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Inter-Departmental Collaboration MOU

GOVST Canadian National Report 2011 Canadian Operational Network of Coupled Environmental PredicTion Systems CONCEPTS November 16 th 2011 Authors Fraser Davidson, Greg Smith Hal Ritchie, Denis Lefaivre, Youyu Lu, Fred Dupont, Jean Francois Lemieux, Youyu Lu. Data Assimiliation Codes

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Inter-Departmental Collaboration MOU

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  1. GOVST Canadian National Report2011Canadian Operational Network of Coupled Environmental PredicTion SystemsCONCEPTSNovember 16th 2011Authors Fraser Davidson, Greg Smith Hal Ritchie, Denis Lefaivre,Youyu Lu, Fred Dupont, Jean Francois Lemieux, Youyu Lu

  2. Data Assimiliation Codes Mecator Ocean Modelling Algorithms Data Exchange Agreements Partnership Inter-Departmental Collaboration MOU CONCEPTSBudget linked to Annual workplan and report

  3. Project Management Team CONCEPTS Structure Steering Committee A Director General from each Department Secretariat A Division Manager/ Director from each Department Annex 1 Prediction Systems Ritchie Davidson Lefaivre Annex 2 Ocean Monitoring Gilbert et al.

  4. The Gulf of St. Lawrence (GSL) Coupled Regional Deterministic Prediction System • Operational regional forecasting system (GEM-Ops) has tendency to overestimate cold events in winter. • Increased heat fluxes in coupled system buffers air temperatures and improves forecasts • Demonstrates importance of air-sea-ice coupling even for short-range weather forecasts • Coupled GSL system now operational at CMC • Since summer -5°C -15°C -25°C S. Desjardins

  5. CONCEPTSCanadian Operational Network of Coupled Environmental Prediction • Project Targets: • Global coupled medium-to-monthly forecasting system: • GEM atmospheric model and 4DVAR/EnKF analysis system • Coupled to 1/4° resolution (ORCA025) NEMO ice-ocean model • Ocean initialized using Mercator analysis system (PSY3) • Initially: produce 10 day uncoupled ice-ocean forecasts • Regional short-term forecasting system • Build on V-0 developments / CNOOFS (F. Davidson et al.) • Ocean initialized using Mercator analysis (PSY2) output • NEMO on ORCA12 sub-domain NW Atlantic + Arctic • Support MET/NAVAREAS 17 & 18 • To be coupled to CMC regional forecasting system • Initially: produce 10 day uncoupled ice-ocean forecasts • Products and Client Product Validation • Build on developments made • by CNOOFS and Observatoire Global du St. Laurent • Consolidation of CONCEPTS output with distribution tools • Outreach and Client Interaction

  6. CONCEPTS Global - V0 • Ice-ocean model: • NEMO v3.1 : OPA9 ocean model and LIM2-EVP sea ice • ORCA025: Global tri-polar 1/4° resolution • Atmospheric forcing from GEM Global (GDPS; 33km) • Forced using CORE bulk formula • 3hrly forcing frequency (including diurnal cycle) • Initialization: • Ice and ocean fields taken from Mercator (PSY3V2) analysis • Output: • Weekly 10-day forecasts of ocean and ice fields

  7. Comparison with AVHRR SST observations F. Roy Mean • Differences taken between AVHRR SST data and hourly output from weekly forecasts. • Statistics accumulated for each day for forecasts made from May 20, 2009 to Mar 23, 2010. • Results shown for day 10 of forecasts • Poor coverage in polar regions and due to cloud cover Std. dev. Number of comparisons

  8. Comparison with AVHRR SST observations Day 1 Day 10 Mean Mean Development of warm bias Std. dev. Std. dev.

  9. Comparison with AVHRR SST observations Day 1 Day 10 Mean Mean Cold bias present in analysis Std. dev. Std. dev.

  10. Comparison between CMC and RTG SST analyses Figures show difference from GHRSST ensemble median for period May 21-28, 2010 CMC-GHRSSTens RTG-GHRSSTens www.ghrsst.org

  11. Regional RMS differences with AVHRR SST • CMC SST analysis has smaller RMS diff for day1 • Similar error growth in both persistence curves • Forecast beat persistence of analysis for most regions • Forecasts show smaller diff as compared to persistence of CMC SST analyses for N. Atl, N. Pac and T. Ind. Forecasts Persistence of SAM2 analyses Persistence of CMC analyses

  12. CONCEPTS Global V1 • AIM: Produce daily analyses and 10day forecasts. • Based on PSY3V2, with following modifications: • Updated SAM2 to NEMOv3.1, with LIM2-EVP • Assimilate CMC-SST analysis (in place of RTG) • Ocean analysis merged with 3DVAR-FGAT ice analysis • Daily analysis updates (planned) • Status: • Modifications to SAM2 ongoing • Routine production of ice-ocean analyses since Dec. 2010 • Evaluation of ice-ocean forecasts underway • CLASS4 metrics  GODAE IntercomparisonTT • Starting initial trials of coupled runs.

  13. Verification against NOAA IMS analyses M. Buehner • Evaluation of 5km North American analyses • Based on contingency tables values • Uses threshold of 0.4 for ice/noise • Overestimation of ice cover in CMC operational analysis during melt Persistence Forecast Forecast Observation

  14. Verification against Radarsat • Evaluation of 5 day ice forecasts • Model appears to have some skill in predicting mean ice cover, but ice dynamics is still a challenge… • Careful analysis required to understand small-scale details represented in Radarsat image analyses Model (mean error) Model (std. dev.) Persistence of CMCICE (mean error) Persistence of CMCICE (std dev) Persistence Forecast 1/4o CIS Radarsat image analysis Labrador Sea

  15. CONCEPTS Regional V0forecasting system • C-NOOFS: Canadian-Newfoundland Operational Oceanographic Forecasting System • Lead: F. Davidson (NAFC) • Produces daily 10-day forecasts at 1/12° resolution for the Northwest Atlantic • Initialized using Mercator data assimilation system (PSY2). • Merged with 3DVAR-FGAT ice analysis • Designed to meet needs of Coast Guard and Navy, as well as variety of applications influenced by sea ice C-NOOFS

  16. Recreating Drifter track data 23 Drifter tracks [surface + 10m] For Coast Guard Applications of Ocean Forecasts

  17. CNOOFS Comparison with Spring Survey F. Davidson • Comparison of bottom temperature from 2010 Spring Survey of Grand Banks for • NWA025 (~PSY3V2R2) • NWA12 (~PSY2V3R1)

  18. Great Lakes Forecast SystemCONCEPTS Regional Uses NEMO code as other CONCEPTS projects Coupled to Hydrodynamic Model for rivers. Planned coupling to 2 D River model of Saint Laurence System 2km grid • Required to improve weather prediction in highly populated areas

  19. CONCEPTS Regional Great Lakes Forecast System • Required to improve weather prediction in highly populated areas • Uses same tools as Regional and Global Systems • Ice Forecast also important • Forced model run for great lakes shows ability of NEMO system

  20. Great Lakes Forecast SystemThermocline Issue Typical Model Results for Stratification in Lake Erie. Modelled T is for 2006. Observed T is for 2008 Model Observed

  21. CONCEPTS REGIONAL V1 • Impetus from 30 M$ METAREA project development. • Integrated marine Arctic prediction system • marine forecast system using a regional high resolution coupled multi-component modelling (atm., land, snow, ice, ocean, wave) and data assimilation system • Improved Arctic monitoring • Predict: - Atmospheric conditions,- Sea ice (concentration, pressure, drift, ice edge) - Waves and Freezing spray,- Ocean conditions (temperature and currents)

  22. CONCEPTS Regional V1 • Build on CNOOFS and Coupled GSL • Develop coupled forecasting system for N. America/Arctic • Couple NEMO to GEM regional (10km) • 5km LAM over METAREAS 17&18 • with 5km Atm 4DVAR/EnKF • 1/12th regional SAM2 • Produce 48hr weather and marine forecasts C-NOOFS 1/12° GEM RDPS 10km

  23. CONCEPTS Regional Ocean data assimilation 1/12° Atlantic/Arctic system • Evaluate/develop configuration • Add tides (wt conservative non-linear free surface) • Develop 1/12° coastal SAM2 • Combine SAM2 with 3DVAR ice analysis

  24. CONCEPTS RECAP • CONCEPTS Global: • Running 1/4° global 10day forecasting system since Dec. 2010 • Operational transfer in coming year • Next steps: • produce daily analyses and • improve consistency of ice and ocean analyses • CONCEPTS Regional • Develop/evaluate N.Atl/Arctic coastal 1/12th NEMO • Great Lakes Work continues • Begin work on 1/12th regional data assimilation system • Improve Ice Rheologies to better represent fine-scale ice deformations over short lead times? • How do we constrain the ocean under-ice and in the Marginal Ice Zone? • Ice thickness (Radarsat, Cryosat, AVHRR) • Product Development and Dissemination • Central CONCEPTS server being lit up this month • Serving C-NOOFS products to CCG and DND

  25. Target Clients • Canadian Ice Service, Canadian Coast Guard, • Canadian Department of National Defense: Ocean Feature Analysis and Acoustic Situational Awareness • Offshore Oil and Gas Industry. Fog prediction, Pack Ice and Iceberg Management, Deep Water Riser Vibration Prediction, Site planning • Improvements to regional and global weather forecasts (timescales of days to seasonal) are expected. • Fisheries and Oceans ecosystem science initiatives • Oil and Gas Regulation Boards: Oil spill drift and deep well blowout scenarios

  26. Extras…

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