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  • 1
    Publication Date: 2022-05-25
    Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 5439–5460, doi:10.1002/jgrc.20369.
    Description: Underway and in situ observations of surface ocean pCO2, combined with satellite data, were used to develop pCO2 regional algorithms to analyze the seasonal and interannual variability of surface ocean pCO2 and sea-air CO2 flux for five physically and biologically distinct regions of the eastern North American continental shelf: the South Atlantic Bight (SAB), the Mid-Atlantic Bight (MAB), the Gulf of Maine (GoM), Nantucket Shoals and Georges Bank (NS+GB), and the Scotian Shelf (SS). Temperature and dissolved inorganic carbon variability are the most influential factors driving the seasonality of pCO2. Estimates of the sea-air CO2 flux were derived from the available pCO2 data, as well as from the pCO2 reconstructed by the algorithm. Two different gas exchange parameterizations were used. The SS, GB+NS, MAB, and SAB regions are net sinks of atmospheric CO2 while the GoM is a weak source. The estimates vary depending on the use of surface ocean pCO2 from the data or algorithm, as well as with the use of the two different gas exchange parameterizations. Most of the regional estimates are in general agreement with previous studies when the range of uncertainty and interannual variability are taken into account. According to the algorithm, the average annual uptake of atmospheric CO2 by eastern North American continental shelf waters is found to be between −3.4 and −5.4 Tg C yr−1 (areal average of −0.7 to −1.0 mol CO2 m−2 yr−1) over the period 2003–2010.
    Description: We wish to acknowledge the NASA Ocean Biology and Biogeochemistry program for providing funds for this project.
    Keywords: Coastal carbon ; Sea-air CO2 fluxes ; North American east coast
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2010. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 24 (2010): GB3020, doi:10.1029/2009GB003655.
    Description: The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.
    Description: This research was supported by a grant from the National Aeronautics and Space Agency Ocean Biology and Biogeochemistry program (NNG06GA03G).
    Keywords: Marine primary productivity models ; BATS HOT trends ; Multidecadal climate forcing
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2012. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 117 (2012): G03019, doi:10.1029/2011JG001830.
    Description: The upper ocean primary production measurements from the Hawaii Ocean Time series (HOT) at Station ALOHA in the North Pacific Subtropical Gyre showed substantial variability over the last two decades. The annual average primary production varied within a limited range over 1991–1998, significantly increased in 1999–2000 and then gradually decreased afterwards. This variability was investigated using a one-dimensional ecosystem model. The long-term HOT observations were used to constrain the model by prescribing physical forcings and lower boundary conditions and optimizing the model parameters against data using data assimilation. The model reproduced the general interannual pattern in the observed primary production, and mesoscale variability in vertical velocity was identified as a major contributing factor to the interannual variability in the simulation. Several strong upwelling events occurred in 1999, which brought up nitrate at rates several times higher than other years and elevated the model primary production. Our model results suggested a hypothesis for the observed interannual variability pattern of primary production at Station ALOHA: Part of the upwelled nitrate input in 1999 was converted to and accumulated as semilabile dissolved organic nitrogen (DON), and subsequent recycling of this semilabile DON supported enhanced primary productivity for the next several years as the semilabile DON perturbation was gradually removed via export.
    Description: This work was supported in part by the Center for Microbial Oceanography, Research and Education (C-MORE) (NSF EF-0424599), Hawaii Ocean Time series program (NSF OCE09–26766), the Gordon and Betty Moore Foundation, and the Marine Biological Laboratory.
    Description: 2013-03-10
    Keywords: Mesoscale activity ; North Pacific Subtropical Gyre ; Dissolved organic nitrogen ; Interannual variability ; Primary production
    Repository Name: Woods Hole Open Access Server
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  • 4
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2013. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 6319–6328, doi:10.1002/2013JC008939.
    Description: Strong and strategic collaborations among experts from academia, federal operational centers, and industry have been forged to create a U.S. IOOS Coastal and Ocean Modeling Testbed (COMT). The COMT mission is to accelerate the transition of scientific and technical advances from the coastal and ocean modeling research community to improved operational ocean products and services. This is achieved via the evaluation of existing technology or the development of new technology depending on the status of technology within the research community. The initial phase of the COMT has addressed three coastal and ocean prediction challenges of great societal importance: estuarine hypoxia, shelf hypoxia, and coastal inundation. A fourth effort concentrated on providing and refining the cyberinfrastructure and cyber tools to support the modeling work and to advance interoperability and community access to the COMT archive. This paper presents an overview of the initiation of the COMT, the findings of each team and a discussion of the role of the COMT in research to operations and its interface with the coastal and ocean modeling community in general. Detailed technical results are presented in the accompanying series of 16 technical papers in this special issue.
    Description: This project was supported by NOAA via the IOOS Office, award NA10NOS0120063 and NA11NOS0120141, and used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant OCI- 1053575.
    Keywords: Modeling ; Hypoxia ; Inundation ; Waves
    Repository Name: Woods Hole Open Access Server
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  • 5
    Publication Date: 2022-05-25
    Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Geophysical Research: Oceans 118 (2013): 4924–4944, doi:10.1002/jgrc.20331.
    Description: The overall size of the “dead zone” within the main stem of the Chesapeake Bay and its tidal tributaries is quantified by the hypoxic volume (HV), the volume of water with dissolved oxygen (DO) less than 2 mg/L. To improve estimates of HV, DO was subsampled from the output of 3-D model hindcasts at times/locations matching the set of 2004–2005 stations monitored by the Chesapeake Bay Program. The resulting station profiles were interpolated to produce bay-wide estimates of HV in a manner consistent with nonsynoptic, cruise-based estimates. Interpolations of the same stations sampled synoptically, as well as multiple other combinations of station profiles, were examined in order to quantify uncertainties associated with interpolating HV from observed profiles. The potential uncertainty in summer HV estimates resulting from profiles being collected over 2 weeks rather than synoptically averaged ∼5 km3. This is larger than that due to sampling at discrete stations and interpolating/extrapolating to the entire Chesapeake Bay (2.4 km3). As a result, sampling fewer, selected stations over a shorter time period is likely to reduce uncertainties associated with interpolating HV from observed profiles. A function was derived that when applied to a subset of 13 stations, significantly improved estimates of HV. Finally, multiple metrics for quantifying bay-wide hypoxia were examined, and cumulative hypoxic volume was determined to be particularly useful, as a result of its insensitivity to temporal errors and climate change. A final product of this analysis is a nearly three-decade time series of improved estimates of HV for Chesapeake Bay.
    Description: Funding for this study was provided by the IOOS COMT Program through NOAA grants NA10NOS0120063 and NA11NOS0120141. Additional funding was provided by NSF grant OCE-1061564.
    Keywords: Hypoxia ; Hypoxic volume ; Chesapeake Bay ; Dead zone ; Water quality ; Dissolved oxygen
    Repository Name: Woods Hole Open Access Server
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  • 6
    Publication Date: 2022-05-26
    Description: Author Posting. © Inter-Research, 2010. This article is posted here by permission of Inter-Research for personal use, not for redistribution. The definitive version was published in Aquatic Microbial Ecology 60 (2010): 273-287, doi:10.3354/ame01427.
    Description: Previous studies have focused on the role of labile dissolved organic matter (DOM) (defined as turnover time of ~1 d) in supporting heterotrophic bacterial production, but have mostly neglected semilabile DOM (defined as turnover time of ~100 to 1000 d) as a potential substrate for heterotrophic bacterial growth. To test the hypothesis that semilabile DOM supports substantial amounts of heterotrophic bacterial production in the open ocean, we constructed a 1-dimensional epipelagic ecosystem model and applied it to 3 open ocean sites: the Arabian Sea, Equatorial Pacific and Station ALOHA in the North Pacific Subtropical Gyre. The model tracks carbon, nitrogen and phosphorus with flexible stoichiometry. This study used a large number of observations, including measurements of heterotrophic bacterial production rates and standing stocks, and DOM concentration data, to rigorously test and constrain model output. Data assimilation was successfully applied to optimize the model parameters and resulted in simultaneous representation of observed nitrate, phosphate, phytoplankton and zooplankton biomass, primary production, heterotrophic bacterial biomass and production, DOM, and suspended and sinking particulate organic matter. Across the 3 ocean ecosystems examined, the data assimilation suggests semilabile DOM may support 17 to 40% of heterotrophic bacterial carbon demand. In an experiment where bacteria only utilize labile DOM, and with more of the DOM production assigned to labile DOM, the model poorly represented the observations. These results suggest that semilabile DOM may play an important role in sustaining heterotrophic bacterial growth in diverse regions of the open ocean.
    Description: Y.W.L. was supported by fellowships from the Virginia Institute of Marine Sciences and Marine Biological Laboratory as well as NSF Grants OPP-0217282 and 0823101 to H.W.D. and VIMS and MBL, respectively. M.A.M.F.’s participation was supported in part by a grant from the NASA Ocean Biology and Biogeochemistry program (NNX07AF70G), S.C.D.’s participation was supported by an NSF grant to the Center for Microbial Oceanography, Research and Education (CMORE), NSF EF-0424599, and M.J.C. was supported in part by NSF grants EF-0424599 (C-MORE) and OCE 0425363.
    Keywords: Heterotrophic bacteria ; Semilabile dissolved organic matter ; Marine ecosystem model ; Data assimilation
    Repository Name: Woods Hole Open Access Server
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  • 7
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C08001, doi:10.1029/2006JC003852.
    Description: Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.
    Description: This research was supported by the U.S. National Science Foundation through the JGOFS Synthesis and Modeling Project (OCE-0097285) and the National Aeronautics and Space Agency (NAG5-11259 and NNG05GO04G), as well as numerous other grants to the various investigators who participated.
    Keywords: Ecosystem model comparison ; Biogeochemical data assimilation ; Phytoplankton functional groups
    Repository Name: Woods Hole Open Access Server
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