2007
DOI: 10.1175/jcli4147.1
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An Observing System Simulation Experiment for the Indian Ocean

Abstract: An integrated in situ Indian Ocean observing system (IndOOS) is simulated using a high-resolution ocean general circulation model (OGCM) with daily mean forcing, including an estimate of subdaily oceanic variability derived from observations. The inclusion of subdaily noise is fundamental to the results; in the mixed layer it is parameterized as Gaussian noise with an rms of 0.1°C; below the mixed layer a Gaussian interface displacement with an rms of 7 m is used. The focus of this assessment is on the ability… Show more

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Cited by 31 publications
(27 citation statements)
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References 60 publications
(63 reference statements)
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“…Critically, transport of the floats by the mean flow and eddies may affect the basin-scale monitoring of CO 2 uptake and may invalidate the assumption of a random distribution that we have used. In a high-resolution OSSE, the strong currents of the Southern Ocean affected the sampling distribution of floats in the Indian Ocean [54]. While eddies enforce a more uniform sampling distribution [48], strategies for float release, parking depth, time between profiles and ice avoidance will need to be critically evaluated for how they impact the information provided by the whole sampling array and target undersampled regions.…”
Section: Discussionmentioning
confidence: 99%
“…Critically, transport of the floats by the mean flow and eddies may affect the basin-scale monitoring of CO 2 uptake and may invalidate the assumption of a random distribution that we have used. In a high-resolution OSSE, the strong currents of the Southern Ocean affected the sampling distribution of floats in the Indian Ocean [54]. While eddies enforce a more uniform sampling distribution [48], strategies for float release, parking depth, time between profiles and ice avoidance will need to be critically evaluated for how they impact the information provided by the whole sampling array and target undersampled regions.…”
Section: Discussionmentioning
confidence: 99%
“…These include OSSEs that assess specific pre-determined design options [22,23] and techniques that objectively generate "optimal" observation arrays. The latter includes Kalman filter techniques [24], ensemble approaches [25] and adjoint and representer-based methods [26,27,28]. Some of the studies referred to above have contributed to the design to assessment of the Argo array; some have assessed the design of tropical mooring arrays; and others have identified regions that may help constrain model variability in western boundary currents.…”
Section: Observing System Simulation Experimentsmentioning
confidence: 99%
“…These climatological profiles do maintain a strong stability in the water column during the seasonal cycles (Zavatarelli et al, 1998;Fig. 11).…”
Section: Dynamical Adjustment Of Initial Conditionsmentioning
confidence: 92%
“…OSSEs are used for two distinct objectives: to define the best observational network for improving forecasting; to determine the impact of an hypothetical dataset upon a simulated system. The result of the OSSE is in both cases the measure of the distance of the ecosystem evolving with or without the data network under analysis Vecchi and Harrison, 2006). This kind of methodology has been performed by means of the singular evolutive extended Kalman filter and of the ensemble variant of this method respectively in the onedimensional ecosystem model and in the three-dimensional one of the Cretan Sea (Triantafyllou et al, 2005).…”
Section: Introductionmentioning
confidence: 99%