The GWPF has a fascinating paper published recently which is attracting much attention. The author:
Anastasios Tsonis is distinguished professor of atmospheric sciences at the University
of Wisconsin-Milwaukee. He is also an adjunct research scientist with the Hydrologic
Research Center in San Diego.
It starts off talking about ENSO (El Nino/La Nina/Southern Oscillation) and how the frequency of these major modes of weather in the tropical pacific appears to be related to warming/cooling episodes. Basically, Tsonis notes that, as predicted by climate modeling, El Nino episodes appear to occur more often when the global climate is actively warming, and conversely, La Nina episodes predominate when cooling happens. This ties in with what Bob Tisdale has been saying for years, that El Nino events ‘step up’ global warming in discrete stages.
Tsonis identifies four distinct phases or global temperature regimes from the beginning of the 20th century: the 1910-1940s rapid warming, the 1960s cooling, the 1976-98 rapid warming and the ‘pause’ after 1998 (which bizarrely is not evident in the ‘pause-busting’ dataset which he chooses to illustrate the stages – GISS).
The author then goes on to talk about damped oscillating systems, e.g. a simple swinging pendulum and a spring-loaded pendulum. In the case of the simple pendulum, air resistance will eventually bring the pendulum to a predictable fixed position (i.e. at rest, pointing straight down, in line with the force of gravity), no matter from which position the pendulum is initially swung from. In the case of the spring-loaded pendulum, the predictable equilibrium position is not a fixed point but a limit cycle : the motion
is periodic and any fluctuation away from that limit cycle is damped back to the cycle. Such “systems with a fixed point or a limit cycle are said to have Euclidean attractors [equivalent to the equilibrium resting point or limit cycle] and they are predictable: the final state of the system can be known, regardless of the initial condition”. In the case of the climate, however, we have a highly non-linear system and an equilibrium position which is not at all easy to predict using a few simple equations: there is a degree of chaos at work within the system and the fractal determining which way the system will go is said to be a strange attractor. The system thus appears to be random but is in fact deterministic; it’s just that the outcomes are rather more complex to determine!
Tsonis goes on to identify four internal climate subsystems [ENSO, PDO, NAO and the North Pacific Index, NPI] which are associated with the strange attractors of the climate system. It turns out that the behaviour of these internal subsystems and in particular the ways in which these subsystems interact with one another is the key to determining how the system will evolve.
Tsonis then identifies two modes of interaction in operation between these subsytems: synchronisation and coupling. Imagine four swimmers: when they are all swimming in the same direction, doing the same stroke, at the same speed, they are synchronised, but independent. However, if a rope is tied around all their waists, they are physically constrained to move non-independently and are said to be coupled.
Now, as Tsonis explains:
The theory of synchronised chaos predicts that in many cases when such systems synchronise, an increase in coupling between the oscillators may destroy the synchronous state and alter the system’s behaviour.
This principle applies equally in the climate system. Coupling tends to disrupt synchronisation and propel the system abruptly into a new state. Tsonis illustrates the main periods of synchronisation and coupling present in the instrumental global surface temperature data:
As you can see, coupling occurs at the junctures of major shifts in climate: the commencement of 1910-1940s warming; the start of the mid-century cooling period; the re-commencement of rapid warming post 1976, and the pause after 1998. Tsonis says of these shifts:
This mechanism appears to be intrinsic to the climate system: it is found in both control and forced climate simulations. It also appears to be a very robust mechanism. In all 13 synchronisation events found in the observations and model simulations, when the modes are synchronised and the coupling begins to increase, then at some coupling strength threshold synchronisation is destroyed and the system shifts to a new state.
Thus the author appears to have identified a robust predictor of when changes in climate will occur, simply by examining four different modes of internal variability and their interactions. Now, pay attention please, because this is where it gets really interesting. Tsonis asks the question:
When the network is synchronised, does the coupling increase require that all modes must become coupled with each other? To answer these questionsWang et al. split the network of four modes into its six component pairs and investigated the contribution of each pair during each synchronisation event and in the overall coupling of the network. They found that one mode is behind all climate shifts. Surprisingly, the mode concerned is not ENSO but the NAO: it is, without exception, the common ingredient in all shifts in the climate regime and when it is not coupled with any of the Pacific modes no shift ensues . . . . .
Thus, the results indicate not only that NAO is the instigator of climate shifts but that the likely evolution of a climate shift has a path in which the north Atlantic couples to the north Pacific, which in turn couples to the tropics. [my emphasis].
The NAO of course, is a reasonable proxy measure of the AMO/AMOC, and numerous studies indicate a connection between solar variability (in particular solar UV variability) and NAO (e.g., whether it is predominantly positive of negative during northern hemisphere winters). So, all things considered (AMO peaking and turning negative, solar activity declining rapidly, perhaps to a new grand solar minimum), it looks very much like a major shift in climate is due very soon. Of course, this may be a recommencement of rapid warming, but I wouldn’t throw too much money into climate hedge funds along the lines of that particular scenario happening.