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| Title | Evaluation of weather data at different spatial and temporal scales on fire behaviour prediction using PHOENIX RapidFire 4.0 - Kilmore Case Study |
| Publication Type | Report |
| Year of Publication | 2012 |
| Authors | Chong, D, Duff, TJ, Tolhurst, KG |
| Abstract | High resolution models might be expected to produce more accurate predictions, but in the case of weather forecasting data used to predict the spread of the 2009 Kilmore fire, this was not found to be true. Current weather forecasts are available on a 3600 m grid at hourly intervals. In time, computing power will enable finer spatial and temporal forecast weather to be produced operationally. This study was undertaken to understand what benefit finer scaled data might be to fire spread prediction. PHOENIX RapidFire was used to model the 2009 Kilmore fire with different spatial and temporal weather inputs. Because the fire of this size interacts with the local weather, it was found that courser level weather inputs performed better than very fine resolution data. Overall, weather forecasts at 30 minutes intervals and 1200 m spacing provided the best inputs for matching the progression of the fire. Once the fire had reached about 100,000 ha, 60 minute, 3600 m data gave the best predictions. Modelling weather at 400 m resolutions and at 5 minute intervals provides good insights into the dynamics of the weather which assists a weather forecaster, but that additional detail is not of the same benefit to fire spread predictions because large fires "smooth" the weather, terrain and fuel in the landscape. More case-studies need to be undertaken, including smaller fires burning under milder conditions to better understand the relationship between weather data scale and fire spread prediction. |
