Littérature scientifique sur le sujet « Climate change, Structural Design, Snow Loads, Eurocodes »

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.

Climatic loads on structures are commonly defined under the assumption of stationary climate conditions; but, as confirmed by recent studies, they can significantly vary because of climate change effects, with relevant impacts not only for the design of new structures but also for the assessment of the existing ones. In this paper, a general methodology to evaluate the influence of climate change on climatic actions is presented, based on the analysis of observed data series and climate projections. Illustrative results in terms of changes in characteristic values of temperature, precipitation, snow, and wind loads are discussed for Italy and Germany, with reference to different climate models and radiative forcing scenarios. In this way, guidance for potential amendments in the current definition of climatic actions in structural codes is provided. Finally, the influence of climate change on the long-term structural reliability is estimated for a specific case study, showing the potential of the proposed methodology.

The snowfall series of Turin, northwest Italy, is one of the longest available for Europe, with daily observations starting in 1784 and continuous since 1788. The unpublished 207 years data set was carefully obtained from original manuscripts and filed on magnetic media. Mean yearly snowfall amount is 48.9 cm showing a high interannual variability (variation coefficient 79%), with about seven snow days from October through April; the maximum amount was measured in winter 1784–85 (233 cm), followed by 1808–9 with 163 cm. Maximum daily amount was on 4 December 1844 with 64 cm. During the whole period a negative trend is exhibited, increasing in the years following 1890. This pattern is confirmed by the Mann-Kendall test. The change derives from regional climate rather than expansion of the urban area. Return periods of yearly maximum snow loads are calculated in order to contribute to the definition of new values for structural design. A case study of heavy snowfall in January 1987 is examined.

The snowfall series of Turin, northwest Italy, is one of the longest available for Europe, with daily observations starting in 1784 and continuous since 1788. The unpublished 207 years data set was carefully obtained from original manuscripts and filed on magnetic media. Mean yearly snowfall amount is 48.9 cm showing a high interannual variability (variation coefficient 79%), with about seven snow days from October through April; the maximum amount was measured in winter 1784–85 (233 cm), followed by 1808–9 with 163 cm. Maximum daily amount was on 4 December 1844 with 64 cm. During the whole period a negative trend is exhibited, increasing in the years following 1890. This pattern is confirmed by the Mann-Kendall test. The change derives from regional climate rather than expansion of the urban area. Return periods of yearly maximum snow loads are calculated in order to contribute to the definition of new values for structural design. A case study of heavy snowfall in January 1987 is examined.

Structural design of buildings and infrastructures is significantly influenced by the definition of climatic actions (snow, wind and thermal loads) that the structure shall withstand during its life, which could be significantly greater than the design service life. Therefore, the impact of climate change on climatic actions could significantly affect, in the mid-term future, the design of new structures as well as the reliability of existing ones designed in accordance to the provisions of present and past codes, which are based on the assumption of stationary climate conditions. In this work, a general methodology to derive future trends of snow load on structures is presented aiming to study the influence of climate change at European scale in view of the definition of updated snow maps for the new generation of structural Eurocodes. First, a general algorithm based, on Monte Carlo simulations, is defined to estimate ground snow loads maxima considering daily outputs of the climate models, in terms of maximum and minimum air temperatures and precipitation, supplemented by local information of snowfall and snow melting conditions derived from the elaboration of real measurements of actual meteorological events. Once validated the procedure, reproducing observed data series of yearly maximum ground snow loads, future trends in characteristic values of the load are investigated. Analysing different climate models and scenarios, the relevant issue of uncertainty assessment of climate projections is deeply investigated. In particular, the three main sources of uncertainty affecting climate projections: model uncertainty, scenarios uncertainty and internal variability, are assessed also implementing an innovative ad hoc developed weather generator, able to generate future weather series directly from climate model outputs. Factor of change confidence maps are finally derived combining all the presented results and providing guidance for potential amendments of the current version of snow load maps given in structural Codes.

<p>The impact of climate change on climatic actions could significantly affect, in the mid-term future, the design of new structures as well as the reliability of existing ones designed in accordance to the provisions of present and past codes. Indeed, current climatic loads are defined under the assumption of stationary climate conditions but climate is not stationary and the current accelerated rate of changes imposes to consider its effects.</p><p>Increase of greenhouse gas emissions generally induces a global increase of the average temperature, but at local scale, the consequences of this phenomenon could be much more complex and even apparently not coherent with the global trend of main climatic parameters, like for example, temperature, rainfalls, snowfalls and wind velocity.</p><p>In the paper, a general methodology is presented, aiming to evaluate the impact of climate change on structural design, as the result of variations of characteristic values of the most relevant climatic actions over time. The proposed procedure is based on the analysis of an ensemble of climate projections provided according a medium and a high greenhouse gas emission scenario. Factor of change for extreme value distribution’s parameters and return values are thus estimated in subsequent time windows providing guidance for adaptation of the current definition of structural loads.</p><p>The methodology is illustrated together with the outcomes obtained for snow, wind and thermal actions in Italy. Finally, starting from the estimated changes in extreme value parameters, the influence on the long-term structural reliability can be investigated comparing the resulting time dependent reliability with the reference reliability levels adopted in modern Structural codes.</p>

<p>Climate change could heavily affect climatic actions on structures. Indeed, the current definition of climatic actions in structural codes, snow wind thermal and icing loads, is based on the assumption of stationary climate conditions but climate is not stationary and the observed accelerated rate of changes must be considered. A proper evaluation of the consequences of climate change requires the set-up of procedures able to deal with the analysis of climate projections and their intrinsic uncertainties.In the paper, a general methodology is illustrated, aiming to evaluate the impact of climate change on structural design. The proposed procedure is based on the definition of factors of change for climate extremes in moving time windows derived from the analysis of an ensemble of climate projections according different greenhouse gas emission scenarios, combined with an innovative weather generator to obtain a probabilistic description of future changes.The definition of a suitable envelope of characteristic values, provide guidance for a better estimation of climatic action in structural codes taking into account their evolution with time.</p>