This map shows the predicted area of high fire potential for the current
year up to the end of the forecast period as simulated by a modified version of
the MC1 Dynamic General Vegetation Model (DGVM). Different colors indicate the level of
consensus among five different MC1 simulations
(i.e., one for each forecast provided by five different weather models), ranging from one of five to five of five
simulations predicting high fire potential.
The area of high fire potential is
where PDSI and MC1-calculated values of potential fire behavior (fireline intensity
for forest and shrubland and rate of spread of spread for grassland) exceed
calibrated threshold values.
Potential fire behavior in MC1 is estimated using National
Fire Danger Rating System (NFDRS) formulas, monthly climatic (temperature,
precipitation, and relative humidity) data, and fuel moisture and loading estimates.
Monthly climatic data includes
recorded values up to the last observed month and forecast values provided by different weather models.
Future climate forecasts have been made available through cooperation with the
International Research Institute for Climate Prediction (IRI) of Columbia University
which provides monthly updates of 7-month future climate forecasts from
five different general circulation models (GCMs) of the global
atmosphere. GCM results come from the University of Maryland
(COLA), the University of Hamburg (ECHAM4.5), the National Weather
Service’s Climate Prediction Center (NCEP), NASA’s Goddard Institute of
Space Studies (NSIPP), and the Scripps Oceanographic Institute (ECPC).
Dead fuel moisture is dynamically
estimated from the climatic data using standard formulas that account for lags
in wetting and drying in different fuel-size classes.
Live fuel moisture is dynamically
estimated as a function of soil moisture calculated by the MC1 hydrological
module.
The version of MC1 modified for fire potential forecasting reads static
fuel loads from the NFDRS Fuel Model Map, with the critical exception of
herbaceous fuel loading which remains dynamically estimated by the MC1
vegetation production module.