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We describe an approach to partition a vertical profile of chlorophyll-a concentration into contributions from two communities of phytoplankton: one (community 1) that resides principally in the turbulent mixed-layer of the upper ocean and is observable through satellite visible radiometry; the other (community 2) residing below the mixed-layer, in a stably stratified environment, hidden from the eyes of the satellite. The approach is tuned to a time-series of profiles from a Biogeochemical-Argo float in the northern Red Sea, selected as its location transitions from a deep mixed layer in winter (characteristic of vertically well-mixed systems) to a shallow mixed layer in the summer with a deep chlorophyll-a maximum (characteristic of vertically stratified systems). The approach is extended to reproduce profiles of particle backscattering, by deriving the chlorophyll-specific backscattering coefficients of the two communities and a background coefficient assumed to be dominated by non-algal particles in the region. Analysis of the float data reveals contrasting phenology of the two communities, with community 1 blooming in winter and 2 in summer, community 1 negatively correlated with epipelagic stratification, and 2 positively correlated. We observe a dynamic chlorophyll-specific backscattering coefficient for community 1 (stable for community 2), positively correlated with light in the mixed-layer, suggesting seasonal changes in photoacclimation and/or taxonomic composition within community 1. The approach has the potential for monitoring vertical changes in epipelagic biogeography and for combining satellite and ocean robotic data to yield a three-dimensional view of phytoplankton distribution.

Anthropogenically-induced global warming is expected to decrease primary productivity in the subtropical oceans by strengthening stratification of the water column and reducing the flux of nutrients from deep-waters to the sunlit surface layers. Identification of such changes is hindered by a paucity of long-term, spatially-resolved, biological time-series data at the basin scale. This paper exploits Atlantic Meridional Transect (AMT) data on physical and biogeochemical properties (1995–2014) in synergy with a wide range of remote-sensing (RS) observations from ocean colour, Sea Surface Temperature (SST), Sea Surface Salinity (SSS) and altimetry (surface currents), combined with different modelling approaches (both empirical and a coupled 1-D Ecosystem model), to produce a synthesis of the seasonal functioning of the North and South Atlantic Sub-Tropical Gyres (STGs), and assess their response to longer-term changes in climate. We explore definitive characteristics of the STGs using data of physical (SST, SSS and peripheral current systems) and biogeochemical variables (chlorophyll and nitrate), with inherent criteria (permanent thermal stratification and oligotrophy), and define the gyre boundary from a sharp gradient in these physical and biogeochemical properties. From RS data, the seasonal cycles for the period 1998–2012 show significant relationships between physical properties (SST and PAR) and gyre area. In contrast to expectations, the surface layer chlorophyll concentration from RS data (CHL) shows an upward trend for the mean values in both subtropical gyres. Furthermore, trends in physical properties (SST, PAR, gyre area) differ between the North and South STGs, suggesting the processes responsible for an upward trend in CHL may vary between gyres. There are significant anomalies in CHL and SST that are associated with El Nino events. These conclusions are drawn cautiously considering the short length of the time-series (1998–2012), emphasising the need to sustain spatially-extensive surveys such as AMT and integrate such observations with models, autonomous observations and RS data, to help address fundamental questions about how our planet is responding to climate change. A small number of dedicated AMT cruises in the keystone months of January and July would complement our understanding of seasonal cycles in the STGs.

Surface pigment data from a transect along the eastern boundary of the Atlantic Ocean was analysed using CHEMTAX to yield more detailed information on the composition of phytoplankton communities. Total chlorophyll a concentrations varied from 0.03 mg m?3 in a northern oligotrophic region to 30.3 mg m?3 in the Benguela ecosystem. Diatoms dominated the Benguela, while both diatoms and haptophytes were the major groups in the Canary ecosystem and the temperate NE Atlantic. Prochlorococcus was the most prominent group in the southern oligotrophic region (15.5°S-15°N) although haptophytes were also a significant component of the population. In contrast, haptophytes dominated the northern oligotrophic region (21°-40°N). Photo-pigment indices indicated that chlorophyll b was mainly associated with prasinophytes and chlorophyll c with diatoms. Elevated photosynthetic carotenoids were due to increased proportions of haptophytes, but also linked with diatoms and dinoflagellates. Photoprotective carotenoids were more prominently associated with Prochlorococcus and to a lesser extent to Synechococcus.

Error-quantified, synoptic-scale relationships between chlorophyll-a (Chl-a) and phytoplankton pigment groups at the sea surface are presented. A total of ten pigment groups were considered to represent three Phytoplankton Size Classes (PSCs, micro-, nano- and picoplankton) and seven Phytoplankton Functional Types (PFTs, i.e. diatoms, dinoflagellates, green algae, prymnesiophytes (haptophytes), pico-eukaryotes, prokaryotes and Prochlorococcus sp.). The observed relationships between Chl-a and PSCs/PFTs were well-defined at the global scale to show that a community shift of phytoplankton at the basin and global scales is reflected by a change in Chl-a of the total community. Thus, Chl-a of the total community can be used as an index of not only phytoplankton biomass but also of their community structure. Within these relationships, we also found non-monotonic variations with Chl-a for certain pico-sized phytoplankton (pico-eukaryotes, Prokaryotes and Prochlorococcus sp.) and nano-sized phytoplankton (Green algae, prymnesiophytes). The relationships were quantified with a least-square fitting approach in order to enable an estimation of the PFTs from Chl-a where PFTs are expressed as a percentage of the total Chl-a. The estimated uncertainty of the relationships depends on both PFT and Chl-a concentration. Maximum uncertainty of 31.8% was found for diatoms at Chl-a = 0.49 mg m−3. However, the mean uncertainty of the relationships over all PFTs was 5.9% over the entire Chl-a range observed in situ (0.02 < Chl-a < 4.26 mg m−3). The relationships were applied to SeaWiFS satellite Chl-a data from 1998 to 2009 to show the global climatological fields of the surface distribution of PFTs. Results show that microplankton are present in the mid and high latitudes, constituting only ~10.9% of the entire phytoplankton community in the mean field for 1998–2009, in which diatoms explain ~7.5%. Nanoplankton are ubiquitous throughout the global surface oceans, except the subtropical gyres, constituting ~45.5%, of which prymnesiophytes (haptophytes) are the major group explaining ~31.7% while green algae contribute ~13.9%. Picoplankton are dominant in the subtropical gyres, but constitute ~43.6% globally, of which prokaryotes are the major group explaining ~26.5% (Prochlorococcus sp. explaining 22.8%), while pico-eukaryotes explain ~17.2% and are relatively abundant in the South Pacific. These results may be of use to evaluate global marine ecosystem models.

The phytoplankton pigment composition (chlorophylls and carotenoids) from 17 Atlantic Meridional Transect (AMT) cruises over the period 1995–2005 was analysed to determine the distributions of pigments and plankton in the Atlantic Ocean between 50°N and 50°S. Data were quality assured by statistical methods, including regression of total chlorophyll a (TChla) versus accessory pigments (AP) and comparison of the AMT-TChla with contemporary SeaWiFS-TChla (cruises AMT-05 to -17). Comparisons of province-mean TChla (±SD) for in situ and satellite data showed good agreement for each cruise. ‘Taxa-specific’ pigments were used to define phytoplankton functional types (PFTs) for each of the biogeochemical provinces along the AMT. Pigment ratios (e.g. TChla/AP) were analysed for each cruise and for each province as indices (characteristic properties) of particular PFTs. Mostly robust positive correlations were observed between TChla and pigment ratios for different PFTs, for some provinces and most cruises. These were consistent with previous observations. Generally there were no significant trends of mean TChla or pigment ratios within provinces over the period 1995–2005, although the previously reported perturbation due to the 1997–1998 ENSO was evident.

Based on the view of ecological pattern being steady state, rather than an equilibrium phenomenon, we assert that, if real, ecological biomes and provinces in the ocean should be detectable in surface fields obtained from satellite data as coherent, co-varying spatial regions with a high degree of permanence. Likewise, hierarchy is an important property of ecological systems that should be exhibited by such patterns if they represent real ecological structure. In this paper, we apply a combination of multivariate statistics and classification techniques to a time series of satellite-derived, surface-ocean chlorophyll data from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), (a) to provide an objective characterisation and classification of ecological pattern in the ocean and (b) to investigate the characteristic system properties (persistence, hierarchy) of the broad-scale patterns observed to test whether they behave as autonomous ecological systems. Comparison of this classification with Longhurst [Longhurst, A. (1998), Ecological Geography of the Sea. San Diego: Academic Press, 398 pp.] suggests the need for equatorial forcing processes to be taken into account to explain observed ecological pattern at the biome level.

We have developed a model linking phytoplankton absorption to phytoplankton size classes (PSCs) that uses a single variable, the optical absorption by phytoplankton at 443 nm, a ph (443), which can be derived from the inversion of ocean colour data. The model is based on the observation that the absolute value of a ph (443) co-varies with the spectral slope of phytoplankton absorption in the range of 443–510 nm, which is also a characteristic of phytoplankton size classes. The model when used for analysis of SeaWiFS global data, showed that picoplankton dominated ~ 79.1% of surface waters, nanoplankton ~ 18.5% and microplankton the remainder (2.3%). The N. and S. Atlantic and the N. and S. Pacific Oceans showed seasonal cycles with both micro and nanoplankton increasing in spring and summer in each hemisphere, while picoplankton, dominant in the oligotrophic gyres, decreased in the summer. The PSCs derived from SeaWiFS data were verified by comparing contemporary 8-day composites with PSCs derived from in situ pigment data from quasiconcurrent Atlantic Meridional Transect cruises.

We review the concept of phytoplankton functional types (PFTs) in marine ecosystems as a means of advancing bio-mechanistic models that can be coupled to the global carbon cycle and the Earth's climate system. Conventional classification of phytoplankton by size may seem arbitrary, but there appears clear links between size and environmental characteristics (availability of essential nutrients and light) that regulate photosynthesis, phytoplankton selection and succession. Taking a minimalist approach, small phytoplankton (picoplankton) survive in permanently stratified systems with low nutrients, high surface light and low light in deep clines, whereas large phytoplankton (microplankton) thrive in high nutrient, turbulent, high light, near surface systems. Nutrient-light environmental conditions are characteristic properties of globally, latitudinal-dispersed biogeochemical provinces. These contrasting nutrient-light regimes define the extreme ends of the bio-energetic scale of photosynthesis and set the end points of the primary range of phytoplankton functional processes. To determine PFTs from remotely sensed ocean colour data, there must be a specific bio-optical trait (BOT) that can be associated with the phytoplankton species or taxa. We investigate the connection of the bio-energetic scale to phytoplankton types and their BOTs, which is the first, but crucial step for classifying PFTs on the basis of functional processes, from which refinements and further partitioning can be developed.

Photosynthetic electron transport directly generates the energy required for carbon fixation and thus underlies the aerobic metabolism of aquatic systems. We determined photosynthetic electron turnover rates, ETRs, from ca. 100 FRR fluorescence water-column profiles throughout the subtropical and tropical Atlantic during six Atlantic Meridional Transect cruises (AMT 6, May–June 1998, to AMT 11, September–October 2000). Each FRR fluorescence profile yielded a water-column ETR-light response from which the maximum electron turnover rate ( ETR RCII max ) , effective absorption (σPSII) and light saturation parameter (Ek) specific to the concentration of photosystem II reaction centres (RCIIs) were calculated. ETR RCII max and Ek increased whilst σPSII decreased with mixed-layer depth and the daily integrated photosynthetically active photon flux when all provinces were considered together. These trends suggested that variability in maximum ETR can be partly attributed to changes in effective absorption. Independent bio-optical measurements taken during AMT 11 demonstrated that σPSII variability reflects taxonomic and physiological differences in the phytoplankton communities. ETR RCII max and Ek, but not σPSII, remained correlated with mixed-layer depth and daily integrated photosynthetically active photon flux when data from each oceanic province were considered separately, indicating a decoupling of electron turnover and carbon fixation rates within each province. Comparison of maximum ETRs with 14C-based measurements of Pmax further suggests that light absorption and C fixation are coupled to differing extents for the various oligotrophic Atlantic provinces. We explore the importance of quantifying RCII concentration for determination of ETRs and interpretation of ETR-C fixation coupling.

The successful exploitation of remotely sensed observations of water colour in the coastal zone requires atmospheric correction methods that can determine water reflectance from top-of-atmosphere radiometric measurements over waters containing significant non-phytoplanktonic particulate material. These so-called Case II waters often have significant water leaving radiance at near infra-red (NIR) wavelengths which invalidates conventional “dark pixel” atmospheric correction procedures, including those using the Siegel-type NIR iterative-correction scheme. A coupled ocean-atmosphere model is described that solves for water-leaving radiance and atmospheric path radiance over Case II turbid waters from measurements by the NASA ocean colour satellite sensor, SeaWiFS. The theoretical basis of this model is described, together with its implementation within the SeaWiFS data processing system, SeaDAS. The resulting products are validated using five test images of European waters, where the modified atmospheric correction leads to significant increases in normalised water leaving-radiances across the whole spectrum and to fewer negative water leaving radiances.

Case-based reasoning systems, in general, and instance-based reasoning systems, in particular, are used more and more in industrial applications nowadays. During the last few years, researchers have been working in the development of techniques to automate the reasoning stages identified in this methodology. This paper presents a method for automating the retrieval stage and indexation of instance-based reasoning systems. This method is based on a modification of a new type of topology preserving map that can be used for scale invariant classification. The scale invariant map is an implementation of the negative feedback network to form a topology-preserving mapping. Maximum/minimum likelihood learning is applied in this paper to the scale invariant map and its possibilities are explored. This method automates the organization of cases and the retrieval stage of case-based reasoning systems. The proposed methodology groups instances with similar structure, identifying clusters automatically in a data set ...

Estimating the primary productivity of phytoplankton as they are mixed through the surface layer is often hampered by methodological or conceptual constraints. Fast Repetition Rate Fluorometry (FRRF) allows some of these constraints to be overcome by providing measurements of the instantaneous, depth-dependent rates of primary productivity of phytoplankton in situ. Data acquired by FRR fluorescence is used in this paper to determine the parameters of the photosynthesis‐irradiance curve and the instantaneous photosynthetic rates for phytoplankton from the mixed layer during a cruise in the Celtic Sea in May 2000. FRR fluorescence-based estimates of the initial slope of the photosynthesis‐light curve (� B ) ranged from 7.5 in well-mixed conditions to 12.7 g C (mol photons) � 1 m 2 (g Chl a) � 1 under stratified conditions. FRR fluorescence-based estimates of the light saturation parameter, Ek, were strongly correlated with the logarithm of the surface PAR. FRR fluorescence-based estimates of the Chl a-specific, light saturated photosynthesis rate (Pm B ) ranged from 1.4 to 2.8 g C (g Chl a) � 1 h � 1 . The FRRF determined values of Pm B were consistent with those measured using radiocarbon techniques, however, there were systematic differences

Phytoplankton photosynthetic quantum efficiency (PQE), pigments, absorption characteristics, species composition (converted to phytoplankton carbon, Cph) and other variables were measured at an offshore site in the western English Channel throughout 2001, using an opportunistic weekly sampling schedule. The variation of chlorophyll-a (Chla) and other phytoplankton pigments followed the classical seasonal cycle, driven by incident light, patterns of stratification and nutrient availability. Phytoplankton and pigment concentrations were low in the winter, rising to a peak in the spring ‘bloom’, with episodic blooms throughout the summer, an autumn bloom and a decline to the winter minimum. Surface layer Chla and total pigment (Tpig) concentrations were highly correlated for the whole year, yet it was observed that the fraction of Chla in Tpig (Chla/Tpig) was not constant and had a distinct seasonal pattern, low in winter and higher in spring, summer and autumn blooms. Chlorophyll-a/Tpig was linearly correlated with recent ambient light fluxes and maximum PQE (PQEm) throughout most of the year, though more significantly within seasonal periods. Chlorophyll-a and Tpig were both linearly correlated to Cph and the Chla/Cph ratio was significantly correlated with both Chla/Tpig and PQEm. Also the optical absorption ratios, a674/a443 and a674/a490 were significantly correlated with PQE and Chla/Tpig, indicating probable optical signatures for these two parameters. The seasonal cycle of measurements of photosynthetic quantum efficiency provided a bench-mark against which all the photosynthetically-driven seasonal changes of biological properties can be understood, in terms of incident solar radiation and nutrient availability. We conclude that phytoplankton synthesize Chla preferentially to other pigments or carbon compounds in conditions beneficial to growth. The PQEm, the ratios of Chla/Tpig, Chla/Cph and a674/a443 are greater when plants are growing actively. In periods of nutrient sufficiency, PQEm, Chla/Tpig and a674/a443 are all linear functions of the mean total photon flux for the recent few days. Photosynthetically driven changes in Chla synthesis, cause observed changes of Chla/Tpig and Chla/Cph ratios.

An approach to hybrid artificial intelligence problem solving is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. In situations in which the rules that determine a system are unknown or fuzzy, the prediction of the parameter values that determine the characteristic behavior of the system can be a problematic task. In such a situation, it has been found that a hybrid artificial intelligence model can provide a more effective means of performing such predictions than either connectionist or symbolic techniques used separately. The hybrid forecasting system that has been developed consists of a case-based reasoning system integrated with a radial basis function artificial neural network. The results obtained from experiments in which the system operated in real time in the oceanographic environment, are presented.

Pigment patterns and associated absorption properties of phytoplankton were investigated in the euphotic zone along two meridional transects in the Atlantic Ocean, between the UK and the Falkland Islands, and between South Africa and the UK. Total chlorophyll a (TChla=MVChla+DVChla+chlorophyllide a) concentrations and the biomarker pigments for diatoms (fucoxanthin), nanoflagellates and cyanobacteria (zeaxanthin) appeared to have similar distribution patterns in the spring and in the autumn in the temperate NE Atlantic and the northern oligotrophic gyre. Divinyl chlorophyll a levels (prochlorophytes) were greater in spring at the deep chlorophyll maximum in the oligotrophic gyre, however. Marked seasonal differences were observed in the NW African upwelling region. TChla concentrations were twice as high in the upper mixed layer in the spring, with the community dominated by diatoms and prymnesiophytes (19?-hexanoyloxyfucoxanthin). A layered structure was prevalent in the autumn where cyanobacteria, diatoms and prymnesiophytes were located in the upper water column and diatoms and mixed nanoflagellates at the sub-surface maximum. In the South Atlantic, the Benguela upwelling ecosystem and the Brazil-Falklands Current Confluence Zone (BFCCZ) were the most productive regions with the TChla levels being twice as high in the Benguela. Diatoms dominated the Benguela system, while nanoflagellates were the most ubiquitous group in the BFCCZ. Pigment concentrations were greater along the eastern boundary of the southern oligotrophic gyre and distributed at shallower depths. Deep chlorophyll maxima were a feature of the western boundary oligotrophic waters, and cyanobacteria tended to dominate the upper water column along both transects with a mixed group of nanoflagellates at the chlorophyll maximum. Absorption coefficients were estimated from spectra reconstructed from pigment data. Although absorption was greater in the productive areas, the TChla-specific coefficients were higher in oligotrophic regions. In communities that were dominated by diatoms or nanoflagellates, pigment absorption was generally uniform with depth and attenuating irradiance, with TChla being the major absorbing pigment at 440 nm and photosynthetic carotenoids (PSC) at 490 nm. Absorption by chlorophyll c and photoprotective carotenoids (PPC) was much lower. Populations where cyanobacteria were prevalent were characterized by high PPC absorption, particularly at 490 nm, throughout most of the euphotic zone. The data suggested that the effect of pigments on the variability of phytoplankton absorption was due primarily to the variations in absorption by PPC.

Reduced sulfur gases and optical properties were measured in the upper ocean during an Atlantic Meridional Transect cruise of the RRS James Clark Ross from England to the Falkland Islands in 1998. Sea surface concentrations of carbonyl sulfide (COS) exhibited a pronounced diel variation at low latitudes but no diel cycle at mid and high latitudes possibly because of oceanic fronts and the longer hydrolysis time constant in cold water. The highest COS concentrations were observed in coastal and upwelling areas. CS2 concentrations varied less than those of COS, and the highest concentrations were found in the North African upwelling area with decreasing concentrations both northward and southward of this maximum. Dimethylsulfide (DMS) had the largest concentrations in the upper ocean, but methyl mercaptan (CH3SH) was an important reduced sulfur species in some coastal and upwelling areas. This may be associated with high bacterial growth rates. Colored dissolved organic matter (CDOM) fluorescence and absorbance also exhibit the highest values in coastal and upwelling areas and the lowest values in the southern subtropical gyre. The results suggest that carbon disulfide (CS2) outgassed from the oceans and oxidized in the atmosphere may represent a larger source of COS to the atmosphere than the direct flux of COS across the sea-air interface.

Estimates of gross primary production (GPP) based on fast repetition rate fluorometer (FRRF) measurements were compared with independent 14 C and O2 at three stations during a spring bloom in the North Atlantic. A photosynthesis versus irradiance (P-E) curve was constructed for each station from the observations of in situ photon efficiency of photosynthesis. This composite P-E curve was compared with P-E curves determined for discrete samples from 14 C assimilation. Estimates of a Chl and Pm Chl from the 14 C-uptake method were 1.5‐2.5-fold lower than those estimated from the FRRF data. Much of this discrepancy can be accounted for if 14 C assimilation approximates net phytoplankton photosynthesis with use of a photosynthetic quotient of 1.4 mol O2 (mol CO2) 21 . Photosynthetic oxygen consumption may have also contributed to the difference. In situ GPP was calculated from incident irradiance, light attenuation, light absorption by phytoplankton, and the light dependence of the in situ photon efficiency. This estimate of GPP was two times greater than net community photosynthesis determined from diel changes of in situ oxygen concentration. Thus, the in situ net O 2 and in vitro 14 C techniques yielded similar estimates of phytoplankton photosynthesis that were about twofold lower than the estimates of GPP provided by FRRF. Uncertainties in the FRRF technique associated with choosing an appropriate value of photosynthetic unit size and fitting a P-E curve to the in situ measurements are discussed. Despite these uncertainties, the FRRF results were consistent with the independent estimates of phytoplankton productivity.

An instance-based problem solving model is presented in which the aim is to forecast, in real time, the physical parameter values of a complex and dynamic environment: the ocean. The situations in which the rules that determine a system are unknown, the prediction of the parameter values that determine the characteristic behaviour of the system can be a problematic task. In such a situation it has been found that an instance-based reasoning system can provide a more effective means of performing such predictions than other connectionist or symbolic techniques. The instance-based reasoning system incorporates a radial basis function artificial neural network for the instance adaptation. The results obtained from experiments, in which the system operated in real time in the oceanographic environment, are presented.

Coincident pigment and underwater radiometric data were collected during a cruise along the 20°W meridian from 60°N to 37°N in the north-eastern Atlantic Ocean as part of the Natural Environment Research Council (NERC) thematic programme: plankton reactivity in the marine environment (PRIME). These data were used to simulate the retrieval of two bio-optical variables from remotelysensed measurements of ocean colour (for example by the NASA Sea-viewing wide field-of-view sensor, SeaWiFS), using two-band semi-empirical algorithms. The variables considered were the diffuse attenuation coefficient at 490 nm, ( K d (490), units: m −1 ) and the phytoplankton pigment concentration expressed as optically-weighted chlorophyll- a concentration [ C a , units: mg m −3 ]. There was good agreement between the measured and the retrieved bio-optical values. Algorithms based on the PRIME data were generated to compare the performance of local algorithms (algorithms which apply to a restricted area and/or season) with global algorithms (algorithms developed on data from a wide variety of water masses). The use of local algorithms improved the average accuracy, but not the precision, of the retrievals: errors were still ±36% ( K d ) and ±117% ( C a ) using local algorithms.

An objective methodology for identifying oceanic provinces in hydrographic data is presented, although, the technique is sufficiently general so as to be applicable to a variety of data sets. The sub- and near-surface temperature (T) and salinity (S) of the Atlantic Ocean were measured on two Atlantic Meridional Transect (AMT) cruises covering approximately 100° of latitude and 50° of longitude. The cruises covered the boreal autumn and austral spring (AMT-1) and the boreal spring and austral autumn (AMT-2) during 1995 and 1996, respectively. There are distinct patterns of change in T-S from 50°N to 50°S for both sub- and near-surface measurements, although this study concentrates primarily on the latter. Near-surface density (σt) encapsulates the variations in T-S. The position of localized extrema in the σt first spatial derivative locates the change in bulk T-S properties and, hence, the extent of a physical province. The province identification methodology is validated by comparing the results obtained using in situ density, a mixed layer depth space series constructed from expendable bathythermograph profiles, and climatological density. Additional validation of the methodology is achieved by intercomparing different in situ data sources between the two cruise periods. The comparisons show the near-surface measurements are indicative of the mixed layer and that the AMT-1 and AMT-2 cruises are representative of the corresponding climatological months. A simple scheme for investigating how far a province extends away from the cruise track uses the climatological data in concert with a T-S description of each province from the AMT along-track observations to produce a two-dimensional map of the geographical extent of each province. Although exceptions between the province extents and the basic circulation of the Atlantic Ocean occur, the majority of the provinces have the correct shape and extent, that is, their edges follow the flow fields associated with the currents that bound them and they extend over an appropriate area. The province identification methodology is sensitive and reliable enough to investigate temporal differences in oceanic provinces, which means it might be useful for parameterizing global budget calculations in numerical models.

The Atlantic Meridional Transect programme uses the twice-annual passage of the RRS James Clark Ross between the UK and the Falkland Islands, before and after the Antarctic research programme in the Austral Summer (see Aiken, J., & Bale, A. J. (2000). An introduction to the Atlantic Meridional Transect (AMT) Programme. Progress in Oceanography, this issue). This paper examines the scientific rationale for a spatially-extensive time and space series programme and reviews the relevant physical and biological oceanography of the Atlantic Ocean. The main scientific observations from the research programme are reported. These are set in the context of historical and contemporary observations pertinent to the principal objectives of the cruise, notably the satellite remotely sensed observations of ocean properties. The extent to which the programme goals have been realised by the research to date is assessed and discussed. New bio-optical signatures, which can be related to productivity parameters, have been derived. These can be used to interpret remotely sensed observations of ocean colour in terms of productivity and production processes such as the air/sea exchange of biogenic gases, which relate to the issues of climate change and the sustainability of marine ecosystems.

The use of CZCS-type band-ratio algorithms to estimate the diffuse attenuation coefficient, percentage light depths, and near-surface optically weighted phytoplankton pigment concentrations from remotely sensed ocean colour data was investigated on two cruises in the Arabian Sea and Gulf of Oman during autumn and winter 1994. The variations of upwelling radiance and downwelling irradiance with depth were measured along with phytoplankton pigment concentrations by HPLC. A spectroradiometer was used on the second cruise to investigate the feasibility of measuring water-leaving radiance from above the sea surface. Retrieval of the diffuse downwelling attenuation coefficient at 490 nm was accurate to within 22% of the actual value across both cruises. There was also a robust relationship between the diffuse attenuation coefficient and the 10, 1 and 0.1% light depths. Above-surface estimates of water-leaving radiance agreed with SeaWiFS-standard estimates to within 10% between 443 and 555 nm. The global 443 : 555 band-ratio algorithms of Aiken et al. [NASA Tech. Memo 104566, Vol. 29, SeaWiFS Technical Report Series, 34 pp] estimated near-surface chlorophyll-a and fluorometric pigment concentrations with mean absolute errors of less than 35% of the actual values (which were all less than 2.0 mg m-3). The performance of algorithms based on the 490 : 555 ratio was poorer. The estimates given by the algorithms were generally higher than the measured pigment concentrations and the variance of the accuracy of the estimates was high. There appears to be no significant change in the performance of the algorithms between cruises (approximately 2 1 2 months apart in time). There is no evidence that the Gulf of Oman should be treated as a separate bio-optical province to the Arabian Sea/Omani shelf area for the purpose of the retrieval of near-surface pigment concentrations from ocean colour observations.

Atmospheric and oceanic partial pressures of CO2 (pCO2) have been recorded automatically along two Atlantic meridional transects in 1995. The tropical Atlantic ocean (20°S–20°N) is generally a source of CO2 for the atmosphere, but in the region of the North Equatorial Countercurrent an undersaturation of CO2 has been observed. Undersaturations previously reported in the literature are explained by the decrease of salinity due to the high precipitations associated with the Intertropical Convergence Zone. In June 1995, strong CO2 undersaturations (ΔpCO2 = −70μatm) were observed near 8°N, which suggests, in addition of the salinity effect, an uptake of CO2 due to biological activity. This undersaturation, although weaker than in spring, also appeared at other periods of the year 1995.

We present a synthesis of physical, chemical and biological shipboard observations of a convergent front at 2°N, 140°W and its surrounding environment. The front was a component of a tropical instability wave generated by shear between westward-flowing equatorial waters to the south and warmer equatorial counter current water to the north. Surface waters on the cold side were undersaturated with oxygen, which suggests that the water had only been exposed at the sea surface for a period of a few weeks. Although the atmospheric exposure time was short, the effects of biological activity could be detected in enhanced concentrations of total (dissolved plus suspended particulate) organic carbon concentration, proving that TOC can be produced in the top centimeters of the changing environmental conditions. The front itself was dominated by the accumulation of a “patch” of buoyant diatoms Rhizosolenia castracanei concentrated in the top centimeters of the warm surface water north of the front, and elevated chlorophyll concentrations were observed from the air over a spatial scale of order 10–20 km northward from the front. The nitrogen budget and thorium data suggest that a significant fraction of the elevated POC, and virtually all of the PON, arrived in the patch waters as imported particles rather than in situ photosynthesis. Photosynthetic uptake of carbon appears to have occurred in patch waters, but without corresponding uptake of fixed nitrogen (an uncoupling of the usual Redfield stoichiometry). Solute chemistry of the patch appears to be controlled by turbulent mixing, which flushes out patch waters on a time scale of days

Rates of phytoplankton production and nitrogen assimilation were measured at various stations along a transect in the northwestern Indian Ocean, from near the equator, northwards into the upwelling system off the Arabian peninsula, during September–October 1986. The measurements were made using in situ incubation techniques with the simultaneous use of 14C and 15N isotopes. Samples were fractionated after the incubations into three size classes: 0.2–0.8μm, 0.8–5.0 μm, and >5.0μm for the 14C incubations; and 5μm for the 15N incubations. The assimilation of nitrate and ammonium was measured. These measurements were supported by a detailed description of the horizontal and vertical distributions of chlorophyll, temperature and underwater light field, by the deployment of a towed undulating oceanographic recorder. Rates of primary production ranged from approximately 0.5 g C m−2 day−1 at the equator, reducing to 2.5 in the upwelling region off the coast of Oman; total nitrogen assimilation followed a similar pattern. Very significant variations in the size distribution of the activity of the plankton were observed. Over 75% of the carbon and nitrogen assimilation was in the

The oceans have a fundamental role in the global climate system because of their capacity to store and transport heat and absorb and emit trace gases which affect the earth's radiation budget. Although good progress has been made with issues such as carbon and sulfur cycling, feedback responses related to the impact of climate change on biological systems, and links between plankton ecology and climate, there is a lack of information on the distributions of biological properties on a global scale. This article reviews the potential contribution of ocean color measurements for biological studies within the context of climate change. The remote sensing of oceanic phytoplankton from satellites measuring radiance at visible and near infrared wavelenghts has produced a wealth of new information on biomass distributions and has provided a basis for new approaches to estimation of global marine primary productivity.

This work presents a multiagent system for evaluating automatically the interaction that exists between the atmosphere and the ocean surface, monitoring and evaluating within the ocean carbon dioxide exchange process is a function requiring working with a great amount of data: satellite images and in situ Vessel’s data. The system presented in this work focuses on Ambient Intelligence (AmI) technologies since the vision of AmI assumes seamless, unobtrusive, and often invisible but also controllable interactions between humans and technology. The work presents the construction of an open multiagent architecture which, based on the use of deliberative agents incorporating Case-Based Reasoning (CBR) systems, offers a distributed model for such an interaction. This work also presents an analysis and design methodology that facilitates the implementation of CBR agent-based distributed artificial intelligent systems. Moreover, the architecture takes into account the fact that the working environment is dynamic and therefore it requires autonomous models that evolve overtime. In order to resolve this problem an intelligent environment has been developed, based on the use of CBR agents, which are capable of handling several goals, constructing plans from the data obtained through satellite images and research Vessels, acquiring knowledge, and of adapting to environmental changes, are incorporated. The artificial intelligence system has been successfully tested in the North Atlantic ocean, and the results obtained will be presented within this work.

The Atlantic Meridional Transect (AMT) cruises have been operating since 1995 with SeaWiFS satellite ocean colour data being available since September 1997. AMT sampling includes both underway and CTD stations with analysis of chlorophyll-a undertaken through HPLC. Matchups between AMT HPLC and SeaWiFS chlorophyll-a have been analysed using the SeaWiFS 8-day composites, and there is generally a good agreement (R2 from 0.68-0.91, slopes from 0.89-1.08 and intercepts of less than plusmn0.19). However, the long time series has uncovered inconsistencies which could be attributed to biases in the HPLC data once further research is undertaken

By improving accuracy in the quantification of the ocean’s CO2 budget, a more precise estimation can be made of the terrestrial fraction of global CO2 budget and its subsequent effect on climate change. First steps have been taken towards this from an environmental and economic point of view, by using an instance based reasoning system, which incorporates a novel clustering and retrieval method – a Cooperative Maximum Likelihood Hebbian Learning model (CoHeL). This paper reviews the problems of measuring the ocean’s CO2 budget and presents the CoHeL model developed and outlines the IBR system developed to resolve the problem.

The interaction of the atmosphere and the ocean has a profound effect on climate, while the uptake by the oceans of a major fraction of atmospheric carbon dioxide has a moderating influence. By improving accuracy in the quantification of the ocean’s carbon dioxide budget, a more precise estimation can be made of the terrestrial fraction of global carbon dioxide budget and its subsequent effect on climate change. First steps have been taken towards this from an environmental and economic point of view, by using an instance based reasoning system, which incorporates a novel clustering and retrieval method. This paper reviews the problems of measuring the ocean’s carbon dioxide budget and presents the model developed to resolve them.

The long-term goal is to obtain better measurements of the inherent optical properties of seawater (IOPs, absorption a and back-scattering bb ) to provide better parameterisations of the absorption of light by seawater, to improve heat budget models of surface ocean stratification. The proposed work will extend on-going research at PML on furthering the understanding, accurate interpretation and exploitation of remotely sensed data of ocean colour, from sensors: SeaWiFS, MODIS (NASA), MERIS (ESA). Assimilation of data from these sensors into 1-D and 3-D ocean circulation models is a long-term goal.

CBR systems are normally used to assist experts in the resolution of problems. During the last few years researchers have been working in the development of techniques to automate the reasoning stages identified in this methodology. This paper presents a Maximum Likelihood Hebbian Learning-based method that automates the organisation of cases and the retrieval stage of case-based reasoning systems. The proposed methodology has been derived as an extension of the Principal Component Analysis, and groups similar cases, identifying clusters automatically in a data set in an unsupervised mode. The method has been successfully used to completely automate the reasoning process of an oceanographic forecasting system and to improve its performance.

[1] Atmospheric and oceanic partial pressures of carbon dioxide and fluorescence were measured underway off the coast of northern Chile in January 1997. Seawater samples were taken for the analysis of nutrient and chlorophyll concentrations at 31 stations. The objectives were to improve the understanding of the biologically induced responses of upwelling processes off the coast of Chile and to assess the air-sea exchange of CO2 during the austral summer. The cruise sampled within a grid from 22°40S to 24°S extending offshore to 71°52′W during 10–16 January 1997 (survey 1) and 22–27 January 1997 (survey 2). Survey 1 measurements showed relatively uniform hydrographic and chemical properties, except south of the Mejillones peninsula, where colder and fresher water was observed. During the second survey, concurrent satellite imagery showed colder water in a narrow coastal band. The relatively cold and fresh water recorded there suggested that upwelled water originated mainly from subantarctic water rather than from the nutrient-rich equatorial subsurface water. Onshore-offshore variability dominated over longshore variability. The offshore subtropical water was characterized by a temperature of 23°C, a salinity of 34.9, and relatively uniform pCO2 around 400 μatm that was mainly temperature driven. Although strong CO2 drawdowns (pCO2 as low as 200 μatm) were located close to the coast following the upwelling events, overall, the region was a source of CO2 to the atmosphere. A pCO2 algorithm was constructed using the cruise data of sea surface temperature (SST) and salinity (S). Synthetic salinity was calculated from S-SST relationships determined for survey 2 and used with advanced very high resolution radiometer SST to calculate pCO2 over the cruise area, weekly, from January to March. European Centre for Medium-Range Weather Forecasts wind speeds were used to calculate the CO2 flux in the upwelling off Chile (22°S–29°S, 68°W–73°W). The region was a source of CO2 flux of 1.6 mmol m−2 d−1 from 1 January to 25 March 1997.

Geo-engineering proposals to mitigate global warming have focused either on methods of carbon dioxide removal, particularly nutrient fertilization of plant growth, or on cooling the Earth's surface by reducing incoming solar radiation (shading). Marine phytoplankton contribute half the Earth's biological carbon fixation and carbon export in the ocean is modulated by the actions of microbes and grazing communities in recycling nutrients. Both nutrients and light are essential for photosynthesis, so understanding the relative influence of both these geo-engineering approaches on ocean ecosystem production and processes is critical to the evaluation of their effectiveness. In this paper, we investigate the relationship between light and nutrient availability on productivity in a stratified, oligotrophic subtropical ocean ecosystem using a one-dimensional water column model coupled to a multi-plankton ecosystem model, with the goal of elucidating potential impacts of these geo-engineering approaches on ecosystem production. We find that solar shading approaches can redistribute productivity in the water column but do not change total production. Macronutrient enrichment is able to enhance the export of carbon, although heterotrophic recycling reduces the efficiency of carbon export substantially over time. Our results highlight the requirement for a fuller consideration of marine ecosystem interactions and feedbacks, beyond simply the stimulation of surface blooms, in the evaluation of putative geo-engineering approaches.

Biological and optical characterization of the Arctic Front (AF), which separates North Atlantic waters from the Greenland Sea Gyre, has not been well studied and we report, herein, the first synoptic description of bio-optical and temperature variability across the AF utilizing both shipboard (vertical and horizontal measurements utilizing the towed Undulating Oceanographic Record, UOR) and satellite (AVHRR) observations of sea surface temperature and visible band reflectances (580–680 nm). The UOR measures depth, temperature, in vivo chlorophyll fluorescence, upwelling and downwelling hemispherical (450, 488 and 550 nm) and vector (488 and 550 nm) irradiances at 10 s intervals during vertical undulations from 2 to 50 m. During a UOR tow on 19 August 1986, the AF was encountered as a sharp boundary with an abrupt change in bio-optical properties within the upper 50 m over a few miles. Temperatures increased from 5.7° to 8.4°C with the average chlorophyll concentration and diffuse attenuation coefficient [K(450)] increasing by factors of 4.1 and 1.8, respectively. Discrete samples for species composition and HPLC pigment analysis, taken within this high pigment region (150 miles in width), indicated that this near surface bloom was a mixed phytoplankton population with moderate concentrations of the coccolithophorid, Emiliania huxleyi. AVHRR visible band imagery showed a high reflectance patch adjacent to the frontal boundary which are normally associated with substantial concentration of coccolithophorids. If our observations on the magnitude and extent of the biomass are typical of the AF, it should have an important role in marine biogeochemical production in this high latitude area.

The abstract presents a hybrid system that has proved capable of creating a prediction detailing the physical interactions occurring in a rapidly changing oceanographic environment. The aim of the system is to identify and forecast the thermal structure of the water ahead of an ongoing vessel. The work focuses on the development of a system for forecasting the behaviour of complex environments, in which the underling knowledge of the domain is not completely available, the rules governing the system are fuzzy and the sets of data samples are limited and incomplete. The paper presents a hybrid approach that combines the ability of a case based reasoning system (CBR) for Selecting previous similar situations and the generalising ability of artificial neural networks (ANN) to guide the adaptation stage of the case base reasoning system. The system has been successfully tested in the Atlantic Ocean in September 1997.

The remote sensing of turbid waters (Case II) using the Medium Resolution Imaging Spectrometer (MERIS) requires new approaches for atmospheric correction of the data. Unlike the open ocean (Case I waters) there are no wavelengths where the water-leaving radiance is zero. A coupled hydrological atmospheric model is described here. The model solves the water-leaving radiance and atmospheric path radiance in the near-infrared (NIR) over Case II turbid waters. The theoretical basis of this model is described, together with its place in the proposed MERIS processing architecture. Flagging procedures are presented that allow seamless correction of both Case I waters, using conventional models, and Case II waters using the proposed model. Preliminary validation of the model over turbid waters in the Humber estuary, UK is presented using Compact Airborne Spectrographic Imager (CASI) imagery to simulate the MERIS satellite sensor. The results presented show that the atmospheric correction scheme has superior perfo...