A 3‐D variational assimilation scheme in coupled transport‐biogeochemical models: Forecast of Mediterranean biogeochemical properties. Issue 1 (13th January 2014)

• Record Type: Journal Article
• Authors: Teruzzi, Anna; Dobricic, Srdjan; Solidoro, Cosimo; Cossarini, Gianpiero
• Is Part Of: Journal of geophysical research. Volume 119:Issue 1(2014:Jan.)
• Page Start: 200
• Page End: 217
• Publication Date: 2014-01-13
• Subjects: Oceanography -- Periodicals; 551.4605
• DOI: 10.1002/2013JC009277
• Languages: English
• ISSNs: 2169-9275

Abstract

<abstract abstract-type="main"> <title> <x xml:space="preserve">Abstract</x> </title> <p>[1] Increasing attention is dedicated to the implementation of suitable marine forecast systems for the estimate of the state of the ocean. Within the framework of the European MyOcean infrastructure, the pre‐existing short‐term Mediterranean Sea biogeochemistry operational forecast system has been upgraded by assimilating remotely sensed ocean color data in the coupled transport‐biogeochemical model OPATM‐BFM using a 3‐D variational data assimilation (3D‐VAR) procedure. In the present work, the 3D‐VAR scheme is used to correct the four phytoplankton functional groups included in the OPATM‐BFM in the period July 2007 to September 2008. The 3D‐VAR scheme decomposes the error covariance matrix using a sequence of different operators that account separately for vertical covariance, horizontal covariance, and covariance among biogeochemical variables. The assimilation solution is found in a reduced dimensional space, and the innovation for the biogeochemical variables is obtained by the sequential application of the covariance operators. Results show a general improvement in the forecast skill, providing a correction of the basin‐scale bias of surface chlorophyll concentration and of the local‐scale spatial and temporal dynamics of typical bloom events. Further, analysis of the assimilation skill provides insights into the functioning of the model. The computational costs of the assimilation scheme adopted are low compared to other assimilation techniques, and its modular structure facilitates further developments. The 3D‐VAR scheme results especially suitable for implementation within a biogeochemistry operational forecast system.</p> </abstract>