New understanding of ultra-long timescales provides a new take on climate.
London, 6 April 2018 A newly published paper in the journal Physica A suggests that there is an undiscovered universe all around us that we are too short-lived to perceive.
Authors Prof. Christopher Essex (Applied Mathematics, University of Western Ontario) and Prof. Anastasios Tsonis (Mathematical Sciences, University of Wisconsin-Milwaukee) explain that even without external influences (e.g. man-made carbon dioxide) the weather patterns change over very long timescales, locally and globally.
If some elderly person claims to recall summers, say, that were different when that person was a child, that may not be faulty memory. Just because summers seemed warmer or colder; spring or winter seemed sooner; more or less snow was recalled, it doesn’t follow that the climate system has changed in any meaningful way.
Prof. Essex explains, “Unlike the stable virtual ‘climates’ seen in computer simulations, corresponding real-world conditions aren’t stable at all. There are perpetual, natural, internal changes in play that take longer than human lifetimes to play out.”
No human will ever fully perceive this change. No one lives long enough. But some astute people, in their later years, might just be able to make a little of it out.
Prof. Essex adds, “There is an ultraslow, mysterious, unseen world out there, under our very noses, that we cannot perceive. It’s beyond our measurement capabilities, and beyond the capabilities of our best computers using our very best physical theories. It belongs to a class of problems that we cannot overwhelm with data, or crush with our biggest computers.”
Nevertheless, there is hope. As Professor Tsonis explains, our growing understanding of the nature of natural ocean modes and how they are linked may open up a whole new field of research into ultra-long timescales taking us beyond the virtual stability of modified meteorological models:
“Ocean modes like the North Atlantic Oscillation and the Pacific Decadal Oscillation, known natural internal dynamical features, affect weather patterns globally over years, decades and longer. They are deep structures that are coming to be understood on their own terms. We understand better than ever how they are linked, and we understand the mathematical structures in play in ways that we could not have only a few decades ago. We are on the verge of being able to predict what they will do next. If we succeed, a hitherto invisible world will open to us. We will see new wonders through new eyes.”
Professors Essex and Tsonis are both members of the GWPF’s Academic Advisory Council.
Christopher Essex and Anastasios A.Tsonis (2018) Model falsifiability and climate slow modes, Physica A, Volume 502, July 2018, Pages 554-562
Highlights
- • Climate models do not and cannot employ known physics fully. Thus, they are falsified, a priori.
- • Incomplete physics and the finite representation of computers can induce false instabilities.
- • Eliminating instability can lead to computational overstabilization or false stability.
- • Models on ultra-long timescales are dubiously stable. This is referred to as the “climate state.” Is it real?
- • Decadal variability is understandable in terms of a specific class of nonlinear dynamical systems.
Abstract
The most advanced climate models are actually modified meteorological models attempting to capture climate in meteorological terms. This seems a straightforward matter of raw computing power applied to large enough sources of current data. Some believe that models have succeeded in capturing climate in this manner. But have they? This paper outlines difficulties with this picture that derive from the finite representation of our computers, and the fundamental unavailability of future data instead. It suggests that alternative windows onto the multi-decadal timescales are necessary in order to overcome the issues raised for practical problems of prediction.
PDF copies of the paper are available on request from the authors
Contact
Prof Christopher Essex
Department of Applied Mathematics, the University of Western Ontario, London, Canada N6A 5B7. essex@uwo.ca
Prof Anastasios Tsonis
Department of Mathematical Sciences, Atmospheric Sciences Group, University of Wisconsin-Milwaukee, Milwaukee, WI 53201-0413, USA. aatsonis@uwm.edu