1 KLAUS KELLER Department of Geosciences, Penn State with contributions from Catherine Brennan, David McInerney, and Richard Matear NOAA Climate Observation Program 4th. Annual Systems Review May 2006, Silver Spring, MD What are the implications of a potential MOC collapse for the design of ocean observation systems?

2 Climate Change can be abrupt when thresholds are crossed. Data from Meese et al. (1994) and Stuiver et al. (1995). 20 year running mean,  O 18 -temp conversion based on Cuffey et al, What is a climate threshold? - -Would we have enough warning time? - -How could we improve the warning time? - -What are open challenges?

3 What is a climate threshold? - -A negative feedback switches to a positive feedback loop. - -The response can occur faster than the forcing and show hysteresis. - -An actionable early warning sign (before the forcing threshold is crossed) may be of considerable economic value. - -Prediction (not just detection) is the relevant task for many decision-making frameworks. - -How does this relate to ocean circulation changes?

4 Pictures: Rahmstorf (1997, left) and Stocker et al (2001, right, modified) The North Atlantic meridional overturning circulation (MOC) may collapse in a threshold response to anthropogenic forcing. What would be possible impacts of a MOC collapse?

5 What are the implications of a potential MOC collapse for the design of ocean observation systems? A MOC collapse has been interpreted as “dangerous anthropogenic interference with the climate system” [O’Neil and Oppenheimer, 2002].

6 Designing observation systems requires: (i) (i) Fundamental advances in the disciplines; and (ii) (ii) A solid integration across disciplines.

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8 Current MOC predictions are deeply uncertain. Schmittner et al, 2005

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10 Would we have enough warning time? Vellinga and Wood [2004] –Detection of MOC changes is possible within decades (neglecting structural and observational uncertainties). Baehr et al (2006); Keller et al (2006); Brennan et al (2006) –Decadal-scale hydrographic transects may well fail at reliably detecting MOC changes within this century. –A continuation of the 26 o N MOC observation array could succeed in detecting MOC changes within this century. –These conclusions are somewhat robust across models, forcing scenarios, and initial conditions. –The economic value of information associated with a skillful MOC prediction can be on the order of billions of US$. Early detection may well be possible with currently know systems. What about early prediction?

11 Modified simple box-model from Zickfeld et al (2004) with superimposed AR(1) process error to mimic time-series properties of more complex models. A simple model that mimics the underlying dynamics and internal variability and may provide some robust insights. How can we quantify detection and prediction times?

12 Deriving Detection and Prediction Times Detection: –Extension of the Santer et al (1995) bootstrap method to account for uncertainty in observations and the initial conditions. –Simple Frequentist hypothesis testing. –Use the high sensitivity case to generate potential future observations. –Detection time: When can one reject H o of the unforced state with p < 0.05? Prediction: –Bayesian data assimilation using Markov Chain Monte Carlo and the Metropolis Hastings algorithm. –Likelihood function accounting for autocorrelated errors [Zellner, 1964]. –Uncertainty about a single parameter, the NA hydrological sensitivity, with prior uniform range taken from Zickfeld et al (2004). –Prediction time: When are the predictions to 95 % correct about the threshold crossing? This approach neglects several important uncertainties. Considering these uncertainties would likely strengthen our forthcoming conclusions. Would observing the MOC intensity alone enable early prediction?

13 Observation systems designed for early detection may fail at the task of early prediction. - -Detection and prediction times are random variables. - -Early detection may well be possible based on MOC observations alone. - -Ocean observation systems designed for early detection of MOC changes may be insufficient for early prediction of a future MOC collapse. - -Early prediction could be achieved using a fingerprint with a higher signal-to-noise ratio.

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15 CSIRO model results, cf. Brennan, Matear, and Keller (2006) Hydrographic tracers may show a larger signal-to-noise ratio than reconstructed flows. Maximum overturning in North Atlantic Average oxygen concentration 45-60N, m.

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17 Extension of the DICE model (McInerney and Keller, 2006) What are economically efficient risk- management strategies? MOC model

18 - -Economically “optimal” risk management under uncertainty and learning about the MOC sensitivity (cf. Keller et al, 2004) – –The economic value of information associated with a skillful early prediction might be nontrivial. – –What would be the order of magnitude benefit-cost ratio for an early warning signal? Reducing the uncertainty about future climate thresholds can improve risk- management strategies. Keller et al (in prep)

19 Early prediction capabilities of the MOC response can have significant economic value. Keller et al (in prep) Value: One the order of billions of U.S. $ in this very simple example. Price: So far unknown (as we have not done the science yet). Note: typically implemented observation systems cost on the on the order of millions.

20 Main Conclusions  The currently well tested praxis of relatively infrequent and uncertain MOC observations would likely fail in detecting MOC changes within this century.  Continuing observations similar to the 26 o N MOC observation array could succeed in detecting anthropogenic MOC changes within this century.  Prediction of threshold crossing is the relevant task for many decision-making frameworks.  Observation systems designed for early detection may fail at the task of early prediction.  Adding frequent and dense tracer observations (e.g., oxygen or CFC) is a promising strategy to improve the MOC prediction capabilities and may well be part of an economically efficient risk management strategy.

21 Some Background Information K. Keller, C. Deutsch, M. G. Hall and D. F. Bradford: Early detection of changes in the North Atlantic meridional overturning circulation: Implications for the design of ocean observation systems. Journal of Climate, in the press, (2006). K. Keller, M. Schlesinger, and G. Yohe, Managing the risks of climate thresholds: Uncertainties and information needs (An editorial essay), Climatic Change, in the press, (2006). D. McInerney and K. Keller: Economically optimal risk reduction strategies in the face of uncertain climate thresholds Climatic Change, in the press (2006). K. Keller, D. McInerney, and B. Haupt, Early detection versus prediction of ocean circulation changes: Implications for the design of observation systems. EOS, 87(36) Ocean Sci. Meet. Supp. (2006). C. Brennan, R. Matear, and K. Keller, Detecting changes in the North Atlantic meridional overturning circulation using oxygen trends, EOS, 87(36) Ocean Sci. Meet. Supp., (2006). K. Keller, M. Hall, S.-R. Kim, D. F. Bradford, and M. Oppenheimer: Avoiding dangerous anthropogenic interference with the climate system, Climatic Change, 73, , (2005). D.-H. Min and K. Keller: Errors in estimated temporal tracer trends due to changes in the historical observation network: A case study of oxygen trends in the Southern Ocean. Ocean and Polar Research, 27(2), (2005). K. Keller, B. M. Bolker, and D. F. Bradford: Uncertain climate thresholds and economic optimal growth, Journal of Environmental Economics and Management, 48, (2004). K. Keller, R. D. Slater, M. Bender and R. M. Key: Possible biological or physical explanations for decadal scale trends in North Pacific nutrient concentrations and oxygen utilization, Deep-Sea-Research, II, 49, (2002). K. Keller, K. Tan, F. M. M. Morel, and D. F. Bradford: Preserving the ocean circulation: Implications for climate policy, Climatic Change, 47 (1-2) (2000). N. Gruber, K. Keller, and R. M. Key: What story is told by oceanic tracer concentrations? Science, 290, 455, 2000.

22 Open Challenges  What kind of observation and analysis system could deliver a skilled early prediction of a potential threshold response across the relevant parametric and structural uncertainties?  How can we use historic and paleo-observations to better constrain MOC predictions?  Which future observations would improve the MOC forecast skill the most?  What would be an “actionable early warning signal”?  How do stakeholders and decision-makers rank different strategies under deep uncertainty?  What are robust risk management strategies in the face of deeply uncertain climate thresholds?