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.     

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 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.     

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.     

Validation of coastal sea and lake surface temperature measurements derived from NOAA/AVHRR data

An interactive validation monitoring system is being used at the NOAA/NESDIS to validate the sea surface temperature (SST) derived from the NOAA-12 and NOAA-14 polar orbiting satellite AVHRR sensors for the NOAA CoastWatch program. In 1997, we validated the SST in coastal regions of the Gulf of Mexico, Southeast US and Northeast US and the lake surface temperatures in the Great Lakes every other month. The in situ     

Satellite and ground-based pasture production assessment in Niger: 1986-1988

Abstract

The standing crop of herbaceous biomass produced during the 2-4?month summer rainy season by the annual grasses in the Sahel zone provides an indication of resource availability for livestock for the following 9-month dry season. Combined use of NOAA advanced very high resolution radiometer (AVHRR) local area coverage (LAC) satellite data and biomass data, obtained through vegetation sampling of 25-100 km₂ areas, allowed the development of a method for biomass assessment in Niger. Vegetation sampling involved both visual estimates and clipped plots (double sampling). The relationship between time-integrated normalized difference vegetation index (NDVI) statistics derived from NOAA AVHRR LAC data (dependent variable) and total herbaceous biomass (independent variable) was obtained through regression analysis. An inverse prediction was used to estimate biomass from the satellite data. Biomass maps and statistics of the grasslands were produced for the end of each rainy season: 1986, 1987 and 1988. This information is being used for planning purposes by the pastoral resource managers of the Government of Niger.     

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.     

Determination of land surface spectral reflectances using Meteosat and NOAAA/AVHRR Shortwave Channel Data

Abstract

A method to derive surface spectral reflectances from currently available Meteosat geostationary and NOAA/AVHRR polar orbiting satellite data is described. Broadband reflectance was derived from Meteosat measurements while NOAA/AVHRR vegetation index provided a spectral weighting which enabled the spectral reflectances on either side of 0-7 μm to be estimated. The method takes into account satellite calibrations, viewing geometry, and correction of some atmospheric effects. Conversion from narrow-band to broadband reflectances is discussed. The method was applied to a month of data to obtain the surface spectral reflectances of Africa which are compared with some data sets used by climate modellers, in order to assess them and to monitor their seasonal and interannual changes on a global scale.     

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.     

Combined remote-sensing,model, and in situ measurements of sea surface temperature as an aid to recreational navigation: crossing the Gulf Stream

Combined in situ, model, and satellite remote-sensing observations are used to determine the location of the Gulf Stream as an aid to safe navigation for small recreational vessels.

A field study was executed from Hamilton, Bermuda, to Virginia Beach, USA, over a period of 5 days, from 30 June 2010 to 4 July 2010 to test the feasibility of using remote-sensing products as an aid to cross the Gulf Stream from the point of view of a small, slow-moving (?6 knots, 3 m s^?1) sailboat. The in situ data collected were compared to NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) remote-sensing data, to the Global High Resolution Sea Surface Temperature (GHRSST) microwave and infrared blended data set, to the National Oceanic and Atmospheric Administration Real-Time Ocean Forecast System (NOAARTOFS) ocean model, and to selected NOAA buoy and ship measurements.

A spatio-temporal analysis was performed by comparing the in situ measurements with observations retrieved at the same time and location in each of the data sets. The least error (correlation coefficient r?=?0.94) was obtained using MODIS data, and the largest error (r?=?0.78) was obtained using the RTOFS model data. Overall, most observations agree with the general spatio-temporal trend of the in situ data, with 95% of the errors within ±1°C and 98% of the errors within ±2°C.

The study shows that MODIS data are particularly suited to identification of the location of the Gulf Stream, which can be used by small vessels to optimize the crossing route and to minimize the risks associated with the passage.     

Determination of land surface temperature and its lapse rate in the Satluj River basin using NOAA data

Temperature lapse rate (TLR), an essential parameter for snowmelt runoff analysis, was determined for the Satluj River basin in the Western Himalayas. National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) data sets were used to determine the land surface temperature (LST) of the region using the split‐window algorithm proposed by Coll and Caselles (Journal of Geophysical Research, 1997, 102, pp. 16697–16713). The LST was correlated with the elevation values obtained from a US Geological Survey digital elevation model (USGS‐DEM) of the same area and the trend showed an inverse relationship between LST and elevation. The TLRs for the study area on 2 February, 1 March, 26 March, 16 October, 1 November and 20 November 2004 were in the range 0.6–0.74°C/100 m. The results obtained were compared with lapse rates determined using Moderate Resolution Imaging Spectroradiometer (MODIS) LST maps. TLR determination in the past was based on air temperature data available from meteorological stations that are sparsely located in rugged terrain such as the Himalayas. As these measurements were point data and had been measured manually, they may have led to erroneous results. Satellite data, however, provide continuous and potentially unbiased recording provided an accurate radiometric calibration and atmospheric correction can be achieved. A previous TLR calculation using air temperature from meteorological stations for the western Himalayan region was found to be 0.65°C/100 m. Air temperature and LST from NOAA‐AVHRR and MODIS‐Terra data were found to be in good agreement. This type of study will be useful for snowmelt runoff modelling studies for the Himalayan region.     

Provincial nature of chlorophyll and sea surface temperature observed by satellite

Monthly composite SeaWiFS derived chlorophyll, National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) derived sea surface temperature (SST) and QuikScat derived wind data of 2003–2005 (January–December) were analysed to study the provincial nature of chlorophyll‐a (chl‐a), SST and wind speed in the Arabian sea and Bay of Bengal. The study was confined to five provinces, three in the Arabian Sea and two in the Bay of Bengal. Results indicate provincial variability in the SST‐chl‐a relation. It suggests that the correlation between chlorophyll and SST is not always negative. A negative correlation was observed in provinces 1, 2 and 3 for all the seasons, whereas, except for the month of January–February, it was positively correlated for province 4. Analysis shows the provincial specific nature of chlorophyll variability to physical forcing and suggests that treatment of such a problem should not be undertaken on the basin scale.     

NOAA operational sounding products for advanced TOVS

The National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite Data and Information Service (NESDIS) operates a fleet of civilian, polar‐orbiting, environmental satellites that provide users and researchers with a continuous suite of atmospheric and surface products on a global scale. The first advanced TIROS operational vertical sounder (ATOVS) radiometer configuration, onboard NOAA‐15, was successfully launched into an early evening orbit on 13 May 1998. The ATOVS featured the new 13 channel advanced microwave sounding unit (AMSU) module A1, the 2 channel AMSU‐A2 and 5 channel AMSU‐B radiometers, which replaced the MSU and SSU, along with a similar HIRS and AVHRR instrument payload (Goodrun G., Kidwell, K.B. and Winston, W., 2000, NOAA‐KLM users guide: September 2000 revision, Technical Document, National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service, National Climatic Data Center) that had been operational since 1979. The ATOVS onboard NOAA‐16 was successfully launched into an afternoon orbit on 21 September 2000, followed by NOAA‐17 into a late evening orbit on 24 June 2002, creating the first ever three‐satellite constellation of operational polar satellites (ATOVS). The following report summarizes the online and offline scientific processing systems, respectively, for deriving the NESDIS operational ATOVS sounding products and presents a series of results for the unique three‐operational‐satellite configuration of NOAA‐15, 16 and 17. Results focus on the value of the derived products in the analyses of global and regional scale weather, including direct comparisons against collocated numerical weather prediction (NWP) forecast and radiosonde data. The report is prefaced by a brief history of satellite weather products and concludes with future plans to meet expanding user requirements.     

NOAA polar orbiting sensor systems Today and tomorrow

Abstract

For almost a quarter of a century, imagery and sounding data have been directly broadcast to users worldwide from polar orbiting satellites operated by the U.S. National Oceanic and Atmospheric Administration (NOAA). For more than a decade, almost the same payloads and data transmissions have been utilized. However, in the decade of the 1990s, several sensor improvements are planned or projected. This paper outlines payloads planned for NOAA Series spacecraft through the present century and the resulting changes in direct broadcast services.     

Sea and lake surface temperature retrieval from Landsat thermal data in Northern Germany

Landsat thermal data are employed to derive lake and sea surface temperatures. The limitations of this approach are obvious, since the calculation of surface temperatures based solely on image data requires at least two thermal bands to compensate the atmospheric influence which is mainly caused by water vapour absorption. However, the 1 km spatial resolution of currently available multi‐band thermal satellite sensors (NOAA‐AVHRR, MODIS) is often not appropriate for lake and coastal zone applications. Therefore, it is worthwhile investigating the accuracy which can be obtained with single‐band thermal data using radiosonde information of the atmospheric water vapour column from meteorological stations in the study area. In addition, standard atmospheres from the MODTRAN code were considered that are based on seasonal climatologic values of water vapour, e.g. mid‐latitude summer, mid‐latitude winter, etc.

The study area of this investigation comprises various lakes and coastal zones of the Baltic Sea in NE Germany. Landsat‐7 ETM+ imagery of nine acquisition dates was selected covering the time span from February to November 2000. Results of derived lake and sea surface temperatures were compared with in situ measurements and with an empirical model of the Deutscher Wetterdienst (Germany's National Meteorological Service, DWD). RMS deviations of 1.4 K were obtained for the satellite‐derived lake surface temperatures with respect to in situ measurements and 2.2 K with respect to the empirical DWD model. RMS deviations of 1.6 K were obtained with respect to in situ bulk temperatures in coastal zones of the Baltic Sea. This level of agreement can be considered as satisfactory given the principal constraints of this approach. A better accuracy can only be obtained with high spatial resolution (<100 m) multi‐band thermal instruments delivering imagery on an operational basis.     

A new method of data transformation for satellite images: I. Methodology and transformation equations for TM images

These two papers deal with a new method of data transformation. By analysing grey level curves (broken lines) of various ground features in image bands of different satellites, we have found that, inherent in 3‐ or 4‐band satellite images (SPOT, IKONOS, Quick Bird, OrbView, FORMOSAT and MSS) there are three basic remote‐sensing characteristics as follows: (1) the general radiance level L; (2) the visible–infrared radiation balance B; and (3) the band radiance variation vector (direction and speed) V. However, inherent in 5‐ or 7‐band satellite images (NOAA, TM), besides the above three, there is an extra basic remote‐sensing characteristic, i.e. the thermal radiation intensity I. This is denoted by thermal bands, i.e. the TM band 6 or NOAA (AVHRR) bands 4 and 5, which are relatively independent and can be used directly, and hence are unnecessary for information extraction or data transformation. Therefore, the data transformation only lies in extracting the L, B and V from original satellite images. Furthermore, we have also found that there are three basic ground‐cover elements on the Earth's surface: i.e. the bare land (in a broad sense), the vegetation and the water body, which, in different proportions, constitute all ground cover. Moreover, there are three basic (primitive) colours on colour image (including colour composite of satellite images): i.e. red, green and blue, which generate all colours on the colour image. Further research has revealed that the three basic remote‐sensing characteristics, the three basic ground‐cover elements and the three basic colours on the composite can conceptually constitute a three‐to‐three corresponding regular triangle scheme. Perhaps a good method of data transformation should make the scheme realistic, i.e. make the three ‘threes’ all correspond to each other. The research presented here has completed this task by regression calculations and selection of specific variables. First, the methodology and transformation equations for TM images are discussed. The transformed L, B and V images have relatively independent and equally distributed information as well as clear and definite physical, mathematical and geographical significance. They can be used effectively for generating high‐quality colour composites, on which the red, green, blue, yellow, pink, cyan and other colours of various kinds are all generated and all pure, saturated, equilibrated, meaning‐definite and close to the colours of ground features in nature. As a result, interpretations and discriminations of ground features can be easier and conducted not only by experience, but also by logic. The L, B and V images can also be used effectively for classification and digital analysis of ground features. With regard to the transformation equations for SPOT, NOAA, IKONOS, Quick Bird, OrbView, FORMOSAT and MSS images and the method application will be dealt with in the second paper.     

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.     

Examining teacher growth in professional learning groups for in‐service teachers of mathematics

Abstract

Teachers may face important challenges when encouraged to improve their mathematics teaching. Their personal beliefs, knowledge, confidence and personal intentions towards growth and change are all complex factors which may influence teachers’ capacity, and their decisions about personal change in their teaching. In this study, intermediate teachers and the conversations that took place during their monthly Professional Learning Group meetings over a one‐year period were examined in order to better understand issues teachers face in their growth and development as teachers of mathematics. We critically examine the notion and meaning of success to different stakeholders.