Global warming projections derived from an observation-based minimal model
- Department of Mathematics and Statistics, UiT The Arctic University of Norway, Tromsø, Norway
Abstract. A simple conceptual model for the global mean surface temperature (GMST) response to CO2 emissions is presented and analysed. It consists of linear long-memory models for the GMST anomaly response ΔT to radiative forcing and the atmospheric CO2-concentration response ΔC to emission rate. The responses are connected by the standard logarithmic relation between CO2 concentration and its radiative forcing. The model depends on two sensitivity parameters, αT and αC, and two "inertia parameters," the memory exponents βT and βC. Based on observation data, and constrained by results from the Climate Model Intercomparison Project Phase 5 (CMIP5), the likely values and range of these parameters are estimated, and projections of future warming for the parameters in this range are computed for various idealised, but instructive, emission scenarios. It is concluded that delays in the initiation of an effective global emission reduction regime is the single most important factor that influences the magnitude of global warming over the next 2 centuries. The most important aspect of this study is the simplicity and transparency of the conceptual model, which makes it a useful tool for communicating the issue to non-climatologists, students, policy makers, and the general public.