Search

This paper presents an analysis of the lightning production of convective cells. The cells were detected by the MeteoSwiss Thunderstorms Radar Tracking (TRT) algorithm in the course of a lightning measurement campaign that took place in the summer of 2017 in the area surrounding the Säntis mountain, in the northeastern part of Switzerland. For this campaign, and for the first time in the Alps, a lightning mapping array (LMA) was deployed. In the first part of the paper, we examine the relationship between the intra-cloud (IC) and cloud-to-ground (CG) activity and the cell severity, as derived by the TRT algorithm, of a large dataset of cells gathered during the campaign. We also propose and analyse the performance of a new metric to quantify lightning intensity, the rimed-particle column (RPC) height and base altitude. In the second part, we focus on two of the most severe cells detected during the campaign that produced significantly different outcomes in terms of lightning activity. The paper shows that the newly proposed metric (RPC) seems to be a very promising predictor of lightning activity, particularly for IC flashes. Future lightning nowcasting algorithms should be probabilistic in nature and incorporate the polarimetric properties of the convective cells as well as the lightning climatology. [ABSTRACT FROM AUTHOR]

In this paper we present an analysis of a large dataset of lightning and polarimetric weather radar data collected in the course of a lightning measurement campaign that took place in the summer of 2017 in the area surrounding Säntis, in the northeastern part of Switzerland. For this campaign and for the first time in the Alps, a lightning mapping array (LMA) was deployed. The main objective of the campaign was to study the atmospheric conditions leading to lightning production with a particular focus on the lightning discharges generated due to the presence of the 124 m tall Säntis telecommunications tower. In this paper we relate LMA very high frequency (VHF) sources data with co-located radar data in order to characterise the main features (location, timing, polarimetric signatures, etc.) of both the flash origin and its propagation path. We provide this type of analysis first for all of the data and then we separate the datasets into intra-cloud and cloud-to-ground flashes (and within this category positive and negative flashes) and also upward lightning. We show that polarimetric weather radar data can be helpful in determining regions where lightning is more likely to occur but that lightning climatology and/or knowledge of the orography and man-made structures is also relevant. [ABSTRACT FROM AUTHOR]

In this paper, we attempt to highlight the relevance of cutoff low systems (CoLs) to large-scale heavy precipitation events within the Alpine region which often lead to catastrophic flooding. The main results of this study are (1) a detailed climatology (1971-1999) of CoLs for the European region, (2) contribution of CoLs to extreme precipitation events in the European Alpine region, (3) identification of regions within the European Alps most affected by extreme precipitation caused by CoLs, and (4) identification of regions where presence of CoLs is related to extreme precipitation in the Alpine region. The findings of this paper suggest that CoLs have a significant correlation with extreme precipitation events and strongly influence the climate of the Alpine region. The total contribution of CoLs to large-scale heavy precipitation events ranges between 20 and 95 % and is most pronounced in the northern and eastern parts of the Alps. More than 80 % of the events occur in the summer season. The area around the Alps and West of Spain (over the Atlantic Ocean) is the most affected region. The location of the center of CoLs that affect the Alpine region most occur on the northern and southern sides of the Alpine ridge. [ABSTRACT FROM AUTHOR]

A climatology of snow water equivalent (SWE) based on data collected at 240 gauging sites was performed for the Italian Alps over the 1967–2020 period, when Enel routinely conducted snow depth and density measurements with homogeneous methods. Six hydrological sub-regions were investigated spanning from the eastern Alps to the western Alps at altitudes ranging from 1000 to 3000 m a.s.l. Measurements were conducted at fixed dates at the beginning of each month from 1 February to 1 June and on 15 April. To our knowledge, this is the most comprehensive and homogeneous dataset of measured snow depth and density for the Italian Alps. Significant decreasing trends over the years at all fixed dates and elevation classes were identified for both snow depth, equal to -0.12 ± 0.06 m per decade, and snow water equivalent, equal to -51 ± 37 mm per decade, on average in the six macro-basins we selected. The analysis of bulk snow density data showed a temporal evolution along the snow accumulation and melt season, but no altitudinal trends were found. A Moving Average and Running Trend Analysis (MARTA triangles), combined with a Pettitt's test change-point detection, highlighted a decreasing change of snow climatology occurring around the end of the 1980s. The comparison with winter temperature and precipitation data from the HISTALP dataset identified a major role played by temperature on the long-term decrease and changing points of snow depth and SWE with respect to precipitation, mainly responsible for its variability. Correlation with climatic indexes indicates significant negative values of the Pearson correlation coefficient with winter North Atlantic Oscillation (NAO) and positive values with winter Western Mediterranean Oscillation (WeMO) for some areas and elevation classes. Results of this climatology are synthesized in a temporal polynomial model that is useful for climatological studies and water resources management in mountain areas. [ABSTRACT FROM AUTHOR]

There is still considerable uncertainty about precipitation at high elevation in mountain terrain due to the relatively few in situ measurements available and to the particular variability of the parameter. In this study, several spatialization techniques were tested, some for climatological time scale and others for daily fields, for precipitation over the western Alps for the period of 1990-2012. The study domain and period were chosen for the quality of available in situ observations and density of the network. First, a weather-type classification was established with a technique based on canonical correlation analysis combining large- and regional-scale data. The spatialization techniques applied for the climatological time scale were adapted from the Aurelhy method which uses elevation and principal components of the topography as predictors. The spatialization techniques applied to daily fields were based on kriging of daily rain gauges and used the climatological fields as predictors. This study aims to validate the advantage of using the climatology of the weather type of the day as predictor for daily fields over a monthly climatology. The climatology of the weather type of the day seems to demonstrate some small improvement. Finally, annual means over the period of 1990-2012 were produced using several methods, including some from accumulation of daily fields and others from the spatialization of in situ station means. Precipitation at high elevations and vertical climatological gradients were particularly scrutinized. Annual means based on sums of daily fields seem to have better performances. This paper only presents results for precipitation but temperature was also analysed. [ABSTRACT FROM AUTHOR]

Avalanches result from an interaction of weather and terrain, where past weather and internal snow cover processes play important roles. So far, climatology was mainly based on weather data, as regional snow instability information, such as avalanche activity, is scarce on climatological time scales. We present a new approach to create a snow avalanche climatology from simulations of avalanche problem types based on snow cover simulations of reanalysis data and a cluster analysis. Analyzing the winters between 1958 and 2020 in the French Alps, wet-snow situations dominated natural release. Dry-snow situations with non-persistent and persistent weak layers occurred each on at least one third of the days. Four typical patterns of avalanche problem types were identified. They follow the main orography with more new snow situations in the northern regions and more cases of persistent weak layers in inner-Alpine regions. In the front-ranges and in southern regions wet-snow situations occurred early in winter – typical for coastal snow climates. Agreement with the standard snow climate classification and the geography of the French Alps suggests that mountain regions with similar conditions can now be outlined. This method for snow avalanche climatology will inform avalanche forecasting and facilitate climate change impact studies. [ABSTRACT FROM AUTHOR]

The aims of the paper are (I) to describe the annual distribution of extreme runoff events on the Mura, Drava and Sava Rivers, (ii) to demonstrate their association with moisture fluxes, and (iii) to explain their annual distribution by moisture flux climatology. Extreme runoff events were de- fined as rapid increases in daily mean discharge. Moisture flux anomalies were studied within six pixels of the ERA-40 database around the studied region. In general, extreme runoff events were concentrated in the summer and autumn and were usually associated with anomalies in moisture flux, mainly from the south. Nevertheless, while southern and western moisture fluxes were typical of Sava River events that occurred mainly in autumn, summer events prevailed on the Mura River and were frequently associated with moisture fluxes from the east or the north. It is remarkable that moisture fluxes from the west and south have their maxima in the autumn, whereas those from the east and north have their maxima in the summer. Therefore, the climatology of moisture flux seems to be one of the major reasons for the annual distribution of extreme runoff events in the study region. This result should be confirmed in other regions in the future. [ABSTRACT FROM AUTHOR]

This paper investigates the dependence on environmental conditions of altitudinal precipitation differences in the northern Alps, based on high-resolution numerical simulations with the MM5 model for a selected region in the Bavarian Alps (Zugspitze mountain and surrounding valley stations). Three exemplary precipitation events representing climatological regimes with different orographic enhancement characteristics are selected. After validating the MM5 precipitation fields against the available surface observations, the model results are used to analyse the interactions of atmospheric dynamics and cloud microphysics with the local orography. The first two cases (19–22 March 1997, 05–09 February 1999) are characterized by a strong northwesterly or northerly flow, associated with large precipitation differences between the mountain and the surrounding valley stations. For these cases, the model results indicate a dominance of the classical seeder–feeder mechanism, with strong orographic lifting generating dense orographic clouds over each individual mountain ridge, which in turn intensify precipitation. The related surface precipitation maxima can be found near the mountain peaks or somewhat in the lee due to hydrometeor drifting. The third case (05–07 December 1992) represents conditions with relatively small (i.e. below climatological average) precipitation differences between the Zugspitze and the surrounding valley stations. For this event, the model results indicate that relatively weak ambient winds at and below Alpine crest level (700 hPa) were primarily responsible for the lack of substantial precipitation enhancement. Precipitation was nevertheless moderately intense because of strong frontal lifting at higher levels. In all three cases, the agreement between simulated and observed precipitation patterns is so high that there is good reason to expect that mountain–valley precipitation differences will be quantitatively predictable for nonconvective events once a sufficiently high model resolution is computationally affordable. [ABSTRACT FROM AUTHOR]

Climate change is not only a likely prospect for the end of this century, but it is already occurring. Part of the changes will include global warming and increasing temperature variability, both at global and regional scales. This increased variability was investigated in this paper from the point of view of the occurrence of cold spells in the Alps in the future climate (2071-2100), compared with the present climate (1961-1990). For this purpose, a regionalisation of the climate change effects was performed within the Alps. To avoid possible errors in the estimate of the 2m air temperature, the analysis was performed on the soil surface temperature. To get realistic values for this variable, a land surface scheme, UTOPIA, has been run on the selected domain, using the output of the Regional Climate Model (RegCM3) simulations as the driving force. The results show that, in general, the number of cold breaks is decreasing over the Alps, due to the temperature increment. However, there are certain zones where the behaviour is more complicated. The analysis of the model output also allowed a relationship to be found between the number of cold breaks and their duration. The significance of these results over the whole area was assessed. [ABSTRACT FROM AUTHOR]

This paper examines the flow conditions associated with frontal widespread and moderate precipitation over the Lago Maggiore Target Area (LMTA) of the Mesoscale Alpine Programme, and observed during the intensive observation periods (IOPs) 4 (30 September 1999), 8 (21 October), 9 (23 October) and 15 (6 November). The flow organization that led precipitation maxima to occur away from the relief instead of being concentrated on the windward southern slopes of the Alps is investigated from three ground-based Doppler radars.Different aspects of this organization are noted. Post-frontal flow had a primary role in IOPs 4 and 15, and the intensity and vertical extension of the incoming flow modulated the precipitation intensity and duration over the LMTA. In IOPs 4 and 9, westerly-to-northwesterly downslope flow opposed the south-southeasterly moist inflow, but the larger thickness and intensity of the inflow in IOP 9 yielded longer rain duration. Also the occurrence of such downslope flow on the lee side was accompanied by foehn effects. In IOP 15, the southerly inflow was strong enough to rise over a deep and strong northerly downslope post-frontal cold flow (in connection with a deep lee cyclone) which was probably enhanced by melting and evaporation of hydrometeors, and behaved like a severe downslope wind. The IOP 8 event was a case of blocked flow and slow frontal passage, and was accompanied with persistent stratiform precipitation over the LMTA. The blocking was due to the stable character of the east-southeasterly incoming flow which favored flow deflection (barrier flow) along the southeastward-facing slopes of the Alps. It is also found that gravity waves activity during IOPs 8 and 9 modulated the precipitation distribution over the LMTA. [ABSTRACT FROM AUTHOR]

Summary This paper explores the possibility of using ring-width measurements derived from string instruments as a potential source of palaeoclimate information. From a data-base of 1800 measured series, we have identified two sub-sets that compare well with living high elevation spruce (Picea abies (L.) Karst) chronologies from the Bavarian Forest and Austrian Alps. The problems of using historical tree-ring data for dendroclimatic purposes are addressed and by combining the living and historic ring-width data from these two regions, a preliminary proxy of past June/July mean temperatures is developed. This proxy summer temperature record shows striking similarities with a tree-ring based temperature reconstruction for the Central Eastern Alps, the CLIMHIST June/July temperature record from Switzerland and glacial records from the Austrian Alps. This explorative study demonstrates that ring-width series from string instruments may allow the identification of generalised source regions of wood used for instrument making and, most importantly, provide a new unique source for palaeoclimate information at a variety of both temporal and spatial scales for high elevations in central Europe. [ABSTRACT FROM AUTHOR]

Snowfall and snow accumulation play a crucial role in shaping ecosystems and human activities in the Alpine region. This resource is under threat as a consequence of the visible effects of global warming, and, therefore, it appears urgent to understand how snowfall trends have changed in time and space. In this context, we recovered data from over a hundred snowfall (HN) time series covering the period 1980–2020 over the mountain region of Trentino‐South Tyrol in the northeastern Italian Alps and analysed them to understand snowfall climatology in the region, recent trends and their dependence on elevation and timing of the season. Negative, although not always statistically significant, trends were found in the lowest elevation range (0–1,000 m a.s.l.) over the whole winter season, while some positive and even significant trends were found from January to March above 2,000 m a.s.l. The intermediate elevation range (1,000–2,000 m a.s.l.) exhibits a strong variability with no clear trend. Negative and statistically significant trends were found in April for all elevations. An attribution analysis was performed using precipitation (P), mean air temperature (TMEAN), and large‐scale synoptic descriptors, such as the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO) indices. The analysis shows that, overall, P is the driver that best explains the snowfall trends, but, for low elevations, especially during mid‐winter, TMEAN is more relevant. Low elevations are facing a clear decrease in HN due to a significant increase in mean temperatures, while high elevations during mid‐winter display a slight increase in HN, associated with a general increase in precipitation. NAO and AO indices exhibit no significant correlations with HN, except at the lowest elevations and at the beginning of the season. [ABSTRACT FROM AUTHOR]

This paper evaluates Integrated Multi-Satellite Retrievals from GPM (IMERG-F) over Europe for the period 2014–2018 in order to evaluate application of the retrievals to hydrology. IMERG-F is compared with a large pan-European precipitation dataset built on rain gauge stations, i.e., the ENSEMBLES OBServation (E-OBS) gridded dataset. Although there is overall agreement in the spatial distribution of mean precipitation (R2 = 0.8), important discrepancies are revealed in mountainous regions, specifically the Alps, Pyrenees, west coast of the British Isles, Scandinavia, the Iberian and Italian peninsulas, and the Adriatic coastline. The results show that the strongest contributors to poor performance are pixels where IMERG-F has no gauges available for adjustment. If rain gauges are available, IMERG-F yields results similar to those of the surface observations, although the performance varies by region. However, even accounting for gauge adjustment, IMERG-F systematically underestimates precipitation in the Alps and Scandinavian mountains. Conversely, IMERG-F overestimates precipitation in the British Isles, Italian Peninsula, Adriatic coastline, and eastern European plains. Additionally, the research shows that gauge adjustment worsens the spatial gradient of precipitation because of the coarse resolution of Global Precipitation Climatology Centre data. [ABSTRACT FROM AUTHOR]

Extreme precipitation in the Northern French Alps are mainly associated with large‐scale circulations (LSCs) bringing moist air from the Atlantic Ocean and the Mediterranean Sea—two atmospheric influences that are very frequent in the climatology. In this work, we investigate what characterizes the Atlantic/Mediterranean circulations driving extreme precipitation in the Northern French Alps in comparison to 'random' Atlantic/Mediterranean circulations. We focus on extreme 3‐day precipitation over two medium size neighbouring catchments from 1950 to 2017. Atlantic and Mediterranean circulations are identified using an existing weather pattern classification established for Southern France. Every single LSC is characterized using three atmospheric descriptors based on analogy in geopotential shapes at 500 hPa over Western Europe that were introduced in previous works. They are (a) the celerity, characterizing the stationary nature of a geopotential shape, and (b) the singularity and relative singularity, characterizing the resemblance of a geopotential shape to its analogs, in other words the way this geopotential shape is closely reproduced in the climatology. We add to these analogy‐based descriptors a new (non‐analogy) descriptor accounting for the strength of the low and high‐pressure systems. We show that Atlantic/Mediterranean circulations driving extreme 3‐day precipitation in the Northern French Alps are the Atlantic/Mediterranean circulations featuring the strongest centres of action as well as the most stationary and the most reproducible geopotential shapes—characteristics that are rare for both atmospheric influences. In the Atlantic case, these characteristics appear to be even more pronounced and rare with regard to the whole climatology, pointing LSC as an important driver of extreme precipitation. In the Mediterranean case, these characteristics appear to be more random with regard to the whole climatology, pointing a more balanced contribution between specific LSC and humidity in driving extreme precipitation. [ABSTRACT FROM AUTHOR]

Abstract: This paper summarises the results of tephrochronological investigations into a suite of central and southern European records, which include: Rotmeer, southern Germany; Soppensee and Rotsee, central Swiss Plateau; Lago di Lavarone and Lago Piccolo di Avigliana, Italian southern Alpine foreland. These sites provide records of palaeoenvironmental changes for the Last Glacial to Interglacial Transition (LGIT) at the boundary between North Atlantic and Mediterranean climatic influences. Chemical characterisation of glass shards in volcanic ash layers indicates that multiple volcanic sources have contributed to the central European tephra record. Amongst other volcanic markers, the Laacher See Tephra, originating from the Eifel region of Germany c. 12.9 ± 0.1 ka, and the Vedde Ash from Iceland c. 12.1 ± 0.1 ka, are found co-located within the sediments of Rotmeer, Soppensee, Rotsee and Lago Piccolo di Avigliana. These key horizons, which bracket the onset of the Younger Dryas stadial, provide precise calendrically-dated tie points around which a detailed picture of the timing of local and regional environmental transitions can be constructed. Using the co-located tephra layers the re-colonisation of Northern Italian catchment areas by Quercus is shown to occur just prior to the deposition of the Laacher See Tephra layer, whereas to the North of the Alps Quercus and other thermophilous trees do not reappear until several centuries after the deposition of the Vedde Ash. Furthermore, the discovery of the Vedde Ash in Lago Piccolo di Avigliana and Lago di Lavarone is indicative of atmospheric transport of polar air into southern Europe during the Younger Dryas stadial, matching evidence proposed for such transport of polar air during the Last Glacial Maximum (LGM). [Copyright &y& Elsevier]

The successive occurrence of extreme precipitation events on sub-seasonal timescales can lead to large precipitation accumulations and extreme river discharge. In this study, we analyze the sub-seasonal clustering of precipitation extremes in Switzerland and its link to the occurrence and duration of extreme river discharge. We take a statistical approach based on Ripley's K function to characterize the significance of the clustering for each season separately. Temporal clustering of precipitation extremes exhibits a distinct spatiotemporal pattern. It occurs primarily on the northern side of the Alps in winter and on their southern side in fall. Cluster periods notably account for 10 %–16 % of seasonal precipitation in these two regions. The occurrence of a cluster of precipitation extremes generally increases the likelihood and duration of high-discharge events compared to non-clustered precipitation extremes, particularly at low elevations. It is less true in winter, when the magnitude of precipitation extremes is generally lower and much of the precipitation falls as snow. In fall, however, temporal clusters associated with large precipitation accumulations over the southern Alps are found to be almost systematically followed by extreme discharge. [ABSTRACT FROM AUTHOR]

This paper investigates temperature variability in the Alps and their surroundings based on 97 instrumental series of monthly mean temperatures. A discussion of the initial homogenizing procedure illustrates its advantages and risks. A comparison of the homogenized series with the original series clearly shows the necessity to homogenize. Each of the original series had breaks (an average of five per series) and the mean of all series was systematically biased by non-climatic noise. This noise has subdued the long-term amplitude of the temperature evolution in the region by 0.5 K. The relatively high spatial resolution of the data enabled a regionalization within the study area of 680 000 km2 into six sub-regions based on principal component analysis of the monthly series. Long-term temperature evolution proved to be highly similar across the region—thus making a mean series (averaged over all 97 single series) representative of the study area. Trend analysis (based on progressive forward and backward Mann–Kendall statistics and on progressive analysis of linear regression coefficients) was performed on seasonal and annual series. The results diverge from those of global datasets. This is mainly due to the extension of the 240-year Alpine dataset by 100 years prior to the mid-19th century, and also due to the advantages of a dense and homogenized regional dataset. The long-term features include an initial decrease of the annual and seasonal series to a minimum followed by a positive trend until 1998. The minima are 1890 for the entire year and winter, 1840 for spring and 1920 for summer and autumn, respectively. The initial decreasing trend is more evident in spring and summer, less in autumn and smallest in winter. The mean annual temperature increase since 1890 in the Alps is 1.1 K, which is twice as much as the 0.55 K in the respective grid boxes of the most frequently used global dataset of the Climatic Research Unit (CRU), University of East Anglia. To enable an easier and more systematic handling of the dataset, these data have been interpolated to a 1°×1° longitude–latitude grid. The 105 low-elevation and 16 high-elevation grid point series are widely available without restrictions for scientific research and can be obtained from the authors. Copyright © 2001 Royal Meteorological Society [ABSTRACT FROM AUTHOR]

Changes in precipitation over the European Alps are investigated with the regional climate model MAR (Modèle Atmosphérique Régional) applied with a 7 km resolution over the period 1903–2010 using the reanalysis ERA-20C as forcing. A comparison with several observational datasets demonstrates that the model is able to reproduce the climatology as well as both the interannual variability and the seasonal cycle of precipitation over the European Alps. The relatively high resolution allows us to estimate precipitation at high elevations. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km -1 (1.21 mm d -1 km -1) in summer and 38 % km -1 (1.15 mm d -1 km -1) in winter, on average, over 1971–2008 and shows a large spatial variability. A significant (p value < 0.05) increase in mean winter precipitation is simulated in the northwestern Alps over 1903–2010, with changes typically reaching 20 % to 40 % per century. This increase is mainly explained by a stronger simple daily intensity index (SDII) and is associated with less-frequent but longer wet spells. A general drying is found in summer over the same period, exceeding 20 % to 30 % per century in the western plains and 40 % to 50 % per century in the southern plains surrounding the Alps but remaining much smaller (<10 %) and not significant above 1500 m a.s.l. Below this level, the summer drying is explained by a reduction in the number of wet days, reaching 20 % per century over the northwestern part of the Alps and 30 % to 50 % per century in the southern part of the Alps. It is associated with shorter but more-frequent wet spells. The centennial trends are modulated over the last decades, with the drying occurring in the plains in winter also affecting high-altitude areas during this season and with a positive trend of autumn precipitation occurring only over the last decades all over the Alps. Maximum daily precipitation index (Rx1day) takes its highest values in autumn in both the western and the eastern parts of the southern Alps, locally reaching 50 to 70 mm d -1 on average over 1903–2010. Centennial maxima up to 250 to 300 mm d -1 are simulated in the southern Alps, in France and Italy, as well as in the Ticino valley in Switzerland. Over 1903–2010, seasonal Rx1day shows a general and significant increase at the annual timescale and also during the four seasons, reaching local values between 20 % and 40 % per century over large parts of the Alps and the Apennines. Trends of Rx1day are significant (p value < 0.05) only when considering long time series, typically 50 to 80 years depending on the area considered. Some of these trends are nonetheless significant when computed over 1970–2010, suggesting a recent acceleration of the increase in extreme precipitation, whereas earlier periods with strong precipitation also occurred, in particular during the 1950s and 1960s. [ABSTRACT FROM AUTHOR]

While soil ecosystems undergo important modifications due to global change, the effect of soil properties on plant distributions is still poorly understood. Plant growth is not only controlled by soil physico‐chemistry but also by microbial activities through the decomposition of organic matter and the recycling of nutrients essential for plants. A growing body of evidence also suggests that plant functional traits modulate species' response to environmental gradients. However, no study has yet contrasted the importance of soil physico‐chemistry, microbial activities and climate on plant species distributions, while accounting for how plant functional traits can influence species‐specific responses. Using hierarchical effects in a multi‐species distribution model, we investigate how four functional traits related to resource acquisition (plant height, leaf carbon to nitrogen ratio, leaf dry matter content and specific leaf area) modulate the response of 44 plant species to climatic variables, soil physico‐chemical properties and microbial decomposition activity (i.e. exoenzymatic activities) in the French Alps. Our hierarchical trait‐based model allowed to predict well 41 species according to the TSS statistic. In addition to climate, the combination of soil C/N, as a measure of organic matter quality, and exoenzymatic activity, as a measure of microbial decomposition activity, strongly improved predictions of plant distributions. Plant traits played an important role. In particular, species with conservative traits performed better under limiting nutrient conditions but were outcompeted by exploitative plants in more favorable environments. We demonstrate tight associations between microbial decomposition activity, plant functional traits associated to different resource acquisition strategies and plant distributions. This highlights the importance of plant–soil linkages for mountain plant distributions. These results are crucial for biodiversity modelling in a world where both climatic and soil systems are undergoing profound and rapid transformations. [ABSTRACT FROM AUTHOR]

Snow is a sensitive component of the climate system. In many parts of the world, water stored as snow is a vital resource for agriculture, tourism and the energy sector. As uncertainties in climate change assessments are still relatively large, it is important to investigate the interdependencies between internal climate variability and anthropogenic climate change and their impacts on snow cover. We use regional climate model data from a new single-model large ensemble with 50 members (ClimEX LE) as a driver for the physically based snow model SNOWPACK at eight locations across the Swiss Alps. We estimate the contribution of internal climate variability to uncertainties in future snow trends by applying a Mann–Kendall test for consecutive future periods of different lengths (between 30 and 100 years) until the end of the 21st century. Under RCP8.5, we find probabilities between 10 % and 60 % that there will be no significant negative trend in future mean snow depths over a period of 50 years. While it is important to understand the contribution of internal climate variability to uncertainties in future snow trends, it is likely that the variability of snow depth itself changes with anthropogenic forcing. We find that relative to the mean, interannual variability of snow increases in the future. A decrease in future mean snow depths, superimposed by increases in interannual variability, will exacerbate the already existing uncertainties that snow-dependent economies will have to face in the future. [ABSTRACT FROM AUTHOR]

The sudden interruption of recurring larch budmoth (LBM; Zeiraphera diniana or griseana Gn.) outbreaks across the European Alps after 1982 was surprising, because populations had regularly oscillated every 8–9 years for the past 1200 years or more. Although ecophysiological evidence was limited and underlying processes remained uncertain, climate change has been indicated as a possible driver of this disruption. An unexpected, recent return of LBM population peaks in 2017 and 2018 provides insight into this insect's climate sensitivity. Here, we combine meteorological and dendrochronological data to explore the influence of temperature variation and atmospheric circulation on cyclic LBM outbreaks since the early 1950s. Anomalous cold European winters, associated with a persistent negative phase of the North Atlantic Oscillation, coincide with four consecutive epidemics between 1953 and 1982, and any of three warming-induced mechanisms could explain the system's failure thereafter: (1) high egg mortality, (2) asynchrony between egg hatch and foliage growth, and (3) upward shifts of outbreak epicentres. In demonstrating that LBM populations continued to oscillate every 8–9 years at sub-outbreak levels, this study emphasizes the relevance of winter temperatures on trophic interactions between insects and their host trees, as well as the importance of separating natural from anthropogenic climate forcing on population behaviour. [ABSTRACT FROM AUTHOR]

Meltwater from glaciers is not only a stable source of water but also affects downstream streamflow dynamics. One of these dynamics is the interannual variability of streamflow. Glaciers can moderate streamflow variability because the runoff in the glacierized part, driven by temperature, correlates negatively with the runoff in the non‐glacierized part of a catchment, driven by precipitation, thereby counterbalancing each other. This is also called the glacier compensation effect (GCE), and the effect is assumed to depend on relative glacier cover. Previous studies found a convex relationship between streamflow variability and glacier cover of different glacierized catchments, with lowest streamflow variability at a certain optimum glacier cover. In this study, we aim to revisit these previously found curves to find out if a universal relationship between interannual streamflow variability and glacier cover exists, which could potentially be used in a space‐for‐time substitution analysis. Moreover, we test the hypothesis that the dominant climate drivers (here precipitation and temperature) switch around the suggested optimum of the curve. First, a set of virtual nested catchments, with the same absolute glacier area but varying non‐glacierized area, were modelled to isolate the effect of glacier cover on streamflow variability. The modelled relationship was then compared with a multicatchment data set of gauged glacierized catchments in the European Alps. In the third step, changes of the GCE curve over time were analysed. Model results showed a convex relationship and the optimum in the simulated curve aligned with a switch in the dominant climate driver. However, the multicatchment data and the time change analyses did not suggest the existence of a universal convex relationship. Overall, we conclude that GCE is complex due to entangled controls and changes over time in glacierized catchments. Therefore, care should be taken to use a GCE curve for estimating and/or predicting interannual streamflow variability in glacierized catchments. [ABSTRACT FROM AUTHOR]

Sub-orbital-scale climate variability of the last glacial period provides important insights into the rates at which the climate can change state, the mechanisms that drive such changes, and the leads, lags, and synchronicity occurring across different climate zones. Such short-term climate variability has previously been investigated using δ18O from speleothems (δ18O calc) that grew along the northern rim of the Alps (NALPS), enabling direct chronological comparisons with δ18O records from Greenland ice cores (δ18O ice). In this study, we present NALPS19, which includes a revision of the last glacial NALPS δ18O calc chronology over the interval 118.3 to 63.7 ka using 11, newly available, clean, precisely dated stalagmites from five caves. Using only the most reliable and precisely dated records, this period is now 90 % complete and is comprised of 16 stalagmites from seven caves. Where speleothems grew synchronously, the timing of major transitional events in δ18O calc between stadials and interstadials (and vice versa) are all in agreement on multi-decadal timescales. Ramp-fitting analysis further reveals that, except for one abrupt change, the timing of δ18O transitions occurred synchronously within centennial-scale dating uncertainties between the NALPS19 δ18O calc record and the Asian monsoon composite speleothem δ18O calc record. Due to the millennial-scale uncertainties in the ice core chronologies, a comprehensive comparison with the NALPS19 chronology is difficult. Generally, however, we find that the absolute timing of transitions in the Greenland Ice Core Chronology (GICC) 05 modelext and Antarctic Ice Core Chronology (AICC) 2012 are in agreement on centennial scales. The exception to this is during the interval of 100 to 115 ka, where transitions in the AICC2012 chronology occurred up to 3000 years later than in NALPS19. In such instances, the transitions in the revised AICC2012 chronology of Extier et al. (2018) are in agreement with NALPS19 on centennial scales, supporting the hypothesis that AICC2012 appears to be considerably too young between 100 and 115 ka. Using a ramp-fitting function to objectively identify the onset and the end of abrupt transitions, we show that δ18O shifts took place on multi-decadal to multi-centennial timescales in the North Atlantic-sourced regions (northern Alps and Greenland) as well as the Asian monsoon. Given the near-complete record of δ18O calc variability during the last glacial period in the northern Alps, we also offer preliminary considerations regarding the controls on mean δ18O calc for given stadials and interstadials. We find that, as expected, δ18O calc values became increasingly lighter with distance from the oceanic source regions, and increasingly lighter with increasing altitude. Exceptions were found for some high-elevation sites that locally display δ18O calc values that are heavier than expected in comparison to lower-elevation sites, possibly caused by a summer bias in the recorded signal of the high-elevation site, or a winter bias in the low-elevation site. Finally, we propose a new mechanism for the centennial-scale stadial-level depletions in δ18O such as the Greenland Stadial (GS)-16.2, GS-17.2, GS-21.2, and GS-23.2 "precursor" events, as well as the "within-interstadial" GS-24.2 cooling event. Our new high-precision chronology shows that each of these δ18O depletions occurred in the decades and centuries following rapid rises in sea level associated with increased ice-rafted debris and southward shifts of the Intertropical Convergence Zone, suggesting that influxes of meltwater from moderately sized ice sheets may have been responsible for the cold reversals causing the Atlantic Meridional Overturning Circulation to slow down similar to the Preboreal Oscillation and Older Dryas deglacial events. [ABSTRACT FROM AUTHOR]

Mountain permafrost is sensitive to climate change and is expected to gradually degrade in response to the ongoing atmospheric warming trend. Long-term monitoring of the permafrost thermal state is a key task, but problematic where temperatures are close to 0 ∘ C because the energy exchange is then dominantly related to latent heat effects associated with phase change (ice–water), rather than ground warming or cooling. Consequently, it is difficult to detect significant spatio-temporal variations in ground properties (e.g. ice–water ratio) that occur during the freezing–thawing process with point scale temperature monitoring alone. Hence, electrical methods have become popular in permafrost investigations as the resistivities of ice and water differ by several orders of magnitude, theoretically allowing a clear distinction between frozen and unfrozen ground. In this study we present an assessment of mountain permafrost evolution using long-term electrical resistivity tomography monitoring (ERTM) from a network of permanent sites in the central Alps. The time series consist of more than 1000 datasets from six sites, where resistivities have been measured on a regular basis for up to 20 years. We identify systematic sources of error and apply automatic filtering procedures during data processing. In order to constrain the interpretation of the results, we analyse inversion results and long-term resistivity changes in comparison with existing borehole temperature time series. Our results show that the resistivity dataset provides valuable insights at the melting point, where temperature changes stagnate due to latent heat effects. The longest time series (19 years) demonstrates a prominent permafrost degradation trend, but degradation is also detectable in shorter time series (about a decade) at most sites. In spite of the wide range of morphological, climatological, and geological differences between the sites, the observed inter-annual resistivity changes and long-term tendencies are similar for all sites of the network. [ABSTRACT FROM AUTHOR]

We investigate the influence of geomorphic and climate conditions on the spatiotemporal variability in debris flow occurrence using a dedicated hierarchical Bayesian model. The case study includes 104 catchments from the French Alps with debris flow occurrences since 1970. We identify from a list of 21 variables two geomorphic and two climate variables that explain 72% of the total variance. Lithology is identified as the primary driver (42%) of the spatiotemporal variability of debris flow activity. To analyze the effect of the duration of the observation on inferred relations, we run the model using debris flow occurrence data and climate variables from the last 12 and 23 years of the study period, respectively. The model is significant as soon as at least 23 years of observations are considered. To detect the influence of spatial variability in debris flow frequency, we partition our data set into two subsamples composed of catchments with at least or less than 4 debris flows over the period. This reveals that precipitation during the event and the 2 days before exceeding 20 mm in total are the most important variables for both subsamples. It explains at least 57% of the total variance and 73% of its climate component. We conclude that difference in debris flow occurrences from one catchment to another is mostly due to geomorphologic conditions, whereas homogeneous groups of catchments react strongly to climatic conditions in a rather similar way. [ABSTRACT FROM AUTHOR]

Near‐surface seasonal and annual mean wind speed in Switzerland is investigated using homogenized observations, Twentieth Century Reanalysis (20CRv2c) data and raw model output of a 75 member EURO‐COoRdinated Downscaling EXperiment regional climate model (RCM) ensemble for present day and future scenarios. The wind speed observations show a significant decrease in the Alps and on the southern Alpine slopes in the period 1981–2010. However, the 20CRv2c data reveal that the recent trends lie well within the decadal variability over longer time periods and no clear signs of a systematic wind stilling can be found for Switzerland. The ensemble of RCMs shows large biases in the annual mean wind speed over the Jura mountains, and some members also show large biases in the Alps compared to station observations. The spatial distribution of the model biases varies strongly between the RCMs, while the resolution and the driving global model have less impact on the pattern of the model bias. The RCMs are mostly able to represent the seasonality of wind speed on the Plateau but miss important details in complex terrain related to local wind systems. Most models show no significant changes in near‐surface mean wind speed until the end of the 21st century. The model ensemble changes range from a 7% decrease to a 6% increase with an ensemble mean decrease of 1 to 2%. Due to model biases, the scale mismatch between model grid and station observations and the missing representation of local winds in the simulations, the changes need to be interpreted with utmost care. Future assessments might lead to major revisions even for the sign of the projected changes, in particular over complex terrain. [ABSTRACT FROM AUTHOR]

The deterministic nature of conventional precipitation data sets complicates their utility in applications. The underlying estimation principle (minimizing errors) involves biases in extremes, and conventional uncertainty quantification (cross‐validation) is impractical. We present a method to derive spatial analyses of daily precipitation, probabilistically, as an ensemble, conditional on the available rain gauge data. The method builds on and extends previous techniques using conditional simulation with Gaussian Random Fields. The extension involves trans‐Gaussian and piecewise covariance modeling to let the ensemble respond to regional precipitation conditions, Bayesian inference to account for parameter uncertainty, and simulation on a primary grid to ensure the ensemble has a well‐defined areal support. While addressing prevalent issues of existing techniques, our method involves a compromise in global consistency that limits the utility of the ensemble over large domains. We apply the method to derive ensembles of area‐mean precipitation for hydrological area units in the Alps. The ensembles are demonstrated to plausibly capture variations in uncertainty with rainfall condition, rain gauge density, and averaging area. Evaluations suggest that the probabilistic estimates are internally consistent and of good statistical reliability. There is a tendency to underestimate uncertainty for light precipitation. Results point to remarkable uncertainties, even with the dense gauge networks in the Alps: For means over 500‐km2 areas we find the ensemble spread to be typically a factor of 2–4 (factor of 1.5) for intense convective (stratiform) events. This also implies nonnegligible uncertainty in climate indices. Probabilistic representation of interpolation uncertainty in spatial data sets allows users to track them into applications. Key Points: An ensemble instead of a single estimate remedies prevalent difficulties in the application of spatial precipitation data setsUncertainty in the interpolation of rain gauge data may be larger than is expected, in general, even in areas with dense networks [ABSTRACT FROM AUTHOR]

Snowpack liquid water percolation is a sensitive model process that is crucial for snowpack runoff forecasts yet varies in sensitivity between climates and snow seasons. Therefore, models of varied complexity developed for different climates and purposes use different percolation representations. We investigated how liquid fluxes in a multilayer snow model vary as represented by discrete representations of gravity drainage and snow density thresholds. We evaluated performance and sensitivity to nonphysical parameters using point measurements of snow water equivalent (SWE) at a maritime site in Washington, USA, and measurements of both SWE and runoff in the French and Swiss Alps. At all three locations, the gravity drainage simulations reduced parameter sensitivity and increased model performance. Average Nash‐Sutcliffe efficiency improved from 0.06 to 0.61 between density threshold and gravity drainage simulations with default parameters. The disparity in model performance was particularly evident at the maritime site (Washington, USA), where the gravity drainage peak SWE was biased by 6% (0.10 m) but density threshold peak SWE was biased by 85% (1.51 m). Simulated runoff and SWE also decreased in performance and increased in parameter sensitivity when including a widely used two‐layer percolation routine. This demonstrates the importance of testing and evaluating models across a wide range of climates, with close attention paid to warmer regions, where percolation has high parameter sensitivity. This is particularly important for global snow modeling and climate change scenarios where multiple regions and snow seasons must be adequately represented with a single model implementation. Key Points: Simplifying models with nonphysical parameters can lead to unexpected resultsGravity drainage with multiple layers, while still simple, consistently outperforms density threshold and two‐layer model simplificationsPercolation schemes in models should account for climates with midseason melt and rain on snow [ABSTRACT FROM AUTHOR]

The uncertainty of the precipitation parameter in the ECMWF twentieth-century (ERA-20C) centennial reanalysis is assessed by means of a comparison with the GPCC in situ product Full Data Monthly Version 7 (FDM-V7). For the spatial and temporal validation of ERA-20C, global temporal scores were calculated on monthly, seasonal, and annual time scales. These include contingency table scores, correlations, and differences in the trend, along with time series analyses. Not surprisingly, the regions with the strongest deviations correspond to regions with data scarcity, such as mountainous regions with their upwind and downwind effects, and monsoon regions. They all show a strong systematic bias (ERA-20C minus FDM-V7) and significant breaks in the time series. The mean annual global bias is about 37 mm, and the median is about 8 mm yr−1. Among the largest mean annual biases are, for example, 3361 mm in the southern Andes, 2603 mm in the Western Ghats, and 2682 mm in Papua New Guinea. However, if there is high station density, the precipitation distribution is correctly reproduced, even in orographically demanding regions such as the Alps. [ABSTRACT FROM AUTHOR]

Potential increases in extreme rainfall induced hazards in a warming climate have motivated studies to link precipitation intensities to temperature. Increases exceeding the Clausius-Clapeyron (CC) rate of 6-7%/°C-1 are seen in short-duration, convective, high-percentile rainfall at mid latitudes, but the rates of change cease or revert at regionally variable threshold temperatures due to moisture limitations. It is unclear, however, what these findings mean in term of the actual risk of extreme precipitation on a regional to local scale. When conditioning precipitation intensities on local temperatures, key influences on the scaling relationship such as from the annual cycle and regional weather patterns need better understanding. Here we analyze these influences, using sub-hourly to daily precipitation data from a dense network of 189 stations in south-eastern Austria. We find that the temperature sensitivities in the mountainous western region are lower than in the eastern lowlands. This is due to the different weather patterns that cause extreme precipitation in these regions. Sub-hourly and hourly intensities intensify at super-CC and CC-rates, respectively, up to temperatures of about 17 °C. However, we also find that, because of the regional and seasonal variability of the precipitation intensities, a smaller scaling factor can imply a larger absolute change in intensity. Our insights underline that temperature precipitation scaling requires careful interpretation of the intent and setting of the study. When this is considered, conditional scaling factors can help to better understand which influences control the intensification of rainfall with temperature on a regional scale. [ABSTRACT FROM AUTHOR]

In this study we compare three gridded observed datasets of daily precipitation (EOBS, MAP and NWIOI) over the Great Alpine Region (GAR) and a subregion in northwest Italy (NWI) in order to better understand the past variability of daily climate extremes and to set up a basis for developing regional climate scenarios. The grids are first compared with respect to their temporal similarity by calculating the correlation and relative mean absolute error of the time series. They are then compared with respect to their spatial similarity to the climatology of the ETCCDI indices (characterizing total precipitation, dry and wet spells and extremes with short return periods). The results indicate first that most EOBS gridpoint series in northeastern Italy have to be shifted back by 1 day to have maximum overlap of the measurement period and, second, that both the temporal and spatial similarities of most indices are higher between the NWIOI and MAP than between MAP or the NWIOI and EOBS. These results suggest that, although there is generally good temporal agreement between the three datasets, EOBS should be treated with caution, especially for extreme indices over the GAR region, and it does not provide reliable climatology over the NWI region. The high agreement between MAP and NWIOI, on the other hand, builds confidence in using these datasets. Users should consider carefully the limitations of the gridded observations available: the uncertainties of the observed datasets cannot be neglected in the overall uncertainties cascade that characterizes climate change studies. [ABSTRACT FROM AUTHOR]

Operational radar data reveal that precipitation systems occurring on the southern side of the Alps near Locarno, Switzerland, follow seasonal patterns of vertical reflectivity structure. Storms occurring in summer are more convective than winter season storms as indicated by more frequent observation of reflectivity at higher altitudes during summer. Individual precipitation events occurring year-round are classified by comparison to average seasonal vertical reflectivity structure. Seasonal classification of individual storms reveals a transition between winter- and summer-type storms during spring and fall that follows changes in average daily surface temperature. In addition to distinct vertical structure, summer- and winter-type storms have differences in duration, intensity, and interval between storms. Although summer- and winter-type storms result in a similar amount of total precipitation, summer-type storms have shorter duration, and therefore greater intensity. The dependence of storm types on temperature has implications for intensification of the hydrologic cycle due to climate change. Warmer winter, spring, or fall surface temperatures may affect average precipitation intensity by increasing the number of days per year that experience more intense convective precipitation while decreasing the probability of less intense stratiform precipitation. [ABSTRACT FROM AUTHOR]

The authors present stable water isotope and trace element data for fresh winter snow from two temperate maritime glaciers located on opposite sides of the New Zealand Southern Alps. The isotopes δ18O and δD were more depleted at the eastern Tasman Glacier site because of prevailing westerly flow and preferential rainout of heavy isotopes as air masses crossed the Alps. The deuterium excess provided some indication of moisture provenance, with the Tasman Sea contributing ∼70% of the moisture received at Franz Josef and Tasman Glaciers. This source signal was also evident in trace elements, with a stronger marine signal (Na, Mg, and Sr) associated with snow from the Tasman Sea and larger concentrations of terrestrial species (Pb, V, and Zr) in air masses from the Southern and Pacific Oceans. Although postdepositional modification of signals was detected, the results indicate that there is exciting potential to learn more about climate trends and moisture source pathways and to learn from geochemical signals contained in snow and ice in the New Zealand region. [ABSTRACT FROM AUTHOR]

The article discusses a reanalysis on the detection and climatology of fronts over the Alps. It provides the atmospheric fronts, local and synoptic. It states that the 3-year study is based on the non-hydrostatic model of the Consortium for Small scale Modeling (COSMO). The article also comprises the front detection scheme which includes the basic strategy, frontal motion and type, and thermal parameter.

We present an extensive new network of ring-width chronologies, comprising data from 100 sites within the Austrian Eastern Alps, made up of multiple tree species. Principal components analysis and cluster analysis were used to identify five separate high-frequency tree-growth signals from these data. Tree-growth variability at these sites is explained by site altitude and species differences that moderate the effects of the annually varying climatic forcing on tree growth. Recently developed, two-century long gridded climate data sets for the Greater Alpine Region were used to assess the relationship between climate and tree growth. Tree growth at low altitudes is controlled mainly by spring-summer moisture availability. At high altitudes precipitation is no longer a limiting factor and growth is mostly determined by summer temperature. In the intermediate altitudinal range, we did not find any direct relationships with specific climatic variables. High-altitude chronologies suitable for reconstructing past temperatures and low-altitude chronologies suitable for reconstructing past precipitation were identified. [ABSTRACT FROM AUTHOR]

This contribution provides an overview of the intricacies of mountain climates, particularly as they pertain to the European Alps. Examples will be given of issues that are related to climatic change as observed in the Alps during the course of the 20th century, and some of the physical mechanisms that may be responsible for those changes. The discussion will then focus on the problems related to assessing climatic change in regions of complex topography, the potential shifts in climate during the 21st century that the alpine region may be subjected to, and the associated climate-generated impacts on mountain environments. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary¶The Alpine Surface Radiation Budget (ASRB) project was initiated in 1994 to investigate the altitude dependence of the surface radiation budget with a particular focus on accurate measurements of the longwave downward radiation. Meanwhile broadband short- and longwave radiation fluxes are continuously measured within this network at eleven stations between 370 and 3580 m a.s.l. in the Swiss Alps. New calibration techniques, modified pyrgeometers and an adequate ventilation and heating system decreased the uncertainty for longwave radiation measurements even under harsh alpine weather conditions to about ±3 W m-2. Four years of continuous measurements of short- and longwave radiation fluxes at the ASRB stations were examined. A clear-sky climatology was determined for each station. Yearly cycles, seasonal and annual mean values and altitude gradients were analyzed for the individual radiation fluxes. Net fluxes and the surface cloud forcing was calculated for all stations. Annual mean values of global radiation demonstrate an altitude gradient of 1.3 W m-2/100 m, where as the summer gradient at stations below 2000 m a.s.l. is slightly negative due to the convective clouds at the lower mountain stations. At stations above 2800 m the vertical gradient is positive due to the multiple reflection between the clouds and the often snow covered high-alpine surrounding. Annual mean net shortwave radiation was found to be almost constant (80 W m-2) throughout the alpine stations due to the counterbalancing effect of the albedo. Longwave downward radiation fluxes show an almost linear decrease of 2.9 W m-2/100 m altitude for annual mean values. Annual mean net radiation ranges from 50 W m-2 at lower stations to almost zero (but still positive) at high altitude stations. The analysis of the cloud forcing and its seasonal influence revealed that clouds have a warming effect in the Alps (i.e. above 1500 m a.s.l.), which is maximum during the winter month (ca. 40 W m-2). [ABSTRACT FROM AUTHOR]

Climate change in the European Alps during recent years has led to decreased snow cover duration as well as increases in the frequency and intensity of summer heat waves. The risk of drought for alpine wetlands and temporary pools, which rely on water from snowmelt and provide habitat for specialist plant and amphibian biodiversity, is largely unknown and understudied in this context. Here, we test and validate a novel application of Sentinel-2 imagery aimed at quantifying seasonal variation in water surface area in the context of 95 small (median surface area <100 m2) and shallow (median depth of 20 cm) alpine wetlands in the French Alps, using a linear spectral unmixing approach. For three study years (2016–2018), we used path-analysis to correlate mid-summer water surface area to annual metrics of snowpack (depth and duration) and spring and summer climate (temperature and precipitation). We further sought to evaluate potential biotic responses to drought for study years by monitoring the survival of common frog (Rana temporaria) tadpoles and wetland plant biomass production quantified using peak Normalized Difference Vegetation Index (NDVI). We found strong agreement between citizen science-based observations of water surface area and Sentinel-2 based estimates (R2 = 0.8–0.9). Mid-summer watershed snow cover duration and summer temperatures emerged as the most important factors regulating alpine wetland hydrology, while the effects of summer precipitation, and local and watershed snow melt-out timing were not significant. We found that a lack of summer snowfields in 2017 combined with a summer heat wave resulted in a significant decrease in mid-summer water surface area, and led to the drying up of certain wetlands as well as the observed mortality of tadpoles. We did not observe a negative effect of the 2017 summer on the biomass production of wetland vegetation, suggesting that wetlands that maintain soil moisture may act as favorable microhabitats for above treeline vegetation during dry years. Our work introduces a remote sensing-based protocol for monitoring the surface hydrology of alpine wetland habitats at the regional scale. Given that climate models predict continued reduction of snow cover in the Alps during the coming years, as well as particularly intense warming during the summer months, our conclusions underscore the vulnerability of alpine wetlands in the face of ongoing climate change. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]