Prediction and Predictability of the Prediction and Predictability of the Global Atmosphere-Ocean SystemGlobal Atmosphere-Ocean System

from Days to Decadesfrom Days to Decades

Presenters: Presenters:

Keith Thompson, Hal Ritchie,Keith Thompson, Hal Ritchie,George BoerGeorge Boer

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Overview of proposal accepted for Overview of proposal accepted for funding by CFCASfunding by CFCAS

Science: Proposal must be scientifically sound

Targeted: Clear contribution must be made

National: Clear contribution to a national effort

Expertise: Capacity and capability to deliver

Collaboration: Number of partners preferred

Funding: Need for CFCAS funds and leverage

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Overall Goal and ApproachOverall Goal and Approach

Goal: Improve predictions of the ocean and atmosphere on time-scales of days to decades, and space scales of tens of km to global

Approach: Improvements in data assimilative models of the ocean and atmosphere, and a better understanding of the physical mechanisms that permit, and limit, predictability

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MotivationMotivationThe Need Government departments such as EC, DFO and DND need the products

that our network will develop (e.g. an interactive ocean to extend the predictability of NWP models, ocean initial conditions for seasonal predictions and climate simulations, open boundary conditions for regional marine ecosystem models, nowcasts of ocean state).

The public, decision-makers and policy-makers all need information based on the best possible science.

The Opportunity New data streams (e.g. Argo, sea surface topography).

Momentum resulting from significant Canadian investment in research programs such as Clivar and GODAE.

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Structure of the ProposalStructure of the Proposal

The proposal built on two themes distinguished by time scale:Theme I: Days to Seasons

Theme II: Seasons to Decadesand the network will work toward a seamless prediction capability that bridges the time-scales

The two themes reflect:• the expertise in both weather and climate modelling and prediction available in Canada• the potential advantages of multi-model approaches• the developing international activities in THORPEX and WCRP COPES melding weather and climate prediction

.

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Theme I ProjectsTheme I Projects

Sub-theme I.1: Ocean Modelling and Data Assimilation

Suppression of bias and drift in ocean model components Statistics of observed variability for model testing and improvement Multivariate assimilation of altimeter and Argo data Ocean reanalysis and forecasting Modelling and assimilation of sea ice

Sub-theme I.2: Coupled AO Modeling and Data Assimilation Assimilation into coupled models Studies on joint assimilation into coupled models Simulation and prediction of variability using a coupled Tropical -

Pacific global atmosphere model

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Mean Sea Surface Topography From SpaceMean Sea Surface Topography From Space

Observed from space Comparison with model

What is the message here?

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Theme II ProjectsTheme II ProjectsSub-theme II.1: Analysis and Mechanisms Tropical Modes: El Niño - Southern Oscillation and the MJO Pacific Decadal Oscillation, Southern and Northern Annular Modes

Sub-theme II.2: Predictability of the Coupled System Potential predictability of current and future climates Prognostic predictability from ensembles of coupled model simulations

Sub-theme II.3: Prediction Coupled Model Initialization The Coupled Model Historical Forecasting Project Forecast Combination, Calibration and Verification

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SS

T A

NO

M

1997-98 El Nino

SS

T A

NO

M

1982-83 El Nino

Obs. Obs.

EnsembleAvg.

EnsembleAvg.

Initial coupled model NINO3.4 SST prediction

attempts using the CCCma CGCM

1988-1989 La Nina

SS

T A

NO

M

Obs.

EnsembleAvg.

SS

T A

NO

M

1975-1976 La Nina

Obs.

EnsembleAvg.

1 2 3 4 5 6 7 8 9 10 11 12 Forecast range (months)

1 2 3 4 5 6 7 8 9 10 11 12 Forecast range (months)

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Science Criterion: Proposal must be scientifically sound

Ocean data assimilation

Ocean Analysis and forecasting

•Regional

•Global

Role of eddies

Applications

Analysis and mechanisms

Predictability of the coupled system

•Diagnostic

•Prognostic

Coupled forecast initialization

Coupled historical forecasting project

Verification

•Data assimilation

•Coupling

•Analysis methods

•Modes of variability

•Limits to predictability

•Value of forecasts

Theme I Theme IITheme I Theme II

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Summary of Science PlanSummary of Science Plan• Tackling an important scientific and technical issue: Prediction and

predictability of the atmosphere ocean system on time-scales of days to decades. Part of an international effort involving many major research centers. Connections to GODAE, CLIVAR, THORPEX, WCRP COPES initiative.

• Clear, feasible research plan based on 15 projects organized in two themes. Joint activities, and mechanisms for collaboration between themes, have been identified.

• Network brings together Canadian research groups that have previously worked independently (e.g. atmosphere and ocean data assimilators, east coast regional ocean modellers and west coast climate modellers) leading to synergistic collaborations.

• Builds on previous Canadian research efforts and investments in support of Clivar, GODAE and Argo.

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The Network will …The Network will … Build on existing expertise in universities and government in ocean, atmosphere and coupled modelling

Accelerate development of Canadian expertise in the assimilation of ocean data and the generation of ocean products

Produce research leading to skillful seasonal-interannual-decadal predictions of social and economic value to Canada

Contribute new knowledge to the coupled predictability problem spanning time-scales of days to decades

Move Canada toward a seamless prediction capability

Make a strong contribution in the training of highly qualified personnel

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The network has 3 major partners: EC, DFO and DND

It also has international links (Clivar, GODAE, THORPEX, Mercator)

Co-applicants represent 7 universities. Each has a strong research record and plays a clearly defined role.

The co-applicants have diverse backgrounds e.g. 8 out of the16 co-applicants are adjuncts 9 of the co-applicants are in Theme I, and 7 in Theme II 6 co-applicants have primarily atmospheric expertise, 8

oceanographic, and 2 interdisciplinary

Given the co-applicants’ diverse backgrounds, there is great potential for interactions that will cross traditional boundaries, and lead to cross fertilization of ideas and techniques

Partners and InteractionsPartners and Interactions

Myers (UA)

Boer, Flato, Fyfe, Merryfield

(UVic)

Tang (UNBC) Demirov

(MUN)

Derome (McGill)Gauthier (UQAM)

Foreman, Hsieh (UBC)

Greatbatch, Ritchie, Thompson, Wright

(Dal)

Stacey (RMC)

The Need for a Network ApproachThe Need for a Network Approach

Institution Discipline Theme

Adjunct

Academic

Atmos

Ocean

Theme I

Theme II

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Expertise and ExperienceExpertise and Experience

Co-applicants have the required range of expertise: ocean and atmospheric modelling and assimilation, NWP and climate prediction, dynamics, parameterizations and skill assessment

Past involvement in large, collaborative and successful research programs and projects

Experience with technology transfer and development of operational systems (e.g. NWP, seasonal climate predictions and storm surge forecasting)

Ongoing involvement in international programs

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Need for Funds and LeveragingNeed for Funds and Leveraging

77% of funds for training of HQP

No duplication of existing funds

Builds on, and feeds into, existing and planned government initiatives (e.g. seasonal prediction, intergovernmental initiative, Argo)

Highly leveraged

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• Canada will slip further behind those nations with operational weather forecast centers that are beginning to use coupled models. In five years CMC will still be issuing 1-season forecasts using a 2-tier approach, even though their competitors are issuing multi-season forecasts based on coupled models.

• Development of research, and an operational capability, in ocean data assimilation will not accelerate.

• Canada will not advance significantly in operational ocean forecasting over the next 5 years and will not be able to respond adequately to the growing demand for ocean products.

• Ocean products will have to be imported and this could be both costly

and ineffective in terms of meeting Canada’s specific needs.

Reverse Impact Statement: Reverse Impact Statement: What if the study is not funded?What if the study is not funded?