A MODEL FOR REAL-TIME QUANTITATIVE RAINFALL FORECASTING USING REMOTE-SENSING .1. FORMULATION

A physically based rainfall forecasting model for real-time hydrologic applications is developed with emphasis on utilization of remote sens ing observations. Temporal and spatial scales of interest are lead tim es of the order of hours and areas of the order of 10 km2. The dynamic model is derived from conservation of mass in a cloud column as defin ed by the continuity equations for air, liquid water, water vapor, and cloud water. Conservation of momentum is modeled using a semi-Lagrang ian frame of reference. The model state is vertically integrated liqui d water content in a column of the atmosphere. Additionally, laws of t hermodynamics, adiabatic air parcel theory, and cloud microphysics are applied to derive a basic parameterization of the governing equations of model dynamics. The parameterization is in terms of hydrometeorolo gic observables including radar reflectivity, satellite-infrared brigh tness temperature, and ground-level air temperature, dew point tempera ture, and pressure. Implementation and application is described by Fre nch et al. (this issue) and involves incorporation of uncertainty anal ysis and a two-dimensional spatial domain, where the dynamics of the c ontinuous space-time rainfall process are discretized onto a rectangul ar grid.