Analysis of temporal and spatial characteristics of sea surface wind field in Taiwan Strait based on CCMP
-
摘要: 利用1993−2022年最新版交叉标定多平台风场资料（CCMP V3.1），针对台湾海峡海面风场的年、季、月、日变化特征进行了分析。结果表明：台湾海峡及台湾岛周边海域风场具有明显的空间分布特征，地形效应导致不同海域出现风速极大值区和极小值区。其中台湾海峡中部受“狭管效应”的影响，在冬季风速最大，风向基本与海峡走向平行；夏季风速低于海峡外部的风速，无“狭管效应”。此外，海面风场还具有明显的季、月变化特征，冬季盛行东北风，风速为全年最高；夏季盛行西南风，风速最低；春、秋两季风场特征相似，皆盛行东北风；冬季风比夏季风盛行期长，约占全年的四分之三。对风场的年际变化分析时，结果表明夏季风向易发生较大角度的偏转；年平均风速保持基本平缓的线性趋势，在一些年份的异常偏高或偏低与海气相互作用现象厄尔尼诺−南方涛动的发生相关。研究日变化特征时则发现，在夜间20时风速和风向波动最大；风速一天内存在周期性变化；风向日变化夏季偏转最明显。Abstract: The annual, seasonal, monthly and diurnal variations of sea surface wind field over the Taiwan Strait were analyzed based on the new version of Cross-Calibrated Multi-Platform Version 3.1 (CCMP V3.1) wind data from 1993 to 2022. The results showed that the wind field in the Taiwan Strait and the water around Taiwan Island had obvious spatial distribution characteristics, the topographic effect leads to the maximum and minimum wind speed regions in different sea areas. Because the central Taiwan Strait was affected by the “narrow tube effect”, the wind speed was the highest and the wind direction was basically parallel to the strait in winter; the wind speed in summer was lower than the speed outside the channel, and there was no “narrow tube effect”. In addition, the sea surface wind field also had obvious seasonal and monthly variation characteristics. The northeast wind prevailed in winter, and in this season the wind speed was the highest in the whole year; the southwest wind prevailed in summer with the lowest wind speed; the characteristics of spring and autumn monsoon fields were similar, both prevailing northeast wind; winter monsoon last longer than summer monsoon, accounting for about three quarters of the year. The analysis of the inter-annual variation of wind field showed that the wind direction tended to deflect at a large angle in summer. The annual mean wind speed maintained a basically flat linear trend, and the abnormal high or low in some years was related to the occurrence of El Niño-Southern Oscillation (ENSO). When the diurnal variation characteristics were studied, it was found that the wind speed and direction fluctuated most at 20 PM. The wind speed varied periodically within a day. The diurnal variation of wind direction deflection was most obvious in summer.
-
Key words:
- CCMP /
- Taiwan Strait /
- sea surface wind field /
- temporal and spatial characteristics
-
图 1 多年月平均海面风场的空间分布
Fig. 1 Spatial distribution of the monthly mean sea surface wind field for many years
图 2 多年季节平均海面风场的空间分布
Fig. 2 Spatial distribution of the seasonal mean sea surface wind field for many year
图 3 海面风速多年平均方差空间分布
Fig. 3 Spatial distribution of sea surface wind speed mean variances for many years
图 8 多年月平均风速和风向的日变化
Fig. 8 Diurnal variation of mean monthly wind speed and direction for many years
图 10 风向日变化的分布特征
Fig. 10 Distribution characteristics of diurnal variation of wind direction
图 11 浮标观测的风速和风向日变化
Fig. 11 Observations of diurnal variations in wind speed and direction at buoy
表 1 UTC与LST时间转换表
Tab. 1 UTC and LST time conversion
UTC LST 00:00 8:00（早晨） 06:00 14:00（中午） 12:00 20:00（夜间） 18:00 2:00（+1)(次日凌晨） 
下载: 导出CSV
-
[1] 林明森, 邹巨洪, 解学通, 等. HY-2A微波散射计风场反演算法[J]. 中国工程科学, 2013, 15(7): 68−74. doi: 10.3969/j.issn.1009-1742.2013.07.010Lin Mingsen, Zou Juhong, Xie Xuetong, et al. HY-2A microwave scatterometer wind retrieval algorithm[J]. Engineering Sciences, 2013, 15(7): 68−74. doi: 10.3969/j.issn.1009-1742.2013.07.010 [2] 詹思玙, 齐琳琳, 卢伟. 基于CCMP资料和现场观测资料的西北太平洋海面风场特征分析[J]. 海洋预报, 2017, 34(2): 10−20. doi: 10.11737/j.issn.1003-0239.2017.02.002Zhan Siyu, Qi Linlin, Lu Wei. Analysis of sea surface wind in Northwest Pacific based on CCMP satellite data[J]. Marine Forecasts, 2017, 34(2): 10−20. doi: 10.11737/j.issn.1003-0239.2017.02.002 [3] 金铸钰, 刘凯, 郭安博宇, 等. 基于CCMP的西北太平洋海面风场特征分析[J]. 海洋预报, 2022, 39(2): 20−33. doi: 10.11737/j.issn.1003-0239.2022.02.003Jin Zhuyu, Liu Kai, Guo Anboyu, et al. Characteristics analysis of the sea surface wind in the Northwest Pacific based on CCMP satellite data[J]. Marine Forecasts, 2022, 39(2): 20−33. doi: 10.11737/j.issn.1003-0239.2022.02.003 [4] 陈心一, 郝增周, 潘德炉, 等. 中国近海海面风场的时空特征分析[J]. 海洋学研究, 2014, 32(1): 1−10.Chen Xinyi, Hao Zengzhou, Pan Delu, et al. Analysisoftemporaland spatialfeature ofsea surface wind field in China offshore[J]. Journal of Marine Sciences, 2014, 32(1): 1−10. [5] 沈春, 蒋国荣, 施伟来, 等. 南海QuikSCAT海面风场变化特征分析[J]. 海洋预报, 2012, 29(3): 1−8. doi: 10.3969/j.issn.1003-0239.2012.03.001Shen Chun, Jiang Guorong, Shi Weilai, et al. Characteristic analysis of the variability of QuikSCAT wind in the South China Sea[J]. Marine Forecasts, 2012, 29(3): 1−8. doi: 10.3969/j.issn.1003-0239.2012.03.001 [6] 潘卫华, 林毅. 近10年台湾海峡海面风场的时空特征变化动态分析[J]. 热带气象学报, 2019, 35(3): 296−303.Pan Weihua, Lin Yi. Spatial feature and seasonal variability characteristics of sea surface wind field in Taiwan Strait from 2007 to 2017[J]. Journal of Tropical Meteorology, 2019, 35(3): 296−303. [7] Giglio D, Gille S T, Cornuelle B D, et al. Annual modulation of diurnal winds in the tropical oceans[J]. Remote Sensing, 2022, 14(3): 459. doi: 10.3390/rs14030459 [8] Turk F J, Hristova-Veleva S, Giglio D. Examination of the daily cycle wind vector modes of variability from the constellation of microwave scatterometers and radiometers[J]. Remote Sensing, 2021, 13(1): 141. doi: 10.3390/rs13010141 [9] Lang T, Xu Weixin, Rutledge S. Investigating the seasonal and diurnal cycles of ocean vector winds, precipitation, and lightning near the philippines[C]//International Ocean Vector Winds Science Team Meeting. San Diego, CA, United States: Sponsors: Center for Ocean-Atmospheric Prediction Studies (COAPS), 2017. [10] Tang Wenqing, Liu W T, Stiles B, et al. Detection of diurnal cycle of ocean surface wind from space-based observations[J]. International Journal of Remote Sensing, 2014, 35(14): 5328−5341. doi: 10.1080/01431161.2014.926413 [11] 伍伯瑜. 台湾海峡的气候特征[J]. 台湾海峡, 1982, 1(2): 14−18.Wu Boyu. Climatic characteristics of the Taiwan Strait[J]. Taiwan Strait, 1982, 1(2): 14−18. [12] 郭婷婷, 高文洋, 高艺, 等. 台湾海峡气候特点分析[J]. 海洋预报, 2010, 27(1): 53−58. doi: 10.3969/j.issn.1003-0239.2010.01.010Guo Tingting, Gao Wenyang, Gao Yi, et al. Analysis of climate characteristics in Taiwan Strait[J]. Marine Forecasts, 2010, 27(1): 53−58. doi: 10.3969/j.issn.1003-0239.2010.01.010 [13] 旷芳芳, 张友权, 张俊鹏, 等. 3种海面风场资料在台湾海峡的比较和评估[J]. 海洋学报, 2015, 37(5): 44−53.Kuang Fangfang, Zhang Youquan, Zhang Junpeng, et al. Comparison and evaluation of three sea surface wind products in Taiwan Strait[J]. Haiyang Xuebao, 2015, 37(5): 44−53. [14] Mears C, Lee T, Ricciardulli L, et al. Improving the accuracy of the Cross-Calibrated Multi-Platform (CCMP) ocean vector winds[J]. Remote Sensing, 2022, 14(17): 4230. doi: 10.3390/rs14174230 [15] 吕明华, 闫江雨, 姚仁太, 等. 风向的统计方法研究[J]. 气象与环境学报, 2012, 28(3): 83−89. doi: 10.3969/j.issn.1673-503X.2012.03.015Lü Minghua, Yan Jiangyu, Yao Renta, et al. Study on the statistical method of wind direction[J]. Journal of Meteorology and Environment, 2012, 28(3): 83−89. doi: 10.3969/j.issn.1673-503X.2012.03.015 [16] Zhang Haifeng, Beggs H, Wang Xiaohua, et al. Seasonal patterns of SST diurnal variation over the Tropical Warm Pool region[J]. Journal of Geophysical Research: Oceans, 2016, 121(11): 8077−8094. doi: 10.1002/2016JC012210 [17] Ricciardulli L, Foltz G R, Manaster A, et al. Assessment of Saildrone extreme wind measurements in Hurricane Sam using MW satellite sensors[J]. Remote Sensing, 2022, 14(12): 2726. doi: 10.3390/rs14122726 [18] 翁国玲, 唐寒秋. 台湾海峡狭管效应引起的大风增强[J]. 数字化用户, 2019, 25(27): 222−224.Weng Guoling, Tang Hanqiu. Increased winds caused by the narrow tube effect in the Taiwan Strait[J]. Digitization User, 2019, 25(27): 222−224. [19] 高成志, 郑崇伟, 陈璇. 基于CCMP风场的中国近海风能资源的长期变化分析[J]. 海洋预报, 2017, 34(5): 27−35. doi: 10.11737/j.issn.1003-0239.2017.05.003Gao Chengzhi, Zheng Chongwei, Chen Xuan. Long-term trend analysis of wind energy resource in the China Sea and adjacent waters based on the CCMP wind data[J]. Marine Forecasts, 2017, 34(5): 27−35. doi: 10.11737/j.issn.1003-0239.2017.05.003 [20] 张磊, 郑崇伟, 李庆红. 1988−2009年北印度洋海域风候统计分析[J]. 海洋通报, 2012, 31(5): 575−580.Zhang Lei, Zheng Chongwei, Li Qinghong. Wind climate analysis for the North Indian Ocean from 1988 to 2009[J]. Marine Science Bulletin, 2012, 31(5): 575−580. [21] 潘静, 刘铸飘, 郑崇伟, 等. 1958−2001年全球海域海表风速变化趋势[J]. 气象科技, 2014, 42(1): 104−109. doi: 10.3969/j.issn.1671-6345.2014.01.017Pan Jing, Liu Zhupiao, Zheng Chongwei, et al. Analysis of global ocean sea surface wind speed over recent 44 years[J]. Meteorological Science and Technology, 2014, 42(1): 104−109. doi: 10.3969/j.issn.1671-6345.2014.01.017 [22] 林刚. 南中国海风场和海浪场统计分析及其应用[D]. 大连: 大连理工大学, 2018.Lin Gang. Statistical analysis and application of wind field and sea wave field in South China Sea[D]. Dalian: Dalian University of Technology, 2018. [23] 郑崇伟. 基于CCMP风场的近22年中国海海表风场特征分析[J]. 气象与减灾研究, 2011, 34(3): 41−46. doi: 10.3969/j.issn.1007-9033.2011.03.007Zheng Chongwei. Sea surface wind field analysis in the China Sea during the last 22 years with CCMP wind field[J]. Meteorology and Disaster Reduction Research, 2011, 34(3): 41−46. doi: 10.3969/j.issn.1007-9033.2011.03.007 [24] 赵宗慈, 罗勇, 黄建斌. 全球变暖和厄尔尼诺事件[J]. 气候变化研究进展, 2023, 19(5): 663−666.Zhao Zongci, Luo Yong, Huang Jianbin. Global warming and El Niño events[J]. Climate Change Research, 2023, 19(5): 663−666. [25] 吴滨, 林长城, 文明章, 等. 福建沿海地区海陆风的时空分布特征[J]. 应用海洋学学报, 2013, 32(1): 125−132.Wu Bin, Lin Changcheng, Wen Mingzhang, et al. Spatial and temporal distribution characteristic of sea-land breeze over the Fujian coast[J]. Journal of Applied Oceanography, 2013, 32(1): 125−132. [26] Short E, Vincent C L, Lane T P. Diurnal cycle of surface winds in the Maritime Continent observed through satellite scatterometry[J]. Monthly Weather Review, 2019, 147(6): 2023−2044. doi: 10.1175/MWR-D-18-0433.1 -
图(11) / 表(1)
计量
- 文章访问数: 240
- HTML全文浏览量: 88
- PDF下载量: 25
- 被引次数: 0
