1 / 24

Ocean and sea-ice data assimilation and forecasting in the TOPAZ system

Ocean and sea-ice data assimilation and forecasting in the TOPAZ system. L. Bertino, K.A. Lisæter, I. Kegouche, S. Sandven NERSC, Bergen, Norway. Arctic ROOS meeting, 18 th Dec. 2007. Motivation. Objective:

villarreals
Download Presentation

Ocean and sea-ice data assimilation and forecasting in the TOPAZ system

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Ocean and sea-ice data assimilation and forecasting in the TOPAZ system L. Bertino, K.A. Lisæter, I. Kegouche, S. Sandven NERSC, Bergen, Norway Arctic ROOS meeting, 18th Dec. 2007

  2. Motivation • Objective: • Provide short-term (10 days) forecasts of physical and biogeochemical ocean parameters to the public at large and intermediate users. • Strategy • Focus on advanced data assimilation techniques • Gradual increase of resolution (as affordable…) • Nesting on regions of higher interest

  3. Method • The ice-ocean system has two sources of information • A nonlinear ice-ocean model • A regular flow of observations • Uncertainties arise primarily from • The initial state • Surface boundary conditions • Measurements errors • Monte Carlo methods can handle non-linear dynamics. • Provide the best estimate • Provide the residual uncertainty • Each source of uncertainty must be simulated realistically.

  4. Sequential data assimilationRecursive Monte Carlo method Forecast Analysis Member1 Member2 …… 2 1 Member99 • Initial uncertainty • Model uncertainty • Measurement uncertainty Member100 3 Observations

  5. The TOPAZ model system • TOPAZ: Atlantic and Arctic • HYCOM • EVP ice model coupled • 11- 16 km resolution • 22 hybrid layers • EnKF • 100 members • Sea Level Anomalies (CLS) • Sea Surface Temperatures • Sea Ice Concentrations (SSM/I) • Sea ice drift (CERSAT) • Runs weekly since Jan 2003 • ECMWF atmos. forcing

  6. Model upgrade TOPAZ3 TOPAZ2 • Doubling the horizontal resolution • TOPAZ2: 18 to 36 km • TOPAZ3: 11 to 16 km

  7. System Validation Consistency? Accuracy? Performance?

  8. Consistency: Against Climatology TOPAZ2 TOPAZ3 Temperature anomalies at 30 m depths

  9. Accuracy: against ice concentrations TOPAZ2 TOPAZ3 Model minus obs.

  10. AccuracyAgainst in-situ profiles from NPEOAerial CTD casts Temperature Salinity

  11. Assimilation on 4th and 11th April Up to +10 days forecast

  12. Forecast skills: Barents Sea - ice concentrations Average Winter 2007 Average Summer 2007

  13. Ice drift validation • In-situ • Ice drifting buoys (Statoil/CMR) • Manned expeditions • Remote sensing • ASAR (NERSC) WP2 • QuickSCAT (Ifremer) • Modelling • TOPAZ V1, class 1 • A good agreement [ J. Wåhlin]

  14. Historical minimum Arctic sea-ice area, summer 2007 Observed sea-ice from SSM/I, NORSEX algorithm

  15. Forecasting the ice minimum in TOPAZ • Overlay of successive forecasts • TOPAZ catches the freeze-up

  16. Products Standards Delivery Timeliness

  17. MERSEA products Class 1: 3D daily fields ocean and sea-ice Anomalies to climatolgy Class 2: Predefined sections Predefined moorings Class 3: Volume fluxes through sections Salt and heat transports Class 4: Differences with observations, Forecast skills Other products (targeted) Ensemble uncertainties, Predicted drift Icebergs What products?

  18. Class 2 metrics • Sections stored daily Moorings stored daily

  19. Uncertainty estimatesexample sea-ice thickness Ensemble average 13th March 2007 Ensemble standard dev. 13th March 2007

  20. TOPAZ successive forecasts in red Actual positions of Tara from DAMOCLES in black Updated on Google Earth Forecasting the drift of Tara [ K. A. Lisæter]

  21. An iceberg is sensitive to Winds Waves Currents Ice drift Ice thickness Iceberg shape Tides Melting … 8m draft Iceberg simulations 18m draft 13m draft [ I, Keghouche, NERSC ]

  22. Availability • Forecast updated every Thursday • 10 days forecast horizon • Available freely via • Webpage http://topaz.nersc.no (static pictures) • OPeNDAP http://topaz.nersc.no/thredds (data) • No password required • But feedback is welcome • Available to date • TOPAZ2: October 2005 to October 2007 • TOPAZ3: July 2007 to present

  23. Plans • Ongoing projects (MERSEA, BOSS4GMES) • Assimilation of additional data (Argo) • Inclusion of ecosystem model • NORWECOM from IMR, Bergen. • RT exploitation of TOPAZ at met.no • Developments of TOPAZ at NERSC • Exploitation at met.no (ongoing) • Planned project MyOcean (2008-2011) • 30-years reanalysis

More Related