991 resultados para SATELLITE OCEAN COLOR


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The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.

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Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models.

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Owing to their important roles in biogeochemical cycles, phytoplankton functional types (PFTs) have been the aim of an increasing number of ocean color algorithms. Yet, none of the existing methods are based on phytoplankton carbon (C) biomass, which is a fundamental biogeochemical and ecological variable and the "unit of accounting" in Earth system models. We present a novel bio-optical algorithm to retrieve size-partitioned phytoplankton carbon from ocean color satellite data. The algorithm is based on existing methods to estimate particle volume from a power-law particle size distribution (PSD). Volume is converted to carbon concentrations using a compilation of allometric relationships. We quantify absolute and fractional biomass in three PFTs based on size - picophytoplankton (0.5-2 µm in diameter), nanophytoplankton (2-20 µm) and microphytoplankton (20-50 µm). The mean spatial distributions of total phytoplankton C biomass and individual PFTs, derived from global SeaWiFS monthly ocean color data, are consistent with current understanding of oceanic ecosystems, i.e., oligotrophic regions are characterized by low biomass and dominance of picoplankton, whereas eutrophic regions have high biomass to which nanoplankton and microplankton contribute relatively larger fractions. Global climatological, spatially integrated phytoplankton carbon biomass standing stock estimates using our PSD-based approach yield - 0.25 Gt of C, consistent with analogous estimates from two other ocean color algorithms and several state-of-the-art Earth system models. Satisfactory in situ closure observed between PSD and POC measurements lends support to the theoretical basis of the PSD-based algorithm. Uncertainty budget analyses indicate that absolute carbon concentration uncertainties are driven by the PSD parameter No which determines particle number concentration to first order, while uncertainties in PFTs' fractional contributions to total C biomass are mostly due to the allometric coefficients. The C algorithm presented here, which is not empirically constrained a priori, partitions biomass in size classes and introduces improvement over the assumptions of the other approaches. However, the range of phytoplankton C biomass spatial variability globally is larger than estimated by any other models considered here, which suggests an empirical correction to the No parameter is needed, based on PSD validation statistics. These corrected absolute carbon biomass concentrations validate well against in situ POC observations.

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Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color-based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BCGCMs) represent a key resource for biogeochemical and ecological studies at global as well as regional scales. Calibration and validation of these PP models are not straightforward, however, and comparative studies show large differences between model estimates. The goal of this paper is to compare PP estimates obtained from 30 different models (21 SatPPMs and 9 BOGCMs) to a tropical Pacific PP database consisting of similar to 1000 C-14 measurements spanning more than a decade (1983-1996). Primary findings include: skill varied significantly between models, but performance was not a function of model complexity or type (i.e. SatPPM vs. BOGCM); nearly all models underestimated the observed variance of PR specifically yielding too few low PP (< 0.2 g Cm-2 d(-1)) values; more than half of the total root-mean-squared model-data differences associated with the satellite-based PP models might be accounted for by uncertainties in the input variables and/or the PP data; and the tropical Pacific database captures a broad scale shift from low biomassnormalized productivity in the 1980s to higher biomass-normalized productivity in the 1990s, which was not successfully captured by any of the models. This latter result suggests that interdecadal and global changes will be a significant challenge for both SatPPMs and BOGCMs. Finally, average root-mean-squared differences between in situ PP data on the equator at 140 degrees W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison 6 years ago. The success of these types of comparison exercises is illustrated by the continual modification and improvement of the participating models and the resulting increase in model skill. (C) 2008 Elsevier BY. All rights reserved.

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Ocean biogeochemical and ecosystem processes are linked by net primary production (NPP) in the ocean's surface layer, where inorganic carbon is fixed by photosynthetic processes. Determinations of NPP are necessarily a function of phytoplankton biomass and its physiological status, but the estimation of these two terms from space has remained an elusive target. Here we present new satellite ocean color observations of phytoplankton carbon (C) and chlorophyll (Chl) biomass and show that derived Chl:C ratios closely follow anticipated physiological dependencies on light, nutrients, and temperature. With this new information, global estimates of phytoplankton growth rates (mu) and carbon-based NPP are made for the first time. Compared to an earlier chlorophyll-based approach, our carbon-based values are considerably higher in tropical oceans, show greater seasonality at middle and high latitudes, and illustrate important differences in the formation and demise of regional algal blooms. This fusion of emerging concepts from the phycological and remote sensing disciplines has the potential to fundamentally change how we model and observe carbon cycling in the global oceans.

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Five years (1979-1983) of Coastal Zone Color Scanner satellite ocean color data are used to examine seasonal patterns of phytoplankton pigment concentration along the Chilean coast from 20 degrees S to 45 degrees S. Four kilometer resolution, 2-4 day composites document the presence of filaments of elevated pigment concentration extending offshore throughout the study area, with maximum offshore extension at higher latitudes. In three years, 1979, 1981, and 1983, sufficient data exist in monthly composites to allow recreation of portions of the seasonal cycle. Data in 1979 are the most complete. Near-shore concentrations and cross-shelf extension of pigment concentrations in 1979 are maximum in austral winter throughout the study area and minimum in summer. Available data from 1981 and 1983 are consistent with this temporal pattern but with concentrations approximately double those of 1979. Seasonal, spatial patterns within 10 km of shore and 50 km offshore indicate a latitudinal discontinuity both in absolute concentration and in the magnitude of the seasonal cycle at approximately 33 degrees S in both 1979 and in the climatological time series. The discontinuity is strongest ill fall-winter and weakest in summer. South of this latitude, concentrations are relatively high (2-3 mg m(-3) in 1979), a strong seasonal cycle is present, and patterns 50 km offshore are correlated with those within 10 km of shore. North of 33 degrees S, concentrations are < 1.5 mg m(-3) (in 1979), and the seasonal cycle within 10 km of shore is present but much weaker and less obviously correlated with that 50 km offshore. The seasonal cycle of pigment concentrations is 180 degrees out of phase with monthly averaged upwelling favorable winds. Noncoincident Pathfinder sea surface temperature data show that over most latitudes, coastal low surface temperatures lag wind forcing by 1-2 months, but these too are out of phase with the pigment seasonal cycle. These data point to control of pigment patterns along the Chilean coast by the interaction of upwelling with circulation patterns unconnected to local wind forcing.

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In this paper, modernized shipborne procedures are presented to collect and process above-water radiometry for remote sensing applications. A setup of five radiometers and a bidirectional camera system, which provides panoramic sea surface and sky images, is proposed for the collection of high-resolution radiometric quantities. Images from the camera system can be used to determine sky state and potential glint, whitecaps, or foam contamination. A peak in the observed remote sensing reflectance RRS spectra between 750-780 nm was typically found in spectra with relatively high surface reflected glint (SRG), which suggests this waveband could be a useful SRG indicator. Simplified steps for computing uncertainties in SRG corrected RRS are proposed and discussed. The potential of utilizing "unweighted multimodel averaging," which is the average of four or more common SRG correction models, is examined to determine the best approximation RRS. This best approximation RRS provides an estimate of RRS based on various SRG correction models established using radiative transfer simulations and field investigations. Applying the average RRS provides a measure of the inherent uncertainties or biases that result from a user subjectively choosing any one SRG correction model. Comparisons between inherent and apparent optical property derived observations were used to assess the robustness of the SRG multimodel averaging ap- proach. Correlations among the standard SRG models were completed to determine the degree of association or similarities between the SRG models. Results suggest that the choice of glint models strongly affects derived RRS values and can also influence the blue to green band ratios used for modeling biogeochemical parameters such as for chlorophyll a. The objective here is to present a uniform and traceable methodology for determining ship- borne RRS measurements and its associated errors due to glint correction and to ensure the direct comparability of these measurements in future investigations. We encourage the ocean color community to publish radiometric field measurements with matching and complete metadata in open access repositories.

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Mode of access: Internet.

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A procedure has been proposed by Ciotti and Bricaud (2006) to retrieve spectral absorption coefficients of phytoplankton and colored detrital matter (CDM) from satellite radiance measurements. This was also the first procedure to estimate a size factor for phytoplankton, based on the shape of the retrieved algal absorption spectrum, and the spectral slope of CDM absorption. Applying this method to the global ocean color data set acquired by SeaWiFS over twelve years (1998-2009), allowed for a comparison of the spatial variations of chlorophyll concentration ([Chl]), algal size factor (S-f), CDM absorption coefficient (a(cdm)) at 443 nm, and spectral slope of CDM absorption (S-cdm). As expected, correlations between the derived parameters were characterized by a large scatter at the global scale. We compared temporal variability of the spatially averaged parameters over the twelve-year period for three oceanic areas of biogeochemical importance: the Eastern Equatorial Pacific, the North Atlantic and the Mediterranean Sea. In all areas, both S-f and a(cdm)(443) showed large seasonal and interannual variations, generally correlated to those of algal biomass. The CDM maxima appeared in some occasions to last longer than those of [Chl]. The spectral slope of CDM absorption showed very large seasonal cycles consistent with photobleaching, challenging the assumption of a constant slope commonly used in bio-optical models. In the Equatorial Pacific, the seasonal cycles of [Chl], S-f, a(cdm)(443) and S-cdm, as well as the relationships between these parameters, were strongly affected by the 1997-98 El Ni o/La Ni a event.

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Intense phytoplankton blooms were observed along the Patagonian shelf-break with satellite ocean color data, but few in situ optical observations were made in that region. We examine the variability of phytoplankton absorption and particulate scattering coefficients during such blooms on the basis of field data. The chlorophyll-a concentration, [Chla], ranged from 0.1 to 22.3 mg m−3 in surface waters. The size fractionation of [Chla] showed that 80% of samples were dominated by nanophytoplankton (N-group) and 20% by microphytoplankton (M-group). Chlorophyll-specific phytoplankton absorption coefficients at 440 and 676 nm, a*ph(440) and a*ph(676), and particulate scattering coefficient at 660 nm, b*p(660), ranged from 0.018 to 0.173, 0.009 to 0.046, and 0.031 to 2.37 m2 (mg Chla)−1, respectively. Both a*ph(440) and a*ph(676) were statistically higher for the N-group than M-group and also considerably higher than expected from global trends as a function of [Chla]. This result suggests that size of phytoplankton cells in Patagonian waters tends to be smaller than in other regions at similar [Chla]. The phytoplankton cell size parameter, Sf, derived from phytoplankton absorption spectra, proved to be useful for interpreting the variability in the data around the general inverse dependence of a*ph(440), a*ph(676), and b*p(660) on [Chla]. Sf also showed a pattern along the increasing trend of a*ph(440) and a*ph(676) as a function of the ratios of some accessory pigments to [Chla]. Our results suggest that the variability in phytoplankton absorption and scattering coefficients in Patagonian waters is caused primarily by changes in the dominant phytoplankton cell size accompanied by covariation in the concentrations of accessory pigments.

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The oceans play a critical role in the Earth's climate, but unfortunately, the extent of this role is only partially understood. One major obstacle is the difficulty associated with making high-quality, globally distributed observations, a feat that is nearly impossible using only ships and other ocean-based platforms. The data collected by satellite-borne ocean color instruments, however, provide environmental scientists a synoptic look at the productivity and variability of the Earth's oceans and atmosphere, respectively, on high-resolution temporal and spatial scales. Three such instruments, the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) onboard ORBIMAGE's OrbView-2 satellite, and two Moderate Resolution Imaging Spectroradiometers (MODIS) onboard the National Aeronautic and Space Administration's (NASA) Terra and Aqua satellites, have been in continuous operation since September 1997, February 2000, and June 2002, respectively. To facilitate the assembly of a suitably accurate data set for climate research, members of the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project and SeaWiFS Project Offices devote significant attention to the calibration and validation of these and other ocean color instruments. This article briefly presents results from the SIMBIOS and SeaWiFS Project Office's (SSPO) satellite ocean color validation activities and describes the SeaWiFS Bio-optical Archive and Storage System (SeaBASS), a state-of-the-art system for archiving, cataloging, and distributing the in situ data used in these activities.

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The purpose of the present study was to explore the composition and variation of the pico-, nano- and micro-plankton communities in Norwegian coastal waters and Skagerrak, and the co-occurrence of bacteria and viruses. Samples were collected along three cruise transects from Jaeren, Lista and Oksoy on the south coast of Norway and into the North Sea and Skagerrak. We also followed a drifting buoy for 55 h in Skagerrak in order to observe diel variations. Satellite ocean color images (SeaWiFS) of the chlorophyll a (chl a) distribution compared favorably to in situ measurements in open waters, while closer to the shore remote sensing chl a data was overestimated compared to the in situ data. Using light microscopy, we identified 49 micro- and 15 nanoplankton sized phototrophic forms as well as 40 micro- and 12 nanoplankton sized heterotrophic forms. The only picoeukaryote (0.2-2.0 µm) we identified was Resultor micron (Pedinophyceae). Along the transects a significant variation in the distribution and abundance of different plankton forms were observed, with Synechococcus spp and autotrophic picoeukaryotes as the most notable examples. There was no correlation between viruses and chl a, but between viruses and bacteria, and between viruses and some of the phytoplankton groups, especially the picoeukaryotes. Moreover, there was a negative correlation between nutrients and small viruses (Low Fluorescent Viruses) but a positive correlation between nutrients and large viruses (High Fluorescent Viruses). The abundance of autotrophic picoplankton, bacteria and viruses showed a diel variation in surface waters with higher values around noon and late at night and lower values in the evening. Synechococcus spp were found at 20 m depth 25-45 nautical miles from shore apparently forming a bloom that stretched out for more than 100 nautical miles from Skagerrak and up the south west coast of Norway. The different methods used for assessing abundance, distribution and diversity of microorganisms yielded complementary information about the plankton community. Flow cytometry enabled us to map the distribution of the smaller phytoplankton forms, bacteria and viruses in more detail than has been possible before but detection and quantification of specific forms (genus or species) still requires taxonomic skills, molecular analysis or both.