An investigation of the differences between Real Time Mesoscale Analysis and observed meteorological conditions at RAWS stations in the northeast United States

Fire weather forecasts and the weather observations commonly used to determine fire danger and anticipate fire behavior derive from two different and often independent sources of meteorological information. Fire weather forecasts are produced from the National Digital Forecast Database (NDFD), which is a gridded analysis of meteorological fields generated by forecasters at National Weather Service forecast offices nationwide. The NDFD is verified by comparing its gridded meteorological fields against the Real Time Mesoscale Analysis (RTMA), which is an advanced modeling and data assimilation system that employs METAR (aviation weather station) and mesonet data to provide the best-available 5-km gridded estimate of surface and near-surface conditions on an hourly basis. The meteorological observations used to assess fire danger and to predict possible fire behavior are collected at Remote Automated Weather Stations (RAWS). RAWS stations are not routinely incorporated into the RTMA in all regions of the United States, and therefore are not used to verify the NDFD.

This Joint Fire Science Plan sponsored project is working to document the manner in which RAWS observations differ from the RTMA, and by association the NDFD. Our study area is the northeastern United States, which is a densely populated and heavily forested region of the country where numerous prescribed burns and wildfires occur each year. We are performing a statistical comparison between the RTMA and RAWS stations for two years of hourly weather data from August 2008 through August 2010. Systematic differences between the two sources of meteorological information are being quantified, and the influence of land surface characteristics, elevation, topography, diurnal patterns, and other factors are being investigated. When the project is completed, we will recommend methods by which these differences can be accounted for when preparing fire weather forecasts and making fire management decisions.