The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea

Wang Ya; Wang Qingyuan; Liu Binxian

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Wang Ya, Wang Qingyuan, Liu Binxian. The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea[J]. Haiyang Xuebao, 2015, 37(9): 10-16.

Citation:

Wang Ya, Wang Qingyuan, Liu Binxian. The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea[J]. Haiyang Xuebao, 2015, 37(9): 10-16.

Wang Ya, Wang Qingyuan, Liu Binxian. The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea[J]. Haiyang Xuebao, 2015, 37(9): 10-16.

Citation:

Wang Ya, Wang Qingyuan, Liu Binxian. The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea[J]. Haiyang Xuebao, 2015, 37(9): 10-16.

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The ensemble wave forecast and test of cold air wave by using SWAN model in the Bohai Sea and the Yellow Sea

Tianjin Meteorological Observatory, Tianjin 300074, China

Received Date: 2014-09-12
Rev Recd Date: 2015-06-10

Abstract

Abstract

In the paper,a wave forecast system is established by running the wave model SWAN (Simulating Waves Nearshore). The forcing wind field in this system is reconstructed by the 51 members of EC ensemble weather forecast system. Then,a case study of the cold air during December 2013 to February 2014 is conducted to analysis the features of wave effected by the cold air using this system. Furthermore,using buoys data,the system forecasts are verified and compared. The main results are as follows: for the view of hourly mean bias,in 24 h forecast period the performance of ensemble mean is similar to control forecast,in 48 to 72 h forecast period the performance of ensemble mean is better than control forecast. The forecast of ensemble mean and control forecast are smaller than the reality. In both periods,the performance of ensemble statistics (75%,90% and extreme value) is better than control forecast and especially better in the long period of validity. Meanwhile,the forecast of ensemble extreme value is equal to or slightly larger than the reality; for the view of 24 hourly mean bias,the products of ensemble statistics (75%,90% and extreme value) are closer to the reality than the ensemble mean and control forecast value. To sum up,the products of ensemble statistics (75%,90% and extreme value) have higher accuracy of cold wave field. Conclusions show this system can improve the forecast level of wave influenced on cold air and have a good prospect of application.
- ensemble wave prediction,
- SWAN,
- cold air

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References(13)

References

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