eCite Digital Repository

Assessing the impact of observations on ocean forecasts and reanalyses: Part 1, Global studies


Oke, PR and Larnicol, G and Fujii, Y and Smith, GC and Lea, DJ and Guinehut, S and Remy, E and Balmaseda, MA and Rykova, T and Surcel-Colan, D and Martin, MJ and Sellar, AA and Mulet, S and Turpin, V, Assessing the impact of observations on ocean forecasts and reanalyses: Part 1, Global studies, Journal of Operational Oceanography, 8, (S1) pp. S49-S62. ISSN 1755-876X (2015) [Refereed Article]


Copyright Statement

Copyright 2015 CSIRO Australia. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.1080/1755876X.2015.1022067


Under GODAE OceanView the operational ocean modelling community has developed a suite of global ocean forecast, reanalysis and analysis systems. Each system has a critical dependence on ocean observations routinely assimilating observations of in-situ temperature and salinity, and satellite sea-level anomaly and sea surface temperature. This paper demonstrates the value and impact of ocean observations to three global eddy-permitting forecast systems, one global eddy-permitting model-independent analysis system, one eddy-resolving reanalysis system, and two seasonal prediction systems. All systems have been used to assess the impact of Argo profiles, including scenarios with no Argo data, and a degraded Argo array unanimously concluding that Argo is a critical data set the most critical for seasonal prediction, and as critical as satellite altimetry for eddy-permitting applications. Most systems show that TAO data are as important as Argo in the tropical Pacific, and that XBT data have an impact that is comparable to other data types in the vicinity of XBT transects. It is clear that no currently available data type is redundant. On the contrary, the components of the global ocean observing system complement each other remarkably well, providing sufficient information to monitor and forecast the global ocean.

Item Details

Item Type:Refereed Article
Keywords:data assimilation, model, salinity
Research Division:Earth Sciences
Research Group:Oceanography
Research Field:Physical oceanography
Objective Division:Environmental Management
Objective Group:Marine systems and management
Objective Field:Measurement and assessment of marine water quality and condition
UTAS Author:Oke, PR (Dr Peter Oke)
ID Code:120257
Year Published:2015
Web of Science® Times Cited:51
Deposited By:Oceans and Cryosphere
Deposited On:2017-08-17
Last Modified:2017-10-24
Downloads:129 View Download Statistics

Repository Staff Only: item control page