The climate change risk measures the site's long-term warming and how much this increases overall exposure. It is estimated by comparing the annual mean temperature of each future year with that of a historical reference period: the more the anomaly grows relative to the past, the higher the risk.
Indicator. Annual mean temperature anomaly (°C) relative to the historical reference period.
Data. Variable "monthly mean of daily mean temperature" (mean near-surface temperature, 2 m, °C) from the Copernicus Climate Data Store (CDS); multi-model ensemble annual mean. Reference period: 1950–1970. Scenarios: SSP1-2.6 / SSP2-4.5 / SSP3-7.0 / SSP5-8.5. Observed temperature of the site: ERA5-Land (ECMWF reanalysis at about 9 km, Muñoz-Sabater et al. 2021), 1995–2014 mean, from the Open-Meteo archive. Where ERA5-Land has no land cell (small islands, open sea) ERA5 is used, the reanalysis it derives from (about 25 km).
Calculation.
(1) On the historical data 1950–1970 the mean of the ensemble annual means is computed → a single reference value (°C).
(2) For each scenario and future year the ensemble annual mean (°C) is taken.
(3) The anomaly = future value − reference value (°C) is computed.
(4) The anomaly is classified against ordered thresholds.
(5) The temperatures shown are corrected on the site's observed value (delta change, linear scaling: Teutschbein and Seibert 2012): model value + (ERA5-Land 1995–2014 mean at the site − model 1995–2014 mean). This is needed because the model cell, about 100 km wide, mixes the site with the land around it (at Mendrisio 8.5 °C from the models against 12.7 °C from ERA5-Land; the MeteoSwiss Stabio station measures 11.5 °C). The class does not change, because it is based on the rise over 1950–1970.
Thresholds → level A–F.
• anomaly < 0.5 °C → A
• 0.5–1.0 → B
• 1.0–1.5 → C
• 1.5–2.0 → D
• 2.0–2.5 → E
• ≥ 2.5 °C → F.
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. Version 2025 also turned the impact level into a value at risk with a damage factor per class, a xNatura estimate without a published source: for this risk that figure is no longer shown.
Energy cost (Version 2026). Warmer days change what the site spends on energy for cooling and heating: the extra yearly cost is estimated in euro (shown per employee and multiplied by the site's employees). Basis: "xNatura estimate", because national long-run responses are applied to one site.
• Effect: van Ruijven, De Cian and Sue Wing 2019 (estimates of De Cian and Sue Wing 2019) give, for industry, commerce and agriculture, in temperate and tropical climates, how electricity and gas demand changes per extra hot day (daily mean above 27.5 °C) and per extra cold day (below 12.5 °C); demand change = exp(effect per hot day × extra hot days + effect per cold day × extra cold days) − 1, as in the paper. Temperate or tropical from the site's Köppen-Geiger class (group A tropical), a site-level reading of the paper's country rule. Sectors from the paper's activity lists; energy industries, refining and transport have no estimate. Gas use of temperate industry is left out: the paper finds no stable relation for it.
• Beyond 2060 the demand change grows linearly from its 2060 value (the paper projects to 2040-2060).
• Days: hot and cold days with the daily mean taken as (maximum + minimum) / 2, as the paper does, from NASA NEX-GDDP-CMIP6 for each of ten climate models (the ISIMIP3b set): change between the 20 years around the year and 1995-2014, then the mean of the models.
• Energy: the site's yearly electricity and gas in kWh entered in Locate; if missing, the energy per person employed of the site's sector in Eurostat industry data, times the employees, where Eurostat has it.
• Price: Eurostat price for non-household consumers without VAT and recoverable taxes, in the band of the site's consumption; Switzerland electricity: ElCom median tariff of the category nearest to the site's consumption (medium voltage at 500 MWh, an xNatura choice). Without a price (gas in Switzerland, countries outside Eurostat) that fuel has no cost.
• A saving (fewer cold days, less heating) is shown as 0.
Sources.
• [Copernicus Climate Data Store (CDS)](Copernicus Climate Data Store (CDS))
• [Climate Change 2021: The Physical Science Basis](Climate Change 2021: The Physical Science Basis)
• [Climate Change 2022: Impacts, Adaptation and Vulnerability](Climate Change 2022: Impacts, Adaptation and Vulnerability)
• [Global Warming of 1.5 ºC](Global Warming of 1.5 ºC)
• [Allowable CO2 emissions based on regional and impact-related climate targets](Allowable CO2 emissions based on regional and impact-related climate targets)
• [Tipping elements in the Earth's climate system](Tipping elements in the Earth's climate system)
• [Teutschbein and Seibert 2012, Bias correction of regional climate model simulations](Teutschbein and Seibert 2012, Bias correction of regional climate model simulations)
• [Muñoz-Sabater et al. 2021, ERA5-Land](Muñoz-Sabater et al. 2021, ERA5-Land)
• [van Ruijven et al. 2019, Amplification of future energy demand growth due to climate change](van Ruijven et al. 2019, Amplification of future energy demand growth due to climate change)
• [Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6](Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6)
• [De Cian and Sue Wing 2019, Global Energy Consumption in a Warming Climate](De Cian and Sue Wing 2019, Global Energy Consumption in a Warming Climate)
• [Eurostat, energy consumption of industry by NACE (nrg_d_indq_n)](Eurostat, energy consumption of industry by NACE (nrg_d_indq_n))
• [Eurostat, electricity prices for non-household consumers (nrg_pc_205)](Eurostat, electricity prices for non-household consumers (nrg_pc_205))
• [Eurostat, gas prices for non-household consumers (nrg_pc_203)](Eurostat, gas prices for non-household consumers (nrg_pc_203))
• [ElCom, median electricity tariff for Switzerland (opendata.swiss)](ElCom, median electricity tariff for Switzerland (opendata.swiss)).
Indicator. Annual mean temperature anomaly (°C) relative to the historical reference period.
Data. Variable "monthly mean of daily mean temperature" (mean near-surface temperature, 2 m, °C) from the Copernicus Climate Data Store (CDS); multi-model ensemble annual mean. Reference period: 1950–1970. Scenarios: SSP1-2.6 / SSP2-4.5 / SSP3-7.0 / SSP5-8.5. Observed temperature of the site: ERA5-Land (ECMWF reanalysis at about 9 km, Muñoz-Sabater et al. 2021), 1995–2014 mean, from the Open-Meteo archive. Where ERA5-Land has no land cell (small islands, open sea) ERA5 is used, the reanalysis it derives from (about 25 km).
Calculation.
(1) On the historical data 1950–1970 the mean of the ensemble annual means is computed → a single reference value (°C).
(2) For each scenario and future year the ensemble annual mean (°C) is taken.
(3) The anomaly = future value − reference value (°C) is computed.
(4) The anomaly is classified against ordered thresholds.
(5) The temperatures shown are corrected on the site's observed value (delta change, linear scaling: Teutschbein and Seibert 2012): model value + (ERA5-Land 1995–2014 mean at the site − model 1995–2014 mean). This is needed because the model cell, about 100 km wide, mixes the site with the land around it (at Mendrisio 8.5 °C from the models against 12.7 °C from ERA5-Land; the MeteoSwiss Stabio station measures 11.5 °C). The class does not change, because it is based on the rise over 1950–1970.
Thresholds → level A–F.
• anomaly < 0.5 °C → A
• 0.5–1.0 → B
• 1.0–1.5 → C
• 1.5–2.0 → D
• 2.0–2.5 → E
• ≥ 2.5 °C → F.
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. Version 2025 also turned the impact level into a value at risk with a damage factor per class, a xNatura estimate without a published source: for this risk that figure is no longer shown.
Energy cost (Version 2026). Warmer days change what the site spends on energy for cooling and heating: the extra yearly cost is estimated in euro (shown per employee and multiplied by the site's employees). Basis: "xNatura estimate", because national long-run responses are applied to one site.
• Effect: van Ruijven, De Cian and Sue Wing 2019 (estimates of De Cian and Sue Wing 2019) give, for industry, commerce and agriculture, in temperate and tropical climates, how electricity and gas demand changes per extra hot day (daily mean above 27.5 °C) and per extra cold day (below 12.5 °C); demand change = exp(effect per hot day × extra hot days + effect per cold day × extra cold days) − 1, as in the paper. Temperate or tropical from the site's Köppen-Geiger class (group A tropical), a site-level reading of the paper's country rule. Sectors from the paper's activity lists; energy industries, refining and transport have no estimate. Gas use of temperate industry is left out: the paper finds no stable relation for it.
• Beyond 2060 the demand change grows linearly from its 2060 value (the paper projects to 2040-2060).
• Days: hot and cold days with the daily mean taken as (maximum + minimum) / 2, as the paper does, from NASA NEX-GDDP-CMIP6 for each of ten climate models (the ISIMIP3b set): change between the 20 years around the year and 1995-2014, then the mean of the models.
• Energy: the site's yearly electricity and gas in kWh entered in Locate; if missing, the energy per person employed of the site's sector in Eurostat industry data, times the employees, where Eurostat has it.
• Price: Eurostat price for non-household consumers without VAT and recoverable taxes, in the band of the site's consumption; Switzerland electricity: ElCom median tariff of the category nearest to the site's consumption (medium voltage at 500 MWh, an xNatura choice). Without a price (gas in Switzerland, countries outside Eurostat) that fuel has no cost.
• A saving (fewer cold days, less heating) is shown as 0.
Sources.
• [Copernicus Climate Data Store (CDS)](Copernicus Climate Data Store (CDS))
• [Climate Change 2021: The Physical Science Basis](Climate Change 2021: The Physical Science Basis)
• [Climate Change 2022: Impacts, Adaptation and Vulnerability](Climate Change 2022: Impacts, Adaptation and Vulnerability)
• [Global Warming of 1.5 ºC](Global Warming of 1.5 ºC)
• [Allowable CO2 emissions based on regional and impact-related climate targets](Allowable CO2 emissions based on regional and impact-related climate targets)
• [Tipping elements in the Earth's climate system](Tipping elements in the Earth's climate system)
• [Teutschbein and Seibert 2012, Bias correction of regional climate model simulations](Teutschbein and Seibert 2012, Bias correction of regional climate model simulations)
• [Muñoz-Sabater et al. 2021, ERA5-Land](Muñoz-Sabater et al. 2021, ERA5-Land)
• [van Ruijven et al. 2019, Amplification of future energy demand growth due to climate change](van Ruijven et al. 2019, Amplification of future energy demand growth due to climate change)
• [Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6](Thrasher et al. 2022, NASA Global Daily Downscaled Projections, CMIP6)
• [De Cian and Sue Wing 2019, Global Energy Consumption in a Warming Climate](De Cian and Sue Wing 2019, Global Energy Consumption in a Warming Climate)
• [Eurostat, energy consumption of industry by NACE (nrg_d_indq_n)](Eurostat, energy consumption of industry by NACE (nrg_d_indq_n))
• [Eurostat, electricity prices for non-household consumers (nrg_pc_205)](Eurostat, electricity prices for non-household consumers (nrg_pc_205))
• [Eurostat, gas prices for non-household consumers (nrg_pc_203)](Eurostat, gas prices for non-household consumers (nrg_pc_203))
• [ElCom, median electricity tariff for Switzerland (opendata.swiss)](ElCom, median electricity tariff for Switzerland (opendata.swiss)).