Free Standard AU & NZ Shipping For All Book Orders Over $80!
Register      Login
International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Evaluation of the Weather Research and Forecasting model in simulating fire weather for the south-west of Western Australia

Jatin Kala https://orcid.org/0000-0001-9338-2965 A C , Alyce Sala Tenna A , Daniel Rudloff A B , Julia Andrys A , Ole Rieke A B and Thomas J. Lyons A
+ Author Affiliations
- Author Affiliations

A Environmental and Conservation Sciences and Centre for Climate Impacted Terrestrial Ecosystems, Harry Butler Institute, Murdoch University, Murdoch, WA 6150, Australia.

B Climate Physics: Meteorology and Physical Oceanography, Kiel – Christian-Albrechts-Universität zu Kiel, Kiel 24118, Germany.

C Corresponding author. Email: J.Kala@murdoch.edu.au

International Journal of Wildland Fire 29(9) 779-792 https://doi.org/10.1071/WF19111
Submitted: 23 July 2019  Accepted: 29 April 2020   Published: 21 May 2020

Abstract

The Weather Research and Forecasting (WRF) model was used to simulate fire weather for the south-west of Western Australia (SWWA) over multiple decades at a 5-km resolution using lateral boundary conditions from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)-Interim reanalysis. Simulations were compared with observations at Australian Bureau of Meteorology meteorological stations and the McArthur Forest Fire Danger Index (FFDI) was used to quantify fire weather. Results showed that, overall, the WRF reproduced the annual cumulative FFDI at most stations reasonably well, with most biases in the FFDI ranging between –600 and 600. Biases were highest at stations within the metropolitan region. The WRF simulated the geographical gradients in the FFDI across the domain well. The source of errors in the FFDI varied markedly between the different stations, with no one particular variable able to account for the errors at all stations. Overall, this study shows that the WRF is a useful model for simulating fire weather for SWWA, one of the most fire-prone regions in Australia.


References

Andrys J, Lyons TJ, Kala J (2015) Multidecadal evaluation of WRF downscaling capabilities over Western Australia in simulating rainfall and temperature extremes. Journal of Applied Meteorology and Climatology 54, 370–394.
Multidecadal evaluation of WRF downscaling capabilities over Western Australia in simulating rainfall and temperature extremes.Crossref | GoogleScholarGoogle Scholar |

Andrys J, Lyons TJ, Kala J (2016) Evaluation of a WRF ensemble using GCM boundary conditions to quantify mean and extreme climate for the southwest of Western Australia (1970–1999). International Journal of Climatology 36, 4406–4424.
Evaluation of a WRF ensemble using GCM boundary conditions to quantify mean and extreme climate for the southwest of Western Australia (1970–1999).Crossref | GoogleScholarGoogle Scholar |

Andrys J, Kala J, Lyons TJ (2017) Regional climate projections of mean and extreme climate for the southwest of Western Australia (1970–1999 compared to 2030–2059). Climate Dynamics 48, 1723–1747.
Regional climate projections of mean and extreme climate for the southwest of Western Australia (1970–1999 compared to 2030–2059).Crossref | GoogleScholarGoogle Scholar |

Bates BC, Hope P, Ryan B, Smith I, Charles S (2008) Key findings from the Indian Ocean Climate Initiative and their impact on policy development in Australia. Climatic Change 89, 339–354.
Key findings from the Indian Ocean Climate Initiative and their impact on policy development in Australia.Crossref | GoogleScholarGoogle Scholar |

Brown T, Mills G, Harris S, Podnar D, Reinbold H, Fearon M (2016) A bias corrected WRF mesoscale fire weather dataset for Victoria, Australia1972–2012. Journal of Southern Hemisphere Earth Systems Science 66, 281–313.
A bias corrected WRF mesoscale fire weather dataset for Victoria, Australia1972–2012.Crossref | GoogleScholarGoogle Scholar |

Chen F, Dudhia J (2001) Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: model implementation and sensitivity. Monthly Weather Review 129, 569–585.
Coupling an advanced land surface–hydrology model with the Penn State–NCAR MM5 modeling system. Part I: model implementation and sensitivity.Crossref | GoogleScholarGoogle Scholar |

Clarke H, Evans JP (2019) Exploring the future change space for fire weather in southeast Australia. Theoretical and Applied Climatology 136, 513–527.
Exploring the future change space for fire weather in southeast Australia.Crossref | GoogleScholarGoogle Scholar |

Clarke H, Evans JP, Pitman AJ (2013a) Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia from 1985 to 2009. International Journal of Wildland Fire 22, 739–746.
Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia from 1985 to 2009.Crossref | GoogleScholarGoogle Scholar |

Clarke H, Lucas C, Smith P (2013b) Changes in Australian fire weather between 1973 and 2010. International Journal of Climatology 33, 931–944.
Changes in Australian fire weather between 1973 and 2010.Crossref | GoogleScholarGoogle Scholar |

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-J, Park B-K, Peubey C, de Rosnay P, Tavolato C, Thépaut J-N, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quarterly Journal of the Royal Meteorological Society 137, 553–597.
The ERA-Interim reanalysis: configuration and performance of the data assimilation system.Crossref | GoogleScholarGoogle Scholar |

Dudhia J (1989) Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. Journal of the Atmospheric Sciences 46, 3077–3107.
Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model.Crossref | GoogleScholarGoogle Scholar |

Ferguson E (2016) ‘Reframing rural fire management: Report of the Special Inquiry into the January 2016 Waroona fire’. (Government of Western Australia: Perth)

Finkele K, Mills GA, Beard G, Jones DA (2006) National daily gridded soil moisture deficit and drought factors for use in prediction of forest fire danger index in Australia. Research Report No 119. Bureau of Meteorology Research Centre.

Firth R, Kala J, Lyons TJ, Andrys J (2017) An analysis of regional climate simulations for Western Australia’s wine regions: model evaluation and future climate projections. Journal of Applied Meteorology and Climatology 56, 2113–2138.
An analysis of regional climate simulations for Western Australia’s wine regions: model evaluation and future climate projections.Crossref | GoogleScholarGoogle Scholar |

Fox-Hughes P, Harris R, Lee G, Grose M, Bindoff N (2014) Future fire danger climatology for Tasmania, Australia, using a dynamically downscaled regional climate model. International Journal of Wildland Fire 23, 309–321.
Future fire danger climatology for Tasmania, Australia, using a dynamically downscaled regional climate model.Crossref | GoogleScholarGoogle Scholar |

Gentilli J (1971) ‘Climates of Australia and New Zealand.’ (Elsevier: Amsterdam)

Hong S-Y (2010) A new stable boundary-layer mixing scheme and its impact on the simulated East Asian summer monsoon. Quarterly Journal of the Royal Meteorological Society 136, 1481–1496.
A new stable boundary-layer mixing scheme and its impact on the simulated East Asian summer monsoon.Crossref | GoogleScholarGoogle Scholar |

Hong S-Y, Dudhia J, Chen S-H (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Monthly Weather Review 132, 103–120.
A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation.Crossref | GoogleScholarGoogle Scholar |

Hope P, Abbs D, Bhend J, Chiew F, Church J, Ekström M, Kirono D, Lenton A, Lucas C, McInnes K, Moise A, Monselesan D, Mpelasoka F, Timbal B, Webb L, Whetton P (2015) ‘Southern and south-western flatlands cluster report’. Climate change in Australia: projections for Australia’s Natural Resource Management Regions. (CSIRO and Bureau of Meteorology, Australia). Available at: https://www.climatechangeinaustralia.gov.au/media/ccia/2.1.6/cms_page_media/172/SSWFLATLANDS_CLUSTER_REPORT.pdf. [Verified 1 May 2018]

Kain JS (2004) The Kain–Fritsch convective parameterization: an update. Journal of Applied Meteorology 43, 170–181.
The Kain–Fritsch convective parameterization: an update.Crossref | GoogleScholarGoogle Scholar |

Kala J, Andrys J, Lyons TJ, Foster IJ, Evans BJ (2015) Sensitivity of WRF to driving data and physics options on a seasonal time-scale for the southwest of Western Australia. Climate Dynamics 44, 633–659.
Sensitivity of WRF to driving data and physics options on a seasonal time-scale for the southwest of Western Australia.Crossref | GoogleScholarGoogle Scholar |

Kumar V, Dharssi I (2017) ‘Evaluation of daily soil moisture deficit used in Australian forest fire danger rating system.’ Bushfire and Natural Hazards CRC, report no. 349. Available at: https://www.bnhcrc.com.au/publications/biblio/bnh-4219 [Verified 1 May 2018]

Lee J, Hong J (2016) Implementation of spaceborne lidar-retrieved canopy height in the WRF model. Journal of Geophysical Research, D, Atmospheres 121, 6863–6876.
Implementation of spaceborne lidar-retrieved canopy height in the WRF model.Crossref | GoogleScholarGoogle Scholar |

Lyons TJ (2002) Clouds prefer native vegetation. Meteorology and Atmospheric Physics 80, 131–140.
Clouds prefer native vegetation.Crossref | GoogleScholarGoogle Scholar |

Lyons TJ, Fuqin L, Hacker JM, Cheng W-L, Xinmei H (2001) Regional turbulent statistics over contrasting natural surfaces. Meteorology and Atmospheric Physics 78, 183–194.
Regional turbulent statistics over contrasting natural surfaces.Crossref | GoogleScholarGoogle Scholar |

McArthur AG (1967) ‘Fire behaviour in eucalypt forests.’ Forestry and Timber Bureau Leaflet no. 107. (Forestry and Timber Bureau: Canberra)

McCaw WL, Hanstrum B (2003) Fire environment of Mediterranean south-west Western Australia. In ‘Fire in ecosystems of south-west Western Australia: impacts and management’. (Eds I Abbott, N Burrows) pp. 87–106. (Backhuys Publishers: Kerkwerve, The Netherlands)

Mlawer EJ, Taubman SJ, Brown PD, Iacono MJ, Clough SA (1997) Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research, D, Atmospheres 102, 16663–16682.
Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave.Crossref | GoogleScholarGoogle Scholar |

Mount AB (1972) ‘The derivation and testing of a soil dryness index using run-off data’. Bulletin No. 4, Forestry Commission of Tasmania. (Forestry Commission: Hobart)

Noble IR, Gill AM, Bary GA (1980) McArthur’s fire-danger meters expressed as equations. Austral Ecology 5, 201–203.
McArthur’s fire-danger meters expressed as equations.Crossref | GoogleScholarGoogle Scholar |

Paget MJ, King EA (2008) ‘MODIS Land data sets for the Australian region’. CSIRO Marine and Atmospheric Research Internal Report, 004. (Canberra, ACT, Australia)10.4225/08/585C173339358.

Peace M, McCaw LW, Kepert JD, Mills GA, Mattner T (2015) WRF and SFIRE simulations of the Layman fuel reduction burn. Australian Meteorological and Oceanographic Journal 65, 302–317.
WRF and SFIRE simulations of the Layman fuel reduction burn.Crossref | GoogleScholarGoogle Scholar |

Perkins SE, Pitman AJ, Holbrook NJ, McAneney J (2007) Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. Journal of Climate 20, 4356–4376.
Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions.Crossref | GoogleScholarGoogle Scholar |

Pitman AJ, Narisma GT, McAneney J (2007) The impact of climate change on the risk of forest and grassland fires in Australia. Climatic Change 84, 383–401.
The impact of climate change on the risk of forest and grassland fires in Australia.Crossref | GoogleScholarGoogle Scholar |

Russell-Smith J, Yates CP, Whitehead PJ, Smith R, Craig R, Allan GE, Thackway R, Frakes I, Cridland S, Meyer MCP, Gill AM (2007) Bushfires ‘down under’: patterns and implications of contemporary Australian landscape burning. International Journal of Wildland Fire 16, 361–377.
Bushfires ‘down under’: patterns and implications of contemporary Australian landscape burning.Crossref | GoogleScholarGoogle Scholar |

Simard M, Pinto N, Fisher JB, Baccini A (2011) Mapping forest canopy height globally with spaceborne lidar. Journal of Geophysical Research 116, G04021
Mapping forest canopy height globally with spaceborne lidar.Crossref | GoogleScholarGoogle Scholar |

Simpson CC, Pearce HG, Sturman AP, Zawar-Reza P (2014) Verification of WRF modelled fire weather in the 2009–10 New Zealand fire season. International Journal of Wildland Fire 23, 34–45.
Verification of WRF modelled fire weather in the 2009–10 New Zealand fire season.Crossref | GoogleScholarGoogle Scholar |

Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang X-Y, Wang W, Powers JG (2008) ‘A description of the advanced research WRF version 3’. NCAR Technical Note NCAR/TN-475+STR. (National Center for Atmospheric Research: Boulder, CA, USA)10.5065/D68S4MVH.

Steffen W, Hughes L, Pearce A (2015) The heat is on: climate change, extreme heat and bushfires in WA. (Climate Council of Australia: Sydney, NSW) Available at: http://www.climatecouncil.org.au/uploads/7be174fe8c32ee1f3632d44e2cef501a.pdf [Verified 1 May 2018]

Williams AAJ, Karoly DJ, Tapper N (2001) The sensitivity of Australian fire danger to climate change. Climatic Change 49, 171–191.
The sensitivity of Australian fire danger to climate change.Crossref | GoogleScholarGoogle Scholar |

Xinmei H, Lyons TJ, Smith RCG (1995) Meteorological impact of replacing native perennial vegetation with annual agricultural species. Hydrological Processes 9, 645–654.
Meteorological impact of replacing native perennial vegetation with annual agricultural species.Crossref | GoogleScholarGoogle Scholar |