EGU2020-9464
https://doi.org/10.5194/egusphere-egu2020-9464
EGU General Assembly 2020
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Implications of intrinsic variability for economic assessments of climate change

David Stainforth1,2,4, Raphael Calel1,3, Sandra Chapman4, and Nicholas Watkins2,4
David Stainforth et al.
  • 1London School of Economics, Grantham Research Institute, London, UK (d.a.stainforth@lse.ac.uk)
  • 2London School of Economics, Centre for the Analysis of Timeseries, London, UK (d.a.stainforth@lse.ac.uk, nickwatkins62@fastmail.com)
  • 3Georgetown University, McCourt School of Public Policy, Washington DC, USA (raphael.calel@georgetown.edu)
  • 4University of Warwick, Department of Physics, Coventry, UK (S.C.Chapman@warwick.ac.uk)

Integrated Assessment Models (IAMs) are widely used to evaluate the economic costs of climate change, the social cost of carbon and the value of mitigation policies. These IAMs include simple energy balance models (EBMs) to represent the physical climate system and to calculate the timeseries of global mean temperature in response to changing radiative forcing[1]. The EBMs are deterministic in nature which leads to smoothly varying GMT trajectories so for simple monotonically increasing forcing scenarios (e.g. representative concentration pathways (RCPs) 8.5, 6.0 and 4.5) the GMT trajectories are also monotonically increasing. By contrast real world, and global-climate-model-derived, timeseries show substantial inter-annual and inter-decadal variability. Here we present an analysis of the implications of this intrinsic variability for the economic consequences of climate change.

We use a simple stochastic EBM to generate large ensembles of GMT trajectories under each of the RCP forcing scenarios. The damages implied by each trajectory are calculated using the Weitzman damage function. This provides a conditional estimate of the unavoidable uncertainty in implied damages. It turns out to be large and positively skewed due to the shape of the damage function. Under RCP2.6 we calculate a 5-95% range of -30% to +52% of the deterministic value; -13% to +16% under RCP 8.5. The risk premia associated with such unavoidable uncertainty are also significant. Under our economic assumptions a social planner would be willing to pay 32 trillion dollars to avoid just the intrinsic uncertainty in RCP8.5. This figure rises further when allowance is made for epistemic uncertainty in relation to climate sensitivity. We conclude that appropriate representation of stochastic variability in the climate system is important to include in future economic assessments of climate change.


[1] Calel, R. and Stainforth D.A., “On the Physics of Three Integrated Assessment Models”, Bulletin of the American Meteorological Society, 2017.

 

How to cite: Stainforth, D., Calel, R., Chapman, S., and Watkins, N.: Implications of intrinsic variability for economic assessments of climate change, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9464, https://doi.org/10.5194/egusphere-egu2020-9464, 2020.