scholarly journals Observed snow depth trends in the European Alps 1971 to 2019

2020 ◽  
Author(s):  
Michael Matiu ◽  
Alice Crespi ◽  
Giacomo Bertoldi ◽  
Carlo Maria Carmagnola ◽  
Christoph Marty ◽  
...  
Keyword(s):  
Snow Depth ◽  
Principal Component ◽  
Alpine Region ◽  
European Alps ◽  
Climatic Forcing ◽  
Climate Zones ◽  
Modes Of Variability ◽  
Regional Trends ◽  
Spatial Coverage ◽  
Regional Analyses

Abstract. The European Alps stretch over a range of climate zones, which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine wide analysis of snow depth from six Alpine countries: Austria, France, Germany, Italy, Slovenia, and Switzerland; including altogether more than 2000 stations. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions, which match the climatic forcing zones: north and high Alpine, northeast, northwest, southeast and southwest. Linear trends of mean monthly snow depth between 1971 to 2019 showed decreases in snow depth for 87 % of the stations. December to February trends were on average −1.1 cm decade−1 (min, max: −10.8, 4.4; elevation range 0–1000 m), −2.5 (−25.1, 4.4; 1000–2000 m) and −0.1 (−23.3, 9.9; 2000–3000 m), with stronger trends in March to May: −0.6 (−10.9, 1.0; 0–1000 m), −4.6 (−28.1, 4.1; 1000–2000 m) and −7.6 (−28.3, 10.5; 2000–3000 m). However, regional trends differed substantially, which challenges the notion of generalizing results from one Alpine region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

scholarly journals Observed snow depth trends in the European Alps 1971 to 2019

2021 ◽  
Author(s):  
Michael Matiu ◽  
Alice Crespi ◽  
Giacomo Bertoldi ◽  
Carlo Maria Carmagnola ◽  
Christoph Marty ◽  
...  
Keyword(s):  
Snow Depth ◽  
Principal Component ◽  
European Alps ◽  
Climatic Forcing ◽  
Modes Of Variability ◽  
Regional Trends ◽  
Spatial Coverage ◽  
Trend Assessment ◽  
Snow Cover Duration ◽  
Regional Analyses

<p>The European Alps stretch over a range of climate zones, which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses, which complicates comparisons between regions and makes Alpine wide conclusions questionable. Here, we present an Alpine wide analysis of snow depth from six Alpine countries: Austria, France, Germany, Italy, Slovenia, and Switzerland; including altogether more than 2000 stations, of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions, which match the climatic forcing zones: north & high Alpine, northeast, northwest, southeast, and south & high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations for November to May. The average trend among all stations for seasonal (November to May) mean snow depth was -8.4 % per decade, for seasonal maximum snow depth -5.6 % per decade, and for seasonal snow cover duration -5.6 % per decade. However, regional trends differed substantially after accounting for elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.</p>

scholarly journals Observed snow depth trends in the European Alps: 1971 to 2019

2021 ◽  
Vol 15 (3) ◽  
pp. 1343-1382
Author(s):  
Michael Matiu ◽  
Alice Crespi ◽  
Giacomo Bertoldi ◽  
Carlo Maria Carmagnola ◽  
Christoph Marty ◽  
...  
Keyword(s):  
Snow Depth ◽  
Principal Component ◽  
European Alps ◽  
North West ◽  
Modes Of Variability ◽  
North East ◽  
Regional Trends ◽  
Spatial Coverage ◽  
Snow Cover Duration ◽  
Regional Analyses

Abstract. The European Alps stretch over a range of climate zones which affect the spatial distribution of snow. Previous analyses of station observations of snow were confined to regional analyses. Here, we present an Alpine-wide analysis of snow depth from six Alpine countries – Austria, France, Germany, Italy, Slovenia, and Switzerland – including altogether more than 2000 stations of which more than 800 were used for the trend assessment. Using a principal component analysis and k-means clustering, we identified five main modes of variability and five regions which match the climatic forcing zones: north and high Alpine, north-east, north-west, south-east, and south and high Alpine. Linear trends of monthly mean snow depth between 1971 and 2019 showed decreases in snow depth for most stations from November to May. The average trend among all stations for seasonal (November to May) mean snow depth was −8.4 % per decade, for seasonal maximum snow depth −5.6 % per decade, and for seasonal snow cover duration −5.6 % per decade. Stronger and more significant trends were observed for periods and elevations where the transition from snow to snow-free occurs, which is consistent with an enhanced albedo feedback. Additionally, regional trends differed substantially at the same elevation, which challenges the notion of generalizing results from one region to another or to the whole Alps. This study presents an analysis of station snow depth series with the most comprehensive spatial coverage in the European Alps to date.

scholarly journals The climate of the European Alps: Shift of very high resolution Köppen-Geiger climate zones 1800–2100

2017 ◽  
Vol 26 (2) ◽  
pp. 115-125 ◽  
Author(s):  
Franz Rubel ◽  
Katharina Brugger ◽  
Klaus Haslinger ◽  
Ingeborg Auer
Keyword(s):  
High Resolution ◽  
European Alps ◽  
Climate Zones ◽  
Very High

Soil sampling design optimization by using conditioned Latin Hypercube sampling    

2021 ◽  
Author(s):  
Fatemeh Hateffard ◽  
Tibor József Novák
Keyword(s):  
Principal Component ◽  
Latin Hypercube Sampling ◽  
Feature Space ◽  
Simple Random Sampling ◽  
Soil Sampling ◽  
Latin Hypercube ◽  
Landsat Images ◽  
Original Distribution ◽  
Spatial Coverage ◽  
Elevation Model

<p>One of the most critical steps in digital soil mapping is finding a sampling approach to cover a good spatial coverage of the area regarding the soil spatial variation. In this matter, environmental variables can aid in taking samples in more innovative and more precise locations while reducing the soil sampling efforts such as time and costs. Conditioned Latin hypercube sampling (cLHS) is a stratified random design strategy that perfectly represents the variability of auxiliary variables in feature space. This study applied this method and compared it to simple random sampling to optimize sampling designs for mapping in the agricultural study site in Hungary. The covariates were indices extracted by the digital elevation model and Landsat images. The principal component analysis (PCA) was applied to reduce the data overlap and select the most important variables as the model's inputs. By computing the statistical criteria (mean, variance, standard deviation, etc.) for covariates and comparing these results between the sampling populations and the entire one, we may conclude that both designs gave almost similar predictions. However, for most covariates, statistical means of cLHS provide the closest approximation compared to the random approach sampling method, but the statistical variances and SDs retrieved similar results. Furthermore, the histogram distribution of most variables in the cLHS was following more closely to the original distribution of the environmental covariates. Overall, considering the type of the study site and the chosen variables, it seems that cLHS is a more applicable method.</p> <p> </p>

Observing Snow Depth at Sub-Kilometer Resolution over the European Alps from Sentinel-1

2021 ◽  
Author(s):  
Hans Lievens ◽  
Isis Brangers ◽  
Hans-Peter Marshall ◽  
Tobias Jonas ◽  
Marc Olefs ◽  
...  
Keyword(s):  
Snow Depth ◽  
European Alps

Climate change and tick-borne encephalitis in the Greater Alpine region.

2021 ◽  
pp. 354-359
Author(s):  
Franz Rubel
Keyword(s):  
Climate Change ◽  
Far East ◽  
Climate Change Impacts ◽  
Alpine Region ◽  
European Alps ◽  
Far East Of Russia ◽  
The Caucasus ◽  
Tick Density ◽  
Tick Borne Encephalitis ◽  
Tick Borne Disease

Abstract Tick-borne encephalitis (TBE) is a viral tick-borne disease. The distribution of human TBE cases ranges from the French departments bordering Germany through Central and Eastern Europe, the Caucasus and Kazakhstan to the Far East of Russia and China. In this expert opinion, TBE is described in the greater area of the European Alps, denoted as the Greater Alpine Region (GAR). It also includes reported tick-borne encephalitis cases and evidence for climate change impacts on tick density and distribution as well as the prevalence and intensity of TBE.

Geographic Variation in Habitat Structure of the Black-Throated Green Warbler (Dendroica virens)

The Auk ◽  
1983 ◽  
Vol 100 (2) ◽  
pp. 382-389 ◽  
Author(s):  
Scott L. Collins
Keyword(s):  
New York ◽  
Plant Community ◽  
Habitat Structure ◽  
Habitat Management ◽  
Principal Component ◽  
Structural Features ◽  
Wide Range ◽  
White Mountain National Forest ◽  
Study Sites ◽  
Regional Analyses

Abstract Habitat structure of the Black-throated Green Warbler (Dendroica virens) was examined at five study sites: (1) Mount Desert Island, Maine; (2) Mount Blue State Park, Maine; (3) White Mountain National Forest, New Hampshire; (4) southern Adirondacks, New York; and (5) Itasca State Park, Minnesota. Principal component analysis of 13 habitat-structure variables measured at each site produced habitat gradients from tall to shorter canopies, large to smaller trees, and coniferous to deciduous forests. A second ordination indicated that the habitat sampled included five plant-community types: pine forests, spruce-arbor vitae, balsam fir, mixed spruce-fir-deciduous, and beech-maple-birch. Consistent structural features within the total range of habitats sampled were difficult to identify. I suggest that widely occurring species such as the Black-throated Green Warbler have a wide range of habitats with a suitable structure and that regional analyses, even within a single plant-community type, may be of limited value with regard to habitat management when considering the entire range of many species.

Historical Land Uses and Their Changes in the European Alps

2019 ◽  
Author(s):  
Ulrike Tappeiner ◽  
Erich Tasser
Keyword(s):  
Land Use ◽  
20Th Century ◽  
Land Reclamation ◽  
Alpine Region ◽  
Ecosystem Functions ◽  
Mountain Range ◽  
European Alps ◽  
Ligurian Sea ◽  
Arable Farming ◽  
The Alps

The Alps are the highest and largest mountain range in Europe. They extend from the Ligurian Sea to the Pannonian Basin in an arc 744 miles (1,200 km) long and between 93 and 155 miles (150–250 km) wide. The settlement history of this large European landscape is closely linked to the settlement of Europe as a whole, whereby the inner Alpine region was not permanently settled until around 4500 bce because of topographical and climatic disadvantages. Dense forest cover initially made it difficult to use large grazing areas, but transhumance gradually developed in the Alpine region when the animals spent their summers high up in the mountains and their winters in the valleys. At about the same time, the Alpine self-sufficiency economy of arable farming and livestock breeding was added, which made permanent settlement possible. However, the most intensive settlement and land reclamation advance took place in the Middle Ages. In the 19th century, industrialization reached the Alpine region a little delayed, and globalization in the middle of the 20th century. This also led to a fundamental change in society. The previous agricultural society was replaced by the service society of the 20th century. Developments since the late 1950s have taken place against the background of developments in the European Union (EU) as a whole, above all the Common Agricultural Policy and the European Spatial Development Perspective (ESDP), but these developments were and still are influenced by additional agreements specific to the Alps, such as the Alpine Convention, the Alpine Protection Commission (CIPRA), and the Alpine Working Community (Arge Alp). All these factors mean that historical and current development of land use in the Alpine region has been and is always linked to developments in Europe. Many studies on land use in the Alpine region should therefore be seen in this context. Moreover, past land use often has long-lasting legacy effects on ecosystems and their development. Therefore, in this article we deal not only with historical land use but also with current and future developments and their impacts on ecosystem functions and services.

scholarly journals Evaluation of Multi-Reanalysis Solar Radiation Products Using Global Surface Observations

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 42 ◽  
Author(s):  
Xiaomin Peng ◽  
Jiangfeng She ◽  
Shuhua Zhang ◽  
Junzhong Tan ◽  
Yang Li
Keyword(s):  
Solar Radiation ◽  
Large Scale ◽  
Spatial Scales ◽  
Global Solar Radiation ◽  
Hydrological Process ◽  
China Meteorological Administration ◽  
Surface Solar Radiation ◽  
Climate Zones ◽  
Tropical Regions ◽  
Spatial Coverage

Solar radiation incident at the Earth’s surface is an essential driver of the energy exchange between the atmosphere and the surface and is also an important input variable in the research on the surface eco-hydrological process. The reanalysis solar radiation dataset is characterized by a long time series and wide spatial coverage and is used in the research of large-scale eco-hydrological processes. Due to certain errors in their production process of the reanalysis of solar radiation products, reanalysis products should be evaluated before application. In this study, three global solar-radiation reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) in different temporal scales and climate zones were evaluated using surface solar-radiation observations from the National Meteorological Information Center of the China Meteorological Administration (CMA, Beijing, China) and the Global Energy Balance Archive (GEBA, Zürich, Switzerland) from 2000 to 2009. All reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) overestimated with an annual bias of 14.86 W/m2, 22.61 W/m2, and 31.85 W/m2; monthly bias of 15.17 W/m2, 21.29 W/m2, and 36.91 W/m2; and seasonal bias of 15.08 W/m2, 21.21 W/m2, and 36.69 W/m2, respectively. In different Köppen climate zones, the annual solar radiation of ERA-Interim performed best in cold regions with a bias of 10.30 W/m2 and absolute relative error (ARE) of 8.98%. However, JRA-55 and NCEP-DOE showed the best performance in tropical regions with a bias of 20.08 W/m2 and −0.12 W/m2, and ARE of 11.00% and 9.68%, respectively. Overall, through the evaluations across different temporal and spatial scales, the rank of the three reanalysis products in order was the ERA-Interim, JRA-55, and NCEP-DOE. In addition, based on the evaluation, we analyzed the relationship between the error (ARE) of the reanalysis products and cloud cover, aerosol, and water vapor, which significantly influences solar radiation and we found that cloud was the main cause for errors in the three solar radiation reanalysis products. The above can provide a reference for the application and downscaling of the three solar radiation reanalysis products.

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