本文選題：中尺度渦 + WA算法�。� 參考：《國(guó)家海洋環(huán)境預(yù)報(bào)中心》2015年碩士論文

【摘要】：中尺度渦是普遍存在于世界各大洋的一種中尺度海洋現(xiàn)象。近年來(lái),隨著衛(wèi)星高度計(jì)的迅速發(fā)展,采用大覆蓋、準(zhǔn)同步、長(zhǎng)時(shí)間連續(xù)觀測(cè)的高度計(jì)資料研究全球或特定海域中尺度渦的統(tǒng)計(jì)特征和傳播特征已成為當(dāng)今的一大研究熱點(diǎn)。因此,如何運(yùn)用自動(dòng)識(shí)別技術(shù)在這海量的衛(wèi)星數(shù)據(jù)中快速、準(zhǔn)確的識(shí)別中尺度渦就顯得尤為重要,這也成為定量計(jì)算中尺度渦的各項(xiàng)統(tǒng)計(jì)特征的基礎(chǔ)。本文主要針對(duì)目前為止使用最廣泛的3種渦旋自動(dòng)識(shí)別算法——WA算法、OW算法和無(wú)閾值等值線法,在實(shí)現(xiàn)并總結(jié)原算法的基礎(chǔ)上,對(duì)各算法所存在的問(wèn)題分別加以改進(jìn),以提高算法的識(shí)別精度和計(jì)算效率。同時(shí)對(duì)三種改進(jìn)算法進(jìn)行對(duì)比分析,采用識(shí)別精度最高的WA算法與CTD實(shí)測(cè)資料相結(jié)合,探討了2013年夏秋兩季越南東南外海暖渦的演化特征、水文特征和內(nèi)部結(jié)構(gòu)。具體工作如下:1)本文在介紹了WA算法實(shí)現(xiàn)過(guò)程中用到的處理技巧和心得體會(huì)的基礎(chǔ)上,針對(duì)WA算法計(jì)算量大、計(jì)算過(guò)程復(fù)雜的問(wèn)題,提出了一種新的“流線聚類”算法以及與之對(duì)應(yīng)的“渦旋邊緣識(shí)別算法”。新的流線聚類算法不僅計(jì)算量較小,而且無(wú)需人為設(shè)定聚類半徑閾值,精度更高、聚類結(jié)果更加可靠;兩種新算法的結(jié)合也解決了原算法無(wú)法識(shí)別內(nèi)部結(jié)構(gòu)較為復(fù)雜的多渦結(jié)構(gòu)的問(wèn)題。2)本文針對(duì)OW算法常見的兩個(gè)問(wèn)題:受衛(wèi)星高度計(jì)數(shù)據(jù)噪聲影響顯著、同一W等值線內(nèi)常包含極性相反的渦旋,分別進(jìn)行了改進(jìn)。尤其針對(duì)后一個(gè)問(wèn)題,提出了兩種分離算法,即“渦度法”和“單連通區(qū)域法”,并對(duì)它們各自的實(shí)驗(yàn)結(jié)果進(jìn)行了對(duì)比和分析。3)本文利用SLA數(shù)據(jù)對(duì)無(wú)閾值等值線法進(jìn)行檢驗(yàn),檢驗(yàn)結(jié)果證實(shí)該算法不僅適用于SSH數(shù)據(jù),也很好的適用于SLA數(shù)據(jù)。在此基礎(chǔ)上我們針對(duì)原算法無(wú)法識(shí)別渦核位置以及多渦結(jié)構(gòu)的問(wèn)題,提出了一種“邊核匹配”算法,該算法能夠準(zhǔn)確識(shí)別渦旋中渦核的數(shù)量、每個(gè)渦核的位置以及強(qiáng)度等。4)本文在三種改進(jìn)算法之間進(jìn)行比較分析,通過(guò)專家目視判別的方式定量地統(tǒng)計(jì)每一種算法的識(shí)別精度,通過(guò)計(jì)算每種算法的成功識(shí)別率、過(guò)量識(shí)別率、漏識(shí)率、類信噪比、面積重疊率等,定量分析各算法間的精度差異,并考慮到了由專家主觀因素引起的評(píng)估結(jié)果的不確定性,給出了允許的誤差上限。5)本文采用識(shí)別精度最高的WA渦旋自動(dòng)識(shí)別算法,對(duì)2013年夏秋兩季越南東南外海暖渦的演化特征做了初步分析,并結(jié)合CTD實(shí)測(cè)資料對(duì)比驗(yàn)證WA算法的識(shí)別結(jié)果,分析越南東南外海暖渦在演化過(guò)程中內(nèi)部性質(zhì)、結(jié)構(gòu)發(fā)生的變化。
[Abstract]:Mesoscale vortex is a kind of mesoscale ocean phenomenon that exists in every ocean of the world. In recent years, with the rapid development of satellite altimeters, the use of large coverage, quasi-synchronous, long-term continuous observation altimeter data to study the global or specific sea area mesoscale vortex statistical characteristics and propagation characteristics has become a major research hotspot. Therefore, how to use automatic recognition technology to identify mesoscale vortices quickly and accurately in these massive satellite data is particularly important, which becomes the basis of quantitative calculation of the statistical features of mesoscale vortices. This paper mainly aims at three kinds of vortex automatic recognition algorithms, WA algorithm OW algorithm and non-threshold contour method, based on the realization and summary of the original algorithm, the existing problems of each algorithm are improved respectively. In order to improve the recognition accuracy and computational efficiency of the algorithm. At the same time, three improved algorithms are compared and analyzed. The evolution, hydrological characteristics and internal structure of warm vortex in Southeast Vietnam Sea in summer and autumn 2013 are discussed by combining WA algorithm with CTD data. The specific work is as follows: 1) on the basis of introducing the processing skills and experience used in the implementation of WA algorithm, this paper aims at the problems of the large amount of calculation and complex calculation process of WA algorithm. A new "streamline clustering" algorithm and a corresponding "vortex edge recognition algorithm" are proposed. The new streamline clustering algorithm not only needs less computation, but also does not need to set the threshold of clustering radius artificially, so the accuracy is higher and the clustering result is more reliable. The combination of two new algorithms also solves the problem that the original algorithm can not identify the complex multi-vortex structure of the internal structure. This paper aims at two common problems of the OW algorithm: it is significantly affected by the satellite altimeter data noise. The vortex with opposite polarity is often contained in the same W isoline, which is improved respectively. Especially for the latter problem, two separation algorithms, vorticity method and single connected region method, are proposed, and their respective experimental results are compared and analyzed. 3) in this paper, SLA data are used to test the contours without threshold. The results show that the algorithm is not only suitable for SSH data, but also suitable for SLA data. On the basis of this, we propose a "edge kernel matching" algorithm, which can accurately identify the number of vortex cores in a vortex, aiming at the problem that the original algorithm is unable to identify the location of vortex cores and the structure of multiple vortices. The location and intensity of each vortex core are compared and analyzed among the three improved algorithms. The recognition accuracy of each algorithm is quantitatively counted by the method of expert visual discrimination, and the recognition rate of each algorithm is calculated. Excess recognition rate, miss recognition rate, class signal-to-noise ratio, area overlap rate, etc., quantitative analysis of the accuracy differences among the algorithms, and taking into account the uncertainty of the evaluation results caused by the subjective factors of experts, The allowable upper limit of error is given. (5) in this paper, the evolution characteristics of warm vortex in southeast Vietnam in summer and autumn 2013 are preliminarily analyzed by using WA vortex automatic recognition algorithm with the highest recognition accuracy. The results of WA algorithm are compared with CTD data, and the internal properties and structure changes of warm vortices in southeast Vietnam are analyzed.
【學(xué)位授予單位】：國(guó)家海洋環(huán)境預(yù)報(bào)中心
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：P715.6

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