Wind vector change and fire weather index in New Zealand as a modified metric in evaluating fire danger
Siena Brody-Heine A * , Jiawei Zhang
A B , Marwan Katurji A , H. Grant Pearce C and Michael Kittridge A
+ Author Affiliations
- Author Affiliations
A University of Canterbury, School of Earth and Environment, Christchurch, New Zealand.
B Scion, New Zealand Forest Research Institute Limited, Christchurch, New Zealand.
C Fire and Emergency New Zealand, Christchurch, New Zealand.
* Correspondence to: siena.brody@gmail.com
International Journal of Wildland Fire 32(6) 872-885 https://doi.org/10.1071/WF22106
Submitted: 23 June 2022 Accepted: 16 March 2023 Published: 31 March 2023
© 2023 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Background: Wildfire spread is influenced significantly by the weather variability. Wind speed and direction changes, resulting from synoptic weather systems and small-scale meteorological processes in complex terrain, can drastically alter fire intensity and spread.
Aims: To investigate the use of vector wind change (VWC) integrated with the Fire Weather Index (FWI) as a new metric in fire danger.
Methods: A 20-year FWI and modified FWI was calculated from weather station and gridded numerical weather simulation data.
Key results: High VWC is found primarily on the South Island, inland and in areas of complex terrain. After incorporating VWC into the FWI, data from the modified FWI show spatiotemporal patterns that highlight the impact of wind variability in the fire danger.
Conclusions: High VWC station data mapped with synoptic type suggest the primary factor in determining high VWC is meso- and micro-scale terrain-driven meteorology, not larger synoptic regimes.
Implications: The current fire danger metric, the Fire Weather Index (FWI), does not include wind direction changes for high wind speeds. Therefore, the inclusion of VWC as an additional metric in fire danger calculations in a modified FWI could increase operational understanding of high-danger locations and terrain impacts on extreme and unpredictable fire behaviour.
Keywords: danger, fire behaviour, fire severity, FWI, mesoscale meterology, vector wind change, weather, wildfire risk.
References
AFAC (2017) ‘Independent Operational Review: Port Hills Fires – February 2017.’ (Australasian Fire and Emergency Service Authorities Council Limited: East Melbourne, Vic.)AFAC (2019) ‘AFAC Independent Operational Review: A review of the management of the Tasman fires of February 2019.’ (Australasian Fire and Emergency Service Authorities Council Limited: East Melbourne, Vic.)
Alexander ME (2010) Feasibility study for the setting up of a global wildland fire danger rating system (Study Report for Contract No. P200915719ALEX). (European Commission, Joint Research Centre, Institute of Environment and Sustainability, Land Management and Natural Hazards Unit: Ispra, Italy)
Amiro BD, Logan KA, Wotton BM, Flannigan MD, Todd JB, Stocks BJ, Martell DL (2004) Fire Weather Index system components for large fires in the Canadian boreal forest. International Journal of Wildland Fire 13, 391–400.
| Fire Weather Index system components for large fires in the Canadian boreal forest.Crossref | GoogleScholarGoogle Scholar |
Anderson S (2005) Forest and rural fire danger rating in New Zealand. In ‘Forestry Handbook’. (Ed. M Colley) pp. 241–244. (New Zealand Institute of Forestry: Christchurch, NZ)
Avolio E, Federico S, Miglietta MM, Lo Feudo T, Calidonna CR, Sempreviva AM (2017) Sensitivity analysis of WRF model PBL schemes in simulating boundary-layer variables in southern Italy: An experimental campaign. Atmospheric Research 192, 58–71.
| Sensitivity analysis of WRF model PBL schemes in simulating boundary-layer variables in southern Italy: An experimental campaign.Crossref | GoogleScholarGoogle Scholar |
Banks RF, Baldasano JM (2016) Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain. Science of The Total Environment 572, 98–113.
| Impact of WRF model PBL schemes on air quality simulations over Catalonia, Spain.Crossref | GoogleScholarGoogle Scholar |
Boadh R, Satyanarayana ANV, Rama Krishna TVBPS, Madala S (2016) Sensitivity of PBL schemes of the WRF-ARW model in simulating the boundary layer flow parameters for their application to air pollution dispersion modeling over a tropical station. Atmósfera 29, 61–81.
| Sensitivity of PBL schemes of the WRF-ARW model in simulating the boundary layer flow parameters for their application to air pollution dispersion modeling over a tropical station.Crossref | GoogleScholarGoogle Scholar |
Cheney P, Gould J, McCaw L (2001) The Dead-Man Zone – a neglected area of firefighter safety. Australian Forestry 64, 45–50.
| The Dead-Man Zone – a neglected area of firefighter safety.Crossref | GoogleScholarGoogle Scholar |
Dong L, Leung LR, Qian Y, Zou Y, Song F, Chen X (2021) Meteorological environments associated with California wildfires and their potential roles in wildfire changes during 1984–2017. Journal of Geophysical Research: Atmospheres 126, e2020JD033180
| Meteorological environments associated with California wildfires and their potential roles in wildfire changes during 1984–2017.Crossref | GoogleScholarGoogle Scholar |
Foley J (2020) ‘Fire and Emergency New Zealand Wildfire Investigation Report: Lake Ohau Fire.’ (Fire and Emergency New Zealand: Wellington)
Forestry Canada Fire Danger Group (1992) Development and structure of the Canadian Forest Fire Behavior Prediction System. Information Report ST-X-3. (Forestry Canada, Science and Sustainable Development Directorate: Ottawa, ON)
Harris S, Mills G, Brown T (2017) Variability and drivers of extreme fire weather in fire-prone areas of south-eastern Australia. International Journal of Wildland Fire 26, 177–190.
| Variability and drivers of extreme fire weather in fire-prone areas of south-eastern Australia.Crossref | GoogleScholarGoogle Scholar |
Hilton JE, Miller C, Sullivan AL, Rucinski C (2015) Effects of spatial and temporal variation in environmental conditions on simulation of wildfire spread. Environmental Modelling & Software 67, 118–127.
| Effects of spatial and temporal variation in environmental conditions on simulation of wildfire spread.Crossref | GoogleScholarGoogle Scholar |
Huang X, Mills G (2006a) Objective identification of wind change timing from single station observations. Part 2: Towards the concept of a wind change climatology. Australian Meteorological Magazine 55, 275–288.
Huang X, Mills G (2006b) Objective identification of wind change timing from single station observations. Part 1: Methodology and comparison with subjective wind change timings. Australian Meteorological Magazine 55, 261–274.
Kidson JW (2000) An analysis of New Zealand synoptic types and their use in defining weather regimes. International Journal of Climatology 20, 299–316.
| An analysis of New Zealand synoptic types and their use in defining weather regimes.Crossref | GoogleScholarGoogle Scholar |
Kitteridge M (2021) Tethysts. Available at https://tethysts.readthedocs.io/en/latest/license-terms.html
Macara G (2021) ‘Annual Climate Summary.’ (NIWA National Climate Centre: Auckland)
Mahrt L (2011) Surface wind direction variability. Journal of Applied Meteorology and Climatology 50, 144–152.
| Surface wind direction variability.Crossref | GoogleScholarGoogle Scholar |
Mandal A, Nykiel G, Strzyzewski T, Kochanski A, Wrońska W, Gruszczynska M, Figurski M (2021) High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model. International Journal of Wildland Fire 31, 149–162.
| High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model.Crossref | GoogleScholarGoogle Scholar |
Mills G, Harris S, Brown T, Chen A (2020) Climatology of wind changes and elevated fire danger over Victoria, Australia. Journal of Southern Hemisphere Earth Systems Science 70, 290–303.
| Climatology of wind changes and elevated fire danger over Victoria, Australia.Crossref | GoogleScholarGoogle Scholar |
Mughal MO, Lynch M, Yu F, McGann B, Jeanneret F, Sutton J (2017) Wind modelling, validation and sensitivity study using Weather Research and Forecasting model in complex terrain. Environmental Modelling & Software 90, 107–125.
| Wind modelling, validation and sensitivity study using Weather Research and Forecasting model in complex terrain.Crossref | GoogleScholarGoogle Scholar |
Pan X, Li X, Shi X, Han X, Luo L, Wang L (2012) Dynamic downscaling of near-surface air temperature at the basin scale using WRF-a case study in the Heihe River Basin, China. Frontiers of Earth Science 6, 314–323.
| Dynamic downscaling of near-surface air temperature at the basin scale using WRF-a case study in the Heihe River Basin, China.Crossref | GoogleScholarGoogle Scholar |
Pearce HG (2018) The 2017 Port Hills wildfires – a window into New Zealand’s fire future? Australasian Journal of Disaster and Trauma Studies 22, 35–50.
Pearce HG, Alexander ME (1994) Fire danger ratings associated with New Zealand’s major pine plantation wildfires. In ‘Proceedings, 12th Conference on Fire and Forest Meteorology’, 25–29 October 1993, Jekyll Island, GA, USA. (SAF Publication 94-02) (Eds JM Saveland, J Cohen) pp. 534–543. (Society of American Foresters: Bethesda, MD)
Pretorius I, Sturman A, Strand T, Katurji M, Pearce G (2020) A meteorological study of the Port Hills Fire, Christchurch, New Zealand. Journal of Applied Meteorology and Climatology 59, 263–280.
| A meteorological study of the Port Hills Fire, Christchurch, New Zealand.Crossref | GoogleScholarGoogle Scholar |
Renwick J (2021) Kidson Type Time Series New Zealand 1948-2021.
Scion (2020) New Zealand Seasonal Fire Danger Outlooks. Available at https://www.ruralfireresearch.co.nz/tools/new-zealand-seasonal-fire-danger-outlooks
Simpson CC, Grant Pearce H, Sturman AP, Zawar-Reza P (2014) Behaviour of fire weather indices in the 2009–10 New Zealand wildland fire season. International Journal of Wildland Fire 23, 1147–1164.
| Behaviour of fire weather indices in the 2009–10 New Zealand wildland fire season.Crossref | GoogleScholarGoogle Scholar |
Solbakken K, Birkelund Y, Samuelsen EM (2021) Evaluation of surface wind using WRF in complex terrain: Atmospheric input data and grid spacing. Environmental Modelling & Software 145, 105182
| Evaluation of surface wind using WRF in complex terrain: Atmospheric input data and grid spacing.Crossref | GoogleScholarGoogle Scholar |
Sturman AP, Tapper NJ (2006) ‘ The weather and climate of Australia and New Zealand’, 2nd edn. 541 pp. (Oxford University Press)
Van Wagner CE (1987) Development and structure of the Canadian Forest Fire Weather Index System. Forestry Technical Report 35. (Canadian Forestry Service: Ottawa, ON)
Werth PA, Potter BE, Alexander ME, Clements CB, Cruz MG, Finney MA, Forthofer JM, Goodrick SL, Hoffman C, Jolly WM, Mcallister SS, Ottmar RD, Parsons RA (2016) Synthesis of Knowledge of Extreme Fire Behavior: Volume 2 for fire behavior specialists, researchers, and meteorologists. General Technical Report PNW-GTR-891. (USDA Forest Service, Pacific Northwest Research Station: Portland, OR)
Wotton BM (2009) Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications. Environmental and Ecological Statistics 16, 107–131.
| Interpreting and using outputs from the Canadian Forest Fire Danger Rating System in research applications.Crossref | GoogleScholarGoogle Scholar |
Wotton BM, Alexander ME, Taylor SW (2009) Updates and revisions to the 1992 Canadian Forest Fire Behavior Prediction System. Information Report GLC-X-10. (Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre: Sault Ste Marie, ON)
