PreSAC 2008 1 Progress on NEMOVAR. Overview of NEMOVAR status First NEMOVAR experiments Use of NEMOVAR analyses to initialize ocean only forecasts Missing.

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preSAC Progress on NEMOVAR. Overview of NEMOVAR status First NEMOVAR experiments Use of NEMOVAR analyses to initialize ocean only forecasts Missing bits for operational implementation

preSAC Overview of NEMOVAR status A comprehensive 3D-VAR system is now available at ECMWF usable for scientific experimentation.  So far we have been investigating the assimilation of in-situ (T,S) observations.  SLA and SST assimilation is possible, but we have not done any work on this yet. oFor the SLA we need to investigate what to do about the MDT and the trend. oFor SST we use strong relaxation for now.  For all observations we use quality controlled observations. oWork is ongoing to use a Met. Office developed QC code.  No ensembles of analyses is available (yet). CERFACS and INRIA is working to code the TL/AD of NEMO enabling us to do 4D-VAR.

preSAC First NEMOVAR experiments 1 3D-VAR FGAT using a 10 day window with 40 iterations in the inner loop.  The cost of the inner loop is around 2 times the 10 day forecast of the outer loop with running with 16 MPI tasks. The experiments starts from climatology in continuing until ORCA1 configuration (1 deg resolution with 1/3 deg equatorial refinement). Potential temperature and salinity from the ENSEMBLES quality controlled data set has been assimilated.

preSAC First NEMOVAR experiments 2 The T, S and SSH increments are applied using incremental analysis update (IAU).  The final outer loop observation statistics are problematic since observations at the beginning of the window do not “see” the increment.  I will use it anyway ;-). The 3D-VAR experiments are compared to an equivalent control run.  Comparison with the assimilated observations. oThe 3D-VAR experiment should definitively fit the observations closer than the control experiment.  Comparison with independent data altimeter data. oHopefully the assimilation scheme improves the fit to the independent data.

preSAC Comparison with assimilated temperature observations (global)

preSAC Comparison with assimilated salinity observations (global)

preSAC Comparison with assimilated T observations (eastern pacific). Spikes most likely due to TAO data. More investigations are needed.

preSAC Comparison with assimilated T observations (western pacific).

preSAC Fit to independent altimeter data and comparison with HOPE. hc and ha is HOPE ctl and ana. nc and na is NEMO ctl and ana. Results are a bit mixed.  The tropical pacific is improved. Comparison with HOPE assimilation is not fair, since HOPE assimilate the altimeter data.

preSAC Conclusions of the first NEMOVAR assimilation runs. The assimilation system works like it is supposed to work.  The observation statistics behaves like expected.  The fit to the independent altimeter data improves in some regions.  Tuning of the background and observations covariances are needed. oIn the first runs we used the same background and observation errors as for OPAVAR ORCA2 with ½ length scales.  Quality control of the input observations using the actual background state could be an issue. oWe blindly trust the ENSEMBLES data. oHOPE experiences show that some of the data in the ENSEMBLES data are problematic. But are the NEMOVAR analyses any good?

preSAC Use NEMOVAR analyses to initialise forecasts. To answer the question an experiment using the analyses as initial conditions for a series of 6 month forced ocean integrations were done. A total of 4 forecast per year with start dates: 1/1, 1/4, 1/7 and 1/10 were made for the period of 1988 to The analyses from the previous discussed 3D-VAR experiment were used as initial conditions. The forecasts are compared with the control run and the analyse run. The same strong relaxation to observed SST as for the control run was applied.

preSAC Global ocean impact of assimilation.

preSAC Pacific ocean impact of assimilation. EasternWestern

preSAC Conclusions from the ocean forecast experiments In general the NEMOVAR 3D-VAR analysis scheme maintain the fit to the observations for several months in most regions. An exception is the temperature at the surface (not shown) due to the strong relaxation to SST. In some areas (like the western pacific) the assimilation scheme clearly has some problems. The answer to “But are the NEMOVAR analyses any good?” is a very cautious “yes” at this point in time.  Hopefully it will be a firmer “yes” soon …

preSAC Missing bits for operational implementation of NEMOVAR Minimum requirements:  Tuning of background and observation errors.  The QC code needs to be integrated with our real time ocean observational data.  The SLA data needs to be included. oThis includes the processing chain of along track data.  A similar bias treatment as in HOPE has to be implemented.  An ensembles of analyses needs to be setup.  A real time (accelerated) analysis scheme for VAREPS/monthly has to be implemented. oSome ideas are floating around but no real work done yet. Wish list:  Include ODB software to facilitate access to observation feedback information.