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Ocean Science An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/os-2019-85
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-2019-85
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 06 Aug 2019

Submitted as: research article | 06 Aug 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Ocean Science (OS).

Evaluation of fraternal versus identical twin approaches for observation impact assessments: An EnKF-based ocean assimilation application for the Gulf of Mexico

Liuqian Yu1,2, Katja Fennel1, Bin Wang1, Arnaud Laurent1, Keith R. Thompson1, and Lynn K. Shay3 Liuqian Yu et al.
  • 1Department of Oceanography, Dalhousie University, Halifax, Nova Scotia, Canada
  • 2Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong
  • 3Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida, USA

Abstract. Assessments of ocean data assimilation (DA) systems and observing system design experiments typically rely on identical or fraternal twin experiments. The identical twin approach has been recognized as yielding biased impact assessments in atmospheric predictions but these shortcomings are not sufficiently appreciated for oceanic DA applications. Here we present the first direct comparison of the fraternal and identical twin approach in an ocean DA application. We assess the assimilation impact for both approaches in a DA system for the Gulf of Mexico that uses the Ensemble Kalman Filter. Our comparisons show that, despite a reasonable error growth rate in both approaches, the identical twin produces a biased skill assessment overestimating the improvement from assimilating sea surface height and sea surface temperature observations while underestimating the value of assimilating temperature and salinity profiles. Such biases can lead to an undervaluation of some observing assets (in this case profilers) and thus misguided distribution of observing system investments.

Liuqian Yu et al.
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Short summary
We present a first direct comparison of fraternal versus identical twin approaches for an ocean data assimilation system. We show that the identical twin approach overestimates the value of assimilating satellite observations and undervalues the benefit of assimilating temperature and salinity profiles. Misleading assessments such as undervaluing the impact of some observational assets are problematic and can lead to misguided decisions on balancing investments among different observing assets.
We present a first direct comparison of fraternal versus identical twin approaches for an ocean...
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