Met Office Pseudoscience

Met Office Pseudoscience

UK National Weather Service Rushes Out Extreme Weather Attribution Of India/Pakistan Heatwave

Jaime Jessop19 hr ago11

You’ve maybe heard of extreme weather attribution, where ‘scientists’ attempt to attribute a heatwave, storm or flood etc. to man-made climate change, some time after the event. You’ve heard of rapid extreme weather attribution where they fall over themselves to get the attribution done as quickly as possible whilst the event is still fresh in people’s minds and the main stream media hype is still ongoing. Well, our very own Meteorological Office has now gone one better and done a quick-fire rapid attribution whilst the extreme event in question is still in progress. The problem is, so eager have they been to lay the blame on climate change (TM) for what is in fact a not unprecedented or even particularly unusual heatwave, that they’ve shot themselves in the foot.

I’ve already discussed the alleged ‘unprecedented’ heatwave in Pakistan here, which forms part of the same general meteorological setup in that region responsible for the very hot weather this Spring. So it was inevitable that the usual suspects peddling pseudoscientific ‘climate crisis’ alarmism in defence of global communism would get around to telling us all how this is yet another symptom of our ‘pollution’ of the atmosphere with demonic carbon dioxide released by burning fossil fuels. Their go to ‘science’ of course is the climate models. This allows them to put the dodgy rubber stamp of ‘expert authenticity’ on their decidedly dodgy extreme weather attribution pseudoscience which is barely an improvement on reading the tea leaves or chicken entrails.

So without further ado, let us look at this stunning in vivo attribution study and see what it says. Firstly, here’s what the Met Office themselves say it says:

The chances of a record-breaking heatwave in north-west India and Pakistan has been made over 100 times more likely because of climate change says a Met Office study.

Oh no! Like, if we don’t stop pumping CO2 into the atmosphere by this time next Thursday, over a billion Indians and Pakistanis are going to get roasted every other week! OK, not every other week, but once every 3 years, increasing to nearly once a year by the end of the century. The entire population of the Indian subcontinent will have to be relocated to the green and pleasant continent of Antarctica by then, which will be one of the few remaining habitable places on earth. Most of the rest of the planet will be baked desert or under water. Penguins and polar bears ain’t gonna be happy, to be sure.

The study shows that the natural probability of a heatwave exceeding the average temperature in 2010 is once in 312 years. In the current climate – accounting for climate change – the probabilities increase to once in every 3.1 years. And by the end of the century, the study – incorporating climate change projections – shows this will increase to once every 1.15 years.

But hang on, this attribution study was done on the basis of temperatures exceeding the record set in 2010 and yet, they don’t even know if the current observed heatwave will exceed or even match 2010! The models say it’s very likely though, so that’s all OK.

Although a new record is thought likely, climate scientists will have to wait until after the end of the month – when all the temperature records for the April-May period have been collated – to see whether the current heatwave will exceed the levels experienced in 2010.

Not that likely, by the sound of it:

The extreme pre-monsoon heatwave has eased a little after peak temperatures reached 51°C in Pakistan on Sunday.

Paul Hutcheon, of the Met Office’s Global Guidance Unit, said: “However, the heat looks likely to build again from mid-week, peaking later in the week or into the weekend, with maximum temperatures again likely to reach 50°C in some spots, with continued very high overnight temperatures, Through the weekend temperatures are likely to lower again closer to average.

So, if the heatwave does not match up to 2010, do you think that the Met Office will withdraw their real time attribution study? Not bloody likely I’d say, and I don’t even need a sophisticated model run on a mainframe supercomputer to tell me that!

Let’s take a look at the actual study itself:

Sounds really technical and sciency doesn’t it? So it must be legit, cos ‘science’ . . . . . . . . and stuff. But lift the bonnet and you’ll see that the reliable, smooth running engine underneath has blown a gasket, leaks oil and is hissing steam. Firstly, let’s take a brief look at Christidis, 2021, which is the method used to attribute this heatwave in ‘near real time’. Note it’s written by the same author, so not exactly an independent verification.

The paper starts off with the usual blah, blah, blah about attribution studies and comparison of risk of an observed extreme event happening with and without anthropogenic forcings, generated using sophisticated computer models to arrive at a fraction of attributable risk. This ‘scientific’ method was pioneered by Peter Stott of the Met Office in response to the exceptional European heatwave of 2003. For those interested, I wrote about this and the heatwaves of 2018 and 2019, in the context of the 1947 central European heatwave a while ago now. The take home message was that meteorological dynamics, much more than thermodynamics (greenhouse gas forcings), form the main determinants of continental heatwaves and thus they are crucial in determining the probability of any given event.

So here’s where it gets interesting because Christidis 2021 specifically excludes current meteorological conditions in order to calculate an unconditional probability of an extreme event happening. Completely ignores them. The so called natural computer runs are performed in a hypothetical world minus current meteorological conditions, minus anthropogenic forcings. Can you believe that? Don’t take my word for it though. this is actually what Christidis says:

Blimey. Talk about throwing the baby out with the bathwater! Christidis is basically saying here that his extreme weather ‘attribution’ method involves totally ignoring current weather conditions, sea surface temperatures, natural cyclical patterns and existing circulation patterns – i.e. reality – in order to arrive at a wholly unrealistic estimate of the probability of an event happening only in the presence of computer generated global warming! Excluding dynamics to focus solely on thermodynamics. Actually, I’m thinking reading chicken entrails might be the more reliable method here!

You would think that using unconditional analysis to attribute extreme weather events was bad enough, but it actually gets worse, because they’re using an ensemble of CMIP6 climate models, which I’ll tell you more about in just a moment:

The HadGEM3-A system is built on an atmospheric model and hence provides attribution assessments conditioned on the observed state of the ocean. Alongside this development, unconditional analyses have also been produced on an ad hoc basis with coupled model data drawn from large multi-model ensembles of the Coupled Model Intercomparison Project phases 5 (CMIP5, Taylor et al. 2012)and 6(CMIP6,Eyring et al., 2016). Unlike the HadGEM3-A simulations that are extended to near-present every month, the CMIP ensembles already span future decades with different emission scenarios and can thus provide assessments of events in near real-time, as well as complementary assessments of future risks. The availability of data from model experiments with the latest CMIP6 models makes it possible to produce some basic attribution information, even while events are still developing, at least for certain types of extremes. This early information conveys the overall anthropogenic influence on the likelihood of the event, while detailed studies may subsequently shed more light on the contributions of individual drivers. We have developed a tool that automates the procedure of organising and carrying out unconditional analyses with CMIP6 ensembles and provides users with an assessment of the event within about an hour after the code is set to run.

So, that’s your real time attribution of happening extreme weather which the Met Office have used to tell us, without caveats, that the probability of the Pakistan and Northern India spring heatwave happening has been made 100 times more likely because of your fossil fuel powered luxury lifestyle. So naturally, your Western lifestyle has to go, along with all your disposable income and wealth, because ‘climate justice’ demands that we don’t incinerate Indians and Pakistanis. And you can’t argue with The Science dammit!

But you can argue with pseudoscience – and using CMIP6 model ensembles to simulate past, present and future climate to generate hypothetical anthropogenically forced climates which in turn generate extremely unrealistic estimates of the influence of man-made global warming on extreme weather events is Mickey Mouse pseudoscientific chicanery. So what’s the big deal about using CMIP6 models? Well, they run too hot, even by the standards of climate alarmists, but don’t take my word for it, listen to Zeke Hausfather, Gavin Schmidt and Kate Marvel. You couldn’t find a more dedicated trio of arch warmists if you tried, so if they say the CMIP6 models are running too hot, then they are, believe me.

We are climate modellers and analysts who develop, distribute and use these projections. We know scientists must treat them with great care. Users beware: a subset of the newest generation of models are ‘too hot’2 and project climate warming in response to carbon dioxide emissions that might be larger than that supported by other evidence37. Some suggest that doubling atmospheric CO2 concentrations from pre-industrial levels will result in warming above 5 °C, for example. This was not the case in previous generations of simpler models.

The CMIP6 models include more sophisticated treatments of ice, water and clouds than earlier ones did, including those in phase 5 (CMIP5). The latest models also include a wider variety of physical processes than before. As models become more realistic, they are expected to converge. In the meantime, individual improvements can affect how sensitive the models are to certain warming processes, in ways that are often impossible to predict.

The Intergovernmental Panel on Climate Change (IPCC), to its credit, has recognized this ‘hot model’ problem. Scientists contributing to the main sections of its Sixth Assessment Report (AR6; published over the past few months) reconciled the newest climate models with key observational constraints on global mean warming, sea-level rise and ocean heat content, and other analyses. They applied statistics to determine the most reasonable projections, consistent with many lines of evidence, which they call ‘assessed warming’.

Unfortunately, little guidance was made available for scientists wishing to study projections in other contexts. We are concerned that in the absence of such guidance, much of the scientific literature is at risk of reporting projections that are inconsistent with the approach taken by the IPCC, and that are overly influenced by the hot models.

Studies that cover monthly or daily extremes or regional climate impacts, for example, are instead left to use the full set of CMIP6 models. And simply taking an average of those leads to higher projections of warming than the IPCC’s assessed-warming averages. As a result, some studies have reported projections that might be inconsistent with AR6 assessments. Findings that show projected climate change will be ‘worse than we thought’ are often attributable to the hot models in CMIP6.

Oh dear. This appears to be exactly what the Met Office and Christidis have done. Here’s a list of the CMIP6 climate models they used in their attribution analysis:

Note that 25 anthropogenically forced simulations are completed for CanESM5, along with 15 simulations without greenhouse gas forcings present. 40 in total. This is by far the largest contribution from any model used. Is it just coincidence that CanESM5 (Canadian Earth System Model 5) is one of the worst offenders as far as the ‘hot model’ issue is concerned? I think probably not. It has a huge equilibrium climate sensitivity, even worse than HadGem3, another notoriously hot model, which is used to generate 5 anthro and 5 natural simulations.

CanESM5 has a notably higher equilibrium climate sensitivity (5.6 K) than its predecessor, CanESM2 (3.7 K), which we briefly discuss, along with simulated changes over the historical period. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science and service applications in Canada.

Obviously not just in Canada, but here in the UK too, by our very own Met Office, as part of its ‘scientific’ analysis of a heatwave in India and Pakistan. They get around, these climate models.

From the Christidis real time weather attribution, here is the graph of the natural and forced model runs vs. observations for the reference region.

The author uses this to claim that the forced simulations are a good fit to observations, but you can’t actually see what’s happening with the natural (unforced) simulations because the upper limit is hidden beneath the red of the forced multi-model simulations, so that might be a reasonable fit too.

All in all, this is another ludicrous attempt to falsely claim that an imaginary ‘climate crisis’ is responsible for a not very remarkable heatwave happening in a region of the globe which is very prone to such heatwaves. The science employed is virtually non existent but the opportunity to try to scare people into supporting extremely regressive and damaging climate policies by hijacking extreme weather is too tempting to resist, obviously. The Met Office should be ashamed. But they aren’t, because this crap is all over the mainstream media, so job done as far as they’re concerned. It’s not science, it’s hocus pocus in the service of politics.

Update: This doesn’t bode well for the heatwave continuing to the end of May and beating the 2010 record. The rains have finally arrived in Delhi.

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