Development of a method with high-reliability to forecast the occurrence of location and time of local heavy rainfall within 24 hours.

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Forecasting method of local heavy rainfall was developed by using a model ensemble approach combining 32 member ensembles obtained from multiple parameterizations in the mesoscale meteorological model PSU/NCAR MM5. The multi-parameterization ensemble forecasts were combined with the model initialized using the 20km resolution global analyses JMA GSM-GPV with the Radar-data assimilation system. The forecasts averaged by 32 members are found to be very skillful in indicating the area of severe local storm activity, while each member deviates largely from the ensemble average.A new rainfall nowcasting approach based on the image processing method taking in complicated changes of rainfall area was developed, by evaluating the deformational errors between observed and predicted rainfall obtained by Japan Meteorological Agency(JMA) so as to minimize errors of the JMA rainfall nowcasting in real time based on its evaluation. Results of the verification experiments for intense rainfall events verified that the new approach can remarkably improve the accuracy of rainfall nowcasting by considering complicated deformation processes of rainfall area. Further, it made clear that the predictive value for one hour ahead forecasted by the new approach is at least 10% more accurate than that by the original JMA rainfall nowcasting.