基于环杭州湾县区多年实测风速资料,采用资料整理法分析风速时空分布规律,利用嵊泗站近65 a实测风速和台风最佳路径资料,基于多元回归分析法建立台风期嵊泗风速计算公式,结合湾顶乍浦增水情况,采用理论分析法建立乍浦风暴潮增水计算式,将6种不同风浪公式预测值与多年实测波浪进行比较,确定杭州湾风浪公式适用性。结果表明：环杭州湾风速总体呈下降趋势,下降速率呈“南岸>北岸>海岛”的分布特点;风速大小整体呈“海岛>北岸>南岸”的分布特点,越往内陆风速越小,最大风速和平均风速比值k与平均风速大小呈反相关;杭州湾风速相关性较高,平均相关系数为0.66,风速相关性随距离的增加而降低,海岛相关性最高,杭州湾北岸与南岸相关性最差;小风区海湾风浪联系式和基本式差异较小,大风区海湾风浪计算建议采用风浪基本式,杭州湾大风期风速和波高关系基本服从莆田风浪基本式。
Abstract
In this study, the spatial and temporal distributions of wind speed are analyzed based on many years of measured wind speed data from the region around Hangzhou Bay. Using 65 years of measured wind speed and typhoon best-track data from Shengsi Station, a multiple regression analysis method is used to establish a formula to calculate wind speed during typhoons at Shengsi. Storm surge water level increase data from Zhapu in the northern region of Hangzhou Bay are combined with theoretical analysis to establish a formula to calculate storm surge water increase in Zhapu. Finally, the applicability of 6 different wind wave formulas for Hangzhou Bay are assessed by comparing the predicted values against observed wave measurements at Zhapu Station. The results show that the wind speed generally shows a decreasing trend in the reqion around Hangzhou Bay, with the largest decrease in magnitude occurring near the south bank of Hangzhou Bay, followed by the north bank of Hangzhou Bay and then the islands. The wind speed decreases as it moves further inland, with wind speed on the islands being the greatest, followed by the north bank and the south bank of Hangzhou Bay. The ratio k between the maximum wind speed and the average wind speed is inversely correlated with the average wind speed. The correlation of wind speed in Hangzhou Bay is high, with an average correlation coefficient of 0.66. The wind speed correlation decreases with increasing distance, and the correlation among islands is the highest, followed by the north bank and then the south bank of Hangzhou Bay. There is little difference between the connection formula and the basic formula in a short wind field, but there is a significant difference in the long wind field. The relationship between wind speed and wave height in Hangzhou Bay during periods of strong winds essentially obeys the Putian basic formula. It is advisable to calculate wind waves in the bay for a long wind field using the basic formula.
关键词
杭州湾 /
时空数据 /
风速 /
潮汐 /
波浪传播 /
相关性
Key words
Hangzhou Bay /
spatio-temporal data /
wind speed /
tides /
wave propagation /
correlation
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 梁超, 刘永前, 周家慷, 等. 基于卷积循环神经网络的风电场内多点位风速预测方法[J]. 电网技术, 2021, 45(2): 534-542.LIANG C, LIU Y Q, ZHOU J K, et al. Wind speed prediction at multi-locations based on combination of recurrent and convolutional neural networks[J]. Power system technology, 2021, 45(2): 534-542.
[2] PELSER T, WEINAND J M, KUCKERTZ P, et al.Reviewing accuracy & reproducibility of large-scale wind resource assessments[J]. Advances in applied energy, 2024, 13: 100158.
[3] LIANG J, KATO B, WANG Y.Constructing simplified models for dynamic analysis of monopile-supported offshore wind turbines[J]. Ocean engineering, 2023, 271: 113785.
[4] 林逸凡, 杨梓豪, 刘玉飞, 等. 中国沿海风电施工窗口期及功效分析[J]. 太阳能学报, 2023, 44(1): 273-280.LIN Y F, YANG Z H, LIU Y F, et al. Analysis of weather window and construction efficiency for wind power development in offshore China[J]. Acta energiae solaris sinica, 2023, 44(1): 273-280.
[5] LIU F, SUN F B, LIU W B, et al.On wind speed pattern and energy potential in China[J]. Applied energy, 2019, 236: 867-876.
[6] 朱蓉, 王阳, 向洋, 等. 中国风能资源气候特征和开发潜力研究[J]. 太阳能学报, 2021, 42(6): 409-418.ZHU R, WANG Y, XIANG Y, et al. Study on climate characteristics and development potential of wind energy resources in China[J]. Acta energiae solaris sinica, 2021, 42(6): 409-418.
[7] WANG Y, CHAO Q C, ZHAO L, et al.Assessment of wind and photovoltaic power potential in China[J]. Carbon neutrality, 2022, 1(1): 15.
[8] CHEN L, LI D, PRYOR S C.Wind speed trends over China: quantifying the magnitude and assessing causality[J]. International journal of climatology, 2013, 33(11): 2579-2590.
[9] 王楠, 游庆龙, 刘菊菊. 1979—2014年中国地面风速的长期变化趋势[J]. 自然资源学报, 2019, 34(7): 1531-1542.WANG N, YOU Q L, LIU J J. The long-term trend of surface wind speed in China from 1979 to 2014[J]. Journal of natural resources, 2019, 34(7): 1531-1542.
[10] 张鑫凯. 中国近海海上风场分布特征研究: 以近10年(2010—2022年)为例[J]. 江苏科技信息, 2023, 40(26): 72-76.ZHANG X K. Spatial-temporal distribution characteristics of the wind field in the Chinese coastal regions: taking the past decade (2010-2022) as an example[J]. Jiangsu science and technology information, 2023, 40(26): 72-76.
[11] 郭子涵. 中国大陆沿岸代表站海陆风时空分布及影响因素研究[D]. 北京: 中国气象科学研究院, 2023.GUO Z H. Research on the temporal and spatial distribution of sea-land breeze and its influencing factors at representative stations along the coast of Chinese mainland[D]. Beijing: Chinese Academy of Meteorological Sciences, 2023.
[12] 范广宇. 浙江沿海典型地区风资源特性研究[D]. 杭州: 浙江理工大学, 2023.FAN G Y. Characteristics of wind resources in coastal areas of Zhejiang Province[D]. Hangzhou: Zhejiang Sci-Tech University, 2023.
[13] 刘紫薇, 赵帅康, 魏笑然, 等. 主流海表风场资料在舟山群岛近海的性能评估[J]. 海洋与湖沼, 2022, 53(3): 528-537.LIU Z W, ZHAO S K, WEI X R, et al. Performance evaluation of mainstream sea surface wind field data in Zhoushan Archipelago[J]. Oceanologia et limnologia sinica, 2022, 53(3): 528-537.
[14] 宋超辉, 王楠, 王阔, 等. 基于1988—2017年CCMP数据的浙江沿海海表风速变化及成因[J]. 大气科学学报, 2019, 42(4): 562-570.SONG C H, WANG N, WANG K, et al. Variation and cause of sea surface wind speed in Zhejiang coastal area based on CCMP data from 1988 to 2017[J]. Transactions of atmospheric sciences, 2019, 42(4): 562-570.
[15] 潘存鸿, 郑君, 陈刚, 等. 杭州湾潮汐特征时空变化及原因分析[J]. 海洋工程, 2019, 37(3): 1-11.PAN C H, ZHENG J, CHEN G, et al. Spatial and temporal variations of tide characteristics in Hangzhou Bay and cause analysis[J]. The ocean engineering, 2019, 37(3): 1-11.
[16] 张友飞, 黄鹤楼, 沈祥家, 等. 慈溪北部沿海风能资源的计算及分析[J]. 浙江气象, 2008, 29(2): 22-25.ZHANG Y F, HUANG H L, SHEN X J, et al. Calculation and analysis of wind energy resources in the northern coast of Cixi[J]. Journal of Zhejiang meteorology, 2008, 29(2): 22-25.
[17] 张双益, 李熙晨. 气候变化背景下未来中国近海风能资源预估[J]. 太阳能学报, 2022, 43(1): 29-35.ZHANG S Y, LI X C. Future projection of wind energy resources over China’s offshore areas under different climate change scenarios[J]. Acta energiae solaris sinica, 2022, 43(1): 29-35.
[18] 张伯虎, 赵鲁灵. 基于LANDSAT遥感数据的杭州湾庵东边滩变化过程研究[J]. 浙江水利科技, 2016, 44(2): 16-19.ZHANG B H, ZHAO L L. Reclamation process research on Hangzhou Bay Andong beach based on LANDSAT remote sensing data[J]. Zhejiang hydrotechnics, 2016, 44(2): 16-19.
[19] MUSINGUZI A, AKBAR M K.Effect of varying wind intensity, forward speed, and surface pressure on storm surges of hurricane rita[J]. Journal of marine science and engineering, 2021, 9(2): 128.
[20] 周起舞. 北仑港区的波浪特征[J]. 杭州大学学报(自然科学版), 1986, 13(3): 367-380.
ZHOU Q W. Wave characteristics in Beilun Port[J]. Journal of Hangzhou University (nature science), 1986, 13(3): 367-380. Edition), 1986(3): 367-380.
[21] 洪广文, 杨正己. 风浪要素计算方法[J]. 水利水运科技情报, 1978(3): 25-67.
HONG G W, YANG Z J.Calculation method of wind and wave elements[J]. Hydro-science and engineering, 1978(3): 25-67.
[22] 夏期颐, 洪广文. 长江口、杭州湾地区波要素推算及验证[J]. 河海大学学报(自然科学版), 1994, 22(2): 30-38.
XIA Q Y, HONG G W.Computation and verification of wave characteristics along the coastal water of Yangtze River Estuary and Hangzhou Bay[J]. Journal of hohai university (natural sciences), 1994, 22(2): 30-38.
[23] 陈琦, 潘金霞. 浅水风浪要素推算公式比较[J]. 水运工程, 2015(5): 14-21.CHEN Q, PAN J X. Calculation formulas comparison of wind wave factors of shallow water[J]. Port & waterway engineering, 2015(5): 14-21.
[24] 邱大洪. 工程水文学[M]. 4版. 北京: 人民交通出版社, 2011.QIU D H. Engineering hydrology[M]. 4th ed. Beijing: China Communications Press, 2011.
[25] 杨斌, 杨忠良, 叶钦, 等. 杭州湾中部实测波浪特性分析[J]. 海洋工程, 2018, 36(3): 96-103.YANG B, YANG Z L, YE Q, et al. Analysis on wave characteristics of central Hangzhou Bay[J]. The ocean engineering, 2018, 36(3): 96-103.
[26] 杨斌, 杨万康, 谢华伟, 等. 杭州湾北部实测波浪特征[J]. 海洋与湖沼, 2022, 53(4): 999-1006.YANG B, YANG W K, XIE H W, et al. Characteristics of measured waves in the north of Hangzhou Bay, East China Sea[J]. Oceanologia et limnologia sinica, 2022, 53(4): 999-1006.
基金
国家重点研发计划（2023YFC3007903）; 浙江省自然科学基金（LZJWZ23E090005）; 水利部重大科技项目（SKS-2022024）; 浙江省水利厅科技计划（RB2220）
PDF(2893 KB)
