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一種利用浮標(biāo)站資料改進(jìn)海浪模式有效波高預(yù)報(bào)的方法

單位：浙江省舟山市氣象局, 浙江舟山 316021

分類號(hào)：P731.34

出版年·卷·期（頁碼）：2020·37·第一期（50-54）

摘要：

基于浮標(biāo)站海浪歷史數(shù)據(jù)，利用回歸分析方法建立了海浪數(shù)值模式有效波高預(yù)報(bào)產(chǎn)品的一元二次回歸方程訂正統(tǒng)計(jì)模型。通過2017年7月1日—2018年10月10日期間業(yè)務(wù)試運(yùn)行結(jié)果發(fā)現(xiàn)：訂正方程能有效改善有效波高數(shù)值預(yù)報(bào)產(chǎn)品的預(yù)報(bào)精度，且預(yù)報(bào)時(shí)效越短訂正效果越顯著。其中，第6～11 h預(yù)報(bào)時(shí)效內(nèi)的訂正前后平均絕對(duì)誤差值減小0.17～0.241 m，第6～18 h預(yù)報(bào)時(shí)效內(nèi)訂正前后均方根誤差減小幅度為0.103～0.28 m。這說明應(yīng)用訂正統(tǒng)計(jì)模型對(duì)海浪模式輸出產(chǎn)品進(jìn)行訂正，也是改進(jìn)海浪模式預(yù)報(bào)準(zhǔn)確率的一種有效途徑。

Based on the historical wave data of the buoy station, this paper establishes a modified statistical model of the unary quadratic regression equation for the significant wave height prediction product of the wave numerical model using the regression analysis method. The results of the trial operation between July 1, 2017 and October 10, 2018 show that the revised equation has higher forecasting ability and can effectively improve the prediction accuracy of the significant wave height. The shorter prediction time, the more significant is the correction effect. The average absolute error decreases by 0.17-0.241 m and 0.103-0.28 m after correction within 6-11 h and 6-18 h forecast aging, respectively. It shows that establishing a modified statistical model to correct the output of wave model is an effective way to improve the accuracy of numerical wave prediction.

參考文獻(xiàn)：

[1] Makarynskyy O. Improving wave predictions with artificial neural networks[J]. Ocean Engineering, 2004, 31(5-6):709-724.
[2] 許富祥. 海浪預(yù)報(bào)現(xiàn)狀與未來[J]. 海洋預(yù)報(bào), 2005, 22(S1):172-175.
[3] 孟雷, 聞斌, 姜洪峰, 等. 神經(jīng)網(wǎng)絡(luò)方法對(duì)海浪有效波高數(shù)值模擬的改進(jìn)[J]. 海洋預(yù)報(bào), 2010, 27(2):8-14.
[4] 毛科峰, 蕭中樂, 王亮, 等. 數(shù)值模式與統(tǒng)計(jì)模型相耦合的近岸海浪預(yù)報(bào)方法[J]. 海洋學(xué)報(bào), 2014, 36(9):18-29.
[5] Sverdrup H U, Munk W H. Wind, sea and swell:theory of relation for forecasting[M]. Washington:U. S. Navy Hydrographic Office, 1947:44.
[6] Pierson W J Jr, Neumann J G, James R W. Practical methods for observing and forecasting Ocean waves by means of wave spectra and statistics[M]. Washington:U. S. Navy Hydrographic Office, 1955:284.
[7] 中華人民共和國交通部. 海港水文規(guī)范[M]. 北京:人民交通出版社, 1998.
[8] Özger M. Significant wave height forecasting using wavelet fuzzy logic approach[J]. Ocean Engineering, 2010, 37(16):1443-1451.
[9] Tseng C M, Jan C D, Wang J S, et al. Application of artificial neural networks in typhoon surge forecasting[J]. Ocean Engineering, 2007, 34(11-12):1757-1768.
[10] Zamani A, Solomatine D, Azimian A, et al. Learning from data for wind-wave forecasting[J]. Ocean Engineering, 2008, 35(10):953-962.
[11] 梅嬋娟, 趙棟梁, 史劍. 兩種海浪模式對(duì)中國黃海海域浪高模擬能力的比較[J]. 海洋預(yù)報(bào), 2008, 25(2):92-98.
[12] 江麗芳, 張志旭, 齊義泉, 等. WAVEWATCH Ⅲ和SWAN模式在南海北部海域海浪模擬結(jié)果的對(duì)比分析[J]. 熱帶海洋學(xué)報(bào), 2011, 30(5):27-37.
[13] 李燕, 黃振, 張俊峰, 等. WAVEWAT CH Ⅲ模式在渤海海浪預(yù)報(bào)的應(yīng)用與檢驗(yàn)[J]. 氣象與環(huán)境學(xué)報(bào), 2014, 30(1):23-29.
[14] 徐麗麗, 肖文軍, 石少華, 等. WaveWatch Ⅲ和SWAN模型嵌套技術(shù)在業(yè)務(wù)化海浪預(yù)報(bào)系統(tǒng)中的應(yīng)用及檢驗(yàn)[J]. 海洋通報(bào), 2015, 34(3):283-294.
[15] Tolman H L, Banner M L, Kaihatu J M. The NOPP operational wave model improvement project[J]. Ocean Modelling, 2013, 70:2-10.
[16] Dietrich J C, Zijlema M, Allier P E, et al. Limiters for spectral propagation velocities in SWAN[J]. Ocean Modelling, 2013, 70:85-102.
[17] Reikard G, Rogers W E. Forecasting ocean waves:comparing a physics-based model with statistical models[J]. Coastal Engineering, 2011, 58(5):409-416.
[18] 朱智慧, 曹慶, 徐杰. 神經(jīng)網(wǎng)絡(luò)方法在上海沿海海浪預(yù)報(bào)中的應(yīng)用[J]. 海洋預(yù)報(bào), 2018, 35(5):25-33.

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