Improvement of displacement error of rainfall and wind field forecast associated with landfalling tropical cyclone AMPHAN

被引:2
作者
Kotal, S. D. [1 ]
Bhattacharya, S. K. [1 ]
机构
[1] Govt India, India Meteorol Dept Minist Earth Sci, New Delhi, India
关键词
Tropical cyclone; Track forecast; Rainfall forecast; Wind fi eld; Spatial distribution; North Indian ocean; PART I; DATA ASSIMILATION; PRECIPITATION; PREDICTION; MODEL; EVOLUTION; SYSTEM;
D O I
10.1016/j.tcrr.2022.09.004
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Spatial distribution of rainfall and wind speed forecast errors associated with landfalling tropical cyclones (TC) occur significantly due to incorrect location forecast by numerical models. Two major areas of errors are: (i) over-estimation over the model forecast locations and (ii) underestimation over the observed locations of the TCs. A modification method is proposed for real-time improvement of rainfall and wind field forecasts and demonstrated for the typical TC AMPHAN over the Bay of Bengal in 2020. The proposed method to improve the model forecasts is a relocation method through shifting of model forecast locations of TC to the real-time official forecast locations of India Meteorological Department (IMD). The modification is applied to the forecasts obtained from the operational numerical model, the Global Forecast System (GFS) of IMD. Application of the proposed method shows considerable improvement of both the parameters over both the locations. The rainfall forecast errors due to displacement are found to have improved by 44.1%-69.8% and 72.1%-85.2% over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 48 h, 72 h, and 96 h. Similarly, the wind speed forecasts have improved by 27.6%- 56.0% and 63.7%-84.6% over the GFS forecast locations and over the observed locations respectively for the respective forecast lead times 60 h, 72 h, and 84 h. The results show that the proposed technique has capacity to provide improved spatial distributions of rainfall and wind speed forecasts associated with landfalling TCs and useful guidance to operational forecasters.(c) 2022 The Shanghai Typhoon Institute of China Meteorological Administration. Publishing services by Elsevier B.V. on behalf of KeAi Communication Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:146 / 162
页数:17
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