IDEAS home Printed from https://ideas.repec.org/a/spr/climat/v163y2020i1d10.1007_s10584-020-02865-5.html
   My bibliography  Save this article

Downscaling fire weather extremes from historical and projected climate models

Author

Listed:
  • Piyush Jain

    (Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre
    University of Alberta)

  • Mari R. Tye

    (Mesoscale & Microscale Meteorology Laboratory, National Center for Atmospheric Research)

  • Debasish Paimazumder

    (AIG, American International Group, Catastrophe Management and Analytics Center of Excellence)

  • Mike Flannigan

    (University of Alberta)

Abstract

An important aspect of predicting future wildland fire risk is estimating fire weather—weather conducive to the ignition and propagation of fire—under realistic climate change scenarios. Because the majority of area burned occurs on a few days of extreme fire weather, this task should be able to resolve fire weather extremes. In this paper, we present a statistical downscaling procedure based on distribution based scaling (DBS) to bias correct the Fire Weather Index (FWI), part of the Canadian Forest Fire Danger Rating System, as calculated from modeled climate data. Our study area is western Canada (British Columbia and Alberta) and we consider both an historical control period (1990–2000) and three future time periods (2020–2030, 2050–2060, and 2080–2090). The historical data used to calibrate the DBS procedure comprises weather station data and weather from the North American Regional Reanalysis (NARR), whereas the future climate projections are the output of three regional climate models, corresponding to different model parameterizations and downscaled from the NCAR Community Earth System Model under the RCP 8.5 scenario. By fitting a truncated Weibull distribution to observed and modeled FWI values, our method is able to reproduce historical extremes in fire weather indices as determined by the distribution of annual potential spread days, which are defined as days with FWI values greater than 19. Moreover, by calibrating the DBS procedure with gridded reanalysis data as well as station observations, we are able to project future spread day distributions over the entire study area. The results of this study show the DBS procedure leads to a greater number of projected annual spread days at most locations compared with estimates using the uncorrected model output, and that all three RCM models show positive increases in potential annual spread days for the 2050–2060 and 2080–2090 time periods.

Suggested Citation

  • Piyush Jain & Mari R. Tye & Debasish Paimazumder & Mike Flannigan, 2020. "Downscaling fire weather extremes from historical and projected climate models," Climatic Change, Springer, vol. 163(1), pages 189-216, November.
    • Handle: RePEc:spr:climat:v:163:y:2020:i:1:d:10.1007_s10584-020-02865-5
    DOI: 10.1007/s10584-020-02865-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10584-020-02865-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10584-020-02865-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Marie Ekström & Michael R Grose & Penny H Whetton, 2015. "An appraisal of downscaling methods used in climate change research," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 6(3), pages 301-319, May.
    2. M. Ghil & Pascal Yiou & Stéphane Hallegatte & B. D. Malamud & P. Naveau & A. Soloviev & P. Friederichs & V. Keilis-Borok & D. Kondrashov & V. Kossobokov & O. Mestre & C. Nicolis & H. W. Rust & P. Sheb, 2011. "Extreme events: dynamics, statistics and prediction," Post-Print hal-00716514, HAL.
    3. 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.
    4. Rasmus Benestad & Jana Sillmann & Thordis Linda Thorarinsdottir & Peter Guttorp & Michel d. S. Mesquita & Mari R. Tye & Petteri Uotila & Cathrine Fox Maule & Peter Thejll & Martin Drews & Kajsa M. Par, 2017. "New vigour involving statisticians to overcome ensemble fatigue," Nature Climate Change, Nature, vol. 7(10), pages 697-703, October.
    5. 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.
    6. W. Matt Jolly & Mark A. Cochrane & Patrick H. Freeborn & Zachary A. Holden & Timothy J. Brown & Grant J. Williamson & David M. J. S. Bowman, 2015. "Climate-induced variations in global wildfire danger from 1979 to 2013," Nature Communications, Nature, vol. 6(1), pages 1-11, November.
    7. James Done & Greg Holland & Cindy Bruyère & L. Leung & Asuka Suzuki-Parker, 2015. "Modeling high-impact weather and climate: lessons from a tropical cyclone perspective," Climatic Change, Springer, vol. 129(3), pages 381-395, April.
    8. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hong Wen Yu & S. Y. Simon Wang & Wan Yu Liu, 2024. "Estimating wildfire potential in Taiwan under different climate change scenarios," Climatic Change, Springer, vol. 177(1), pages 1-26, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Megan C. Kirchmeier-Young & Francis W. Zwiers & Nathan P. Gillett & Alex J. Cannon, 2017. "Attributing extreme fire risk in Western Canada to human emissions," Climatic Change, Springer, vol. 144(2), pages 365-379, September.
    3. Bruno A. Aparício & João A. Santos & Teresa R. Freitas & Ana C. L. Sá & José M. C. Pereira & Paulo M. Fernandes, 2022. "Unravelling the effect of climate change on fire danger and fire behaviour in the Transboundary Biosphere Reserve of Meseta Ibérica (Portugal-Spain)," Climatic Change, Springer, vol. 173(1), pages 1-20, July.
    4. Xueke Li & Amanda H. Lynch, 2023. "New insights into projected Arctic sea road: operational risks, economic values, and policy implications," Climatic Change, Springer, vol. 176(4), pages 1-16, April.
    5. Alexandra D Syphard & Timothy Sheehan & Heather Rustigian-Romsos & Kenneth Ferschweiler, 2018. "Mapping future fire probability under climate change: Does vegetation matter?," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-23, August.
    6. Carmenta, Rachel & Cammelli, Federico & Dressler, Wolfram & Verbicaro, Camila & Zaehringer, Julie G., 2021. "Between a rock and a hard place: The burdens of uncontrolled fire for smallholders across the tropics," World Development, Elsevier, vol. 145(C).
    7. Jui-Chan Hsu & Wei-Po Huang & Chun-Jhen Ye, 2024. "Comparing the Dominant Factors in Coastal Morphology: Inappropriate Infrastructure vs. Climate Change—A Case Study of the Hsinchu Fishery Harbor, Taiwan," Sustainability, MDPI, vol. 16(13), pages 1-24, June.
    8. Andrew John & Avril Horne & Rory Nathan & Michael Stewardson & J. Angus Webb & Jun Wang & N. LeRoy Poff, 2021. "Climate change and freshwater ecology: Hydrological and ecological methods of comparable complexity are needed to predict risk," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 12(2), March.
    9. Vassiliki Kotroni & Constantinos Cartalis & Silas Michaelides & Julia Stoyanova & Fillipos Tymvios & Antonis Bezes & Theodoros Christoudias & Stavros Dafis & Christos Giannakopoulos & Theodore M. Gian, 2020. "DISARM Early Warning System for Wildfires in the Eastern Mediterranean," Sustainability, MDPI, vol. 12(16), pages 1-30, August.
    10. Andreas Groth & Michael Ghil & Stéphane Hallegatte & Patrice Dumas, 2015. "The role of oscillatory modes in US business cycles," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2015(1), pages 63-81.
    11. Lucash, Melissa S. & Marshall, Adrienne M. & Weiss, Shelby A. & McNabb, John W. & Nicolsky, Dmitry J. & Flerchinger, Gerald N. & Link, Timothy E. & Vogel, Jason G. & Scheller, Robert M. & Abramoff, Ro, 2023. "Burning trees in frozen soil: Simulating fire, vegetation, soil, and hydrology in the boreal forests of Alaska," Ecological Modelling, Elsevier, vol. 481(C).
    12. Chao-Yuan Lin & Pei-Ying Shieh & Shao-Wei Wu & Po-Cheng Wang & Yung-Chau Chen, 2022. "Environmental indicators combined with risk analysis to evaluate potential wildfire incidence on the Dadu Plateau in Taiwan," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(1), pages 287-313, August.
    13. Vassiliki Varela & Diamando Vlachogiannis & Athanasios Sfetsos & Stelios Karozis & Nadia Politi & Frédérique Giroud, 2019. "Projection of Forest Fire Danger due to Climate Change in the French Mediterranean Region," Sustainability, MDPI, vol. 11(16), pages 1-13, August.
    14. Jake F. Weltzin & Julio L. Betancourt & Benjamin I. Cook & Theresa M. Crimmins & Carolyn A. F. Enquist & Michael D. Gerst & John E. Gross & Geoffrey M. Henebry & Rebecca A. Hufft & Melissa A. Kenney &, 2020. "Seasonality of biological and physical systems as indicators of climatic variation and change," Climatic Change, Springer, vol. 163(4), pages 1755-1771, December.
    15. Johnston, David W. & Önder, Yasin Kürşat & Rahman, Muhammad Habibur & Ulubaşoğlu, Mehmet A., 2021. "Evaluating wildfire exposure: Using wellbeing data to estimate and value the impacts of wildfire," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 782-798.
    16. André Vizinho & David Avelar & Cristina Branquinho & Tiago Capela Lourenço & Silvia Carvalho & Alice Nunes & Leonor Sucena-Paiva & Hugo Oliveira & Ana Lúcia Fonseca & Filipe Duarte Santos & Maria José, 2021. "Framework for Climate Change Adaptation of Agriculture and Forestry in Mediterranean Climate Regions," Land, MDPI, vol. 10(2), pages 1-33, February.
    17. Piyush Jain & Quinn E. Barber & Stephen W. Taylor & Ellen Whitman & Dante Castellanos Acuna & Yan Boulanger & Raphaël D. Chavardès & Jack Chen & Peter Englefield & Mike Flannigan & Martin P. Girardin , 2024. "Drivers and Impacts of the Record-Breaking 2023 Wildfire Season in Canada," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    18. Andrea Duane & Marc Castellnou & Lluís Brotons, 2021. "Towards a comprehensive look at global drivers of novel extreme wildfire events," Climatic Change, Springer, vol. 165(3), pages 1-21, April.
    19. Nikolaos Ntinopoulos & Stavros Sakellariou & Olga Christopoulou & Athanasios Sfougaris, 2023. "Fusion of Remotely-Sensed Fire-Related Indices for Wildfire Prediction through the Contribution of Artificial Intelligence," Sustainability, MDPI, vol. 15(15), pages 1-24, July.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:climat:v:163:y:2020:i:1:d:10.1007_s10584-020-02865-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.