Contributors: Christos Giannakopoulos (NATIONAL OBSERVATORY OF ATHENS (NOA)), Anna Karali (NATIONAL OBSERVATORY OF ATHENS (NOA))
1. Introduction
The current document contains a description of the dataset that has been developed with respect to fire danger. In the framework of C3S European Tourism project, climate projections of fire danger are available for the whole European domain. The document describes the modeling workflow i.e. the input data, fire danger model used and output fire danger indicators.
2. Dataset overview
This dataset provides gridded fire danger future projections for the European region. In order to assess fire danger, the Canadian Fire Weather Index System (FWI) is utilized. FWI is a meteorologically based index, used worldwide to estimate fire danger in a generalized fuel type (mature pine stands). It consists of different components that assess the responses of moisture to atmospheric forcing at different soil depths and then combine these in order to derive fire behavior indices in terms of ease of spread and intensity. For the calculation of the index, daily noon values of air temperature, relative humidity, wind speed and 24-h accumulated precipitation are required.
As far as future projections of FWI are concerned, the dataset has been developed using 3-hourly climatic output from state of–the-art GCM/RCM pairs, developed within the EURO-CORDEX initiative. The future period simulations of the models are based on the Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5. The dataset consists of daily FWI values (for the period 1970-2098), as well as pre-calculated FWI indices, in particular, the average FWI values for the period June-September and three, threshold specific indices, describing the number of days with moderate, high and very high fire danger conditions following the European Forest Fire Information System (EFFIS) classification. The historical part of the simulations (1970-2005) are included to provide a reference for the future FWI projections and are necessary to interpret trends in these projections.
3. Description of the climate modeling chain
3.1. Input data, pre-processing and climate models
The meteorological inputs of the FWI System are daily noon values of air temperature, relative humidity, 10m wind speed and precipitation during the previous 24 hours.
For the calculation of the index, 3-hourly climatic output from state-of-the-art RCM/GCM pairs, developed within the EURO-CORDEX (Jacob et al., 2014) initiative, have been utilized.
EURO-CORDEX is the European branch of the CORDEX program. The CORDEX (Coordinated Regional Climate Downscaling Experiment initiative) is sponsored by the World Climate Research Program and is focused on organizing an integrated international framework to produce regional climate change projections for the entire land region, worldwide.
At the time of the project's simulations only the RCA4 RCM of the Swedish Meteorological and Hydrological Institute (SMHI) (Stranberg et al., 2014), driven by different GCMs, had 3-hourly climatic output available. The future period simulations of the models are based on three Representative Concentration Pathways (RCPs): 4.5, 8.5 and RCP2.6, where available.
The GCM/RCM pairs and the climatic experiments that have been implemented in the framework of C3S European Tourism project are presented in Table 1:
Table 1: GCM/RCM pairs and climatic experiments used in the framework of the project
GCM/RCM pairs | Experiments |
ICHEC-EC-EARTH/RCA4 | Historical RCP2.6 RCP4.5 RCP8.5 |
MPI-M-MPI-ESM-LR/RCA4 | Historical RCP2.6 RCP4.5 RCP8.5 |
MOHC-HadGEM2-ES/RCA4 | Historical RCP2.6 RCP4.5 RCP8.5 |
CNRM-CERFACS-CNRM-CM5/RCA4 | Historical RCP4.5 RCP8.5 |
IPSL-IPSL-CM5A-MR/RCA4 | Historical RCP4.5 RCP8.5 |
NCC-NorESM1-M/RCA4 | Historical RCP8.5 |
The ECVs that have been downloaded for FWI calculation are:
Pr: precipitation (daily values)
Tas: surface temperature (3-hourly instantaneous values)
Hurs: near surface relative humidity (3-hourly instantaneous values)
sfcWind: near surface wind speed (3-hourly instantaneous values)
These ECVs were downloaded directly from the climate data node of the Earth System Grid Federation (ESGF) data centre of the German Climate Computer Centre (DKRZ) (https://esgf-data.dkrz.de/search/cordex-dkrz) for the European domain (EUR-11), as they were not available in the CDS.
The pre-processing of the data encompasses the selection of the noon data required for the calculation of FWI for each grid point, throughout the European domain. After several tests the 12 UTC model output was considered to be the most suitable and was selected as input in FWI model.
3.2. Impact model
The FWI system provides numerical, non-dimensional ratings of relative fire potential for a generalized fuel type (mature pine stands), based exclusively on weather observations. FWI is part of the Canadian Forest Fire Danger Rating System, established in Canada in 1971 (van Wagner 1987).
It consists of different components that assess the responses of moisture to atmospheric forcings at different soil depths, then combining these in order to derive fire behavior indices in terms of ease of spread and intensity.
The first three primary sub-indices are fuel moisture codes and are numerical ratings of the moisture content of litter and other fine fuels (FFMC), the average moisture content of loosely compacted organic layers of moderate depth (DMC) and the average moisture content of deep, compact organic layers (DC). The two intermediate sub-indices (ISI, BUI) are fire behaviour indices. The Initial Spread Index (ISI) is a numerical rating of the expected fire rate of spread.
It combines the effect of wind and FFMC on rate of spread without the influence of variable quantities of fuel. The Buildup Index (BUI) is a numerical rating of the total amount of fuel available for combustion that combines the DMC and the DC. The resulting index is the Fire Weather Index (FWI) which combines ISI and BUI. FWI represents the frontal fire intensity and is used to estimate the difficulty of fire control. FWI structure is presented in Figure 1. 
Figure 1: Fire Weather Index (FWI) structure.
Furthermore, since 2007, FWI has been adopted at the EU level and used in a harmonized way throughout Europe by the European Forest Fire Information System (EFFIS) of the Copernicus Emergency Management Service (EMS). The FWI classes used by EFFIS, are presented in Table 2.
Table 2: FWI classes used by EFFIS
Fire Danger Classes | FWI ranges (upper bound excluded) |
Very low | < 5.2 |
Low | 5.2 - 11.2 |
Moderate | 11.2 - 21.3 |
High | 21.3 - 38.0 |
Very high | 38.0 - 50.0 |
Extreme | >= 50.0 |
The Global ECMWF Fire Forecasting (GEFF) model, was modified based on the original FWI code (van Wagner, 1987) and was used for the calculation of daily FWI values. The code has been converted from FORTRAN programming language to Python, in order to be in line with the official language of the CDS Toolbox. Moreover, during the conversion, extensive checking and some amendments to the GEFF code took place, according to the original code (van Wagner and Pickett, 1985).
3.3. Fire danger indicators
The C3S European Tourism Sectoral Climate Impact Indicators (SCIIs) have been derived from the daily outputs of the FWI model. Mean fire season FWI have been calculated, i.e. mean FWI for the months from June to September, when most of the forest fires occur, as well as the number of days per year with moderate/high/very high fire danger according to EFFIS homogenous classification for the European domain. The values in the middle of each EFFIS class (i.e. 15, 30, 45) were selected as thresholds for moderate/high/very high fire danger class. FWI is calculated using multi-model combinations, i.e. the multi-model mean is the average FWI calculated from all the GCM projections. The best case and worse case scenarios are the calculated FWI defined as the lowest and highest FWI values respectively of all the projections at each grid point.
3.3.1. Product specifications
Table 3: Description of the variables available in the dataset.
Name | Units | Description |
Daily fire weather index | Count | The fire weather index values at a daily temporal resolution for the selected year. The higher the index value, the more favourable the meteorological conditions to trigger a wildfire are. |
Seasonal fire weather index | Count | The mean fire weather index value over the European fire season (June-September). This is calculated as the sum of the daily fire weather index over the European fire season divided by the total number of days within this date range. |
Number of days with moderate fire danger | Number of days | The number of days per year with a daily fire weather index greater than 15 based upon the European Forest Fire Information System (EFFIS) classification. |
Number of days with high fire danger | Number of days | The number of days per year with a daily fire weather index greater than 30 based upon the European Forest Fire Information System (EFFIS) classification. |
Number of days with very high fire danger | Number of days | The number of days per year with a daily fire weather index greater than 45 based upon the European Forest Fire Information System (EFFIS) classification. |
4. References
Bedia, J., Golding, N., Casanueva , A., Iturbide, M., Buontempo, C., Gurierez, J.M., 2018: Seasonal predictions of Fire Weather Index: paving the way for their operational applicability in Mediterranean Europe, Climate Services 9, 101-110.
Mason, S.J., and N.E. Graham, 1999: Conditional probabilities, relative operating characteristics, and relative operating levels, Wea. Forecasting, 14, 713–725.
Jacob, D. et al., 2014: EURO-CORDEX: new high-resolution climate change projections for European impact research, Regional Environmental Change, 14(2), 563-578.
Strandberg, G., Bärring, A., Hansson, U., Jansson, C., Jones, C., Kjellström, E., 2014: CORDEX scenarios for Europe from the Rossby Centre regional climate model RCA4 Reports Meteorology and Climatology, 116, SMHI, SE-60176 Norrköping, Sverige
Van Wagner, C. E.,1987: Development and structure of a Canadian forest fire weather index system, Forestry Tech. Rep. 35, Canadian Forestry Service, Ottawa.
Van Wagner, C.E. and Pickett, T.L., 1985: Equations and FORTRAN Program for the Canadian Forest Fire Weather Index System, Forestry Tech. Rep. 33, Canadian Forestry Service, Ottawa.
5. Related articles
copernicus.eu copernicus.eu ecmwf.int
