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. Assessments of ocean data assimilation (DA) systems and observing systemdesign experiments typically rely on identical or nonidentical twinexperiments. The identical twin approach has been recognized as yieldingbiased impact assessments in atmospheric predictions, but these shortcomingsare not sufficiently appreciated for oceanic DA applications. Here wepresent the first direct comparison of the nonidentical and identical twinapproaches in an ocean DA application. We assess the assimilation impact forboth approaches in a DA system for the Gulf of Mexico that uses the ensembleKalman filter. Our comparisons show that, despite a reasonable error growthrate in both approaches, the identical twin produces a biased skillassessment, overestimating the improvement from assimilating sea surfaceheight and sea surface temperature observations while underestimating thevalue of assimilating temperature and salinity profiles. Such biases canlead to an undervaluation of some observing assets (in this case profilers)and thus a misguided distribution of observing system investments.

ocean science

Evaluation of nonidentical versus identical twin approaches for observation impact assessments: an ensemble-Kalman-filter-based ocean assimilation application for the Gulf of Mexico