Satellite-derived Sea Surface Temperature Data Research Articles

Monitoring red tide with satellite imagery and numerical models: A case study in the Arabian Gulf

A red tide event that occurred in August 2008 in the Arabian Gulf was monitored and assessed using satellite observations and numerical models. Satellite observations revealed the bloom extent and evolution from August 2008 to August 2009. Flow patterns of the bloom patch were confirmed by results from a HYCOM model. HYCOM data and satellite-derived sea surface temperature data further suggested that the bloom could have been initiated offshore and advected onshore by bottom Ekman layer. Analysis indicated that nutrient sources supporting the bloom included upwelling, Trichodesmium, and dust deposition while other potential sources of nutrient supply should also be considered. In order to monitor and detect red tide effectively and provide insights into its initiation and maintenance mechanisms, the integration of multiple platforms is required. The case study presented here demonstrated the benefit of combing satellite observations and numerical models for studying red tide outbreaks and dynamics.

A comparison of satellite-derived sea surface temperature fronts using two edge detection algorithms

Satellite-derived sea surface temperature (SST) fronts provide a valuable resource for the study of oceanic fronts. Two edge detection algorithms designed specifically to detect fronts in satellite-derived SST fields are compared: the histogram-based algorithm of Cayula and Cornillon (1992, 1995) and the entropy-based algorithm of Shimada et al. (2005). The algorithms were applied to 4 months (July and August for both 1995 and 1996) of SST fields and the results are compared with SST data taken by the M.V. Oleander, a container ship that makes weekly transits between New York and Bermuda. There is no significant difference in front pixels found with the Cayula-Cornillon algorithm and those found in the in situ (Oleander) data. Furthermore, for strong fronts, with gradients greater than 0.2K/km, the distribution of fronts found with the Shimada et al. algorithm is quite similar to that of fronts found with the Cayula-Cornillon algorithm. However, there are significant differences in the number of weak fronts found. This is seen clearly in waters south of the Gulf Stream where the gradient magnitude of fronts found is less than 0.1K/km. In this region, the probability that the Shimada et al. algorithm detects a front rarely falls below 4% while neither the Cayula-Cornillon algorithm applied to the satellite-derived SST fields nor the gradient-based algorithm applied to the Oleander temperature time series find fronts more than 1% of the time. These results raise the question of exactly what qualifies as an SST front, a classic problem in edge detection.

The Influence of Loop Current Position on Winter Sea Surface Temperatures in the Florida Straits

Abstract Influences of the Gulf of Mexico's Loop Current (LC) position on the sea surface temperature (SST) in the Florida Straits (FS) during the winter season are investigated. Satellite-derived SST data are analyzed on the basis of the LC configuration (mature or immature) as determined by satellite altimetry analyses. Cumulative distributions of FS SSTs for both LC phases during the months of January and February show greater likelihood of cooler SSTs in the FS during a mature LC than during an immature LC. This work suggests that differing transit times of LC water parcels during mature and immature phases result in differences in heat loss of the LC near-surface water. This may contribute to the observed SST differences in FS during mature and immature LC phases via temperature advection.

Assessment of the MODIS and AMSR-E-Derived SST Products in joining area of Asia and Indian-Pacific Ocean

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer (AMSR-E) aboard the NASA Earth Observation System’s Aqua satellite have been measuring the sea surface temperature (SST) since 2002. Although satellite-derived SST data complement the ground-based SST field data in better understanding the role of SST in coupling the ocean and atmosphere, they need to be validated in order to determine the spatiotemporal variation of their availability, and their error features, and then to decide how they can be used for further applications. In this paper we assess the spatiotemporal coverage and error variation of MODIS and AMSR-E level-3 mapped SSTs during 2003 to 2005 over the joining area of Asia and the Indian-Pacific Ocean. Drifting buoy SST data obtained from the Atlantic Oceanographic and Meteorological Laboratory (AOML) is used as a benchmark for the study. The results show that multi-year and annual average availabilities of MODIS SSTs are lower than those of AMSR-E SSTs due to their different cloud penetration. Weekly mean availability of AMSR-E SSTs is nearly constant during 2003–2005 whereas that of MODIS SSTs shows obvious seasonal variation, i.e. it is low in summer and high in spring and autumn. The intra-annual variation of MODIS and AMSR-E availability is similar for the three year period. The geographical signal of annual mean availability of MODIS is more obvious than that of AMSR-E, i.e. it is high at about latitudes 20°N and 20°S and low around the equatorial regions. For error feature, the overall accuracy and precision of MODIS SSTs are lower than those of AMSR-E SSTs due to their slight differences in atmospheric effects, cloud penetration, spatial resolution, measured depths, and retrieval algorithms. Even so, annual mean biases of these two datasets are both within 0.5 °C. The intraannual variation of the error feature of MODIS is much more obvious than that of AMSR-E due to the wider range of mean bias and standard deviation. The intraannual variations of MODIS and AMSR-E error are similar for the three year period. We also find that the accuracy and precision of MODIS and AMSR-E have an obvious geographical signal for the three year period. That is, the accuracy and precision become higher moving from mid-latitudes of the northern hemisphere through equatorial regions to mid-latitudes of the southern hemisphere.

Spatial and Temporal Characterization of Sea Surface Temperature Response to Tropical Cyclones*

Abstract The spatial structure and temporal evolution of the sea surface temperature (SST) anomaly (SSTA) associated with the passage of tropical cyclones (TCs), as well as their sensitivity to TC characteristics (including TC intensity and translation speed) and oceanic climatological conditions (represented here by latitude), are thoroughly examined by means of composite analysis using satellite-derived SST data. The magnitude of the TC-generated SSTA is larger for more intense, slower-moving, and higher-latitude TCs, and it occurs earlier in time for faster-moving and higher-latitude storms. The location of maximum SSTA is farther off the TC track for faster-moving storms, and it moves toward the track with time after the TC passage. The spatial extension of the cold wake is greater for more intense and for slower-moving storms, but its shape is quite independent of TC characteristics. Consistent with previous studies, the calculations show that the mean SSTA over a TC-centered box nearly linearly correlates with the wind speed for TCs below category 3 intensity while for stronger TCs the SSTA levels off, both for tropical and subtropical regions. While the linear behavior is expected on the basis of the more vigorous mixing induced by stronger winds and is derived from a simple mixed-layer model, the level-off for intense TCs is discussed in terms of the dependence of the maximum amplitude of the area-mean SSTA on TC translation speed and depth of the prestorm mixed layer. Finally, the decay time scale of the TC-induced SSTA is shown to be dominated by environmental conditions and has no clear dependence on its initial magnitude and on TC characteristics.

The Kuroshio variations from satellite-derived sea surface temperature and Argos satellite-tracking Lagrangian drifters

This study aimed to identify the spatial and temporal variations of the Kuroshio using satellite-derived Sea Surface Temperature (SST) data and a total of 585 Argos satellite-tracking Lagrangian drifters during 1987–2006 in the northwestern Pacific Ocean. The threshold of high surface velocity, more than 75 cm s–1, was used to determine the location of the Kuroshio Current and found that its width ranged from 50 to 100 km. Moreover, this study first conducted a synoptic view for three predominant regions of the Kuroshio, including the area east of Taiwan, the area east of the East China Sea (ECS) and the area south of Japan. We found that the Kuroshio flows at a three-step increase in speed from upstream to downstream. The maximum mean surface velocity, 153 cm s–1, occurred to the south of Japan. Furthermore, the higher surface velocity of the Kuroshio was usually during the summertime (from April to September). In addition, the four-cruise CTD (Conductivity, Temperature, Depth)-transect data observed in January 2005 were collected to identify and validate the path of the Kuroshio axes. The results showed that the measure of 17.5°C at a depth of 200 m could be regarded as an indicator of the Kuroshio axis, corresponding with the maximum surface velocities of the Argos drifters. The monthly satellite-derived SST values of the Kuroshio were usually more than 10°C, so it was difficult to find a specific isotherm to express the location of the Kuroshio. However, extensive Kuroshio fronts derived from satellite SST data were found in this study. These Kuroshio fronts, associated with high SST gradients, were usually located on the boundary between the warm water of the Kuroshio and the colder water of the shelf, corresponding with the boundary of high surface velocity of the Argos drifters. Consequently, this study suggests that these Kuroshio fronts can be regarded as an effective indicator of the Kuroshio paths and its main axes.

Spatial and temporal variability of satellite-derived sea surface temperature in the southwestern Atlantic Ocean

Abstract Mean fields, seasonal cycle, and interannual variability of the Southwestern Atlantic Ocean (SAO) sea surface temperature (SST) distribution are examined during an 18-year (January 1985–December 2002) period by means of monthly composite, around 9 km resolution satellite-derived SST data. Temporal evolution of the mean spatial value shows a very marked annual cycle, certain interannual variability and a weak increasing tendency (∼0.06 °C/decade). Spatial distribution of the mean temporal value shows the influence of the horizontal advection over the SST field. Over 90% of the temporal variability is explained by the annual harmonic, which reaches amplitudes of 7 °C over the shallowest zones. The inclusion of the semiannual harmonic improves the description of the seasonal cycle only in those regions of the domain where warming and cooling cycles show different durations. The strong correlation between the surface heat flux and the SST allows, by means of a single diffusion equation, the prediction of the shelf areas which do not stratify seasonally. The EOF analysis shows three modes (which together explain over 97% of the variance) associated with the stationary value, the amplitude and the phase of the annual harmonic, i.e., with the seasonal cycle. The fourth mode (0.22% of the variance) is the first one to show interannual variability, which is well correlated with the Southern Annular Mode (SAM).

Building an Automated Integrated Observing System to Detect Sea Surface Temperature Anomaly Events in the Florida Keys$^{\ast}$

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Satellite-derived sea surface temperature (SST) images have had limited applications in near-shore and coastal environments due to inadequate spatial resolution, incorrect geocorrection, or cloud contamination. We have developed a practical approach to remove these errors using Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS) 1-km resolution data. The objective was to improve the accuracy of SST anomaly estimates in the Florida Keys and to provide the best quality (in particular, high temporal and spatial resolutions) SST data products for this region. After manual navigation of over 47 000 AVHRR images (1993–2005), we implemented a cloud-filtering technique that differs from previously published image processing methods. The filter used a 12-year climatology and <formula formulatype="inline"><tex Notation="TeX">$\pm$</tex> </formula>3-day running SST statistics to flag cloud-contaminated pixels. Comparison with concurrent ( <formula formulatype="inline"><tex Notation="TeX">$\pm$</tex></formula>0.5 h) data from the SEAKEYS <emphasis emphasistype="italic"> in situ</emphasis> stations in the Florida Keys showed near-zero bias errors <formula formulatype="inline"><tex Notation="TeX"> $(≪ 0.05\ ^{\circ}\hbox{C})$</tex></formula> in the weekly anomaly for SST anomalies between <formula formulatype="inline"><tex Notation="TeX">$-$</tex></formula>3 <formula formulatype="inline"><tex Notation="TeX">$^{\circ}\hbox{C}$</tex> </formula> and 3 <formula formulatype="inline"><tex Notation="TeX">$^{\circ}\hbox{C}$</tex></formula>, with standard deviations <formula formulatype="inline"><tex Notation="TeX">$≪ 0.5\ ^{\circ}\hbox{C}$</tex></formula>. The cloud filter was implemented using Interactive Data Language for near-real-time processing of AVHRR and MODIS data. The improved SST products were used to detect SST anomalies and to estimate degree-heating weeks (DHWs) to assess the potential</para>

Building an Automated Integrated Observing System to Detect Sea Surface Temperature Anomaly Events in the Florida Keys

Satellite-derived sea surface temperature (SST) images have had limited applications in near-shore and coastal environments due to inadequate spatial resolution, incorrect geocorrection, or cloud contamination. We have developed a practical approach to remove these errors using Advanced Very High Resolution Radiometer (AVHRR) and MODerate-resolution Imaging Spectroradiometer (MODIS) 1-km resolution data. The objective was to improve the accuracy of SST anomaly estimates in the Florida Keys and to provide the best quality (in particular, high temporal and spatial resolutions) SST data products for this region. After manual navigation of over 47 000 AVHRR images (1993-2005), we implemented a cloud-filtering technique that differs from previously published image processing methods. The filter used a 12-year climatology and plusmn3-day running SST statistics to flag cloud-contaminated pixels. Comparison with concurrent ( plusmn0.5 h) data from the SEAKEYS <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in</i> <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">situ</i> stations in the Florida Keys showed near-zero bias errors (<0.05degC) in the weekly anomaly for SST anomalies between -3degC and 3degC, with standard deviations <0.5degC. The cloud filter was implemented using Interactive Data Language for near-real-time processing of AVHRR and MODIS data. The improved SST products were used to detect SST anomalies and to estimate degree-heating weeks (DHWs) to assess the potential for coral reef stress. The mean and anomaly products are updated weekly, with periodic updates of the DHW products, on a Web site. The SST data at specific geographical locations were also automatically ingested in near real time into National Oceanic and Atmospheric Administration's (NOAA) Integrated Coral Observing Network Web-based application to assist in management and decision making through a novel expert system tool (G2) implemented at NOAA.

Shelf water entrainment by Gulf Stream warm-core rings between 75°W and 50°W during 1978–1999

Previous work concerning Gulf Stream warm-core rings (WCRs) and their associated shelf water entrainments have been based upon single surveys or time series from individual WCRs. To date, estimates of annual shelf water volume entrained into the Slope Sea by WCRs and its interannual variability have not been made. Using a long time series of satellite-derived sea surface temperature (SST) observations of Slope Sea WCRs, we have completed an analysis of 22 years of WCR data (1978–1999) between 75°W and 50°W to understand the interannual variability of WCRs and their role in entraining shelf water. Satellite-derived SST data digitized at Bedford Institute of Oceanography are analyzed using an ellipse-fitting feature model to determine key WCR characteristics including WCR center position, radius and orientation. Key characteristics are then used to compute WCR swirl velocity by finite-differencing WCR orientations ( θ) obtained from the feature model time series. Global mean WCR-edge swirl velocity calculated from all observations is 105.72±10.7 km day −1 (122.36±12.4 cm s −1), and global mean WCR radius is 64.8±6.2 km. Primary and derived WCR data are incorporated into a two-dimensional ring entrainment model (RM) using the quasi-geostrophic approximation of the potential vorticity equation. The RM defines ambient water as entrained by a WCR only if the gradient of relative vorticity term (horizontal shear) dominates the potential vorticity. Proximity of a WCR to the position of the shelf-slope front (SSF) is then used to determine whether the ambient water is entrained from the outer continental shelf. WCR-induced shelf entrainment derived from the RM displays considerable spatial variability, with maximum entrainment occurring offshore of Georges Bank, advecting a mean total annual shelf water volume of 7500 km 3 year −1 from the region. Estimates of shelf water fluxes display significant interannual variability, which may be in part due to the observed covariance between WCR occurrences and the state of the North Atlantic Oscillation (NAO). Increased (decreased) occurrences of WCRs are evidenced during positive (negative) phases of the NAO. The total mean annual shelf-wide WCR-induced shelf water transport is estimated to be 23,700 km 3 year −1 (0.75 Sv), accounting for nearly 25% of the total transport in the Slope Sea region neighboring the outer continental shelf.

Generating time-series grid data of sea surface temperature from isotherms in the Northwestern Pacific Ocean using coupled interpolation

Sea surface temperature (SST) isoline charts that were manually mapped using in situ SST data and satellite-derived SST data are valuable because they incorporate oceanographers’ knowledge and experience. This type of SST data is useful for studying sea conditions of an area, for analyzing environmental factors that could affect fishing grounds, as a parameter for atmospheric or oceanic models, or as a diagnostic tool for comparison with the SSTs produced by ocean models. However, isoline maps must be digitized and interpolated into grid data in order to be used in these applications. Herein, we propose a coupled interpolation (CI), which couples improved multi-section interpolation and single-point change surface interpolation containing orientation, for generating grid data from SST isolines. We interpolated 1049 SST isoline maps (temperature interval 1°), which cover an area of the northwestern Pacific Ocean (125°E–180°E, 26°N–50°N) and were published by the Japan Fisheries Information Service Center (JAFIC) during 1990–2000, to grid datasets with 15′ grid resolution. We assessed the quality of grid datasets by checking noise points, RMSE analysis, checking offset errors, retrieving percentage of Kuroshio axes and visually comparing inverse isotherms with original isotherms. The quality analysis and comparison with four other interpolators showed the CI interpolator to be a good technique for generating SST grid data from isotherms. We also computed the SST anomaly (SSTA) using the SST grid datasets. The amplitude values of integral SSTA in the area of 31–46°N, 170–180°E were low, whereas they were high in the SW–NE rectangular area of 35–46°N, 142–160°E.

A high-resolution satellite-derived sea surface temperature climatology for the western North Atlantic Ocean

Long-term and high-resolution (∼1.2 km) satellite-derived sea surface temperature (SST) fields of a monthly mean time series for the 1985–1999 period, and a daily climatology have been calculated for the North West Atlantic Ocean. The SST fields extend from 78°W to 41°W in longitude, and 30°N to 56°N in latitude, encompassing the region off Cape Hatteras, North Carolina, to the southern Labrador Sea. The monthly mean time series, consists of 180 cloud-masked monthly mean SST fields, derived from a full-resolution NOAA/NASA Pathfinder SST data set for the 1985–1999 period. The satellite-derived monthly mean SST fields, as compared with in situ monthly mean near-surface ocean temperatures from buoys located in the western North Atlantic, yield an overall RMS difference of 1.15 °C. The daily climatology, which consists of 365 fields, was derived by applying a least-squares harmonic regression technique on the monthly mean SST time series for the full study period. The monthly mean and daily climatological SST fields will be useful for studying inter-annual variability related to climate variability of SST over the study domain.

Relationships between satellite-measured thermal features and Alexandrium-imposed toxicity in the Gulf of Maine

Relationships between satellite-derived sea-surface temperature (SST) patterns and the occurrence of paralytic shellfish poisoning (PSP) toxicity events caused by Alexandrium fundyense in the western Gulf of Maine are examined. Comparisons between surface A. fundyense cell distribution patterns and SST images indicate that highest cell concentrations are associated with colder waters of the eastern segment of the Gulf of Maine coastal current (EMCC) and that frontal zones at the edges of the EMCC often act as boundaries to surface distributions. Surface thermal patterns coincident with a May 2000 PSP toxic event and shellfish harvesting closure on the western Maine coast show enhanced connectivity between the EMCC and the western Gulf of Maine, suggesting transport linking A. fundyense cells in the EMCC to inshore areas of the western Gulf of Maine. Surface drifter data support such transport. Thirteen years (1990–2002) of toxicity data from eight monitoring sites along the coast of Maine and concurrent SST data show that in years of either large or very reduced toxicity, a consistent relationship exists between the timing and strength of fronts, taken as an indicator of alongshore connectivity, and the occurrence and strength of toxic events. Years with weak fronts and/or fronts that become established relatively late in the summer growing season are years of the strongest toxicity events in western Gulf of Maine. Years of early and strong fronts are years with few and/or weak toxicity events. Our results suggest that advective connections exist between cells present in the EMCC and toxicity along the western Gulf of Maine coast and that largescale hydrographic processes, characterized here as surface thermal patterns, influence A. fundyense populations in the western Gulf of Maine, either through delivery of actual cells or advection of advantageous conditions into the region. These data point to the utility of satellite and other coastal observing system data for the monitoring and prediction of conditions linked to toxic events in coastal waters. r 2005 Published by Elsevier Ltd.

Using PPCA to Estimate EOFs in the Presence of Missing Values

Abstract One of the problems encountered when using satellite-derived sea surface temperature (SST) data is the impossibility of retrieving data where the ocean surface is obscured by cloud. Empirical orthogonal function (EOF) analysis cannot be carried out easily when there are missing values within the dataset. One possible solution is to interpolate using the existing data. In this paper an alternative technique is investigated, probabilistic principal component analysis (PPCA), and applied to calculate the principal EOFs of North Atlantic SSTs. This analysis uses results obtained from interpolating the SST data using a simplified Kalman filter, with data randomly removed to simulate missing values, and then reconstructs the data using PPCA, obtaining the principal EOFs. The calculation of the EOFs was quicker than traditional EOF analysis, as the covariance matrix was estimated rather than calculated. The replacement of missing values was also computationally more efficient than using the Kalman filte...

Simulating the temporal and spatial dynamics of the North Sea using the new model GETM (general estuarine transport model)

Here we present results of a 1-year realistic North Sea simulation from the new model GETM (general estuarine transport model) and assess the capabilities of this model by comparing them to model results from the well-known HAMSOM (Hamburg shelf sea and ocean model) model, in situ data from the North Sea project and satellite-derived sea-surface temperature data. The annual cycle and the spatial variability of stratification and mixing in the North Sea is simulated. It is shown that the new model is successful in reproducing the general temporal and spatial dynamics of the North Sea. The major advantages of GETM for achieving improved results in this simulation are the implementation of general vertical coordinates, of a state-of-the-art turbulence model and of higher-order advection schemes. By exploiting the full capabilities of these features a more realistic simulation could be achieved. We found that the greatest differences in the model results are produced by applying advection schemes of different complexity. Here we are able to demonstrate that better advection schemes lead to stronger horizontal gradients and stronger vertical stratification during summer. When comparing these results to measurements from the North Sea project and to satellite data, we find that these stronger gradients are more realistic. Therefore, we consider it as essential to use such high-order advection schemes if the spatial variability of estuarine or shelf seas like the North Sea is to be resolved adequately. The advanced turbulence closure scheme also contributed to more realistic simulation of the vertical stratification. Finally, general vertical coordinates better resolve the shallow regions, but are also useful for the deeper regions, as they allow a better estimation of sea-surface temperature compared to traditional σ coordinates.

Inverse estimation of sea surface heat flux over the equatorial Pacific Ocean: Seasonal cycle

An assimilation of satellite‐derived sea surface temperature (SST) observations into the Poseidon quasi‐isopycnal ocean model is conducted to study the seasonal cycle of surface thermodynamics of the equatorial Pacific Ocean and to estimate the sea surface heat flux inversely from the SST observations. A simplified approach in the use of the thermodynamic submodel that separates the momentum and the temperature fields in the variational assimilation procedure proves successful in improving the model simulation of the observed SST. From a comparison with several existing bulk estimates, it is seen that the seasonal cycle of sea surface heat flux has been captured well by the inversion except in the eastern equatorial Pacific, where the optimized surface heat flux shows an upward flux during the boreal summer/fall season when the cold tongue SST starts to decrease dramatically. This spurious upward surface heat flux is inconsistent with the bulk estimates and is determined to be due to model deficiencies in calculating vertical turbulent diffusion. The SST data assimilation is shown to have improved the model simulation of horizontal temperature advection significantly. A comparison of the inferred heat budget is made with an analysis by Wang and McPhaden [1999] from TAO mooring observations.

Toward Improved Validation of Satellite Sea Surface Skin Temperature Measurements for Climate Research

A poor validation strategy will compromise the quality of satellite-derived sea surface temperature (SST) products because confidence limits cannot be quantified. This paper addresses the question of how to provide the best operational strategy to validate satellite-derived skin sea surface temperature (SSTskin) measurements. High quality in situ observations obtained using different state-of-the-art infrared radiometer systems are used to characterize the relationship between the SSTskin, the subsurface SST at depth (SSTdepth), and the surface wind speed. Data are presented for different oceans and seasons. These data indicate that above a wind speed of approximately 6 m s−1 the relationship between the SSTskin and SSTdepth, is well characterized for both day- and nighttime conditions by a cool bias of −0.17 ± 0.07 K rms. At lower wind speeds, stratification of the upper-ocean layers during the day may complicate the relationship, while at night a cooler skin is normally observed. Based on these observations, a long-term global satellite SSTskin validation strategy is proposed. Emphasis is placed on the use of autonomous, ship-of-opportunity radiometer systems for areas characterized by prevailing low–wind speed conditions. For areas characterized by higher wind speed regimes, well-calibrated, quality-controlled, ship and buoy SSTdepth observations, corrected for a cool skin bias, should also be used. It is foreseen that SSTdepth data will provide the majority of in situ validation data required for operational satellite SST validation. We test the strategy using SSTskin observations from the Along Track Scanning Radiometer, which are shown to be accurate to approximately 0.2 K in the tropical Pacific Ocean, and using measurements from the Advanced Very High Resolution Radiometer. We note that this strategy provides for robust retrospective calibration and validation of satellite SST data and a means to compare and compile in a meaningful and consistent fashion similar datasets. A better understanding of the spatial and temporal variability of thermal stratification of the upper-ocean layers during low–wind speed conditions is fundamental to improvements in SST validation and development of multisensor satellite SST products.

Hydrographic and Satellite Observations of Summertime Upwelling in the Taiwan Strait: A Preliminary Description

Combination of the hydrographic and satellite-derived Sea Surface Temperature (SST) data provides Dew evidence for the existence of four Upwelling-related Low Temperature Zones (LTZs) in the Taiwan Strait in summer. These LTZs are located along the southwestern coast of the Taiwan Strait (SW-LTZ), along the northwestern coast of the Taiwan Strait (NW-LTZ), near the Taiwan Bank (TB-LTZ) and around the Penghu Islands (PH-LTZ), respectively. The hydrographic data from three August cruises during 1997-1999 show that these LTZs also possess relatively higher salinity (greater than 34) at the surface layer. Four years of higher resolution AVHRR satellite-derived SST data clearly indicate the summertime pattern of these upwelling-related LTZs and demonstrate their inter-annual and inter-monthly variability.

An application of satellite-derived sea surface temperature data to the Australian fishing industry in near real-time

Abstract A four-year project conducted from 1981 to 1985 examined the application of satellite-derived near real-time sea surface temperature data in assisting the Tuna fishing industry located along the southwestern coast of Australia. The satellite imagery employed was obtained from the NOAA series of polar orbiting satellites. Since the southern bluefin tuna is a pelagic species, it had been anticipated that a good correlation would be found between sea surface temperatures and catches. Early experimental results tended to confirm that view, but a number of anomalies existed in those results. It is now suggested that a weak correlation exists between temperature and catches, but this is due to localized factors. A theory justifying this assumption is given.

Time and space scales of surface temperatures in the Tasman Sea, from satellite data

Five years (1979–1984) of satellite-derived sea surface temperature data for the Tasman and Southern Coral seas (20–45°S, 150–175°E) show time scales of 80 days and space scales of 125 km in the East Australian Current area, with longer time scales off the west coast of New Zealand's South Island. The Tasman Front, hitherto not well documented, appears as a band of high sea surface temperature variance leading from the East Australian Current area eastwards to North Cape, New Zealand.