Evaluation of nonidentical versus identical twin approaches for observation impact assessments: an ensemble-Kalman-filter-based ocean assimilation application for the Gulf of Mexico
<p>Assessments of ocean data assimilation (DA) systems and observing system design experiments typically rely on identical or nonidentical twin experiments. The identical twin approach has been recognized as yielding biased impact assessments in atmospheric predictions, but these shortcomings...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2019-12-01
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| Series: | Ocean Science |
| Online Access: | https://www.ocean-sci.net/15/1801/2019/os-15-1801-2019.pdf |
| Summary: | <p>Assessments of ocean data assimilation (DA) systems and observing system
design experiments typically rely on identical or nonidentical 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 nonidentical and identical twin
approaches 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 a misguided distribution of observing system investments.</p> |
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| ISSN: | 1812-0784 1812-0792 |