Improving Wrf-Letkf Radar Assimilation for Heavy Rainfall Prediction with Different Characteristics

Project Details


The project aims to advance the WRF-LETKF radar assimilation system (WLRAS) to provide multi-scale corrections and further improve heavy rainfall at different scales. WLRAS will also be optimized to assimilate large volume of data from the CWB radar network.For the heavy rainfall associated with synoptic-meso scale, we plan to implement the dual-localization for multi-domains to derive the multi-scale analysis corrections from the radar and surface data and expect improvement for predicting the long-life heavy rainfall. On the other hand, for improving the small-scale characteristics and short-life heavy rainfall events, we plan to better use the high-resolution radar observations by increasing the resolution of the superobs. This will be achieved by using a correlated observation error covariance in WLRAS.
Effective start/end date1/08/2031/07/21

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities
  • SDG 17 - Partnerships for the Goals


  • Data assimilation
  • Ensemble Kalman Filter
  • Radar observation
  • heavy rainfall prediction


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