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4 results on '"French Ministry of the Environment, Risk Division (DGPR)"'

1. Extreme avalanche cycles: Return levels and probability distributions depending on snow and meteorological conditions

Author

Guillaume Evin, Pascal Dkengne Sielenou, Nicolas Eckert, Philippe Naveau, Pascal Hagenmuller, Samuel Morin, Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Université Grenoble Alpes (UGA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), This study was supported by the French Ministry of the Environment, Risk Division (DGPR) through the ECANA project and the 'wet snow avalanche' action. INRAE and CNRM/CEN are members of LabEx OSUG., This study was supported by the French Ministry of the Environment, Risk Division (DGPR) through the ECANA project and the ?wet snow avalanche? action. INRAE and CNRM/CEN are members of LabEx OSUG., Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)

Subjects
Avalanche cycles, [SDU]Sciences of the Universe [physics], Meteorology. Climatology, Extreme value theory, QC851-999, French alps, Physics::Geophysics, Discrete distributions
Abstract

International audience; Remarkable episodes of avalanche events, so-called snow avalanche cycles, are recurring threats to people and infrastructures in mountainous areas. This study focuses on the hazard assessment of snow avalanche cycles defined by daily occurrence numbers exceeding the 2-year return level. To this aim, extreme value distributions are tailored to account for discrete observations and potential covariates. A comprehensive statistical framework is provided including model fitting, model selection and evaluation, and derivation of quantities of interest such as return levels. In each of the 23 massifs of the French Alps, two discrete generalized Pareto (dGP) models are applied to extreme avalanche cycles extracted from 60 years of daily avalanche activity observations from 1958 to 2018, an unconditional version and a conditional version incorporating snow and meteorological covariates. In the conditional dGP model, the scale parameter is allowed to depend on snow and meteorological conditions from a local reanalysis, leading the corresponding distributions to outperform their unconditional counterparts in about half of the French Alps massifs. Unconditional dGP models provide valuable estimates of high return levels of avalanche numbers. In particular, it is shown that the number of avalanches per path which can be expected on average every 100 and 300 years for the French Alps is approximately equal to 0.25 (roughly one avalanche for four paths) and 0.32 (one avalanche for three paths). As exemplified with the January 2018 Eleanor winter storm, conditional dGP models refine the statistical description of the largest avalanche cycles by providing the information conditional to specific meteorological and snow conditions, with potential applications to avalanche forecasting and climate change impact studies. The same framework could be put to work in other mountain areas and for analyzing extreme counts of various other damaging phenomena.

Published
2021
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2. Combining random forests and class-balancing to discriminate between three classes of avalanche activity in the French Alps

Author

Pascal Dkengne Sielenou, Marie Dumont, Philippe Naveau, Léo Viallon-Galinier, Pascal Hagenmuller, Deborah Verfaillie, Samuel Morin, Nicolas Eckert, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Extrèmes : Statistiques, Impacts et Régionalisation (ESTIMR), Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Centre d'Etudes de la Neige (CEN), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA), Université Catholique de Louvain = Catholic University of Louvain (UCL), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), French Ministry of the Environment, Risk Division (DGPR), French Gestion des Impacts du Changement ClimatiqueGICC and Obervatoire National du Changement climatiqueONERC programs (ADAMONT grant), and ANR-16-CE01-0006,EBONI,Dépot, devenir et impact des impuretés absorbantes dans le manteau neigeux(2016)

Subjects
business.industry, Computer science, Physics::Instrumentation and Detectors, Forest decision trees, Moderate activity, Geotechnical Engineering and Engineering Geology, Machine learning, computer.software_genre, Snow, Class (biology), Random forest, Physics::Geophysics, Avalanche forecasting, Variable (computer science), [SPI]Engineering Sciences [physics], Avalanche statistical forecasting, Snow and meteorological conditions and reanalyses, [SDE]Environmental Sciences, General Earth and Planetary Sciences, High activity, Artificial intelligence, business, Cluster analysis, French Alps, computer
Abstract

International audience; Determining avalanche activity corresponding to given snow and meteorological conditions is an old problem of high practical relevance. To address it, numerous statistical forecasting models have been developed, but intercomparisons of their efficiency on very large datasets are seldom. In this work, an approach combining random forests with class-balancing is presented and systematically compared with competing methods currently described in the avalanche literature. On more than 50 years of daily avalanche observations, in the 23 massifs of the French Alps, the competing classifiers are evaluated on their ability to distinguish three classes of avalanche activity: non-avalanche days, days with moderate activity, and days with high activity. Moreover, the variables of higher importance in the random forest classifiers are shown to be coherent with current avalanche literature and a clustering based on these variable importance separates massifs which are known to have different avalanche activities. Our approach opens perspectives to support operational avalanche forecasting.

Published
2021
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3. Temporal trends in avalanche activity in the French Alps and subregions: from occurrences and runout altitudes to unsteady return periods

Author

Hélène Castebrunet, Mohamed Naaim, Nicolas Eckert, Christopher J. Keylock, Aurore Lavigne, Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Mathématiques et Informatique Appliquées (MIA-Paris), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Eros Torrentielle Neige & Avalanches, Department of Civil and Structural Engineering [Sheffield], University of Sheffield [Sheffield], French National Research Agency [ANR-09-RISK-007-01], French Ministry of the Environment (Risk Division (DGPR), British Council, French Ministere des Affaires Etrangeres et Europeennes, The British Council in India, ANR-09-RISK-0007,MOPERA,MOdélisation Probabiliste pour l'Evaluation du Risque Avalanche(2009), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), and Institut National de la Recherche Agronomique (INRA)-AgroParisTech

Subjects
Return period, [SDV.SA]Life Sciences [q-bio]/Agricultural sciences, 010506 paleontology, 010504 meteorology & atmospheric sciences, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, 01 natural sciences, Altitude, CHANGE-POINT ANALYSIS, SWISS ALPS, [SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Earth-Surface Processes, CLIMATE-CHANGE, LAST 50 YEARS, SNOW-COVER, FLUCTUATIONS, Snow, MODEL, VARIABILITY, 13. Climate action, HYDROMETEOROLOGICAL TIME-SERIES, Climatology, DEPTH, Period (geology), [STAT.ME]Statistics [stat]/Methodology [stat.ME], Geology
Abstract

We 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.

Published
2013
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4. Snow and weather climatic control on snow avalanche occurrence fluctuations over 50 yr in the French Alps

Author

Hélène Castebrunet, Nicolas Eckert, Gérald Giraud, Groupe d'étude de l'atmosphère météorologique (CNRM-GAME), Institut national des sciences de l'Univers (INSU - CNRS)-Météo France-Centre National de la Recherche Scientifique (CNRS), Erosion torrentielle neige et avalanches (UR ETGR (ETNA)), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Ecosystèmes méditerranéens et risques (UR EMAX), Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Centre national de recherches météorologiques (CNRM), Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), French Ministry of the Environment, Risk Division (DGPR), French National Research Agency (ANR), and Centre National de la Recherche Scientifique (CNRS)

Subjects
010504 meteorology & atmospheric sciences, Stratigraphy, lcsh:Environmental protection, 0207 environmental engineering, 02 engineering and technology, [SDU.STU.ME]Sciences of the Universe [physics]/Earth Sciences/Meteorology, 01 natural sciences, lcsh:Environmental pollution, lcsh:TD169-171.8, 020701 environmental engineering, ComputingMilieux_MISCELLANEOUS, lcsh:Environmental sciences, 0105 earth and related environmental sciences, lcsh:GE1-350, FREQUENCE, Global and Planetary Change, [SHS.STAT]Humanities and Social Sciences/Methods and statistics, Paleontology, Regression analysis, ALPES FRANCAISES, Snowpack, Snow, HISTORIQUE, [SDU]Sciences of the Universe [physics], 13. Climate action, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, Climatology, Weather data, lcsh:TD172-193.5, [SDE]Environmental Sciences, Period (geology), Environmental science, VARIABILITE CLIMATIQUE, Weather patterns, AVALANCHE, Regional differences
Abstract

[Departement_IRSTEA]Eaux [TR1_IRSTEA]RIVAGE [Departement_IRSTEA]Eaux [TR1_IRSTEA]RIVAGE; International audience; Snow avalanche activity is controlled to a large extent by snow and weather patterns. However, its response to climate fluctuations remains poorly documented. Previous studies have focused on direct extraction of trends in avalanche and winter climate data, and this study employs a time-implicit method to model annual avalanche activity in the French Alps during the 1958–2009 period from its most representative climatic drivers. Modelled snow and weather data for different elevations and aspects are considered as covariates that explain actual observed avalanche counts, modelled instability indexes, and a combination of both avalanche activity indicators. These three series present relatively similar fluctuations over the period and good consistency with historically harsh winters. A stepwise procedure is used to obtain regression models that accurately represent trends as well as high and low peaks with a small number of physically meaningful covariates, showing their climatic relevance. The activity indicators and their regression models seen as time series show, within a high interannual variability, a predominant bell-shaped pattern presumably related to a short period of colder and snowier winters around 1980, as well as a very slight but continuous increase between 1975 and 2000 concomitant with warming. Furthermore, the regression models quantify the respective weight of the different covariates, mostly temperature anomalies and south-facing snowpack characteristics to explain the trends and most of the exceptional winters. Regional differences are discussed as well as seasonal variations between winter and spring activity and confirm rather different snow and weather regimes influencing avalanche activity over the Northern and Southern Alps, depending on the season.

Published
2012
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