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  • 1
    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
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  • 2
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ocean Modelling 121 (2018): 49-75, doi:10.1016/j.ocemod.2017.11.008.
    Description: Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing.
    Description: EvS has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No 715386). This research for PJW was supported as part of the Energy Exascale Earth System Model (E3SM) project, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. Funding for HFD was provided by Grant No. DE-SC0012457 from the US Department of Energy. PB acknowledges support for this work from NERC grant NE/R011567/1. SFG is supported by NERC National Capability funding through the Extended Ellett Line Programme.
    Keywords: Ocean circulation ; Lagrangian analysis ; Connectivity ; Particle tracking ; Future modelling
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 3
    Publication Date: 2021-02-08
    Description: Highlights: • Lagrangian ocean analysis is a powerful way to analyse the output of ocean circulation models • We present a review of the Kinematic framework, available tools, and applications of Lagrangian ocean analysis • While there are unresolved questions, the framework is robust enough to be used widely in ocean modelling Abstract: Lagrangian analysis is a powerful way to analyse the output of ocean circulation models and other ocean velocity data such as from altimetry. In the Lagrangian approach, large sets of virtual particles are integrated within the three-dimensional, time-evolving velocity fields. Over several decades, a variety of tools and methods for this purpose have emerged. Here, we review the state of the art in the field of Lagrangian analysis of ocean velocity data, starting from a fundamental kinematic framework and with a focus on large-scale open ocean applications. Beyond the use of explicit velocity fields, we consider the influence of unresolved physics and dynamics on particle trajectories. We comprehensively list and discuss the tools currently available for tracking virtual particles. We then showcase some of the innovative applications of trajectory data, and conclude with some open questions and an outlook. The overall goal of this review paper is to reconcile some of the different techniques and methods in Lagrangian ocean analysis, while recognising the rich diversity of codes that have and continue to emerge, and the challenges of the coming age of petascale computing.
    Type: Article , PeerReviewed
    Format: text
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