Dynamic downscaling based on weather types classification: An application to extreme rainfall in south-east Japan

Dynamic downscaling based on weather types classification: An application to extreme rainfall in south-east Japan

By J.F Vuillaume and S Herath

  • Optimization of weather forecast systems is crucial for efficient real-time weather predictions.
  • This research focuses on optimizing the physical scheme of numerical weather prediction for the south-east coast of Japan, specifically the Tokyo area.
  • Weather types are used to cluster and optimize the physical scheme.
  • Calibration and validation of physical schemes were done using observed rainfall at gauge stations near Tokyo, categorized by weather circulation.
  • 24 ensemble members and 20 heavy rainfall events from 4 weather types were used for validation.
  • The physical scheme ensemble consisted of micro-physics, cumulus, planetary boundary, and radiative schemes, simulated using the weather research and forecasting model.
  • Limited physical scheme variability was observed within a weather type cluster for a station pool, but significant variations were present among stations.
  • Rainfall Cumulative Probability Distribution Function curves were computed, showing wide differences due to clustering.
  • Results allowed for:
    • Selection of optimal physical scheme for each weather type.
    • Development of weather type-specific bias correction curves.
    • Evaluation of spatial distribution of regional bias correction.
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