1. Forecasting and Uncertainties GLOBEC Program DiLorenzo Bond Ballerini Brodeur Collie Hastings Kimmel Ribic Strub Wiebe

2. What we learned from GLOBEC Improvement of physical/biological dynamical model (e.g. ROMS, FVCOM, NPZD, IBM) Trained a generation of multi-disciplinary (e.g. from observationalist to modelers, from biologist to physical scientist) Appreciation of the importance of forecast

3. What processes can we model? using Dynamical and Statistical models 1) Processes that we understand and model that can lead to forecast. 2) How to propagate uncertainties in current and future states of the physical/biological system, both observed and modeled. 3) Still limitations due to lack of observations to assemble statistics.

4. Dynamical and Ecosystem Regional Models ROMS 3D circulation model upwelling transport dynamics changes in property distribution vertical distribution and mix layer stratification COAMPS, RSM upwelling winds boundary layer dynamics (e.g. fog) heat/fresh water fluxes Satellite products (winds, SST, SSH, CHL- a) NPZD CHL-a distribution Nutrient distributions Zooplankton Parameters uncertainty FVCOM tidal and estuarine environment surface currents and transport baroclinic eddy circulation

5. What is the role of the dynamical models in forecasting? Large-scale variability: ENSO, NAO, SAM, PDO, NPGO, etc. forecast the delayed ecosystem response dynamical model 20% regression model 80% nowcast of unobservable states

6. What is the role of the dynamical models in forecasting? Dynamical model can be used to compile statistics and constrain the processes that we understand Statistical characterizations of things we cannot model Bayesian/Hybrid Modeling Frameworks A possible approach

7. Need for specific examples of forecasting Outcomes: we learn from trying relative merit of different approaches synthesis activity in that it forces us to define what we really understand and model

8. Recommendation for present projects: Obligation to assess uncertainties in models Sources of error and measures of skill Sources of uncertainties and relative importance Summary of modeling applications

9. Future recommendations: Pilot forecasting experiments with interdisciplinary team. Real time basin-wide physical-biological model in assimilative mode to give a first order estimate of the states. Continue the development of low-dimensional or simple models. GLOBEC involved in IPCC assessments

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