Fire risk in the Greater Alpine Region from CMIP5 climate models

Author(s)

Abstract
Wildfires strongly impact Central and Southern Europe. While the Mediterranean basin represents the region most prone to severe fire events, recently Alpine regions experienced an increasing number of summer forest fires. Additionally, current climate projections indicate that the Alps are especially exposed to temperature rise, leading to more suitable conditions for the forest fires ignition. The assessment of fire risk worldwide is provided by fire weather indices, closely related to daily meteorological conditions: they give information on both current fire risk and potential fire behaviour. In this study, we investigate the application of Atmosphere–Ocean Global Climate Model simulations, performed in the fifth phase of the Coupled Model Intercomparison Project (CMIP5), in order to evaluate fire risk over the alpine regions in the coming decades. Climate projections are used to estimate the Fire Weather Index and the Fine Fuel Moisture Code, based on the Canadian Forest Fire Danger Rating System. We perform a preliminary analysis aimed at the skill assessment of these models in describing wildfires: the weather variables required by fire indices and the fires indices themselves are examinated comparing the CMIP5 historical simulations with the corresponding ERA-INTERIM reanalysis. The good skill revealed by CMIP5 simulations provide a quantitative basis for estimating future fire risk. At this aim, we adopt the radiative forcing scenario Representative Concentration Pathways RCP45, to evaluate changes in fire risk across the Alps over the 21st century. A general increase of mean and extreme fire events weather conditions is expected, particularly south of the Alps.

Keywords
Climate change, forest fires, Alps, adaptation, climate models,Fire Weather Index (FWI), CMIP5, rcp45

Cite this paper
Barbarino Simona, Cane Daniele, von Hardenberg Jost, Pelosini Renata, Provenzale Antonello, Fire risk in the Greater Alpine Region from CMIP5 climate models , SCIREA Journal of Forestry. Volume 1, Issue 1, October 2016 | PP. 1-23.

References

[ 1 ]	Auer I, Böhm R, Jurkovic A, Lipa W, Orlik A, Potzmann R, Schoner W, Ungersbock M, Matulla C, Briffa K, Jones P, Efthymiadis D, Brunetti M, Nanni T, Maugeri M, Mercalli L, Mestre O, Moisselin JM, Begert M, Muller-Westermeier G, Kveton V, Bochnicek O, Stastny P, Lapin M, Szalai S, Szentimrey T, Cegnar T, Dolinar M, Gajic-Capka M, Zaninovic K, Majstorovic Z, Nieplova E (2007) HISTALP-historical instrumental climatological surface time series of the Greater Alpine Region. Int J Climatol 27.1:17-46. doi: 10.1002/joc.1377
[ 2 ]	Barbosa P, Camia A, Kucera J, Libertà G, Palumbo I, San-Miguel-Ayanz J, Schmuck G (2008) Assessment of forest fire impacts and emissions in the European Union based on the European Forest Fire Information System. Dev Environ Sci 8:197-208. doi: 10.1016/S1474-8177(08)00008-9
[ 3 ]	Brandt M (2010) EC-Earth documentation. http://ecearth.knmi.nl/EC-Earth_model_documentation.pdf
[ 4 ]	Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP,Monge-Sanz BM, Morcrette JJ, Park B-K, Peubey C, de Rosnay P, Tavolato C, Thépaut JN,Vitart F (2011) The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q J R Meteorol Soc 137.656: 553-597. doi: 10.1002/qj.828
[ 5 ]	Dufresne JL, Foujols MA, 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 JP, Ethé C, Fairhead L, Fichefet T, Flavoni S, Friedlingstein P, Grandpeix JY, Guez L, Guilyardi E, Hauglustaine D, Hourdin F, Idelkadi A, Ghattas J, Joussaume S, Kageyama M, Krinner G, Labetoulle S, Lahellec A, Lefebvre MP, Lefevre F, Levy C, Li ZX, 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 40.9-10: 2123-2165. doi: 10.1007/s00382-012-1636-1
[ 6 ]	Efron B, Tibshirani RJ (1994) An introduction to the bootstrap. Chapman & Hall/CRC press.
[ 7 ]	Efron B (2003) Second thoughts on the bootstrap. Statistical Science 18.2: 135-140. doi: 10.1214/ss/1063994968
[ 8 ]	FAO Fire management: voluntary guidelines. Principles and strategic actions (2006) Fire Management Working Paper 17, Rome. www.fao.org/forestry/site/35853/en
[ 9 ]	Hazeleger W, Severijns C, Semmler T, Stefanescu S, Yang S, Wang X, Wyser K, Dutra E, Baldasano JM, Bintanja R, Bougeault P, Caballero R, Ekman AML, Christensen JH, van den Hurk B, Jimenez P, Jones C, Kållberg P, Koenigk T, McGrath R, Miranda P, van Noije T, Palmer T, Parodi JA, Schmith T, Selten F, Storelvmo T, Sterl A, Tapamo H, Vancoppenolle M, Viterbo P, Willén U (2010) EC-Earth: a seamless earth-system prediction approach in action. Bull Am Meteorol Soc 91.10: 1357-1363. doi: 10.1175/2010bams2877.1
[ 10 ]	Hazeleger W, Wang X, Severijns C, Stefănescu S, Bintanja R, Sterl A, Wyser K, Semmler T, Yang S, van den Hurk B, van Noije T, van der Linden E, van der Wiel K (2012) EC-Earth V2. 2: description and validation of a new seamless earth system prediction model. Clim Dyn 39.11: 2611-2629. doi: 10.1007/s00382-011-1228-5
[ 11 ]	IPCC, 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (2013) Camb Univ Press. doi: 10.1017/CBO9781107415324
[ 12 ]	Marcos R, Turco M, Bedia J, Llasat MC, Provenzale A (2015) Seasonal predictability of summer fires in a Mediterranean environment. Int J Wildland Fire. doi: http://dx.doi.org/10.1071/WF15079
[ 13 ]	Millar CI, Stephenson NL, Stephens SL (2007) Climate change and forests of the future: managing in the face of uncertainty. Ecol Appl 17.8: 2145-2151. doi: 10.1890/06-1715.1
[ 14 ]	Moriondo M, Good P, Durao R, Bindi M, Giannakopoulos C, Corte-Real J (2006) Potential impact of climate change on fire risk in the Mediterranean area. Clim Res, 31.1: 85-95. doi: 10.3354/cr031085
[ 15 ]	Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, an Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nat 463.7282:747-756. doi: 10.1038/nature08823
[ 16 ]	Reinhard M, Rebetez M, Schlaepfer R (2005) Recent climate change: Rethinking drought in the context of Forest Fire Research in Ticino, South of Switzerland. Theor Appl Climatol 82.1-2: 17-25. doi: 10.1007/s00704-005-0123-6
[ 17 ]	Ruosteenoja K, Tuomenvirta H, Jylhä K (2007) GCM-based regional temperature and precipitation change estimates for Europe under four SRES scenarios applying a super-ensemble pattern-scaling method. Clim Chang 81.1: 193-208. doi: 10.1007/s10584-006-9222-3
[ 18 ]	Taylor KE, Stouffer R.J, Meehl, GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93.4: 485-498. http://dx.doi.org/10.1175/BAMS-D-11-00094.1
[ 19 ]	Turco M, Llasat MC, Tudela A, Castro X, Provenzale A (2013a) Brief communication Decreasing fires in a Mediterranean region (1970–2010, NE Spain).Nat Hazard Earth Syst Sci 13.3: 649-652. doi: 10.5194/nhess-13-649-2013
[ 20 ]	Turco M, Llasat MC, von Hardenberg J, Provenzale A (2013b) Climate change impacts on wildfires in a Mediterranean environment. Clim Chang 125.3-4: 369-380. doi: 10.1007/s10584-014-1183-3
[ 21 ]	Marcos R, Turco M, Bedía J, Llasat MC, Provenzale A (2015) Seasonal predictability of summer fires in a Mediterranean environment. Int. J. Wildland Fire 24.8: 1076-1084. http://dx.doi.org/10.1071/WF15079
[ 22 ]	Valcke S (2006) OASIS3 user guide. PRISM Tech. Rep 3: 64. http://www.prism.enes.org/Publications/Reports/oasis3_UserGuide_T3.pdf
[ 23 ]	Valese E, Conedera M, Vacik H, Japelj A, Beck A, Cocca G, Cvenkel H, Di Narda N, Ghiringhelli A, Lemessi A, Mangiavillano A, Pelfini F, Pelosini R, Ryser D, Wastl C (2011) Wildfires in the Alpine region: first results from the ALP FFIRS project. Proc of 5th Int Wildland Fire Conf Sun City, South Africa. http://www.infopuntveiligheid.nl/Infopuntdocumenten/Dossier%20Natuurbranden/Wildfire%20Conference%20Zuid-Afrika%202011/79%20Eva%20Valese_et_al.pdf
[ 24 ]	Van Vuuren DP, Edmonds J, Kainuma M, Riahi K, Thomson A, Hibbard K, Hurtt GC, Kram T, Krey V, Lamarque JF, Masui T, Meinshausen M, Nakicenovic N, Smith SJ, Rose SK (2011) The representative concentration pathways: an overview. Clim Chang 109: 5-31. doi: 10.1007/s10584-011-0148-z
[ 25 ]	Van Wagner CE (1987) Development and Structure of the Canadian Forest Fire Weather Index System. Can For Serv For Tech Rep 35, Ottawa.
[ 26 ]	Vélez R (2002) Causes of forest fires in the Mediterranean Basin. Risk manag sustain for EFI Proceedings 42: 35-42
[ 27 ]	Voldoire A, Sanchez-Gomez E, y Mélia D S, Decharme B, Cassou C, Sénési S,
[ 28 ]	Valcke S, Beau I, Alias A, Chevallier M, Déqué M, Deshayes J, Douville H, Fernandez E, Madec G, Maisonnave E, Moine MP, Planton S, Saint-Martin D, Szopa S, Tyteca S, Alkama R, Belamari Z, Braun A, Coquart L, Chauvin F (2013) The CNRM-CM5. 1 global climate model: description and basic evaluation. Clim Dyn 40.9-10: 2091-2121. doi: 10.1007/s00382-011-1259-y
[ 29 ]	Wu T, Yu R, Zhang F (2008) A modified dynamic framework for the atmospheric spectral model and its application. J Atmos Sci 65.7: 2235-2253. doi: http://dx.doi.org/10.1175/2007JAS2514.1
[ 30 ]	Wu T, Yu R, Zhang F, Wang Z, Dong M, Wang L, Jin X, Chen D, Li L (2010) The Beijing Climate Center atmospheric general circulation model: description and its performance for the present-day climate.Clim Dyn 34.1: 123-147. doi: 10.1007/s00382-008-0487-2
[ 31 ]	Wu T (2012) A mass-flux cumulus parameterization scheme for large-scale models: Description and test with observations. Clim Dyn 38.3-4: 725-744. doi: 10.1007/s00382-011-0995-3
[ 32 ]	Wu T, Li W, Ji J, Xin X, Li L, Wang Z, Zhang Y, Li J, Zhang F, Wie M, Shi X, Wu F, Zhang L, Chu M, Jie W, Liu Y, Wang F, Liu X, Li Q, Dong M, Liang X, Gao Y, Zhang J (2013) Global carbon budgets simulated by the Beijing Climate Center Climate System Model for the last century. J Geophys Res: Atmos 118.10: 4326-4347. doi:. 10.1002/jgrd.50320