1. Components of the Global Climate Change Process IPCC AR4

2. Detection: e.g. Monitoring & Description Attribution: e.g. Research & Analysis Prediction: e.g. Models & Projections Impacts (ecological, human, infrastructural, socio-economic): e.g. Projections & Assessments Adaptation: e.g. Management & Design Mitigation: e.g. Policy & Technology Other Decision- and Policy-making Potential Elements of a Conceptual Framework for approaching NW Atlantic Climate Change and Impacts Typical Components of a Climate Change Program Science Other Sectors

3. The Nature of Climate Atmosphere-Ice-Ocean-Biosphere –A coupled & nested complex system –Pronounced geographic & temporal variability Natural Modes of Variability Weather: Present state or short-term (days to years) variability –Some short-term predictability (days to seasons) Climate: Statistics of Weather over period (decades) and region –Large spatial and significant temporal variability –Multiple forcings (pressures) –Very limited predictability => Need stochastic (probabilistic) approach

4. Greater complexity, nonlinearity and variability Greater anthropogenic pressures The Nature of Ecosystems (and Human Populations) Future Projection of Climate Change, Impacts & Adaptation A Formidable Challenge! - How to deal with uncertainty

5. Complexities & Semantics of Climate Change & Attribution UNFCCC & Simplest Terminology –“Climate Variability” is Natural Variability –“Climate Change” is Anthropogenic variation (typically assumed as trend or shift) But: Natural & anthropogenic variations are inter-related & difficult to separate “Natural modes of variability” will probably dominate over anthropogenic changes for some properties in next few decades It is the “Natural + Anthropogenic” variations that matters

6. IPCC & A More Sophisticated Scientific Terminology “Climate Change” is a change of climate statistics (e.g. 30 yrs) over time can include both natural and anthropogenic variations –Anthropogenic changes can be trends, shifts, or changes in statistics (e.g. extremes) –Natural changes can be trends, shifts of changes in statistics

7. Observed Change on Ocean Heat Content (IPCC AR4) Linear trends (1955–2003) of change in ocean heat content per unit surface area (W m–2) for the 0 to 700 m layer, based on the work of Levitus et al. (2005a). The linear trend is computed at each grid point using a least squares fit to the time series at each grid point. The contour interval is 0.25 W m–2. Red shading indicates values equal to or greater than 0.25 W m–2 and blue shading indicates values equal to or less than –0.25 W m– 2

8. Ocean Climate of the NW Atlantic Shaped by “Regional” Factors - Labrador Current in subpolar gyre - Arctic outflows (T, S, ice, other) - Seasonality from continental lee - Freshwater run-off from St Lawrence & other - Local & advected sea ice - Proximity to Gulf Stream & subtropical gyre - Complex regional coastline & bathymetry Strong natural temporal variability from: - Seasonal cycle - Variable jet stream & polar-subtropical air mass boundary - Regional modes of coupled air-sea-ice system (e.g. NAO) which have rich temporal structure - Continental and subtropical influences Difficulties with “downscaling” climate change projections from coupled global models (e.g. IPCC) which don’t have good representations of some of these “regional” factors; => Difficulties in developing regional climate change projections Temperature at 100m in Season

9. Potential Elements of Conceptual Framework for approaching Ocean Climate Change in the NW Atlantic - I Identify relevant time horizons, considering potential changes & societal context “ Near Term”, e.g. 2010-2025: Perturbed natural variability? “Mid Century”, e.g. 2040-2060: Emerging new regional climate-/eco-system? “Late Century”: e.g. 2080-2100: A scary new world?

10. Potential Elements of Conceptual Framework for approaching Ocean Climate Change in the NW Atlantic - II Triage regional ocean climate components & variables as to their likelihood, and impacts of change : likelihood from global vs regional effects, observed & theoretical support, etc. impacts from vulnerability, adaptive capacity, socioeconomic value, etc. towards a risk assessment essential to consider both uncertainties & risks