Elevation-dependent trends in extreme snowfall in the French Alps from 1959 to 2019

Abstract. Climate change projections indicate that extreme snowfall is expected to increase in cold areas, i.e., at high latitudes and/or high elevation, and to decrease in warmer areas, i.e., at mid-latitudes and low elevation. However, the magnitude of these contrasting patterns of change and their precise relations to elevation at the scale of a given mountain range remain poorly known. This study analyzes annual maxima of daily snowfall based on the SAFRAN reanalysis spanning the time period 1959–2019 and provided within 23 massifs in the French Alps every 300 m of elevation. We estimate temporal trends in 100-year return levels with non-stationary extreme value models that depend on both elevation and time. Specifically, for each massif and four elevation ranges (below 1000, 1000–2000, 2000–3000, and above 3000 m), temporal trends are estimated with the best extreme value models selected on the basis of the Akaike information criterion. Our results show that a majority of trends are decreasing below 2000 m and increasing above 2000 m. Quantitatively, we find an increase in 100-year return levels between 1959 and 2019 equal to +23 % (+32kgm-2) on average at 3500 m and a decrease of −10 % (-7kgm-2) on average at 500 m. However, for the four elevation ranges, we find both decreasing and increasing trends depending on location. In particular, we observe a spatially contrasting pattern, exemplified at 2500 m: 100-year return levels have decreased in the north of the French Alps while they have increased in the south, which may result from interactions between the overall warming trend and circulation patterns. This study has implications for natural hazard management in mountain regions.

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Elevation-dependent trends in extreme snowfall in the French Alps from 1959 to 2019

10.5194/tc-2021-64 ◽

2021 ◽

Author(s):

Erwan Le Roux ◽

Guillaume Evin ◽

Nicolas Eckert ◽

Juliette Blanchet ◽

Samuel Morin

Keyword(s):

Temporal Trends ◽

Information Criterion ◽

Warming Trend ◽

High Elevation ◽

Extreme Value ◽

Mountain Range ◽

French Alps ◽

The North ◽

Return Levels ◽

Increasing Trends

Abstract. Climate change projections indicate that extreme snowfall are expected to increase in cold areas, i.e. at high latitude and/or high elevation, and to decrease in warmer areas, i.e. at mid-latitude and low elevation. However, the magnitude of these contrasted patterns of change and their precise relations to elevation at the scale of a given mountain range remain ill-known. This study analyzes annual maxima of daily snowfall based on the SAFRAN reanalysis spanning the time period 1959–2019, and provided within 23 massifs in the French Alps every 300 m of elevation. We estimate temporal trends in 100-year return levels with non-stationary extreme value models that depend both on elevation and time. Specifically, for each massif and four elevation ranges (below 1000 m, 1000–2000 m, 2000–3000 m and above 3000 m), temporal trends are estimated with the best extreme value models selected on the basis of the Akaike information criterion. Our results show that a majority of trends are decreasing below 2000 m and increasing above 2000 m. Quantitatively, we find an increase of 100-year return levels between 1959 and 2019 equal to +23 % (+32 kg m−2) on average at 3500 m, and a decrease of −10 % (−7 kg m−2) on average at 500 m. However, for the four elevation ranges, we find both decreasing and increasing trends depending on location. In particular, we observe a spatially contrasted pattern, exemplified at 2500 m: 100-year return levels have decreased in the north of the French Alps while they have increased in the south which may result from interactions between the overall warming trend and circulation patterns. This study has implications for natural hazards management in mountain regions.

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Reanalysis of 47 Years of Climate in the French Alps (1958–2005): Climatology and Trends for Snow Cover

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc1810.1 ◽

2009 ◽

Vol 48 (12) ◽

pp. 2487-2512 ◽

Cited By ~ 137

Author(s):

Yves Durand ◽

Gérald Giraud ◽

Martin Laternser ◽

Pierre Etchevers ◽

Laurent Mérindol ◽

...

Keyword(s):

Snow Cover ◽

Snow Depth ◽

Numerical Models ◽

High Elevation ◽

Climatic Conditions ◽

Spatial And Temporal Variability ◽

The South ◽

French Alps ◽

Mountainous Regions ◽

The North

Abstract Since the early 1990s, Météo-France has used an automatic system combining three numerical models to simulate meteorological parameters, snow cover stratigraphy, and avalanche risk at various altitudes, aspects, and slopes for a number of mountainous regions (massifs) in the French Alps and the Pyrenees. This Système d’Analyse Fournissant des Renseignements Atmosphériques à la Neige (SAFRAN)–Crocus–Modèle Expert de Prévision du Risque d’Avalanche (MEPRA) model chain (SCM), usually applied to operational daily avalanche forecasting, is here used for retrospective snow and climate analysis. For this study, the SCM chain used both meteorological observations and guess fields mainly issued from the newly reanalyzed atmospheric model 40-yr ECMWF Re-Analysis (ERA-40) data and ran on an hourly basis over a period starting in the winter of 1958/59 until recent past winters. Snow observations were finally used for validation, and the results presented here concern only the main climatic features of the alpine modeled snowfields at different spatial and temporal scales. The main results obtained confirm the very significant spatial and temporal variability of the modeled snowfields with regard to certain key parameters such as those describing ground coverage or snow depth. Snow patterns in the French Alps are characterized by a marked declining gradient from the northwestern foothills to the southeastern interior regions. This applies mainly to both depths and durations, which exhibit a maximal latitudinal variation at 1500 m of about 60 days, decreasing strongly with the altitude. Enhanced at low elevations, snow depth shows a mainly negative temporal variation over the study period, especially in the north and during late winters, while the south exhibits more smoothed features. The number of days with snow on the ground shows also a significant general signal of decrease at low and midelevation, but this signal is weaker in the south than in the north and less visible at high elevation. Even if a statistically significant test cannot be performed for all elevations and areas, the temporal decrease is present in all the studied quantities. Concerning snow duration, this general decrease can also be interpreted as a sharp variation of the mean values at the end of the 1980s, inducing a step effect in its time series rather than a constant negative temporal trend. The results have also been interpreted in terms of potential for a viable ski industry, especially in the southern areas, and for different changing climatic conditions. Presently, French downhill ski resorts are economically viable from a range of about 1200 m MSL in the northern foothills to 2000 m in the south, but future prospects are uncertain. In addition, no clear and direct relationship between the North Atlantic Oscillation (NAO) or the ENSO indexes and the studied snow parameters could be established in this study.

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One Hundred Years of Solitude: rediscovery of Catasticta lycurgus (Godman & Salvin, 1880), a yellow butterfly from the Sierra Nevada de Santa Marta, Colombia (Lepidoptera: Pieridae)

Zootaxa ◽

10.11646/zootaxa.4975.1.7 ◽

2021 ◽

Vol 4975 (1) ◽

pp. 176-186

Author(s):

BLANCA HUERTAS ◽

CARLOS PRIETO ◽

FREDY MONTERO ◽

MIKE ADAMS ◽

JEAN FRANÇOIS LE CROM ◽

...

Keyword(s):

Sierra Nevada ◽

High Elevation ◽

Mountain Range ◽

Conservation Assessment ◽

The North ◽

The Andes ◽

San Pedro ◽

Systematic Relationships ◽

The Uk ◽

First Time

Catasticta lycurgus is a striking endemic butterfly, restricted to high elevation habitats in the Sierra Nevada de Santa Marta, an isolated mountain range separate from the Andes in the north of Colombia. The type, which for almost a hundred years was the only known specimen, was collected in 1878 by Frederick Simons in the vicinity of Atánquez and was sent to the UK to be described by renowned naturalists Godman and Salvin in 1880. In 1972, explorers Adams and Bernard collected a second specimen of C. lycurgus in the locality of San Pedro at 2,900m of elevation in the Sierra Nevada de Santa Marta. These two specimens were the only known ones for many decades until recently, when Colombian entomologists found the species again in San Pedro de la Sierra and later, when a female was discovered in 2013. Here, we report the rediscovery of this rare and charismatic species, with new specimens collected near the type locality, which have not been reported previously. The female of C. lycurgus is described and illustrated for the first time as well the male genitalia of this species. We combine all information available to provide some insights on the systematic relationships of this species within the genus Catasticta Butler, discuss its distribution and provide a preliminary conservation assessment. Despite the newly collected specimens, the species remains very rare in the field and in collections.

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Climate-driven biophysical changes in feeding and breeding environments explain the decline of southernmost European Atlantic salmon populations

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2018-0297 ◽

2019 ◽

Vol 76 (9) ◽

pp. 1581-1595 ◽

Cited By ~ 4

Author(s):

Ana Almodóvar ◽

Daniel Ayllón ◽

Graciela G. Nicola ◽

Bror Jonsson ◽

Benigno Elvira

Keyword(s):

Atlantic Salmon ◽

Regime Shift ◽

Temporal Trends ◽

Atlantic Multidecadal Oscillation ◽

Warming Trend ◽

Trophic Conditions ◽

Proximate Cause ◽

The North ◽

Spanish Atlantic ◽

Biophysical Changes

The consistency of the global declining trend of Atlantic salmon (Salmo salar) populations suggests that climate-driven reduced survival and growth at sea are the main driving factors. The southernmost populations have experienced the greatest declines, consistent with harsher conditions in natal fresh waters. We analyzed temporal trends in Spanish Atlantic salmon, important food organisms at sea, and climatic variables in the breeding (fresh water) and feeding (marine) salmon areas from 1950 onwards to elucidate drivers of declining patterns. Salmon abundance dropped abruptly in 1970–1971, plausibly linked to widespread overfishing coincident with incipient changes in the marine food webs and freshwater hydrology. A major regime shift in biophysical conditions throughout the North Atlantic salmon feeding grounds occurred in 1986–1987, driven by the concurrence of an abrupt acceleration in the anthropogenic warming trend and the warm phase of the Atlantic Multidecadal Oscillation. This regime shift may be the proximate cause of the collapse of Spanish salmon observed in 1988–1989, which kept declining in parallel to trends of ever-increasing ocean and freshwater temperatures, decreasing river flows, and poorer marine trophic conditions.

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Non-stationary extreme value analysis of ground snow loads in the French Alps: a comparison with building standards

Natural Hazards and Earth System Science ◽

10.5194/nhess-20-2961-2020 ◽

2020 ◽

Vol 20 (11) ◽

pp. 2961-2977

Author(s):

Erwan Le Roux ◽

Guillaume Evin ◽

Nicolas Eckert ◽

Juliette Blanchet ◽

Samuel Morin

Keyword(s):

Snow Depth ◽

Extreme Value ◽

Extreme Value Analysis ◽

Snow Density ◽

Value Analysis ◽

French Alps ◽

Return Levels ◽

Snow Loads ◽

Structure Collapse ◽

Building Standards

Abstract. In a context of climate change, trends in extreme snow loads need to be determined to minimize the risk of structure collapse. We study trends in 50-year return levels of ground snow load (GSL) using non-stationary extreme value models. These trends are assessed at a mountain massif scale from GSL data, provided for the French Alps from 1959 to 2019 by a meteorological reanalysis and a snowpack model. Our results indicate a temporal decrease in 50-year return levels from 900 to 4200 m, significant in the northwest of the French Alps up to 2100 m. We detect the most important decrease at 900 m with an average of −30 % for return levels between 1960 and 2010. Despite these decreases, in 2019 return levels still exceed return levels designed for French building standards under a stationary assumption. At worst (i.e. at 1800 m), return levels exceed standards by 15 % on average, and half of the massifs exceed standards. We believe that these exceedances are due to questionable assumptions concerning the computation of standards. For example, these were devised with GSL, estimated from snow depth maxima and constant snow density set to 150 kg m−3, which underestimate typical GSL values for the snowpack.

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Temporal trends in avalanche activity in the French Alps and subregions: from occurrences and runout altitudes to unsteady return periods

Journal of Glaciology ◽

10.3189/2013jog12j091 ◽

2013 ◽

Vol 59 (213) ◽

pp. 93-114 ◽

Cited By ~ 34

Author(s):

N. Eckert ◽

C. J. Keylock ◽

H. Castebrunet ◽

A. Lavigne ◽

M. Naaim

Keyword(s):

Change Point ◽

Snow Depth ◽

Temporal Trends ◽

Major Change ◽

Strongly Correlated ◽

Low Frequencies ◽

Bayesian Hierarchical ◽

French Alps ◽

The North ◽

Main Change

AbstractWe present an analysis of temporal trends in ∼55 000 avalanches recorded between 1946 and 2010 in the French Alps and two north/south subregions. First, Bayesian hierarchical modelling is used to isolate low-, intermediate- and high-frequency trends in the mean avalanche occurrence and runout altitude per year/winter. Variables are then combined to investigate their correlation and the recent evolution of large avalanches. Comparisons are also made to climatic and flow regime covariates. The results are important for risk assessment, and the development of new high-altitude climate proxies. At the entire French Alps scale, a major change-point exists in ∼1978 at the heart of a 10 year period of high occurrences and low runout altitudes corresponding to colder and snowier winters. The differences between this change-point and the beginning/end of the study period are 0.1 avalanche occurrences per winter and per path and 55 m in runout altitude. Trends before/after are well correlated, leading to enhanced minimal altitudes for large avalanches at this time. A marked upslope retreat (80 m for the 10 year return period runout altitude) accompanied by a 12% decrease in the proportion of powder snow avalanches has occurred since then, interrupted from about 2000. The snow-depth and temperature control on these patterns seems significant (R = 0.4–0.6), but is stronger at high frequencies for occurrences, and at lower frequencies for runout altitudes. Occurrences between the northern and southern French Alps are partially coupled (R∼0.4, higher at low frequencies). In the north, the main change-point was an earlier shift in ∼1977, and winter snow depth seems to be the main control parameter. In the south, the main change-point occurred later, ∼1979–84, was more gradual, and trends are more strongly correlated with winter temperature.

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Extreme Precipitation in the Eastern Mediterranean in ERA5

10.5194/egusphere-egu21-10019 ◽

2021 ◽

Author(s):

Alexander Rischmüller ◽

Alexia Karwat ◽

Richard Blender ◽

Christian Franzke

Keyword(s):

Goodness Of Fit ◽

Scale Parameter ◽

Eastern Mediterranean ◽

Grid Point ◽

Information Criterion ◽

Ratio Test ◽

Changing Scale ◽

The North ◽

Return Levels ◽

The North Atlantic Oscillation

Datasets with precipitation indices from the coastal areas of Syria, Lebanon and Israel are defined from the ERA5-Land database (0.1&#176; resolution). In each coastal area the grid point with the highest hourly precipitation is selected. The declustered datasets are modelled by generalised Pareto distribution. The parameters of the stationary models are estimated using the maximum likelihood (MLE) and Bayesian inference methods. Non-stationary models with several different covariates, i.e., time and teleconnection indices are incorporated into the scale parameter. The parameters of the non-stationary models are estimated using the MLE. The goodness-of-fit of stationary models is assessed by the Anderson-Darling test. QQ-plots subjectively assess the goodness-of-fit for both stationary and non-stationary models. The goodness-of-fit of non-stationary models is assessed in comparison to the stationary models with the likelihood ratio test (LRT) and with the differences in the Akaike information criterion (AIC). The results show clear non-stationarity with the time covariates. Non-stationarity with teleconnection covariates is incoherent, except for the North Atlantic oscillation (NAO) in Syria. Return levels are estimated for stationary and non-stationary models which are obtained from different quantiles of the time-changing scale parameter vector according to -risk scenarios. The results show that return levels are highest in Syria and lowest in Israel.

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Species composition and elevational distribution of bumble bees (Hymenoptera, Apidae, Bombus Latreille) in the East Himalaya, Arunachal Pradesh, India

ZooKeys ◽

10.3897/zookeys.851.32956 ◽

2019 ◽

Vol 851 ◽

pp. 71-89

Author(s):

Martin Streinzer ◽

Jharna Chakravorty ◽

Johann Neumayer ◽

Karsing Megu ◽

Jaya Narah ◽

...

Keyword(s):

High Elevation ◽

Bumble Bees ◽

Mountain Range ◽

Arunachal Pradesh ◽

The North ◽

Unique Character ◽

Future Assessment ◽

Himalayan Mountain ◽

Suitable Habitats ◽

Abundance And Distribution

The East Himalaya is one of the world’s most biodiverse ecosystems. However, very little is known about the abundance and distribution of many plant and animal taxa in this region. Bumble bees are a group of cold-adapted and high elevation insects that fulfil an important ecological and economical function as pollinators of wild and agricultural flowering plants and crops. The Himalayan mountain range provides ample suitable habitats for bumble bees. Systematic study of Himalayan bumble bees began a few decades ago and the main focus has centred on the western region, while the eastern part of the mountain range has received little attention and only a few species have been verified. During a three-year survey, more than 700 bumble bee specimens of 21 species were collected in Arunachal Pradesh, the largest of the north-eastern states of India. The material included a range of species that were previously known from a limited number of collected specimens, which highlights the unique character of the East Himalayan ecosystem. Our results are an important first step towards a future assessment of species distribution, threat, and conservation. Clear elevation patterns of species diversity were observed, which raise important questions about the functional adaptations that allow bumble bees to thrive in this particularly moist region in the East Himalaya.

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Bicycle Speed Modelling Considering Cyclist Characteristics, Vehicle Type and Track Attributes

World Electric Vehicle Journal ◽

10.3390/wevj12010043 ◽

2021 ◽

Vol 12 (1) ◽

pp. 43

Author(s):

Xingchen Yan ◽

Xiaofei Ye ◽

Jun Chen ◽

Tao Wang ◽

Zhen Yang ◽

...

Keyword(s):

Information Criterion ◽

Lateral Position ◽

Extreme Value ◽

Optimal Number ◽

Generalized Extreme Value ◽

Vehicle Type ◽

Lane Width ◽

Bike Sharing ◽

Mode Of Transport ◽

Best Fit

Cycling is an increasingly popular mode of transport as part of the response to air pollution, urban congestion, and public health issues. The emergence of bike sharing programs and electric bicycles have also brought about notable changes in cycling characteristics, especially cycling speed. In order to provide a better basis for bicycle-related traffic simulations and theoretical derivations, the study aimed to seek the best distribution for bicycle riding speed considering cyclist characteristics, vehicle type, and track attributes. K-means clustering was performed on speed subcategories while selecting the optimal number of clustering using L method. Then, 15 common models were fitted to the grouped speed data and Kolmogorov–Smirnov test, Akaike information criterion, and Bayesian information criterion were applied to determine the best-fit distribution. The following results were acquired: (1) bicycle speed sub-clusters generated by the combinations of bicycle type, bicycle lateral position, gender, age, and lane width were grouped into three clusters; (2) Among the common distribution, generalized extreme value, gamma and lognormal were the top three models to fit the three clusters of speed dataset; and (3) integrating stability and overall performance, the generalized extreme value was the best-fit distribution of bicycle speed.

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A multi-proxy reconstruction of climate during the late-Pleistocene to early Holocene transition in the northeastern, USA

Quaternary Research ◽

10.1017/qua.2020.127 ◽

2021 ◽

pp. 1-17

Author(s):

Laurie D. Grigg ◽

Kevin J. Engle ◽

Alison J. Smith ◽

Bryan N. Shuman ◽

Maximilian B. Mandl

Keyword(s):

Late Pleistocene ◽

Climatic Variability ◽

Warming Trend ◽

Early Holocene ◽

Individual Species ◽

Environmental Preferences ◽

The North ◽

Show Evidence ◽

Dry Conditions ◽

Components Analysis

Abstract A multiproxy record from Twin Ponds, VT, is used to reconstruct climatic variability during the late Pleistocene to early Holocene transition. Pollen, ostracodes, δ18O, and lithologic records from 13.5 to 9.0 cal ka BP are presented. Pollen- and ostracode-inferred climatic reconstructions are based on individual species’ environmental preferences and the modern analog technique. Principal components analysis of all proxies highlights the overall warming trend and centennial-scale climatic variability. During the Younger Dryas cooling event (YD), multiple proxies show evidence for cold winter conditions and increasing seasonality after 12.5 cal ka BP. The early Holocene shows an initial phase of rapid warming with a brief cold interval at 11.5 cal ka BP, followed by a more gradual warming; a cool, wet period from 11.2 to 10.8 cal ka BP; and cool, dry conditions from 10.8 to 10.2 cal ka BP. The record ends with steady warming and increasing moisture. Post-YD climatic variability has been observed at other sites in the northeastern United States and points to continued instability in the North Atlantic during the final phases of deglaciation.

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