Optical characterization of marine phytoplankton assemblages within surface waters of the western Arctic Ocean.

An extensive data set of measurements within the Chukchi and Beaufort Seas is used to characterize the optical properties of seawater associated with different phytoplankton communities. Hierarchical cluster analysis of diagnostic pigment concentrations partitioned stations into four distinct surface phytoplankton communities based on taxonomic composition and average cell size. Concurrent optical measurements of spectral absorption and backscattering coefficients and remote-sensing reflectance were used to characterize the magnitudes and spectral shapes of seawater optical properties associated with each phytoplankton assemblage. The results demonstrate measurable differences among communities in the average spectral shapes of the phytoplankton absorption coefficient. Similar or smaller differences were also observed in the spectral shapes of nonphytoplankton absorption coefficients and the particulate backscattering coefficient. Phytoplankton on average, however, contributed only 25% or less to the total absorption coefficient of seawater. Our analyses indicate that the interplay between the magnitudes and relative contributions of all optically significant constituents generally dampens any influence of varying phytoplankton absorption spectral shapes on the total absorption coefficient, yet there is still a marked discrimination observed in the spectral shape of the ratio of the total backscattering to total absorption coefficient and remote-sensing reflectance among the phytoplankton assemblages. These spectral variations arise mainly from differences in the bio-optical environment in which specific communities were found, as opposed to differences in the spectral shapes of phytoplankton optical properties per se. These results suggest potential approaches for the development of algorithms to assess phytoplankton community composition from measurements of seawater optical properties in western Arctic waters

Evaluating the spatial transferability and temporal repeatability of remote sensing-based lake water quality retrieval algorithms at the European scale:a meta-analysis approach

Many studies have shown the considerable potential for the application of remote-sensing-based methods for deriving estimates of lake water quality. However, the reliable application of these methods across time and space is complicated by the diversity of lake types, sensor configuration, and the multitude of different algorithms proposed. This study tested one operational and 46 empirical algorithms sourced from the peer-reviewed literature that have individually shown potential for estimating lake water quality properties in the form of chlorophyll-a (algal biomass) and Secchi disc depth (SDD) (water transparency) in independent studies. Nearly half (19) of the algorithms were unsuitable for use with the remote-sensing data available for this study. The remaining 28 were assessed using the Terra/Aqua satellite archive to identify the best performing algorithms in terms of accuracy and transferability within the period 2001–2004 in four test lakes, namely Vänern, Vättern, Geneva, and Balaton. These lakes represent the broad continuum of large European lake types, varying in terms of eco-region (latitude/longitude and altitude), morphology, mixing regime, and trophic status. All algorithms were tested for each lake separately and combined to assess the degree of their applicability in ecologically different sites. None of the algorithms assessed in this study exhibited promise when all four lakes were combined into a single data set and most algorithms performed poorly even for specific lake types. A chlorophyll-a retrieval algorithm originally developed for eutrophic lakes showed the most promising results (R2 = 0.59) in oligotrophic lakes. Two SDD retrieval algorithms, one originally developed for turbid lakes and the other for lakes with various characteristics, exhibited promising results in relatively less turbid lakes (R2 = 0.62 and 0.76, respectively). The results presented here highlight the complexity associated with remotely sensed lake water quality estimates and the high degree of uncertainty due to various limitations, including the lake water optical properties and the choice of methods

Validation of standard and alternative satellite ocean-color chlorophyll products off Western Iberia

Chlorophyll a concentration (Chl) product validation off theWestern Iberian coast is here undertaken by directly comparing remote sensing data with in situ surface reference values. Both standard and recently developed alternative algorithms are considered for match-up data analysis. The investigated standard products are those produced by the MERIS (algal 1 and algal 2) and MODIS (OC3M) algorithms. The alternative data products include those generatedwithin the CoastColour Project and Ocean Color Climate Change Initiative (OC-CCI) funded by ESA, as well as a neural net model trained with field measurements collected in the Atlantic off Portugal (MLPATLP). Statistical analyses showed that satellite Chl estimates tend to be larger than in situ reference values. The study also revealed that a non-uniform Chl distribution in the water column can be a concurring factor to the documented overestimation tendency when considering larger optical depth match-up stations. Among standard remote sensing products, MODIS OC3M and MERIS algal 2 yield the best agreement with in situ data. The performance of MLPATLP highlights the capability of regional solutions to further improve Chl retrieval by accounting for environmental specificities. Results also demonstrate the relevance of oceanographic regions such as the Nazaré area to evaluate how complex hydrodynamic conditions can influence the quality of Chl products.This studywas performed in the framework of HabSpot FCT Project, PTDC/MAR/100348/2008 and European Space Agency projects DUE CoastColour (ESRIN/AO/1-6141/09/l-EC) and Climate Change Iniciative — Ocean Color (AO-1/6207/09/I-LG). The work has been also partially supported by the European Space Agency within the framework of the MERIS Validation Activities under contract n. 12595/09/I-OL, and sampling activities benefited from European projects HERMES (GOCE-CT-2005-511234) and Hermione (EC contract 226354) support. We would like to thank NASA OBPG for the MODIS data and ESA Project AOPT-2423 for providing MERIS full resolution images. Ana C. Brito was funded by a Portuguese Post-doc grant from FCT (BPD/63017/2009) and by the Investigador FCT Program (IF/00331/2013). Davide D'Alimonte was funded by Investigador FCT Program (IF/00541/2013).info:eu-repo/semantics/publishedVersio

Long-Term Trends in Phytoplankton Chlorophyll a and Size Structure in the Benguela Upwelling System

This is the final version. Available from American Geophysical Union (AGU) via the DOI in this record.The Benguela Upwelling System (BUS) is among the most productive ecosystems globally, supporting numerous fisheries and ecosystem services in Southern Africa. Sea-viewing Wide Field-of-view Sensor and Moderate-resolution Imaging Spectroradiometer-Aqua chlorophyll a (Chla) concentrations between September 1997 and February 2018 were used to investigate long-term trends in phytoplankton biomass and size structure (microphytoplankton [>20 μm], nanophytoplankton [2–20 μm], and picophytoplankton [<2 μm]) in the Northern Benguela, Southern Benguela (SB), and Agulhas Bank (AB) shelf and open ocean regions of the BUS. Trends in upwelling and correlations with Chla and size structure were examined. Increasing Chla and microphytoplankton trends occurred in the Northern Benguela shelf and open ocean, while decreases were evident on the SB shelf in all seasons. In the SB open ocean, small increases occurred during austral winter, with a decrease in spring. On the AB shelf, increases in Chla and microphytoplankton occurred in summer with decreases during the other seasons. Patterns differed in the AB open ocean, with increases in winter and spring and decreases in summer and autumn. Although R 2 values indicated that linear trends accounted for a reasonable portion of the variance, and most trends were statistically significant, they showed only small changes on the shelf domains and little to no change in the open ocean. Strong correlations between upwelling, Chla, and the size classes were observed, but distinct seasonal differences occurred in each region. This is the first 20-year analysis of phytoplankton biomass and community structure in the BUS and provides a baseline against which future changes can be monitored.NERC National Centre for Earth ObservationSouth African National Research Foundation (NRF)South African Department of Environmental Affair

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

Ocean colour changes in the North Pacific since 1930

In this paper we present an analysis of historical ocean colour data from the North Pacific Ocean. This colour is described by the Forel-Ule colour index, a sea colour comparator scale that is composed of 21 tube colours that is routinely measured since the year 1890. The main objective of this research is to characterise colour changes of the North Pacific Ocean at a timescale of decades. Next to the seasonal colour changes, due to the yearly cycle of biological activity, this time series between 1930 and 1999 might contain information on global changes in climate conditions. From seasonal independent analyses of the long-term variations it was found that the greenest values, with mean Forel-Ule scale ((FU) ̅) of 4.1 were reached during the period of 1950-1954, with a second high ((FU) ̅ = 3) in the period 1980-1984. The bluest ocean was encountered during the years 1990-1994. The data indicate that after 1955 a remarkable long bluing took place till 1980

Biomineralization plasticity and environmental heterogeneity predict geographical resilience patterns of foundation species to future change.

Although geographical patterns of species' sensitivity to environmental changes are defined by interacting multiple stressors, little is known about compensatory processes shaping regional differences in organismal vulnerability. Here, we examine large-scale spatial variations in biomineralization under heterogeneous environmental gradients of temperature, salinity and food availability across a 30° latitudinal range (3,334 km), to test whether plasticity in calcareous shell production and composition, from juveniles to large adults, mediates geographical patterns of resilience to climate change in critical foundation species, the mussels Mytilus edulis and M. trossulus. We find shell calcification decreased towards high latitude, with mussels producing thinner shells with a higher organic content in polar than temperate regions. Salinity was the best predictor of within-region differences in mussel shell deposition, mineral and organic composition. In polar, subpolar, and Baltic low-salinity environments, mussels produced thin shells with a thicker external organic layer (periostracum), and an increased proportion of calcite (prismatic layer, as opposed to aragonite) and organic matrix, providing potentially higher resistance against dissolution in more corrosive waters. Conversely, in temperate, higher salinity regimes, thicker, more calcified shells with a higher aragonite (nacreous layer) proportion were deposited, which suggests enhanced protection under increased predation pressure. Interacting effects of salinity and food availability on mussel shell composition predict the deposition of a thicker periostracum and organic-enriched prismatic layer under forecasted future environmental conditions, suggesting a capacity for increased protection of high-latitude populations from ocean acidification. These findings support biomineralization plasticity as a potentially advantageous compensatory mechanism conferring Mytilus species a protective capacity for quantitative and qualitative trade-offs in shell deposition as a response to regional alterations of abiotic and biotic conditions in future environments. Our work illustrates that compensatory mechanisms, driving plastic responses to the spatial structure of multiple stressors, can define geographical patterns of unanticipated species resilience to global environmental change

A high-performance computing framework for Monte Carlo ocean color simulations

This paper presents a high-performance computing (HPC) framework for Monte Carlo (MC) simulations in the ocean color (OC) application domain. The objective is to optimize a parallel MC radiative transfer code named MOX, developed by the authors to create a virtual marine environment for investigating the quality of OC data products derived from in situ measurements of in-water radiometric quantities. A consolidated set of solutions for performance modeling, prediction, and optimization is implemented to enhance the efficiency of MC OC simulations on HPC run-time infrastructures. HPC, machine learning, and adaptive computing techniques are applied taking into account a clear separation and systematic treatment of accuracy and precision requirements for large-scale MC OC simulations. The added value of the work is the integration of computational methods and tools for MC OC simulations in the form of an HPC-oriented problem-solving environment specifically tailored to investigate data acquisition and reduction methods for OC field measurements. Study results highlight the benefit of close collaboration between HPC and application domain researchers to improve the efficiency and flexibility of computer simulations in the marine optics application domain. (C) 2016 The Authors. Concurrency and Computation: Practice and Experience Published by John Wiley & Sons Ltd.Portuguese Foundation for Science and Technology (FCT/MEC) [PEst-OE/EEI/UI0527/2011]; ESA [22576/09/I-OL, ARG/003-025/1406/CIMA]; NOVA LINCS [UID/CEC/04516/2013]info:eu-repo/semantics/publishedVersio

Dynamic biogeochemical provinces in the global ocean

In recent decades, it has been found useful to partition the pelagic environment using the concept of biogeochemical provinces, or BGCPs, within each of which it is assumed that environmental conditions are distinguishable and unique at global scale. The boundaries between provinces respond to features of physical oceanography and, ideally, should follow seasonal and interannual changes in ocean dynamics. But this ideal has not been fulfilled except for small regions of the oceans. Moreover, BGCPs have been used only as static entities having boundaries that were originally established to compute global primary production. In the present study, a new statistical methodology based on non-parametric procedures is implemented to capture the environmental characteristics within 56 BGCPs. Four main environmental parameters (bathymetry, chlorophyll a concentration, surface temperature, and salinity) are used to infer the spatial distribution of each BGCP over 1997–2007. The resulting dynamic partition allows us to integrate changes in the distribution of BGCPs at seasonal and interannual timescales, and so introduces the possibility of detecting spatial shifts in environmental conditions