ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Greenhouse gases  (2)
  • Sea level  (2)
  • American Geophysical Union  (4)
  • Blackwell Publishing Ltd
  • Wiley
  • 2020-2023  (4)
  • 1985-1989
  • 1980-1984
  • 1970-1974
Collection
Keywords
Publisher
Years
Year
  • 1
    facet.materialart.
    Unknown
    Understanding of contemporary regional sea-level change and the implications for the future (2020)
    American Geophysical Union
    Details
    Publication Date: 2022-10-26
    Description: Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Reviews of Geophysics 58(3), (2020): e2019RG000672, doi:10.1029/2019RG000672.
    Description: Global sea level provides an important indicator of the state of the warming climate, but changes in regional sea level are most relevant for coastal communities around the world. With improvements to the sea‐level observing system, the knowledge of regional sea‐level change has advanced dramatically in recent years. Satellite measurements coupled with in situ observations have allowed for comprehensive study and improved understanding of the diverse set of drivers that lead to variations in sea level in space and time. Despite the advances, gaps in the understanding of contemporary sea‐level change remain and inhibit the ability to predict how the relevant processes may lead to future change. These gaps arise in part due to the complexity of the linkages between the drivers of sea‐level change. Here we review the individual processes which lead to sea‐level change and then describe how they combine and vary regionally. The intent of the paper is to provide an overview of the current state of understanding of the processes that cause regional sea‐level change and to identify and discuss limitations and uncertainty in our understanding of these processes. Areas where the lack of understanding or gaps in knowledge inhibit the ability to provide the needed information for comprehensive planning efforts are of particular focus. Finally, a goal of this paper is to highlight the role of the expanded sea‐level observation network—particularly as related to satellite observations—in the improved scientific understanding of the contributors to regional sea‐level change.
    Description: The research was carried out in part at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The authors acknowledge support from the National Aeronautics and Space Administration under Grants 80NSSC17K0565, 80NSSC170567, 80NSSC17K0566, 80NSSC17K0564, and NNX17AB27G. A. A. acknowledges support under GRACE/GRACEFO Science Team Grant (NNH15ZDA001N‐GRACE). T. W. acknowledges support by the National Aeronautics and Space Administration (NASA) under the New (Early Career) Investigator Program in Earth Science (Grant: 80NSSC18K0743). C. G. P was supported by the J. Lamar Worzel Assistant Scientist Fund and the Penzance Endowed Fund in Support of Assistant Scientists at the Woods Hole Oceanographic Institution.
    Keywords: Sea level ; Satellite observations ; Remote sensing
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OA)
  • 2
    facet.materialart.
    Unknown
    The relationship between U.S. East Coast sea level and the Atlantic Meridional Overturning Circulation: a review (2020)
    American Geophysical Union
    Details
    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 Little, C. M., Hu, A., Hughes, C. W., McCarthy, G. D., Piecuch, C. G., Ponte, R. M., & Thomas, M. D. The relationship between U.S. East Coast sea level and the Atlantic Meridional Overturning Circulation: a review. Journal of Geophysical Research-Oceans, 124(9), (2019): 6435-6458, doi:10.1029/2019JC015152.
    Description: Scientific and societal interest in the relationship between the Atlantic Meridional Overturning Circulation (AMOC) and U.S. East Coast sea level has intensified over the past decade, largely due to (1) projected, and potentially ongoing, enhancement of sea level rise associated with AMOC weakening and (2) the potential for observations of U.S. East Coast sea level to inform reconstructions of North Atlantic circulation and climate. These implications have inspired a wealth of model‐ and observation‐based analyses. Here, we review this research, finding consistent support in numerical models for an antiphase relationship between AMOC strength and dynamic sea level. However, simulations exhibit substantial along‐coast and intermodel differences in the amplitude of AMOC‐associated dynamic sea level variability. Observational analyses focusing on shorter (generally less than decadal) timescales show robust relationships between some components of the North Atlantic large‐scale circulation and coastal sea level variability, but the causal relationships between different observational metrics, AMOC, and sea level are often unclear. We highlight the importance of existing and future research seeking to understand relationships between AMOC and its component currents, the role of ageostrophic processes near the coast, and the interplay of local and remote forcing. Such research will help reconcile the results of different numerical simulations with each other and with observations, inform the physical origins of covariability, and reveal the sensitivity of scaling relationships to forcing, timescale, and model representation. This information will, in turn, provide a more complete characterization of uncertainty in relevant relationships, leading to more robust reconstructions and projections.
    Description: The authors acknowledge funding support from NSF Grant OCE‐1805029 (C. M. L.) and NASA Contract NNH16CT01C (C. M. L. and R. M. P.), the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy's Office of Biological & Environmental Research Cooperative Agreement DE‐FC02‐97ER62402 (A. H.), Natural Environment Research Council NE/K012789/1 (C. W. H.), Irish Marine Institute Project A4 PBA/CC/18/01 (G. D. M.), and NSF Awards OCE‐1558966 and OCE‐1834739 (C. G. P.). The National Center for Atmospheric Research is sponsored by National Science Foundation. The authors thank the two reviewers for their comments, and CLIVAR and the U.S. AMOC Science Team for inspiration and patience. All CMIP5 data used in Figures 4-6 are available at http://pcmdi9.llnl.gov/ website; the AMOC strength fields were digitized from Chen et al. (2018, supporting information Figure S3).
    Keywords: Sea level ; AMOC ; United States ; Coastal ; Climate model ; Review
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OA)
  • 3
    facet.materialart.
    Unknown
    River Inflow Dominates Methane Emissions in an Arctic Coastal System (2020)
    American Geophysical Union
    Details
    Publication Date: 2022-10-20
    Description: Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geophysical Research Letters 47 (2020): e2020GL087669, doi:10.1029/2020GL087669.
    Description: We present a year‐round time series of dissolved methane (CH4), along with targeted observations during ice melt of CH4 and carbon dioxide (CO2) in a river and estuary adjacent to Cambridge Bay, Nunavut, Canada. During the freshet, CH4 concentrations in the river and ice‐covered estuary were up to 240,000% saturation and 19,000% saturation, respectively, but quickly dropped by 〉100‐fold following ice melt. Observations with a robotic kayak revealed that river‐derived CH4 and CO2 were transported to the estuary and rapidly ventilated to the atmosphere once ice cover retreated. We estimate that river discharge accounts for 〉95% of annual CH4 sea‐to‐air emissions from the estuary. These results demonstrate the importance of resolving seasonal dynamics in order to estimate greenhouse gas emissions from polar systems.
    Description: All data generated by the authors that were used in this article are available on PANGAEA (https://doi.org/10.1594/PANGAEA.907159) and model code for estimating CH4 transport is available on GitHub (https://doi.org/10.5281/zenodo.3785893). We acknowledge the use of imagery from the NASA Worldview application (https://worldview.earthdata.nasa.gov), part of the NASA Earth Observing System Data and Information System (EOSDIS), and data from Ocean Networks Canada, and Environment Canada. We thank everyone involved in the fieldwork including C. Amegainik, Y. Bernard, A. Cranch, F. Emingak, S. Marriott, and A. Pedersen. Laboratory analysis and experiments were performed by A. Cranch, R. McCulloch, A. Morrison, and Z. Zheng. We thank J. Brinckerhoff, the Arctic Research Foundation, and the staff of the Canadian High Arctic Research Station for support with field logistics. Funding for the work was provided by MEOPAR NCE funding to B. Else, a WHOI Interdisciplinary Award to A. Michel., D. Nicholson. and S. Wankel, and Canadian NSERC grants to P. Tortell. and B. Else. Authors received fellowships, scholarships, and travel grants including an NSERC postdoctoral fellowship to C. Manning, an NDSEG fellowship to V. Preston, NSERC PGS‐D and Izaak Walton Killam Pre‐Doctoral scholarships to S. Jones, and Northern Scientific Training Program funds (Polar Knowledge Canada, administered by the Arctic Institute of North America, University of Calgary) to S. Jones and P. Duke. We also thank Polar Knowledge Canada (POLAR) and Nunavut Arctic College for laboratory space and field logistics support.
    Description: 2020-10-23
    Keywords: Greenhouse gases ; Biogeochemistry ; Arctic coastal waters ; Biogeochemical sensing ; Seasonal cycles ; Methane
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OA)
  • 4
    facet.materialart.
    Unknown
    A geostatistical framework for quantifying the imprint of mesoscale atmospheric transport on satellite trace gas retrievals (2020)
    American Geophysical Union
    Details
    Publication Date: 2022-10-26
    Description: Author Posting. © American Geophysical Union, 2019. 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-Atmospheres 124 (17-18), (2019): 9773-9795, doi: 10.1029/2018JD029933.
    Description: National Aeronautics and Space Administration's Orbiting Carbon Observatory‐2 (OCO‐2) satellite provides observations of total column‐averaged CO2 mole fractions (XCO2 ) at high spatial resolution that may enable novel constraints on surface‐atmosphere carbon fluxes. Atmospheric inverse modeling provides an approach to optimize surface fluxes at regional scales, but the accuracy of the fluxes from inversion frameworks depends on key inputs, including spatially and temporally dense CO2 observations and reliable representations of atmospheric transport. Since XCO2 observations are sensitive to both synoptic and mesoscale variations within the free troposphere, horizontal atmospheric transport imparts substantial variations in these data and must be either resolved explicitly by the atmospheric transport model or accounted for within the error covariance budget provided to inverse frameworks. Here, we used geostatistical techniques to quantify the imprint of atmospheric transport in along‐track OCO‐2 soundings. We compare high‐pass‐filtered (〈250 km, spatial scales that primarily isolate mesoscale or finer‐scale variations) along‐track spatial variability in XCO2 and XH2O from OCO‐2 tracks to temporal synoptic and mesoscale variability from ground‐based XCO2 and XH2O observed by nearby Total Carbon Column Observing Network sites. Mesoscale atmospheric transport is found to be the primary driver of along‐track, high‐frequency variability for OCO‐2 XH2O. For XCO2 , both mesoscale transport variability and spatially coherent bias associated with other elements of the OCO‐2 retrieval state vector are important drivers of the along‐track variance budget.
    Description: The authors thank the leadership and participants of the NASA OCO‐2 mission and acknowledge financial support from NASA Award NNX15AH13G. A.D. Torres also acknowledges support from the NASA Earth and Space Science Fellowship Award 80NSSC17K0382. We thank TCCON for providing observations. We thank A. Jacobson and the National Oceanographic and Atmospheric Administration Earth System Research Laboratory in Boulder, CO, for providing CarbonTracker CT2017 data, available online (http://carbontracker.noaa.gov). We thank S. Wofsy for providing HIPPO data, funded by the National Science Foundation and NOAA and available online (https://www.eol.ucar.edu/field_projects/hippo). The TCCON Principal Investigators acknowledge funding from their national funding organizations. TCCON data were obtained from the archive at the https://tccondata.org Web site. NARR data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site (https://www.esrl.noaa.gov/psd/).
    Keywords: Atmospheric transport ; Greenhouse gases ; CO2 ; Mesoscale ; OCO‐2 ; TCCON
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
    PAPER (OA)
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...