Abstract
To improve short-term (i.e., less than one hour) forecasting, a cell-tracking algorithm was applied to meso-γ-scale convective systems (MγCSs). Composite surface rainfall data derived from an X-band multiparameter radar and operational C-band radars of the Japan Meteorological Agency (JMA) were used as initial data and the Algorithm for the Identification and Tracking Convective Cells (AITCC) was used to estimate the movement vectors of MγCSs. The results demonstrate that the cell-tracking system improves forecasting of hourly rainfall compared with conventional pattern-matching extrapolation, especially for quasi-stationary rainfall systems such as back-building storms.
