1 Data assimilation developments for NEMO  A working group was created at the 2006 Developers Meeting with the objective of standardizing for NEMO certain operations that are common to different data assimilation algorithms –These developments concern the so-called “outer loop” of the assimilation algorithm  The outer loop and TAM developments (Arthur’s presentation) are subtasks of a larger project called NEMOVAR –NEMOVAR inherits the basic 3D-Var/4D-Var algorithmic structure of OPAVAR (developed for OPA8.2) but is being designed to fit within the NEMO environment and to run on massively parallel machines –NEMOVAR core development team: K. Mogensen, M. Balmaseda (ECMWF); A. Vidard (INRIA); A. Weaver (CERFACS)

2 The basic structure of the NEMOVAR algorithm (inherited from OPAVAR) Compute the model background trajectory, and initial data-model misfit BEGIN OUTER LOOP BEGIN INNER LOOP Compute an increment to reduce the misfit (iteratively minimize a quadratic cost function) END INNER LOOP Update the model trajectory using the increment, and compute the new data-model misfit END OUTER LOOP

3  To develop observation operators and to include different data-sets for online model-data comparisons  To develop routines for outputting the model trajectory for use with the data assimilation method in the “inner loop”  To develop procedures for reading and applying the increment generated by the data assimilation method Outer loop developments for NEMO: objectives

4 Outer loop developments for NEMO: current status  Observation operators –T and S profiles, sea-level anomalies –2D interpolation: bilinear remapping, nearest neighbour, polynomial –1D interpolation: linear, cubic spline –Parallel grid search  Observations distributed according to NEMO domain decomposition –Temporal averaging (e.g., for some buoy data) –Supports point measurements and maps –Designed so that it is straightforward to add a new data type (e.g., SSS from SMOS)  Data-bases currently available –T and S profiles from ENACT/ENSEMBLES historical data-base –T and S profiles from Coriolis real-time data-base –Altimeter data  Along-track anomalies from CLS multi-satellite data-base  Model-gridded MDT (Rio and model-generated products)  Data-bases to be included in the near future –Model-gridded SST (from Reynolds OIv2 + HadSST) –SST from OSTIA (GHRSST-PP) –TAO currents

5 Outer loop developments for NEMO cont.  Feedback files of obs-model information for diagnostic studies and/or assimilation (in the inner loop)  Model trajectory storage –Output of the background state at selected times using IOM –Full trajectory storage for 4D-Var not yet implemented  Applying the assimilation increment in NEMO (merging of OPAVAR and Met Office NEMO developments) 1.Incremental Analysis Updating (IAU)  Include T, S, SSH, u and v increments in extra tendency terms in the model equations  Possibility to use different IAU weights and variable IAU intervals 2.Direct Initialization  Correct the “now” initial conditions directly  Restart the integration with an Euler forward step  Reinitialize certain diagnostic variables

6 Interest for NEMO  Opportunity to standardize outer loop operations (obs. operators, application of increments, trajectory output) that are common to incremental-based assimilation algorithms  The comparison of model and data via observation operators provides a valuable stand-alone diagnostic for model validation and observation monitoring in forced or coupled mode

7 Goals for the NEMOVAR project  Short term (in ~2 years) goal –To have a 3D-Var system based on NEMO –Support distributed memory parallelization  Possible also support shared memory parallelization –Support different global (ORCA) configurations  Limited area versions of NEMO may be included later –Support T and S profiles, multi-satellite altimeter observations, SST and SSS products, and velocity observations –Support multi-incremental configurations where lower resolution can be used in the inner loop compared to the outer loop –Analysis ensembles for forecast initialization and background-error calibration  Long term goal –A full 4D-Var system with all of the above properties –Depends on the availability of TAM

8 NEMOVAR implementation plan: overview  We have defined the following plan: Phase 1: Split the existing OPAVAR Fortran code into separate executables for the inner and outer loops Phase 1: Split the existing OPAVAR Fortran code into separate executables for the inner and outer loops Phase 2: Develop an MPP implementation of the observation operators in the outer loop using NEMO Phase 2: Develop an MPP implementation of the observation operators in the outer loop using NEMO –Phase 3: Develop a hybrid system with NEMO in the outer loop and OPAVAR in the inner loop –Phase 4: Develop an MPP implementation of 3D-Var with NEMO in the outer loop and NEMOVAR in the inner loop –Phase 5: Develop an MPP implementation of 4D-Var with NEMO in the outer loop and NEMOVAR in the inner loop  Phase 3 is ongoing  By Phase 4 we will have achieved our short term goal  By Phase 5 we will have achieved our long term goal