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

Roux, Erwan Le; Evin, Guillaume; Eckert, Nicolas; Blanchet, Juliette; Morin, Samuel

doi:10.5194/nhess-20-2961-2020

Cited by 23 publications

(16 citation statements)

References 59 publications

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“…Their accuracy on the mesoscale is significantly enhanced thanks to fine spatial sampling, and improved representation of: soil atmosphere interactions, orographic effects, land-use effects, and land-ocean contrasts [23]. Reanalysis of weather data (precipitation, temperature, humidity, radiation, and wind speed) can also be used to run snowpack models and derive snow water equivalent data [47,48].…”

Section: Reanalysis Datasetmentioning

confidence: 99%

Evaluation of Current Trends of Climatic Actions in Europe Based on Observations and Regional Reanalysis

2021

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Since extreme values of climatic actions are commonly derived assuming the climate being stationary over time, engineering structures and infrastructures are designed considering design actions derived under this assumption. Owing to the increased relevance of the expected climate change effects and the correlated variations of climate actions extremes, ad hoc strategies for future adaption of design loads are needed. Moreover, as current European maps for climatic actions are generally based on observations collected more than 20 years ago, they should be updated. By a suitable elaboration of the projections of future climate changes, the evolution over time of climatic actions can be assessed; this basic and crucial information allows us to facilitate future adaptations of climatic load maps, thus improving the climate resilience of structures and infrastructures. In this paper, current trends of climatic actions in Europe, daily maximum and minimum temperatures, daily precipitation, and ground snow loads, are investigated based on available gridded datasets of observations (E-OBS) and regional reanalysis (Uncertainties in Ensembles of Regional Re-Analyses, UERRA), to assess their suitability to be used in the elaboration of maps for climatic actions. The results indicate that the E-OBS gridded datasets reproduce trends in extreme temperatures and precipitation well in the investigated regions, while reanalysis data, which include snow water equivalent, show biases in the assessment of ground snow load modifications over the years in comparison with measurements. As far as climate change effects are concerned, trends of variation of climatic actions are estimated considering subsequent time windows, 40 years in duration, covering the period 1950–2020. Results, in terms of factors of change, are critically discussed, also in comparison with the elaborations of reliable datasets of real observations, considering a case study covering Germany and Switzerland.

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Section: Reanalysis Datasetmentioning

confidence: 99%

Evaluation of Current Trends of Climatic Actions in Europe Based on Observations and Regional Reanalysis

2021

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“…On the other hand, climate projections for the Pyrenees and the Alps under a high greenhouse gas emission scenario (SRES A2 and RCP8.5, respectively) show that the mean seasonal maximum of snowfall is expected to decrease below a transition elevation and increase above it. López-Moreno et al (2011) estimated a transition elevation of around 2000 m for the Pyrenees (comparing 2070-2100to 1960-1990), while Frei et al (2018 estimated a transition of around 3000 m for the Alps (comparing 2070Alps (comparing -2099Alps (comparing to 1981Alps (comparing -2010. In the French Alps, despite the existence of sufficient snowfall records and of previous studies that exploited them in an explicit extreme value framework, temporal trends in extreme snowfall remain poorly described.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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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“…Recent collapses of large-span lightweight roofs [6,7,[16][17][18] confirmed that extreme snow loads can cause significant economic damages and causalities [19]. A discussion about the reliability and failure of roofs subjected to snow loads can be found in [20] where a total of 249 roof collapses during the winter 2005/2006 is investigated identifying main observed causes into human errors and insufficient code provisions.…”

Section: Introductionmentioning

confidence: 99%

Extreme Ground Snow Loads in Europe from 1951 to 2100

Croce

Formichi

Landi

2021

Climate

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Lightweight roofs are extremely sensitive to extreme snow loads, as confirmed by recently occurring failures all over Europe. Obviously, the problem is further emphasized in warmer climatic areas, where low design values are generally foreseen for snow loads. Like other climatic actions, representative values of snow loads provided in structural codes are usually derived by means of suitable elaborations of extreme statistics, assuming climate stationarity over time. As climate change impacts are becoming more and more evident over time, that hypothesis is becoming controversial, so that suitable adaptation strategies aiming to define climate resilient design loads need to be implemented. In the paper, past and future trends of ground snow load in Europe are assessed for the period 1950–2100, starting from high-resolution climate simulations, recently issued by the CORDEX program. Maps of representative values of snow loads adopted for structural design, associated with an annual probability of exceedance p = 2%, are elaborated for Europe. Referring to the historical period, the obtained maps are critically compared with the current European maps based on observations. Factors of change maps, referred to subsequent time windows are presented considering RCP4.5 and RCP8.5 emission trajectories, corresponding to medium and maximum greenhouse gas concentration scenarios. Factors of change are thus evaluated considering suitably selected weather stations in Switzerland and Germany, for which high quality point measurements, sufficiently extended over time are available. Focusing on the investigated weather stations, the study demonstrates that climate models can appropriately reproduce historical trends and that a decrease of characteristic values of the snow loads is expected over time. However, it must be remarked that, if on one hand the mean value of the annual maxima tends to reduce, on the other hand, its standard deviation tends to increase, locally leading to an increase of the extreme values, which should be duly considered in the evaluation of structural reliability over time.

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

Cited by 23 publications

References 59 publications

Evaluation of Current Trends of Climatic Actions in Europe Based on Observations and Regional Reanalysis

Evaluation of Current Trends of Climatic Actions in Europe Based on Observations and Regional Reanalysis

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

Extreme Ground Snow Loads in Europe from 1951 to 2100

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