Application of eSQG method in vertical velocity diagnosis in the South China Sea
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摘要: 本文利用OFES模式0.1°×0.1°高分辨率温盐、流速和海面高度（SSH）数据，分析eSQG方法在南海垂向流速诊断中的适用性和南海垂向流速的时空变化特征。结果表明，基于SSH和eSQG的诊断垂向流速ωeSQG与OFES模拟“真值”垂向流速ωOFES整体量级基本相当，为O（10−5 m/s），空间上呈现北强南弱。深海盆（水深大于1 000 m）ωeSQG与ωOFES的水平空间分布的相关系数rs在次表层150 m左右达到最大，高于南海全海域的空间相关系数，表明eSQG在远离边界的深水区更有效。季节上，ωeSQG总体夏强冬弱，与ωOFES的相关系数rs冬季大、夏季小，表明eSQG更适用于冬季南海垂向流速的诊断。eSQG诊断垂向流速在台湾西南部和越南以东适用性更高，与ωOFES的时间相关系数rt超过0.6；海盆南部和西北部陆架区诊断效果较差，时间相关系数rt多小于0.2。同一区域ωeSQG和ωOFES空间相关系数存在18～55 d的周期变化。分析显示，海面高度与海面密度同相位分布时，ωeSQG与“真值”ωOFES更接近。时间分辨率对eSQG诊断效果几乎无影响，空间分辨率降低到0.25°时rs整体增大，说明eSQG在中尺度诊断效果更好。Abstract: Using 0.1°×0.1° high-resolution temperature, salinity, velocity and sea surface height (SSH) data from the ocean general circulation model for the earth simulator (OFES) model, this study analyzes the capability and applicability of the eSQG (effective Surface Quasi-Geostrophy) method in vertical velocity diagnosis in the South China Sea (SCS), as well as the spatiotemporal variation of vertical velocities. The diagnosed vertical velocities ωeSQG from SSH with the eSQG method are of the same order of 10−5 m/s as the “true” vertical velocities ωOFES from the OFES model. ωeSQG shows spatial variations with higher values in northern basin. The correlation coefficients of the horizontal distribution of ωeSQG and ωOFES (rs) are greater in deep basin than that in the whole SCS, suggesting that the eSQG method is more efficient in vertical velocity diagnosis in deep water far from boundaries. Vertically, the correlation coefficient has maximum values occurring in the subsurface layer at about 150 m. ωeSQG is stronger in summer and rs show seasonal variation with higher values in winter, indicating more efficient in eSQG diagnosis in winter. ωeSQG is reliable in the regions southwest of Taiwan and east of Vietnam, where the temporal correlation coefficients of ωeSQG and ωOFES (rt) exceed 0.6, while ωeSQG is poorly correlated to ωOFES in the shelf regions in the southern and northwestern SCS with rt mostly under 0.2. rs in the same region is varying at periods of about 18−55 d. ωeSQG performs better as the distributions of the SSH and the sea surface density are in same phase. ωeSQG varies little as the temporal resolution of SSH varies, while rs increases as spatial resolution reduced to 0.25° in mesoscales.
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Key words:
- vertical velocity /
- eSQG /
- spatio-temporal variation /
- South China Sea /
- OFES
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图 1 2012年3月29日黑潮延伸体400 m深度ωeSQG（a）和ωOFES（b）的水平分布，ωeSQG和ωOFES的空间相关系数rs的垂向时间序列（c）以及年平均结果（d）
图c中黑色线表示平均混合层深度，图d中红色线表示年平均混合层深度，阴影表示标准差
Fig. 1 Horizontal distribution of vertical velocity ωeSQG (a) and ωOFES (b) at 400 m in the Kuroshio Extension area on 29 March 2012, time series (c) and yearly average (d) of vertical profiles of spatial correlation coefficient rs between ωeSQG and ωOFES in the area
The black line in panel c denotes the area-averaged mixed layer depth，the red line in panel d represents the yearly-mean mixed layer depth, and the cyan shading denotes the standard deviations
图 2 单日（2012年5月16日，a−c）、年平均（d−f）、夏季（g−i）、冬季（j−l）南海100 m深度ωeSQG、ωOFES和二者差值的水平分布
黑色线表示100 m和1 000 m等深线
Fig. 2 Horizontal distribution of ωeSQG, ωOFES and their difference at 100 m in the South China Sea on 16 May 2012 (a−c), in the whole year (d−f), summer (g−i) and winter (j−l)
Black lines denote the 100 m and 1 000 m isobath
图 3 南海全域和深水区ωeSQG和ωOFES的空间相关系数
$r^s_{{\rm{total}}} $ （a−b）和$r^s_{{\rm{deep}}} $ （c−d）的垂向时间序列及其年平均黑色虚线表示平均混合层深度，阴影表示标准差
Fig. 3 Time series and yearly average of vertical profiles of correlation coefficient
$r^s_{{\rm{total}}} $ and$r^s_{{\rm{deep}}} $ between ωeSQG and ωOFES in the whole South China Sea (a−b) and the deep basin (c−d)Black dashed lines denote the area-averaged mixed layer depth, cyan shadings denote the standard deviations
图 4 南海50 m（a）和100 m（b）层各网格点上2012年3月至2013年2月ωeSQG和ωOFES的时间相关系数rt的水平分布
黑色线表示100 m和1 000 m等深线
Fig. 4 Horizontal distribution of temporal correlation rt between ωeSQG and ωOFES at 50 m (a) and 100 m (b) in the South China Sea from March 2012 to February 2013
Black lines denote the 100 m and 1000 m isobath
图 5 R1–R5区ωeSQG和ωOFES空间相关系数rs的垂向时间序列及其年平均和季节平均结果
黑色虚线表示平均混合层深度，横杠和阴影表示标准差
Fig. 5 Time series, yearly average and seasonal average of correlation rs between ωeSQG and ωOFES in regions from R1 to R5
Black lines denote the box-averaged mixed layer depth, horizontal bars and cyan shadings denote the standard deviations
图 6 R1–R5区ωeSQG和ωOFES空间相关系数rs的概率分布及其功率谱
Fig. 6 Probability distribution and power spectra of correlation rs between ωeSQG and ωOFES in regions R1 to R5
图 7 9 d时间分辨率南海ωeSQG和ωOFES的空间相关系数
$r^s_{{\rm{total}}} $ 和$r^s_{{\rm{deep}}} $ 的垂向时间序列（a, d）及其年平均（b, e）和季节平均（c, f）黑色虚线表示平均混合层深度（a, d），横杠和阴影表示标准差（b–c, e–f）
Fig. 7 Time series (a, d), yearly average (b, e) and seasonal average (c, f) of correlation
$r^s_{{\rm{total}}} $ and$r^s_{{\rm{deep}}} $ between ωeSQG and ωOFES in the South China Sea derived from data with temporal resolution of 9 daysBlack dashed lines denote the area-averaged mixed layer depth (a, d), horizontal bars and color shadings denote the standard deviations (b–c, e–f)
图 8 0.25o空间分辨率南海ωeSQG和ωOFES的空间相关系数
$r^s_{{\rm{total}}} $ 和$r^s_{{\rm{deep}}} $ 的垂向时间序列（a, d）及其年平均（b, e）和季节平均（c, f）黑色虚线表示平均混合层深度（a, d），横杠和阴影表示标准差（b–c, e–f）
Fig. 8 Time series (a, d), yearly average (b, e) and seasonal average (c, f) of correlation
$r^s_{{\rm{total}}} $ and$r^s_{{\rm{deep}}} $ between ωeSQG and ωOFES in the South China Sea derived from data with horizontal resolution of 0.25oBlack dashed lines denote the area-averaged mixed layer depth (a, d), horizontal bars and color shadings denote the standard deviations (b–c, e–f)
图 9 年平均、夏季和冬季南海100 m深度相对涡度的水平分布
黑色线表示100 m等深线
Fig. 9 Horizontal distribution of relative vorticity at 100 m in the South China Sea in the whole year, summer and winter
Black line denotes 100 m isobath
图 10 R1区海面高度（SSH）（a）、ωeSQG（b）和ωOFES（c）谱分析结果
Fig. 10 Power spectra of sea surface height (SSH) (a), ωeSQG (b), and ωOFES (c) in the Region R1
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