南海西部夏季上升流鋒面的次中尺度特征分析*

黃小龍, 經(jīng)志友, 鄭瑞璽,2, 張旭,2

海洋水文學(xué)

南海西部夏季上升流鋒面的次中尺度特征分析*

黃小龍1, 2, 經(jīng)志友1, 鄭瑞璽1,2, 張旭1,2

1. 熱帶海洋環(huán)境國(guó)家重點(diǎn)實(shí)驗(yàn)室(中國(guó)科學(xué)院南海海洋研究所), 廣東 廣州 510301; 2. 中國(guó)科學(xué)院大學(xué), 北京 100049

利用衛(wèi)星遙感資料和區(qū)域海洋數(shù)值模式ROMS(regional ocean modeling system)高分辨率數(shù)值模擬結(jié)果, 對(duì)南海西部夏季上升流鋒面的次中尺度特征及其非地轉(zhuǎn)過(guò)程進(jìn)行了探討。高分辨率衛(wèi)星遙感觀測(cè)和數(shù)值模擬結(jié)果顯示, 南海西部夏季鋒面海域存在活躍的次中尺度現(xiàn)象, 其水平尺度約為1~10km, 且具有(1)羅斯貝數(shù)(Rossby number, Ro)的典型次中尺度動(dòng)力學(xué)特征。進(jìn)一步的診斷分析表明, 在夏季西南風(fēng)的驅(qū)動(dòng)下, 沿鋒面射流方向的風(fēng)應(yīng)力(down-front wind stress)引起的跨鋒面?？寺斶\(yùn)有利于將海水由鋒面冷水側(cè)向暖水側(cè)輸運(yùn), 減小了鋒面海域的垂向?qū)咏Y(jié)和Ertel位渦, 加劇了鋒面的不穩(wěn)定, 并形成跨鋒面的垂向次級(jí)環(huán)流。高分辨率模擬結(jié)果顯示, 鋒面海域最大垂向流速可達(dá)100m?d–1, 顯著增強(qiáng)了上層海洋的垂向物質(zhì)交換。因此, 活躍在鋒面海域的次中尺度過(guò)程可能是增強(qiáng)南海西部上升流海域垂向物質(zhì)交換的重要貢獻(xiàn)者。

上升流鋒面; 次中尺度過(guò)程; 區(qū)域海洋數(shù)值模式; 衛(wèi)星遙感; 南海西部

海洋環(huán)流包含了從幾千公里的大尺度環(huán)流, 到幾百公里的中尺度過(guò)程和幾公里的次中尺度過(guò)程, 直到百米以下的小尺度湍流混合過(guò)程。其中關(guān)于大尺度環(huán)流、中尺度過(guò)程和小尺度湍流混合過(guò)程的研究已取得了豐碩的成果(Munk et al, 1998; Mauritzen et al, 2002; Tian et al, 2009; Chelton et al, 2011; Alford et al, 2015; Wunsch et al, 2018)。但受限于資料分辨率等因素, 目前對(duì)介于中尺度和小尺度之間, 水平尺度為(1~10km), 時(shí)間尺度為幾小時(shí)到數(shù)天的次中尺度過(guò)程尚缺乏足夠的理解。近年來(lái)隨著觀測(cè)技術(shù)的革新、高分辨率模式的發(fā)展以及相關(guān)理論認(rèn)知的提高, 對(duì)普遍存在于上層海洋的次中尺度過(guò)程研究也逐漸深入。

在中尺度背景環(huán)流、非對(duì)稱(chēng)的大氣強(qiáng)迫(海表風(fēng)場(chǎng)和降溫)以及地形誘導(dǎo)等因素的影響下, 次中尺度過(guò)程在強(qiáng)流、中尺度渦旋邊緣以及鋒面海域尤其活躍(Thomas et al, 2008)。次中尺度過(guò)程具有典型的(1)羅斯貝數(shù)(Rossby number, Ro)和理查森數(shù)(Richardson number, Ri), 表現(xiàn)為完全的三維運(yùn)動(dòng)特征(McWilliams, 2016)。一方面, 現(xiàn)場(chǎng)觀測(cè)和高分辨率數(shù)值研究表明, 次中尺度過(guò)程及其不穩(wěn)定能夠誘發(fā)強(qiáng)烈的垂向非地轉(zhuǎn)次級(jí)環(huán)流, 有利于增強(qiáng)上層海洋熱通量、浮力、營(yíng)養(yǎng)鹽和動(dòng)量的垂向輸運(yùn), 是影響區(qū)域海洋生態(tài)環(huán)境變化的重要?jiǎng)恿^(guò)程之一(Mahadevan et al, 2012; Omand et al, 2015; McKinley et al, 2016; Zhang et al, 2019)。另一方面, 理論分析和觀測(cè)研究顯示, 次中尺度過(guò)程也是平衡態(tài)地轉(zhuǎn)能量向小尺度過(guò)程正向串級(jí)的重要媒介過(guò)程之一(Capet et al, 2008a)。次中尺度不穩(wěn)定(例如對(duì)稱(chēng)不穩(wěn)定和混合層斜壓不穩(wěn)定)能夠有效地汲取地轉(zhuǎn)動(dòng)能并釋放鋒面有效位能, 并在次級(jí)不穩(wěn)定的作用下將能量進(jìn)一步串級(jí)至小尺度湍流混合過(guò)程(Boccaletti et al, 2007; D'Asaro et al, 2011; Barkan et al, 2015)。因此, 次中尺度過(guò)程是中、小尺度相互作用的關(guān)鍵動(dòng)力過(guò)程。

南海地處東亞季風(fēng)區(qū)(Fang et al, 2002), 在大氣強(qiáng)迫、復(fù)雜海底地形等因素的影響下, 具有多尺度的動(dòng)力過(guò)程(Wang et al, 2003; Chen et al, 2011; Zhang et al, 2016), 是研究次中尺度過(guò)程和中、小尺度相互作用的理想海域(Jing et al, 2016; Zhong et al, 2017; 冀承振等, 2017)。其中南海西部是南海中尺度過(guò)程活躍的主要區(qū)域之一(Zhuang et al, 2010), 且已被現(xiàn)場(chǎng)觀測(cè)所證實(shí)。衛(wèi)星遙感觀測(cè)顯示(圖1), 南海西部海面高度變化(圖1中黑色框)顯著高于中部海盆區(qū), 和南海東北部海域同為南海兩個(gè)典型的中尺度渦旋活躍海區(qū)(Hu et al, 2011; Zhang et al, 2016)。在夏季西南風(fēng)的驅(qū)動(dòng)下, 南海西部出現(xiàn)顯著的東向離岸上升流(Chen et al, 2014a; Li et al, 2014)。同時(shí), 沿岸徑流輸入(Chen et al, 2012)、風(fēng)應(yīng)力旋度(Xie et al, 2003, 2007)以及渦度水平輸運(yùn)(Wang et al, 2006; Gan et al, 2008)等均對(duì)該上升流的生成與不同時(shí)間尺度的演變有著重要影響。上升流將下層低溫、高營(yíng)養(yǎng)鹽的海水帶至表層, 并在平流作用下向東輸運(yùn), 在南海西部形成顯著的溫度鋒面和葉綠素濃度高值區(qū)(Kuo et al, 2000; Chen et al, 2014b)。高分辨率水色遙感觀測(cè)結(jié)果顯示, 南海西部夏季鋒面海域廣泛存在著細(xì)絲狀和渦旋狀的次中尺度結(jié)構(gòu)(Liu et al, 2015; Yu et al, 2018), 但關(guān)于該海域次中尺度過(guò)程的動(dòng)力學(xué)特征及其對(duì)上層海洋的影響尚缺乏足夠的理解。本文嘗試?yán)酶叻直媛蕯?shù)值模擬并結(jié)合衛(wèi)星觀測(cè)資料分析, 探討南海西部夏季上升流鋒面的次中尺度特征及其非地轉(zhuǎn)過(guò)程, 以期為南海西部鋒面海域的高葉綠素濃度和中尺度過(guò)程變異提供動(dòng)力學(xué)解釋, 進(jìn)一步加深對(duì)南海西部多尺度相互作用和生態(tài)效應(yīng)的認(rèn)識(shí)。

圖1 南海海表面高度均方根的空間分布

黑色矩形框表示本文研究區(qū)域; 地圖來(lái)自Matlab軟件自帶底圖, 下同

Fig. 1 Spatial distribution of SSH root mean square (rms) in the South China Sea (SCS).The research domain is delineated by the black box

1 數(shù)據(jù)來(lái)源與分析方法

1.1 衛(wèi)星遙感資料

本文使用的衛(wèi)星遙感資料包括高分辨率海表溫度數(shù)據(jù)(sea surface temperature, SST)、海表面高度(sea surface height, SSH)、海表高度異常(sea level anomaly, SLA)、風(fēng)場(chǎng)數(shù)據(jù)和葉綠素濃度數(shù)據(jù)。海表溫度數(shù)據(jù)(2006—2017年)采用英國(guó)氣象局制作并由美國(guó)國(guó)家海洋數(shù)據(jù)中心發(fā)布的高分辨率融合產(chǎn)品(http://data.nodc.noaa.gov/ghrsst/L4/GLOB/UKMO/OSTIA/), 空間分辨率為0.05°×0.05°, 時(shí)間分辨率為1d, 反演精度約為0.57℃(Dong et al, 2014)。日平均的高度計(jì)數(shù)據(jù)(SSH和SLA,1993—2016年)來(lái)源于法國(guó)國(guó)家空間研究中心提供的AVISO(Archiving Validation and Interpolation of Satellite Oceanographic)網(wǎng)格化產(chǎn)品(ftp://ftp.aviso.oceanobs. com/global/), 空間分辨率為0.25°×0.25°, 反演精度約為0.02m。日平均海表風(fēng)場(chǎng)數(shù)據(jù)(1999—2009年)來(lái)自QuikSCAT(Quick Scatterometer)衛(wèi)星散射計(jì), 空間分辨率為0.25°×0.25°, 資料精度為1m?s–1。海表葉綠素濃度數(shù)據(jù)(2002—2012年)來(lái)自中等分辨率成像光譜儀(MEdium Resolution Imaging Spectrometer, MERIS)提供的2級(jí)產(chǎn)品數(shù)據(jù)(ftp:// merisfrs-fts-ds.eo.esa.int), 水平分辨率約為300m, 絕對(duì)精確度達(dá)到10–3mg·m–3。

1.2 模式配置

本文利用ROMS(regional oceanic modeling system)數(shù)值模式對(duì)南海及其西部海域進(jìn)行高分辨率的嵌套模擬。其中最外層模擬區(qū)域覆蓋西太平洋(ROMS0, 7.5km分辨率), 第一層嵌套覆蓋南海區(qū)域(ROMS1, 1.5km分辨率, 如圖2所示), 第二層嵌套聚焦南海西部海域(ROMS2, 500m分辨率); 模式垂向分層均為60層, 并在上邊界和底邊界適當(dāng)加密。初始邊界條件以及風(fēng)場(chǎng)強(qiáng)迫分別采用SODA(simple ocean data assimilation data)海洋數(shù)據(jù)集的氣候態(tài)月平均數(shù)據(jù)(1990—2010年, Carton et al, 2008)和氣候態(tài)日平均QuikSCAT(Quick Scatterometer)風(fēng)場(chǎng)數(shù)據(jù)(Risien et al, 2008)。其中, 采用的SODA數(shù)據(jù)集包含溫度、鹽度、水平和垂直速度以及SSH等變量, 該再分析同化資料的空間分辨率為0.5°×0.5°, 對(duì)應(yīng)的數(shù)據(jù)精度約為: 溫度0.41℃、鹽度0.5‰、速度不確定性小于30%和SSH 0.03m(Carton et al, 2000)。熱通量和淡水通量等氣候態(tài)月平均?！?dú)馔縼?lái)源于國(guó)際海洋大氣綜合數(shù)據(jù)集(International Comprehensive Ocean-Atmosphere Data Set, ICOADS) (Woodruff et al, 2011), 空間分辨率為1°×1°。地形數(shù)據(jù)采用美國(guó)國(guó)家海洋和大氣管理局(National Oceanic and Atmospheric Administration, NOAA)提供的ETOPO2數(shù)據(jù)。小尺度湍流混合采用KPP參數(shù)化方案(K-profile parameterization)進(jìn)行參數(shù)化(Large et al, 1994)。ROMS0診斷計(jì)算20年后, 在線嵌套的ROMS1和ROMS2計(jì)算第21年并輸出日平均模擬結(jié)果。本文選取500m分辨率的ROMS2模擬結(jié)果對(duì)南海西部上升流鋒面海域的次中尺度動(dòng)力特征進(jìn)行分析。

圖2 南海嵌套模擬區(qū)域示意圖

第一層嵌套(ROMS1)包括南海海域, 第二層嵌套(ROMS2)為南海西部海域(黑色矩形框)

Fig. 2 The diagram for the nested ROMS model domain. The western SCS is the nested domain for the ROMS2 simulation (black box) while the nested domain of ROMS1 covers the SCS

1.3 相關(guān)參數(shù)診斷計(jì)算

位渦(potential vorticity, PV)作為一種重要的動(dòng)力學(xué)示蹤物, 反映海洋環(huán)流和多尺度動(dòng)力過(guò)程的穩(wěn)定性(Hoskins, 1974; Thomas et al, 2013)。由于北半球恒為正值, 因此當(dāng)Ertel位渦小于零時(shí), 易誘發(fā)對(duì)稱(chēng)不穩(wěn)定(Thomas et al, 2013)。在地轉(zhuǎn)平衡的假設(shè)條件下, Ertel位渦定義如下(Hoskins, 1974):

為評(píng)估風(fēng)應(yīng)力引起的艾克曼輸運(yùn)對(duì)改變海表浮力的作用, 本文計(jì)算了埃克曼浮力通量(Ekman buoyancy flux, EBF), 表達(dá)式如下:

2 結(jié)果分析

2.1 鋒面的次中尺度動(dòng)力學(xué)特征

高分辨率MERIS水色遙感資料顯示, 南海西部上升流海域有著顯著的葉綠素濃度高值區(qū), 側(cè)向?qū)挾燃s20~40km的高葉綠素帶狀區(qū)域由近岸109°12'E向東延伸至112°30'E, 并且在空間分布形態(tài)上與衛(wèi)星觀測(cè)的溫度鋒面位置一致(圖3)。同時(shí), 從高分辨率葉綠素濃度圖像可以清晰地看到鋒面兩側(cè)渦旋狀和渦絲狀的次中尺度結(jié)構(gòu), 這些次中尺度現(xiàn)象的側(cè)向尺度約為10km, 該特征尺度與呂宋海峽、南海西部等海域的現(xiàn)場(chǎng)觀測(cè)結(jié)果一致(Zheng et al, 2008; Song et al, 2019)。

圖3 南海西部2009年7月26日的海表葉綠素濃度、海表風(fēng)速(箭頭)和海表溫度(等值線, 單位: ℃)平面分布

本文選取11°48'—12°06'N, 110°30'—110°54'E的典型鋒面區(qū)域(圖4a虛線矩形框)對(duì)次中尺度過(guò)程進(jìn)行進(jìn)一步分析, 其水平分布和跨鋒面結(jié)構(gòu)如圖5所示。沿流軸方向露頭等密線顯示, 流軸附近存在寬約5km的狹長(zhǎng)密度鋒面。垂向上, 密度鋒面主要存在于混合層內(nèi)20m以淺, 且南側(cè)等密線相對(duì)北側(cè)更加密集。

圖4 模式第21年8月4日南海西部數(shù)值模擬海表溫度、表層流(箭頭)、SLA(等值線, 單位: m)(a)和羅斯貝數(shù)Ro(b)分布

黑色實(shí)線表示流軸位置(相對(duì)渦度為0); a中虛線矩形框?yàn)楸疚倪x取的典型鋒面區(qū)域

Fig. 4 Maps of SST (a) and Ro (b) from the ROMS2 simulation. The vectors are surface currents. The gray contours represent the SLA, and the black line is the jet axis

圖5 典型鋒面區(qū)域鋒面強(qiáng)度F、地轉(zhuǎn)流ug(箭頭)和海水密度(灰色等值線, 單位: kg·m–3)的水平分布(a)和斷面分布(b)

a中紫紅色實(shí)線表示斷面位置, 黑色實(shí)線表示流軸; b中黑色實(shí)線表示混合層深度

Fig. 5 Spatial distribution of the intensity of front: horizontal distribution (a) and vertical profile (b). The geostrophic flows (vector) and density (grey contour) are also shown. Black line is the jet axis in (a) and the mixed layer depth in (b). The location of the vertical profile is shown by the magenta line in (a)

2.2 垂向次級(jí)環(huán)流與位渦分布特征

為了進(jìn)一步討論上升流鋒面區(qū)域垂向環(huán)流結(jié)構(gòu), 本文通過(guò)空間濾波的方法提取次中尺度的流速信號(hào)。圖6給出了次中尺度垂向流速異常的水平和垂向分布?？梢源_定, 鋒面附近存在明顯的跨鋒面的非地轉(zhuǎn)次級(jí)環(huán)流, 其表層海水在鋒面區(qū)域輻聚下沉, 而在其兩側(cè)存在上升流, 最大垂向流速出現(xiàn)在15m深度附近(圖6b), 其中最大垂向流速可達(dá)100m?d–1, 顯著增強(qiáng)了上層海洋物質(zhì)的垂向交換。該特征與利用南海西部、南海北部等海域的現(xiàn)場(chǎng)觀測(cè)及高分辨率模擬診斷的結(jié)果一致(Xie et al, 2017; Zhong et al, 2017)。

理論研究結(jié)果表明：局地非地轉(zhuǎn)次級(jí)環(huán)流與次中尺度不穩(wěn)定密切相關(guān)(Mahadevan et al, 2006; Gula et al, 2014; McWilliams, 2017)。當(dāng)Ertel位渦與反號(hào)時(shí), 有利于促發(fā)多種類(lèi)型的次中尺度不穩(wěn)定, 其中對(duì)稱(chēng)不穩(wěn)定是能量增長(zhǎng)最快的一種模態(tài)(Hoskins et al, 1972)。與傳統(tǒng)的中尺度過(guò)程不同, 鋒面弱垂向?qū)踊?qiáng)水平浮力梯度以及垂向剪切等均使得位渦的水平斜壓分量(EPVh)與其垂向分量(EPVv)量值相當(dāng), 有利于負(fù)Ertel位渦的發(fā)生并易于引發(fā)次中尺度不穩(wěn)定。

圖7顯示了基于高分辨率數(shù)值模擬診斷計(jì)算得到的Ertel位渦、水平位渦分量和垂向位渦分量的空間分布。負(fù)Ertel位渦主要出現(xiàn)在上層海洋次中尺度鋒面附近, 表明鋒面區(qū)域發(fā)生次中尺度斜壓不穩(wěn)定。通過(guò)比較各位渦分量可以發(fā)現(xiàn), Ertel位渦水平分量絕對(duì)值大于水平分量, 使得Ertel位渦小于零(圖7a—c)。由Ertel位渦的跨鋒面垂向結(jié)構(gòu)分布可知, 受次級(jí)環(huán)流作用, 海表的負(fù)位渦水體沿等密度面自海表進(jìn)入混合層內(nèi); 下層高位渦海水受鋒面兩側(cè)上升流影響抬升至海表, 表明表層和下層海水在次級(jí)環(huán)流的作用下發(fā)生垂向交換且浮力發(fā)生再分配(圖7d)。在此過(guò)程中, 增強(qiáng)的垂向次級(jí)環(huán)流能夠有效地將下層較豐富的營(yíng)養(yǎng)鹽帶進(jìn)入海表, 為鋒面海域的浮游生物生長(zhǎng)提供營(yíng)養(yǎng)鹽供給。

圖6 10m層垂向流速異常的水平和垂向分布

a. 垂向流速異常′(填色)、水平流速異?！?箭頭)和海水密度(等值線, 單位: kg·m–3)的水平分布; b. 斷面溫度(填色)、跨鋒面和垂向流速異常(箭頭)、海水密度(等值線, 單位: kg·m–3)分布; a中紫紅色實(shí)線表示斷面位置; 黑色實(shí)線表示流軸; b中黑色實(shí)線表示混合層深度

Fig. 6 Map (a) and vertical (b) profile of vertical velocity anomaly at 10 m. (a) Black arrows refer to surface currents anomalies. Magenta line indicates the section for the vertical profile, and black line indicates the jet axis. (b) Shading denotes temperature, and black vector represents the cross-front and vertical velocity anomaly. Black line represents mixed layer depth. Grey contour is for density

圖7 典型鋒面海域Ertel位渦(填色)、表層流u(箭頭)和海水密度(灰色等值線)分布

a—c分別表示Ertel位渦(EPV)、Ertel位渦水平分量(EPVh)和Ertel位渦垂向分量(EPVv)的水平分布, 黑色實(shí)線表示流軸; d為Ertel位渦斷面分布, 斷面位置如a中紫紅色實(shí)線所示, 黑色實(shí)線表示混合層深度, 灰色等值線為密度(單位: kg·m–3)

Fig. 7 Snapshot of the Ertel PV. (a-c) are the EPV, EPVh and EPVv, respectively. The black line represents the jet axis. Black arrows denote surface currents. (d) is vertical distribution of EPV. The location of the vertical section is shown by the magenta line in (a). Black line represents mixed layer depth

海表外強(qiáng)迫是上層海洋位渦發(fā)生改變的主要源之一(Thomas, 2005; Thomas et al, 2005)。在夏季西南風(fēng)強(qiáng)迫引起的浮力損失等非保守過(guò)程影響下, 南海西部鋒面海域易出現(xiàn)負(fù)Ertel位渦。診斷計(jì)算結(jié)果顯示, 在沿鋒面射流風(fēng)應(yīng)力(down-front wind stress)的作用下, 最大?？寺×ν砍霈F(xiàn)在流軸附近, 大小約為1×10–5m2?s–3, 表明沿鋒面射流方向的風(fēng)應(yīng)力引起的?？寺斶\(yùn)將冷水向暖水側(cè)跨鋒面輸運(yùn)(圖8), 進(jìn)一步改變鋒面浮力分布并減弱垂向?qū)咏Y(jié), 加強(qiáng)鋒面的水平浮力梯度以及減小Ertel位渦水平斜壓分量, 最終導(dǎo)致負(fù)Ertel位渦出現(xiàn), 從而加劇鋒面的不穩(wěn)定。

圖8 典型鋒面海域的埃克曼浮力通量(填色)、地轉(zhuǎn)流ug(黑色箭頭)、風(fēng)應(yīng)力tstr(紫紅色箭頭)和海水密度(等值線,單位: kg·m–3)的水平分布

從空間分布形態(tài)來(lái)看, ?？寺×ν靠臻g分布與Ertel位渦結(jié)構(gòu)也有著良好的對(duì)應(yīng)關(guān)系。在一定程度上, 這些結(jié)果表明沿鋒面射流風(fēng)應(yīng)力驅(qū)動(dòng)的跨鋒面?？寺斶\(yùn)過(guò)程可能是導(dǎo)致夏季南海西部鋒面海域發(fā)生次中尺度對(duì)稱(chēng)不穩(wěn)定的重要原因。

3 結(jié)論

本文利用高分辨率衛(wèi)星遙感資料并結(jié)合數(shù)值模擬結(jié)果, 分析了夏季南海西部上升流鋒面的次中尺度特征及其非地轉(zhuǎn)過(guò)程。高分辨率水色遙感觀測(cè)顯示, 南海西部上升流鋒面海域存在豐富的次中尺度現(xiàn)象。高分辨率模擬結(jié)果發(fā)現(xiàn), 上升流鋒面有顯著的非地轉(zhuǎn)特征并伴隨次中尺度過(guò)程發(fā)生。診斷計(jì)算結(jié)果顯示, 跨鋒面的非線性的埃克曼水平凈輸運(yùn)將海水自鋒面冷水側(cè)向暖水側(cè)輸運(yùn), 增強(qiáng)了鋒面水平浮力梯度并減弱其垂向?qū)咏Y(jié), 導(dǎo)致鋒面海域出現(xiàn)負(fù)Ertel位渦, 為次中尺度對(duì)稱(chēng)不穩(wěn)定提供了有利條件。因此, 沿鋒面射流風(fēng)應(yīng)力引起的浮力損失可能是導(dǎo)致南海西部上升流海域鋒面發(fā)生次中尺度對(duì)稱(chēng)不穩(wěn)定的重要機(jī)制之一。同時(shí), 診斷結(jié)果顯示, 次中尺度過(guò)程能夠引起跨鋒面的垂向次級(jí)環(huán)流, 最大垂向流速可達(dá)100m?d–1, 顯著增強(qiáng)了鋒面海域的垂向物質(zhì)交換。本文基于數(shù)值模擬初步探討了南海西部鋒面海域次中尺度過(guò)程, 關(guān)于其形成與演變的動(dòng)力過(guò)程, 還需要結(jié)合現(xiàn)場(chǎng)觀測(cè)資料進(jìn)行深入研究。

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Analysis of submesoscale characteristics of summer upwelling fronts in the western South China Sea

HUANG Xiaolong1,2, JING Zhiyou1, ZHENG Ruixi1,2, ZHANG Xu1,2

1. State Key Laboratory of Tropical Oceanography (South China Sea Institute of Oceanology, Chinese Academy of Sciences), Guangzhou 510301, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China

We investigate submesoscale characteristics of summer upwelling fronts in the western South China Sea (WSCS) and associated ageostrophic processes by using satellite measurements and high-resolution ROMS simulations. Active submesoscale filaments with a typical horizontal scale of(1-10) km are detected to be characterized by(1) Rossby number (Ro) from the fine-resolution satellite images and simulation results. The diagnostic analysis shows that down-front wind forcing drives a net cross-front Ekman transport and advects heavy water over light water. This process at submesoscale tends to reduce the stratification and potential vorticity (PV), exacerbates the frontal instabilities, and forms the cross-front secondary circulation. The high-resolution simulation results show that the maximum vertical velocity in the frontal zone can reach 100m?d–1, which significantly enhances vertical material exchange. In this context, active submesoscale processes may contribute to enhanced vertical exchanges of the upper ocean in the summer upwelling front of the western SCS.

upwelling front; submesoscale process; ROMS; satellite remote sensing; western South China Sea

P731.21

A

1009-5470(2020)03-0001-09

10.11978/2019086

http://www.jto.ac.cn

2019-09-12;

2019-12-20。

林強(qiáng)編輯

中國(guó)科學(xué)院基礎(chǔ)前沿科學(xué)研究計(jì)劃原始創(chuàng)新項(xiàng)目(ZDBS-LY-DQC011); 國(guó)家自然科學(xué)基金項(xiàng)目(41776040); 中國(guó)科學(xué)院南海生態(tài)環(huán)境工程創(chuàng)新研究院自主部署項(xiàng)目(ISEE2018PY05); 青島海洋科學(xué)與技術(shù)試點(diǎn)國(guó)家實(shí)驗(yàn)室OCFL功能實(shí)驗(yàn)室開(kāi)放課題(OCFL-201804); 廣州市科學(xué)研究計(jì)劃(201904010420)。

黃小龍(1992—), 男, 廣東省信宜市人, 碩士研究生, 主要從事上層海洋次中尺度過(guò)程研究。E-mail: huangxiaolong@scsio.ac.cn

經(jīng)志友。E-mail: jingzhiyou@scsio.ac.cn

*感謝三位審稿專(zhuān)家提出的寶貴修改意見(jiàn)。

2019-09-12;

2019-12-20.

Editor: LIN Qiang

Original Innovation Project of Basic Frontier Scientific Research Program of CAS (ZDBS-LY-DQC011); National Natural Science Foundation of China (41776040); Innovation Academy of South China Sea Ecology and Environmental Engineering, CAS (ISEE2018PY05); Laboratory for Ocean Dynamics and Climate, Pilot Qingdao National Laboratory for Marine Science and Technology (OCFL-201804); Guangzhou Science and Technology Project (201904010420).

JING Zhiyou. E-mail: jingzhiyou@scsio.ac.cn