MC1 DGVM fire potential forecast January-August 2012 (based on ECPC 7-month weather forecast)
Dates
Original Data Basin Creation Date
2012-03-26 09:07:08
Original Data Basin Modified Date
2012-07-10 00:12:09
Summary
This dataset 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). 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 [...]
Summary
This dataset 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).
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 the weather model identified in the dataset title.
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.
