Seasonal variation in the three-dimensional structures of costal thermal front off West Guangdong

Yan Zhang Lili Zeng Qiang Wang Bingxu Geng Changjian Liu Rui Shi Na Liu Weiping Wang Dongxiao Wang

Yan Zhang, Lili Zeng, Qiang Wang, Bingxu Geng, Changjian Liu, Rui Shi, Na Liu, Weiping Wang, Dongxiao Wang. Seasonal variation in the three-dimensional structures of costal thermal front off West Guangdong[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1739-9
Citation: Yan Zhang, Lili Zeng, Qiang Wang, Bingxu Geng, Changjian Liu, Rui Shi, Na Liu, Weiping Wang, Dongxiao Wang. Seasonal variation in the three-dimensional structures of costal thermal front off West Guangdong[J]. Acta Oceanologica Sinica. doi: 10.1007/s13131-021-1739-9

doi: 10.1007/s13131-021-1739-9

Seasonal variation in the three-dimensional structures of costal thermal front off West Guangdong

Funds: The National Natural Science Foundation of China under contract Nos 41776025, 41576003, 41776026, 41676018 and 41806035; the Pearl River S&T Nova Program of Guangzhou under contract No. 201906010051; the Rising Star Foundation of the South China Sea Institute of Oceanology under contract No. NHXX2019WL0101; the Science and Technology Program of Guangzhou under contract No. 202002030490.
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  • Figure  1.  Bathymetry (contours in m), in situ CTD stations (red dots). Four repeated cruise observations with 18 hydrographic transects along the cross-shelf red lines were implemented in summer (2006), winter (2006/2007), spring (2007), and autumn (2007), respectively. The blue box is the model area.

    Figure  2.  Seasonal mean SST gradients (shading) and SST (contours in°C) in situ in the northern South China Sea.

    Figure  3.  Vertical structures of in situ temperature in the representative cross-shelf transects L03 (a–d), L14 (e–h) and L17 (i–l) in four seasons.

    Figure  4.  Monthly climatological variations in probability of thermal front occurrence in the NSCS. The probabilities are calculated from satellite-derived OSTIA daily SST data for 2006–2014 with temperature gradients greater than 0.03°C/km. The yellow box is the regional-mean area.

    Figure  5.  Monthly climatological surface wind in the NSCS.

    Figure  6.  Seasonal cycles of alongshore (a) and offshore (b) wind speed (blue) and thermal front index (red) averaged over the shelf (yellow dashed box shown in Fig. 4). The thermal front index is defined as the intensity of the surface thermal front multiplied by the probability of front occurrence. The time series are all normalized by their respective root-mean-square variance.

    Figure  7.  The satellite-derived (left) surface thermal fronts (shading) and SST (contours in °C), and model simulation (right) surface thermal fronts (shading) and SST (contours in °C).

    Figure  8.  Model simulation results for the thermal front lifecycle for the L03 profile. Thermal fronts: shading, and temperature: contours in °C.

    Figure  9.  Model simulation results for the thermal front lifecycle for the L17 profile. Thermal fronts: shading, and temperature: contours in °C.

    Table  1.   Total number of CTDs and CTDs selected in this study from the 4 surveys

    CruiseSurvey periodTotal number of CTDsNumber of selected CTDs
    Winter 2006/2007December 20, 2006–January 20, 2007234234
    Spring 2007April 06–May 4, 2007233233
    Summer 2006July 14–August 28, 2006220186
    Autumn 2007October 09–December 5, 2007234234
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出版历程
  • 收稿日期:  2020-07-17
  • 录用日期:  2020-09-17
  • 网络出版日期:  2021-06-18

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