The Construction and Examination of historical Fuel Moisture Parameters across Southern California

Wednesday, 17 December 2014
Cameron Whiteman1, Scott B Capps1 and Tom Rolinski2, (1)Vertum Partners, Los Angeles, CA, United States, (2)US Forest Service Riverside, Predictive Services, Riverside, CA, United States
A historical dataset containing various meteorological and wildfire fuel parameters has been constructed across southern California spanning from 1984 through 2013. Meteorological data provided by the North American Regional Reanalysis (NARR) dataset was dynamically downscaled to 3km horizontal resolution using the Weather Research and Forecasting (WRF) model. Wildfire fuel parameters within this dataset include Live Fuel Moisture (LFM), Normalized Difference Vegetative Index (NDVI), Energy Release Component (ERC), and both the ten hour and one hundred hour dead fuel moisture time-lags (F10 and F100 respectfully). NDVI and LFM were calculated using statistical models with predictors derived from the North American Land Data Assimilation System (NLDAS). Dead fuel moistures were calculated using the Nelson Dead Fuel Moisture model forced by the WRF output with an appropriate initial spin-up period for longer time-lag fuels. ERC was calculated using the National Fire Danger Rating System (NFDRS) algorithm with dead fuel moisture input supplied from the Nelson model, and meteorology from WRF. This historical dataset was used to guide and develop the multiple fuel and weather inputs into the Santa Ana Wildfire Threat index (SAWT), which is now operational. Additionally, current SAWT forecasts can now be placed into historical perspective with the use of this dataset. Applications for this unprecedented dataset will include correlation of historical fire activity to various fuel and weather parameters.