Modeling the wind-fields of accidental releases by mesoscale forecasting

Modeling atmospheric releases even during fair weather can present a sever challenge to diagnostic, observed-data-driven, models. Such schemes are often handicapped by sparse input data from meteorological surface stations and soundings. Forecasting by persistence is only acceptable for a few hours and cannot predict important changes in the diurnal cycle or from synoptic evolution. Many accident scenarios are data-sparse in space and/or time. Here we describe the potential value of limited-area, mesoscale, forecast models for real-time emergency response. Simulated wind-fields will be passed to ARAC`s operational models to produce improved forecasts of dispersion following accidents