Accurate regional weather forecasts are critical to successful wildfire operations and prescribed burns. Computer forecast models produce indispensable information about atmospheric conditions, but they can also generate some significant inaccuracies, most notably in relative humidity, ambient temperature, wind speed and direction. Accurate forecasts of these weather components are vital for successful assessment of fire danger. This project sought to improve the accuracy of forecast models, like MM5, which was used until recently by the USDA Forest Service, Rocky Mountain Center to predict fire weather over the western U.S. This project increased forecast accuracy by coupling MM5 with a new forecast model called FORFLUX. The combination, known as MFF, improves accuracy by measuring how much moisture will end up in the atmosphere as a result of ecosystem processes taking place at the earth's surface. MFF improves weather forecasts by providing more data about of the interactions between vegetation, soil and atmosphere and their resulting impacts on regional fire weather.