Applying the Multi-Scale, Multi-Resolution Data Assimilation Framework to Investigate the Predictability of Severe Weather in the Taiwan Area(2/3)

Project Details


Heavy rain and strong wind prediction in Taiwan is very challenging. Moreover, the predictability of severe weather in northern Taiwan is even more complicated due to the movement/development of the severe weather system, interaction with the environment or local circulation, microphysics and complex terrain. The convective-scale data assimilation and prediction actually involves forecast errors multi-scales. The proposal aims to study the predictability of the severe weather in northern Taiwan based on the observations collected during TAHOPE and PRECIP2020 and through the high-resolution, multi-scale data assimilation system. Particularly, we will focus on the assimilation of moisture observations and study the impact of moisture errors on the development of severe weather systems. As a preparation for TAHOPE, issues related to intensity prediction will be investigated based on the observation system experiments and observation system simulation experiments.
Effective start/end date1/08/1931/07/20

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 7 - Affordable and Clean Energy
  • SDG 11 - Sustainable Cities and Communities
  • SDG 17 - Partnerships for the Goals


  • severe weather prediction
  • data assimilation
  • Ensemble Kalman Filter
  • Heavy rainfall prediction
  • Strong wind prediction


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