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1. HYPERNETS: a network of automated hyperspectral radiometers to validate water and land surface reflectance (380–1680 nm) from all satellite missions

Author

Kevin G. Ruddick, Agnieszka Bialek, Vittorio E. Brando, Pieter De Vis, Ana I. Dogliotti, David Doxaran, Philippe Goryl, Clémence Goyens, Joel Kuusk, Daniel Spengler, Kevin R. Turpie, and Quinten Vanhellemont

Subjects
satellite validation, hyperspectral reflectance, in situ measurements, automated network, radiometry, Geophysics. Cosmic physics, QC801-809, Meteorology. Climatology, QC851-999
Abstract

Satellites are now routinely used for measuring water and land surface reflectance and hence environmentally relevant parameters such as aquatic chlorophyll a concentration and terrestrial vegetation indices. For each satellite mission, radiometric validation is needed at bottom of atmosphere for all spectral bands and covering all typical conditions where the satellite data will be used. Existing networks such as AERONET-OC for water and RadCalNet for land provide vital information for validation, but (AERONET-OC) do not cover all spectral bands or (RadCalNet) do not cover all surface types and viewing angles. In this Perspective Article we discuss recent advances in instrumentation, measurement methods and uncertainty estimation in the field of optical radiometry and put forward the viewpoint that a new network of automated hyperspectral radiometers is needed for multi-mission radiometric validation of water and land surface reflectance. The HYPERNETS federated network concept is described, providing a context for research papers on specific aspects of the network. This network is unique in its common approach to both land and water surfaces. The common aspects and the differences between land and water measurements are explained. Based on early enthusiasm for HYPERNETS data from validation-oriented workshops, it is our viewpoint that this new network of automated hyperspectral radiometers will be useful for multi-mission radiometric validation of water and multi-angle land surface reflectance. The HYPERNETS network has strong synergy with other measurement networks (AERONET, AERONET-OC, RadCalNet, FLUXNET, ICOS, skycam, etc.) and with optional supplementary measurements, e.g., water turbidity and fluorescence, land surface temperature and soil moisture, etc.

Published
2024
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2. Editorial: Science and Applications of Coastal Remote Sensing

Author

Kevin R. Turpie, Steven G. Ackleson, Kristin B. Byrd, and Tiffany A. H. Moisan

Subjects
remote sensing, coastal water areas, marine ecosystems, coastal processes, turbid and shallow water, Science, General. Including nature conservation, geographical distribution, QH1-199.5
Published
2021
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3. Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI)

Author

Emmanuel Devred, Kevin R. Turpie, Wesley Moses, Victor V. Klemas, Tiffany Moisan, Marcel Babin, Gerardo Toro-Farmer, Marie-Hélène Forget, and Young-Heon Jo

Subjects
hyperspectral remote sensing, phytoplankton, absorption, ocean optics, Science
Abstract

Interpretation of remote sensing reflectance from coastal waters at different wavelengths of light yields valuable information about water column constituents, which in turn, gives information on a variety of processes occurring in coastal waters, such as primary production, biogeochemical cycles, sediment transport, coastal erosion, and harmful algal blooms. The Hyperspectral Infrared Imager (HyspIRI) is well suited to produce global, seasonal maps and specialized observations of coastal ecosystems and to improve our understanding of how phytoplankton communities are spatially distributed and structured, and how they function in coastal and inland waters. This paper draws from previously published studies on high-resolution, hyperspectral remote sensing of coastal and inland waters and provides an overview of how the HyspIRI mission could enable the retrieval of new aquatic biophysical products or improve the retrieval accuracy of existing satellite-derived products (e.g., inherent optical properties, phytoplankton functional types, pigment composition, chlorophyll-a concentration, etc.). The intent of this paper is to introduce the development of the HyspIRI mission to the coastal and inland remote sensing community and to provide information regarding several potential data products that were not originally part of the HyspIRI mission objectives but could be applicable to research related to coastal and inland waters. Further work toward quantitatively determining the extent and quality of these products, given the instrument and mission characteristics, is recommended.

Published
2013
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4. The Future: Nasa’s Surface Biology and Geology Mission and the Dark (Aquatic) Side

Author

Liane S Guild, Kevin R Turpie, David S Schimel, Benjamin Poulter, Charles Miller, E Natasha Stavros, Michelle M Gierach, Stephanie Schollaert Uz, Christine M Lee, and Jeffrey C Luvall

Subjects
Earth Resources And Remote Sensing
Abstract

With the release of NASA’s Earth System Observatory (ESO) measurement targets that includes studying the Earth’s Surface Biology and Geology (SBG), a global visible to shortwave infrared imaging spectrometer and a multispectral thermal infrared imager have been planned to launch in the late 2020s. This mission will enable unprecedented interdisciplinary science and applications relevant to studying the biology and geology of the Earth's surface. Measurement targets are directly aligned for studying coastal and inland waters ecosystems and water quality, including coralreef ecosystems, snow and ice, mineralogy, volcanology, biology, ecology, biodiversity, and components of radiative forcing from the surface such as greenhouse gas emissions. The observations not only have scientific value in studying feedbacks and interactions of surface processes (e.g., harmful algal blooms, domoic acid, oil spills, and other hazardous events), but also societal benefit – with the capacity to support real-world decision-making such as response to theseevents and inland water conservation, protection of drinking water quality for public and environmental health, and habitat conservation. The work presented here outlines the conducted mission and architecture study and the initiation of science performance trades (signal sensitivity; spectral, spatial, and temporal resolution; and atmospheric effects) informing the design of the SBG segment of the ESO providing the most value to myriad science and applications as possible. Science and applications synergies and algorithms with the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) and the Geostationary Littoral Imaging and Monitoring Radiometer (GLIMR) is opportunistic for advancing aquatics research and applications.

Published
2022

5. Spectral Fidelity of Earth's Terrestrial and Aquatic Ecosystems

Author

David R. Thompson, Philip G. Brodrick, Kerry Cawse-Nicholson, K. Dana Chadwick, Robert O. Green, Benjamin Poulter, Shawn Serbin, Alexey N. Shiklomanov, Philip A. Townsend, and Kevin R. Turpie

Subjects
Earth Resources And Remote Sensing
Abstract

The Surface Biology and Geology (SBG) investigation will create global maps of spectral surface reflectance and emissivity at a cadence of 16 days or better, with coverage to address global questions about Earth's geology, cryosphere and ecosystems. The revolutionary potential poses a commensurate challenge: creating contiguous maps free from regional biases induced by atmosphere, observation geometry, or inversion error. This will require an accurate calibration with precise knowledge of each channel's spectral response. Here, we quantify the impact of spectral calibration on SBG's aquatic and terrestrial ecosystem objectives. We find that contemporary algorithms for ecosystem trait retrieval demand more accurate spectral calibration than historical missions. Errors due to drift or spatial nonuniformity in the wavelength calibration that have previously been considered acceptable can cause systematic errors larger than the instrument noise and of the same order as the variability SBG aims to measure. Moreover, their impact on atmospheric correction can induce climate-dependent systematic errors that thwart comparisons between ecosystems. These results underscore the importance of spectral response accuracy in SBG mission design.

Published
2021
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6. The NASA OBPG 2020 On-Orbit Calibration of SNPP VIIRS for Ocean Color Applications

Author

Robert E. Eplee, Jr, Gerhard Meister, Frederick S Patt, Kevin R Turpie, Sean W Bailey, and Bryan A Franz

Subjects
Communications And Radar
Abstract

The NASA Ocean Biology Processing Group (OBPG) has continued monitoring the SNPP VIIRS on-orbit calibration for bands M1-M11 over its mission to optimize the calibration for ocean color applications. The OBPG has recently implemented several changes to the calibration scheme: using solar-derived f-factors to detrend the lunar observations; using long-term exponentials of time as basis vectors (along with libration angles) for radiometric fits to any resulting lunar temporal drifts; deriving gain adjustments to the solar f-factors from these exponentials; and deriving gain adjustments due to modulated RSRs outside of the solar/lunar calibration using TOA reference spectra. These calibration changes minimize the impact of uncertainties in any one component of the calibration on the derived f-factors. The final f-factors incorporate VIIRS solar diffuser measurements, h-factor BRDF corrections, lunar-derived gains, and modulated RSR gains. The combined BRDF corrections, lunar gain adjustments, and mRSR gain adjustments define effective h-factors for each band. The improvements in the on-orbit calibration are validated by evaluation of globally-derived anomaly plots of remote sensing reflectance for the ocean color bands. The ultimate goal of the OBPG calibration effort is incorporation of a consistent SNPP VIIRS ocean color data set into the NASA multi-mission ocean color climate data record.

Published
2019
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7. Comparison of two methodologies for calibrating satellite instruments in the visible and near infrared

Author

David Moyer, Christopher C. Moeller, Kevin R. Turpie, James J. Butler, Steven W. Brown, Robert A. Barnes, Keith R. Lykke, Bruce Guenther, F. DeLuccia, and Thomas Schwarting

Subjects
Visible Infrared Imaging Radiometer Suite, business.industry, Materials Science (miscellaneous), Astrophysics::Instrumentation and Methods for Astrophysics, Physics::Optics, Field of view, Industrial and Manufacturing Engineering, Article, Integrating sphere, Optics, Calibration, Radiance, Radiometry, Environmental science, Monochromatic color, Business and International Management, business, Radiometric calibration, Remote sensing
Abstract

Traditionally, satellite instruments that measure Earth-reflected solar radiation in the visible and near infrared wavelength regions have been calibrated for radiance responsivity in a two-step method. In the first step, the relative spectral response (RSR) of the instrument is determined using a nearly monochromatic light source such as a lamp-illuminated monochromator. These sources do not typically fill the field of view of the instrument nor act as calibrated sources of light. Consequently, they only provide a relative (not absolute) spectral response for the instrument. In the second step, the instrument views a calibrated source of broadband light, such as a lamp-illuminated integrating sphere. The RSR and the sphere's absolute spectral radiance are combined to determine the absolute spectral radiance responsivity (ASR) of the instrument. More recently, a full-aperture absolute calibration approach using widely tunable monochromatic lasers has been developed. Using these sources, the ASR of an instrument can be determined in a single step on a wavelength-by-wavelength basis. From these monochromatic ASRs, the responses of the instrument bands to broadband radiance sources can be calculated directly, eliminating the need for calibrated broadband light sources such as lamp-illuminated integrating spheres. In this work, the traditional broadband source-based calibration of the Suomi National Preparatory Project Visible Infrared Imaging Radiometer Suite sensor is compared with the laser-based calibration of the sensor. Finally, the impact of the new full-aperture laser-based calibration approach on the on-orbit performance of the sensor is considered.

Published
2015

8. Prospective HyspIRI global observations of tidal wetlands

Author

Young-Heon Jo, Victor V. Klemas, Kristin B. Byrd, Maggi Kelly, and Kevin R. Turpie

Subjects
Hydrology, geography, Biomass (ecology), geography.geographical_feature_category, Marsh, Soil Science, Geology, Wetland, Groundwater recharge, Ecotone, Geological & Geomatics Engineering, Physical Geography and Environmental Geoscience, Geomatic Engineering, Geophysics, Habitat, Brackish marsh, Salt marsh, Environmental science, Computers in Earth Sciences, Remote sensing
Abstract

© 2015. Tidal wetlands are highly productive and act as critical habitat for a wide variety of plants, fish, shellfish, and other wildlife. These ecotones between aquatic and terrestrial environments also provide protection from storm damage, run-off filtering, and recharge of aquifers. Many wetlands along coasts have been exposed to stress-inducing alterations globally, including dredge and fill operations, hydrologic modifications, pollutants, impoundments, fragmentation by roads/ditches, and sea level rise. For wetland protection and sensible coastal development, there is a need to monitor these ecosystems at global and regional scales. Recent advances in satellite sensor design and data analysis are providing practical methods for monitoring natural and man-made changes in wetlands. However, available satellite remote sensors have been limited to mapping primarily wetland location and extent. This paper describes how the HyspIRI hyperspectral and thermal infrared sensors can be used to study and map key ecological properties, such as species composition, biomass, hydrology, and evapotranspiration of tidal salt and brackish marshes and mangroves, and perhaps other major wetland types, including freshwater marshes and wooded/shrub wetlands.

Published
2015
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9. An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-a based models

Author

Patricia A. Matrai, Timothy J Smyth, Bernard Gentili, Frédéric Mélin, Takahiko Kameda, Younjoo Lee, David Antoine, Ichio Asanuma, Toru Hirawake, Michele Scardi, Zhongping Lee, Mathieu Ardyna, Christian Katlein, Toby K. Westberry, Marjorie A. M. Friedrichs, Marcel Babin, Simon Bélanger, Sang Heon Lee, Kevin R. Turpie, Shilin Tang, Emmanuel Devred, Vincent S. Saba, Mar Fernández-Méndez, Kirk Waters, Sung-Ho Kang, Maxime Benoît‐Gagné, Bigelow Laboratory for Ocean Sciences, Virginia Institute of Marine Science (VIMS), Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Takuvik Joint International Laboratory ULAVAL-CNRS, Université Laval [Québec] (ULaval)-Centre National de la Recherche Scientifique (CNRS), Université du Québec à Rimouski (UQAR), Fisheries and Oceans Canada (DFO), Norwegian Polar Institute, Hokkaido University [Sapporo, Japan], KIOST, Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), European Commission - Joint Research Centre [Ispra] (JRC), Università degli Studi di Roma Tor Vergata [Roma], Plymouth Marine Laboratory (PML), Plymouth Marine Laboratory, NASA, Department of Botany and Plant Pathology, Oregon State University (OSU), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), and Université Laval [Québec] (ULaval)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0106 biological sciences, In situ, Chlorophyll a, 010504 meteorology & atmospheric sciences, Settore BIO/07, Arctic Ocean, model skill assessment, net primary productivity, ocean color model, remote sensing, subsurface chlorophyll‐a maximum, Oceanography, Atmospheric sciences, Biogeosciences, 01 natural sciences, Remote Sensing, chemistry.chemical_compound, Oceanography: Biological and Chemical, Forum for Arctic Modeling and Observational Synthesis (FAMOS): Results and Synthesis of Coordinated Experiments, Geochemistry and Petrology, Phytoplankton, Earth and Planetary Sciences (miscellaneous), 14. Life underwater, Arctic Region, Research Articles, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, 0105 earth and related environmental sciences, 010604 marine biology & hydrobiology, Arctic and Antarctic oceanography, Primary production, Model Verification and Validation, The arctic, Sea surface temperature, Oceanography: General, Geophysics, chemistry, 13. Climate action, Space and Planetary Science, Ocean color, Chlorophyll, Environmental science, Antarctica, Geographic Location, Computational Geophysics, Research Article
Abstract

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll‐a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed‐layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite‐derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low‐productivity seasons as well as in sea ice‐covered/deep‐water regions. Depth‐resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption‐based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll‐a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic‐relevant parameters., Key Points The models reproduced primary productivity better using in situ chlorophyll‐a than satellite valuesThe models performed well in low‐productivity seasons and in sea ice‐covered/deep‐water regionsNet primary productivity models need to be carefully tuned for the Arctic Ocean

Published
2015
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10. A comparison of global estimates of marine primary production from ocean color

Author

John P. Ryan, Steven E. Lohrenz, Richard T. Barber, Erik T. Buitenhuis, Nicolas Hoepffner, Maki Noguchi Aita, John P. Dunne, Michele Scardi, Heidi M. Dierssen, Áurea Maria Ciotti, David Antoine, André Morel, Ichio Asanuma, Kevin R. Turpie, Gavin H. Tilstone, Takahiko Kameda, Keith Moore, Olivier Aumont, Kirk Waters, Wayne E. Esaias, Steve Groom, Yasuhiro Yamanaka, Tasha E. Reddy, Corinne Le Quéré, Watson W. Gregg, Mary-Elena Carr, Michael J. Behrenfeld, John Marra, Mark Dowell, Frédéric Mélin, Timothy J Smyth, Bernard Gentili, Joji Ishizaka, Robert R. Bidigare, Kevin R. Arrigo, Marjorie A. M. Friedrichs, Janet W. Campbell, M. Schmeltz, Virginia Institute of Marine Science (VIMS), Laboratoire d'océanographie de Villefranche (LOV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Department of Geophysics [Stanford], Stanford EARTH, Stanford University-Stanford University, Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (LOCEAN), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP)-Institut de Recherche pour le Développement (IRD)-Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU), Oregon State University (OSU), Max-Planck-Institut für Biogeochemie (MPI-BGC), Ocean Process Analysis Laboratory (OPAL), University of New Hampshire (UNH), Universidade de São Paulo (USP), Department of Chemistry [York, UK], University of York [York, UK], Global Modeling and Assimilation Office (GMAO), NASA Goddard Space Flight Center (GSFC), Remote Sensing Group, Plymouth Marine Laboratory, Joint Research Centre of the European Commission, JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre [Ispra] (JRC), Monterey Bay Aquarium Research Institute (MBARI), Monterey Bay Aquarium Research Institute, Department of Biology, University of Roma, Plymouth Marine Laboratory (PML), Frontier Research Center for Global Change (FRCGC), Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), and Universidade de São Paulo = University of São Paulo (USP)

Subjects
0106 biological sciences, Chlorophyll, 010504 meteorology & atmospheric sciences, Perturbation techniques, Photosynthetically-available radiation (PAR), Oceanography, 01 natural sciences, General circulation models (GCM), chemistry.chemical_compound, sea surface temperature, satellite sensor, Photosynthesis, comparative study, Mathematical models, Radiation, Biosphere, Eutrophication, biogeochemical cycle, Ocean color, Correlation methods, Algorithms, primary production, Biogeochemical cycle, Settore BIO/07, Satellites, Parameterization, Ecosystems, Biogeochemical models, general circulation model, ocean color, Phytoplankton, Parameter estimation, Ecosystem, 14. Life underwater, Measurement theory, Southern Ocean, photosynthetically active radiation, [SDU.STU.OC]Sciences of the Universe [physics]/Earth Sciences/Oceanography, Sea-surface temperature (SST), chlorophyll, environmental conditions, 0105 earth and related environmental sciences, 010604 marine biology & hydrobiology, chemistry, 13. Climate action, Environmental science
Abstract

International audience; 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.

Published
2006
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