A new approach is developed to forecast the fire radiative power (FRP) observed by the satellite sensor with a lead time of one day. The method is based on a threshold autoregression model. Visualization of the t-statistics of the sorted time series has helped to discern six regimes, for which the model coefficients were specified separately. Nesterov fire index was used as one of the predictors. Data for European part of Russia for summer 2010 were used. It was shown that threshold autoregression forecast is superior to inertial forecast of FRP. Aerosols emissions (PM10 concentrations) were also predicted based on FRP forecast for the next day. The forecast errors were lower then the errors of inertial forecast of PM10 for four of six regimes that were dominating either in terms of number or coverage area. The method will be incorporated into the air quality model.
fires, forecast, radiative power, satellite measurements, threshold autoregression