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

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  • J. Bedia
  • S. Herrera
  • D. Martín
  • N. Koutsias
  • J. Gutiérrez

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. Copyright Springer Science+Business Media Dordrecht 2013

Suggested Citation

  • J. Bedia & S. Herrera & D. Martín & N. Koutsias & J. Gutiérrez, 2013. "Robust projections of Fire Weather Index in the Mediterranean using statistical downscaling," Climatic Change, Springer, vol. 120(1), pages 229-247, September.
  • Handle: RePEc:spr:climat:v:120:y:2013:i:1:p:229-247
    DOI: 10.1007/s10584-013-0787-3
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    References listed on IDEAS

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    1. S. Herrera & J. Bedia & J. Gutiérrez & J. Fernández & J. Moreno, 2013. "On the projection of future fire danger conditions with various instantaneous/mean-daily data sources," Climatic Change, Springer, vol. 118(3), pages 827-840, June.
    2. Meg Krawchuk & Steve Cumming & Mike Flannigan, 2009. "Predicted changes in fire weather suggest increases in lightning fire initiation and future area burned in the mixedwood boreal forest," Climatic Change, Springer, vol. 92(1), pages 83-97, January.
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    1. A. Casanueva & M. Frías & S. Herrera & D. San-Martín & K. Zaninovic & J. Gutiérrez, 2014. "Statistical downscaling of climate impact indices: testing the direct approach," Climatic Change, Springer, vol. 127(3), pages 547-560, December.
    2. A. Casanueva & J. Bedia & S. Herrera & J. Fernández & J. M. Gutiérrez, 2018. "Direct and component-wise bias correction of multi-variate climate indices: the percentile adjustment function diagnostic tool," Climatic Change, Springer, vol. 147(3), pages 411-425, April.
    3. Marco Turco & Maria-Carmen Llasat & Jost Hardenberg & Antonello Provenzale, 2014. "Climate change impacts on wildfires in a Mediterranean environment," Climatic Change, Springer, vol. 125(3), pages 369-380, August.
    4. Marion Lestienne & Boris Vannière & Thomas Curt & Isabelle Jouffroy-Bapicot & Christelle Hély, 2022. "Climate-driven Mediterranean fire hazard assessments for 2020–2100 on the light of past millennial variability," Climatic Change, Springer, vol. 170(1), pages 1-18, January.
    5. Enoch Bessah & Emmanuel A. Boakye & Sampson K. Agodzo & Emmanuel Nyadzi & Isaac Larbi & Alfred Awotwi, 2021. "Increased seasonal rainfall in the twenty-first century over Ghana and its potential implications for agriculture productivity," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(8), pages 12342-12365, August.
    6. Xianli Wang & Dan Thompson & Ginny Marshall & Cordy Tymstra & Richard Carr & Mike Flannigan, 2015. "Increasing frequency of extreme fire weather in Canada with climate change," Climatic Change, Springer, vol. 130(4), pages 573-586, June.
    7. B. Hewitson & J. Daron & R. Crane & M. Zermoglio & C. Jack, 2014. "Interrogating empirical-statistical downscaling," Climatic Change, Springer, vol. 122(4), pages 539-554, February.
    8. Hamish Clarke & Andrew J. Pitman & Jatin Kala & Claire Carouge & Vanessa Haverd & Jason P. Evans, 2016. "An investigation of future fuel load and fire weather in Australia," Climatic Change, Springer, vol. 139(3), pages 591-605, December.
    9. J. Bedia & S. Herrera & A. Camia & J. M. Moreno & J. M. Gutiérrez, 2014. "Forest fire danger projections in the Mediterranean using ENSEMBLES regional climate change scenarios," Climatic Change, Springer, vol. 122(1), pages 185-199, January.
    10. Melania Michetti & Mehmet Pinar, 2019. "Forest Fires Across Italian Regions and Implications for Climate Change: A Panel Data Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 207-246, January.

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