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  • 1
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    Massachusetts Institute of Technology and Woods Hole Oceanographic Institution
    Publication Date: 2022-05-25
    Description: Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 2008
    Description: Coupled ocean/atmosphere simulations exhibit systematicwarm biases over the SouthWest African (SWA) coastal region. Recent investigations indicate that coastal ocean dynamics may play an important role in determining the SST patterns, but none of them provide a detailed analysis. In this study, I analyze simulations produced both by coupled models and by idealized models. Then results are interpreted on the basis of a theoretical framework. Finally the conclusion is reached that the insufficient resolution of the ocean component in the coupled model is responsible for the warm biases over the SWA coastal region. The coarse resolution used in the ocean model has an artificially stretched coastal side-wall boundary layer, which induces a smaller upwelling velocity in the boundary layer. The vertical heat transport decreases even when the volume transport is unchanged because of its nonlinear relationship with the magnitude of the upwelling velocity. Based on the scaling of the idealized model simulations, a simplified calculation shows that the vertical heat transport is inversely proportional to the zonal resolution over the coastal region. Therefore, increasing the horizontal resolution can considerably improve the coastal SST simulation, and better resolve the coastal dynamics.
    Keywords: Ocean-atmosphere interaction ; Computer simulation
    Repository Name: Woods Hole Open Access Server
    Type: Thesis
    Format: application/pdf
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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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