be chosen, e.g. the tangenshyperbolic function. The unknown parameters of this function, s0 and T0 i.e. the temperature where s is largest, are fitted for the data set of a single station. The sensitivity is negative everywhere and adopts its (negative) maximum at n = 0:5.
An investigation of change in snow cover (maximum depth and snow cover duration) over the 1931-2000 period was carried out at sixteen climate stations located in mountainous areas of Bulgaria. The mountain climate has been characterized by widespread warming and decreased winter precipitation over this period. However, there was no evidence of similar large-scale reductions in snow depth or snow cover duration: some sites showed significant decreases in snow cover, some no change, while others showed significant increases. Further analysis is required to understand the reasons for the varied response of snow cover to a changing climate
The mean snow depth, the duration of continuous snow cover and the number of snowfall days in the Swiss Alps all show very similar trends during the observation period 1931–99: a gradual increase until the early 1980s (with insignificant interruptions during the late 1950s and early 1970s) followed by a statistically significant decrease towards the end of the century. Regional and altitudinal variations are large; high altitudes show only slight changes, and the trends become more pronounced at mid and low altitudes. At any particular time the southern part of the Alps often has different conditions than the north. Shorter snow duration is mainly caused by earlier snow melting in spring than by later first snowfalls in autumn.
Trends for heavy snowfall events are somewhat different: at elevations above 1300 m a.s.l. a very weak increasing trend towards heavier snowfalls has persisted since the 1960s, and only low altitudes below 650 m a.s.l. show a marked drop since the early 1980s, indicating that heavy winter precipitation to an increasing degree falls in the form of rain instead of snow.
A literature review confirms that, throughout the temperate and subpolar Northern Hemisphere, a similar general pattern of temporal snow variations occurred during the 20th century. Copyright
¶In many instances, snow cover and duration are a major controlling factor on a range of environmental systems in mountain
regions. When assessing the impacts of climatic change on mountain ecosystems and river basins whose origin lie in the Alps,
one of the key controls on such systems will reside in changes in snow amount and duration. At present, regional climate models
or statistical downscaling techniques, which are the principal methods applied to the derivation of climatic variables in
a future, changing climate, do not provide adequate information at the scales required for investigations in which snow is
playing a major role. A study has thus been undertaken on the behavior of snow in the Swiss Alps, in particular the duration
of the seasonal snow-pack, on the basis of observational data from a number of Swiss climatological stations. It is seen that
there is a distinct link between snow-cover duration and height (i.e., temperature), and that this link has a specific “signature”
according to the type of winter. Milder winters are associated with higher precipitation levels than colder winters, but with
more solid precipitation at elevations exceeding 1,700–2,000 m above sea-level, and more liquid precipitation below. These
results can be combined within a single diagram, linking winter minimum temperature, winter precipitation, and snow-cover
duration. The resulting contour surfaces can then be used to assess the manner in which the length of the snow-season may
change according to specified shifts in temperature and precipitation. While the technique is clearly empirical, it can be
combined with regional climate model information to provide a useful estimate of the length of the snow season with snow cover,
for various climate-impacts studies.
Uses a model of snow-cover duration, an observed climate data set for the Australian alpine area, and a set of regional climate-change scenarios to assess quantitatively how changes in climate may affect snow cover in the Australian Alps. The model provides a reasonable simulation of the sensitivities of snow-cover duration to changes in temperature and precipitation in the Australian Alps. The input climate data are then modified in line with scenarios of regional climate change for the years 2030 and 2070. Under the best case scenario for 2030, simulated average snow-cover duration and the frequency of years of more than 60 days cover decline at all sites considered. However, at the higher sites (eg more than 1700 m) the effect is not very marked. For the worst case scenario, a much more dramatic decline in snow conditions is simulated. At higher sites, simulated average snow cover duration rougly halves by 2030 and approaches zero by 2070. At lower sites (around 1400 m), near zero average values are simulated by 2030 (compared to durations of around 60 days for current climate).
Instrumental observations and reconstructions of global and hemispheric temperature evolution reveal a pronounced warming during the past approximately 150 years. One expression of this warming is the observed increase in the occurrence of heatwaves. Conceptually this increase is understood as a shift of the statistical distribution towards warmer temperatures, while changes in the width of the distribution are often considered small. Here we show that this framework fails to explain the record-breaking central European summer temperatures in 2003, although it is consistent with observations from previous years. We find that an event like that of summer 2003 is statistically extremely unlikely, even when the observed warming is taken into account. We propose that a regime with an increased variability of temperatures (in addition to increases in mean temperature) may be able to account for summer 2003. To test this proposal, we simulate possible future European climate with a regional climate model in a scenario with increased atmospheric greenhouse-gas concentrations, and find that temperature variability increases by up to 100%, with maximum changes in central and eastern Europe.
Climatology is, to a large degree, the study of the statistics of our climate. The powerful tools of mathematical statistics therefore find wide application in climatological research. The purpose of this book is to help the climatologist understand the basic precepts of the statistician's art and to provide some of the background needed to apply statistical methodology correctly and usefully. The book is self contained: introductory material, standard advanced techniques, and the specialised techniques used specifically by climatologists are all contained within this one source. There are a wealth of real-world examples drawn from the climate literature to demonstrate the need, power and pitfalls of statistical analysis in climate research. Suitable for graduate courses on statistics for climatic, atmospheric and oceanic science, this book will also be valuable as a reference source for researchers in climatology, meteorology, atmospheric science, and oceanography.
In both regions there is a consistent linear relationship between altitude and duration of snow cover. Based on that relationship the estimated area of land covered by snow for an average of 90 days each winter is 41 times as great in Switzerland as in mainland Australia. -from Authors
There are over 100 high summits in the Alps for which historical (>40 years) records on vascular plant species richness exist. The earliest summit record is from Piz Linard, a nival summit of 3411 m a.s.l. in SE Switzerland, from the year 1835 (Herr 1866). The majority of these summits exceed 3000 m, reaching the subnival belt above the closed alpine grassland, or the nival belt above the climatic snow line. A comparison of early (Braun-Blanquet 1957, 1955) and recent (Hofer 1992; Gottfried et al. 1994; Grabherr et al. 1994, 1995, 2001; Pauli et al. 1996) re-investigations provided evidence for an upward migration of vascular plants on many of these summits.
Climate changes revealed by trends in snow cover duration and surface albedo over the whole snowy season for Estonian territory are studied. An indirect method is used for deducing surface albedo from snow cover duration. Approximate values for the monthly albedo have been derived from the snow cover data for some 100 spots from 1962 to 1995. As indicators of climate changes, the time series of mean areal values and standard deviations of snow cover duration and surface albedo have been considered. It is concluded that for this period the snow cover duration bind surface albedo have substantially decreased and their areal variability in Estonia have increased.
The Climate Change 2001 volumes of the Third Assessment Report of the
IPCC provide the most comprehensive assessment of climate change since
its second report, Climate Change 1995. This Synthesis Report gives a
comprehensive summary of the main points of the three separate volumes
of the Report: The Scientific Basis; Impacts, Adaptation, and
Vulnerability; and Mitigation.
Historical fluctuations of North American snow extent from November
through March are reconstructed back to 1900 using a combination of
satellite and station observations. Using results of principal
components analyses (PCA) from a companion study (Frei, A. and Robinson,
D.A. Int. J. Climatol., this volume), simple and multiple linear
regression models are used to take advantage of the spatial coverage of
satellite observations and the temporal extent of station observations.
This analysis more than triples the remotely-sensed record length, which
begins in 1972.Model results indicate that North American winter snow
extent tended to increase between the 1930s and around 1980, followed by
a subsequent decrease during the 1980s. Long-term trends during November
are less dramatic, with small increases since the 1960s. During March a
different signal is observed, with snow extent decreasing since the
1950s. These results suggest a possible shift in the snow
season.Historical signals from smaller regions within North America are
identified during December and January. During December, the
continental-scale signal is driven mainly by fluctuations over the
western US, while January fluctuations are more strongly driven by an
eastern signal. Models are sufficiently accurate to estimate changes in
interannual variability over North America only during February, as well
as over the eastern portion of the continent during December and
January. Continental-scale interannual variability during February has
been high since the mid-1970s compared to any previous time this decade.
Regional-scale interannual variability over eastern North America in
January has also been higher in recent years, but in December the
highest interannual variability occurred during the 1940s.
Network design permeates every corner of modern communication research and continues
to provide new algorithmic challenges. In this issue we present eight papers on
designing the physical layout of new networks and designing protocols for efficient information
delivery on existing networks. The contribution of these papers is not limited
to the solutions they present, but also the new problems they introduce.
One-way wave operators are powerful tools for forward modeling and migration. Here, we describe a recently developed true-amplitude implementation of modified one-way operators and present some numerical examples. By "true-amplitude" one-way forward modeling we mean that the solutions are dynamically correct as well as kinematically correct. That is, ray theory applied to these equations yields the upward- and downward-traveling eikonal equations of the full wave equation, and the amplitude satisfies the transport equation of the full wave equation. The solutions of these equations are used in the standard wave-equation migration imaging condition. The boundary data for the downgoing wave is also modified from the one used in the classic theory because the latter data is not consistent with a point source for the full wave equation. When the full wave-form solutions are replaced by their ray-theoretic approximations, the imaging formula reduces to the common-shot Kirchhoff inversion formula. In this sense, the migration is true amplitude as well. On the other hand, this new method retains all of the fidelity features of wave equation migration. Computer output using numerically generated data confirms the accuracy of this inversion method. However, there are practical limitations. The observed data must be a solution of the wave equation. Therefore, the data must be collected from a single common-shot experiment. Multi-experiment data, such as common-offset data, cannot be used with this method as presently formulated.
The Global Historical Climatology Network version 2 temperature database was released in May 1997. This century-scale dataset consists of monthly surface observations from 7000 stations from around the world. This archive breaks considerable new ground in the field of global climate databases. The enhancements include 1) data for additional stations to improve regional-scale analyses, particularly in previously data-sparse areas; 2) the addition of maximum-minimum temperature data to provide climate information not available in mean temperature data alone; 3) detailed assessments of data quality to increase the confidence in research results; 4) rigorous and objective homogeneity adjustments to decrease the effect of nonclimatic factors on the time series; 5) detailed metadata (e.g., population, vegetation, topography) that allow more detailed analyses to be conducted; and 6) an infrastructure for updating the archive at regular intervals so that current climatic conditions can constantly be put into historical perspective. This paper describes these enhancements in detail.
The presence of seasonal snow cover during the cold season of the annual air temperature cycle has significant influence on the ground thermal regime in cold regions. Snow has high albedo and emissivity that cool the snow surface, high absorptivity that tends to warm the snow surface, low thermal conductivity so that a snow layer acts as an insulator, and high latent heat due to snowmelt that is a heat sink. The overall impact of snow cover on the ground thermal regime depends on the timing, duration, accumulation, and melting processes of seasonal snow cover; density, structure, and thickness of seasonal snow cover; and interactions of snow cover with micrometeorological conditions, local microrelief, vegetation, and the geographical locations. Over different timescales either the cooling or warming impact of seasonal snow cover may dominate. In the continuous permafrost regions, impact of seasonal snow cover can result in an increase of the mean annual ground and permafrost surface temperature by several degrees, whereas in discontinuous and sporadic permafrost regions the absence of seasonal snow cover may be a key factor for permafrost development. In seasonally frozen ground regions, snow cover can substantially reduce the seasonal freezing depth. However, the influence of seasonal snow cover on seasonally frozen ground has received relatively little attention, and further study is needed. Ground surface temperatures, reconstructed from deep borehole temperature gradients, have increased by up to 4°C in the past centuries and have been widely used as evidence of paleoclimate change. However, changes in air temperature alone cannot account for the changes in ground temperatures. Changes in seasonal snow conditions might have significantly contributed to the ground surface temperature increase. The influence of seasonal snow cover on soil temperature, soil freezing and thawing processes, and permafrost has considerable impact on carbon exchange between the atmosphere and the ground and on the hydrological cycle in cold regions/cold seasons.
Contemporary large-scale changes in solid and total precipitation and satellite-derived snow cover were examined over the North American continent. Annual snow cover extent over the last 19 years decreased up to 6 [times] 10[sup 5] km[sub 2] relative to a 0.93[degrees]C (0.33[degrees]C) increase in North American (Northern Hemisphere) temperature. A strong correlation exists between snow cover and temperature where up to 78% of the variance in regional snow cover and snowfall is explained by the anomalies of monthly mean maximum temperature. Over the last two decades the decrease in snow cover during winter (December-March) has largely occurred through reduced frequency of snow cover in areas that typically have a high probability of snow on the ground with little change in the frequency of snow cover in other areas. Similar characteristics were observed during spring (April-May) in areas with high snow cover probability except for an expansion of the snow-free regions. Anomalies in these two seasons dominate the interannual variability (nearly three-fourths of the variance) of snow cover. 48 refs., 15 figs., 10 tabs.
Summary Induced by global warming, mountain plant species are migrating upwards. Species inhabiting the nival zone of today are threatened by competitors which move from the alpine zone towards the summits. The manner in which species move depends on their abilities to cope with microtopographical situations. We present a spatially explicit predictive model which draws scenarios of future species distribution patterns at a typical high mountain of the European Alps. The altitudinal temperature gradient is examined. Based on the lapse rate and on definitions of topographical niches of species, a +1 °C- and a +2 °C-warming scenario are modelled using a fine-scaled digital elevation model. Nival species will lose area and become restricted to specific topographical situations. Alpine and subnival grassland species are predicted to expand their area, mainly along stable surface situations. Whether the migration will take place as a filling or a moving process is specific to the particular species. Overall, biodiversity is apparently not threatened on the decadal scale. In special cases, however, genetic losses are likely both on a local and on a regional scale.
Land-based compilations of gridded monthly surface air temperature anomalies, averaged into hemispheric values for the last 140 years, have been available for climatological analyses for the last 10 years or so. The analysis techniques used in their construction, particularly the need for a common reference period, mean that it is difficult to include, retrospectively, any of the new temperature datasets now available for some countries. So, despite data availability improvements in some areas, the number of stations used has fallen since 1970, both in the hemispheric averages and in their constituent grid-box datasets. The present study is a reanalysis of both the existing and the newly available temperature datasets to produce a grid-box dataset of 5{degrees} x 5{degrees} temperature anomalies. The reanalysis not only uses over 1000 more stations (2961 in total), principally covering the period from the 1920s to about 1990, but also arrests the decline of stations incorporated in real time for the latest years. Two hundred and fifty-two more stations are used in this analysis for the 1991-1993 period, compared with earlier analyses. The purpose of the reanalysis, however, is not just to calculate hemispheric averages. The improvements in station numbers used mean that the grid-box dataset should better estimate time series for small subcontinental scales. Despite the dramatic improvements in the numbers of stations used, the results change little from earlier analyses for the Northern Hemisphere average, indicating the robustness of the earlier time series. Similar results could have been achieved with as few as 109 stations. Over the Southern Hemisphere, comparisons of the results indicate larger (but still relatively small) differences with earlier analyses, particularly over continental-scale regions. 22 refs., 10 figs., 5 tabs.
Global warming, resulting from increased concentrations of greenhouse gases, may affect ecosystems in different ways and to various extents (Emanuel et al. 1985; Bolin et al. 1986; Solomon and Shugart 1993, etc.). Coral reefs, mangroves, the arctic tundra, and high mountain ecosystems are particularly vulnerable (Markham et al. 1993).
The purpose of this book is to help the climatologist understand the basic precepts of the statistician's art and to provide some of the background needed to apply statistical methodology correctly and usefully. The book is self contained: introductory material, standard advanced techniques, and the specialized techniques used specifically by climatologists are all contained within this one source. There are a wealth of real-world examples drawn from the climate literature to demonstrate the need, power and pitfalls of statistical analysis in climate research.
This study discusses problems of the concept of normal period–based anomalies arising from climate variability and ongoing climate change. The widely used WMO 1961–1990 (61–90) standard normal period is compared to other consecutive 30-year normal periods in detail. Focus is given to the temperature distribution in Switzerland and on the European continent. In these regions, the temperature trend of the last decades led to an unusually high number of months with positive temperature anomalies relative to the WMO 61–90 standard normal period. Swiss anomalies based on the 61–90 normal are up to 1.25 K higher than those based on the Latest 30-years Running Normal (LRN). The probability to observe a positive temperature anomaly with respect to the 61–90 normal increased from 50% to near 80% for certain months of the year. Compared to the LRN, this change is statistically significant for 7 out of the 12 months on the 95% level. The strongest signal can be found for the summer months, whereas temperatures in fall do not show any trends. Similar results are found for more than 90% of the European continental area. For most regions, 2–5 are statistically inconsistent with the 61–90 distribution. For southern France, parts of Spain and southern Scandinavia even 7–9 months are inconsistent. Copyright © 2005 Royal Meteorological Society.
A 1961–1990 mean monthly climatology for a ‘greater European’ region extending from 32°W to 66°E and from 25° to 81°N has been constructed at a resolution of 0.5°latitude by 0.5° longitude for a suite of nine surface climate variables: minimum, maximum, and mean air temperature; precipitation totals; sunshine hours; vapour pressure; wind speed; and (ground) frost day and rain day ( > 0.1 mm) frequencies. This climatology has been constructed from observed station data distributed across the region. Station frequencies range from 936 (wind speed) to 3078 (precipitation). Over 95 per cent of these data are based on observations between 1961 and 1990 and over 90 per cent were supplied by individual national meteorological agencies (NMAs) on specific request. For four variables, some standardization of the data had to be performed because different countries supplied data under different definitions. Thus cloud cover had to be converted to sunshine hours, relative humidity to vapour pressure, air frost days to ground frost days and rain days > 1 mm to rain days > 0.1 mm.
The interpolation of the station data to the grid used elevation as one of the predictor variables and thus enabled three climate surfaces to be produced for each variable, reflecting the minimum, mean, and maximum elevation within each 0.5° by 0.5° cell. Subsets of stations were used for the interpolation of each variable, the selection being based on optimizing the spatial distribution, source priority and length of record. The accuracy of the various interpolations was assessed using validation sets of independent station data (i.e. those not used in the interpolation). Estimated mean absolute errors (MAE) ranged from under 4 per cent for vapour pressure to about 10 per cent for precipitation and up to 20 per cent for wind speed. The accuracy of the interpolated surfaces for minimum and maximum temperature was between 0.5°C and 0.8°C.
We believe these results constitute the first climatology that has been constructed for this extensive European region at such a fine spatial resolution (0.5° by 0.5°) from relatively dense station networks, for three different elevation surfaces and for a wide range of surface climate variables, all expressed with respect to a standard 30‐year period. The climatology is already being used by researchers for applications in the areas of ecosystem modelling, climate change impact assessment and climate model validation, and is available from the authors.
The basic characteristics of snow cover occurrence in eastern Europe are described. For each month from October to May the range of ‘active’ snow-cover areas in Europe was determined. The boundary criterion for ‘active’ regions was adopted as snow-cover probability of between 10 and 90%. The correlation coefficients between the snow-cover characteristics (number of days with snow cover and its monthly mean depth) and other climatic variables (temperature and precipitation) were calculated. A strong positive correlation between the annual number of days with snow cover and the annual number of days with mean temperature <0 °C was discovered for most parts of the study area. A negative correlation between the monthly number of days with snow cover and monthly mean temperature was found and its spatial distribution was analysed. A positive correlation between snow depth and precipitation appeared significant only in some areas. The influence of atmospheric circulation, expressed by North Atlantic oscillation (NAO) index values, on snow cover in the particular months was analysed. The correlation between the number of days with snow cover and the NAO index is large and statistically significant only in central Europe and it becomes insignificant to the east of 30° λ E. High values are noted only in the winter months. In autumn and spring, when the range of the ‘active’ areas moves to the east and the NAO becomes weak, the correlation is very small. Copyright © 2004 Royal Meteorological Society
After a brief historical account of probability's evolution over the past five centuries, the article presents techinical overviews of concepts that are central to computer science and engineering applications. These areas are probability spaces, combinatorics, random variables and their distributions, convergence modes, computer simulations, and statistical inference. Each section begins with elementary definitions, continues with the most frequently used techniques and theorems, and concludes with more advanced results. Examples and typical computations accompany the presentations.
The number of days with snow cover at Austrian climate stations, normalized by the maximum possible snow days within a season, is denoted n. This seasonal relative snow cover duration is considered a function of station height H and of the seasonal mean temperature T over Europe. When T increases, n decreases and vice versa. The function becomes saturated both for high stations at low European temperature (‘always snow’, n=1) and for low stations at high temperature (‘never snow’, n=0). In the saturated regions, the sensitivity s≡∂n(H, T)/∂T is practically zero, while in the transition region, s is extreme. The observed interannual fluctuations of T are considered here as simulation of a possible climate shift. s is determined for the climate stations of Austria from its snow cover record [1961–1990, 84 stations between 153 and 3105 m above sea level (a.s.1.)] by fitting the data of n for each individual station (local mode) as well as for all Austrian stations (global mode) with a hyperbolic tangent function. In the global mode, s reaches an extreme value of −0.34±0.04 K−1 in winter and −0.46±0.13 K−1 in spring.The implications of these results are discussed. Included in this discussion is the fact that a rise in the European temperature by 1 K may reduce the length of the snow cover period in the Austrian Alps by about 4 weeks in winter and 6 weeks in spring. However, these extreme values apply only to the height of maximum sensitivity (575 m in winter, 1373 m in spring); the actual sensitivity of individual stations located at higher or lower levels is less. Copyright © 2000 Royal Meteorological Society
This paper describes the HISTALP database, consisting of monthly homogenised records of temperature, pressure, precipitation, sunshine and cloudiness for the ‘Greater Alpine Region’ (GAR, 4–19°E, 43–49°N, 0–3500m asl). The longest temperature and air pressure series extend back to 1760, precipitation to 1800, cloudiness to the 1840s and sunshine to the 1880s. A systematic QC procedure has been applied to the series and a high number of inhomogeneities (more than 2500) and outliers (more than 5000) have been detected and removed. The 557 HISTALP series are kept in different data modes: original and homogenised, gap-filled and outlier corrected station mode series, grid-1 series (anomaly fields at 1° × 1°, lat × long) and Coarse Resolution Subregional (CRS) mean series according to an EOF-based regionalisation. The leading climate variability features within the GAR are discussed through selected examples and a concluding linear trend analysis for 100, 50 and 25-year subperiods for the four horizontal and two altitudinal CRSs. Among the key findings of the trend analysis is the parallel centennial decrease/increase of both temperature and air pressure in the 19th/20th century. The 20th century increase (+1.2 °C/+ 1.1 hPa for annual GAR-means) evolved stepwise with a first peak near 1950 and the second increase (1.3 °C/0.6hPa per 25 years) starting in the 1970s. Centennial and decadal scale temperature trends were identical for all subregions. Air pressure, sunshine and cloudiness show significant differences between low versus high elevations. A long-term increase of the high-elevation series relative to the low-elevation series is given for sunshine and air pressure. Of special interest is the exceptional high correlation near 0.9 between the series on mean temperature and air pressure difference (high-minus low-elevation). This, further developed via some atmospheric statics and thermodynamics, allows the creation of ‘barometric temperature series’ without use of the measures of temperature. They support the measured temperature trends in the region. Precipitation shows the most significant regional and seasonal differences with, e.g., remarkable opposite 20th century evolution for NW (9% increase) versus SE (9% decrease). Other long- and short-term features are discussed and indicate the promising potential of the new database for further analyses and applications. Copyright © 2006 Royal Meteorological Society.
A database of monthly climate observations from meteorological stations is constructed. The database includes six climate elements and extends over the global land surface. The database is checked for inhomogeneities in the station records using an automated method that refines previous methods by using incomplete and partially overlapping records and by detecting inhomogeneities with opposite signs in different seasons. The method includes the development of reference series using neighbouring stations. Information from different sources about a single station may be combined, even without an overlapping period, using a reference series. Thus, a longer station record may be obtained and fragmentation of records reduced. The reference series also enables 1961–90 normals to be calculated for a larger proportion of stations.
The station anomalies are interpolated onto a 0.5° grid covering the global land surface (excluding Antarctica) and combined with a published normal from 1961–90. Thus, climate grids are constructed for nine climate variables (temperature, diurnal temperature range, daily minimum and maximum temperatures, precipitation, wet-day frequency, frost-day frequency, vapour pressure, and cloud cover) for the period 1901–2002. This dataset is known as CRU TS 2.1 and is publicly available (http://www.cru.uea.ac.uk/). Copyright
This paper combines a wide-area assessment of forecast changes in wintertime synoptic conditions over western North America with a meso-scale alpine hydrometeorology model to evaluate the impacts of forecast climate change on snowpack conditions in an alpine watershed. The synoptic analysis was used to generate long-term climate time series scenarios using the Canadian Centre for Climate Modelling and Analysis first-generation coupled general circulation model (GCM). The alpine hydrometeorology model SIMGRID is used to predict changes in wintertime precipitation at the watershed scale. The SNOPAC model is a simple snow model that predicts the overall snow accumulation throughout a watershed based on the output from SIMGRID. A vapour transfer model has been incorporated into the SNOPAC model to estimate snow volumes more accurately. The model is applied to a small alpine watershed in the southern Canadian Rockies. The synoptic analysis and GCM output forecasts a modest increase in both winter precipitation and temperatures in the study area. The hypothesis herein is that the increase in winter precipitation due to synoptic conditions will not compensate for regional changes in the rain-to-snow ratios. The net result will be a decline in winter accumulations of precipitation as snow, and hence an expected decline in spring runoff. Copyright © 2005 Royal Meteorological Society.
Results from four snow models-two used in climate models, one being developed for hydrological forecasting and one used for
avalanche forecasting-are compared with observations made during two contrasting winters at a site in the French Alps. The
models are all driven with hourly measurements of air temperature, windspeed, humidity, snowfall and downward longwave and
shortwave radiation, but they differ greatly in complexity. Results from the models are compared with measurements of snowdepth,
snow water equivalent, surface temperature, runoff and albedo. The models all represent the duration of snow cover well, but
differ in their predictions of peak accumulation and timing of runoff. Experience gained in this study is used to make recommendations
for a more ambitious intercomparison between a larger number of models for a wide range of environments.
Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.
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Corrigendum to Snow cover duration in Switzerland compared to Austria Influence of the seasonal snow cover on the ground thermal regime: an overview
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