A RELOCATABLE DATA ASSIMILATION SYSTEM FOR THE COASTAL OCEAN
The objective of this study (SHOM-IRD project 20CP09), involving a postdoctoral researcher (Bénédicte Lemieux-Dudon), is to provide CROCO with a data assimilation capability for the coastal ocean at the regional scale, using both global analysis systems (CMEMS), satellite observations (altimetry, surface temperature), global datasets of in-situ observations (Argo floats, XBT, CTD, buoys), and « new » or local data that may be available (HF radars, gliders, ship drifts, etc.). Due to its computational efficiency in assimilating a large number of observations, the incremental 3DVAR variational method (correcting the deviation between analysis and background state) is being actively developed for real-time high-resolution forecasting of coastal systems. In this project, we will integrate the multi-scale MS-3DVAR system developed by Zhijin Li (Li et al 2008, 2015; Chao et al., 2008; Sepulveda et al., 2013) into CROCO. This choice is consistent with SHOM’s and IRD’s objectives: to propose a system of community interest, efficient, reliable, easy to implement and relocatable.
MEDITERRANEAN DEMONSTRATOR
We use as a demonstrator the western Mediterranean Sea, which is representative of the various coastal and oceanic environments. This first operational system started in February 2023 in preparation for a sea campaign devoted to SWOT (March 2023), to which SHOM is committed. This first version of the system is to be continually improved until a second campaign in 2024 and further. The assimilation system is based on generic data (Altimetry, SST, Argo floats). The model forcing is from regional and global analyses and forecasts: CMEMS MED for the oceanic lateral boundaries and NOAA for the surface fluxes. New python tools, based on the CROCO Forecast_tools (Marchesiello et al., 2008), are used to process the forcing data. The analysis and simulation were performed with the HPC resources of CALMIP supercomputing center (Grant 2023-p22007).
Current ANALYSIS & FORECAST
| REGION | ANALYSIS | FORECAST |
|---|---|---|
| WESTERN MEDITERRANEAN | SSH – SST | SSH-SST-SSS |
| NW REGION | SSH – SST |
REFERENCES
Chao Y., Z. Li, J. Farrara, J.C. McWilliams, J. Bellingham, X. Capet, F. Chavez, J.-K. Choi, R. Davis, J. Doyle, D. Frantaoni, P. Li, P. Marchesiello, M.A. Moline, J. Paduan and S. Ramp, 2009: Development, implementation and evaluation of a data-assimilative ocean forecasting system off the central California coast. Deep-Sea Research II, 56, 100-126.
Li, Z., Y. Chao, J. C. McWilliams, and K. Ide, 2008: A three-dimensional variational data assimilation scheme for the Regional Ocean Modelling System: Implementation and basic experiments. J. Geophys. Res., 113, C05002.
Li Z, McWilliams JC, Ide K, Farrara JD, 2015: A multi-scale variational data assimilation scheme: formulation and illustration. Mon Wea Rev 143:3804–3822.
Marchesiello P., et al, 2008: Keys to affordable regional marine forecast systems. Mercator Ocean Quarterly Newsletter, 30, 38-48, July 2008.
Sepulveda H.H., P. Marchesiello and Z. Li, 2013: Oceanic data assimilation study in northern Chile: use of a 3DVAR method. Lat. Am. J. Aquat. Res., 41(3), 570-575.