The BBC’s Matt McGrath has just reported, under the above ‘Climate Change’ headline, the findings of a paper in Nature linking Arctic variability and change with extreme winter weather in the United States (lead author Dr Judah Cohen, a professor at the Massachusetts Institute of Technology (MIT)):
“A new study shows that increases in extreme winter weather in parts of the US are linked to accelerated warming of the Arctic.
The scientists found that heating in the region ultimately disturbed the circular pattern of winds known as the polar vortex.
This allowed colder winter weather to flow down to the US, notably in the Texas cold wave in February. ”.
There are a number of reasons for being highly sceptical – unlike Matt McGrath – about this paper:
- The climate models all show greater warming away from the tropics, and especially more warming in winter than in summer.
- The climate models are known to be particularly weak at regional predictions, which is one major reason why the climate scientists use an ensemble of models for their predictions.
- The scientists have told us repeatedly that no one extreme weather event can be attributed to global warming.
So what is going on, and why are they making these claims?
The answer is in the way that they tune their models.
They have no way of associating the Polar Vortex, or any other major climate feature, with the drivers of climate, other than through their models. So, when an unpredicted event like extreme cold winter weather hits the USA, they go to their models to try to find out why. The way they do this is to tweak the many parameters in the models, until they get a match with what they are looking for. They then analyse how the models got to the answer and proclaim that as the reason for it.
I explained the tuning process a long time ago in How Reliable are the Climate Models?:
“The fourth IPCC report [para 9.1.3] says : “Results from forward calculations are used for formal detection and attribution analyses. In such studies, a climate model is used to calculate response patterns (‘fingerprints’) for individual forcings or sets of forcings, which are then combined linearly to provide the best fit to the observations.”
To a mathematician that is a massive warning bell. You simply cannot do that. [To be more precise, because obviously they did actually do it, you cannot do that and retain any credibility]. Let me explain :
The process was basically as follows
(1) All known (ie. well-understood) factors were built into the climate models, and estimates were included for the unknowns (The IPCC calls them parametrizations – in UK English : parameterisations).
(2) Model results were then compared with actual observations and were found to produce only about a third of the observed warming in the 20th century.
(3) Parameters controlling the unknowns in the models were then fiddled with (as in the above IPCC report quote) until they got a match.
(4) So necessarily, about two-thirds of the models’ predicted future warming comes from factors that are not understood.”.
The same basic process applies in this case – the extreme winter weather in the USA. To explain it, they turned to their models and tried to get the models to replicate it.
When the modellers had tweaked their parameters to match the required extreme winter weather in the USA, they found that all the climate processes involved led back to the increased CO2 in the atmosphere as the cause. Well, surprise, surprise, there was no way that they can ever find any other cause. Why is that? Well, it’s because there are no other possible causes coded into the models.
As I said in the above quoted article, they haven’t coded any of the following into their models as possible causes (mostly because they can’t but partly because they won’t): ENSO (El Nino Southern Oscillation), ocean oscillations, ocean currents, volcanoes, wind, water cycle, sun, GCRs (Galactic Cosmic Rays), Milankovitch cycles, water vapour, clouds. Yes, they have coded some of these into the models to some extent, but not as primary causes of anything, only as constants or almost-constants, eg. the sun, or as features that react to CO2-induced changes, eg. water vapour and clouds (the IPCC calls them feedbacks).
The causes of the extreme winter weather in the USA remain unknown, apart from the obvious reason: the Polar Vortex. The reasons put forward in the above Nature paper are all based on circular logic, because they come only from the climate models when tuned to give the observed result. ie, the result is an input, which is by definition circular logic.
The situation is that the climate modellers do not know what caused the extreme winter weather in the USA, and they won’t get any nearer to knowing while they remain chained to their models.