Assessments of Use of Blended Radar–Numerical Weather Prediction Product in Short-Range Warning of Intense Rainstorms in Localized Systems (SWIRLS) for Quantitative Precipitation Forecast of Tropical Cyclone Landfall on Vietnam’s Coast

Author:

Hung Mai Khanh12,Tien Du Duc1,Quan Dang Dinh1,Duc Tran Anh13ORCID,Dung Pham Thi Phuong1,Hole Lars R.4ORCID,Nam Hoang Gia1

Affiliation:

1. Vietnam National Center for Hydro-Meteorological Forecasting, 8 Phao Dai Lang Str., Hanoi 100000, Vietnam

2. Institute of Engineering Innovation, The University of Tokyo, Tokyo 113-8656, Japan

3. Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, 82467 Garmisch-Partenkirchen, Germany

4. Norwegian Meteorological Institute, 5007 Bergen, Norway

Abstract

This research presents a blended system implemented by the Vietnam National Center for Hydro-Meteorological Forecasting to enhance the nowcasting and forecasting services of quantitative precipitation forecasts (QPFs) of tropical cyclone (TC) landfalls on Vietnam’s coast. Firstly, the extrapolations of rain/convective systems from multiple radars in Vietnam in ranges up to 6 h were carried out using Short-Range Warning of Intense Rainstorms in Localized Systems (SWIRLS) developed by the Hong Kong Observatory. Secondly, the forecast from the numerical weather prediction (NWP) system, based on the WRF-ARW model running at 3 km horizontal resolution, was blended with radar-based quantitative precipitation estimates and nowcasts of SWIRLS. The analysis showed that the application of the nowcast system to TC-related cloud forms is complicated, which is related to the TC’s evolution and the different types and multiple layers of storm clouds that can affect the accuracy of the derived motion fields in nowcast systems. With hourly accumulated rainfall observation, skill score validation conducted for several TCs that landed in the center of Vietnam demonstrated that the blending of nowcasting and NWP improve the quality of the QPFs of TCs in forecast ranges up to 3 h compared to the pure NWP forecasts.

Publisher

MDPI AG

Subject

Atmospheric Science,Environmental Science (miscellaneous)

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