Increased Chlorophyll Levels in the Southern Caspian Sea Following an Invasion of Jellyfish

A significant correlation was observed between satellite derived chlorophyll a (Chl a) concentrations and the biomass of the invasive comb jellyfish Mnemiopsis leidyi in the southern Caspian Sea. By consuming the herbivorous zooplankton, the predatory ctenophore M. leidyi may have caused levels of Chl a to rise to very high values (∼9 mg m−3) in the southern Caspian Sea. There might also be several other factors concurrent with predation effects of M. leidyi influencing Chl a levels in this region, such as eutrophication and climatic changes which play major roles in nutrient, phytoplankton, and zooplankton variations. The decrease in pelagic fishes due to overfishing, natural, and anthropogenic impacts might have provided a suitable environment for M. leidyi to spread throughout this enclosed basin

Experimental and numerical analysis of the chromatic dispersion dependence upon the actual profile of small core microstructured fibres

International audienceThe chromatic dispersion curve of the fundamental mode in small core microstructured fibres (SCMF) is both calculated using a Finite Element Method (FEM) and measured with a low coherence interferometric method. The great sensitivity of the chromatic dispersion to variations of the geometrical parameters of SCMFs (the pitch and the diameter) is pointed out. An excellent agreement is obtained between the numerical and the experimental results over a half micrometer spectral bandwidth [1.1 µm-1.6 µm]

System Vicarious Calibration for Ocean Color Climate Change Applications: Requirements for In Situ Data

System Vicarious Calibration (SVC) ensures a relative radiometric calibration to satellite ocean color sensors that minimizes uncertainties in the water-leaving radiance Lw derived from the top of atmosphere radiance LT. This is achieved through the application of adjustment gain-factors, g-factors, to pre-launch absolute radiometric calibration coefficients of the satellite sensor corrected for temporal changes in radiometric sensitivity. The g-factors are determined by the ratio of simulated to measured spectral LT values where the former are computed using: i. highly accurate in situ Lw reference measurements; and ii. the same atmospheric model and algorithms applied for the atmospheric correction of satellite data. By analyzing basic relations between relative uncertainties of Lw and LT, and g-factors consistently determined for the same satellite missions using different in situ data sources, this work suggests that the creation of ocean color Climate Data Records (CDRs) should ideally rely on: i. one main long-term in situ calibration system (site and radiometry) established and sustained with the objective to maximize accuracy and precision over time of g-factors and thus minimize possible biases among satellite data products from different missions; and additionally ii. unique (i.e., standardized) atmospheric model and algorithms for atmospheric correction to maximize cross-mission consistency of data products at locations different from that supporting SVC. Finally, accounting for results from the study and elements already provided in literature, requirements and recommendations for SVC sites and field radiometers radiometric measurements are streamlined

An ocean-colour time series for use in climate studies: the experience of the ocean-colour climate change initiate (OC-CCI)

Ocean colour is recognised as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS); and spectrally-resolved water-leaving radiances (or remote-sensing reflectances) in the visible domain, and chlorophyll-a concentration are identified as required ECV products. Time series of the products at the global scale and at high spatial resolution, derived from ocean-colour data, are key to studying the dynamics of phytoplankton at seasonal and inter-annual scales; their role in marine biogeochemistry; the global carbon cycle; the modulation of how phytoplankton distribute solar-induced heat in the upper layers of the ocean; and the response of the marine ecosystem to climate variability and change. However, generating a long time series of these products from ocean colour data is not a trivial task: algorithms that are best suited for climate studies have to be selected from a number that are available for atmospheric correction of the satellite signal and for retrieval of chlorophyll-a concentration; since satellites have a finite life span, data from multiple sensors have to be merged to create a single time series, and any uncorrected inter-sensor biases could introduce artefacts in the series, e.g., different sensors monitor radiances at different wavebands such that producing a consistent time series of reflectances is not straightforward. Another requirement is that the products have to be validated against in situ observations. Furthermore, the uncertainties in the products have to be quantified, ideally on a pixel-by-pixel basis, to facilitate applications and interpretations that are consistent with the quality of the data. This paper outlines an approach that was adopted for generating an ocean-colour time series for climate studies, using data from the MERIS (MEdium spectral Resolution Imaging Spectrometer) sensor of the European Space Agency; the SeaWiFS (Sea viewingWide-Field-of-view Sensor) and MODIS-Aqua (Moderate-resolution Imaging Spectroradiometer-Aqua) sensors from the National Aeronautics and Space Administration (USA); and VIIRS (Visible and Infrared Imaging Radiometer Suite) from the National Oceanic and Atmospheric Administration (USA). The time series now covers the period from late 1997 to end of 2018. To ensure that the products meet, as well as possible, the requirements of the user community, marine-ecosystem modellers, and remote-sensing scientists were consulted at the outset on their immediate and longer-term requirements as well as on their expectations of ocean-colour data for use in climate research. Taking the user requirements into account, a series of objective criteria were established, against which available algorithms for processing ocean-colour data were evaluated and ranked. The algorithms that performed best with respect to the climate user requirements were selected to process data from the satellite sensors. Remote-sensing reflectance data from MODIS-Aqua, MERIS, and VIIRS were band-shifted to match the wavebands of SeaWiFS. Overlapping data were used to correct for mean biases between sensors at every pixel. The remote-sensing reflectance data derived from the sensors were merged, and the selected in-water algorithm was applied to the merged data to generate maps of chlorophyll concentration, inherent optical properties at SeaWiFS wavelengths, and the diffuse attenuation coefficient at 490 nm. The merged products were validated against in situ observations. The uncertainties established on the basis of comparisons with in situ data were combined with an optical classification of the remote-sensing reflectance data using a fuzzy-logic approach, and were used to generate uncertainties (root mean square difference and bias) for each product at each pixel

Sinking Jelly-Carbon Unveils Potential Environmental Variability along a Continental Margin

Particulate matter export fuels benthic ecosystems in continental margins and the deep sea, removing carbon from the upper ocean. Gelatinous zooplankton biomass provides a fast carbon vector that has been poorly studied. Observational data of a large-scale benthic trawling survey from 1994 to 2005 provided a unique opportunity to quantify jelly-carbon along an entire continental margin in the Mediterranean Sea and to assess potential links with biological and physical variables. Biomass depositions were sampled in shelves, slopes and canyons with peaks above 1000 carcasses per trawl, translating to standing stock values between 0.3 and 1.4 mg C m2 after trawling and integrating between 30,000 and 175,000 m2 of seabed. The benthopelagic jelly-carbon spatial distribution from the shelf to the canyons may be explained by atmospheric forcing related with NAO events and dense shelf water cascading, which are both known from the open Mediterranean. Over the decadal scale, we show that the jelly-carbon depositions temporal variability paralleled hydroclimate modifications, and that the enhanced jelly-carbon deposits are connected to a temperature-driven system where chlorophyll plays a minor role. Our results highlight the importance of gelatinous groups as indicators of large-scale ecosystem change, where jelly-carbon depositions play an important role in carbon and energy transport to benthic systems

Assessing the uncertainties of model estimates of primary productivity in the tropical Pacific Ocean

Author Posting. © Elsevier B.V., 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 76 (2009): 113-133, doi:10.1016/j.jmarsys.2008.05.010.Depth-integrated primary productivity (PP) estimates obtained from satellite ocean color based models (SatPPMs) and those generated from biogeochemical ocean general circulation models (BOGCMs) 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 ~1000 14C 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 PP, specifically yielding too few low PP (< 0.2 gC m-2d-2) 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 biomass-normalized 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°W and PP estimates from the satellite-based productivity models were 58% lower than analogous values computed in a previous PP model comparison six 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.This research was supported by a grant from the National Aeronautics and Space Agency Ocean Biology and Biogeochemistry program (NNG06GA03G), as well as by numerous other grants to the various participating investigator

SeaWiFS-derived products in the Baltic Sea: performance analysis of a simple atmospheric correction algorithm

Abstract The accuracy analysis of an approximate atmospheric correction algorithm for the processing of SeaWiFS data has been investigated for the Baltic Sea. The analysis made use of theoretical radiances produced with the FEM radiative transfer code for representative atmosphere-water test cases. The study showed uncertainties in the determination of the aerosol optical thickness at 865 nm and of theÅngström exponent lower than ±5% and ±10%, respectively. These results were confirmed by the analysis of 59 match-ups between satellite-derived and in situ measurements for a site located in the central Baltic. Because of the relatively high yellow substance absorption, often combined with the slanted solar illumination, the retrieval of the water-leaving radiance in the blue part of the spectrum appeared to be highly degraded, to the extent that almost no correlation was found between retrieved and simulated values. Better results were obtained at the other wavelengths. The accuracy in the estimation of the remote sensing reflectance ratio R 35 decreased with diminishing chlorophyll a concentration and increasing yellow substance absorption, ranging between ±7% and ±47%. The complete text of the paper is available at http://www.iopan.gda.pl/oceanologia/ 656 B. Bulgarelli, F. Mélin, G. Zibordi The propagation of R 35 uncertainties on chlorophyll a estimation was quantified. Keeping the same atmosphere-water conditions, the atmospheric correction scheme appeared sensitive to seasonal changes in the Sun zenith

Uncertainty Estimate of Satellite-Derived Normalized Water-Leaving Radiance

5 pages, 3 figures, 2 tablesThe quantification of uncertainties affecting satellite ocean color products is a fundamental step to ensure their compliance with mission and science requirements. This work investigated a methodology relying on the use of in situ radiometric data with known uncertainties to determine those affecting matching satellite data. By exploiting in situ radiometric data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC), an advanced method was applied to radiometric data products from the Ocean and Land Color Instruments onboard the Sentinel-3A satellite (OLCI-A) and the Visible Infrared Imager Radiometer Suite onboard the Suomi National-Polar Orbiting Partnership satellite (VIIRS-S). The results from the analysis support the relevance of the method proposedWith the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)Peer reviewe

SeaWiFS-derived products in the Baltic Sea: performance analysis of a simple atmospheric correction algorithm

The accuracy analysis of an approximate atmospheric correction algorithm for the processing of SeaWiFS data has been investigated for the Baltic Sea. The analysis made use of theoretical radiances produced with the FEM radiative transfer code for representative atmosphere-water test cases. The study showed uncertainties in the determination of the aerosol optical thickness at 865 nm and of the Ångström exponent lower than ± 5% and ± 10%, respectively. These results were confirmed by the analysis of 59 match-ups between satellite-derived and in situ measurements for a site located in the central Baltic. Because of the relatively high yellow substance absorption, often combined with the slanted solar illumination, the retrieval of the water-leaving radiance in the blue part of the spectrum appeared to be highly degraded, to the extent that almost no correlation was found between retrieved and simulated values. Better results were obtained at the other wavelengths. The accuracy in the estimation of the remote sensing reflectance ratio R35 decreased with diminishing chlorophyll a concentration and increasing yellow substance absorption, ranging between ± 7% and ± 47%. The propagation of R35 uncertainties on chlorophyll a estimation was quantified. Keeping the same atmosphere-water conditions, the atmospheric correction scheme appeared sensitive to seasonal changes in the Sun zenith