2014
DOI: 10.1175/jtech-d-13-00011.1
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Rigorous Evaluation of a Fraternal Twin Ocean OSSE System for the Open Gulf of Mexico

Abstract: A new fraternal twin ocean observing system simulation experiment (OSSE) system is validated in a Gulf of Mexico domain. It is the first ocean system that takes full advantage of design criteria and rigorous evaluation procedures developed to validate atmosphere OSSE systems that have not been fully implemented for the ocean. These procedures are necessary to determine a priori that the OSSE system does not overestimate or underestimate observing system impacts. The new system consists of 1) a nature run (NR) … Show more

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Cited by 102 publications
(110 citation statements)
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“…This is done through sequential data assimilation based on the Kalman approach, using an Ensemble Optimal Interpolation (EnOI) filter (e.g., Counillon and Bertino 2009). The methodology and numerical tools are the same as those used for performing Observing System Simulation Experiments (OSSEs) in the GoM for testing the impact of airborne ocean profile surveys, using the HYCOM model at lower resolution (Halliwell et al 2014. Details about the data assimilation filter can be found in the appendix of Halliwell et al (2014).…”
Section: Gom-hycom Data Assimilationmentioning
confidence: 99%
“…This is done through sequential data assimilation based on the Kalman approach, using an Ensemble Optimal Interpolation (EnOI) filter (e.g., Counillon and Bertino 2009). The methodology and numerical tools are the same as those used for performing Observing System Simulation Experiments (OSSEs) in the GoM for testing the impact of airborne ocean profile surveys, using the HYCOM model at lower resolution (Halliwell et al 2014. Details about the data assimilation filter can be found in the appendix of Halliwell et al (2014).…”
Section: Gom-hycom Data Assimilationmentioning
confidence: 99%
“…OSSE has been used widely in the atmospheric community for 4 decades to design new observation tools, for error assessment in large models and for parameter estimation (Arnold Jr. and Dey, 1986;Masutani et al, 2010). Atlas (1997) summarizes the criteria established by the atmospheric community to perform credible OSSE . Halliwell Jr. et al (2014 gave an example of an ocean OSSE in the Gulf of Mexico by following those criteria.…”
mentioning
confidence: 99%
“…Nonetheless, value uncertainty should be assessed via rigorous uncertainty propagation and accounting for the correlated nature of errors, not least as a contribution to constraining the steric change in parts of the ocean that are inadequately observed. Community efforts are underway with the Global Ocean Data Assimilation Experiment (GODAE) Ocean View (https://www.godae.org/OSSE-OSEhome.html) and the European initiative AtlantOS (https://www.atlantos-h2020.eu/) through observing system evaluations and observing system simulation experiments (e.g., Halliwell et al 2014). However, these efforts should, in future, be supported by a community effort to quantify error covariance estimates for classes of profile observation, in addition to the extensive existing body of work on observational bias (e.g., Abraham et al 2013) Historically, there has been enormous community effort to maintain, improve and understand the in situ record (e.g., Wijffels et al 2008;Hamon et al 2012;Abraham et al 2013;Boyer et al 2016 and references therein).…”
Section: Discussionmentioning
confidence: 99%