Tuesday, 24 January 2012: 11:30 AM
Developing a Global, Short-Term Fire Weather Forecasting Tool Using NWP Input Meteorology and Satellite Fire Data
Room 238 (New Orleans Convention Center )
In order to meet the emerging need for better estimates of biomass burning emissions in air quality and climate models, a statistical model is developed to characterize the effect of a given set of meteorological conditions on the following day's fire activity, including ignition and spread potential. Preliminary tests are conducted within several spatial domains of the North American boreal forest by investigating a wide range of meteorological information, including operational fire weather forecasting indices, such as the Canadian Forest Fire Danger Rating System (CFFDRS). However, rather than using local noon surface station data, the six components of the CFFDRS are modified to use inputs from the North America Regional Reanalysis (NARR) and the Navy's Operational Global Atmospheric Prediction System Model (NOGAPS). The Initial Spread Index (ISI) and the Fire Weather Index (FWI) are shown to be the most relevant components of the CFFDRS for short-term changes in fire activity. However, both components are found to be highly sensitive to variations in relative humidity and wind speed input data. Several variables related to fire ignition from dry lighting, such as instability and the synoptic pattern, are also incorporated. Cases of fire ignition, growth, decay, and extinction are stratified using satellite fire observations from the Geostationary Operational Environmental Satellites (GOES) and the MODerate Resolution Imaging Spectroradiometer (MODIS) and compared to the available suite of meteorological information. These comparisons reveal that combinations of meteorological variables, such as the FWI, ISI, and additional indices developed for this study, produce the greatest separability between major fire growth and decay cases, which are defined by the observed change in fire counts and fire radiative power. This information is used to derive statistical relationships affecting the short-term changes in fire activity and subsequently applied to other spatial domains across North America, with the ultimate goal of producing a global, short-term fire weather forecasting tool.
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