Evaluation of CONCEPTS Ice-Ocean Forecasting Systems

Greg Smith1, Christiane Beaudoin1, Alain Caya1, Mark Buehner1, Francois Roy2 , Jean-Marc Belanger1, Frederic Dupont1, Fraser Davidson3, Jennifer

Wells3, Tom Carrieres4 , Hal Ritchie5, Youyu Lu6 , Charles-Emmanuel Testut7 and Gilles Garric7

1 Meteorological Research Division, Environment Canada, Dorval, CANADA2 Canadian Meteorological Centre, Environment Canada, Dorval, CANADA

3 Northwest Atlantic Fisheries Centre, Fisheries and Oceans Canada, CANADA4 Canadian Ice Service, Environment Canada, Ottawa, CANADA

5 Meteorological Research Division, Environment Canada, Dartmouth, CANADA6 Bedford Institute of Oceanography, Fisheries and Oceans Canada, Bedford, CANADA

7Mercator-Océan, Toulouse, FRANCE

GODAE Oceanview Workshop, Santa Cruz, USA (Jun 13-17, 2011)

OutlineOutline

• Operational Gulf of St. Lawrence Coupled Atmosphere-Ice-Ocean Forecasting System

• CONCEPTS Objectives

• Global Forecasting System

– Evaluation with AVHRR and Radarsat

• NW Atlantic/Arctic Forecasting System

– Evaluation against IMS analyses

• Future Work and Interests

The Gulf of St. Lawrence (GSL) Coupled Regional Deterministic Prediction System (RDPS-CGSL)

-5°C-5°C

-15°C-15°C

-25°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

– as of last week!

S. Desjardins

CONCEPTS

• Canadian Operational Network of Coupled Environmental Prediction Systems

• Aim:– Development of Regional and Global Coupled Atmosphere-Ice-Ocean Development of Regional and Global Coupled Atmosphere-Ice-Ocean

Forecasting SystemsForecasting Systems

– 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▪ Preparation and issuing service for MET/NAVAREAS 17&18▪ Build on developments made by CNOOFS (F. Davidson et al.) ▪ Coupled to CMC regional forecasting system (RDPS)▪ Based on subdomain of ORCA12 for NW Atlantic + Arctic

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

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

Comparison with AVHRR SST observations

Mean

Std. dev.

Mean

Std. dev.

Day 1 Day 10

Development of warm bias

Comparison with AVHRR SST observations

Mean

Std. dev.

Mean

Std. dev.

Day 1 Day 10

Cold bias present in analysis

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

CONCEPTS Global V1

• AIM: Produce daily analyses and 10day forecasts.

• Based on PSY3V2, with following modifications:– Updated SAM2 to NEMOv3.1, with LIM2-EVP(done)– Assimilate CMC-SST analysis (in place of RTG)(done)– Ocean analysis merged with 3DVAR-FGAT ice analysis (done)– Daily analysis updates (planned)

• Status:– Modifications to SAM2 ongoing– Routine production of ice-ocean analyses since Dec. 2010– Evaluation of ice-ocean forecasts underway– Starting initial trials of coupled runs.

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/I AMSR-E

CIS Chart RadarSAT

Verification against NOAA IMS analyses

• Evaluation of 5km North American analyses

• Based on contingency tables values

• Uses threshold of 0.4 for ice/noice

• Overestimation of ice cover in CMC operational analysis during melt

M. Buehner

CONCEPTS Global V1

• AIM: Produce daily analyses and 10day forecasts.

• Based on PSY3V2, with following modifications:– Updated SAM2 to NEMOv3.1, with LIM2-EVP(done)– Assimilate CMC-SST analysis (in place of RTG)(done)– Ocean analysis merged with 3DVAR-FGAT ice analysis (done)– Daily analysis updates (planned)

• Status:– Modifications to SAM2 ongoing– Routine production of ice-ocean analyses since Dec. 2010– Evaluation of ice-ocean forecasts underway– Starting initial trials of coupled runs.

Comparison with PSY3V2R2

• Difference after 28 cycles (valid 20091125)

• Cycle started 20090513

• Impact of changes to SST assimilation

• Difference in SSS due to relaxation timescale, atm forcing and ice assimilation

Verification against Radarsat

• Evaluation of 30 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)

CONCEPTS Regional 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

CNOOFS Comparison with Spring Survey

• Comparison of bottom temperature from 2010 Spring Survey of Grand Banks for

– NWA025 (~PSY3V2R2)– NWA12 (~PSY2V3R1)

F. Davidson

EC/MSC’s involvement in METAREA’s

• Development of an integrated marine Arctic prediction system in support of METAREA monitoring and warnings.

• Development of short-term marine forecast system using a regional high resolution coupled multi-component modelling (atmosphere, land, snow, ice, ocean, wave) and data assimilation system

• To predict:- Near Surface atmospheric conditions,- Sea ice (concentration, pressure, drift, ice edge)

- Freezing spray,- Waves, and- Ocean conditions (temperature and currents)

• Improved Arctic monitoring

Regional Coupled Forecasting System

• 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

Plans and interests

• 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– Begin work on 1/12th regional data assimilation system

• Evaluation and intercomparison of ice-covered waters– Ice thickness (Radarsat, Cryosat, AVHRR)– Marginal ice zone (MIZ)– How can ice rheologies be improved to better represent fine-scale ice

deformations over short lead times?– How do we constrain the ocean under-ice and in the MIZ?