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  • 1
    Publication Date: 2022-05-25
    Description: 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.
    Description: 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.
    Description: 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 investigators
    Keywords: Primary production ; Modeling ; Remote sensing ; Satellite ocean color ; Statistical analysis ; Tropical Pacific Ocean (15°N to 15°S and 125°E to 95°W)
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
    Format: application/pdf
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  • 2
    Publication Date: 2022-05-25
    Description: 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): 95-112, doi:10.1016/j.jmarsys.2008.05.015.
    Description: We present a generalized framework for assessing the skill of global upper ocean ecosystem-biogeochemical models against in-situ field data and satellite observations. We illustrate the approach utilizing a multi-decade (1979-2004) hindcast experiment conducted with the Community Climate System Model (CCSM-3) ocean carbon model. The CCSM-3 ocean carbon model incorporates a multi-nutrient, multi-phytoplankton functional group ecosystem module coupled with a carbon, oxygen, nitrogen, phosphorus, silicon, and iron biogeochemistry module embedded in a global, threedimensional ocean general circulation model. The model is forced with physical climate forcing from atmospheric reanalysis and satellite data products and time-varying atmospheric dust deposition. Data-based skill metrics are used to evaluate the simulated time-mean spatial patterns, seasonal cycle amplitude and phase, and subannual to interannual variability. Evaluation data include: sea surface temperature and mixed layer depth; satellite derived surface ocean chlorophyll, primary productivity, phytoplankton growth rate and carbon biomass; large-scale climatologies of surface nutrients, pCO2, and air-sea CO2 and O2 flux; and time-series data from the Joint Global Ocean Flux Study (JGOFS). Where the data is sufficient, we construct quantitative skill metrics using: model-data residuals, time-space correlation, root mean square error, and Taylor diagrams.
    Description: This work was supported in part by grants from the NSF/ONR National Ocean Partnership Program (N000140210370), the NASA Ocean Biology and Biogeochemistry Program (NNX07AL80G), and the NSF Center for Microbial Oceanography Research and Education (C-MORE).
    Keywords: Marine ecology ; Biogeochemistry ; Modeling ; Evaluation ; Skill
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 3
    Publication Date: 2022-10-26
    Description: © The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Licker, R.; Ekwurzel, B.; Doney, S. C.; Cooley, S. R.; Lima, I. D.; Heede, R.; Frumhoff, P. C. Attributing ocean acidification to major carbon producers. Environmental Research Letters. 14(12), (2019): 124060, doi:10.1088/1748-9326/ab5abc.
    Description: Recent research has quantified the contributions of CO2 and CH4 emissions traced to the products of major fossil fuel companies and cement manufacturers to global atmospheric CO2, surface temperature, and sea level rise. This work has informed societal considerations of the climate responsibilities of these major industrial carbon producers. Here, we extend this work to historical (1880–2015) and recent (1965–2015) acidification of the world's ocean. Using an energy balance carbon-cycle model, we find that emissions traced to the 88 largest industrial carbon producers from 1880–2015 and 1965–2015 have contributed ~55% and ~51%, respectively, of the historical 1880–2015 decline in surface ocean pH. As ocean acidification is not spatially uniform, we employ a three-dimensional ocean model and identify five marine regions with large declines in surface water pH and aragonite saturation state over similar historical (average 1850–1859 to average 2000–2009) and recent (average 1960–1969 to average of 2000–2009) time periods. We characterize the biological and socioeconomic systems in these regions facing loss and damage from ocean acidification in the context of climate change and other stressors. Such analysis can inform societal consideration of carbon producer responsibility for current and near-term risks of further loss and damage to human communities dependent on marine ecosystems and fisheries vulnerable to ocean acidification.
    Description: The approach of using equation (1) benefited from discussions with Myles R Allen (University of Oxford) and Inez Fung (University of California, Berkeley). M W Dalton provided insights for the incorporation of the updated carbon producers data. Chloe Ames provided support for references. S Doney acknowledges support from the US National Science Foundation and the University of Virginia Environmental Resilience Institute. R Licker, B Ekwurzel and P C Frumhoff acknowledge the support of the Grantham Foundation for the Protection of the Environment, Wallace Global Fund, and Rockefeller Family Fund to the Union of Concerned Scientists. R Heede gratefully acknowledges the financial support of Wallace Global Fund, Rockefeller Brothers Fund, and Union of Concerned Scientists. We thank two anonymous reviewers for their helpful comments, which greatly improved our manuscript.
    Keywords: Ocean acidification ; Carbon producers ; Attribution ; Climate impacts ; Fossil fuels
    Repository Name: Woods Hole Open Access Server
    Type: Article
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