Name: Hybrid Coordinate Ocean Model (HYCOM) EnOI Version 1.1 Raw (L3R) Regional Agulhas 10km Ocean State Estimate 2009
License: https://creativecommons.org/licenses/by-sa/4.0/

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Title	Hybrid Coordinate Ocean Model (HYCOM) EnOI Version 1.1 Raw (L3R) Regional Agulhas 10km Ocean State Estimate 2009
Project	Hybrid Coordinate Ocean Model (HYCOM)
Authors	Björn C Backeberg Council for Scientific and Industrial Research Principal Researcher Meiring Naudé Road, Brummeria, Pretoria, South Africa, BBackeberg@csir.co.za Johnny A Johannessen Nansen Environmental and Remote Sensing Center Associate Researcher Nansen-Tutu Centre for Marine Environmental Research, Department of Oceanography, Mare Institute, University of Cape Town, Rondebosch, Cape Town, South Africa
Publisher	Department of Forestry, Fisheries and the Environment (2016)
Contributors	Contact Person: François Counillon Nansen Environmental and Remote Sensing Center Associate Researcher Nansen-Tutu Centre for Marine Environmental Research, Department of Oceanography, Mare Institute, University of Cape Town, Rondebosch, Cape Town, South Africa, email: francois.counillon@nersc.no
Abstract	The greater Agulhas Current is one of the most energetic current systems in the global ocean. It plays a fundamental role in determining the mean state and variability of the regional marine environment, affecting its resources and ecosystem, the regional weather and the global climate on a broad range of temporal and spatial scales. In the absence of a coherent in-situ and satellite-based observing system in region, modelling and data assimilation techniques play a crucial role in both furthering and quantitative understanding and proving better forecasts of this complicated western boundary current system.
Methods	In this study, we use a regional implementation of the Hybrid Coordinate Ocean Model and assimilate along-track satellite sea level anomaly (SLA) data using the Ensemble Optimal Interpolation (EnOI) data assimilation scheme. This study lays the foundation towards the development of a regional prediction system for the greater Agulhas Current system. Comparisons to independent in-situ drifter observations show that data assimilation reduces the error compared to a free model run over a 2-year period. Mesoscale features are placed in more consistent agreement with the drifter trajectories and surface velocity errors are reduced. While the model-based forecasts of surface velocities are not as accurate as persistence forecasts derived from satellite altimeter observations, the error calculated from the drifter measurements for eddy kinetic energy is significantly lower in the assimilation system compares to the persistence forecast. While the assimilation of along-track SLA data introduces a small bias in sea surface temperatures, the representation of water mass properties and deep current velocities in the Agulhas system is improved.
Data	Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) Terms of use These data are made available with the express understanding that any such use will properly acknowledge the originator(s) and publisher and cite the accession numbers and/or associated Digital Object Identifiers. Anyone wishing to use these data should properly cite and attribute the data providers listed as authors in the metadata provided with each dataset. It is expected that all the conditions of the data license will be strictly honoured. Use of any material herein should be properly cited using the dataset’s persistent identifiers such as accession numbers and DOIs. I agree to the terms of use
Temporal extent	01 Jan 2008 – 29 Dec 2009
Geographic extent	Southeast Atlantic Ocean, Southwest Indian Ocean North: -5.0166807 South: -51.2278557 West: -2.2567065 East: 68.8293762
Keywords	Agulhas Current, Hybrid Coordinate Ocean Model, HYCOM, Ocean Prediction, Ocean Reanalysis

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