Spatiotemporal analysis of the FWI over Europe and North Africa: Historical trends and climate projections under RCP4.5 and RCP8.5

Abstract

Wildfires represent an escalating environmental threat across Europe and North Africa, increasingly exacerbated by climate-driven shifts in temperature, precipitation, and drought patterns. However, there is still limited large-scale, methodologically consistent research that simultaneously assesses historical patterns and future projections of fire danger across these regions, particularly in terms of both frequency and duration of risk under different climate scenarios. This study addresses this gap by providing a high-resolution, spatiotemporal assessment of fire weather conditions, with the aim of offering critical insights to support climate-adaptive fire management strategies, extended preparedness frameworks, and the integration of future fire weather projections into land-use and risk governance policies. To achieve this, we investigate historical (1979-2021) and projected (2000-2098) trends in fire danger using the Canadian Fire Weather Index (FWI), based on ERA5 reanalysis data and outputs from five Global Climate Models (GCMs) under RCP4.5 and RCP8.5 scenarios. Over 50,000 land grid cells were analyzed to assess the frequency and duration of six FWI danger classes. Different metrics were used to quantify the agreement between historical reanalysis data and GCM outputs, while the Seasonal Kendall (SK) test was applied to detect trends. Results reveal a substantial decline in the duration of the very low FWI class, from 36 to 23 months, and significant increases in both the duration and frequency of the extreme FWI class, reaching up to 6.38 months and 14.42% under the RCP8.5 scenario. Correlation coefficients exceed 0.8 across much of Southern Europe and North Africa, indicating strong temporal agreement. Trend analyses reveal statistically significant increases in fire danger across southern latitudes, while Northern Europe shows mixed or decreasing trends. These findings project a dramatic intensification and expansion of fire-prone conditions, particularly under high-emission scenarios.

Keywords

Climate change / Fire weather index / Global climate models / Trend analysis

CRediT authorship contribution statement

Fabio Di Nunno: Writing - original draft, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Francesco Granata: Writing - original draft, Visualization, Supervision, Methodology, Investigation, Data curation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.gsf.2025.102178.

References

[1] Abatzoglou, J.T., Williams, A.P., 2016. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl. Acad. Sci. U.S.A. 113 (42), 11770-11775. https://doi.org/10.1073/pnas.1607171113.

[2] Abatzoglou, J.T., Williams, A.P., Barbero, R., 2019. Global emergence of anthropogenic climate change in fire weather indices. Geophys. Res. Lett. 46 (1), 326-336.

[3] Aparício, B.A., Santos, J.A., Freitas, T.R., Sá A.C.L., Pereira, J.M.C., Fernandes, P.M., 2022. Unravelling the effect of climate change on fire danger and fire behaviour in the transboundary biosphere reserve of Meseta Ibérica (Portugal-Spain). Clim. Change 173, 5. https://doi.org/10.1007/s10584-022-03399-8.

[4] Achugbu, I.C., Chen, L., Hu, Q., Muñoz-Arriola, F., 2025. Evaluating the historical performance and future change in extreme precipitation indices over the Missouri river basin based on NA-CORDEX multimodel ensemble. Atmosphere 16, 579. https://doi.org/10.3390/atmos16050579.

[5] Avcıog˘lu, A., Akbas ¸ A., Görüm, T., Yetemen, Ö., 2025. The compound effect of topography, weather, and fuel type on the spread and severity of the largest wildfire in NW of Turkey. Nat. Hazards 121, 3219-3237. https://doi.org/10.1007/s11069-024-06885-7.

[6] Bedia, J., Herrera, S., Martín, D.S., Koutsias, N., Gutiérrez, J.M., 2013. Robust projections of fire weather index in the Mediterranean using statistical downscaling. Clim. Change 120, 229-247. https://doi.org/10.1007/s10584-013-0787-3.

[7] Bedia, J., Golding, N., Casanueva, A., Iturbide, M., Buontempo, C., Gutiérrez, J.M., 2018. Seasonal predictions of fire weather index: Paving the way for their operational applicability in Mediterranean Europe. Clim. Serv. 9, 101-110. https://doi.org/10.1016/j.cliser.2017.04.001.

[8] Berio Fortini, L., Kaiser, L.R., Frazier, A.G., Giambelluca, T.W., 2023. Examining current bias and future projection consistency of globally downscaled climate projections commonly used in climate impact studies. Clim. Change 176, 169. https://doi.org/10.1007/s10584-023-03623-z.

[9] Caesar, J., Palin, E., Liddicoat, S., Lowe, J., Burke, E., Pardaens, A., Sanderson, M., Kahana, R., 2013. Response of the HadGEM2 earth system model to future greenhouse gas emissions pathways to the year 2300. J. Climate 26, 3275-3284. https://doi.org/10.1175/JCLI-D-12-00577.1.

[10] Calheiros, T., Pereira, M.G., Nunes, J.P., 2021. Assessing impacts of future climate change on extreme fire weather and pyro-regions in Iberian Peninsula. Sci. Total Environ. 754, 142233.

[11] Cane, D., Ciccarelli, N., Gottero, F., Francesetti, A., Pelfini, F., Pelosini, R., 2008. Fire weather index application in north-western Italy. Adv. Sci. Res. 2 (1), 77-80.

[12] Carvalho, A.C., Carvalho, A., Martins, H., Marques, C., Rocha, A., Borrego, C., Viegas, D. X., Miranda, A.I., 2011. Fire weather risk assessment under climate change using a dynamical downscaling approach. Environ. Model. Softw. 26 (9), 1123-1133.

[13] Colmet-Daage, A., Sanchez-Gomez, E., Ricci, S., Llovel, C., Estupina, V.B., Quintana-Seguí P., Llasat, M.C., Servat, E., 2018. Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles. Hydrol. Earth Syst. Sci. 22, 673-687. https://doi.org/10.5194/hess-22-673-2018.

[14] Di Giuseppe, F., McNorton, J., Lombardi, A., Wetterhall, F., 2025. Global data-driven prediction of fire activity. Nat. Commun. 16, 2918. https://doi.org/10.1038/s41467-025-58097-7.

[15] Di Nunno, F., De Matteo, M., Izzo, G., Granata, F., 2023. A combined clustering and trends analysis approach for characterizing reference evapotranspiration in Veneto. Sustainability 15 (14), 11091.

[16] Di Nunno, F., de Marinis, G., Granata, F., 2024. Analysis of SPI index trend variations in the United Kingdom - A cluster-based and Bayesian ensemble algorithms approach. J. Hydrol. Reg. Stud. 52, 101717. https://doi.org/10.1016/j.ejrh.2024.101717.

[17] Di Nunno, F., Granata, F., 2025. Unraveling drought patterns and abrupt changes in the Western Alps: A dual index approach. Earth Syst. Environ. 9, 1253-1272. https://doi.org/10.1007/s41748-025-00633-y.

[18] Döscher, R., Acosta, M., Alessandri, A., Anthoni, P., Arsouze, T., Bergman, T., Bernardello, R., Boussetta, S., Caron, L.-P., Carver, G., Castrillo, M., Catalano, F., Cvijanovic, I., Davini, P., Dekker, E., Doblas-Reyes, F.J., Docquier, D., Echevarria, P., Fladrich, U., Fuentes-Franco, R., Gröger, M., Hardenberg, J., Hieronymus, J., Karami, M.P., Keskinen, J.-P., Koenigk, T., Makkonen, R., Massonnet, F., Ménégoz, M., Miller, P.A., Moreno-Chamarro, E., Nieradzik, L., van Noije, T., Nolan, P., O’Donnell, D., Ollinaho, P., van den Oord, G., Ortega, P., Prims, O.T., Ramos, A., Reerink, T., Rousset, C., Ruprich-Robert, Y., Le Sager, P., Schmith, T., Schrödner, R., Serva, F., Sicardi, V., Sloth Madsen, M., Smith, B., Tian, T., Tourigny, E., Uotila, P., Vancoppenolle, M., Wang, S., Wårlind, D., Willén, U., Wyser, K., Yang, S., Yepes-Arbós, X., Zhang, Q., 2022. The EC-Earth 3 earth system model for the coupled model intercomparison project 6. Geosci. Model Dev. 15, 2973-3020. https://doi.org/10.5194/gmd-15-2973-2022.

[19] Dufresne, J.-L., Foujols, M.-A., Denvil, S., Caubel, A., Marti, O., Aumont, O., Balkanski, Y., Bekki, S., Bellenger, H., Benshila, R., Bony, S., Bopp, L., Braconnot, P., Brockmann, P., Cadule, P., Cheruy, F., Codron, F., Cozic, A., Cugnet, D., de Noblet, N., Duvel, J.-P., Ethé C., Fairhead, L., Fichefet, T., Flavoni, S., Friedlingstein, P., Grandpeix, J.-Y., Guez, L., Guilyardi, E., Hauglustaine, D., Hourdin, F., Idelkadi, A., Ghattas, J., Joussaume, S., Kageyama, M., Krinner, G., Labetoulle, S., Lahellec, A., Lefebvre, M.-P., Lefevre, F., Levy, C., Li, Z.X., Lloyd, J., Lott, F., Madec, G., Mancip, M., Marchand, M., Masson, S., Meurdesoif, Y., Mignot, J., Musat, I., Parouty, S., Polcher, J., Rio, C., Schulz, M., Swingedouw, D., Szopa, S., Talandier, C., Terray, P., Viovy, N., Vuichard, N., 2013. Climate change projections using the IPSL-CM5 Earth System Model: From CMIP3 to CMIP5. Clim. Dyn. 40, 2123-2165. https://doi.org/10.1007/s00382-012-1636-1.

[20] Dupuy, J.-L., Fargeon, H., Martin-StPaul, N., Pimont, F., Ruffault, J., Guijarro, M., Hernando, C., Madrigal, J., Fernandes, P., 2020. Climate change impact on future wildfire danger and activity in southern Europe: A review. Ann. Forest. Sci. 77, 35. https://doi.org/10.1007/s13595-020-00933-5.

[21] El Garroussi, S., Di Giuseppe, F., Barnard, C., Wetterhall, F., 2024. Europe faces up to tenfold increase in extreme fires in a warming climate. Npj Clim. Atmos. Sci. 7, 30. https://doi.org/10.1038/s41612-024-00575-8.

[22] Feron, S., Cordero, R.R., Damiani, A., MacDonell, S., Pizarro, J., Goubanova, K., Valenzuela, R., Wang, C., Rester, L., Beaulieu, A., 2024. South America is becoming warmer, drier, and more flammable. Commun. Earth Environ. 5, 501.

[23] Field, R.D., 2020. Evaluation of global fire weather database reanalysis and short-term forecast products. Nat. Hazards Earth Syst. Sci. 20 (4), 1123-1147.

[24] Galizia, L.F., Curt, T., Barbero, R., Rodrigues, M., 2022. Understanding fire regimes in Europe. Int. J. Wildland Fire 31, 56-66.

[25] Gallo, C., Eden, J.M., Dieppois, B., Drobyshev, I., Fulé P.Z., San-Miguel-Ayanz, J., Blackett, M., 2023. Evaluation of CMIP 6 model performances in simulating fire weather spatiotemporal variability on global and regional scales. Geosci. Model Dev. 16, 3103-3122. https://doi.org/10.5194/gmd-16-3103-2023.

[26] Giorgetta, M.A., Jungclaus, J., Reick, C.H., Legutke, S., Bader, J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K.D., Stockhause, M., Timmreck, C., Wegner, Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., Stevens, B., 2013. Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the coupled model intercomparison project phase 5. J. Adv. Model. Earth Syst. 5, 572-597. https://doi.org/10.1002/jame.20038.

[27] Goss, M., Swain, D.L., Abatzoglou, J.T., Kolden, C.A., Williams, A.P., Diffenbaugh, N.S., 2020. Climate change is increasing the likelihood of extreme autumn wildfire conditions across California. Environ. Res. Lett. 15, 9. https://doi.org/10.1088/1748-9326/ab83a7.

[28] Hetzer, J., Forrest, M., Ribalaygua, J., Prado-López, C., Hickler, T., 2024. The fire weather in Europe: Large-scale trends towards higher danger. Environ. Res. Lett. 19, 084017.

[29] Hirsch, R.M., Slack, J.R., 1984. A nonparametric trend test for seasonal data with serial dependence. Water Resour. Res. 20 (6), 727-732.

[30] Horing, J., Shivaram, R., Azevedo, I.M.L., 2025. Perceptions of wildfire risk and adaptation behaviour in California. Environ. Res. Clim. 4, 015010. https://doi.org/10.1088/2752-5295/ada8ca.

[31] Jain, P., Tye, M.R., Paimazumder, D., Flannigan, M., 2020. Downscaling fire weather extremes from historical and projected climate models. Clim. Change 163, 189-216. https://doi.org/10.1007/s10584-020-02865-5.

[32] Jain, P., Castellanos-Acuna, D., Coogan, S.C.P., Abatzoglou, J.T., Flannigan, M., 2022. Observed increases in extreme fire weather driven by atmospheric humidity and temperature. Nat. Clim. Change 12, 63-70. https://doi.org/10.1038/s41558-021-01224-1.

[33] Kumar, A., Kumar, S., Rautela, K.S., Shekhar, S., Ray, T., Thangavel, M., 2023a. Assessing seasonal variation and trends in rainfall patterns of Madhya Pradesh. Central India, J. Water Clim. Change 14 (10), 3692-3712.

[34] Kumar, A., Kumar, S., Rautela, K.S., Kumari, A., Shekhar, S., Thangavel, M., 2023b. Exploring temperature dynamics in Madhya Pradesh: A spatial-temporal analysis. Environ. Sci. Pollut. Res. 195, 1313. https://doi.org/10.1007/s10661-023-11884-5.

[35] Kumar, A., Ray, T., Mohanasundari, T., 2024. Exploring climatic dynamics in Madhya Pradesh, India utilizing long-term gridded data (1951-2021):An integrated statistical and GIS modules. In: Yadav A.K., Yadav K., Singh V.P. (Eds.), Integrated Management of Water Resources in India: A Computational Approach, vol. 129. Water Science and Technology Library, Springer, Cham, pp. 2-21.

[36] Kumar, A., Thangavel, M., 2025. Unravelling the dynamics of rainfall patterns in Bihar, India: A comprehensive spatiotemporal analysis. Environ. Sci. Pollut. Res. 32, 8564-8584.

[37] Leonardos, L., Gnilke, A., Sanders, T.G.M., Shatto, C., Stadelmann, C., Beierkuhnlein, C., Jentsch, A., 2024. Synthesis and perspectives on disturbance interactions, and forest fire risk and fire severity in Central Europe. Fire 7 (12), 470. https://doi.org/10.3390/fire7120470.

[38] McBride, L.A., Hope, A.P., Canty, T.P., Bennett, B.F., Tribett, W.R., Salawitch, R.J., 2021. Comparison of CMIP 6 historical climate simulations and future projected warming to an empirical model of global climate. Earth Syst. Dyn. 12, 545-579. https://doi.org/10.5194/esd-12-545-2021.

[39] Miller, J., Böhnisch, A., Ludwig, R., Brunner, M.I., 2024. Climate change impacts on regional fire weather in heterogeneous landscapes of central Europe. Nat. Hazards Earth Syst. Sci. 24, 411-428. https://doi.org/10.5194/nhess-24-411-2024.

[40] Mosha, N.S., Semgomba, D.S., Ntigwaza, C.Y., Masunga, D.J., 2025. Physical origins of spatial pattern of summer extreme high temperature days over northern Africa. J. Geosci. Environ. Protect. 13, 32-50.

[41] Pinto, M.M., DaCamara, C.C., Hurduc, A., Trigo, R.M., Trigo, I.F., 2020. Enhancing the fire weather index with atmospheric instability information. Environ. Res. Lett. 15, 0940b7.

[42] Richardson, D., Ribeiro, A.F.S., Batibeniz, F., Quilcaille, Y., Taschetto, A.S., Pitman, A.J., Zscheischler, J., 2025. Increasing fire weather season overlap between North America and Australia challenges firefighting cooperation. Earth’s Future 13, e2024EF005030.

[43] Rovithakis, A., Grillakis, M.G., Seiradakis, K.D., 2022. Future climate change impact on wildfire danger over the Mediterranean: The case of Greece. Environ. Res. Lett. 17, 045022. https://doi.org/10.1088/1748-9326/ac5f94.

[44] Senande-Rivera, M., Insua-Costa, D., Miguez-Macho, G., 2025. Climate change aggravated wildfire behaviour in the Iberian Peninsula in recent years. Npj Clim. Atmos. Sci. 8, 19. https://doi.org/10.1038/s41612-025-00906-3.

[45] Tomaševic´ I.Cˇ., Cheung, K.K.W., Vucˇetic´ V., Fox-Hughes, P., 2022. Comparison of wildfire meteorology and vlimate at the Adriatic coast and southeast Australia. Atmosphere. 13 (5), 755. https://doi.org/10.3390/atmos13050755.

[46] Varela, V., Vlachogiannis, D., Sfetsos, A., Karozis, S., Politi, N., Giroud, F., 2019. Projection of forest fire danger due to climate change in the french Mediterranean region. Sustainability 11 (16), 4284. https://doi.org/10.3390/su11164284.

[47] Voldoire, A., Sanchez-Gomez, E., Salas y Mélia, D., Decharme, B., Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A., Chevallier, M., Déqué M., Deshayes, J., Douville, H., Fernandez, E., Madec, G., Maisonnave, E., Moine, M.-P., Planton, S., Saint-Martin, D., Szopa, S., Tyteca, S., Alkama, R., Belamari, S., Braun, A., Coquart, L., Chauvin, F., 2013. The CNRM-CM5.1 global climate model: description and basic evaluation. Clim. Dyn. 40, 2091-2121. https://doi.org/10.1007/s00382-011-1259-y.

[48] Zaidi, A., 2023. Predicting wildfires in Algerian forests using machine learning models. Heliyon 9 (7), e18064. https://doi.org/10.1016/j.heliyon.2023.e18064.