The Anthropogenic Earth System: Modeling Social Systems, Landscapes, and Urban Dynamics as a Coupled Human+Climate System up to Planetary Scale (TAES) Session 1
Time and Date: 10:00 - 12:30 on 21st Sep 2016
Room: I - Roland Holst kamer
Chair: John T. Murphy
|32000||Introduction, Session Scope, Structure, and Goals||Murphy, John T.; Zellner, Moira; and Filatova, Tatiana|
|32001|| Economic impacts and damages in integrated assessment models: bridging the gap between micro and macro
Abstract: Climate change is causing substantial disruption of socio-economic systems around the world. Climate mitigation and adaptation measures are vital and require careful analysis of economic costs and benefits. Integrated Assessment Models (IAMs) are widely applied for these purposes in an attempt to support policy decisions. Despite their recent advancements, IAMs still suffer from substantial methodological limitations risking to mislead policy makers (Stern, 2016). It is argued that IAMs should further improve on the following assumptions: (i) a rough assessment of impacts on broad aggregated regions assuming a representative economic agent, (ii) a focus primarily on the reduction of economic output due to climate impacts ignoring destruction of livelihoods, loss of life and migration, (iii) assuming an incremental change in the GDP loss as temperatures increase ignoring the presence of potential tipping points, (iv) absence of learning, (v) simplified representation of technological change in the energy sector (Pindyck, 2013; Farmer et.al. 2015; Burke et.al. 2016). Together with the traditional problems with intergenerational discounting these issues form a significant challenge for the scientific community. Significant research effort is being invested currently in improving (iv) and (v), which both alter the estimation of costs of mitigation. Estimation of benefits of mitigation ? i.e. avoided losses (i-iii) ? did not yet received enough attention. The main issue here is that adverse impacts of climate change are quite unevenly distributed between regions and various socio-economic groups within them. Global damage estimates are likely to be significantly different if this heterogeneity, interactions between various entities, endogenous learning and non-linearity in economies reactions to climate is accounted for. While a myriad of local empirical studies provides an ample evidence that it matters for the overall damage assessment, the task of aggregating and finding general patterns and processes in this body of knowledge is not easy. We discuss the potential ways to address this problem.Firstly, we review the general approaches to estimate climate-driven economic impacts and damages in IAMs on the macro level. Then we outline how regional and local studies approach the same issue accounting for micro-level processes. We finally discuss few alternative approaches to bridge the two. To what extent can this gap be covered by adjusting the existing IAMs design? Should a completely different approach be taken by constructing the entire global economy from the bottom up? What are the risks and advantages of using a suit of models or nested model as a compromise solution? During the conference we would like to discuss these issues and corresponding pros and cons of each of the alternatives. References:Burke, M., et.al. Opportunities for advances in climate change economics. Science, 2016. 352(6283): p. 292-293.Farmer, J.D., C. Hepburn, P. Mealy, and A. Teytelboym, A Third Wave in the Economics of Climate Change. Environmental Resource Economics, 2015. 62: p. 329?357.Pindyck, R.S., Climate Change Policy: What Do the Models Tell Us? Journal of Economic Literature, 2013. 51(3): p. 860?872.Stern, N., Current climate models are grossly misleading. Nature, 2016. 530: p. 407-409.
|32002|| Integrating human agency in global land change models to advance integrated assessment
Abstract: Human agency is a main determinant of land use and global land use change emerges from individual land use decisions in response to driving factors operating across multiple spatial and temporal scales. However, in global integrated models used for climate assessments, land use change is either presented by simplified aggregate decision making using profit optimization assumptions or by heuristics accounting for location suitability. There is a common understanding that there is a need to better represent (variation in) human agency in such large scale land use assessments (Rounsevell et al., 2014; Verburg et al., 2016).In this presentation I will discuss how a systematic review of case-studies on land use change is used to characterize different human land use decision mechanisms and how these are linked to contextual conditions. Based on this empirical knowledge land change models may vary their behavioral assumptions across time and space to better represent variation and evolvement of human agency. In the context of climate change a representation of human agency should capture feedbacks between land use change and climate change beyond the physical responses, i.e. in terms of mitigation and adaptation behavior. A first idea on including such feedbacks and constraints in model implementation is discussed.References:Rounsevell MDA, Arneth A, Alexander P, Brown DG, De Noblet-Ducoudr? N, Ellis E, Finnigan J, Galvin K, Grigg N, Harman I, Lennox J, Magliocca N, Parker D, O'Neill BC, Verburg PH, Young O. 2014. Towards decision-based global land use models for improved understanding of the Earth system. Earth Syst. Dynam., 5, 117-137. http://dx.doi.org/10.5194/esd-5-117-2014Verburg PH, Dearing J, Dyke J, Leeuw Svd, Seitzinger S, Steffen W, Syvitski J. 2015. Methods and Approaches to Modelling the Anthropocene. Global Environmental Change doi: 10.1016/j.gloenvcha.2015.08.007
|Verburg, Peter H.|
|32003|| Global Scale Feedbacks Between Climate and Land-Use in the Integrated Earth System Model
Abstract: Until recently, projections of future climate have been obtained by first projecting the evolution of society ? in particular human energy and land-use activities ? and then examining the implications of those activities on climate and ecosystems within Earth system models.Typically, these assessments have not considered feedbacks from climate and ecosystem change onto the evolution of society and therefore energy and land-use, which are the primary anthropogenic drivers of climate change. Here we present the rationale for and theoretical basis of a coupled model framework known as the Integrated Earth System Model (iESM) that combines the physical representations of an Earth System Model with the human system representations of an Integrated Assessment Model. We demonstrate a previously unexplored feedback whereby future climatic, biological, and geochemical changes influence the productivity of land resources and therefore the evolution of land-use, agriculture, bioenergy use, and fossil fuel emissions. We further decompose this effect into the separate influences of climate change and the elevated CO2 concentrations, and we examine the role of climate mitigation policies in affecting the magnitude and nature of this feedback. The synchronous coupling of human and Earth systems in the iESM is enabled by a generalized software framework that could in principle accommodate a wide variety of human and Earth system models with varying levels of spatial and temporal resolution, as well as process detail. We discuss key lessons learned in building such an architecture and highlight the theoretical and practical challenges encountered in coupling models that represent linked processes at fundamentally different scales.
|Jones, Andrew D.|
|32004|| Faraway, so Close: An Agent-Based Model for Climate, Energy and Macroeconomic Policy Analysis
Abstract: This paper presents an agent based model for the study of coupled economic and climate dynamics that endogenously co-evolve across a range of different scenarios. The model offers a flexible laboratory to test various combinations of macroeconomic, industrial and climate policies both in the context of long run economic growth and medium run transition towards a greener economy. Furthermore, we propose a stochastic description of the feedbacks stemming from a warming and more volatile climate and study how such negative shocks propagate through the economy. For this reason, the model is particularly well suited for the study of extreme climate events, which are usually forgotten by standard integrated assessment models.