Wednesday, 19 November 2003: 10:45 AM
Fire Danger Forecasts
The Scripps Experimental Climate Prediction Center (ECPC) has been making routine experimental, near real-time weekly to seasonal fire danger forecasts for the past 5 years. Images from these forecasts are regularly shown on the worldwide web (WWW) site (http://ecpc.ucsd.edu/) as well as a number of other national and international sites (e.g. the Global Fire Monitoring Center http://www.fire.uni-freiburg.de/). The global model is a version of the National Centers for Environmental Prediction’s (NCEP’s) global spectral model used for the NCEP/NCAR reanalysis. With the GSM forecasts as boundary conditions a higher resolution regional spectral model (RSM) is also run for various regions to provide increased geophysical detail. The initial conditions and SST boundary conditions for these experimental global forecasts come from the NCEP Global Data Assimilation (GDAS) 00UTC operational analysis, which is available nearly every day in near real time on rotating disk archives, to interested researchers. Transforming NCEP’s higher-resolution operational global analyses to lower (vertical and horizontal) resolution initial conditions for the global model, 7-day global and regional forecasts are made every day and every weekend these global and regional forecasts are extended to 16 weeks. The purpose of this talk is to describe ECPC's forecast and analysis system of fire danger, which is based on the US National Fire Danger Rating System (NFDRS). NFDRS fire danger indices currently being forecast for the US include the Ignition Component (IC), Energy Release component (ER), Burning Index (BI), Spread Component (SC), Keetch Byram drought index (KB), and the Fosberg fire weather index (FWI). The FWI is also forecast globally. As will be shown, all indices can be predicted well at weekly times scales and have some skill even out to seasonal time scales in certain locations. Comparisons of these fire danger predictions to actual fire characteristics (incidents and extent) are being analyzed for parts of the US and will be presented at the conference.
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