The precipitation pattern change risk captures the intensification of both heavy rains and prolonged dry spells. It is assessed with two indices, the maximum 5-day rainfall and the longest sequence of dry days, compared with the historical distribution: when either of the two worsens relative to the past, the risk grows.
Indicator. Rx5day = annual maximum of cumulative rainfall over 5 days (mm); CDD = maximum annual sequence of consecutive dry days (days), where dry day = precipitation < 1 mm.
Data. Variable daily precipitation (pr) from the Copernicus Climate Data Store (CDS), converted from kg m⁻² s⁻¹ to mm/day. Historical period 1850–1970, used for the distributions of Rx5day and CDD. The daily rainfall is the mean of the climate models: the values shown and the class are computed on this mean. Scenarios: SSP1-2.6 / SSP2-4.5 / SSP3-7.0 / SSP5-8.5.
Calculation.
(1) Daily precipitation is converted to mm/day.
(2) From the historical period Rx5day (maximum of the 5-day moving sum, per year) and CDD (maximum sequence of days with rain < 1 mm) are computed.
(3) The empirical percentiles P20, P40, P60, P80, P95 of the two historical distributions are computed.
(4) For each scenario and year Rx5day and CDD are computed and classified against the percentiles; the level is the worst of the two indices.
Thresholds → level A–F.
• F: Rx5day > P95 or CDD > P95
• E: > P80
• D: > P60
• C: > P40
• B: > P20
• A: otherwise.
The 20 / 40 / 60 / 80 / 95 percentiles are a xNatura choice without a published source.
From physical to impact. The physical level (A–F) is combined with the production process's sensitivity through the risk matrix (6 physical levels by 5 sensitivity bands) → impact level. The euro amount of this risk is the one described in the "Production damage" paragraph (Version 2026): the damage factor per class of Version 2025 is no longer used for this risk.
Production damage. Rain is counted for what it does to the work of the site rather than to the building: the value added lost is estimated, in euro per employee per year (multiplied by the site's employees). Basis: "xNatura estimate", because a regional estimate is applied to one site.
• Effect: Kotz, Levermann and Wenz 2022 measure, on 1,554 regions from 1979 to 2019, how the output of manufacturing and of services changes with the number of wet days (days with more than 1 mm of rain): one more wet day is about -0.07% of output in manufacturing and -0.09% in services, a little less where wet days are already many. Manufacturing coefficients for industry, mining, energy, water and construction, services coefficients for the other activities (an xNatura mapping); agriculture is not significant in the study and gets no loss.
• Climate: for each of ten climate models (the ISIMIP3b set), NASA NEX-GDDP-CMIP6 daily rain, cells of 0.25° (about 25 km), corrected on observations (Thrasher et al. 2022); change between the 20 years around the year and 1995-2014, then the mean of the models. The correction keeps each model's day-to-day sequence, so the wet days are often about half again as many as at weather stations: only the change within each model is used.
• The change is applied as a lasting change of the level of output, as Waidelich et al. 2024 do with the same functions. Where it rains less than in 1995-2014 the study implies a small gain, shown as 0.
• Euro: share lost × yearly value added per employed person of the country and sector of the site's production processes, as for heat stress and air quality (Eurostat in Europe, World Bank and ILO outside).
Sources.
• [Copernicus Climate Data Store (CDS)](Copernicus Climate Data Store (CDS))
• [ETCCDI Climate Change Indices](ETCCDI Climate Change Indices)
• [Climate Change 2021: The Physical Science Basis](Climate Change 2021: The Physical Science Basis)
• [Indices for monitoring changes in extremes based on daily temperature and precipitation data](Indices for monitoring changes in extremes based on daily temperature and precipitation data)
• [Kotz et al. 2022, The effect of rainfall changes on economic production](Kotz et al. 2022, The effect of rainfall changes on economic production)
• [Waidelich et al. 2024, Climate damage projections beyond annual temperature](Waidelich et al. 2024, Climate damage projections beyond annual temperature)
• [Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6](Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6)
• [Eurostat, national accounts by industry (nama_10_a64)](Eurostat, national accounts by industry (nama_10_a64))
• [World Bank, gross value added at basic prices](World Bank, gross value added at basic prices)
• [ILOSTAT, employment (ILO modelled estimates)](ILOSTAT, employment (ILO modelled estimates)).
Indicator. Rx5day = annual maximum of cumulative rainfall over 5 days (mm); CDD = maximum annual sequence of consecutive dry days (days), where dry day = precipitation < 1 mm.
Data. Variable daily precipitation (pr) from the Copernicus Climate Data Store (CDS), converted from kg m⁻² s⁻¹ to mm/day. Historical period 1850–1970, used for the distributions of Rx5day and CDD. The daily rainfall is the mean of the climate models: the values shown and the class are computed on this mean. Scenarios: SSP1-2.6 / SSP2-4.5 / SSP3-7.0 / SSP5-8.5.
Calculation.
(1) Daily precipitation is converted to mm/day.
(2) From the historical period Rx5day (maximum of the 5-day moving sum, per year) and CDD (maximum sequence of days with rain < 1 mm) are computed.
(3) The empirical percentiles P20, P40, P60, P80, P95 of the two historical distributions are computed.
(4) For each scenario and year Rx5day and CDD are computed and classified against the percentiles; the level is the worst of the two indices.
Thresholds → level A–F.
• F: Rx5day > P95 or CDD > P95
• E: > P80
• D: > P60
• C: > P40
• B: > P20
• A: otherwise.
The 20 / 40 / 60 / 80 / 95 percentiles are a xNatura choice without a published source.
From physical to impact. The physical level (A–F) is combined with the production process's sensitivity through the risk matrix (6 physical levels by 5 sensitivity bands) → impact level. The euro amount of this risk is the one described in the "Production damage" paragraph (Version 2026): the damage factor per class of Version 2025 is no longer used for this risk.
Production damage. Rain is counted for what it does to the work of the site rather than to the building: the value added lost is estimated, in euro per employee per year (multiplied by the site's employees). Basis: "xNatura estimate", because a regional estimate is applied to one site.
• Effect: Kotz, Levermann and Wenz 2022 measure, on 1,554 regions from 1979 to 2019, how the output of manufacturing and of services changes with the number of wet days (days with more than 1 mm of rain): one more wet day is about -0.07% of output in manufacturing and -0.09% in services, a little less where wet days are already many. Manufacturing coefficients for industry, mining, energy, water and construction, services coefficients for the other activities (an xNatura mapping); agriculture is not significant in the study and gets no loss.
• Climate: for each of ten climate models (the ISIMIP3b set), NASA NEX-GDDP-CMIP6 daily rain, cells of 0.25° (about 25 km), corrected on observations (Thrasher et al. 2022); change between the 20 years around the year and 1995-2014, then the mean of the models. The correction keeps each model's day-to-day sequence, so the wet days are often about half again as many as at weather stations: only the change within each model is used.
• The change is applied as a lasting change of the level of output, as Waidelich et al. 2024 do with the same functions. Where it rains less than in 1995-2014 the study implies a small gain, shown as 0.
• Euro: share lost × yearly value added per employed person of the country and sector of the site's production processes, as for heat stress and air quality (Eurostat in Europe, World Bank and ILO outside).
Sources.
• [Copernicus Climate Data Store (CDS)](Copernicus Climate Data Store (CDS))
• [ETCCDI Climate Change Indices](ETCCDI Climate Change Indices)
• [Climate Change 2021: The Physical Science Basis](Climate Change 2021: The Physical Science Basis)
• [Indices for monitoring changes in extremes based on daily temperature and precipitation data](Indices for monitoring changes in extremes based on daily temperature and precipitation data)
• [Kotz et al. 2022, The effect of rainfall changes on economic production](Kotz et al. 2022, The effect of rainfall changes on economic production)
• [Waidelich et al. 2024, Climate damage projections beyond annual temperature](Waidelich et al. 2024, Climate damage projections beyond annual temperature)
• [Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6](Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6)
• [Eurostat, national accounts by industry (nama_10_a64)](Eurostat, national accounts by industry (nama_10_a64))
• [World Bank, gross value added at basic prices](World Bank, gross value added at basic prices)
• [ILOSTAT, employment (ILO modelled estimates)](ILOSTAT, employment (ILO modelled estimates)).