Economic losses from climate-related extremes in Europe

Indicator Assessment
Prod-ID: IND-182-en
Also known as: CSI 042 , CLIM 039
Created 24 Jan 2019 Published 02 Apr 2019 Last modified 02 Apr 2019
18 min read
In the EEA member countries (EEA-33), the total reported economic losses caused by weather and climate-related extremes over the period 1980-2017 amounted to approximately EUR 453 billion (in 2017 Euro values).  Average annual economic losses in the EEA member countries varied between EUR 7.4 billion over the period 1980-1989, EUR 13.4 billion (1990-1999) and EUR 14.0 billion (2000-2009). Between 2010 and 2017, average annual losses were around EUR 13.0 billion. This high variability makes the analysis of historical trends difficult, since the choice of years heavily influences the trend outcome. The observed variations in reported economic losses over time are difficult to interpret since a large share of the total deflated losses has been caused by a small number of events. Specifically, more than 70 % of economic losses were caused by less than 3 % of all unique registered events. In the EU Member States (EU-28), disasters caused by weather and climate-related extremes accounted for some 83 % of the monetary losses over the period 1980-2017. Weather and climate-related losses amounted to EUR 426 billion (at 2017 values). The most expensive climate extremes in the EU Member States include the 2002 flood in Central Europe (over EUR 21 billion), the 2003 drought and heat wave (almost EUR 15 billion), and the 1999 winter storm Lothar and October 2000 flood in Italy and France (both EUR 13 billion), all at 2017 values.

Key messages

  • In the EEA member countries (EEA-33), the total reported economic losses caused by weather and climate-related extremes over the period 1980-2017 amounted to approximately EUR 453 billion (in 2017 Euro values). 
  • Average annual economic losses in the EEA member countries varied between EUR 7.4 billion over the period 1980-1989, EUR 13.4 billion (1990-1999) and EUR 14.0 billion (2000-2009). Between 2010 and 2017, average annual losses were around EUR 13.0 billion. This high variability makes the analysis of historical trends difficult, since the choice of years heavily influences the trend outcome.
  • The observed variations in reported economic losses over time are difficult to interpret since a large share of the total deflated losses has been caused by a small number of events. Specifically, more than 70 % of economic losses were caused by less than 3 % of all unique registered events.
  • In the EU Member States (EU-28), disasters caused by weather and climate-related extremes accounted for some 83 % of the monetary losses over the period 1980-2017. Weather and climate-related losses amounted to EUR 426 billion (at 2017 values).
  • The most expensive climate extremes in the EU Member States include the 2002 flood in Central Europe (over EUR 21 billion), the 2003 drought and heat wave (almost EUR 15 billion), and the 1999 winter storm Lothar and October 2000 flood in Italy and France (both EUR 13 billion), all at 2017 values.

What is the trend in economic losses from climate-related extremes in Europe?

Impacts of extreme weather and climate related events in the EEA member countries (1980-2017)

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Natural hazards in EU and EEA Member States (1980-2017)

EEA-33
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EU-28
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Table
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Economic damage caused by weather and climate-related extreme events in Europe (1980-2017)

EEA-33
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EU-28
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Past trends

According to data on natural disasters in the member countries of the European Environment Agency (EEA) between 1980 and 2017 — from the NatCatSERVICE of Munich Re (1) — weather and climate-related extremes (2) accounted for around 81 % of total losses caused by natural hazards.

Specifically, weather and climate related losses amounted to EUR 453 billion (at 2017 Euro values (3)), at an average of EUR 12 billion per year, EUR 79 200 per square kilometre or EUR 811 per capita (4). The cumulative defalted losses over the period analysed are equal to nearly 3 % of the GDP of all EEA member countries in 2017. Overall, around 35 % of the  total losses were insured, although  the proportion of the insured losses ranged from 1 % in Romania and Lithuania to 70 % in the UK (Figure 1). There were 90 325 casualties registered over the period. 

Reported economic losses mainly reflect monetised direct damages to certain assets. The loss of human life, cultural heritage or ecosystem services is not part of the estimation.

The distribution of weather and climate related losses among the 33 EEA member countries is uneven. The highest overall economic losses in absolute terms (in order of rank) were registered in Germany, Italy and France (see Figure 1). The highest losses per capita were recorded in Switzerland, Denmark and Austria, while those per square kilometre were recorded in Switzerland, Luxembourg and Germany. The greatest shares of total losses in terms of cumulative GDP were registered in Croatia, Czech Republic and Hungary. The three least affected countries in absolute terms were Liechtenstein, Malta and Iceland. In relative terms (per capita) the least affected countries were Turkey, Estonia and Malta. In terms of loss as a share of cumulative GDP, the least affected countries were Liechtenstein, Iceland and Estonia.

The largest 39 events caused about half of the recorded losses.

It is important to understand to what extent the observed increase in overall losses during recent decades is attributable to changing climatic conditions rather than other factors. According to AR5 of the IPCC [i], the increasing exposure of people and economic assets to weather and climate-related disasters has been the major cause of long-term increases in economic losses from them. Available studies for economic losses from river floods and storms in Europe suggest that the observed increases in losses are primarily because of increases in populations, economic wealth and developments in hazard-prone areas, but the observed increase in heavy precipitation in parts of Europe may have also played a role [ii]. There is evidence that improved flood protection and prevention has contributed to reducing losses over time in some cases [iii].

Globally, the 'attribution science' has made significant progress in recent years in assessing whether global climate change has affected the odds of a specific observed extreme weather event. A recent review of these studies shows that, globally, the large majority of the analysed heat waves, and a majority of droughts and heavy rain and flooding events were found to have become more likely and/or severe as a result of global climate change [iv]. The attribution of storms and (other) small-scale events to global climate change is much more difficult, mainly because of their poor representation in climate models 

For the period 1980-2017, the economic losses from all natural disasters in the EEA member countries amounted to EUR 557 billion and the insured losses were approximately EUR 162 billion (in 2017 values) (Figure 2). Around 63 % of all economic losses were a result of meteorological and hydrological events, while most fatalities were caused by heatwaves. This large portion of fatalities is highly influenced by the heatwave of 2003, where around 68 000 fatalities were reported as excess mortality (Figure 2).

Recorded economic losses from weather and climate related extremes in Europe have varied substantially over time. The average annual economic loss (inflation-corrected) was around EUR 7.4 billion per year in the 1980s, EUR 13.4 billion in the 1990s and EUR 14.0 billion per year in the 2000s (2000-2009). In the period 2010-2017, the average annual economic loss amounted to around EUR 13.0 billion (Figure 3). However, the pattern that can be found in the recorded loss is obscured by high variability: around 3 % of events — some of which affected more than one country — account for around 75 % of total deflated losses. Conversely, some three quarters of the registered events were responsible for only 0.7 % of total losses. The increased economic wealth has a major effect on annual losses.

Currently there is no mechanism in place for EU Member States to report the economic losses from weather and climate-related events to the European Commission or the EEA. However, activities coordinated by the JRC (6) are underway to improve national databases on disaster losses. The Organisation for Economic Co-operation and Development (OECD) has conducted a review of the countries’ efforts to collect information on the economic impacts of disasters and the level of public resources invested in the management of risk [v]. The UN Sendai Framework for Disaster Risk Reduction 2015-2030 (SFDRR) [vi] laid down priorities for action and policy targets. Progress in achieving these targets is monitored and assessed by means of 38 indicators, some of which are also used to report on the Sustainable Development Goals. The Sendai Framework Monitor was launched in March 2018 to facilitate the reporting. The Centre for Research on the Epidemiology of Disasters (CRED) and the UN Office for Disaster Risk Reduction have published a global review of disaster impacts over the period 1998-2017 [vii], building on the EMDAT database. The summarised losses are not complete, since the majority (63 %) of disaster reports to EMDAT contains no economic estimates of losses. Once comparable national databases are available for all EU Member States and EEA member countries, and the data are reported, this EEA indicator will be based on such country data. 

Projections

The IPCC AR5 concludes that high temperature extremes, heavy precipitation events and droughts will markedly increase in all or most world regions, including in Europe. Furthermore, large parts of Europe will face an increasing drought risk [i]. There is medium confidence in the fact that climate change will increase the likelihood of systemic failures across European countries as a result of extreme climate events affecting multiple sectors [viii]. Increasing extremes will presumably lead to greater losses. However, the future cost of climate-related hazards in Europe will depend on several factors, including the resilience and vulnerability of society, which are variable across hazards and regions.

Notes

[1] NatCatSERVICE [www.munichre.com/natcatservice] is one of the most comprehensive natural catastrophe loss databases managed by the Munich Reinsurance Company (German: Münchener Rück; Münchener Rückversicherungs-Gesellschaft), based in Munich, Germany. As a proprietary database, it is not publicly accessible. The Munich Re dataset was provided to the EEA under institutional agreement, including that the data may only be analysed and used for evaluations in connection with the project and that the dataset may not be forwarded to third parties.

[2] The analysed hazards are split into four categories by Munich Re: geophysical, meteorological, hydrological and climatological. For the purpose of this indicator 'weather and climate-related events' are defined as the combination of 'meteorological, hydrological and climatological' events in NatCatSERVICE.

[3] The exact estimates differ by several percentage points depending on choices made, including the price indices chosen for accounting for inflation and the reference base (annual, monthly) for the conversion between losses expressed in USD and EUR, etc.

[4] Based on average population over the entire period 1980-2016.

[5] The Eurostat indicators used for the analysis include nama_10_gdp, nama_gdp and ert_bil_eur_m

[6] See: http://drr.jrc.ec.europa.eu/Loss-Data online

[i] IPCC,Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge; New York: Cambridge University Press, 2013), http://www.climatechange2013.org/.

[ii] e.g.
-J.I. Barredo, “Normalised Flood Losses in Europe: 1970–2006,”Natural Hazards and Earth System Sciences 9 (February 9, 2009): 97–104, doi:10.5194/nhess-9-97-2009;
- J. I. Barredo, “No Upward Trend in Normalised Windstorm Losses in Europe: 1970–2008,”Natural Hazards and Earth System Science 10, no. 1 (January 15, 2010): 97–104, doi:10.5194/nhess-10-97-2010;
- Bob Maaskant, Sebastiaan N. Jonkman, and Laurens M. Bouwer, “Future Risk of Flooding: An Analysis of Changes in Potential Loss of Life in South Holland (The Netherlands),”Environmental Science & Policy 12, no. 2 (April 2009): 157–69, doi:10.1016/j.envsci.2008.11.004;
- Laurens M. Bouwer, Philip Bubeck, and Jeroen C.J.H. Aerts, “Changes in Future Flood Risk due to Climate and Development in a Dutch Polder Area,”Global Environmental Change 20, no. 3 (August 2010): 463–71, doi:10.1016/j.gloenvcha.2010.04.002;
- A. H. te Linde et al., “Future Flood Risk Estimates along the River Rhine,”Natural Hazards and Earth System Science 11, no. 2 (February 15, 2011): 459–73, doi:10.5194/nhess-11-459-2011;
- Luc Feyen et al., “Fluvial Flood Risk in Europe in Present and Future Climates,”Climatic Change 112, no. 1 (2012): 47–62, doi:10.1007/s10584-011-0339-7;
- Hans Visser et al., “Weather-Related Disasters: Past, Present and Future,” PBL publication (Netherlands Environmental Assessment Agency, 2012), http://www.pbl.nl/sites/default/files/cms/publicaties/PBL_2012_Weather%20Disasters_555076001.pdf; Rodrigo Rojas, Luc Feyen, and Paul Watkiss, “Climate Change and River Floods in the European Union: Socio-Economic Consequences and the Costs and Benefits of Adaptation,”Global Environmental Change 23, no. 6 (December 2013): 1737–51, doi:10.1016/j.gloenvcha.2013.08.006.

[iii] e.g. Annegret H. Thieken et al., “Review of the Flood Risk Management System in Germany after the Major Flood in 2013,”Ecology and Society 21, no. 2 (2016): 51, doi:10.5751/ES-08547-210251.

[iv] Quirin Schiermeier, "Droughts, heatwaves and floods: How to tell when climate change is to blame - Weather forecasters will soon provide instant assessments of global warming's influence on extreme events", Nature 560, 20-22 (2018), doi: 10.1038/d41586-018-05849-9.

[v] OECD, 2018, Assessing the Real Cost of Disasters: The Need for Better Evidence, OECD Reviews of Risk Management Policies, OECD Publishing, Paris, https://doi.org/10.1787/9789264298798-en.

[vi] UN, 2015, Sendai Framework for Disaster Risk Reduction 2015–2030, A/CONF.224/CRP.1, 18 March 2015, available at: https:// www.unisdr.org/files/43291_sendaiframeworkfordrren.pdf.

[vii] CRED and UNISDR, 2018, Economic Losses, Poverty & Disasters 1998-2017, The Centre for Research on the Epidemiology of Disasters (CRED) and the UN Office for Disaster Risk Reduction, https://www.unisdr.org/2016/iddr/IDDR2018_Economic%20Losses.pdf

[viii] IPCC,Climate Change 2014: Impacts, Adaptation and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, ed. Vicente R. Barros et al. (Cambridge; New York: Cambridge University Press, 2014), https://ipcc-wg2.gov/AR5/report/; R. S. Kovats et al., “Europe,” inClimate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, ed. V. R. Barros et al. (Cambridge; New York: Cambridge University Press, 2014), 1267–1326, http://www.ipcc.ch/pdf/assessment-report/ar5/wg2/WGIIAR5-Chap23_FINAL.pdf.

Indicator specification and metadata

Indicator definition

This indicator considers the number of fatalities, and the overall and insured economic losses from climate-related disasters.

Units

The units used in this indicator are the number of events, and damages in euros (2015 Euro value).


Policy context and targets

Context description

In April 2013, the European Commission presented the EU Adaptation Strategy Package (http://ec.europa.eu/clima/policies/adaptation/what/documentation_en.htm). This package consisted of the EU Strategy on adaptation to climate change (COM/2013/0216 final) and a number of supporting documents. One of the objectives of the adaptation strategy is better informed decision-making, which should occur through bridging the knowledge gap and further developing Climate-ADAPT as the 'one-stop shop' for adaptation information in Europe. Further objectives include promoting action by Member States and climate-proofing EU action, i.e. promoting adaptation in key vulnerable sectors. Many EU Member States have already taken action, such as by adopting national adaptation strategies, and several have also prepared action plans on climate change adaptation.

The European Commission and the EEA 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 human health; on relevant research; on EU, national and sub-national adaptation strategies and plans; and on adaptation case studies.

Article 6 of Decision No. 1313/2013/EU of the European Parliament and the Council of 17 December 2013 on a Union Civil Protection Mechanism obliges the EU Member States to develop risk assessments at national or appropriate sub-national levels and to make a summary of the relevant elements thereof available to the Commission by 22 December 2015 and every 3 years thereafter.

The Sendai Framework for Disaster Risk Reduction (UN, Sendai Framework for Disaster Risk Reduction 2015-2030 A/CONF.224/CRP.1. 18 March 2015, 2015), under Priority 1 (Understanding disaster risk), requires that the signatory countries systematically evaluate, record, share and publicly account for disaster losses and understand the economic impacts at national and sub-national levels.

In September 2016, the EC presented an indicative road map for the evaluation of the EU Adaptation Strategy by 2018.

In November 2013, the European Parliament and the European Council adopted the Seventh EU Environment Action Programme (7th EAP) to 2020, 'Living well, within the limits of our planet'. The 7th EAP is intended to help guide EU action on the environment and climate change up to and beyond 2020. It highlights that 'action to mitigate and adapt to climate change will increase the resilience of the Union’s economy and society, while stimulating innovation and protecting the Union’s natural resources.' Consequently, several priority objectives of the 7th EAP refer to climate change adaptation.

Targets

The Sendai Framework for Disaster Risk Reduction (SFDRR) sets a target of reducing direct disaster economic loss in relation to global gross domestic product (GDP) by 2030, compared with 2005-2015 baselines. The European Union and all member countries of the EEA have endorsed the SFDRR.

Related policy documents

  • Climate-ADAPT: Country information
    Overview of activities of EEA member countries in preparing, developing and implementing adaptation strategies
  • 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
  • Decision No 1313/2013/EU of the European Parliament and of the Council on a Union Civil Protection Mechanism
    The EU Civil Protection Mechanism was set up to enable coordinated assistance from the participating states to victims of natural and man-made disasters in Europe and elsewhere. The European Commission supports and complements the prevention and preparedness efforts of participating states, focusing on areas where a joint European approach is more effective than separate national actions. These include improving the quality of and accessibility to disaster information, encouraging research to promote disaster resilience, and reinforcing early warning tools.
  • DG CLIMA: Adaptation to climate change
    Adaptation means anticipating the adverse effects of climate change and taking appropriate action to prevent or minimise the damage they can cause, or taking advantage of opportunities that may arise. It has been shown that well planned, early adaptation action saves money and lives in the future. This web portal provides information on all adaptation activities of the European Commission.
  • EU Adaptation Strategy Package
    In April 2013, the European Commission adopted an EU strategy on adaptation to climate change, which has been welcomed by the EU Member States. The strategy aims to make Europe more climate-resilient. By taking a coherent approach and providing for improved coordination, it enhances the preparedness and capacity of all governance levels to respond to the impacts of climate change.

Methodology

Methodology for indicator calculation

This assessment is based on the Munich Re NatCatSERVICE dataset and the Eurostat collection of economic indicators (5), whereas data from earlier years not covered by Eurostat have been completed using data from the Annual Macro-Economic Database of the European Commission (AMECO), the International Monetary Fund’s (IMF) World Economic Outlook (WEO), the Total Economy Database (TED) and the World Bank database.

Data are received from the Munich Re NatCatSERVICE under institutional agreement and have been adjusted to account for inflation. They are presented in EUR 2015 values.

Definition of a loss event: the event can occur in several countries; events are counted by country and by category of natural hazard.

The European Commission is working with Member States, the ISDR and other international organisations to improve data on disaster losses. The JRC has prepared guidance for recording and sharing disaster damage and loss data, status and best practices for disaster loss data recording in EU Member States and recommendations for a European approach for recording  disaster losses. Once comparable national databases on disaster losses are available for all EU Member States and EEA member countries and these data are reported, this EEA indicator can possibly be based on such data. 

The analysis reported here includes all EEA Member States and Turkey, including that part of the country that is classified by NatCatSERVICE as not belonging to Europe. This is why the results reported here may be slightly different to data reported by Munich Re itself.

 

Methodology for gap filling

The value of economic loss has not been corrected, other than for the relatively small inconsistencies that have been removed in agreement with Munich Re. The economic data for damage normalisation were taken from Eurostat, and where the Eurostat data series did not cover the entire period, the gaps were filled with the data from AMECO (Annual macro-economic database of the European Commission), the International Monetary Fund, the World Bank or by reasoned expert opinion. 

Methodology references

Uncertainties

Methodology uncertainty

Not applicable

Data sets uncertainty

Information for Europe can be extracted from two global disaster databases, namely the EMDAT database maintained by CRED (1) that places a particular focus on human fatalities, and displaced and affected people, and the NatCatSERVICE database maintained by Munich Re that provides data on insured and overall losses (used in this indicator). The 'disaster thresholds' for an event to be included in these global databases are as follows:

  • EMDAT: 10 or more people killed and/or 100 or more people affected and/or declaration of a state of emergency and/or call for international assistance;
  • NatCatSERVICE: Small-scale property damage and/or one fatality. Additionally, Munich Re uses different classes to classify the events.

Over recent years, these global databases have been harmonised, although some differences remain. During recent decades both databases have improved their reporting, which means that caution is needed in formulating conclusions about trends. In addition, both databases are less suitable for analysing the impacts of smaller events or for analysis at the sub-national level. However, despite these considerations, both databases serve as a good starting point for getting an overview of the impact and damage costs of disasters in Europe.

Further information on uncertainties is provided in the EEA report on Climate change, impacts, and vulnerability in Europe 2016 (http://www.eea.europa.eu/publications/climate-impacts-and-vulnerability-2016/)

 


[1] See http://www.emdat.be/ online.

Rationale uncertainty

Not applicable.

Data sources

Metadata

Topics:

information.png Tags:
, ,
DPSIR: Impact
Typology: Descriptive indicator (Type A - What is happening to the environment and to humans?)
Indicator codes
  • CSI 042
  • CLIM 039
Temporal coverage:

Dates

Frequency of updates

Updates are scheduled once per year

EEA Contact Info

Wouter Vanneuville
Document Actions
European Environment Agency (EEA)
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Phone: +45 3336 7100