1 Department of Meteorology, Hydrology and Climate change, Ho Chi Minh University of Natural Resources and Environment; email@example.com
2 Student of Department of Meteorology, Hydrology and Climate change, Ho Chi Minh University of Natural Resources and Environment; firstname.lastname@example.org
3 Department of General Science Ho Chi Minh University of Natural Resources and Environment; email@example.com; firstname.lastname@example.org
4 Department of Information Systems and Remote Sensing, Ho Chi Minh University of Natural Resources and Environment; email@example.com
*Corresponding author: firstname.lastname@example.org; Tel.: +84–936069249
This study applicates the multi–physical method in ensemble Kalman filter determining error of WRF models to forecast the track and intensity of storm Damrey in 2017. The study run three experiments with assimilation of satellite data to forecast Damrey in 2017 at the beginning 00 UTC and 12 UTC November 1st and 2nd: (1) 21 ensemble members which are combinated from 11 physics options, no increase in error correlation (MP); (2) Using single set of physical model, 21 ensemble members, inflation factor λ = 6.5 (MI); (3) Using single set of physical model, 21 ensemble members without increase in error correlation (PF). Statistical results of track errors in MP test at the 24, 48, 72–hour is 12–32% reduction in compared with tests MI and PF. For storm intensity, absolute error of Pmin in the MP test at 24 and 72–hour is decreased from 30–47% in compared to the other two tests. And the absolute error of Vmax in the MP test at all forecasting terms is 13–26% reduction in compared with tests MI and PF. Thus, the multi–physical ensemble Kalman filter can forecast the track and intensity of storms affecting Vietnam.
Cite this paper
Minh, P.T.; Trung, L.D.; Hang, T.N.; Tuong, H.T.T.; Thuy, K.P. Forecasting the track and intensity Damrey storm in 2017 by the multi–physical ensemble Kalman filter. VN J. Hydrometeorol. 2022, 11, 57-71.
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