1. 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

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

3. 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 2Ocean Monitoring Gilbert et al. Project Management Team

4. The Gulf of St. Lawrence (GSL) Coupled Regional Deterministic Prediction System -5°C -15°C -25°C 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 S. Desjardins

5. CONCEPTS Canadian 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 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 Mean Std. dev. Number of comparisons F. Roy

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

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

10. Comparison between CMC and RTG SST analyses Figures show difference from GHRSST ensemble median for period May 21-28, 2010 RTG-GHRSST ens CMC-GHRSST ens 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. CMC/CIS Sea-ice Analysis System Uses 3DVAR-FGAT, with covariances obtained from EnKF North American Analysis: Four analyses per day of ice concentration at 5 km resolution Global Analysis: two analyses per day on 10km grid Currently assimilates: SSM/I, AMSR-E, CIS daily charts, RadarSAT image analyses Work in progress to add: SSMIS, scatterometer, visible-infrared, SAR and ice thickness satellite-based observations M. Buehner SSM/IAMSR-E CIS Chart RadarSAT

14. Verification against NOAA IMS analyses 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 M. Buehner Ice Ice Wat Wat IceWat Forecast Observation Persistence Forecast

15. 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 CIS Radarsat image analysis Labrador Sea Model (mean error) Model (std. dev.) Persistence of CMCICE (mean error) Persistence of CMCICE (std dev) Persistence Forecast 1/4o

16. CONCEPTS Regional V0 forecasting 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

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

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

19. 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 Great Lakes Forecast System CONCEPTS Regional Required to improve weather prediction in highly populated areas

20. 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

21. Great Lakes Forecast System Thermocline Issue Model Observed Typical Model Results for Stratification in Lake Erie. Modelled T is for 2006. Observed T is for 2008

22. 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)

23. 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 1/12 th regional SAM2 Produce 48hr weather and marine forecasts C-NOOFS 1/12° GEM RDPS 10km

24. 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

25. 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 1/12 th NEMO –Great Lakes Work continues –Begin work on 1/12 th 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

26. 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

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