Fire weather simulation skill by the Weather Research and Forecasting (WRF) model over south-east Australia from 1985 to 2009
Hamish Clarke A B D , Jason P. Evans A and Andrew J. Pitman C
+ Author Affiliations
- Author Affiliations
A Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia.
B Climate and Atmospheric Science Branch, NSW Office of Environment and Heritage, PO Box A290, Sydney South, NSW 1232, Australia.
C ARC Centre of Excellence for Climate System Science, University of New South Wales, Sydney, NSW 2052, Australia.
D Corresponding author. Email: h.clarke@student.unsw.edu.au
International Journal of Wildland Fire 22(6) 739-756 https://doi.org/10.1071/WF12048
Submitted: 28 March 2012 Accepted: 3 January 2013 Published: 13 May 2013
Abstract
The fire weather of south-east Australia from 1985 to 2009 has been simulated using the Weather Research and Forecasting (WRF) model. The US National Oceanic and Atmospheric Administration Centers for Environmental Prediction and National Center for Atmospheric Research reanalysis supplied the lateral boundary conditions and initial conditions. The model simulated climate and the reanalysis were evaluated against station-based observations of the McArthur Forest Fire Danger Index (FFDI) using probability density function skill scores, annual cumulative FFDI and days per year with FFDI above 50. WRF simulated the main features of the FFDI distribution and its spatial variation, with an overall positive bias. Errors in average FFDI were caused mostly by errors in the ability of WRF to simulate relative humidity. In contrast, errors in extreme FFDI values were driven mainly by WRF errors in wind speed simulation. However, in both cases the quality of the observed data is difficult to ascertain. WRF run with 50-km grid spacing did not consistently improve upon the reanalysis statistics. Decreasing the grid spacing to 10 km led to fire weather that was generally closer to observations than the reanalysis across the full range of evaluation metrics used here. This suggests it is a very useful tool for modelling fire weather over the entire landscape of south-east Australia.
Additional keywords: bush fire, McArthur Forest Fire Danger Index (FFDI), model evaluation, model grid spacing, reanalysis, regional climate model (RCM), wildland fire.
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