Authors

Affiliations

The middle central Regional Hydro-Meteorological Center

The northern Red river delta Regional Hydro-Meteorological Center

Sai Gon University

*Corresponding author: vovanhoa80@yahoo.com

Abstracts

The paper presents the verification of capacity of heavy rainfall forecast IFS model by using the dataset of 75 automatic rain gauges collected of 59 heavy rainfall events of 2011-2018 rainfall seasons. The verification results based on ME, MAE, RMSE, R, BIAS, POD, FAR and ETS indices shown that the heavy rain forecast of IFS has good skill in forecast range of 1-3 days ahead. In addition, rainfall forecast of IFS model is over-estimated at small and medium rainfall thresholds and under-estimated in large and extreme large rainfall thresholds. The extreme rainfall forecast predictability of IFS model is good in some heavy rainfall events that caused by large-scale weather patterns. 

Keywords

Cite this paper

Le Viet Xe, Vo Van Hoa, Le Thai Son (2019), A verification of heavy rainfall evens forecast skill of IFS model at the Middle Central of Vietnam. Vietnam Journal of Hydrometeorology, 3, 48-55.

References

1. Cuong, H.D., et al., 2008. Research on heavy rainfall forecast in Viet Nam by using MM5 model. Scientific research project report of Ministry of Natural Resources and Environment, pp. 190.

2. Hang, V.T., Xin, K.T., 2007. The heavy rainfall forecast in the middle region of Viet Nam by using Heise convective parameterization scheme in HRM model. Scientific and Technical Hydro-Meteorological Journal, 660, 49-54.

3. Hoa, V.V., 2016. Comparison of heavy rainfall forecast skill of some global NWP models for the middle and central highland area of Viet Nam. Scientific and Technical Hydro-Meteorological Journal, 667, 1-8.

4. Hoa V. V., et al., (2012), Research on developing the short range enssemble prediction system (SREPS) for Viet Nam. Scientific research project report of Ministry of Natural Resources and Environment, pp. 188.

5. Hoa, V.V., et al., 2017. Research on using of ECMWF forecast dataset in order to improve operational seasonal and monthly prediction in Viet Nam. Scientific research project report of Ministry of Natural Resources and Environment, pp. 150.

6. Tang, B.V., et al., 2014. Developing the short range heavy rainfall forecast system to serve for flood early warning in the middle area of Viet Nam. Report of national scientific project, pp. 337.

7. Wilks, D.S., 2006. Statistical Methods in the Atmospheric Sciences. Academic Press, Second Edition, pp. 649.