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Satellite Observation of Upwelling along the Western Coast of the South China Sea
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Satellite Observation of Upwelling along the Western Coast of the South China Sea Nan-Jung Kuo,* Quanan Zheng,† and Chung-Ru Ho*
W
e observed the evolution of upwelling along the western coast of the South China Sea (SCS). The data we used are NOAA (National Oceanic and Atmospheric Administration) satellite AVHRR (Advanced Very High Resolution Radiometer) IR (infrared) images taken in 1996 and 1997 summer at the HRPT (High Resolution Picture Transmission) receiving station built on Tai-Ping Island, which is located in the central SCS. An upwelling intensity, defined by the total heat loss in the upwelling cold water region, is used to determine the relationship between coastal upwelling and the wind stress derived from the ERS-2 (European Remote Sensing Satellite) data. The results show that the upwelling intensity has a good linear relationship with the total alongshore wind stress while it has a low correlation with the cross-shore component of wind stress. These results imply that the alongshore wind stress is the main factor to pump the cold water up to the sea surface layer. Meanwhile, the satellite infrared images also indicate that the centroid of cold water moved southward from 15⬚N to 11⬚N during the observation period. The size of upwelling area changed as well, and finally evolved into a cold jet stretching offshore along 11⬚N–12⬚N in the mid-August 1997. Satellite infrared and altimeteric data show that the evolution of upwelling region is closely associated with the development of two anticyclonic circulations in the western SCS. Elsevier Science Inc., 2000
* Department of Oceanography, National Taiwan Ocean University, Keelung, Taiwan † The College of Marine Studies, University of Delaware, Newark Address correspondence to N.-J. Kuo, Dept. of Oceanography, National Taiwan Ocean Univ., Keelung, Taiwan, Republic of China. E-mail: [email protected] Received 7 May 1999; revised 17 April 2000 REMOTE SENS. ENVIRON. 74:463–470 (2000) Elsevier Science Inc., 2000 655 Avenue of the Americas, New York, NY 10010
INTRODUCTION Upwelling is a term used to describe the processes that cause the upward movement of sea water from deeper layer into the surface layer. Since the water temperature usually decreases with depth, the upwelled water will be colder than the surface water that it displaces. Very often it has higher concentrations of nutrients than the surface water, which may have been depleted of nutrients of the growth of phytoplankton. Regions of upwelling are usually, therefore, the regions of high biological productivity. Upwelling can be a coastal phenomenon, offering us some of the world’s major fisheries, like those along the west coasts of North and South America, the continental shelves off northwestern and southwestern Africa, and the western coast of the Iberian Peninsula (Smith, 1994). However, upwelling also takes place in open equatorial and polar oceans (Wyrtki, 1961). Upwelling may be generated by different mechanisms. Hseuh and O’Brien (1971) pointed out that an alongshore ocean current can induce a steady coastal upwelling. Using a semigeostrophic model, Samelson and de Szoeke (1988) simulated coastal upwelling with an alongshore wind stress and heating. Federiuk and Allen (1995) simulated upwelling circulation on the Oregon continental shelf with a model forced by surface heat flux, wind stress, and alongshore pressure gradient. Analyses of field measurements by Gibbs et al. (1998) indicated that the local wind stress and intrusion of mesoscale East Australian Current features are the important forcing processes for generating upwelling in the coastal ocean of Sydney, Australia. For the region of SCS, previous studies have shown that upwelling occurs along the western coast during the southwesterly monsoon blowing. Wyrtki (1961) found seasonal upwelling off the Vietnam coast according to the drop of the sea surface temperature (SST) more than 1⬚C in June and July. Using climatological data, Xu et al. (1982) calculated the sea surface dynamic heights in the 0034-4257/00/$–see front matter PII S0034-4257(00)00138-3
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Figure 1. Map of the South China Sea with isobaths of 100 m, 1000 m, 2000 m, 3000 m, and 4000 m.
SCS. Their results (see Fig. 6) showed that there is a relatively low sea surface height region in the offshore of the central Vietnam in the summertime, indicating occurrence of upwelling in that area. Pohlmann (1987) found a negative surface temperature anomaly along the western SCS from Gulf of Tokin to the central Vietnam in summer from numerical results. Shaw and Chao (1994) showed upwelling along the Vietnam coast in August from temperature and salinity fields through numerical modeling. Huang et al. (1994) pointed out that cold water upwelling occurs very often along the western coast of the SCS from Mainland China to the central Vietnam coast. From AXBT (Airborne Expendable Bathythermography) measurements, Chu et al. (1998) found a cold water area with temperature less than 26.5⬚C in the offshore region of the central Vietnam at about 12⬚N in May 1995. In this article, NOAA satellite AVHRR IR images are used for a detailed observation of the upwelling regions along the western coast of the SCS from late spring to summer. A parametrization method is employed to quantify the upwelling intensity and to determine the relation between the upwelling process and the wind stress. The evolution of the upwelling area and dynamical mechanisms are also discussed. OBSERVATIONS Study Area The study area, South China Sea, extending from the equator to 22⬚N and from 99⬚E to 121⬚E, is one of the largest marginal seas of the West Pacific Ocean, as shown in Figure 1. It is surrounded by China, Indo-
China Peninsula, Borneo, the Philippines and Taiwan, and is connected to the East China Sea, the Pacific Ocean, the Sulu Sea, the Java Sea and the Indian Ocean through the Taiwan, Luzon, Balabac, Karimata, and Malacca Straits, respectively. Most of the straits are narrow and shallow except the Luzon Strait with a maximum depth over 2000 m. The bottom topography of the SCS is characterized by a deep basin with a maximum depth of 5000 m at the center, wide continental shelves in the north and south, and steep slopes on the east and west sides. The circulation in the SCS is strongly driven by the monsoon winds (Wyrtki, 1961). The strong northeasterly winds prevail over the whole region in winter while the weaker southwesterly monsoon appears in summer. Meanwhile, because of the vast expanse of the SCS, there is a time lag up to 3 months from south to north for the wind field to reverse direction at the change of seasons (Huang et al., 1994). Different dominating wind fields may coexist at the sea surface during the transitional periods between winter and summer monsoons (Shaw and Chao, 1994). Besides field observations, numerical modeling is an important approach for the SCS circulation studies (Pohlmann, 1987; Shaw, 1991; Shaw and Chao, 1994; Shaw et al., 1996; Chao et al., 1996). Recent technological development has provided the possibility of observing the oceans from satellites. Observation from space has the advantages of synopticity and repetitive coverage. Therefore, it can be used for determining spatial patterns with various scales and the temporal or persistent changes of the observed patterns. Using TOPEX/POSEIDON altimeter data, Ho et al. (2000a) found three dynamically active regions in the SCS. The one located near the central Vietnam coast is believed to be closely associated with coastal upwelling and cold jet. Ho et al. (2000b) also determined the seasonal variability of sea surface height in the SCS and pointed out that the low sea surface height appearing near the central Vietnam coast in summer and fall is related with coastal upwelling. NOAA Satellite Images Previous results have demonstrated that NOAA satellite AVHRR images are suitable for observing dynamical processes of mesoscale ocean phenomena due to its great swath-width more than 2500 km, spatial resolution as high as 1.1 km, repeatable coverage more than twice per day, and SST determination ability. For example, Zheng (1981) and Zheng and Klemas (1982) applied AVHRR IR images to studies of winter temperature patterns, fronts, and surface currents in the Yellow Sea and East China Sea adjacent to the SCS. Zheng et al. (1984) and Kuo (1994) used AVHRR IR images for analyzing dynamics of meso-scale eddies along the Gulf Stream. Ho (1994) and Zheng et al. (1994) observed propagation of
Satellite Observation of Upwelling along the Western Coast of the South China Sea
the Rossby waves in the eastern tropical Pacific using NOAA satellite SST data. For this study, AVHRR IR images received in 1996 and 1997 summer at the HRPT receiving station built on Tai-Ping Island, which is located at the central SCS (see Fig. 1), are used as a principal data source. Each image has been rectified to a standard transverse Mercator projection. The SST has been calculated from the brightness temperatures of AVHRR Bands 3, 4, and 5 by using the Multi-Channel Sea Surface Temperature (MCSST) algorithms (McClain et al., 1985). On account of the high percentage of cloudiness throughout the South China Sea, the images with relatively low cloud coverage around the western coast of the South China Sea in summer were selected for detailed analysis. In order to find cloud-free pixels, the following steps to identify clouds are used in this study. The first step is the threshold test using the measured Channel 4 brightness temperature and the Channel 2 albedo value as a check on cloud contamination. If the measured Channel 4 brightness temperature is below a certain threshold temperature or the Channel 2 albedo above a certain value, the pixel is rejected as cloud-contamined. The second step is a local uniformity test applied on a 3 by 3 pixel array of Channel 4 brightness temperatures and Channel 2 albedo values. The large local variation of the brightness temperature in Channel 4 or the albedo in Channel 2 shows clouds. The uniformity test of Channel 2 is only used for daytime data. The final step applied only at night examines the difference between Channel 3 and Channel 4 brightness temperatures. A large difference in the brightness temperature between these two channels is an indication of cloud contamination. Each pixel must pass all the tests described above to be judged cloud-free; the sea surface temperature can be inferred for these cloud-free pixels. Eighteen 1-day composite MCSST images with relatively cloud-free coverage during the period from May to August 1997 are used for this study. Four of them are shown in Figure 2. These images cover a window of the SCS from 10⬚N to 16.5⬚N latitude and from 106⬚E to 111.5⬚E longitude. The time interval between them is about 1 month. The evolution of SST patterns along the western coast of the SCS with latitude south of 17⬚N is shown on these satellite images. For example, Figure 2a shows the image on 8 May 1997. One can see that a cold water band with temperature below 27⬚C was distributed along the coastal area of Vietnam from 13⬚N to 17⬚N. Meanwhile, the cold water meandered offshore and extended to 150 km seaward at 14⬚N. The location and size of this cold water band also changed. Figure 2b, the image on 10 June 1997, shows that the cold water moved southward to 12⬚N and became smaller in size. On 8 July 1997, about 2 months later, the cold water plume still existed and continuously moved southward as shown in Figure 2c. Figure 2d shows the image on 13 August 1997; a very narrow jet originated at 11⬚N, 109⬚E and
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stretched to more than 200 km offshore. Compared with previous results (e.g., Fang et al., 1998), we found that this cold offshore jet is associated with Southeast Vietnam Offshore Current (SEVOC). UPWELLING ANALYSIS In the SCS, the southwesterly monsoon first appears in central basin in May and then expands over the entire basin in July and August (Shaw and Chao, 1994). Therefore, upwelling occurs during the summertime in the nearshore areas from the southeast mainland China, and northeast of Hainan island to the central Vietnam coast (Huang et al., 1994). By observing from the average annual variation of SST, Wyrtki (1961) found that the SST along the Vietnam coast dropped more than 1⬚C in June and July, and he explained this drop caused by monsooninduced upwelling. In this section, we will analyze the upwelling data obtained from AVHRR IR images and examine the relation between upwelling and wind stress derived from ERS-2 wind data. Parametrization For an upwelling region, two physical parameters can directly be measured from the AVHRR IR images; one is the area, and the other one is SST. In order to examine the relation between upwelling and wind stress by using satellite images, parametrization is necessary. Suppose in a small area, Ai, of the upwelling region, the SST has a drop of ⌬Ti compared to the temperature mean of the surrounding nonupwelling area, the total heat loss in the upwelling region, Q, is given in Eq. (1): Q⫽Cp兺⌬TidiAi ,
(1)
i
where Cp is the specific heat capacity and di is the upwelling depth that should be varied with the change of the local wind. According to Pond and Pickard (1983), di can be estimated as in Eq. (2): d i⫽
4.3Vi , √sin|ui|
(2)
where Vi and ui are the wind speed and latitude of the cold upwelled waters, respectively. Vi can be obtained from ERS-2 scatterometer data, and ui can be determined from NOAA AVHRR images. In this study, we assume that the turbulent heat flux is negligible compared to the advection heat flux caused by upwelling, therefore, we can define an upwelling intensity R as in Eq. (3): R⫽兺⌬TidiAi ,
(3)
i
and we use R as an index to characterize the coastal upwelling in this study.
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Figure 2. Color coded AVHRR IR images of the western coast of the SCS taken on a) 8 May, b) 10 June, c) 8 July, and d) 13 August 1997. The offshore boundary of the cold water region on each image is enclosed with the SST contour of 27⬚C.
Correlation In order to determine the contribution of the wind components to the upwelling, the correlation coefficient between the upwelling intensity R and the wind stress over the upwelling area is computed. The total wind stress M is defined as in Eq. (4): M⫽兺siAi ,
(4)
i
where the wind stress si is derived from weekly mean ERS-2 wind vectors with a spatial resolution of 1⬚ lati-
tude by 1⬚ longitude. The total alongshore component Malong and total offshore components Moff of the wind stress are also computed. Figure 3 shows variations of R, M, Malong, and Moff from May to August 1997, respectively. The correlation coefficients between R and total wind stress, alongshore, and offshore component are listed in Table 1. One can see that total alongshore component of wind stress Malong is highly correlated with the upwelling intensity R. The total offshore component has a low correlation coefficient with R. The data points derived from satellite observations from May to August
Satellite Observation of Upwelling along the Western Coast of the South China Sea
Figure 3. Time series of R in km3 ⬚C and M, Malong, and Moff in Pa km2 from May to August 1997.
1997 and the linear relations between upwelling intensity R and total alongshore component of wind stress Malong are shown in Figure 4. One can see a good agreement of the upwelling intensity and the total alongshore wind stress over the whole cold water area. These results indicate that the Ekman transport plays an important role to induce coastal upwelling in the study area. The relative error of the wind stress, dM/M, can be estimated by 2(dV/V) with the assumption that the wind stress M is proportional to the square of the wind speed V. The relative error of upwelling intensity, dR/R, can be estimated by the sum of d(⌬T)/⌬T and (dV/V). The typical wind speed V we choose is 6 m/s. The dV we choose is about 0.6 m/sec because that the rms error of the ERS-2 wind speed is approximately 1.2 m/s with a resolution of 50 km, and our data are on the average of about 100 km resolution (Jet Propulsion Laboratory, 1998). The typical temperature drop ⌬T we choose in this study is about 2⬚C. The d(⌬T) we choose is about 0.29⬚C because that the deviation of the MCSST is about 0.5⬚C, and our data are the 1-day composite of about three individual images per day. Therefore the error bars shown in Figure 4 are about 20% and 25% for dM/Mand dR/R, respectively. Deformation of the Upwelling Region The above results indicate that the Ekman effect appears to be the dominant mechanism to pump the cold water upward to the surface along the Vietnam coast. The southwesterly monsoon can be considered as a spatially Table 1. Correlation Coefficients between the Upwelling Intensity R and Total Wind Stresses M, Malong, and Moff during the period from May to August 1997
R
M
Malong
Moff
0.86
0.88
⫺0.17
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Figure 4. Relationship between R and Malong from May to August 1997. Straight lines are linear regression of the data.
uniform wind field within the scale of the study area. Therefore, induced upwelling should form a cold water band along the Vietnam coast. However, the cold water region was deformed from a nearly south–northward oriented band in May to a very narrow offshore jet in August as shown on AVHRR IR images in Figure 2. This deformation and movement process of the cold water area can be characterized by movement of its thermal centroid, (Xc, Yc), which is defined as in Eqs. (5) and (6): X c⫽
兺i XiTi , 兺i Ti
(5)
兺i YiTi , 兺i Ti
(6)
and Y c⫽
Figure 5. Southward movement of upwelling centroid with time.
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Figure 6. Dynamic heights (in dyn. m) based on climatological data of the South China Sea in the summertime (from Xu et al., 1982). CJ represents the cold water jet with temperature less than 27⬚C, AC1 represents the warm-core ring with core temperature higher than 28⬚C, and AC2 represents the anticyclone in the south.
where Ti is sea surface water temperature at (Xi, Yi). Figure 5 shows the variation in north–south direction of the location (Xc, Yc) from May to August 1997. One can see that the thermal centroid of the cold water was located at about 14⬚N in May and moved quickly to south to about 11.7⬚N in June, then shifted southward slowly during July and August to about 11.3⬚N. Figure 6 shows the sea surface dynamic heights calculated by Xu et al. (1982) based on the climatological data of the SCS. One can see that a relative low water filament off the coast of central Vietnam was confined in the confluent zone between two anticyclonic high waters: One was in the north and the other one in the south during the summertime. The AVHRR IR image taken on 13 August 1996 shown in Figure 7a and the interpretation map shown in Figure 7b also provide further evidence for existence of coastal upwelling and sea surface circulation patterns. One can see an anticyclonic gyre in the north of the cold offshore jet. In addition, the weekly mean sea surface height anomaly (SSHA) derived from
Figure 7. a) AVHRR IR image taken on 13 August 1996 showing upwelling area along the Vietnam coast south of 12⬚N and an anticyclonic circulation east of the Vietnam coast and b) an interpretation map of a).
TOPEX/POSEIDON and ERS-2 satellite altimeter data during the same period of NOAA AVHRR images in Figure 2 are shown in Figure 8. One can see that SSHA patterns are very close to the results of Xu et al. (1982). These results indicate that coastal upwelling constitutes an important component of the circulation system in the western SCS. Thus, the deformation and movement of
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Figure 8. Contours of sea surface height anomaly on a) 7 May, b) 9 June, c) 9 July, and d) 14 August 1997. They were derived from TOPEX/POSEIDON and ERS-2 satellite altimeters by the Colorado Center for Astrodynamics Research (CCAR) (Web site: http:// www-ccar.colorado.edu/~realtime/global-historical_ssh/).
the upwelled cold water area are certainly associated with the two mesoscale anticyclonic gyres. SUMMARY We observed upwelling along the western coast of the SCS using NOAA AVHRR images received in 1996 and 1997 summer. The images showed the entire view of upwelling area with spatial and temporal resolutions much higher than that derived from field measurements and numerical modeling by previous investigators. In order to describe the evolution process of upwelling quantitatively, we defined a parameter, upwelling intensity, which includes contributions of upwelling area, SST difference,
and upwelling depth derived from simultaneous ERS-2 wind data. Correlation analysis indicated that observed upwelling is mainly induced by the alongshore component of the summer southwesterly monsoon. The analyses also indicated that sea surface circulation system, characterized by two anticyclonic warm gyres which sandwich a cold jet, is responsible for deformation of upwelling area and southward movement of the thermal centroid of the cold water area. Therefore, we may conclude that the observed coastal upwelling belongs to a type of wind-induced and current-modified upwelling. We are indebted to the National Science Council (NSC) of the Republic of China (ROC) and National Taiwan Ocean Univer-
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sity for supporting to build the NOAA AVHRR HRPT receiving station at Tai-Ping Island. We thank Wei-Kang Hu for processing satellite data. This work was supported by the NSC, ROC under Grants NSC 86-2611-M-019-004-OS, NSC 87-2611-M-019-AP7, and NSC 88-2611-M-019-007-AP7, and partly supported by U.S. NASA Oceanography Program under Grant NAG5-7949 (Q. Z.).
REFERENCES Chao, S.-Y., Shaw, P.-T., and Wu, S. Y. (1996), Deep water ventilation in the South China Sea. Deep Sea Res. 43: 445–466. Chu, P. C., Fan, C., Lozano, C. J., and Kerling, J. L. (1998), An airborne expendable bathythermograph survey of the South China Sea, May 1995. J. Geophys. Res. 103(C10): 21,637–21,652. Fang, G., Fang, W., Fang, Y., and Wang, K. (1998), A survey of studies on the South China Sea upper ocean circulation. Acta Oceanogr. Taiwanica 37(1):1–16. Federiuk, J., and Allen, J. S. A. (1995), Upwelling circulation on the Oregon continental shelf. Part II: Simulations and comparisons with observations. J. Phys. Oceanogr. 25: 1867–1889. Gibbs, M. T., Middleton, J. H., and Marchesiello, P. (1998), Baroclinic response of Sydney shelf waters to local wind and deep ocean forcing. J. Phys. Oceanogr. 28:178–190. Ho, C.-R. (1994), A study of dynamics in the tropical Pacific using satellite data, Ph.D. dissertation, University of Delaware, pp. 1–154. Ho, C.-R., Kuo, N.-J., Zheng, Q., and Soong, Y. S. (2000a), Dynamically active areas in the South China Sea detected from TOPEX/POSEIDON satellite altimeter data. Remote Sens. Environ. 71:320–328. Ho, C.-R., Zheng, Q., Soong, Y. S., Kuo, N.-J., and Hu, J.-H. (2000b), Seasonal variability of sea surface height in the South China Sea observed with TOPEX/POSEIDON altimeter data. J. Geophys. Res. 105(C6):13,981–13,990. Hseuh, Y., and O’Brien, J. J. (1971), Steady coastal upwelling induced by an along-shore current. J. Phys. Oceangr. 1: 180–186. Huang, Q.-Z., Wang, W.-Z., Li, Y. S., and Li, C. W. (1994), Current characteristics of the South China Sea. In Oceanology of China Sea (D. Zhou, Y.-B. Liang, and C. K. Tseng, Eds.), Kluwer Academic, Dordrecht, Vol. 1, pp. 39–47. Jet Propulsion Laboratory (1998), Mean surface fields from the ERS-AMI and ADEOS-NSCAT Microwave Scatterometers 91/08/05 to 98/03/01: Scientific user manual, Pasadena, CA, May. Kuo, N.-J. (1994), Dynamic analysis of the decay of mesoscale
eddies by satellite feature tracking and theoretical modeling, Ph.D. dissertation, University of Delaware, pp. 1–129. McClain, E. P., Pichel, W. G., and Walton, C. C. (1985), Comparative performance of AVHRR-based multichannel sea surface temperatures. J. Geophys. Res. 90:11,587–11,601. Pohlmann, T. (1987), A three-dimensional circulation model of the South China Sea. In Three-Dimensional Models of Marine and Estuarine Dynamics (J. J. Nihoul and B. M. Jamart, Eds.), Elsevier, Amsterdam, pp. 245–268. Pond, S., and Pickard, G. L. (1983), Introductory Dynamical Oceanography, 2nd ed., Butterworth-Heinemann, Oxford, pp. 1–329. Samelson, R. M., and de Szoeke, R. A. (1988), Semigeostrophic wind-driven thermocline upwelling at a coastal boundary. J. Phys. Oceanogr. 18:1372–1383. Shaw, P.-T. (1991), The seasonal variation of the intrusion of the Philippine Sea water in the South China Sea. J. Geophys. Res. 96:821–827. Shaw, P.-T., and Chao, S.-Y. (1994), Surface circulation in the South China Sea. Deep Sea Res. Part I 41:1663–1683. Shaw, P.-T., Chao, S.-Y., Liu, K.-K., Pai, S.-C., and Liu, C.-T. (1996), Winter upwelling off Luzon in the northeastern South China Sea. J. Geophys. Res. 101:16,435–16,448. Smith, R. L. (1994), The physical processes of coastal ocean upwelling systems. In Upwelling in the Ocean (C. P. Summerhayes, K.-C. Emeis, M. V. Angel, R. L. Smith, and B. Zeitzschel, Eds.), Wiley, New York, pp. 39–64. Wyrtki, K. (1961), Physical oceanography of the Southeast Asian waters, Scientific results of marine investigations of the South China Sea and the Gulf of Thailand, NAGA Report 2, Scripps Institution of Oceanography, La Jolla, CA, pp. 1–195. Xu, X., Zhang, Q. Z., and Chen, H. (1982), The general descriptions of the horizontal circulation in the South China Sea. In Proc. Symp. Chin. Soc. Mar. Hydrol. Meteorol., Science Press, Beijing, pp.119–127. Zheng, Q. (1981), The winter sea surface temperature patterns of the Yellow Sea and the East China Sea derived from GMS-1 and NOAA-5 IR images. Acta Oceanol. Sin. 3: 523–534. Zheng, Q., and Klemas, V. (1982), Determination of winter temperature patterns, fronts, surface currents in the Yellow Sea and East China Sea from satellite imagery. Remote Sens. Environ. 12:201–218. Zheng, Q., Klemas, V., and Huang, N. E. (1984), The dynamics of the slope water off New England and its influence on the Gulf Stream as inferred from satellite IR data. Remote Sens. Environ. 15:135–153. Zheng, Q., Yan, X.-H., Ho, C.-R., and Tai, C.-K. (1994), The effects of shear flow on propagation of Rossby waves in the equatorial oceans. J. Phys. Oceanogr. 24:1680–1686.
Satellite Observation of Upwelling along the Western Coast of the South China Sea Nan-Jung Kuo,* Quanan Zheng,† and Chung-Ru Ho*
W
e observed the evolution of upwelling along the western coast of the South China Sea (SCS). The data we used are NOAA (National Oceanic and Atmospheric Administration) satellite AVHRR (Advanced Very High Resolution Radiometer) IR (infrared) images taken in 1996 and 1997 summer at the HRPT (High Resolution Picture Transmission) receiving station built on Tai-Ping Island, which is located in the central SCS. An upwelling intensity, defined by the total heat loss in the upwelling cold water region, is used to determine the relationship between coastal upwelling and the wind stress derived from the ERS-2 (European Remote Sensing Satellite) data. The results show that the upwelling intensity has a good linear relationship with the total alongshore wind stress while it has a low correlation with the cross-shore component of wind stress. These results imply that the alongshore wind stress is the main factor to pump the cold water up to the sea surface layer. Meanwhile, the satellite infrared images also indicate that the centroid of cold water moved southward from 15⬚N to 11⬚N during the observation period. The size of upwelling area changed as well, and finally evolved into a cold jet stretching offshore along 11⬚N–12⬚N in the mid-August 1997. Satellite infrared and altimeteric data show that the evolution of upwelling region is closely associated with the development of two anticyclonic circulations in the western SCS. Elsevier Science Inc., 2000
* Department of Oceanography, National Taiwan Ocean University, Keelung, Taiwan † The College of Marine Studies, University of Delaware, Newark Address correspondence to N.-J. Kuo, Dept. of Oceanography, National Taiwan Ocean Univ., Keelung, Taiwan, Republic of China. E-mail: [email protected] Received 7 May 1999; revised 17 April 2000 REMOTE SENS. ENVIRON. 74:463–470 (2000) Elsevier Science Inc., 2000 655 Avenue of the Americas, New York, NY 10010
INTRODUCTION Upwelling is a term used to describe the processes that cause the upward movement of sea water from deeper layer into the surface layer. Since the water temperature usually decreases with depth, the upwelled water will be colder than the surface water that it displaces. Very often it has higher concentrations of nutrients than the surface water, which may have been depleted of nutrients of the growth of phytoplankton. Regions of upwelling are usually, therefore, the regions of high biological productivity. Upwelling can be a coastal phenomenon, offering us some of the world’s major fisheries, like those along the west coasts of North and South America, the continental shelves off northwestern and southwestern Africa, and the western coast of the Iberian Peninsula (Smith, 1994). However, upwelling also takes place in open equatorial and polar oceans (Wyrtki, 1961). Upwelling may be generated by different mechanisms. Hseuh and O’Brien (1971) pointed out that an alongshore ocean current can induce a steady coastal upwelling. Using a semigeostrophic model, Samelson and de Szoeke (1988) simulated coastal upwelling with an alongshore wind stress and heating. Federiuk and Allen (1995) simulated upwelling circulation on the Oregon continental shelf with a model forced by surface heat flux, wind stress, and alongshore pressure gradient. Analyses of field measurements by Gibbs et al. (1998) indicated that the local wind stress and intrusion of mesoscale East Australian Current features are the important forcing processes for generating upwelling in the coastal ocean of Sydney, Australia. For the region of SCS, previous studies have shown that upwelling occurs along the western coast during the southwesterly monsoon blowing. Wyrtki (1961) found seasonal upwelling off the Vietnam coast according to the drop of the sea surface temperature (SST) more than 1⬚C in June and July. Using climatological data, Xu et al. (1982) calculated the sea surface dynamic heights in the 0034-4257/00/$–see front matter PII S0034-4257(00)00138-3
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Figure 1. Map of the South China Sea with isobaths of 100 m, 1000 m, 2000 m, 3000 m, and 4000 m.
SCS. Their results (see Fig. 6) showed that there is a relatively low sea surface height region in the offshore of the central Vietnam in the summertime, indicating occurrence of upwelling in that area. Pohlmann (1987) found a negative surface temperature anomaly along the western SCS from Gulf of Tokin to the central Vietnam in summer from numerical results. Shaw and Chao (1994) showed upwelling along the Vietnam coast in August from temperature and salinity fields through numerical modeling. Huang et al. (1994) pointed out that cold water upwelling occurs very often along the western coast of the SCS from Mainland China to the central Vietnam coast. From AXBT (Airborne Expendable Bathythermography) measurements, Chu et al. (1998) found a cold water area with temperature less than 26.5⬚C in the offshore region of the central Vietnam at about 12⬚N in May 1995. In this article, NOAA satellite AVHRR IR images are used for a detailed observation of the upwelling regions along the western coast of the SCS from late spring to summer. A parametrization method is employed to quantify the upwelling intensity and to determine the relation between the upwelling process and the wind stress. The evolution of the upwelling area and dynamical mechanisms are also discussed. OBSERVATIONS Study Area The study area, South China Sea, extending from the equator to 22⬚N and from 99⬚E to 121⬚E, is one of the largest marginal seas of the West Pacific Ocean, as shown in Figure 1. It is surrounded by China, Indo-
China Peninsula, Borneo, the Philippines and Taiwan, and is connected to the East China Sea, the Pacific Ocean, the Sulu Sea, the Java Sea and the Indian Ocean through the Taiwan, Luzon, Balabac, Karimata, and Malacca Straits, respectively. Most of the straits are narrow and shallow except the Luzon Strait with a maximum depth over 2000 m. The bottom topography of the SCS is characterized by a deep basin with a maximum depth of 5000 m at the center, wide continental shelves in the north and south, and steep slopes on the east and west sides. The circulation in the SCS is strongly driven by the monsoon winds (Wyrtki, 1961). The strong northeasterly winds prevail over the whole region in winter while the weaker southwesterly monsoon appears in summer. Meanwhile, because of the vast expanse of the SCS, there is a time lag up to 3 months from south to north for the wind field to reverse direction at the change of seasons (Huang et al., 1994). Different dominating wind fields may coexist at the sea surface during the transitional periods between winter and summer monsoons (Shaw and Chao, 1994). Besides field observations, numerical modeling is an important approach for the SCS circulation studies (Pohlmann, 1987; Shaw, 1991; Shaw and Chao, 1994; Shaw et al., 1996; Chao et al., 1996). Recent technological development has provided the possibility of observing the oceans from satellites. Observation from space has the advantages of synopticity and repetitive coverage. Therefore, it can be used for determining spatial patterns with various scales and the temporal or persistent changes of the observed patterns. Using TOPEX/POSEIDON altimeter data, Ho et al. (2000a) found three dynamically active regions in the SCS. The one located near the central Vietnam coast is believed to be closely associated with coastal upwelling and cold jet. Ho et al. (2000b) also determined the seasonal variability of sea surface height in the SCS and pointed out that the low sea surface height appearing near the central Vietnam coast in summer and fall is related with coastal upwelling. NOAA Satellite Images Previous results have demonstrated that NOAA satellite AVHRR images are suitable for observing dynamical processes of mesoscale ocean phenomena due to its great swath-width more than 2500 km, spatial resolution as high as 1.1 km, repeatable coverage more than twice per day, and SST determination ability. For example, Zheng (1981) and Zheng and Klemas (1982) applied AVHRR IR images to studies of winter temperature patterns, fronts, and surface currents in the Yellow Sea and East China Sea adjacent to the SCS. Zheng et al. (1984) and Kuo (1994) used AVHRR IR images for analyzing dynamics of meso-scale eddies along the Gulf Stream. Ho (1994) and Zheng et al. (1994) observed propagation of
Satellite Observation of Upwelling along the Western Coast of the South China Sea
the Rossby waves in the eastern tropical Pacific using NOAA satellite SST data. For this study, AVHRR IR images received in 1996 and 1997 summer at the HRPT receiving station built on Tai-Ping Island, which is located at the central SCS (see Fig. 1), are used as a principal data source. Each image has been rectified to a standard transverse Mercator projection. The SST has been calculated from the brightness temperatures of AVHRR Bands 3, 4, and 5 by using the Multi-Channel Sea Surface Temperature (MCSST) algorithms (McClain et al., 1985). On account of the high percentage of cloudiness throughout the South China Sea, the images with relatively low cloud coverage around the western coast of the South China Sea in summer were selected for detailed analysis. In order to find cloud-free pixels, the following steps to identify clouds are used in this study. The first step is the threshold test using the measured Channel 4 brightness temperature and the Channel 2 albedo value as a check on cloud contamination. If the measured Channel 4 brightness temperature is below a certain threshold temperature or the Channel 2 albedo above a certain value, the pixel is rejected as cloud-contamined. The second step is a local uniformity test applied on a 3 by 3 pixel array of Channel 4 brightness temperatures and Channel 2 albedo values. The large local variation of the brightness temperature in Channel 4 or the albedo in Channel 2 shows clouds. The uniformity test of Channel 2 is only used for daytime data. The final step applied only at night examines the difference between Channel 3 and Channel 4 brightness temperatures. A large difference in the brightness temperature between these two channels is an indication of cloud contamination. Each pixel must pass all the tests described above to be judged cloud-free; the sea surface temperature can be inferred for these cloud-free pixels. Eighteen 1-day composite MCSST images with relatively cloud-free coverage during the period from May to August 1997 are used for this study. Four of them are shown in Figure 2. These images cover a window of the SCS from 10⬚N to 16.5⬚N latitude and from 106⬚E to 111.5⬚E longitude. The time interval between them is about 1 month. The evolution of SST patterns along the western coast of the SCS with latitude south of 17⬚N is shown on these satellite images. For example, Figure 2a shows the image on 8 May 1997. One can see that a cold water band with temperature below 27⬚C was distributed along the coastal area of Vietnam from 13⬚N to 17⬚N. Meanwhile, the cold water meandered offshore and extended to 150 km seaward at 14⬚N. The location and size of this cold water band also changed. Figure 2b, the image on 10 June 1997, shows that the cold water moved southward to 12⬚N and became smaller in size. On 8 July 1997, about 2 months later, the cold water plume still existed and continuously moved southward as shown in Figure 2c. Figure 2d shows the image on 13 August 1997; a very narrow jet originated at 11⬚N, 109⬚E and
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stretched to more than 200 km offshore. Compared with previous results (e.g., Fang et al., 1998), we found that this cold offshore jet is associated with Southeast Vietnam Offshore Current (SEVOC). UPWELLING ANALYSIS In the SCS, the southwesterly monsoon first appears in central basin in May and then expands over the entire basin in July and August (Shaw and Chao, 1994). Therefore, upwelling occurs during the summertime in the nearshore areas from the southeast mainland China, and northeast of Hainan island to the central Vietnam coast (Huang et al., 1994). By observing from the average annual variation of SST, Wyrtki (1961) found that the SST along the Vietnam coast dropped more than 1⬚C in June and July, and he explained this drop caused by monsooninduced upwelling. In this section, we will analyze the upwelling data obtained from AVHRR IR images and examine the relation between upwelling and wind stress derived from ERS-2 wind data. Parametrization For an upwelling region, two physical parameters can directly be measured from the AVHRR IR images; one is the area, and the other one is SST. In order to examine the relation between upwelling and wind stress by using satellite images, parametrization is necessary. Suppose in a small area, Ai, of the upwelling region, the SST has a drop of ⌬Ti compared to the temperature mean of the surrounding nonupwelling area, the total heat loss in the upwelling region, Q, is given in Eq. (1): Q⫽Cp兺⌬TidiAi ,
(1)
i
where Cp is the specific heat capacity and di is the upwelling depth that should be varied with the change of the local wind. According to Pond and Pickard (1983), di can be estimated as in Eq. (2): d i⫽
4.3Vi , √sin|ui|
(2)
where Vi and ui are the wind speed and latitude of the cold upwelled waters, respectively. Vi can be obtained from ERS-2 scatterometer data, and ui can be determined from NOAA AVHRR images. In this study, we assume that the turbulent heat flux is negligible compared to the advection heat flux caused by upwelling, therefore, we can define an upwelling intensity R as in Eq. (3): R⫽兺⌬TidiAi ,
(3)
i
and we use R as an index to characterize the coastal upwelling in this study.
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Figure 2. Color coded AVHRR IR images of the western coast of the SCS taken on a) 8 May, b) 10 June, c) 8 July, and d) 13 August 1997. The offshore boundary of the cold water region on each image is enclosed with the SST contour of 27⬚C.
Correlation In order to determine the contribution of the wind components to the upwelling, the correlation coefficient between the upwelling intensity R and the wind stress over the upwelling area is computed. The total wind stress M is defined as in Eq. (4): M⫽兺siAi ,
(4)
i
where the wind stress si is derived from weekly mean ERS-2 wind vectors with a spatial resolution of 1⬚ lati-
tude by 1⬚ longitude. The total alongshore component Malong and total offshore components Moff of the wind stress are also computed. Figure 3 shows variations of R, M, Malong, and Moff from May to August 1997, respectively. The correlation coefficients between R and total wind stress, alongshore, and offshore component are listed in Table 1. One can see that total alongshore component of wind stress Malong is highly correlated with the upwelling intensity R. The total offshore component has a low correlation coefficient with R. The data points derived from satellite observations from May to August
Satellite Observation of Upwelling along the Western Coast of the South China Sea
Figure 3. Time series of R in km3 ⬚C and M, Malong, and Moff in Pa km2 from May to August 1997.
1997 and the linear relations between upwelling intensity R and total alongshore component of wind stress Malong are shown in Figure 4. One can see a good agreement of the upwelling intensity and the total alongshore wind stress over the whole cold water area. These results indicate that the Ekman transport plays an important role to induce coastal upwelling in the study area. The relative error of the wind stress, dM/M, can be estimated by 2(dV/V) with the assumption that the wind stress M is proportional to the square of the wind speed V. The relative error of upwelling intensity, dR/R, can be estimated by the sum of d(⌬T)/⌬T and (dV/V). The typical wind speed V we choose is 6 m/s. The dV we choose is about 0.6 m/sec because that the rms error of the ERS-2 wind speed is approximately 1.2 m/s with a resolution of 50 km, and our data are on the average of about 100 km resolution (Jet Propulsion Laboratory, 1998). The typical temperature drop ⌬T we choose in this study is about 2⬚C. The d(⌬T) we choose is about 0.29⬚C because that the deviation of the MCSST is about 0.5⬚C, and our data are the 1-day composite of about three individual images per day. Therefore the error bars shown in Figure 4 are about 20% and 25% for dM/Mand dR/R, respectively. Deformation of the Upwelling Region The above results indicate that the Ekman effect appears to be the dominant mechanism to pump the cold water upward to the surface along the Vietnam coast. The southwesterly monsoon can be considered as a spatially Table 1. Correlation Coefficients between the Upwelling Intensity R and Total Wind Stresses M, Malong, and Moff during the period from May to August 1997
R
M
Malong
Moff
0.86
0.88
⫺0.17
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Figure 4. Relationship between R and Malong from May to August 1997. Straight lines are linear regression of the data.
uniform wind field within the scale of the study area. Therefore, induced upwelling should form a cold water band along the Vietnam coast. However, the cold water region was deformed from a nearly south–northward oriented band in May to a very narrow offshore jet in August as shown on AVHRR IR images in Figure 2. This deformation and movement process of the cold water area can be characterized by movement of its thermal centroid, (Xc, Yc), which is defined as in Eqs. (5) and (6): X c⫽
兺i XiTi , 兺i Ti
(5)
兺i YiTi , 兺i Ti
(6)
and Y c⫽
Figure 5. Southward movement of upwelling centroid with time.
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Figure 6. Dynamic heights (in dyn. m) based on climatological data of the South China Sea in the summertime (from Xu et al., 1982). CJ represents the cold water jet with temperature less than 27⬚C, AC1 represents the warm-core ring with core temperature higher than 28⬚C, and AC2 represents the anticyclone in the south.
where Ti is sea surface water temperature at (Xi, Yi). Figure 5 shows the variation in north–south direction of the location (Xc, Yc) from May to August 1997. One can see that the thermal centroid of the cold water was located at about 14⬚N in May and moved quickly to south to about 11.7⬚N in June, then shifted southward slowly during July and August to about 11.3⬚N. Figure 6 shows the sea surface dynamic heights calculated by Xu et al. (1982) based on the climatological data of the SCS. One can see that a relative low water filament off the coast of central Vietnam was confined in the confluent zone between two anticyclonic high waters: One was in the north and the other one in the south during the summertime. The AVHRR IR image taken on 13 August 1996 shown in Figure 7a and the interpretation map shown in Figure 7b also provide further evidence for existence of coastal upwelling and sea surface circulation patterns. One can see an anticyclonic gyre in the north of the cold offshore jet. In addition, the weekly mean sea surface height anomaly (SSHA) derived from
Figure 7. a) AVHRR IR image taken on 13 August 1996 showing upwelling area along the Vietnam coast south of 12⬚N and an anticyclonic circulation east of the Vietnam coast and b) an interpretation map of a).
TOPEX/POSEIDON and ERS-2 satellite altimeter data during the same period of NOAA AVHRR images in Figure 2 are shown in Figure 8. One can see that SSHA patterns are very close to the results of Xu et al. (1982). These results indicate that coastal upwelling constitutes an important component of the circulation system in the western SCS. Thus, the deformation and movement of
Satellite Observation of Upwelling along the Western Coast of the South China Sea
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Figure 8. Contours of sea surface height anomaly on a) 7 May, b) 9 June, c) 9 July, and d) 14 August 1997. They were derived from TOPEX/POSEIDON and ERS-2 satellite altimeters by the Colorado Center for Astrodynamics Research (CCAR) (Web site: http:// www-ccar.colorado.edu/~realtime/global-historical_ssh/).
the upwelled cold water area are certainly associated with the two mesoscale anticyclonic gyres. SUMMARY We observed upwelling along the western coast of the SCS using NOAA AVHRR images received in 1996 and 1997 summer. The images showed the entire view of upwelling area with spatial and temporal resolutions much higher than that derived from field measurements and numerical modeling by previous investigators. In order to describe the evolution process of upwelling quantitatively, we defined a parameter, upwelling intensity, which includes contributions of upwelling area, SST difference,
and upwelling depth derived from simultaneous ERS-2 wind data. Correlation analysis indicated that observed upwelling is mainly induced by the alongshore component of the summer southwesterly monsoon. The analyses also indicated that sea surface circulation system, characterized by two anticyclonic warm gyres which sandwich a cold jet, is responsible for deformation of upwelling area and southward movement of the thermal centroid of the cold water area. Therefore, we may conclude that the observed coastal upwelling belongs to a type of wind-induced and current-modified upwelling. We are indebted to the National Science Council (NSC) of the Republic of China (ROC) and National Taiwan Ocean Univer-
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sity for supporting to build the NOAA AVHRR HRPT receiving station at Tai-Ping Island. We thank Wei-Kang Hu for processing satellite data. This work was supported by the NSC, ROC under Grants NSC 86-2611-M-019-004-OS, NSC 87-2611-M-019-AP7, and NSC 88-2611-M-019-007-AP7, and partly supported by U.S. NASA Oceanography Program under Grant NAG5-7949 (Q. Z.).
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