Data assimilation of simulated SSS SMOS products in an ocean forecasting system

Autor: C E Testut Dr, Lionel Renault, C Boone, B Tranchant Dr, G Larnicol Dr, E Obligis Dr, N Ferry Dr
Rok vydání: 2008
Předmět:
Zdroj: Journal of Operational Oceanography. 1:19-27
ISSN: 1755-8778
1755-876X
DOI: 10.1080/1755876x.2008.11020099
Popis: Sea Surface Salinity (SSS) measured from the future Soil Moisture and Ocean Salinity (SMOS) satellite has to be considered as a new type of data. This paper addresses the impact of assimilating two different simulated SSS data types (raw track observations versus a gridded processed product) in an ocean forecasting system through an Observing System Simulation Experiment (OSSE). The OSSE consists of hindcast experiments assimilating an operational dataset of Sea Surface Temperature (SST), in-situ profiles of temperature and salinity and Sea Level Anomalies (SLA) plus various simulated SMOS SSS data. These assimilation experiments use an eddy permitting model (1/38) covering the North Atlantic from 208S to 708N and a multivariate assimilation system referred to as SAM2v1. This assimilation scheme is a Reduced Order Kalman Filter using a 3D multivariate modal decomposition of the forecast error covariance. The OSSE enables an illustration of the impact of SSS assimilation on a Mercator Ocean regional foreca...
Databáze: OpenAIRE