The challenge of non-Markovian energy balance models in climate

Author:

Watkins Nicholas W.12ORCID,Calel Raphael13ORCID,Chapman Sandra C.245ORCID,Chechkin Aleksei678ORCID,Klages Rainer1910ORCID,Stainforth David A.12

Affiliation:

1. Grantham Research Institute on Climate Change and the Environment, The London School of Economics and Political Science 1 , Houghton Street, London WC2A 2AE, United Kingdom

2. Centre for Fusion Space and Astrophysics, University of Warwick 2 , Gibbett Hill Road, Coventry CV4 7AL, United Kingdom

3. McCourt School of Public Policy, Georgetown University 3 , 125 E St. NW, Washington DC 20001, USA

4. Department of Mathematics and Statistics, Faculty of Science and Technology, UiT—The Arctic University of Norway 4 , N-9037 Tromsø, Norway

5. International Space Science Institute 5 , Hallerstrasse 6, 3012 Bern, Switzerland

6. Institute of Physics and Astronomy, University of Potsdam 6 , 14476 Potsdam-Golm, Germany

7. Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center, Wrocław University of Science and Technology 7 , Wyspianskiego 27, 50-370 Wrocław, Poland

8. Akhiezer Institute for Theoretical Physics National Science Center “Kharkiv Institute of Physics and Technology,” 8 61108 Kharkiv, Ukraine

9. Centre for Complex Systems, School of Mathematical Sciences, Queen Mary University of London 9 , Mile End Road, London E1 4NS, United Kingdom

10. London Mathematical Laboratory 10 , 8 Margravine Gardens, London W6 8RH, United Kingdom

Abstract

We first review the way in which Hasselmann’s paradigm, introduced in 1976 and recently honored with the Nobel Prize, can, like many key innovations in complexity science, be understood on several different levels. It can be seen as a way to add variability into the pioneering energy balance models (EBMs) of Budyko and Sellers. On a more abstract level, however, it used the original stochastic mathematical model of Brownian motion to provide a conceptual superstructure to link slow climate variability to fast weather fluctuations, in a context broader than EBMs, and led Hasselmann to posit a need for negative feedback in climate modeling. Hasselmann’s paradigm has still much to offer us, but naturally, since the 1970s, a number of newer developments have built on his pioneering ideas. One important one has been the development of a rigorous mathematical hierarchy that embeds Hasselmann-type models in the more comprehensive Mori–Zwanzig generalized Langevin equation (GLE) framework. Another has been the interest in stochastic EBMs with a memory that has slower decay and, thus, longer range than the exponential form seen in his EBMs. In this paper, we argue that the Mori–Kubo overdamped GLE, as widely used in statistical mechanics, suggests the form of a relatively simple stochastic EBM with memory for the global temperature anomaly. We also explore how this EBM relates to Lovejoy et al.’s fractional energy balance equation.

Funder

European Office of Aerospace Research and Development

Science and Technology Facilities Council

Economic and Social Research Council

Natural Environment Research Council

Publisher

AIP Publishing

Reference123 articles.

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