Predictability of Precipitation from Continental Radar Images. Part III: Operational Nowcasting Implementation (MAPLE)

• DOI: 10.1175/1520-0450(2004)043<0231:popfcr>2.0.co;2
• Publication Date: 2004-02-26T16:36:35Z
• Authors: B. J. Turner; I. Zawadzki; U. Germann
• Keywords: Nowcasting; Predictability; Quantitative precipitation forecast

Filtering of nonpredictable scales precipitation can be used to improve forecast precision (rms). Previous papers have studied the scale dependence predictability patterns instantaneous rainfall rate and probabilistic forecasts. In this paper, motivated by often localized, intermittent nature rainfall, wavelet transform is develop measures at each scale. These are then design optimal filters. This method applied radar composites reflectivity over much continental United States developed appropriate for operational forecasts rates raining areas. For four events studied, average correlation 4-h lead time was increased from 0.50 original nowcasts 0.62 with filtering. filtering incorporated into McGill Algorithm Precipitation Nowcasting Lagrangian Extrapolation (MAPLE), which now includes variational echo tracking, a semi-Lagrangian advection scheme, scale-based filtering, rescaling filtered nowcast fields.