scholarly journals Extreme Ground Snow Loads in Europe from 1951 to 2100

Climate ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 133
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Structural Reliability ◽  
Climate Models ◽  
Extreme Values ◽  
Time Windows ◽  
Climate Change Impacts ◽  
Historical Period ◽  
Extreme Statistics ◽  
Weather Stations ◽  
Snow Loads ◽  
Over Time

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.

Some Pitfalls in Statistical Downscaling of Future Climate

2018 ◽  
Vol 99 (4) ◽  
pp. 791-803 ◽  
Author(s):  
John R. Lanzante ◽  
Keith W. Dixon ◽  
Mary Jo Nath ◽  
Carolyn E. Whitlock ◽  
Dennis Adams-Smith
Keyword(s):  
Climate Change ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Climate Change Impacts ◽  
Future Climate ◽  
Added Value ◽  
Historical Period ◽  
Perfect Model

AbstractStatistical downscaling (SD) is commonly used to provide information for the assessment of climate change impacts. Using as input the output from large-scale dynamical climate models and observation-based data products, SD aims to provide a finer grain of detail and to mitigate systematic biases. It is generally recognized as providing added value. However, one of the key assumptions of SD is that the relationships used to train the method during a historical period are unchanged in the future, in the face of climate change. The validity of this assumption is typically quite difficult to assess in the normal course of analysis, as observations of future climate are lacking. We approach this problem using a “perfect model” experimental design in which high-resolution dynamical climate model output is used as a surrogate for both past and future observations.We find that while SD in general adds considerable value, in certain well-defined circumstances it can produce highly erroneous results. Furthermore, the breakdown of SD in these contexts could not be foreshadowed during the typical course of evaluation based on only available historical data. We diagnose and explain the reasons for these failures in terms of physical, statistical, and methodological causes. These findings highlight the need for caution in the use of statistically downscaled products and the need for further research to consider other hitherto unknown pitfalls, perhaps utilizing more advanced perfect model designs than the one we have employed.

scholarly journals Assessing urban climate model results with crowd-sourced data

2021 ◽  
Author(s):  
Claudia Hahn ◽  
Sandro Oswald ◽  
Brigitta Hollosi ◽  
Robert Goler ◽  
Astrid Kainz ◽  
...  
Keyword(s):  
City Planning ◽  
Climate Models ◽  
Climate Model ◽  
Scale Effects ◽  
Urban Climate ◽  
Monitoring Network ◽  
Climate Change Impacts ◽  
Weather Station ◽  
Weather Stations ◽  
Good Agreement

<p>Climate change impacts are amplified in cities due to the urban heat island effect and the high population density. Information about the intra-urban temperature patterns is therefore crucial to support resilient city planning. Within the ACRP funded project LUCRETIA, the intra-urban temperature patterns in Vienna, Austria, are investigated using urban climate models (MUKLIMO_3, PALM-4U) and data from citizen weather stations.</p><p>While the density of conventional weather station networks is usually too low to capture the temperature patterns in cities and to assess urban climate model results, citizen weather stations provide a dense monitoring network, especially in cities. In Vienna, more than 1000 citizen weather stations from the company Netatmo are available for our study period in August 2018, after the quality control. First investigations showed, that air temperature measurements from citizen weather stations are in good agreement with measurements from conventional stations. The observed differences are attributed to the different locations of the stations and micro-scale effects. A preliminary comparison of citizen weather station data with urban climate model results from MUKLIMO_3 for Vienna revealed for some of the stations similar patterns as the comparison between conventional stations and model results: a reasonably good agreement during the day, after model initialization, and a temperature overestimation at night. Within LUCRETIA we are assessing in more detail the model results (MUKLIMO_3, PALM-4U) for a three day period in August 2018, thereby looking at the effect of the different land-use classes within the city. In addition, we will investigate whether similar spatial temperature patterns are identified when using urban climate models and data from citizen weather stations.</p>

scholarly journals Climate Change: Impacts on Climatic Actions and Structural Reliability

2019 ◽  
Vol 9 (24) ◽  
pp. 5416 ◽  
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Structural Reliability ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Data Series ◽  
Climate Projections ◽  
Climate Conditions ◽  
Climate Change Effects ◽  
Definition Of

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.

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

2021 ◽  
Vol 13 (11) ◽  
pp. 2025
Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi
Keyword(s):  
Climate Change ◽  
Snow Water Equivalent ◽  
Extreme Values ◽  
Time Windows ◽  
Daily Maximum ◽  
Engineering Structures ◽  
Climate Change Effects ◽  
Current Trends ◽  
Regional Reanalysis ◽  
Over Time

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.

scholarly journals Flooding Conditions at Aveiro Port (Portugal) within the Framework of Projected Climate Change

2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Américo Soares Ribeiro ◽  
Carina Lurdes Lopes ◽  
Magda Catarina Sousa ◽  
Moncho Gomez-Gesteira ◽  
João Miguel Dias
Keyword(s):  
Climate Change ◽  
Sea Level ◽  
Climate Change Impacts ◽  
Storm Surges ◽  
Historical Period ◽  
Return Periods ◽  
Wave Regime ◽  
Mean Sea Level ◽  
Sea Levels ◽  
Far Future

Ports constitute a significant influence in the economic activity in coastal areas through operations and infrastructures to facilitate land and maritime transport of cargo. Ports are located in a multi-dimensional environment facing ocean and river hazards. Higher warming scenarios indicate Europe’s ports will be exposed to higher risk due to the increase in extreme sea levels (ESL), a combination of the mean sea level, tide, and storm surge. Located on the west Iberia Peninsula, the Aveiro Port is located in a coastal lagoon exposed to ocean and river flows, contributing to higher flood risk. This study aims to assess the flood extent for Aveiro Port for historical (1979–2005), near future (2026–2045), and far future (2081–2099) periods scenarios considering different return periods (10, 25, and 100-year) for the flood drivers, through numerical simulations of the ESL, wave regime, and riverine flows simultaneously. Spatial maps considering the flood extent and calculated area show that most of the port infrastructures' resilience to flooding is found under the historical period, with some marginal floods. Under climate change impacts, the port flood extent gradually increases for higher return periods, where most of the terminals are at high risk of being flooded for the far-future period, whose contribution is primarily due to mean sea-level rise and storm surges.

scholarly journals Global warming and temperature-mediated increases in cercarial emergence in trematode parasites

Parasitology ◽  
2005 ◽  
Vol 132 (1) ◽  
pp. 143-151 ◽  
Author(s):  
R. POULIN
Keyword(s):  
Global Warming ◽  
Geographical Distribution ◽  
Climate Models ◽  
Extreme Values ◽  
Geometric Mean ◽  
Effect Of Temperature ◽  
Trematode Species ◽  
Intermediate Hosts ◽  
Cercarial Production ◽  
Trematode Parasites

Global warming can affect the world's biota and the functioning of ecosystems in many indirect ways. Recent evidence indicates that climate change can alter the geographical distribution of parasitic diseases, with potentially drastic consequences for their hosts. It is also possible that warmer conditions could promote the transmission of parasites and raise their local abundance. Here I have compiled experimental data on the effect of temperature on the emergence of infective stages (cercariae) of trematode parasites from their snail intermediate hosts. Temperature-mediated changes in cercarial output varied widely among trematode species, from small reductions to 200-fold increases in response to a 10 °C rise in temperature, with a geometric mean suggesting an almost 8-fold increase. Overall, the observed temperature-mediated increases in cercarial output are much more substantial than those expected from basic physiological processes, for which 2- to 3-fold increases are normally seen. Some of the most extreme increases in cercarial output may be artefacts of the methods used in the original studies; however, exclusion of these extreme values has little impact on the preceding conclusion. Across both species values and phylogenetically independent contrasts, neither the magnitude of the initial cercarial output nor the shell size of the snail host correlated with the relative increase in cercarial production mediated by rising temperature. In contrast, the latitude from which the snail-trematode association originated correlated negatively with temperature-mediated increases in cercarial production: within the 20 ° to 55 ° latitude range, trematodes from lower latitudes showed more pronounced temperature-driven increases in cercarial output than those from higher latitudes. These results suggest that the small increases in air and water temperature forecast by many climate models will not only influence the geographical distribution of some diseases, but may also promote the proliferation of their infective stages in many ecosystems.

scholarly journals Future Australian Severe Thunderstorm Environments. Part II: The Influence of a Strongly Warming Climate on Convective Environments

2014 ◽  
Vol 27 (10) ◽  
pp. 3848-3868 ◽  
Author(s):  
John T. Allen ◽  
David J. Karoly ◽  
Kevin J. Walsh
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Vertical Wind Shear ◽  
Atmospheric Model ◽  
Global Climate Models ◽  
Historical Period ◽  
Severe Thunderstorm ◽  
Warming Climate ◽  
Eastern Australia

Abstract The influence of a warming climate on the occurrence of severe thunderstorm environments in Australia was explored using two global climate models: Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6), and the Cubic-Conformal Atmospheric Model (CCAM). These models have previously been evaluated and found to be capable of reproducing a useful climatology for the twentieth-century period (1980–2000). Analyzing the changes between the historical period and high warming climate scenarios for the period 2079–99 has allowed estimation of the potential convective future for the continent. Based on these simulations, significant increases to the frequency of severe thunderstorm environments will likely occur for northern and eastern Australia in a warmed climate. This change is a response to increasing convective available potential energy from higher continental moisture, particularly in proximity to warm sea surface temperatures. Despite decreases to the frequency of environments with high vertical wind shear, it appears unlikely that this will offset increases to thermodynamic energy. The change is most pronounced during the peak of the convective season, increasing its length and the frequency of severe thunderstorm environments therein, particularly over the eastern parts of the continent. The implications of this potential increase are significant, with the overall frequency of potential severe thunderstorm days per year likely to rise over the major population centers of the east coast by 14% for Brisbane, 22% for Melbourne, and 30% for Sydney. The limitations of this approach are then discussed in the context of ways to increase the confidence of predictions of future severe convection.

scholarly journals Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Historical Period ◽  
Mountainous Regions ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

scholarly journals Errors in climate model daily precipitation and temperature output: time invariance and implications for bias correction

2013 ◽  
Vol 17 (6) ◽  
pp. 2147-2159 ◽  
Author(s):  
E. P. Maurer ◽  
T. Das ◽  
D. R. Cayan
Keyword(s):  
Bias Correction ◽  
General Circulation ◽  
Daily Precipitation ◽  
Extreme Values ◽  
Circulation Model ◽  
The United States ◽  
Historical Period ◽  
Late 20Th Century ◽  
Precipitation And Temperature ◽  
Gcm Biases

Abstract. When correcting for biases in general circulation model (GCM) output, for example when statistically downscaling for regional and local impacts studies, a common assumption is that the GCM biases can be characterized by comparing model simulations and observations for a historical period. We demonstrate some complications in this assumption, with GCM biases varying between mean and extreme values and for different sets of historical years. Daily precipitation and maximum and minimum temperature from late 20th century simulations by four GCMs over the United States were compared to gridded observations. Using random years from the historical record we select a "base" set and a 10 yr independent "projected" set. We compare differences in biases between these sets at median and extreme percentiles. On average a base set with as few as 4 randomly-selected years is often adequate to characterize the biases in daily GCM precipitation and temperature, at both median and extreme values; 12 yr provided higher confidence that bias correction would be successful. This suggests that some of the GCM bias is time invariant. When characterizing bias with a set of consecutive years, the set must be long enough to accommodate regional low frequency variability, since the bias also exhibits this variability. Newer climate models included in the Intergovernmental Panel on Climate Change fifth assessment will allow extending this study for a longer observational period and to finer scales.

Sign in / Sign up

Export Citation Format

Share Document