Imperial College London
Alternate

ProfessorRalfToumi

Faculty of Natural Sciences, The Grantham Institute for Climate Change

Co-Director, Grantham Institute - Climate Change&Environment
 
 
 
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Contact

 

+44 (0)20 7594 7668r.toumi Website CV

 
 
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Location

 

713Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Phillipson:2017:10.1016/j.ocemod.2017.04.006,
author = {Phillipson, L and Toumi, R},
doi = {10.1016/j.ocemod.2017.04.006},
journal = {OCEAN MODELLING},
pages = {45--58},
title = {Impact of data assimilation on ocean current forecasts in the Angola Basin},
url = {http://dx.doi.org/10.1016/j.ocemod.2017.04.006},
volume = {114},
year = {2017}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The ocean current predictability in the data limited Angola Basin was investigated using the Regional Ocean Modelling System (ROMS) with four-dimensional variational data assimilation. Six experiments were undertaken comprising a baseline case of the assimilation of salinity/temperature profiles and satellite sea surface temperature, with the subsequent addition of altimetry, OSCAR (satellite-derived sea surface currents), drifters, altimetry and drifters combined, and OSCAR and drifters combined. The addition of drifters significantly improves Lagrangian predictability in comparison to the baseline case as well as the addition of either altimetry or OSCAR. OSCAR assimilation only improves Lagrangian predictability as much as altimetry assimilation. On average the assimilation of either altimetry or OSCAR with drifter velocities does not significantly improve Lagrangian predictability compared to the drifter assimilation alone, even degrading predictability in some cases. When the forecast current speed is large, it is more likely that the combination improves trajectory forecasts. Conversely, when the currents are weaker, it is more likely that the combination degrades the trajectory forecast.
AU  - Phillipson,L
AU  - Toumi,R
DO  - 10.1016/j.ocemod.2017.04.006
EP  - 58
PY  - 2017///
SN  - 1463-5003
SP  - 45
TI  - Impact of data assimilation on ocean current forecasts in the Angola Basin
T2  - OCEAN MODELLING
UR  - http://dx.doi.org/10.1016/j.ocemod.2017.04.006
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000403731800004&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/49895
VL  - 114
ER  -
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