Nan-Jung Kuo

Satellite observation of upwelling along the western coast of the South China Sea

Abstract We 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.

Seasonal variability of sea surface height in the South China Sea observed with TOPEX/Poseidon altimeter data

TOPEX/Poseidon altimeter measurements along 16 ground tracks in the South China Sea from November 1992 to October 1997 were used to observe the seasonal variability of sea surface height (SSH). In winter (November, December, January, and February) the SSH images are generally characterized by a sea surface tilting downward toward the east. High sea levels on the western side of the sea have a little monthly change, and a low (minus) sea level peak is centered in the northeastern deep basin. In spring (March and April), a single high sea level peak (HP) centered at 14°N, 114°E becomes a dominant feature. In summer (May, June, July, and August) the SSH images show a sea surface tilting downward toward the west. The HP moves from 14°N, 114°E in May to the northwest of Luzon Island in July. Low sea levels are centered in the offshore of the northern and southern Vietnamese coast. In fall (September and October) the appearance of an eastward low sea level jet in the western basin between 12° and 14°N constitutes a major feature of the SSH images. These results are comparable with previous results and drifter measurements.

Dynamically Active Areas in the South China Sea Detected from TOPEX/POSEIDON Satellite Altimeter Data

Abstract TOPEX/POSEIDON (T/P) altimeter measurements from December 1992 to April 1998 were processed to study the sea surface height (SSH) variation in the South China Sea (SCS). Patterns of variance of the SSH deviations from the four-year (1993–1996) mean show that there are three high-variation areas in the deep basin. The first is at the northern basin west of Luzon Island (16°–18° N, 117°–119° E), the second is at the center of the SCS (14°–16° N, 113.5°–114.5° E), and the third is off the central Vietnam coast (12°–13° N, 110°–112° E). From empirical orthogonal function (EOF) analysis, we found that the variations of these three active areas are dominated by annual cycles, but out of phase. The first two areas have the highest SSH in June and the lowest SSH in December. The third one off the Vietnam coast has the highest SSH in February and the lowest SSH in August. The EOF analysis also reveals that the variation of SSH in the SCS has a response to El Nino events.

Coastal lee waves on ERS-1 SAR images

Alternative dark-bright patterns on ERS-1 synthetic aperture radar (SAR) images of the west side of the Taiwan Strait taken on December 8, 1994, were recognized to be the sea surface signature of a coastal lee wave. Such waves are called coastal lee waves because they occur along the lee side of the coast. The coastal lee waves appeared in the form of a wave packet distributed within an offshore band 20–40 km wide. The first packet, which occurred in the northern portion of the observed area, contained six waves with variable wavelengths (defined as the spatial separation between two waves) from 1.7 to 2.7 km. The second packet, in the middle, contained 10 waves with a relatively uniform wavelength of 4.2 km. The third packet, in the southern portion, contained 17 waves with an average wavelength of 2.0 km. The crest lengths were from 20 to 80 km. Local meteorologic parameters observed simultaneously at Fuzhou, China, close to the imaged area, showed an offshore wind of 1.5–3.5 m/s and a land surface air temperature of 19°C, which was 4°C lower than the sea surface temperature (SST). Thus the lower atmospheric boundary conditions at imaging time were very favorable both for generating the land breeze circulation and small wind waves on the sea surface, which are in the Bragg-scattering wavelength band of the C band ERS-1 SAR. A physical model of a three-layer atmosphere was developed in order to explain how the land breeze circulation can generate the coastal lee waves. The results showed that the vertical velocity disturbance caused by the wind convergence at the land breeze frontal zone is of vital importance for the generation of coastal lee waves, and the model gave very good estimates of the processes observed. The SAR imaging mechanisms of the waves were analyzed in detail. The differences between coastal lee waves and ocean internal waves, which appear as similar alternative dark-bright patterns on SAR images, were also discussed.

Observation of the Kuroshio intrusion region in the South China Sea from AVHRR data

The variability of sea surface temperature in the region of the Kuroshio intrusion into the South China Sea (SCS) through the Luzon Strait was studied using sea surface temperature (SST) derived from Advanced Very High Resolution Radiometer (AVHRR) from 1985 to 2002. The covariance empirical orthogonal function (CEOF) method was applied for analysing the temporal and spatial variability in the study area. The results show that the Kuroshio intrusion during El Niño periods is weaker than that in La Niña periods. The calculation of surface layer heat of the Kuroshio intrusion region also shows response to the El Niño-La Niña events. The variation is attributed to the changes in wind fields during those events.

Statistical Characteristics of Mesoscale Eddies in the North Pacific Derived from Satellite Altimetry

The sea level anomaly data derived from satellite altimetry are analyzed to investigate statistical characteristics of mesoscale eddies in the North Pacific. Eddies are detected by a free-threshold eddy identification algorithm. The results show that the distributions of size, amplitude, propagation speed, and eddy kinetic energy of eddy follow the Rayleigh distribution. The most active regions of eddies are the Kuroshio Extension region, the Subtropical Counter Current zone, and the Northeastern Tropical Pacific region. By contrast, eddies are seldom observed around the center of the eastern part of the North Pacific Subarctic Gyre. The propagation speed and kinetic energy of cyclonic and anticyclonic eddies are almost the same, but anticyclonic eddies possess greater lifespans, sizes, and amplitudes than those of cyclonic eddies. Most eddies in the North Pacific propagate westward except in the Oyashio region. Around the northeastern tropical Pacific and the California currents, cyclonic and anticyclonic eddies propagate westward with slightly equatorward (197° average azimuth relative to east) and poleward (165 °) deflection, respectively. This implies that the background current may play an important role in formation of the eddy pathway patterns.

Using the shape-matching method to compute sea-surface velocities from AVHRR satellite images

The idea of shape matching is applied to track edge features automatically in a pair of AVHRR IR satellite images. The centroid and radius weighted mean are chosen as shape-specific points of the edges in two sequential images. Through the correspondence of these two shape-specific points, the whole edges properties of rotation, translation, and scaling could be obtained. Also, a better correspondence in the second image is chosen according to the similarity comparison. After that, the total velocities of the points in the pattern can be computed. Velocity components in normal and tangential directions for certain points on the edge are also computed through a simple trial-and-error procedure and vector decomposition. >

Estimating amplitudes of internal waves using satellite ocean colour imagery of the South China Sea

A method is presented for estimating the amplitudes of internal waves (IWs) in ocean colour imagery. The method is tested in the northern South China Sea (SCS) because the environmental conditions there are such that IWs are generated frequently and can therefore be observed easily. A relationship between satellite‐derived chlorophyll concentration (chl) and the amplitudes of IWs is obtained. Using a deep chlorophyll maximum (DCM) model, the amplitude at the light penetration depth can be estimated. From theoretical models, the amplitude of an IW at the depth where the maximum vertical isopycnal displacement appears is also derived. The results indicate that the amplitudes of IWs in the northern SCS determined by the methods developed in this study are comparable with historical regional data.

Satellite chlorophyll retrievals with a bipartite artificial neural network model

An artificial neural network (ANN) model with a bipartite classification scheme is developed to retrieve the chlorophyll‐a concentration (Chl) from sea‐viewing wide field‐of‐view sensor (SeaWiFS) data. Bio‐optical data derived from the SeaWiFS bio‐optical algorithm mini‐workshop (SeaBAM) are used to verify this bipartite artificial neural network (BANN) model. In comparison with SeaWiFS operational algorithms and a general ANN model, the BANN model significantly increases the accuracy of Chl retrieval not only on a log scale but also on a normal scale. The BANN model can significantly improve the accuracy of Chl especially in the high Chl region. The model also performs well in a test with in situ measurements from Taiwan coastal waters. The biases induced by errors in atmospheric correction are also reduced in the coastal water case.

The Use of Neural Networks in Identifying Error Sources in Satellite-Derived Tropical SST Estimates

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%.