Extremes of near-surface wind speed over Europe and their future changes as estimated from an ensemble of RCM simulations

In this study, we analyse the uncertainty of the effect of enhanced greenhouse gas conditions on windiness projected by an ensemble of regional model simulations driven by the same global control and climate change simulations. These global conditions, representative for 1961–1990 and 2071–2100, were prepared by the Hadley Centre based on the IPCC SRES/A2 scenario. The basic data sets consist of simulated daily maximum and daily mean wind speed fields (over land) from the PRUDENCE data archive at the Danish Meteorological Institute. The main focus is on the results from the standard 50 km-resolution runs of eight regional models. The best parameter for determining possible future changes in extreme wind speeds and possible change in the number of storm events is maximum daily wind speed. It turned out during this study that the method for calculating maximum daily wind speed differs among the regional models. A comparison of simulated winds with observations for the control period shows that models without gust parameterisation are not able to realistically capture high wind speeds. The two models with gust parametrization estimate an increase of up to 20% of the number of storm peak (defined as gusts?≥?8 Bft in this paper) events over Central Europe in the future. In order to use a larger ensemble of models than just the two with gust parameterisation, we also look at the 99th percentile of daily mean wind speed. We divide Europe into eight sub-regions (e.g., British Isles, Iberian Peninsula, NE Europe) and investigate the inter-monthly variation of wind over these regions as well as differences between today’s climate and a possible future climate. Results show differences and similarities between the sub-regions in magnitude, spread, and seasonal tendencies. The model ensemble indicates a possible increase in future mean daily wind speed during winter months, and a decrease during autumn in areas influenced by North Atlantic extra-tropical cyclones.     

Tropical and extratropical cyclone damages under climate change

This paper provides the first quantitative synthesis of the rapidly growing literature on future tropical and extratropical cyclone damages under climate change. We estimate a probability distribution for the predicted impact of changes in global surface air temperatures on future storm damages, using an ensemble of 478 estimates of the temperature-damage relationship from nineteen studies. Our analysis produces three main empirical results. First, we find strong but not conclusive support for the hypothesis that climate change will cause damages from tropical cyclones and wind storms to increase, with most models predicting higher future storm damages due to climate change. Second, there is substantial variation in projected changes in losses across regions. Potential changes in damages are greatest in the North Atlantic basin, where the multi-model average predicts that a 2.5 °C increase in global surface air temperature would cause hurricane damages to increase by 63 %. The ensemble predictions for Western North Pacific tropical cyclones and European wind storms (extratropical cyclones) are +28 % and +23 %, respectively. Finally, our analysis shows that existing models of storm damages under climate change generate a wide range of predictions, ranging from moderate decreases to very large increases in losses.     

Insuring future climate catastrophes

The combined influences of a change in climate patterns and the increased concentration of property and economic activity in hazard-prone areas has the potential of restricting the availability and affordability of insurance. This paper evaluates the premiums that private insurers are likely to charge and their ability to cover residential losses against hurricane risk in Florida as a function of (a) recent projections on future hurricane activity in 2020 and 2040; (b) insurance market conditions (i.e., soft or hard market); (c) the availability of reinsurance; and (d) the adoption of adaptation measures (i.e., implementation of physical risk reduction measures to reduce wind damage to the structure and buildings). We find that uncertainties in climate projections translate into a divergent picture for insurance in Florida. Under dynamic climate models, the total price of insurance for Florida (assuming constant exposure) could increase significantly by 2040, from $12.9 billion (in 1990) to $14.2 billion, under hard market conditions. Under lower bound projections, premiums could decline to $9.4 billion by 2040. Taking a broader range of climate change scenarios, including several statistical ones, prices could be between $4.7 and $32.1 billion by 2040. The upper end of this range suggests that insurance could be unaffordable for many people in Florida. The adoption of most recent building codes for all residences in the state could reduce by nearly half the expected price of insurance so that even under high climate change scenarios, insurance premiums would be lower than under the 1990 baseline climate scenario. Under a full adaptation scenario, if insurers can obtain reinsurance, they will be able to cover 100 % of the loss if they allocated 10 % of their surplus to cover a 100-year return hurricane, and 63 % and 55 % of losses from a 250-year hurricane in 2020 and 2040. Property-level adaptation and the maintenance of strong and competitive reinsurance markets will thus be essential to maintain the affordability and availability of insurance in the new era of catastrophe risk.     

Adaptive Wind Gust and Associated Gust-factor Model for the Gust-producing Weather over the Northern South China Sea

Wind gusts are common environmental hazards that can damage buildings, bridges, aircraft, and cruise ships and interrupt electric power distribution, air traffic, waterway transport and port operations. Accurately predicting peak wind gusts in numerical models is essential for saving lives and preventing economic losses. This study investigates the climatology of peak wind gusts and their associated gust factors(GFs) using observations in the coastal and open ocean of the northern South China Se...     

Increased probability of fire during late Holocene droughts in northern New England

A 101 year time-series of storm losses in the Netherlands is developed from the near-surface wind speed records at five Dutch stations. Station metadata combined with results from statistical tests were used to homogenise the data and retain the temporal variability driven solely by changes in climate processes. The wind speed data were transformed into storm damage using a model measuring loss impacts upon society. The resulting windstorm loss time-series for the Netherlands contains some interesting features. Annual losses are stable over the whole period and have a dominant cycle with a period of about 50 years. The Netherlands is currently experiencing the minimum aggregate storm damage of the past 100 years, though only slightly lower than a quiet period of 50 years ago. Both of these minima are driven primarily by lowered rates of occurrence of damaging storms. However, further analysis reveals the present-day minimum has different characteristics from the previous lull: currently, the frequency of stronger storms is slightly above the previous minimum whereas the frequency of weaker storms is uniquely low. A seasonal analysis provides more information: there is a dearth of damaging storms in the earlier half of the storm season in the present day; since this period contains generally weaker storms, this seasonality is also manifested as a lack of weaker storms. These results suggest a different mix of climate forcing mechanisms in modern times compared to 50 years ago, in the earlier half of the storm season.     

Do we need to include soil evolution module in models for prediction of future climate change?

Climate change induce increases in precipitation in Northern Europe that may in turn affect soil evolution by increasing the amounts of water flowing through soils. However, there is a general lack of consideration of the impact of climate change on soil evolution. We propose here to use agricultural soil drainage—that also increases the amount of water flowing through soils—as an analogy to climate change. We thus studied the impact of 16 years of agricultural drainage in one cropped plot of the most common type of soils of Northern Europe. To estimate the importance of the soil evolution induced by drainage, we compared it to the long term natural evolution of that soil. The recent increase in water fluxes by agricultural drainage (16 years) has resulted in an increase in the intensity and velocity of the natural pedological processes. The increased amount of water flowing thorough soils due to drainage is of same order of magnitude than that that would be induced by climate change in the next 50–100 years in northern Europe. Our results demonstrated thus that climate change will significantly affect soil evolution. This evolution induces losses of the finest particles involved in organic carbon sequestration and thus has a feedback effect on climate change. Therefore we consider that soil evolution in response to climate change has to be explicitly studied and included in models predicting global climate change.     

Future Climate Impact on the Productivity of Sugar Beet (Beta vulgaris L.) in Europe

The impact of future climate change on sugar beet yields is assessed over western Europe using future (2021–2050) climate scenario data from a General Circulation Model (GCM) and the Broom's Barn simulation model of rain-fed crop growth and yield. GCM output for the 1961–1990 period is first compared with observed climate data and shown to be reliable for regions west of 24° E. Comparisons east of this meridian were less reliable with this GCM (HadCM2) and so were omitted from simulations of crop yield. Climate change is expected to bring yield increases of around 1 t/ha of sugar in northern Europe with decreases of a similar magnitude in northern France, Belgium and west/central Poland, for the period 2021–2050. Averaged for the study area (weighted by current regional production), yields show no overall change due to changed climate. However, this figure masks significant increases in yield potential (due to accelerated growth in warmer springs) and in losses due to drought stress. Drought losses are predicted to approximately double in areas with an existing problem and to become a serious new problem in NE France and Belgium. Overall west and central Europe simulated average drought losses rise from 7% (1961–1990) to 18% (2021–2050). The annual variability of yield (as measured by the coefficient of variation) will increase by half, from 10% to 15% compared to 1961–1990, again with potentially serious consequences for the sugar industry. The importance of crop breeding for drought tolerance is further emphasised. These changes are independent of the 9% yield increase which we estimate, on the basis of work by Demmers-Derks et al. (1998), is the likely direct effect of the increase in atmospheric CO₂ concentration by 2021–2050.     

Catastrophic winter storms: An escalating problem

Winter storms are a major weather problem in the USA and their losses have been rapidly increasing. A total of 202 catastrophic winter storms, each causing more than $1 million in damages, occurred during 1949–2003, and their losses totaled $35.2 billion (2003 dollars). Catastrophic winter storms occurred in most parts of the contiguous USA, but were concentrated in the eastern half of the nation where 88% of all storm losses occurred. They were most frequent in the Northeast climate district (95 storms), and were least frequent in the West district (14 catastrophic storms). The annual average number of storms is 3.7 with a 1-year high of 9 storms, and 1 year had no storms. Temporal distributions of storms and their losses exhibited considerable spatial variability across the nation. For example, when storms were very frequent in the Northeast, they were infrequent elsewhere, a result of spatial differences in storm-producing synoptic weather conditions over time. The time distribution of the nation’s 202 storms during 1949–2003 had a sizable downward trend, whereas the nation’s storm losses had a major upward trend for the 55-year period. This increase over time in losses, given the decrease in storm incidences, was a result of significant temporal increases in storm sizes and storm intensities. Increases in storm intensities were small in the northern sections of the nation, but doubled across the southern two-thirds of the nation, reflecting a climatic shift in conditions producing intense winter storms.     

Assisted tree migration can reduce but not avert the decline of forest ecosystem services in Europe

European forests are facing multiple natural and anthropogenic pressures that are expected to become more severe in the next decades. Tree diversity is projected to decline in many areas across the continent. How this will affect the provision of forest services remains an open question, whose answer depends, among others, on the practical and theoretical challenges of incorporating assisted migration into climate adaptation strategies. Here, we tackle the issue by combining a large dataset of tree species occurrences, future climatic projections, and data on tree functional traits and tree-specific forest services into a novel modelling framework. We estimate that, by the end of the century and under a natural dispersal scenario, the provision of forest services would decrease on average by 15% in Europe (for RCP 4.5; 23% for RCP 8.5), and up to 52% (70% for RCP 8.5) in the Mediterranean. To explore if and how management could reduce the projected losses, we simulated a suite of alternative assisted migration strategies aimed at identifying, for each locality, the tree species communities offering the best compromise in terms of resilience to climate change and delivery of specific combinations of ecosystem services. Such strategies could reduce losses of services by 10% (15%) on average in Europe, and even increase service availability in the Alpine and Boreal regions but not in the Mediterranean, where losses will remain as high as 33% (54% for RCP 8.5). Our findings highlight how science-driven management strategies could be vital to reduce an otherwise dramatic, European-wide decline of forest services. Our results are qualitatively robust to different assumptions on future carbon emissions and related climate trajectories. That is, our simulated assisted migration strategies identify similar tree species communities under different pathways (RCP 4.5 vs RCP 8.5). This makes our approach a powerful tool for forest management, as it generates advice that is valid regardless of whether, and to what extent, human society will steer away from business-as-usual emission trajectories.     

Numerical investigations of extreme winds over Switzerland during 1990–2010 winter storms with the Canadian Regional Climate Model

This study reports on the ability of the Canadian Regional Climate Model to simulate the surface wind gusts of 24 severe mid-latitude storms in Switzerland during the period 1990–2010. A multiple self-nesting approach is used, reaching a final 2-km grid which is centred over Switzerland, a country characterised by complex topography. A physically-based wind gust parameterization scheme is applied to simulate local surface gusts. Model performance is evaluated by comparing simulated wind speeds to time series at weather stations. While a number of simulated variables are reproduced in a realistic manner, the surface wind gusts show differences when compared to observed values. Results indicate that the performance of this parameterization scheme not only depends on the accuracy of the simulated planetary boundary layer, the vertical temperature, wind speed and atmospheric humidity profiles, but also on the accuracy of the reproduction of the surface fields such as temperature and moisture.     

An assessment of the potential impact of climate change on flood risk in Mumbai

Managing risks from extreme events will be a crucial component of climate change adaptation. In this study, we demonstrate an approach to assess future risks and quantify the benefits of adaptation options at a city-scale, with application to flood risk in Mumbai. In 2005, Mumbai experienced unprecedented flooding, causing direct economic damages estimated at almost two billion USD and 500 fatalities. Our findings suggest that by the 2080s, in a SRES A2 scenario, an ??upper bound?? climate scenario could see the likelihood of a 2005-like event more than double. We estimate that total losses (direct plus indirect) associated with a 1-in-100 year event could triple compared with current situation (to $690?C$1,890 million USD), due to climate change alone. Continued rapid urbanisation could further increase the risk level. The analysis also demonstrates that adaptation could significantly reduce future losses; for example, estimates suggest that by improving the drainage system in Mumbai, losses associated with a 1-in-100 year flood event today could be reduced by as much as 70%.,We show that assessing the indirect costs of extreme events is an important component of an adaptation assessment, both in ensuring the analysis captures the full economic benefits of adaptation and also identifying options that can help to manage indirect risks of disasters. For example, we show that by extending insurance to 100% penetration, the indirect effects of flooding could be almost halved. We conclude that, while this study explores only the upper-bound climate scenario, the risk-assessment core demonstrated in this study could form an important quantitative tool in developing city-scale adaptation strategies. We provide a discussion of sources of uncertainty and risk-based tools could be linked with decision-making approaches to inform adaptation plans that are robust to climate change.     

Climate Risks and Their Impact on Agriculture and Forests in Switzerland

There is growing evidence that, as a result of global climate change, some of the most severe weather events could become more frequent in Europe over the next 50 to 100 years. The paper aims to (i) describe observed trends and scenarios for summer heat waves, windstorms and heavy precipitation, based on results from simulations with global circulation models, regional climate models, and other downscaling procedures, and (ii) discuss potential impacts on agricultural systems and forests in Switzerland. Trends and scenarios project more frequent heavy precipitation during winter corresponding, for example, to a three-fold increase in the exceedance of today's 15-year extreme values by the end of the 21st century. This increases the risk of large-scale flooding and loss of topsoil due to erosion. In contrast, constraints in agricultural practice due to waterlogged soils may become less in a warmer climate. In summer, the most remarkable trend is a decrease in the frequency of wet days, and shorter return times of heat waves and droughts. This increases the risk of losses of crop yield and forage quality. In forests, the more frequent occurrence of dry years may accelerate the replacement of sensitive tree species and reduce carbon stocks, and the projected slight increase in the frequency of extreme storms by the end of the century could increase the risk of windthrow. Some possible measures to maintain goods and services of agricultural and forest ecosystems are mentioned, but it is suggested that more frequent extremes may have more severe consequences than progressive changes in means. In order to effectively decrease the risk for social and economic impacts, long-term adaptive strategies in agriculture and silviculture, investments for prevention, and new insurance concepts seem necessary.     

Damaging Weather Conditions in the United States: A Selection of Data Quality and Monitoring Issues

The limitations of observational data available for the study of damaging weather conditions (e.g., storms and extreme temperature events) are discussed. Crop and property insurance loss records are advocated as a potential supplement to traditional weather observations, as they integrate specific information about the spatial dimension of damaging weather conditions and the cost of damage they cause. Insurance loss data may also be analyzed in combination with meteorological data sets to derive indicator variables for the detection of damaging weather events.Two sets of insurance data are described. One record provides adjusted property losses associated with "catastrophic" weather events since 1949, and the other is an index of the amount of crop-hail losses per year since 1948. Additionally, an example of the benefits of the combination of insurance and meteorological data is presented through a selection of results from a recent study of freezing temperatures in the southeastern United States and associated insurance claims related to pipe bursting.If insurance data are to be applied in the future in similar studies of damaging weather conditions, it is essential that the insurance industry continues to collect and adjust loss data and periodically confirm that adjustment factors are temporally consistent.     

Relating remotely sensed forest damage data to wind data: storms Lothar (1999) and Vivian (1990) in Switzerland

This study compares the surface wind speed and forest damage data of two exceptionally severe winter storms, Vivian 1990 and Lothar 1999. The study area comprises the region that suffered damage in Switzerland. The wind speed data were derived from simulations of MeteoSwiss (Federal Office of Meteorology and Climatology), measurements during the storm periods and expert analyses of the data. The remotely sensed forest damage data were provided by the Federal Office for the Environment and the forest cover data by Swiss Federal Statistical Office. We compared data on the peak gust and maximum average wind speed, with data on the spatially related forest area and forest damage area, and found some clear differences in the correlations between the different wind data and forest damage. Our results point generally to the damage-causing role of near-surface gusts at maximum wind speeds during the storm. These tended to be spatially distributed on a fine scale. In only a few cases were the results statistically significant. However, these results could probably be improved with better wind data. For example, gust measurements spatially closer to forests or simulations of gusts at maximum wind speed could be produced with a spatially higher resolution.     

Evaluation of Weather Catastrophe Data for Use in Climate Change Investigations

A 1950–1994 data set of major weather losses developed by the property insurance industry was examined to assess its potential utility in climate change research and use in assessing the relevance of recent extreme losses in the United States. A process for adjusting these historical storm losses to ever-changing factors including dollar values, amount of insurance coverage per area, and the sensitivity of society to damaging storms was developed by the industry. Analysis of the temporal frequency and losses of these adjusted weather catastrophes revealed differences according to the amount of loss. Temporal changes since 1975 in the catastrophes causing $35 to $100 million in loss were strongly related to changes in U.S. population, whereas catastrophes that created insured losses greater than $100 million appear related to both shifting weather conditions and to regional population changes. This evaluation revealed that the industry's catastrophe adjustment technique did not adequately allow for changes in various demographic and social factors affecting damage; however, results suggest use of population values for normalizing the adjusted catastrophe database to allow meaningful studies of their temporal variability.     

An assessment of global and regional climate change based on the EH5OM climate model ensemble

An analysis of climate change for global domain and for the European/Mediterranean region between the two periods, 1961–1990 (representing the twentieth century or “present” climate) and 2041–2070 (representing future climate), from the three-member ensemble of the EH5OM climate model under the IPCC A2 scenario was performed. Ensemble averages for winter and summer seasons were considered, but also intra-ensemble variations and the change of interannual variability between the two periods. First, model systematic errors are assessed because they could be closely related to uncertainties in climate change. A strengthening of westerlies (zonalization) over the northern Europe is associated with an erroneous increase in MSLP over the southern Europe. This increase in MSLP is related to a (partial) suppression of summer convective precipitation. Global warming in future climate is relatively uniform in the upper troposphere and it is associated with a 10% wind increase in the subtropical jet cores. However, spatial irregularities in the low-level temperature signal single out some regions as particularly sensitive to climate change. For Europe, the largest near-surface temperature increase in winter is found over its north-eastern part (more than 3°C), and the largest summer warming (over 3.5°C) is over south Europe. For south Europe, the increase in temperature averages is almost an order of magnitude larger than the increase in interannual variability. The magnitude of the warming is larger than the model systematic error, and the spread among the three model realisations is much smaller than the magnitude of climate change. This further supports the significance of estimated future temperature change. However, this is not the case for precipitation, implying therefore larger uncertainties for precipitation than for temperature in future climate projections.     

Increasing major hail losses in the U.S.

Property losses due to hailstorms on April 13–14, 2006, resulted in Midwestern property losses that totaled $1.822 billion, an amount considerably more than the previous record high of $1.5 billion set by an April 2001 hail event. The huge April 2006 loss was largely due to multiple severe storms with frequent large hail hitting major metropolitan areas. A highly unstable air mass that developed on April 13 led to several supercell storms and they then produced large hailswaths across portions of Iowa, Illinois, Indiana, and Wisconsin during a 30-h period. This storm event and prior recent major hail losses occurred when several major hailstorms developed and then traveled for hundreds of kilometers. The nation’s top ten loss events during 1950–2006 reveal a notable temporal increase with most losses in the 1992–2006 period. Causes for the increases could be an increasing frequency of very unstable atmospheric conditions leading to bigger, longer lasting storms, and/or a greatly expanded urban society that has become increasingly vulnerable to hailstorms.     

On the future reduction of snowfall in western and central Europe

Large parts of western and central Europe face a 20–50 % future reduction in snowfall on Hellmann days (days with daily-mean temperatures below freezing). This strong reduction occurs in addition to the expected 75 % decrease of the number of Hellmann days near the end of the twenty first century. The result is insensitive to the exact freezing-level threshold, but is in sharp contrast with the winter daily precipitation, which increases under most global warming scenarios. Not only climate model simulations show this. Observational records also reveal that probabilities for precipitation on Hellmann days have been larger in the past. The future reduction is a consequence of the freezing-level threshold becoming a more extreme quantile of the temperature distribution in the future. Only certain circulation types permit these quantiles to be reached, and it is shown that these have intrinsically low precipitation probability.     

Projected change in East Asian summer monsoon precipitation under RCP scenario

Future changes in East Asian summer monsoon precipitation climatology, frequency, and intensity are analyzed using historical climate simulations and future climate simulations under the RCP4.5 scenario using the World Climate Research Programme’s (WCRP) Coupled Model Intercomparison Project 5 (CMIP5) multi-model dataset. The model reproducibility is evaluated, and well performance in the present-day climate simulation can be obtained by most of the studied models. However, underestimation is obvious over the East Asian region for precipitation climatology and precipitation intensity, and overestimation is observed for precipitation frequency. The overestimation of precipitation frequency is mainly due to the large positive bias of the light precipitation (precipitation <10 mm/day) days, and the underestimation of precipitation intensity is mainly caused by the negative bias of the intense precipitation (precipitation >10 mm/day) intensity. For the future climate simulations, simple multi-model ensemble (MME) averages using all of the models show increases in precipitation and its intensity over almost all of East Asia, while the precipitation frequency is projected to decrease over eastern China and around Japan and increase in other regions. When the weighted MME is considered, no large difference can be observed compared with the simple MME. For the MME using the six best models that have good performance in simulating the present-day climate, the future climate changes over East Asia are very similar to those predicted using all of the models. Further analysis shows that the frequency and intensity of intense precipitation events are also projected to significantly increase over East Asia. Increases in precipitation frequency and intensity are the main contributors to increases in precipitation, and the contribution of frequency increases (contributed by 40.8 % in the near future and by 58.9 % by the end of the twenty-first century) is much larger than that of intensity increases (contributed by 29.9 % in the near future and by 30.1 % by the end of the twenty-first century). This finding also implies an increased risk of intense precipitation events over the East Asian region under global warming scenario. These results regarding future climate simulations show much greater reliability than those using CMIP3 simulations.     

The Impacts of Socioeconomic Development and Climate Change on Severe Weather Catastrophe Losses: Mid-Atlantic Region (MAR) and the U.S.

One strand of research relates the magnitude of severe weather disasters to climatic and human development factors; another highlights dramatic growth in catastrophe losses. However, there have been few attempts to put the two strands together. Here we use an explicit modeling framework to determine the contribution of climate variability relative to human factors in reported catastrophe losses. We then examine how future climate change can be expected to affect losses from natural disasters. Simultaneous regression models are constructed from three equations in which the dependent variables are U.S. flood loss, U.S. hurricane loss and U.S. catastrophe loss. Then two kinds of simulation under two climate change scenarios explore how climate change would affect losses. The climate change scenarios respectively project 13.5% and 21.5% increases in annual precipitation. The first simulation increases only the mean value of annual precipitation; the second simulation assumes that the mean and standard deviation of annual precipitation change in the same proportion. Results show that the growth in reported losses from weather-related natural disasters is due mainly to three socioeconomic factors: inflation, population growth and growth in per capita real wealth. However, weather variables such as precipitation and the number of hurricanes per period also clearly affect losses. The three stage least squares (3SLS) simultaneous equation model shows that a 1% increase in annual precipitation would enlarge catastrophe loss by as much as 2.8%. These findings are suggestive as planning signals to decision makers.