Future changes in European windstorm severities and impacts 

2021 ◽  
Author(s):  
Jennifer Catto ◽  
Alex Little ◽  
Matthew Priestley
Keyword(s):  
Severity Index ◽  
Reanalysis Data ◽  
Economic Losses ◽  
Change Scenario ◽  
Climate Projections ◽  
European Continent ◽  
Wind Speeds ◽  
Extreme Wind Speed ◽  
Lagrangian Tracking ◽  
Extreme Winds

<p>Extratropical cyclones that impact Europe are significant natural hazards that can cause severe damages and lead to large socio-economic losses. There are large uncertainties associated with changes in storm number, and storm intensity, in future climate projections. Here we use a Lagrangian tracking algorithm applied to reanalysis data and to historical and two future scenario simulations of a number of CMIP6 models to investigate future changes in characteristics of windstorms over Europe. As well as storm frequencies and peak wind speeds, we also quantify changes in two versions of a storm severity index (SSI), one of which is population weighted. These metrics are calculated using the footprints of cyclones as they pass over the European continent.</p><p>The models show differing abilities to represent the historical SSI compared to ERA5. Future changes in SSI are somewhat uncertain, but tend to show an increase in severities over central and northwest Europe, and a decrease over lower latitudes and the Mediterranean, with responses tending to be larger for the more extreme climate change scenario. These changes are associated with the changes in the extreme winds over land.</p><p>By considering the parameters of population density and wind intensity threshold we could explore the relevance of future socio-economic and adaptive changes on the windstorm impacts. For the population-weighted SSI, smaller increases are found in the future cases where population densities do not change and/or adaptation to increases in extreme wind speed climatologies occur.</p>

Extreme winds in a WRF downscaling for the SAM-22 CORDEX domain for the 1979-2018 Historical Period

2021 ◽  
Author(s):  
Natalia Pillar da Silva ◽  
Rosmeri Porfírio da Rocha ◽  
Natália Machado Crespo ◽  
Ricardo de Camargo ◽  
Jose Antonio Moreira Lima ◽  
...  
Keyword(s):  
Wind Speed ◽  
Oil And Gas ◽  
Offshore Structures ◽  
Horizontal Resolution ◽  
Historical Period ◽  
Climate Projections ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Wind Events ◽  
Extreme Winds

<p>This study aims to evaluate how extreme winds (above the 95th percentile) are represented in a downscaling using the regional model WRF over the CORDEX South American domain in an approximate 25 km (0.22 degrees) horizontal resolution, along with CFSR as input. The main focus of the analysis resides over the coastal Brazilian region, given a large number of offshore structures from oil and gas industries subject to impact by severe events. Model results are compared with a reanalysis product (ERA5),  estimates from satellites product (Cross-Calibrated Multi-Platform Wind Speed), and available buoy data (Brazilian National Buoy Project). Downscaling results from WRF show an underestimation of maximum and extreme wind speeds over the region when compared to all references, along with overestimation in the continental areas. This directly impacts results for extreme value estimation for a larger return period and severity evaluation of extreme wind events in future climate projections. To address this, a correction procedure based on the linear relationship between severe wind from satellite and model results is applied. After linearly corrected, the extreme and maximum wind speed values increase and errors in the representation of severe events are reduced in the downscaling results.</p>

Extreme wind speed climatology over Greece

2021 ◽  
Author(s):  
Georgios Blougouras ◽  
Chris G. Tzanis ◽  
Kostas Philippopoulos
Keyword(s):  
Wind Speed ◽  
Confidence Intervals ◽  
Wind Turbines ◽  
Economic Losses ◽  
Return Periods ◽  
Wind Speeds ◽  
Return Levels ◽  
Extreme Wind ◽  
Extreme Wind Speed ◽  
Extreme Wind Speeds

<p>Extreme wind speeds are a multifaceted environmental risk. They may cause considerable damage to infrastructure (e.g., bridges, private property), they can jeopardize maritime and aviation activities, and sometimes even human safety. Furthermore, the design of wind turbines for on and off-shore wind farms requires a study of the return periods of extreme wind speeds in combination with the lifespan of the wind turbines. Windstorms also result in major economic losses and cause up to 80 % of the natural hazards' long term insurance loss in Europe. The scope of this work is to identify location-specific extreme wind speed thresholds and obtain accurate estimates of exceedances for multiple future horizons. In this context, the Extreme Value Analysis framework is used for providing the return periods and the respective return levels of extreme wind speeds. The Peaks Over Threshold method is utilized for the 10 m wind speed for a domain centered over Greece, in Southeastern Mediterranean. Wind speed data at 10 m are extracted from the ERA5 reanalysis dataset that provides hourly estimates of surface wind speed with a horizontal resolution of 0.25°x0.25°, from 1979/01/01 up to 2019/12/31 (i.e., 41 years). The thresholds are selected using the Mean Residual Life plots, which is the most reliable method for identifying accurate threshold values. The seasonal analysis of the exceedances is discussed in terms of the physical mechanisms in the region. The exceedances are modelled using the Generalized Pareto Distribution, whose shape and scale parameters (<em>ξ</em> and <em>σ</em>, respectively) are estimated using the Maximum Likelihood Estimation method. The return levels and their confidence intervals are estimated for return periods up to 100 years. Geographic Information Systems are used for mapping future projections of extreme wind speeds and the corresponding confidence intervals. The results are discussed in terms of identifying high-risk areas and the findings could assist in informed decision-making in the wind energy industry. The proposed methodological framework could be extended to other areas characterized by particularly high wind speeds and the results can contribute towards sustainable investments and support adaptation mechanisms.</p>

scholarly journals Wind storm loss estimations in the Canton of Vaud (Western Switzerland)

2012 ◽  
Vol 12 (12) ◽  
pp. 3789-3798 ◽  
Author(s):  
C. Etienne ◽  
M. Beniston
Keyword(s):  
Population Data ◽  
Geographic Area ◽  
Economic Losses ◽  
Daily Maximum ◽  
Insurance Company ◽  
Wind Speeds ◽  
Extreme Wind ◽  
Storm Duration ◽  
Extreme Wind Speed ◽  
Weather Stations

Abstract. A storm loss model that was first developed for Germany is applied to the much smaller geographic area of the canton of Vaud, in Western Switzerland. 24 major wind storms that struck the region during the period 1990–2010 are analysed, and outputs are compared to loss observations provided by an insurance company. Model inputs include population data and daily maximum wind speeds from weather stations. These measured wind speeds are regionalised in the canton of Vaud following different methods, using either basic interpolation techniques from Geographic Information Systems (GIS), or by using an existing extreme wind speed map of Switzerland whose values are used as thresholds. A third method considers the wind power, integrating wind speeds temporally over storm duration to calculate losses. Outputs show that the model leads to similar results for all methods, with Pearson's correlation and Spearman's rank coefficients of roughly 0.7. Bootstrap techniques are applied to test the model's robustness. Impacts of population growth and possible changes in storminess under conditions of climate change shifts are also examined for this region, emphasizing high shifts in economic losses related to small increases of input wind speeds.

scholarly journals Modelling of the Discharge Response to Climate Change under RCP8.5 Scenario in the Alata River Basin (Mersin, SE Turkey)

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 483
Author(s):  
Ümit Yıldırım ◽  
Cüneyt Güler ◽  
Barış Önol ◽  
Michael Rode ◽  
Seifeddine Jomaa
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Hydrological Model ◽  
Baseline Period ◽  
Change Scenario ◽  
Climate Projections ◽  
Worst Case ◽  
Distributed Process ◽  
In The Beginning ◽  
Se Turkey

This study investigates the impacts of climate change on the hydrological response of a Mediterranean mesoscale catchment using a hydrological model. The effect of climate change on the discharge of the Alata River Basin in Mersin province (Turkey) was assessed under the worst-case climate change scenario (i.e., RCP8.5), using the semi-distributed, process-based hydrological model Hydrological Predictions for the Environment (HYPE). First, the model was evaluated temporally and spatially and has been shown to reproduce the measured discharge consistently. Second, the discharge was predicted under climate projections in three distinct future periods (i.e., 2021–2040, 2046–2065 and 2081–2100, reflecting the beginning, middle and end of the century, respectively). Climate change projections showed that the annual mean temperature in the Alata River Basin rises for the beginning, middle and end of the century, with about 1.35, 2.13 and 4.11 °C, respectively. Besides, the highest discharge timing seems to occur one month earlier (February instead of March) compared to the baseline period (2000–2011) in the beginning and middle of the century. The results show a decrease in precipitation and an increase in temperature in all future projections, resulting in more snowmelt and higher discharge generation in the beginning and middle of the century scenarios. However, at the end of the century, the discharge significantly decreased due to increased evapotranspiration and reduced snow depth in the upstream area. The findings of this study can help develop efficient climate change adaptation options in the Levant’s coastal areas.

Forecast skill of autumn snow for European winter climate during the 20th century: A multi member seasonal prediction experiment

2021 ◽  
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann
Keyword(s):  
Snow Cover ◽  
General Circulation ◽  
Initial Conditions ◽  
Internal Variability ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Winter Climate ◽  
European Continent ◽  
Near Surface

<p>As the leading climate mode to explain wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Northern Hemispheric cryosphere as possible predictor for the wintertime NAO (Cohen et al. 2014). Although several studies could find seasonal prediction skill in reanalysis data (Orsolini et al. 2016, Duville et al. 2017,Han & Sun 2018), experiments with ocean-atmosphere general circulation models (AOGCMs) still show conflicting results (Furtado et al. 2015, Handorf et al. 2015, Francis 2017, Gastineau et al. 2017). </p><p>Here we use two kinds ECMWF seasonal prediction ensembles starting with November initial conditions taken from the long-term reanalysis ERA-20C and forecasting the following three winter months. Besides the 110-year ensemble of 50 members representing internal variability of the atmosphere, we investigate a second ensemble of 20 members where initial conditions are split between low and high snow cover years for the Northern Hemisphere. We compare two recently used Eurasian snow cover indices for their skill in predicting winter climate for the European continent. Analyzing the two forecast experiments, we found that prediction runs starting with high snow index values in November result in significantly more negative NAO states in the following winter (DJF), which in turn modulates near surface temperatures. We track the atmospheric anomalies triggered by the high snow index through the tropo- and stratosphere as well as for the individual winter months to provide a physical explanation for the formation of this particular climate state.</p><p> </p>

Intrauterine Infections (Ciba Foundation Symposium 10, new series). Amsterdam/London/New York: Associated Scientific Publishers, 1973, 219 pp., $10.50

PEDIATRICS ◽  
1974 ◽  
Vol 53 (1) ◽  
pp. 132-134
Author(s):  
Alex J. Steigman
Keyword(s):  
United States ◽  
New York ◽  
Great Britain ◽  
The United States ◽  
Lessons Learned ◽  
Economic Losses ◽  
Ciba Foundation Symposium ◽  
European Continent ◽  
Intrauterine Infections ◽  
Scientific Publishers

This interesting volume is the result of a proper symposium rather than a collection of submitted reports. The authoritative findings are sprinkled generously with a free flowing discussion which brings sharply into focus what remains to be learned and how to go about it. The 22 well-qualified participants include 17 from Great Britain, 4 from the European continent, and 1 from the United States. Wisely included are the observations of a veterinarian-scientist; lessons learned from studies made primarily to prevent economic losses in animals may become useful to clinicians.

scholarly journals Mitigation of CO2 and N2O Emission from Cabbage Fields in Korea by Optimizing Tillage Depth and N-Fertilizer Level: DNDC Model Simulation under RCP 8.5 Scenario

2019 ◽  
Vol 11 (21) ◽  
pp. 6158 ◽  
Author(s):  
Wonjae Hwang ◽  
Minseok Park ◽  
Kijong Cho ◽  
Jeong-Gyu Kim ◽  
Seunghun Hyun
Keyword(s):  
Model Simulation ◽  
Supply And Demand ◽  
N2o Emission ◽  
Economic Losses ◽  
Change Scenario ◽  
N2o Emissions ◽  
Low Carbon ◽  
Farming Practices ◽  
Dndc Model ◽  
Tillage Depth

In this study, we applied the Denitrification and Decomposition model to predict the greenhouse gas (GHGs; CO2 and N2O) emissions and cabbage yields from 8072 cabbage fields in Korea in the 2020s and 2090s. Model outputs were evaluated as a function of tillage depth (T1, T2, and T3 for 10, 20, and 30 cm) and fertilizer level (F1, F2, and F3 for 100, 200, and 400 kg N ha−1) under the Representative Concentration Pathways 8.5 climate change scenario. For both time periods, CO2 emissions increased with tillage depth, and N2O emissions were predominantly influenced by the level of applied N-fertilizers. Both cabbage yields and GHGs fluxes were highest when the T3F3 farming practice was applied. Under current conventional farming practices (T1F3), cabbage yield was projected at 64.5 t ha−1 in the 2020s, which was close in magnitude to the predicted cabbage demand. In the 2090s, the predicted cabbage supply by the same practice far exceeded the projected demand at 28.9 t ha−1. Cabbage supply and demand were balanced and GHGs emissions reduced by 19.6% in the 2090s when 94% of the total cabbage farms adopted low carbon-farming practices (e.g., reducing fertilizer level). Our results demonstrate the large potential for Korean cabbage farms to significantly contribute towards the mitigation of GHGs emissions through the adoption of low-carbon farming practices. However, in order to incentivize the shift towards sustainable farming, we advise that lower yield and potential economic losses in farmlands from adopting low-carbon practices should be appropriately compensated by institutional policy.

scholarly journals Global hotspots for the occurrence of compound events

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Nina N. Ridder ◽  
Andy J. Pitman ◽  
Seth Westra ◽  
Anna Ukkola ◽  
Hong X. Do ◽  
...  
Keyword(s):  
Western Europe ◽  
Climate Models ◽  
Global Scale ◽  
Reanalysis Data ◽  
Economic Losses ◽  
Multiple Hazards ◽  
Weather And Climate ◽  
Spatial Estimates ◽  
Compound Events ◽  
Climate Events

AbstractCompound events (CEs) are weather and climate events that result from multiple hazards or drivers with the potential to cause severe socio-economic impacts. Compared with isolated hazards, the multiple hazards/drivers associated with CEs can lead to higher economic losses and death tolls. Here, we provide the first analysis of multiple multivariate CEs potentially causing high-impact floods, droughts, and fires. Using observations and reanalysis data during 1980–2014, we analyse 27 hazard pairs and provide the first spatial estimates of their occurrences on the global scale. We identify hotspots of multivariate CEs including many socio-economically important regions such as North America, Russia and western Europe. We analyse the relative importance of different multivariate CEs in six continental regions to highlight CEs posing the highest risk. Our results provide initial guidance to assess the regional risk of CE events and an observationally-based dataset to aid evaluation of climate models for simulating multivariate CEs.

scholarly journals A comparison of Loon balloon observations and stratospheric reanalysis products

2017 ◽  
Vol 17 (2) ◽  
pp. 855-866 ◽  
Author(s):  
Leon S. Friedrich ◽  
Adrian J. McDonald ◽  
Gregory E. Bodeker ◽  
Kathy E. Cooper ◽  
Jared Lewis ◽  
...  
Keyword(s):  
Reanalysis Data ◽  
Location Information ◽  
Data Sets ◽  
Wind Fields ◽  
Weather Forecasts ◽  
Wind Speeds ◽  
Zonal Winds ◽  
Long Duration ◽  
Environmental Prediction ◽  
Modern Era

Abstract. Location information from long-duration super-pressure balloons flying in the Southern Hemisphere lower stratosphere during 2014 as part of X Project Loon are used to assess the quality of a number of different reanalyses including National Centers for Environmental Prediction Climate Forecast System version 2 (NCEP-CFSv2), European Centre for Medium-Range Weather Forecasts (ERA-Interim), NASA Modern Era Retrospective-Analysis for Research and Applications (MERRA), and the recently released MERRA version 2. Balloon GPS location information is used to derive wind speeds which are then compared with values from the reanalyses interpolated to the balloon times and locations. All reanalysis data sets accurately describe the winds, with biases in zonal winds of less than 0.37 m s−1 and meridional biases of less than 0.08 m s−1. The standard deviation on the differences between Loon and reanalyses zonal winds is latitude-dependent, ranging between 2.5 and 3.5 m s−1, increasing equatorward. Comparisons between Loon trajectories and those calculated by applying a trajectory model to reanalysis wind fields show that MERRA-2 wind fields result in the most accurate simulated trajectories with a mean 5-day balloon–reanalysis trajectory separation of 621 km and median separation of 324 km showing significant improvements over MERRA version 1 and slightly outperforming ERA-Interim. The latitudinal structure of the trajectory statistics for all reanalyses displays marginally lower mean separations between 15 and 35° S than between 35 and 55° S, despite standard deviations in the wind differences increasing toward the equator. This is shown to be related to the distance travelled by the balloon playing a role in the separation statistics.

What is the Economics of Wind Hazard Mitigation?

2016 ◽  
Vol 11 (1) ◽  
Author(s):  
Pataya Scott ◽  
Daan Liang
Keyword(s):  
United States ◽  
Hazard Mitigation ◽  
The United States ◽  
Economic Losses ◽  
Policy Makers ◽  
Loss Of Life ◽  
Peace Of Mind ◽  
Wind Hazard ◽  
Extreme Winds

AbstractTornadoes, hurricanes, and other extreme winds cause deaths, injuries, and millions, if not billions, of dollars in damages every year in the United States. Mitigation is necessary to reduce the loss of life, anxiety and suffering, and economic losses. But how much are people willing to invest in their peace of mind? Policy makers typically use the range of $1 million to $10 million per life saved to determine whether a policy that would save lives should be implemented. Individuals have shown that they are willing to pay more for homes with upgrades for mitigation and safety even though they would have no insurance incentive and it is likely that the added cost only affords them peace of mind.

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