| dc.description.abstract | In this study, we used satellite remote sensing data to investigate environmental conditions in the coastal zone off river mouth and in the South China Sea. Satellite remote sensing can provide longer time-series data with wider spatial coverage than traditional ship measuredments without using too much manpower or resources.
To study river plume, we used 14 SPOT satellite images of the coastal zone off the Lanyang River mouth in 2005. We applied a supervised maximum likelihood classification procedure to process the satellite images in order to identify the span of the Lanyang River plume. We suspected that Lanyang River plume should be affected by discharge, so we conducted liner regression between Lanyang River discharge and plume area. We found good correlation between them with R2=0.87 and P<0.01. Besides. we used in situ measured current data to demonstrate that the plume identified by the method is credible.
In order to understand the actual Lanyang River plume distribution and hydrological characteristics, we collected water samples in the coastal zone off Lanyang River moth on Oct. 8, 2011. Assuming that the distribution of the low salinity water was similar to the river plume identified by remote sensing images, we used Yilan County’s rainfall data to derive the discharge of the Lanyang River and calculated the plume area from the discharge using the linear regression relationship mentioned above. From the estimated plume area we determined from the salinity distribution that the Lanyang River plume should be within the salinity contour of 29.4 psu. The plume so defined is consistent with the photos taken during the cruise.
To study the open ocean, we used both MODIS and SeaWiFS satellite remote sensing data get 14 years of chlorophyll-a concentration time-series data at the SEATS station from Sep. 1997 to Dec. 2011. We also used NCEP data of wind speed to delineate their relationship with the chlorophyll-a data. In seasonal variability, both wind speed and chlorophyll-a concentration have higher values in winter. In inter-annual variability, we used Hilbert-Huang Transform to analyze the wind speed and chlorophyll-a data. The results show that the trend of both wind speed and chlorophyll-a concentration decreased. The wind speed decreased by 13%. The chlorophyll-a concentration decreased by 19%.
We compared the SEATS station with the Western Philippine Sea. At the SEATS station, wind speed anomaly and chlorophyll-a concentration anomaly have significant correlation when MEI>0 (El Nino phase), and very poor correlation when MEI<0 (La Nina phase). In the West Philippine Sea, the wind speed anomaly and chlorophyll-a concentration anomaly have worse correlation when MEI<0, and better correlation when MEI>0. The contrast probably results from the fact that the south China Sea is a semi-enclosed basin, where the basin wide upwelling was weaker, when MEI<0, while the WPS is an open ocean and strongly modulated by the North Equatorial Current and Mindanao Dome.
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