Seasonal variation in the three-dimensional structures of coastal thermal front off western Guangdong
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Abstract: The seasonal structure and dynamic mechanism of oceanic surface thermal fronts (STFs) along the western Guangdong coast over the northern South China Sea shelf were analyzed using in situ observational data, remote sensing data, and numerical simulations. Both in situ and satellite observations show that the coastal thermal front exhibits substantial seasonal variability, being strongest in winter when it has the greatest extent and strongest sea surface temperature gradient. The winter coastal thermal front begins to appear in November and disappears after the following April. Although runoff water is more plentiful in summer, the front is weak in the western part of Guangdong. The frontal intensity has a significant positive correlation with the coastal wind speed, while the change of temperature gradient after September lags somewhat relative to the alongshore wind. The numerical simulation results accurately reflect the seasonal variation and annual cycle characteristics of the frontal structure in the simulated area. Based on vertical cross-section data, the different frontal lifecycles of the two sides of the Zhujiang (Pearl) River Estuary are analyzed.
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Key words:
- oceanic thermal fronts /
- South China Sea /
- seasonal dynamics
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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 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
Cruise Survey period Total number of CTDs Number of selected CTDs Winter 2006/2007 Dec. 20, 2006–Jan. 20, 2007 234 234 Spring 2007 Apr. 6–May 4, 2007 233 233 Summer 2006 Jul. 14–Aug. 28, 2006 220 186 Autumn 2007 Oct. 9–Dec. 5, 2007 234 234 
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