Europe's Weather Losses Keep Climbing
But a new loss normalization finds no trend after accounting for economic growth
“The reality is that as climate change continues, the pattern of more heat waves, more droughts, more heavy weather, and of course also more floods is going up. And with this type of events, you know, continuing ever more frequently, you will see more damage. . . the ever-larger economic damage that climate change, unfortunately, is bringing to our societies.”
— Wopke Hoekstra
European Commissioner for Climate, Net Zero and Clean Growth
A disaster loss normalization estimates what direct economic losses related to an extreme event of the past would occur if that same event happened under today’s economic conditions — today’s infrastructure, property, and wealth. Today, I present a new normalization of Europe’s weather and climate catastrophe losses for 1990 to 2024, updating an analysis I first shared here at THB three years ago, covering 1995 to 2019.
The European Environment Agency (EEA) has since updated and reorganized its underlying catastrophe loss dataset. That increases the time series by ten years, includes the catastrophic 2021 floods in Germany and Belgium, and provides a broader country grouping (the full EEA-38, which adds the Western Balkans).1
Countries included in the analysis are shown below.
Here is the top-line conclusion:
Once you account for economic growth, the normalized cost of weather and climate extremes in Europe has not increased over 1990–2024. The overall trend is flat.
This post shares the data, methods, and the significance of the analysis. At the bottom of the post is a methods appendix, a bibliography, and for THB paid subscribers an Excel spreadsheet with all sources, data, and calculations.2
Inflation-adjusted losses are increasing
Economic losses from weather- and climate-related events across the 38 EEA countries over 1990–2024 (in inflation-adjusted 2024 Euros) have increased, as shown in the figure below.
The time series shows a sharp increase over more than three decades. Taken at face value, a casual observer would conclude European disasters are becoming dramatically more expensive, with a growing impact on the continent’s economy.
That conclusion — as expressed in the quote at the top of this post — would be wrong.
Normalization: accounting for economic growth
Over these 35 years the combined economy of the 38 countries more than doubled in real, inflation-adjusted terms — accompanied by an increase in buildings, infrastructure, and wealth, and therefore far more stuff exposed to any storm or flood.
All else equal, the euro cost of a fixed set of physical events must increase simply because there is more wealth exposed to extreme events.
A normalization corrects for changing exposure and vulnerability. The simplest version scales each year’s loss by the ratio of a base year’s economic output (GDP, in this case 2024) to that year’s output:
Normalized loss in year t = Reported loss in year t × ( GDP in 2024 ÷ GDP in year t )
There are in the literature far more sophisticated methodological approaches to normalization. However, the United Nations Sendai Framework on Disaster Risk Reduction has adopted losses as a percent of GDP as an official indicator of progress in disaster risk reduction.
The figure below shows a GDP-based normalization of the time series shown above, adjusted to a constant 2024 level — the dramatic upwards trend in the time series disappears.
The early 1990s — modest in raw terms — become some of the most damaging years on record once exposure is held constant. The 1999 windstorms Lothar and Martin, the 2002 central-European floods, and the 1990 storm season rival or exceed the recent large-loss years.
At ~0.25% of GDP, 2021 was the most economically significant loss year since 2002.. However, normalized losses in 1990 and 1999 were even greater.
A robustness check: does the method matter?
Above, I normalized the aggregate continental losses based on aggregate GDP — scaling Europe’s total losses by Europe’s total GDP growth. But these countries did not grow at the same rate. Poland, Romania, and the Baltics expanded several times faster than Germany or France over this period. If a disproportionate share of early losses fell in fast-growing economies, normalizing the bloc as a whole could distort the picture.
As a robustness check I also normalize losses reported for each country by its own GDP growth and then sum the results. A comparison of the two methods is shown below, and there is very little difference.
Variation within Europe
There are some interesting details at the country level.
First, in aggregated terms, normalized losses are heavily concentrated in the largest economies. Germany, France, Italy, and Spain together account for ~58% of all normalized European losses since 1990; the top eight account for ~80%.
The concentration of normalized losses in a small number of countries largely reflects economic size — big economies post big absolute losses because they are big, not rocket science.
More interesting is the overall economic burden: how large are each country’s losses relative to its own economy? The answer is shown below.
In the context of individual country’s GDP, it is the smaller, more exposed economies that bear the heaviest relative load. Slovenia tops the list at ~1.0% of GDP over 1990-2024 — driven heavily by its catastrophic 2023 floods — followed by Bosnia and Herzegovina and Serbia, all well above the ~0.12% EEA average.
In contrast, Germany, France, Italy, and Spain, which dominate the pie, sit in the middle of the relative ranking.
Why normalization matters
Normalization of Europe’s weather and climate losses helps to answer a narrow question:
Are weather and climate extracting a growing economic toll from Europe over time, once accounting for the fact that economies are growing, resulting in increased exposure to loss?
The evidence presented above shows that the answer is no — after normalization by GDP the resulting time series has no trend. That means that direct economic losses from weather and climate events have scaled proportionately with the region’s growing economy.
It is important to emphasize that this result says nothing about changes in climate. To detect changes in climate variables, always look at weather and climate data — not economic data.
The finding of no trend in normalized losses across the EEA-38 is fully consistent with peer-reviewed literature (see the bibliography below) and with what the IPCC concludes about the difficulty of detecting (and attributing) long-term trends in most categories of extreme weather.
Regardless how climate varies and changes, future losses from extremes will be largely a function of where and how we build, and policies put into place in recognition of the ever-present risks of extreme events.
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BIBLIOGRAPHY
Literature review
Pielke, R. (2021). Economic ‘normalisation’ of disaster losses 1998–2020: a literature review and assessment. Environmental Hazards, 20(2), 93–111. https://doi.org/10.1080/17477891.2020.1800440
Surveys 54 peer-reviewed normalization studies published 1998–2020 across regions, countries, and hazard types. Concludes there is little evidence that any part of the documented increase in global economic losses on climate timescales is attributable to human-caused climate change, with increases instead explained by growth in exposure, wealth, and development. Prepared as a contribution to the IPCC AR6 assessment of this literature (however, it was not cited in the AR6, nor were almost all of the studies in the review).
European normalization studies
Barredo, J. I. (2009). Normalised flood losses in Europe: 1970–2006. Natural Hazards and Earth System Sciences, 9(1), 97–104. https://doi.org/10.5194/nhess-9-97-2009
The foundational normalization of European flood losses. Finds no significant trend in normalized flood losses across Europe once losses are adjusted for changes in population, wealth, and inflation. The methodology underpins the European Environment Agency’s normalized flood-loss indicator.
Barredo, J. I. (2010). No upward trend in normalised windstorm losses in Europe: 1970–2008. Natural Hazards and Earth System Sciences, 10(1), 97–104. https://doi.org/10.5194/nhess-10-97-2010
The companion windstorm study. Finds no upward trend in normalized European windstorm losses over 1970–2008, consistent with the absence of a robust trend in European storminess.
Paprotny, D., Sebastian, A., Morales-Nápoles, O., & Jonkman, S. N. (2018). Trends in flood losses in Europe over the past 150 years. Nature Communications, 9, 1985. https://doi.org/10.1038/s41467-018-04253-1
The most temporally and spatially comprehensive European flood-loss normalization to date, covering 37 European countries back to 1870 using a gridded reconstruction of flood exposure (the HANZE database). After correcting for exposure change, finds increases in inundated area and persons affected since 1870 but a substantial decline in flood fatalities and, in recent decades, in financial losses per year — while cautioning that underreporting of smaller floods affects observed trends.
Formetta, G., & Feyen, L. (2019). Empirical evidence of declining global vulnerability to climate-related hazards. Global Environmental Change, 57, 101920. https://doi.org/10.1016/j.gloenvcha.2019.05.004
Though global in scope, this widely-cited vulnerability analysis is a standard reference in the European normalization literature, documenting declining human and economic vulnerability to climate-related hazards as income rises — the mechanism that offsets rising exposure.
Spinoni, J., Formetta, G., Mentaschi, L., Forzieri, G., & Feyen, L. (2020). Global warming and windstorm impacts in the EU: JRC PESETA IV project – Task 13. Publications Office of the European Union, Luxembourg. https://doi.org/10.2760/039014
EU-wide assessment of windstorm impacts. Reports absolute losses highest in Germany, France, Italy, and the UK, but losses relative to GDP roughly double the EU average in Bulgaria, Estonia, and elevated in the Baltics and Slovenia — the same relative-burden inversion seen when losses are scaled to national economies. Notes no robust trend in European windstorms.
Barredo, J. I., Saurí, D., & Llasat, M. C. (2012). Assessing trends in insured losses from floods in Spain 1971–2008. Natural Hazards and Earth System Sciences, 12(5), 1723–1729. https://doi.org/10.5194/nhess-12-1723-2012
Normalizes insured flood losses for Spain and finds no upward trend once socioeconomic change is accounted for.
Underlying exposure and loss databases
Paprotny, D., Morales-Nápoles, O., & Jonkman, S. N. (2018). HANZE: a pan-European database of exposure to natural hazards and damaging historical floods since 1870. Earth System Science Data, 10(1), 565–581. https://doi.org/10.5194/essd-10-565-2018
The Historical Analysis of Natural HaZards in Europe (HANZE) exposure database, providing the gridded population, asset, and land-use reconstruction that enables exposure-based flood normalization across Europe.
Paprotny, D., et al. (2024). HANZE v2.1: an improved database of flood impacts in Europe from 1870 to 2020. Earth System Science Data, 16, 5145–5170. https://doi.org/10.5194/essd-16-5145-2024
The updated HANZE flood-impact database covering 42 European countries and 2,521 events (1870–2020), compiled from more than 800 sources. Documents the substantial effect of impact-data completeness on estimated normalized-loss trends.
Daniell, J. E., Khazai, B., Wenzel, F., & Vervaeck, A. (2011). The CATDAT damaging earthquakes database. Natural Hazards and Earth System Sciences, 11(8), 2235–2251. https://doi.org/10.5194/nhess-11-2235-2011
Describes CATDAT (Risklayer GmbH), the catastrophe-loss database underlying the European Environment Agency’s economic-loss dashboards used in this analysis. Originally developed for earthquakes, CATDAT now spans weather- and climate-related hazards.
THB on normalization
Part 3: Normalized Hurricane Losses in the United States, 1900 to 2021
Part 4: How would we know if disasters are becoming more costly due to climate change?
An Excel spreadsheet with all sources and data used in this post is available below for THB paid subscribers.
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