Andrew Jarvis
Lancaster
Environment Centre
Lancaster University
LA1 4YQ
+44 1524
593280
a.jarvis(AT)lancs.ac.uk
Here's a sample of my current research activities.
CLIMATE, ENERGY AND INDUSTRIAL SOCIETY
To date, humans have modified many elements of the Earth system. For global greenhouse gas emissions humans are affecting atmospheric composition, but atmospheric composition is not affecting humans to a degree that causes them to modify their behaviour in relation to global-scale emissions. However, because humans rely on climate one can imagine that, if the significant changes in atmospheric composition were to lead to significant modifications to climate, then these effects will ultimately feedback and affect society. What would emerge would be a coupled climate-society system. This type of feedback could be net positive or net negative depending on how the effects of climate change play out.
Because the long-run pattern of anthropogenic CO2 emissions can be described by exponential growth, any feedbacks of climate on society’s behaviour with respect to emissions can be represented as a climate-related modification of the growth rate of emissions. As a result, it is possible to set up a very simple conceptual framework to demonstrate the effects of global-scale climate-society feedbacks and how they relate to the behaviour of a fully coupled climate-society system.
This figure shows the relationship between the strength of the climate-to-society feedback adopted by society (b) and magnitude of global temperature change that results in a standardised climate model, ΔT. Note how very modest levels of climate-society feedback have very significant marginal returns, but that these quickly evaporate as society becomes progressively more sensitive to climate. Note also that delaying the timing of society becoming sensitised to climate results in the need to adopt ever increasing sensitivity if a socio-political objective of staying below certain levels of climate change were desired (see Jarvis et al., (2012) for details).
Despite nearly 25 years of investigating and negotiating on climate change and emissions produced by humans, it appears we have been unable to impact on the trajectory of emissions which have remained stubbornly near their ‘business-as-usual’ trajectory. Blame for the lack of a climate-society feedback for avoiding dangerous climate change is commonly levelled at the political institutions charged with these negotiations. However, it could be that industrial society has modes of behaviour that subvert any attempts to redirect it from its business-as-usual trajectory. Global primary energy use has, on average, grown at about 2.4 % yr-1 since at least 1850, whilst global CO2 emissions have grown at approximately 1.8 % yr-1 over the same period.
This figure shows the historical trajectory of global primary energy use (E), global anthropogenic CO2 emissions (U), and the carbon intensity of this primary energy, c = U/E. For details of the data sources see Jarvis et al., (2012). Note how both primary energy use and emissions have growth near exponentially, but with differing long-run growth rates leading to a systemic decarbonisation of the global energy portfolio.
This difference in the relative growth rates of primary energy use and emissions arises from the persistent decarbonisation of primary energy at approximately -0.6 % yr-1. This is a surprising observation because over this time society has progressively switched from wood, to coal, oil, gas, nuclear and renewables in complex ways. Arnulf Grubler’s book, Technology and Global Change, provides an excellent introduction to this if you're interested. In a paper currently under review we attempt to show that this fuel switching is driven by simple biosphysical-type process associated with the optimisation of resource acquisition and distribution in support of the long-term growth of industrial society. This coupling of the growth in energy use and emissions is one manifestation of the range of processes against which emissions reduction strategies appear to have to fight. More to follow...
Jarvis, AJ, Leedal DT and Hewitt CN. (2012) Climate-society feedbacks and the avoidance of dangerous climate change. Nature Climate Change, 2 (9). pp. 668-671 (pdf)
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. 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 (2008) Are response function representations of the global carbon cycle ever interpretable? Tellus, 61B,361–371 (pdf)