Cooperation or coordination of underwater glider networks? An assessment from observing system simulation experiments in the Ligurian Sea
The coordinated and cooperative-unaware networking of glider fleets have been proposed to obtain a performance gain in ocean sampling over naïve collective behavior. Whether one of these implementations results in a more efficient sampling of the ocean variability remains an open question. This arti...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/414439 |
| Acceso en línea: | http://hdl.handle.net/10261/414439 https://api.elsevier.com/content/abstract/scopus_id/84907999200 |
| Access Level: | acceso abierto |
| Palabra clave: | In situ oceanic observations Sampling Data assimilation Optimization |
| Sumario: | The coordinated and cooperative-unaware networking of glider fleets have been proposed to obtain a performance gain in ocean sampling over naïve collective behavior. Whether one of these implementations results in a more efficient sampling of the ocean variability remains an open question. This article aims at a performance evaluation of cooperative-unaware and coordinated networks of gliders to reduce the uncertainty in operational temperature model predictions. The evaluation is based on an observing system simulation experiment (OSSE) implemented in the northern Ligurian Sea (western Mediterranean) from 21 August to 1 September 2010. The OSSE confronts the forecast skills obtained by the Regional Ocean Modeling System (ROMS) when assimilating data gathered from a cooperative and unaware network of three gliders with the prediction skill obtained when data comes from a coordinated configuration. An asynchronous formulation of the ensemble Kalman filter with a 48-h window is used to assimilate simulated temperature observations. Optimum sampling strategies of the glider networks, based on a pattern search optimization algorithm, are computed for each 48-h forecasting period using a covariance integrated in time and in the vertical direction to reduce the dimensionality of the problem and to enable a rapid resolution. Perturbations of the depth-averaged current field in glider motions are neglected. Results indicate a better performance of the coordinated network configuration due to an enhanced capacity to capture an eddy structure that is responsible for the largest forecast error in the experimental domain. |
|---|