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HEAT
MODEL

You will find on this page all the information relating to the constitution of the model for the "Heat" hazard for the analyzes carried out on Bat-ADAPT:  

Modèle EU Chaleurs
model EU heat

HEAT HAZARD

The model for analyzing climate exposure to the “Heat” hazard in Europe is based on 4 climate indicators:

  • Number of days with a temperature above 35°C

  • Change in maximum temperatures (°C)

  • Change in maximum maximum temperatures (°C)

  • Number of cooling degree days

The combination of this information makes it possible to assess the climatic exposure of an area, compared to the climatic exposure in the rest of Europe.

EU TX35
EU TX
EU TXx
climate indices heat EU
EU TX35 anglais
EU TX anglais
EU TXx anglais

Raw climate exposure indicators

Number of days with a temperature above 35°C

Definition of the indicator: Number of days in the year when the maximum daily temperature is above 35°C at at least one time of the day. 

Indicator ID: EU_TX35

Mesh: ~150km

Source :IPCC Interactive Atlas

Data processing: The climate data was downloaded in NetCDF format from the IPCC's interactive atlas, for the 3 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) and the 3 time horizons retained (short, medium and long term), i.e. 9 data sets. Then, cartographic processing via the QGIS software allowed the transition from point data to data covering the whole of Europe. A legend was applied in view of the minimums and maximums existing on all the datasets.   

Scope: Europe

 

Change in maximum temperatures (°C)

Definition of the indicator: The annual maximum temperature is the average of the maximum daily temperatures over the year. This indicator shows the magnitude of the change from normal.

Indicator ID: EU_TX

Mesh: ~150km

Source :IPCC Interactive Atlas

Data processing: The climate data was downloaded in NetCDF format from the IPCC's interactive atlas, for the 3 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) and the 3 time horizons retained (short, medium and long term), i.e. 9 data sets.  Then, cartographic processing using the QGIS software enabled the transition from point data to data covering the whole of Europe. A legend was applied in view of the minimums and maximums existing on all the datasets.   

Scope: Europe

 

Change in maximum maximum temperatures (°C)

Definition of the indicator: The maximum of the maximum temperatures is the maximum over the year of all the maximum daily temperatures. This indicator shows the magnitude of the change from normal.

Indicator ID: EU_TXx

Mesh: ~150km

Source: IPCC Interactive Atlas

Data processing: The climate data was downloaded in NetCDF format from the IPCC's interactive atlas, for the 3 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) and the 3 time horizons retained (short, medium and long term), i.e. 9 data sets. Then, cartographic processing via the QGIS software allowed the transition from point data to data covering the whole of Europe. A legend was applied in view of the minimums and maximums existing on all the datasets.   

Scope: Europe

Number of cooling degree days

Definition of the indicator: The number of cooling degree days is a measure of the cooling requirement over the year. It is calculated in reference to a threshold (22°C in IPCC statistics), and therefore depends on the excess temperature over this threshold, where cooling is needed. If the average temperature of a day is under or equal to this threshold, the number of degree days over the day is zero. Otherwise, it is equal to the difference between the threshold and the average temperature of the day.

Indicator ID: EU_CD

Mesh: ~150km

Source: IPCC Interactive Atlas

Data processing: The climate data was downloaded in NetCDF format from the IPCC's interactive atlas, for the 3 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5) and the 3 time horizons retained (short, medium and long term), i.e. 9 data sets. Then, cartographic processing via the QGIS software allowed the transition from point data to data covering the whole of Europe. A legend was applied in view of the minimums and maximums existing on all the datasets.   

Scope: Europe

EU_cd_fr
EU_cd_eng
Synthèse exposition EU
Expo synthetis heat EU

In order to obtain a single exposure index revealing the climatic risk situation of a building in an area, the previous indicators have been combined under the following formula:

 

 

 

This formula accounts for the overriding importance of the number of days with a temperature above 35 degrees and the general increase in maximum temperatures for buildings

It puts the risk in a specific location into perspective in relation to the risk existing in the whole of Europe.

These are therefore compared risk ratios, weighted according to their importance, added accordingly, then normalized, to obtain an indicator varying from 0 to 100% with 0% being the minimum risk encountered in Europe from 2020 to 2100 for the 3 scenarios, and 100% the maximum risk, over this same period, for the 3 scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5).

Wix_images_EU_CD.jpg
Fiabilité expo EU
expo reliability heat EU

The exposure reliability index is assigned as follows:

5/5 Models used in the IPCC report empirically verified

4/5 Models used in the IPCC report

3/5 Other models - Very reliable

2/5 Other models - Moderately reliable

1/5 Other models - Unreliable

Modèle FR Chaleurs
model FR Heat

HEAT HAZARD

The “Heat” hazard climate exposure analysis model in France is based on 3 climate indicators and 2 territorial indicators:

  • Number of days with a temperature above 35°C

  • Number of days of heat waves

  • Number of abnormally hot nights

  • UHI: Additional degrees caused by the urban heat island

  • Noise pollution: Day-evening-night noise level

The combination of this information makes it possible to assess the climatic exposure of an area, compared to the climatic exposure in the rest of France.

FR TX35
FR TXHWD
FR TNHT
climat indices heat FR
TX35 fr anglai
txhwd anglais
tnht anglais

Raw climate exposure indicators

Number of days with a temperature above 35°C

Definition of the indicator: Number of days in the year when the maximum daily temperature is above 35°C at at least one time of the day. 

Indicator ID: FR_TX35

Mesh: ~8km (Safran grid)

Source :DRIAS - Meteo France

Data processing: The climate data was uploaded in CSV format to the DRIAS command space, for the 3 scenarios (RCP2.6, RCP4.5, RCP8.5) and the 5 time horizons retained (2020, 2030, 2050, 2070 and 2090), i.e. 15 data sets. Statistical processing was done to smooth the climatic variability. This involves realizing, for each time horizon chosen, the median over 20 years (10 years before and 10 after) of the climate indicator. Cartographic processing via the QGIS software allowed the transition from point data to data covering the whole of France. A legend was applied in view of the minimums and maximums existing on all the datasets.   

Scope: Metropolitan France

 

Number of days of heat waves

Definition of the indicator: Number of days when the maximum daily temperature is more than 5°C higher than normal for at least 5 consecutive days.

Indicator ID: FR_TXHWD

Mesh: ~8km (Safran grid)

Source :DRIAS - Meteo France

Data processing: The climate data was uploaded in CSV format to the DRIAS command space, for the 3 scenarios (RCP2.6, RCP4.5, RCP8.5) and the 5 time horizons retained (2020, 2030, 2050, 2070 and 2090), i.e. 15 data sets. Statistical processing was done to smooth the climatic variability. This involves realizing, for each time horizon chosen, the median over 20 years (10 years before and 10 after) of the climate indicator. Cartographic processing via the QGIS software allowed the transition from point data to data covering the whole of France. A legend was applied in view of the minimums and maximums existing on all the datasets.   

Scope: Metropolitan France

 

Number of abnormally hot nights

Definition of the indicator: Number of days when the minimum daily temperature is more than 5°C higher than normal.

Indicator identifier: FR_TNHT

Mesh: ~8km (Safran grid)

Source :DRIAS - Meteo France

Data processing: The climate data was uploaded in CSV format to the DRIAS command space, for the 3 scenarios (RCP2.6, RCP4.5, RCP8.5) and the 5 time horizons retained (2020, 2030, 2050, 2070 and 2090), i.e. 15 data sets. Statistical processing was done to smooth the climatic variability. This involves realizing, for each time horizon chosen, the median over 20 years (10 years before and 10 after) of the climate indicator. Cartographic processing via the QGIS software allowed the transition from point data to data covering the whole of France. A legend was applied in view of the minimums and maximums existing on all the datasets.   

Scope: Metropolitan France

territorial indicators heat FR
ICU anglais
ICU
Pollution sonre
Noise pollution
expo synthetis heat FR

Raw territorial exposure indicators

UHI: Additional degrees caused by the urban heat island

Definition of the indicator: Effect of the city on the night temperature during a summer situation conducive to a strong urban heat island effect.

Indicator ID: ICU

Mesh: 250m

Source: SWEETIE - CNRM

Data processing: The icu data were retrieved via the MAPUCE project site. Two data sets were used corresponding to two different summer climate models. Cartographic processing made it possible to retain the maximum of the two models for each geographical coordinate studied.

Scope: 42 French cities (more informationhere

Noise pollution: Day-evening-night noise level

Definition of the indicator:  The day-evening-night noise level indicator, named Lden (for Level day-evening-night), represents the weighted average noise level during during the day by giving a greater weight to the noise produced in the evening and during the night.

Indicator ID: LDEN

Mesh: Specific to each noise level

Source: Noise ParifLe Havre MetropoleMontpellier Metropole

Data processing: Only the LDEN indicators and taking into account all sources of noise were retained. Once the 3 maps were uploaded to the metropolitan sites, an interval of noise levels adapted to these 3 data sets was adopted.

Scope: Paris, Le Havre, Montpellier.

In order to obtain a single exposure index revealing the climatic risk situation of a building in an area, the previous indicators have been combined under the following formula:

Synthèse exposition FR
Coef france.jpg

This formula accounts for the equal importance of the 3 climatic indicators selected for the building. 

It puts into perspective the climatic risk in a specific location compared to the risk existing in the whole of France, as well as the aggravation of this risk in view of territorial indicators (ICU and noise pollution) coming to specify the exposure in a given place.

These are therefore compared risk ratios, weighted according to their importance, added accordingly, then normalized, to obtain an indicator varying from 0 to 100% with 0% being the minimum risk encountered in France from 2020 to 2100 for 3 scenarios, and 100% the maximum risk, over this same period, for the 3 scenarios. This risk is then multiplied by a coefficient varying between 1 and 2.2 depending on the intensity of the ICU.

Fiabilité expo FR
expo reliability heat FR

The exposure reliability index is assigned as follows:

5/5 Models used in the IPCC report empirically verified
4/5 Models used in the IPCC report
3/5 Other models - Very reliable
2/5 Other models - Moderately reliable
1/5 Other models - Unreliable

Modèle vulnérabilité chaleurs
vulne model heat

HEAT HAZARD

In order to calculate the vulnerability of buildings to the “Heat” hazard, a certain amount of information is necessary. In order to collect them, a form is available to complete the characteristics of your project.

Three characteristics are ESSENTIAL for the calculation:

  • The useful gross area

  • The number of levels above the basement

  • Window to wall ratio

If no information is passed, the vulnerability defaults to 100%, with zero reliability. 

Matrice vulné chaleurs
Vulne matrix heat

The building vulnerability matrix for the “Heat” hazard is available here for download in Excel format. This allows you to know the intermediate steps of the calculations performed in R4RE. 

The vulnerability ranges between 0% and 100%. The greater the vulnerability, the more the building is subject to adaptation.

fiabilité vulnérabilité
vulne reliability heat

The vulnerability reliability index is calculated from the number of questions answered compared to the total number of questions. It varies from 0 to 5.

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