As we keep saying about the Met Office’s reliance on computer modelling, ‘rubbish in’ derives ‘rubbish out’.
As this piece shows, it’s not just a matter of whether the Met Office models for the stratosphere are right or wrong; it is the absence of peer review and appalling management of their data, coupled with an inability to explain or reproduce the methodology that was used to arrive at their results.
How can any government or organisation have trust or confidence in the findings and forecasts of an entity that has such a slapdash approach to scientific method?
Never mind. The UK government has the Met Office’s back. Most of the media will turn a blind eye to play down public awareness. MPs will stay quiet on the subject in the House of Commons. Public money will continue being poured into Met Office wheezes and climate alarmism campaigns; and the tidy bonuses will continue to flow to its executives.
The science is not important. The money train must be kept running.
Autonomous Mind 
The raw data is available to anyone. If nobody does a published analysis, noone is forced to use an unpublished one. If you borrow a friend’s car you don’t bitterly complain to him if the aircon doesn’t work because he’d tell you to sod off and buy your own.
Even if you didn’t know much about models you might realise it is unlikely that the SSU data is used to “drive” models when models are producing their own inconsistent values – strange the author of the piece cannot see that!
There are many examples where models have produced results that are inconsistent with data because very many of the data products (including those produced by sceptics such as Spencer and Christy) were and remain questionable due to sampling and instrument uncertainties.
This is perhaps yet another example which demonstrates the importance of using models to validate and cross-check data. It also demonstrates that the models are not in anyway twisted to fit the data.
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