The Ocean Version of the Lagrangian Analysis Tool LAGRANTO

The Ocean Version of the Lagrangian Analysis Tool LAGRANTO AbstractThe Lagrangian Analysis Tool (LAGRANTO) is adopted and applied to ECMWF’s latest ocean reanalysis. The primary motivation behind this study is to introduce and document LAGRANTO Ocean (LAGRANTO.ocean) and explore its capabilities in combination with an eddy-permitting ocean reanalysis. The tool allows for flexibly defining starting points, within circles, cylinders, or any user-defined region or volume. LAGRANTO.ocean also offers a sophisticated way to refine a set of computed trajectories according to a wide range of mathematical operations that can be combined into a single refinement criterion. Tools for calculating—for example, along-trajectory cross sections or trajectory densities—are further provided. After introducing the tool, three case studies are presented, which were chosen to reflect a selection of phenomena on different spatial and temporal scales. The case studies also serve as hands-on examples. For the first case study, at the mesoscale, ocean trajectories are computed during the formation of a Gulf Stream cold-core ring to study vertical motion in the developing eddy. In the second example, source waters are traced to the East Greenland Spill Jet. This example highlights the usefulness of a Lagrangian method for identifying sources or sinks of buoyancy. The third example, on annual time scales, focuses on the temporal evolution of extreme potential temperature anomalies in the South Pacific and the memory of the involved water parcels. Near-surface trajectories reveal that it takes approximately 5 months after the highest temperature anomaly before the involved water parcels cool to their climatological mean values at their new positions. LAGRANTO.ocean will be made publicly available. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Atmospheric and Oceanic Technology American Meteorological Society

The Ocean Version of the Lagrangian Analysis Tool LAGRANTO

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Publisher
American Meteorological Society
Copyright
Copyright © American Meteorological Society
ISSN
1520-0426
eISSN
1520-0426
D.O.I.
10.1175/JTECH-D-16-0198.1
Publisher site
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Abstract

AbstractThe Lagrangian Analysis Tool (LAGRANTO) is adopted and applied to ECMWF’s latest ocean reanalysis. The primary motivation behind this study is to introduce and document LAGRANTO Ocean (LAGRANTO.ocean) and explore its capabilities in combination with an eddy-permitting ocean reanalysis. The tool allows for flexibly defining starting points, within circles, cylinders, or any user-defined region or volume. LAGRANTO.ocean also offers a sophisticated way to refine a set of computed trajectories according to a wide range of mathematical operations that can be combined into a single refinement criterion. Tools for calculating—for example, along-trajectory cross sections or trajectory densities—are further provided. After introducing the tool, three case studies are presented, which were chosen to reflect a selection of phenomena on different spatial and temporal scales. The case studies also serve as hands-on examples. For the first case study, at the mesoscale, ocean trajectories are computed during the formation of a Gulf Stream cold-core ring to study vertical motion in the developing eddy. In the second example, source waters are traced to the East Greenland Spill Jet. This example highlights the usefulness of a Lagrangian method for identifying sources or sinks of buoyancy. The third example, on annual time scales, focuses on the temporal evolution of extreme potential temperature anomalies in the South Pacific and the memory of the involved water parcels. Near-surface trajectories reveal that it takes approximately 5 months after the highest temperature anomaly before the involved water parcels cool to their climatological mean values at their new positions. LAGRANTO.ocean will be made publicly available.

Journal

Journal of Atmospheric and Oceanic Technology – American Meteorological Society

Published: Aug 12, 2017

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