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

Abstract

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.

Enhancing the Output of Climate Models: A Weather Generator for Climate Change Impact Studies

“…The results confirm that there is a high probability that extreme temperatures significantly rise over time. This tendency accords with the expectations about mean temperatures [67], but it emerges more markedly, confirming the conclusions obtained analyzing actual measurements [29]. For example, considering the time window 2036-2075, the lower and upper limits of the prediction interval of the increase of the characteristic value of the maximum temperature are 1.87 • C and 3.55 • C, respectively, with an average value of 2.75 • C, considering the RCP4.5 scenario, and 2.47 • C and 4.17 • C, respectively, with an average value of 3.37 • C, considering the RCP8.5 scenario.…”

“…11, µ(i) ∈ R and σ(i) > 0, (9) where µ(i) and σ(i) are the parameters of the distribution, depending on the considered time window, i, to be estimated by means of a suitable method, for example, the least square method (LSM). The Gumbel distribution is assumed to be consistent with the prevailing model adopted in Europe for climatic actions in structural design [56,57], but the choice of the most appropriate distribution function is not straightforward and may depend on the investigated climate variable, the location, and the record length [29]. Thus, the characteristic values of the climatic variable, c k (i), in the i-th time window are…”

“…Assuming suitable extreme value distributions, the aforementioned representative values are commonly evaluated under the hypothesis of climate being stationary over time [4,29]. As this assumption is clearly violated when climate change effects occur, relevant assessment of representative values should duly take into account non-stationarity, also in view of the definition of suitable adaptation strategies for the design of resilient buildings and infrastructures [30,31].…”

Panama’s Current Climate Replicability in a Non-Hydrostatic Regional Climate Model Nested in an Atmospheric General Circulation Model

“…For example, the climatological aspect of the diurnal cycle in the tropics is a key phenomenon to be replicated in regional climate models [28]. The replicability of extreme events [5,11,29,33,34] in the current climate is an important feature in climate modeling, along with the replicability of climates. We expect impact assessment researchers and decisionmakers to make use of the NHRCM to analyze the details of projected global warming and related climate changes around Panama.…”

Extreme Ground Snow Loads in Europe from 1951 to 2100

“…Trends of extreme temperature, precipitation and snow loads in Europe based on observations and reanalysis data have been recently discussed by the authors in [13]. In this paper, the study is extended to ground snow loads considering high resolution climate projections.…”