About the Influence of Snow Cover on the Climate of the Alps

2000 ◽  
pp. 193-218
Author(s):  
Nico Stehr ◽  
Hans von Storch
Keyword(s):  
Snow Cover ◽  
The Alps

scholarly journals Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps – a matter of model limitations or unpredictable nature?

2014 ◽  
Vol 18 (6) ◽  
pp. 2265-2285 ◽  
Author(s):  
O. Rössler ◽  
P. Froidevaux ◽  
U. Börst ◽  
R. Rickli ◽  
O. Martius ◽  
...  
Keyword(s):  
Snow Cover ◽  
Temperature Increase ◽  
Hydrological Model ◽  
Small Scale ◽  
The South ◽  
Flood Peak ◽  
Forecast Data ◽  
The Alps ◽  
Model Setup ◽  
Local Rainfall

Abstract. A rain-on-snow flood occurred in the Bernese Alps, Switzerland, on 10 October 2011, and caused significant damage. As the flood peak was unpredicted by the flood forecast system, questions were raised concerning the causes and the predictability of the event. Here, we aimed to reconstruct the anatomy of this rain-on-snow flood in the Lötschen Valley (160 km2) by analyzing meteorological data from the synoptic to the local scale and by reproducing the flood peak with the hydrological model WaSiM-ETH (Water Flow and Balance Simulation Model). This in order to gain process understanding and to evaluate the predictability. The atmospheric drivers of this rain-on-snow flood were (i) sustained snowfall followed by (ii) the passage of an atmospheric river bringing warm and moist air towards the Alps. As a result, intensive rainfall (average of 100 mm day-1) was accompanied by a temperature increase that shifted the 0° line from 1500 to 3200 m a.s.l. (meters above sea level) in 24 h with a maximum increase of 9 K in 9 h. The south-facing slope of the valley received significantly more precipitation than the north-facing slope, leading to flooding only in tributaries along the south-facing slope. We hypothesized that the reason for this very local rainfall distribution was a cavity circulation combined with a seeder-feeder-cloud system enhancing local rainfall and snowmelt along the south-facing slope. By applying and considerably recalibrating the standard hydrological model setup, we proved that both latent and sensible heat fluxes were needed to reconstruct the snow cover dynamic, and that locally high-precipitation sums (160 mm in 12 h) were required to produce the estimated flood peak. However, to reproduce the rapid runoff responses during the event, we conceptually represent likely lateral flow dynamics within the snow cover causing the model to react "oversensitively" to meltwater. Driving the optimized model with COSMO (Consortium for Small-scale Modeling)-2 forecast data, we still failed to simulate the flood because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus we conclude that this rain-on-snow flood was, in general, predictable, but requires a special hydrological model setup and extensive and locally precise meteorological input data. Although, this data quality may not be achieved with forecast data, an additional model with a specific rain-on-snow configuration can provide useful information when rain-on-snow events are likely to occur.

scholarly journals Relationship between Spatiotemporal Variations of Climate, Snow Cover and Plant Phenology over the Alps—An Earth Observation-Based Analysis

2018 ◽  
Vol 10 (11) ◽  
pp. 1757 ◽  
Author(s):  
Sarah Asam ◽  
Mattia Callegari ◽  
Michael Matiu ◽  
Giuseppe Fiore ◽  
Ludovica De Gregorio ◽  
...  
Keyword(s):  
Snow Cover ◽  
Regional Scale ◽  
Temporal Trends ◽  
Earth Observation ◽  
European Alps ◽  
Climate Variables ◽  
South Tyrol ◽  
Mean Temperature ◽  
The Alps ◽  
The Relationship

Alpine ecosystems are particularly sensitive to climate change, and therefore it is of significant interest to understand the relationships between phenology and its seasonal drivers in mountain areas. However, no alpine-wide assessment on the relationship between land surface phenology (LSP) patterns and its climatic drivers including snow exists. Here, an assessment of the influence of snow cover variations on vegetation phenology is presented, which is based on a 17-year time-series of MODIS data. From this data snow cover duration (SCD) and phenology metrics based on the Normalized Difference Vegetation Index (NDVI) have been extracted at 250 m resolution for the entire European Alps. The combined influence of additional climate drivers on phenology are shown on a regional scale for the Italian province of South Tyrol using reanalyzed climate data. The relationship between vegetation and snow metrics strongly depended on altitude. Temporal trends towards an earlier onset of vegetation growth, increasing monthly mean NDVI in spring and late summer, as well as shorter SCD were observed, but they were mostly non-significant and the magnitude of these tendencies differed by altitude. Significant negative correlations between monthly mean NDVI and SCD were observed for 15–55% of all vegetated pixels, especially from December to April and in altitudes from 1000–2000 m. On the regional scale of South Tyrol, the seasonality of NDVI and SCD achieved the highest share of correlating pixels above 1500 m, while at lower elevations mean temperature correlated best. Examining the combined effect of climate variables, for average altitude and exposition, SCD had the highest effect on NDVI, followed by mean temperature and radiation. The presented analysis allows to assess the spatiotemporal patterns of earth-observation based snow and vegetation metrics over the Alps, as well as to understand the relative importance of snow as phenological driver with respect to other climate variables.

scholarly journals Contrasting seasonal changes in temperature, precipitation and snow cover simulated over the European Alps during the twentieth century

2021 ◽  
Author(s):  
Martin Ménégoz ◽  
Julien Beaumet ◽  
Hubert Gallée ◽  
Xavier Fettweis ◽  
Samuel Morin ◽  
...  
Keyword(s):  
Snow Cover ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Decadal Variability ◽  
Regional Climate ◽  
Horizontal Resolution ◽  
Glacier Mass Balance ◽  
European Alps ◽  
Climate Trends ◽  
The Alps

<p>The evolution of temperature, precipitation and snow cover in the European Alps have been simulated with the regional climate model MAR applied with a 7 kilometre horizontal resolution and driven by the ERA-20C (1902-2010) and the ERA5 reanalyses (1981-2018). A comparison with observational datasets, including French and Swiss local meteorological stations, in-situ glacier mass balance measurements and reanalysis product demonstrates high model skill for snow cover duration and snow water equivalent (SWE) as well as for the climatology and the inter-annual variability of both temperature and precipitation. The relatively high resolution allows to estimate the meteorological variables up to 3000m.a.s.l. The vertical gradient of precipitation simulated by MAR over the European Alps reaches 33% km-1 (1.21 mmd-1.km-1) in summer and 38%km-1 (1.15mmd mmd-1.km-1) in winter, on average over 1971–2008 and shows a large spatial variability. This study evidences seasonal and altitudinal contrasts of climate trends over the Alps. A significant (pvalue< 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, a signal strongly modulated by multi-decadal variability during the second part of the century. 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 smaller (<10%) and not significant above 1500ma.s.l. Over 1903–2010, the maximum of daily precipitation (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 (pvalue<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. Rx1day increase occurs where the annual correlation between temperature and intense precipitation is high. The highest warming rates in MAR are found at low elevations (< 1000 m a.s.l) in winter, whereas they are found at high elevations (> 2000 m a.s.l) in summer. In spring, warming trends show a maximum at intermediate elevations (1500 m to 1800 m). Our results suggest that higher warming at these elevations is mostly linked with the snow-albedo feedback in spring and summer.</p>

The Alpine “Iceman” and Holocene Climatic Change

1996 ◽  
Vol 46 (1) ◽  
pp. 78-83 ◽  
Author(s):  
Carlo Baroni ◽  
Giuseppe Orombelli
Keyword(s):  
Snow Cover ◽  
Climatic Change ◽  
Environmental Conditions ◽  
Buried Soils ◽  
Climatic Warming ◽  
Alpine Glacier ◽  
The Holocene ◽  
Glacier Shrinkage ◽  
New Information ◽  
The Alps

The finding of a prehistoric mummified corpse at the upper edge of the accumulation area of an alpine glacier, together with its unique set of artifacts, provided new information on glacier dimensions during the little-known phases of major glacier shrinkage that characterized the warmest parts of the Holocene. The sudden burial of the corpse in a permanent snow cover occurred 5300–5050 cal yr B.P., indicating a significant climatic change that induced glacier expansion at the beginning of Neoglaciation. New geomorphologic data and two AMS 14C ages from buried soils suggest that the present glacier size, following over 100 yr of shrinkage, is comparable to that immediately preceding Neoglaciation. Therefore, we can deduce that the current global climatic warming may have interrupted the environmental conditions prevailing in the Alps during Neoglacial time, restoring characteristics similar to those prevailing during the climatic optimum that were never achieved during the second half of the Holocene.

scholarly journals “WEBSNOW”: ESTIMATION OF SNOW COVER FROM FREELY ACCESSIBLE WEBCAM IMAGES IN THE ALPS

2020 ◽  
Vol V-2-2020 ◽  
pp. 695-701
Author(s):  
S. Flöry ◽  
C. Ressl ◽  
M. Hollaus ◽  
G. Pürcher ◽  
L. Piermattei ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Snow Cover ◽  
Temporal Resolution ◽  
Small Scale ◽  
Mountain Areas ◽  
Processing Times ◽  
Temporal And Spatial Variability ◽  
The Alps ◽  
Temporal And Spatial ◽  
Aerial Platforms

Abstract. The alpine snow cover exhibits a high spatial variability in the horizontal and vertical directions even on a very small scale, mainly caused by the high variability of alpine terrain. To quantify the annual and inter-annual snow dynamics continuously reliable measurements of the temporal and spatial variability are required. While remote sensing from satellite and aerial platforms have been successfully used to estimate snow cover at larger scales, especially in mountain areas spatial and temporal resolution are too low to capture local changes. In the alpine region, webcam images are freely available for touristic purposes capturing images at high frequency intervals. Within the WebSnow project the feasibility of using such images for the detection of snow was investigated. With the developed workflow, processing times could be reduced and satisfactory results obtained. Our results show, that webcam networks have the potential for monitoring snow at high spatial and temporal resolution.

scholarly journals Operational sub-pixel snow mapping over the Alps with NOAA AVHRR data

2004 ◽  
Vol 38 ◽  
pp. 245-252 ◽  
Author(s):  
Nando Foppa ◽  
Stefan Wunderle ◽  
David Oesch ◽  
Florian Kuchen
Keyword(s):  
Snow Cover ◽  
Real Time ◽  
Principal Component ◽  
European Alps ◽  
Complex Topography ◽  
Heterogeneous Terrain ◽  
Noaa Avhrr ◽  
Research Activities ◽  
The Alps ◽  
Pixel Scale

AbstractThis study is part of research activities concentrating on the real-time application of the U.S. National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) sensor for snow-cover analysis of the European Alps. For mapping snow cover in heterogeneous terrain, we implement the widely used linear spectral mixture algorithm to estimate snow cover at sub-pixel scale. Principal component analysis, including the reflective part of AVHRR channel 3, is used to estimate fractions of “snow” and “not snow” within a pixel, using linear mixture modeling. The combination of these features leads to a fast, simple solution for operational and near-real-time processing. The presented algorithm is applied on the European Alps on 17 January 2003 and successfully maps snow at sub-pixel scale. The detailed snow-cover information makes it easy to recognize the complex topography of the Alps, more so than with either a classic binary map or a Moderate Resolution Imaging Spectroradiometer (MODIS) snow product. The sub-pixel algorithm reasonably identifies snow-cover fractions in regions and at altitudes where neither the classic binary map nor the MODIS algorithm detects any snow. Differences concerning the snow distribution are found in forested areas as well as in the lowest-elevation zones. The algorithm substantially improves snow mapping over complex topography for operational and near-realtime applications.

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