Environmental effects on yellowfin tuna catch by the Taiwan longline fishery in the Arabian Sea

In this study, we collected environmental variables to investigate their effects on the catch per unit effort (CPUE) of yellowfin tuna in the Arabian Sea during the period 1980–2005. We used an advanced time series analysis, including a state-space approach to remove seasonality, and wavelet analysis to investigate transient relationships. For large-scale environmental effects, we used the dipole mode index (DMI) to represent the Indian Ocean dipole; for local environmental factors, we investigated sea surface temperature (SST), thermocline depth and chlorophyll-a (chl-a) concentration. The main factors causing interannual variations in the CPUE might change with time. CPUE showed positive correlations with SST and DMI from the beginning of the 1980s to the middle of the 1990s. It also showed a significant coherence with chl-a, especially a long-term positive correlation for the regular longline fishery in 1998–2005 with a periodicity of 2 years. Both regular and deep longline CPUEs were found to have significant coherence with thermocline depth having a periodicity of 3 years. The relations were of opposite signs such that the shallow thermocline depth produced a high CPUE for the regular longline fishery and deep thermocline depth caused a high CPUE for the deep longline fishery.     

Distribution of hotspots of chub mackerel based on remote-sensing data in coastal waters of China

Sustainable use of fishery resources requires the effective monitoring and managing of fish stocks and fish habitats. Chub mackerel (Scomber japonicus), distributed in the East China Sea and Yellow Sea, are mainly caught by purse seine fishing fleets from China, Japan, and South Korea. This study used fishery data from Chinese large lighting–purse seine fleets and environmental data including sea surface height (SSH), sea surface temperature (SST) from remote sensing, and temperature gradient derived from SST (GSST) during 1998–2010 to develop habitat suitability index (HSI) models. The HSI models were then used to identify hotspots for chub mackerel for each month. HSI models were developed separately for each of the three distribution areas defined for chub mackerel. According to the frequency distribution of the fishing effort with respect to three environmental variables, suitability index (SI) values were calculated and SI models for each environmental variable were established. The three SI models were combined into two different empirical HSI models: the arithmetic mean model (AMM) and the geometric mean model (GMM). The results showed that the AMM was more suitable than the GMM to estimate the HSI for chub mackerel. The monthly latitudinal variation trend of hotspots was consistent with that of the gravity centres of fishing effort in almost all months. Hotspot maps based on the predicted HSI values were validated by fishery data in 2011. This result indicates that the HSI model based on the AMM can reliably predict hotspots for chub mackerel in the coastal waters of China.     

Using remote-sensing data to detect habitat suitability for yellowfin tuna in the Western and Central Pacific Ocean

The empirical habitat suitability index (HSI) has been widely used to examine the habitat characteristics of terrestrial animals, though rarely used in highly migratory fish such as tuna. This study used the geographic information system technique to establish empirical models of HSI for yellowfin tuna (YFT) in the Western and Central Pacific Ocean (WCPO). Daily catch data from the Taiwanese purse seine fishery during 2003–2007 were aggregated monthly into sequential degrees before match processing the conducted data to obtain monthly remote-sensing data for multi-environmental factors, including sea surface temperature (SST), chlorophyll-a (chl-a), sea surface height (SSH) and sea surface salinity (SSS). According to the frequency distribution of each factor on which YFT were caught, this study transformed the values of the four factors into a suitability index (SI) ranging from low to high (0–1). These SI values were consequently combined into different empirical HSI models, and the optimum models were selected using the general linear model. The optimum empirical HSI for YFT in the study area was converted for SI (SST, SSH, chl-a and SSS) using the arithmetic mean model, of which the correct prediction rate was 71.9%. An agreement was present between the average HSI and total YFT catch. Furthermore, the high HSI area corresponds with the displacement of catch per unit effort (CPUE).     

Influence of SST on catches of swordfish and tuna in the Portuguese domestic longline fishery

Catch‐and‐effort data from a longline vessel operating off the west coast of Portugal, and thermal imagery from NOAA satellites were employed to investigate the aggregation and availability of swordfish, bigeye and albacore tuna in relation to transient coastal upwelling features. We found a decreasing trend in swordfish catch per unit effort (CPUE) and an increasing trend in tuna species CPUE during the study period in apparent association with the progressively increasing intensity of the coastal upwelling regime from year to year. Swordfish CPUE were significantly higher on the warm side of surface thermal fronts associated with events of intensification/relaxation of coastal upwelling. The fishing efficiency for tuna species was significantly higher during peak upwelling conditions, in the close vicinity of mushroom‐like structures at the edge of upwelling filaments. The present results do not support the existence of a preferred sea surface temperature (SST) range for these fish species. It is suggested that several mechanisms leading to the local concentration of prey provide adequate explanations for the aggregation of these species in the vicinity of frontal structures associated with coastal upwelling processes.     

Spatio-temporal distribution of skipjack in relation to oceanographic conditions in the west-central Pacific Ocean

The skipjack tuna, Katsuwonus pelamis, is an economically important oceanic species widely distributed in the west-central Pacific Ocean (WCPO). The spatio-temporal distribution of Katsuwonus pelamis with respect to oceanographic and climatic variables during 1995–2010 in the west-central Pacific was examined in this study using purse seine fishery data from South Pacific Fisheries Commission (SPC). ‘Gravitational centre’ of two temporal scales (i.e. monthly and yearly) of catch per unit effort (CPUE) was calculated to represent the variability of local stock abundance on fishing grounds. Significant inter-annual and seasonal variabilities were observed. Monthly longitudinal ‘centres of gravity’ were correlated with sea surface temperature anomaly (SSTA) in Niño 3.4 region and monthly latitudinal ‘centres of gravity’ reflect a ‘South–North’ migration pattern of Katsuwonus pelamis. The distribution–habitat associations were quantitatively evaluated including SST between 28–30°C, sea surface height (SSH)in the range 90–100 cm, gradient SST between 0.1 and 0.7°C 10 km^?1,and chlorophyll-a(chl-a) between 0.1 and 0.6 mg m^?3 by an empirical cumulative distribution function (ECDF). Four clusters of yearly ‘gravitational centres’ were classified using the k-means method, which could be defined as warmpool fishing ground (WFG) and cold-tongue fishing ground (CFG) according to their oceanographic habitat. The integrated environmental distribution map combined with the developed model (R² = 0.28, p < 0.0001) provides an approach for predicting hotspots of Katsuwonus pelamis. This study improves our understanding of the spatio-temporal dynamics of skipjack tuna, which is critical for sustainable management of this important fisheries resources.     

The relationship between multi-sensor satellite data and Bayesian estimates for skipjack tuna catches in the South Brazil Bight

In this study we tested a Bayesian model based on a conjugate gamma/Poisson pair associated with environmental variables derived from satellite data such as sea surface temperature (SST) and its derived gradient fields from Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra, chlorophyll-a concentration from Sea Viewing Wide field of View Sensor (SEAWiFS)/SeaStar and surface winds and Ekman pumping from SeaWinds/Quick Scatterometer (QuikSCAT) to predict weekly catch estimates of the skipjack tuna in the South Brazil Bight. This was achieved by confronting the fishery data with model estimates and regressing the results on the satellite data. The fishery data were expressed by an index of catch per unit effort (CPUE) calculated as the weight of fish caught (in tonnes) by fishing week, and were divided into two series, called historical series (1996–1998; 2001), and validation year (2002). The output of model CPUE estimates is in good agreement with the historical weekly CPUE and generated updated weekly estimates that explained up to 62% of weekly CPUE from 2002. In general, the best proxy for the Bayesian weekly estimates is the gradient zonal SST field. The results refined previous knowledge of the influence of SST on the occurrence of skipjack tuna.     

Detection of potential fishing zones for neon flying squid based on remote-sensing data in the Northwest Pacific Ocean using an artificial neural network

Ommastrephes bartramii is a short-lived species of squid and reacts rapidly to changes in the regional environmental conditions of the fishing ground. Understanding the preferred range of key environmental variables and predicting potential resource distributions are critical to conserve and manage its resources. Commercial fishery data for the western winter–spring cohort of O. bartramii from Chinese squid-jigging vessels during 2003–2013 were used to evaluate a suitable range of three key environmental variables, sea surface temperature (SST), sea surface height (SSH), and chlorophyll-a (chl-a) concentration, and to explore potential fishing zones (PFZs) using an artificial neural network. The neural interpretation diagram and independent variable relevance analysis indicate that month, latitude, and SST had significant influences on the PFZ distribution of O. bartramii, yielding 21.78%, 23.91%, and 26.04% of contribution rates, respectively. Based on the sensitivity analyses, a high abundance of O. bartramii mainly occurred in the waters between 150°–165° E and 37°–42° N during July to August. Suitable ranges of environmental variables for O. bartramii were 11–18°C for SST, ?10 to 60 cm for SSH, and 0.1–1.7 mg/m³ for chl-a concentration, respectively. The back-propagation network model was well developed and could be used to predict the PFZ with 80% accuracy. The actual fishing grounds coincided with the predicted PFZ, suggesting that the established model of PFZ is effective in forecasting the potential habitat of O. bartramii in the Northwest Pacific Ocean.     

Influence of oceanic climate variability on stock level of western winter–spring cohort of Ommastrephes bartramii in the Northwest Pacific Ocean

The western winter–spring cohort of Ommastrephes bartramii exhibited dynamic stock level associated with concurrent shifts in the Pacific Decadal Oscillation (PDO) during 2002–2011. To explore the potential mechanism on regional oceanic conditions related to the large-scale PDO phenomenon affecting O. bartramii stocks, we examined variations in the environmental condition on the spawning ground for recruitment, spatial distribution of fishing effort, and habitat hotspots on the fishing ground during different PDO phases. The PDO was found to be highly correlated with the biophysical environmental conditions on the spawning and fishing grounds of O. bartramii. The suitable spawning zone (SSZ) considered as an indicator of incubation condition was not sufficient to explain the recruitment variability. However, the changing chlorophyll a (Chl-a) concentration induced variations in feeding condition for squid paralarvae and juveniles, primarily influencing the O. bartramii recruitment. Comparing to the cold PDO phase, high frequency of fishing effort occupied the regions with lower sea surface temperature (SST) and relatively enhanced Chl-a concentration during the warm PDO phase. The location of fishing efforts tended to be intensive and shifted westward and northward in the cold PDO phase. Moreover, the warm PDO yielded prominently enlarged squid habitat hotspots. This study suggests that stock level of western winter–spring cohort of O. bartramii can be explained by the local environmental conditions including the food availability on the spawning ground, SST, and Chl-a concentration on the fishing ground affecting squid spatial distributions, which could be reflected by the PDO climate variability in the Northwest Pacific Ocean.     

Location of tuna resources in Indian waters using NOAA AVHRR data

Abstract

The world demand for tuna resources is ever increasing and there is scope for better economic returns in terms of foreign exchange earnings. It is one of the least exploited resources of the Indian seas. Remote sensing based studies on the tuna environment began in the seventies in the Gulf of Guinea. This study helped to establish a fishing strategy during the eighties. But so far this has not been attempted in Indian waters. With the basic understanding that most of the species of tuna respond directly to temperature, a study using NOAA AVHRR data was carried out to locate tuna resources. Thermal data of NOAA AVHRR for eight dates in the 1989-90 season were analysed to generate sea surface temperature (SST) images. Catch per unit effort (CPUE) of tuna longline data acquired from the Fishery Survey of India pertaining to fishing conducted by chartered vessels, was plotted on the SST images. Yellowfin tuna (YFT) comprises the maximum catch plus small quantities of marlins. It was observed that almost all the data points were located near the edge of warm water (27°-29°C). A relation between average CPUE of YFT and multi-channel sea surface temperature (MCSST) charts generated by OPC (the Ocean Products Centre) of NOAA was established. It shows on an average an increasing trend in the CPUE of YFT from 26° C (hooking rate ～ 1 per cent) to 29°C (hooking rate ～3 65 per cent) and then shows a drop with further rise in temperature. Since YFT is known to be present in a wide range of temperatures, it can be concluded that the location of warm water edges having a gradient of about 1°C and the above mentioned range of temperature will be desirable in locating tuna potential areas.     

An application of satellite-derived sea surface temperature data to the skipjack (Katsuwonus pelamis Linnaeus, 1758) and albacore tuna (Thunnus alalunga Bonaterre, 1788) fisheries in the north-east Atlantic

In April-December 1989, June 1990 and July-October (1990-92), AVHRR/NOAA scenes from the north-east Atlantic (10-50° N and 0-30° W) and Mediterranean Alboran Sea were processed. The objective was to study the relationships between the upper ocean dynamics (synoptic and mesoscale fronts and vorticity) with skipjack tuna (Katsuwonus pelamis Linnaeus, 1758) and albacore tuna (Thunnus alalunga Bonaterre, 1788) fishing ground locations by satellite-derived sea surface temperature (SST) maps and in situ data sets. Results show an analogy between the bioecological responses of both species to the large (SST seasonal drifts) and small-scale oceanographic events (eddy fields, as a consequence of their similar physiological response to all the anomalies at sea.     

Typhoon-enhanced upwelling and its influence on fishing activities in the southern East China Sea

Ocean–atmosphere interactions before and after the passage of Typhoons Haitang, Fung-wong, and Morakot across the southern region of the East China Sea (ECS) were examined by assessing satellite measurements of sea surface temperature (SST) and chlorophyll-a (chl-a) concentration in conjunction with wind data. In terms of the satellite-derived data, the SST declined and chl-a concentration increased after the passage of the typhoons, and this could have resulted from the upwelling induced by typhoons via their long-duration, strong winds. According to fisheries data collected after the passing of Typhoon Morakot, the major fishing grounds of the torchlight fishery were found to have shifted northwards from the northern tip of Taiwan to the southern ECS. Moreover, the major target fish species changed from skipjack tuna (pre-typhoon) to squid (post-typhoon), signifying that the typhoon-enhanced upwelling might have caused the skipjack tuna, which typically prefer warm water, to have migrated elsewhere. In contrast, the nutrient-rich, upwelled water might have directly led to increases in chl-a concentrations and contributed the increase in local squid densities. This study suggests that typhoons can cause marked cooling of the sea surface as well as enhance upwelling that previously resulted in not only chl-a increases but also changes of local fish communities and, consequently, fishing activities.     

Synergistic analysis of SeaWiFS chlorophyll concentration and NOAA-AVHRR SST features for exploring marine living resources

Near-synchronous Sea-viewing Wide Field-of-View Sensor (SeaWiFS) derived chlorophyll concentration and National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) derived sea surface temperature (SST) images were used to understand patterns, persistence and inter-relationship between ocean colour and thermal features. Different types of oceanic features were observed on chlorophyll concentration and SST images. An inverse relationship between chlorophyll concentration and SST features was observed. The features observed in the chlorophyll concentration images were well defined and appeared to contained more information than those on the SST images. The frontal zone positions on the chlorophyll concentration images coincided with temperature boundaries at some locations. This coincidence indicates that the physical and bio-chemical processes are closely coupled at these locations. High fish catch points were found in the vicinity of these features. A synergistic analysis of chlorophyll concentration and SST may increase our understanding of the inter-relationship between environmental variables for locating potential fishing grounds.     

Climate-driven latitudinal shift in fishing ground of jumbo flying squid (Dosidicus gigas) in the Southeast Pacific Ocean off Peru

The jumbo flying squid Dosidicus gigas is a pelagic squid species extensively distributed in the Eastern Pacific Ocean with climate-related geographical variability. An analysis was carried out to evaluate impacts of climatic and oceanographic variability on spatial distribution of D. gigas in the Southeast Pacific Ocean off Peru. Logbook data of the 2006–2013 Chinese squid-jigging fishery were used to determine latitudinal gravity centres (LATG) of fishing ground of D. gigas in relation to sea surface temperature (SST), chlorophyll-a (chl-a) concentration and sea surface height (SSH), coupled with the SST anomaly (SSTA) in the Niño 1 + 2 region. Results indicated that the SSTA in the Niño 1 + 2 region played crucial influences on SST, chl-a and SSH on the fishing ground of D. gigas. The LATG of D. gigas exhibited seasonal and interannual variability with closely associations with SST, chl-a, and SSH. Significantly positive relationships were found between monthly LATG and the average latitude of the most favourable contour lines of SST, chl-a, and SSH for D. gigas, with time lags at 0, 7, and 0 month, respectively. The spatial pattern of LATG largely responded to climate-induced oceanographic variability on the squid fishing ground: the Niño 1 + 2 SSTA became warm, the most favourable SST and SSH contour lines for D. gigas would move southward, resulting in a southward movement of the LATG; however, the Niño 1 + 2 SSTA shifted into cold episodes, the most favourable SST and SSH contour lines for D. gigas would shift northward, leading to a northward shift of the LATG. Our findings suggested that the SSTA in the Niño 1 + 2 region coupled with the most favourable contour lines of SST and SSH were the major drivers regulating the latitudinal movement of fishing ground of D. gigas in the Southeast Pacific Ocean off Peruvian waters.     

Synergistic application of oceanographic variables from multi-satellite sensors for forecasting potential fishing zones: methodology and validation results

This study uses synergistic application of satellite-derived chlorophyll concentration (CC), sea surface temperature (SST) and sea surface wind (SSW) for forecasting potential fishing zones (PFZs). PFZs are validated in near-real time through fishing operations and detailed statistical analysis of fishing operation data. CC and SST images were derived from Indian Remote Sensing Satellite-Ocean Colour Monitor (IRS-OCM) and NOAA-AVHRR, respectively, to delineate the oceanographic features exhibiting different oceanic processes. QuikSCAT/SeaWinds derived sea surface wind vectors were used to understand, quantify and demonstrate the variability of wind-induced water mass flow as well as their impacts on features/oceanographic process. Oceanographic features such as eddies, rings and fronts were found to be shifted according to the speed and direction of the wind. An algorithm was developed to compute water mass transport and feature shift. An improved methodology was developed and demonstrated using these prime variables, which are responsible for fishery resources distribution. PFZ forecasts were generated and validated through near-real-time fishing operations. The fishing operations data were taken from the logbooks of fishing vessels for detailed statistical analysis. On average, 80% of observations were recorded with more yield than monthly mean catch in the respective areas. A paired t-test showed statistically significant results.     

Fishing ground prediction using a knowledge-based expert system geographical information system model in the South and Central Sulawesi coastal waters of Indonesia

A knowledge-based expert system model working on the basis of a geographical information system (GIS) was applied to predict fishing ground spots in the coastal waters of South and Central Sulawesi. The model is designed by the integration of multisource data to answer ‘what?’, ‘where?’, and ‘why?’ questions of the fishing ground location. Despite the fact that GIS is a powerful tool for dealing with the first two questions, GIS is inferior for answering the ‘why?’ question in geo-studies. One of the possible ways of overcoming the inferiority of GIS for answering the ‘why?’ question of geo-studies is by integrating an expert system in a GIS to form a knowledge-based expert system GIS model. In this study, we used a series of sea surface temperature (SST) satellite data, sea surface chlorophyll-a (SSC) and turbidity derived from MODIS Aqua in the period 2003–2005 as input data, to understand the temporal and seasonal variability of the marine environment of the study area, and identified the oceanographic phenomena, i.e. upwelling, front or eddy. A spatial configuration map of the predicted fishing ground spots was then developed and integrated using a knowledge-based expert system GIS model generated by the Erdas Macro Language (EML) of Erdas Imagine 9.0 software. To verify this result, a series of in situ fishing ground spot data of the study area were collected for similar periods, and they were then analysed using a simple statistical method. The result shows that the predicted fishing ground spots generated by the knowledge-based expert system GIS model corresponded well with in situ data with a high accuracy level of 85%. This result has demonstrated that the knowledge-based expert system GIS model can be applied to predict, localize and determine fishing ground spots in which their accuracy level will be determined by the completeness of spatial knowledge of the domain expertise and the sophistication level of the programming utilities being used.     

The influence of mesoscale eddies on a commercial fishery in the coastal waters of the Andaman and Nicobar Islands,India

Mesoscale eddies enhance the productivity in a stratified coastal environment by upwelling. The seas around the Andaman and Nicobar Islands have been found to have frequent mesoscale eddy activity. Commercial fishing grounds coincide with upwelling areas associated with cyclonic and anticyclonic eddies and also with areas between two adjacent eddies. There are different eddy zones supporting different types of fishing gears and fish. The current study aims at identifying the different zones of mesoscale eddies in the Andaman Sea and compares the productivity and fishing activity in each of them. Data collected from 454 commercial fishing trips in the Andaman Sea along with maps of sea level anomaly and Moderate Resolution Imaging Spectroradiometer (MODIS) global level 3 mapped thermal infrared (IR) daytime sea surface temperature (SST) from the Aqua and Terra satellites were used for the study. Known upwelling areas such as the periphery of anticyclonic and the core of cyclonic eddies showed higher catches in longlines, ring seines among the fishing gears, and among all the fish species groups. Downwelling areas such as the periphery of cyclonic and the core of anticyclonic eddies showed lower catches with ring seines and the fish species groups. Areas in between adjacent eddies were explored in this study and the fish captures in such areas were found to be different with types of fishing and the target fish group. The study shows results that link eddy activity with the performance of a fishery.     

Space–time behaviour of the Angola–Benguela Frontal Zone during the Benguela Niño of April 1999

The hydrographic conditions in the south-east Atlantic were investigated during the cruise of R/V Poseidon in April 1999. The area of investigation covers the two major eastern boundary currents of the Southern Atlantic and its convergence in the Angola–Benguela Frontal Zone (ABFZ). Hydrographic measurements have been carried out in combination with current measurements and are supplemented with remote sensing data of sea surface temperature (SST) and wind stress.

The Angola Current transported in its surface part less saline water from the great rivers in the north towards the ABFZ. At the same time, south of the front, strong coastal upwelling in the Benguela was observed. At the beginning of April 1999 the ABFZ was found at an unusual southern position. The rapid dynamic response of the ABFZ to wind forcing is discussed on the basis of satellite SST images combined with hydrographic measurements.     

Thermal fronts of the southern South China Sea from satellite and in situ data

The major goal of this study was to find match-ups between thermal fronts mapped from satellite sea surface temperature (SST) imagery and from in situ data in the southern South China Sea (SSCS), using 11 ship surveys conducted by the South China Sea Institute of Oceanology (SCSIO) between 1987 and 1999. Fronts were automatically detected by the Cayula–Cornillon multi-image edge detection algorithm (CCA) applied to satellite-derived maps of the Advanced Very High Resolution Radiometer (AVHRR) SST obtained from the Pathfinder project (8364 twice-daily global fields with 9 km resolution between 1985 and 1996). Twice-daily near-instant frontal maps were composited without any averaging or smoothing to produce individual monthly frontal maps covering the period from January 1985 through December 1996 (144 maps in total). Although the SSCS is a tropical sea with little SST difference between water masses, the CCA turned out to be an effective tool for front mapping in the SSCS. Out of the 11 ship surveys analysed in this study, four surveys produced satisfactory match-ups. The percentage of match-ups is considered reasonably high given that (1) ship surveys were not optimized to cross fronts, therefore most in situ sections missed fronts; (2) satellite measurements of SST with AVHRR are hampered by cloudiness, therefore satellite-derived frontal maps might miss some fronts masked by persistent cloudiness. Fronts are more distinct in winter, when cross-frontal SST gradients are enhanced. From oceanographic vertical sections and horizontal maps, fronts are much sharper in the subsurface layer (represented here by 50 m level). Nonetheless, the CCA successfully detected SST fronts with a cross-frontal step as small as 1°C.     

Comparison between satellite and ship measurements of sea surface temperature in the north-east Atlantic Ocean

Abstract

A comparison is made between in situ measurements of sea surface temperature (SST) in the north-east Atlantic Ocean, obtained during Cruise 145 of RRS Discovery, and SSTs derived from several overpasses of the Advanced Very High Resolution Radiometer on the NOAA-7 satellite during the same period in March 1984. The objective of the analysis was to test the ability of the satellite to map the detailed features of SST structure and to examine the performance of atmospheric correction and temperature calibration procedures in this context. Gross comparison between all the cloud-free ship and satellite data confirms agreement normally within 1 degC. More detailed comparison of SST structure along the cruise tracks shows that the satellite data are able to identify features with a resolution of 0.3°C.     

Sea surface temperature GOES-8 estimation approach for the Brazilian coast

This work presents a quite consistent procedure for estimation of sea surface temperature (SST) using data from the new generation of the Geostationary Operational Environmental Satellite (GOES). The SST methodology is based on the classical split-window equation. The regional split-window coefficients (A ₀, A ₁, A ₂ and A ₃) are estimated by an algorithm regression taking as dependent variable three datasets, i.e. the SST derived from National Oceanic and Atmospheric Administration (NOAA)-14 polar-orbiting satellite and from buoys of Pilot Research Moored Array in Tropical Atlantic (PIRATA) and National Programme of Buoys (PNBOIA). This work shows that the main advantage of the GOES-8 SST algorithm, in comparison with the multi-channel sea surface temperature (MCSST) procedure using Advanced Very High Resolution Radiometer (AVHRR) data, is the high frequency sampling imagery (each half-hour) which permits a daily image with much less quantity of cloud contamination. The algorithm results using AVHRR/NOAA-14 as input dataset for the regression show that the accuracy of the GOES-8 SST algorithm is better than 1.0°C for all Brazilian coast. For regional estimation, the accuracy has been improved to around 0.5°C. Also, the accuracy of GOES-8 SST is better than 0.7°C using in situ SST collected from moored and drifting buoys.