Storms

Assessment versions

Published (reviewed and quality assured)

• Storms (CLIM 005) - Assessment published Nov 2012

Justification for indicator selection

Storms are atmospheric disturbances that are defined by strong sustained wind. In many cases, they are accompanied by heavy precipitation (rain, hail or snow) and lightning. In Europe, storms can range from relatively small and localised events to large features covering a substantial part of the continent. They typically develop from extra-tropical cyclones which are low-pressure weather systems that occur between 30 and 80 °N and capture their energy from the temperature contrast between the sub-tropical and polar air masses that meet in the Atlantic Ocean. These extra-tropical cyclones are closely associated with atmospheric fronts which delineate changes in temperature, moisture, wind speed and direction, and atmospheric pressure. In northern and north-western Europe severe cyclones can occur all year. In central Europe severe cyclones occur mainly between November and February whereas weaker cyclones can also occur in other seasons.

Studies of storm activity have increased in recent years as a result of improved observational datasets and the development of algorithms for the identification and quantification of these phenomena. In addition, high-resolution GCM simulations for both present-day climate and climate change scenarios are increasingly becoming available. Nevertheless, there are still considerable uncertainties in our understanding of the processes influencing current storm activity and how these may be affected by climate change.

Storm events are associated with intense winds and precipitation, which may lead to structural damage, flooding and storm surges. These events can have large impacts on human health and on vulnerable systems, such as forests, and transport and energy infrastructures. According to the Munich Re NatCatSERVICE and the EM-DAT database, storms were the costliest natural hazard (in terms of insured losses) in Europe between 1998 and 2009; they ranked fourth in terms of the number of human casualties.

Scientific references:

• IPCC, 2007. Climate Change: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon, S.; Qin, D.; Manning, M.; Chen, Z.; Marquis, M.; Averyt, K. B.; Tignor M. and Miller H. L. (eds.), Cambridge University Press, Cambridge, UK.

Indicator definition

• Trends in the extreme wind speeds (95th percentile of daily maximum wind speed)

• Projected changes in extreme wind speed (98th percentile of daily maximum wind speed) based on GCM and RCM ensemble

Units

• Interannual standard deviation

• m/s

Policy context and targets

Context description

In April 2009 the European Commission presented a White Paper on the framework for adaptation policies and measures to reduce the European Union's vulnerability to the impacts of climate change. The White Paper stresses the need to improve the knowledge base and to mainstream adaptation into existing and new EU policies. The European Commission will be publishing an EU Adaptation Strategy in 2013. A number of Member States have already taken action, and several have prepared national adaptation plans.

The European Commission and the European Environment Agency have developed the European Climate Adaptation Platform (Climate-ADAPT, http://climate-adapt.eea.europa.eu/) to share knowledge on observed and projected climate change and its impacts on environmental and social systems and on human health; on relevant research; on EU, national and subnational adaptation strategies and plans; and on adaptation case studies.

Targets

No targets have been specified.

Related policy documents

• Climate-ADAPT: Mainstreaming adaptation in EU sector policies
  Overview of EU sector policies in which mainstreaming of adaptation to climate change is ongoing or explored
• Climate-ADAPT: National adaptation strategies
  Overview of activities of EEA member countries in preparing, developing and implementing adaptation strategies
• DG Climate Action: What is the EU doing about climate change?
  Activities of the EU regarding climate change (both mitigation and adaptation)
• White paper - Adapting to climate change: towards a European framework for action
  EU framework for adaptation to climate change, leading to a comprehensive EU adaptation strategy by 2013

Methodology

Methodology for indicator calculation

Trends in the annual 95th percentile of daily maximum wind speeds in the 20th century reanalysis data set (ensemble mean) during the period 1871–2008. The trend is given in the units of the interannual standard deviation and plotted only when significant. Coloured circles indicate trends in the number of ‘gale days’ (an index that represents the number of extreme windy days) over the period at the specific locations.

Ensemble mean of changes in extreme wind speed (defined as the 98th percentile of daily maximum wind speed) for A1B (2071–2100) relative to 1961–2000. Statistical significance above 0.95 is shown by black dots.

Methodology for gap filling

Not applicable

Methodology references

• M. G. Donat et al. (2011): Reanalysis suggests long-term upward trends in European storminess since 1871 GEOPHYSICAL RESEARCH LETTERS, VOL. 38, L14703, 6 PP., doi:10.1029/2011GL047995
• M. G. Donat et al. (2011): Future changes in European winter storm losses and extreme wind speeds inferred from GCM and RCM multi-model simulationsnce Nat. Hazards Earth Syst. Sci., 11, 1351-1370, 2011 www.nat-hazards-earth-syst-sci.net/11/1351/2011/ doi:10.5194/nhess-11-1351-2011

Data specifications

EEA data references

• No datasets have been specified here.

External data references

• Future changes in European winter storm losses and extreme wind speeds
• European storminess

Data sources in latest figures

Uncertainties

Methodology uncertainty

Not applicable

Data sets uncertainty

A dense network of stations across the globe, and particularly in Europe, now provide regular monitoring of key atmospheric climate variables, using standardised measurements, quality control and homogeneity procedures at European level. However, even where sufficient data are available, several problems can limit their use for analysis. These problems are mainly connected with 1) limitations of distributing data in high spatial and temporal resolution by many countries, 2) unavailability of data in easy-to-use digital format, and lack of data homogeneity. The situation in Europe is improving since several EU-funded projects (such as ECA&D and EURO4M) have started to collect, digitalise and homogenise additional time series of the essential climate variables. In addition, EUMETNET  initiated an optional programme, EUMETGRID , which aims to develop and maintain a sustainable common data infrastructure for access to and distribution of gridded climate information in Europe and establish recommendations of best practices for establishing national and European gridded datasets.

Further information on uncertainties is provided in Section 1.7 of the EEA report on Climate change, impacts, and vulnerability in Europe 2012 (http://www.eea.europa.eu/publications/climate-impacts-and-vulnerability-2012/)

Rationale uncertainty

No uncertainty has been specified