ADAPTIVE STRATEGIES IN CLIMATE CHANGE MANAGEMENT

Strategies for managing the effects of climate change generally rely on predictions from a range of models in order to inform future courses of action. However, these predictions are shrouded in uncertainty meaning corrective/adaptive actions will be inevitable as new information becomes available. We have been employing techniques used in control systems analysis to investigate the dynamic implications of these adaptive actions in global climate mitigation and hence to explore what constitutes ‘robust’ approaches to the handling of uncertainty in real-time decision making.

We are currently applying adaptive control techniques to evaluate the management of uncertainty for a range of climate geoengineering technologies in an EPSRC funded project: Integrated Assessment of Geoengineering Proposal (IAGP).

This figure shows the results of a simulation exercise demonstrating the effect of increasing the adaptive capacity of a sequential decision making regime when attempting to drive global mean surface temperature to +2°C under uncertainty (courtesy of Dave Leedal's PhD thesis)

Jarvis AJ and Leedal DT. The geoengineering model intercomparison project: A control perspective. (In press) (pdf)

Jarvis, A; Leedal, D; Taylor, CJ, et al.(2009) Stabilizing global mean surface temperature: A feedback control perspective. Environmental Modelling and Software, 24, 665-674 (pdf)

Jarvis AJ, Young PC, Leedal DT and Chotai A. (2008) A sequential CO₂ emissions strategy based on optimal control of atmospheric CO₂ concentrations. Climatic Change, DOI 10.1007/s10584-007-9298-4

Simple Climate Models

Much of our work relies on understanding the relationship between complex systems such as the Earth’s climate and our conceptualisation of the ‘important’ behavioural features of these systems that we may wish to account for when making decisions. Often we express these important or dominant dynamic features in the form of ‘simple’ climate models. Such models are extremely useful in climate research because, not only do they allow for rapid evaluations of broad portfolios of climate decision making options, they can also be used to attempt to understand what dynamic behaviours might emerge when societal actions are coupled to that of the climate system. It is also important to be able to understand how simple descriptions of the climate system relate to that of the real climate system in order to provide credibility to assessments made using simple models.

These figures show the relationship between the strength of feedbacks in a range of climate models and the timescale over which these feedbacks operate. Despite the complexity of the climate model under investigation, the feedbacks operating on global mean surface temperature lead to rather simple aggregate responses which, in turn, lend to rather simple model dynamics (see Jarvis (2011)).

Jarvis AJ (2011) The magnitudes and timescales of global mean surface temperature feedbacks in climate models. Earth System Dynamics, 2, 213–221 (pdf)

Jarvis AJ and Li S. (2010) The contribution of timescales to the temperature response of climate models. Climate Dynamics ( DOI 10.1007/s00382-010-0753) (pdf)

Li, S; Jarvis A (2009) Long run surface temperature dynamics of an A-OGCM: the HadCM3 4xCO(2) forcing experiment revisited. Climate Dynamics, 33, 817-825 (pdf)

Li, S; Jarvis, AJ; Leedal, DT (2009) Are response function representations of the global carbon cycle ever interpretable? Tellus, 61B,361–371 (pdf)