|Author(s)||Skandrani Chafih1, de Mey Pierre2, Charria Guillaume3|
|Affiliation(s)||1 : NOVELTIS, Toulouse, France
2 : LEGOS, Toulouse, France
3 : Ifremer, LOPS, france
|Meeting||OceanPredict '19 - GODAE OceanView Symposium. May, 6-10, 2019 in Halifax, Nova Scotia, Canada|
In the framework of the European projects FP7 JERICO (http://www.jerico-fp7.eu/) and H2020 JERICO NEXT (http://www.jerico-ri.eu/), this study consisted in carrying out an objective design analysis of coastal HF radar networks with the ArM (Array Modes) method (Le Hénaff et al., 2009; Lamouroux et al., 2016; Charria et al., 2016). The ArM approach is a non-assimilative, data-model synergistic approach: it uses ensembles in response to known error sources to describe prior (model) uncertainties, and aims at quantitatively evaluating the performance of the observation network at detecting those uncertainties amidst observational noise. The ArM analysis consists in calculating and interpreting spectra of the representer matrix, as well as modal representers, making it possible to visualize the model error structures which are detectable by the radar observations and, in a second step, potentially controllable through data assimilation.
Skandrani Chafih, de Mey Pierre, Charria Guillaume (2019). Objective design of coastal HF Radar networks using stochastic array modes (ArM toolbox). OceanPredict '19 - GODAE OceanView Symposium. May, 6-10, 2019 in Halifax, Nova Scotia, Canada. https://archimer.ifremer.fr/doc/00635/74726/