Climatic Change

, Volume 120, Issue 1–2, pp 229–247 | Cite as

Robust projections of Fire Weather Index in the Mediterranean using statistical downscaling

  • J. Bedia
  • S. Herrera
  • D. San Martín
  • N. Koutsias
  • J. M. Gutiérrez
Article

Abstract

The effect of climate change on wildfires constitutes a serious concern in fire-prone regions with complex fire behavior such as the Mediterranean. The coarse resolution of future climate projections produced by General Circulation Models (GCMs) prevents their direct use in local climate change studies. Statistical downscaling techniques bridge this gap using empirical models that link the synoptic-scale variables from GCMs to the local variables of interest (using e.g. data from meteorological stations). In this paper, we investigate the application of statistical downscaling methods in the context of wildfire research, focusing in the Canadian Fire Weather Index (FWI), one of the most popular fire danger indices. We target on the Iberian Peninsula and Greece and use historical observations of the FWI meteorological drivers (temperature, humidity, wind and precipitation) in several local stations. In particular, we analyze the performance of the analog method, which is a convenient first choice for this problem since it guarantees physical and spatial consistency of the downscaled variables, regardless of their different statistical properties. First we validate the method in perfect model conditions using ERA-Interim reanalysis data. Overall, not all variables are downscaled with the same accuracy, with the poorest results (with spatially averaged daily correlations below 0.5) obtained for wind, followed by precipitation. Consequently, those FWI components mostly relying on those parameters exhibit the poorest results. However, those deficiencies are compensated in the resulting FWI values due to the overall high performance of temperature and relative humidity. Then, we check the suitability of the method to downscale control projections (20C3M scenario) from a single GCM (the ECHAM5 model) and compute the downscaled future fire danger projections for the transient A1B scenario. In order to detect problems due to non-stationarities related to climate change, we compare the results with those obtained with a Regional Climate Model (RCM) driven by the same GCM. Although both statistical and dynamical projections exhibit a similar pattern of risk increment in the first half of the 21st century, they diverge during the second half of the century. As a conclusion, we advocate caution in the use of projections for this last period, regardless of the regionalization technique applied.

Notes

Acknowledgements

We are grateful to the Spanish Meteorological Agency (AEMET) and to the Hellenic National Meteorological Service (HNMS) for providing the observational data used in this study. We would also like to thank Erik van Meijgaard from the Royal Netherlands Meteorological Institute for making available ENSEMBLES RACMO2 climate model output verifying at 12:00 UTC and to the Max Planck Institute for providing the appropriate data for the ECHAM5 model used in this work. This work was partly funded by European Union’s Seventh Framework Programme (FP7/2007–2013) under grant agreements 243888 (FUME Project) and from Spanish Ministry MICINN under grant EXTREMBLES (CGL2010-21869). We thank two anonymous referees for their useful comments that helped to improve the original manuscript.

References

  1. Abatzoglou J, Brown T (2012) A comparison of statistical downscaling methods suited for wildfire applications. Int J Climatol 32:772–780. doi:10.1002/joc.2312 CrossRefGoogle Scholar
  2. Andrews P, Loftsgaarden D, Bradshaw L (2003) Evaluation of fire danger rating indexes using logistic regression and percentile analysis. Int J Wildland Fire 12:213–226CrossRefGoogle Scholar
  3. Bedia J, Herrera S, Gutiérrez J, Zavala G, Urbieta I, Moreno J (2012) Sensitivity of Fire Weather Index to different reanalysis products in the Iberian Peninsula. Nat Hazards Earth Syst Sci 12:699–708. doi:10.5194/nhess-12-699-2012 CrossRefGoogle Scholar
  4. Benestad RE (2010) Downscaling precipitation extremes. Theor Appl Climatol 100:1–21. doi:10.1007/s00704-009-0158-1 CrossRefGoogle Scholar
  5. Benestad RE, Hanssen-Bauer I, Chen D (2008) Empirical-Statistical Downscaling, 1st edn. World Scientific Publishing, SingaporeGoogle Scholar
  6. Brands S, Herrera S, San-Martín D, Gutiérrez J (2011) Validation of the ENSEMBLES Global Climate Models over southwestern Europe using probability density functions: A downscaler’s perspective. Climate Res 48:145–161. doi:10.3354/cr00995 CrossRefGoogle Scholar
  7. Brown T, Hall B, Westerling A (2004) The impact of twenty-first century climate change on wildland fire danger in the westerns United States: An applications perspective. Climatic Change 62:365–388CrossRefGoogle Scholar
  8. Camia A, Amatulli G, San Miguel-Ayanz J (2008) Past and future trends of forest fire danger in Europe. Tech. Rep. EUR 23427 EN—2008, Institute for Environment and Sustainability, Joint Research Centre, European Comission, Ispra, ItalyGoogle Scholar
  9. Christensen J, Boberg F, Christensen O, Lucas-Picher P (2008) On the need for bias correction of regional climate change projections of temperature and precipitation. Geophys Res Lett 35:L20,709. doi:10.1029/2008GL035694 CrossRefGoogle Scholar
  10. Cubasch U, vonStorch H, Waszkewitz J, Zorita E (1996) Estimates of climate change in Southern Europe derived from dynamical climate model output. Climate Res 7:129–149CrossRefGoogle Scholar
  11. 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 J, Park B, Peubey C, de Rosnay P, Tavolato C, Thépaut JN, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quart J Roy Meteor Soc 137(656):553–597. doi:10.1002/qj.828 CrossRefGoogle Scholar
  12. Dimitrakopoulos A, Bemmerzouk A, Mitsopoulos I (2011) Evaluation of the Canadian fire weather index system in an eastern Mediterranean environment. Meteorol Appl 18:83–93CrossRefGoogle Scholar
  13. Dowdy A, Mills G, Finkele K, deGroot W (2010) Index sensitivity analysis applied to the Canadian Forest Fire Weather Index and the McArthur Forest Fire Danger Index. Meteorol Appl 17:298–312Google Scholar
  14. Flannigan M, Logan K, Amiro B, Skinner W, Stocks B (2005) Future area burned in Canada. Climatic Change 72(1–2):1–16. doi:10.1007/s10584-005-5935-y Google Scholar
  15. Giorgi F, Lionello P (2008) Climate change projections for the Mediterranean region. Global Planet Change 63:90–104. doi:10.1016/j.gloplacha.2007.09.005 CrossRefGoogle Scholar
  16. Giorgi F, Mearns LO (1999) Introduction to special section: regional climate modeling revisited. J Geophys Res 104:6335–6352CrossRefGoogle Scholar
  17. Groisman PY, Sherstyukov BG, Razuvaev VN, Knight RW, Enloe JG, Stroumentova NS, Whitfield PH, Forland E, Hannsen-Bauer I, Tuomenvirta H, Aleksandersson H, Mescherskaya AV, Karl TR (2007) Potential forest fire danger over Northern Eurasia: Changes during the 20th century. Global Planet Change 56:371–386. doi:10.1016/j.gloplacha.2006.07.029 CrossRefGoogle Scholar
  18. Gutiérrez J M, Ribalaygua J, Llasat C, Romero R, Abaurrea J, Rodríguez-Camino E (2012) Cambio climático: Extremos e Impactos. Publicaciones de la Asociación Española de Climatología (AEC). Serie A 8:125–135Google Scholar
  19. Gutiérrez J, San-Martín D, Brands S, Manzanas R, Herrera S (2012) Reassessing statistical downscaling techniques for their robust application under climate change conditions. J Climate. doi:10.1175/JCLI-D-11-00687.1
  20. Herrera S, Fita L, Fernández J, Gutiérrez J (2010) Evaluation of the mean and extreme precipitation regimes from the ENSEMBLES regional climate multimodel simulations over Spain. J Geophys Res 115. doi:10.1029/2010JD013936
  21. Herrera S, Bedia J, Gutiérrez JM, Fernández J, Moreno JM (2013) On the projection of future fire danger conditions with various instantaneous/mean-daily data sources. Climatic Change, Published online. doi:10.1007/s10584-012-0667-2 Google Scholar
  22. Imbert A, Benestad R (2005) An improvement of analog model strategy for more reliable local climate change scenarios. Theor Appl Climatol 82:245–255. doi:10.1007/s00704-005-0133-4 CrossRefGoogle Scholar
  23. Koutsias N, Arianoutsou M, Kallimanis A, Mallinis G, Halley J, Dimopoulos P (2012) Where did the fires burn in Peloponnisos, Greece the summer of 2007? Evidence for a synergy of fuel and weather. Agr Forest Meteorol 156:41–53CrossRefGoogle Scholar
  24. Krawchuk M, Cumming S, Flannigan M (2009) Predicted changes in fire weather suggest increases in lightning fire initiation and future area burned in the mixedwood boreal forest. Climatic Change 92:83–97. doi:10.1007/s10584-008-9460-7 CrossRefGoogle Scholar
  25. Lawrence M (2005) The relationship between relative humidity and the dewpoint temperature in moist air. A simple conversion and applications. Bull Am Meteorol Soc 86:225–233. doi:10.1175/BAMS-86-2-225 Google Scholar
  26. Lorenz E (1963) Deterministic nonperiodic flow. J Atmos Sci 20:130–141CrossRefGoogle Scholar
  27. Lorenz E (1969) Atmospheric predictability as revealed by naturally occurring analogues. J Atmos Sci 26:636–646. doi:10.1175/1520-0469(1969)26<636:APARBN>2.0.CO:2 CrossRefGoogle Scholar
  28. Maraun D (2012) Nonstationarities of regional climate model biases in European seasonal mean temperature and precipitation sums. Geophys Res Lett 39:L06,706. doi:10.1029/2012GL051210
  29. Maraun D, Wetterhall F, Ireson A M, Chandler R E, Kendon E J, Widmann M, Brienen S, Rust H W, Sauter T, Themessl M, Venema V K C, Chun K P, Goodess C M, Jones R G, Onof C, Vrac M, Thiele-Eich I (2010) Precipitation Downscaling under Climate Change: Recent Developments to Bridge the Gap Between Dynamical Downscaling Models and the End User. Rev Geophys 48:RG3003. doi:10.1029/2009RG000314 CrossRefGoogle Scholar
  30. Meyn A, White P, Buhk C, Jentsch A (2007) Environmental drivers of large, infrequent wildfires: The emerging conceptual model. Prog Phys Geog 31:287–312CrossRefGoogle Scholar
  31. Meyn A, Schmidtlein S, Taylor SW, Girardin MP, Thonicke K, Cramer W (2010) Spatial variation of trends in wildfire and summer drought in British Columbia, Canada, 1920–2000. Int J Wildland Fire 19:272–283. doi:10.1071/WF09055 CrossRefGoogle Scholar
  32. 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. Climate Res 31:85–95CrossRefGoogle Scholar
  33. Palheiro P M, Fernandes P, Cruz M G (2006) A fire behaviour-based fire danger classification for maritime pine stands: Comparison of two approaches. Forest Ecology and Management 234:S54Google Scholar
  34. Pausas J (2004) Changes in fire and climate in the eastern Iberian Peninsula (Mediterranean basin). Climatic Change 63:337–350CrossRefGoogle Scholar
  35. Pechony O, Shindell DT (2010) Driving forces of global wildfires over the past millennium and the forthcoming century. Proc Natl Acad Sci USA 107(45):19167–19170. doi:10.1073/pnas.1003669107 CrossRefGoogle Scholar
  36. Räisänen J (2007) How reliable are climate models? Tellus A 59:2–29CrossRefGoogle Scholar
  37. Seneviratne S, Nicholls N, Easterling D, Goodess C, Kanae S, Kossin J, Luo Y, Marengo J, McInnes K, Rahimi M, Reichstein M, Sorteberg A, Vera C, Zhang X (2012) Changes in climate extremes and their impacts on the natural physical environment. In: Field C, Barros V, Stocker T, Qin D, Dokken D, Ebi K, Mastrandrea M, Mach K, Plattner GK, Allen S, Tignor M, Midgley P (eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. Cambridge University Press, Cambridge, UK, and New York, USA, pp 109–230Google Scholar
  38. Stocks B, Fosberg M, Lynham T, Mearns L, Wotton B, Yang Q, Jin JZ, Lawrence K, Hartley G, Mason J, McKenney D (1998) Climate change and forest fire potential in Russian and Canadian boreal forests. Climatic Change 38:1–13CrossRefGoogle Scholar
  39. Turco M, Llasat M, von Hardenberg J, Provenzale A (2012) Impact of climate variability on summer fires in a Mediterranean environment (northeastern Iberian Peninsula). Climatic Change. doi:10.1007/s10584-012-0505-6
  40. Uppala SM, Kallberg PW, Simmons AJ, Andrae U, Bechtold VD, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Van De Berg L, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Holm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, McNally AP, Mahfouf JF, Morcrette JJ, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J (2012) The ERA-40 re-analysis. Quart J Roy Meteor Soc 131(612, Part b):2961–3012CrossRefGoogle Scholar
  41. van der Linden P, Mitchell J (2009) ENSEMBLES: Climate change and its impacts: Summary of research and results from the ENSEMBLES project. Tech. rep., Met Office Hadley Centre, Exeter, UKGoogle Scholar
  42. van Meijgaard E, van Ulft L, van de Berg W, Bosveld F, van den Hurk B, Lenderink G, Siebesma A (2008) The KNMI regional atmospheric climate model RACMO, version 2.1. Tech. Rep. 302, R. Neth. Meteorol. Inst., De Bilt, NetherlandsGoogle Scholar
  43. van Wagner CE (1970) Conversion of William’s Severity Rating for use with the Fire Weather Index. Information Report PS–X–21, Canadian Forestry Service, Ontario, CanadaGoogle Scholar
  44. van Wagner CE (1987) Development and structure of the Canadian Forest Fire Weather Index. Forestry Tech. Rep. 35, Canadian Forestry Service, Ottawa, CanadaGoogle Scholar
  45. van Wagner CE, Pickett TL (1985) Equations and FORTRAN program for the Canadian forest fire weather index system. Forestry Tech. Rep. 33, Canadian Forestry Service, Ottawa, CanadaGoogle Scholar
  46. Viegas D, Bovio G, Ferreira A, Nosenzo A, Sol B (1999) Comparative study of various methods of fire danger evaluation in southern Europe. Int J Wildland Fire 9:235–246CrossRefGoogle Scholar
  47. Wotton BM (2009) Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications. Environ Ecol Stat 16:107–131. doi:10.1007/s10651-007-0084-2 CrossRefGoogle Scholar
  48. Zorita E, von Storch H (1999) The analog method as a simple statistical downscaling technique: Comparison with more complicated methods. J Climate 12:2474–2489CrossRefGoogle Scholar
  49. Zorita E, Hughes J, Lettemaier D, Von Storch H (1995) Stochastic characterization of regional circulation patterns for climate model diagnosis and estimation of local precipitation. J Climate 8:1023–1042CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • J. Bedia
    • 1
  • S. Herrera
    • 2
    • 3
  • D. San Martín
    • 2
  • N. Koutsias
    • 4
  • J. M. Gutiérrez
    • 1
  1. 1.Instituto de Física de CantabriaCSIC-Universidad de CantabriaSantanderSpain
  2. 2.Predictia Intelligent Data SolutionsSantanderSpain
  3. 3.Dept. Applied Mathematics and Computer SciencesUniversity of CantabriaSantanderSpain
  4. 4.Department of Environmental and Natural Resources ManagementUniversity of IoanninaAgrinioGreece

Personalised recommendations