July Weather Prediction

"The changes in circulation giving these weather patterns will be driven by changes in the Solar-Lunar factors
which govern the behavior of the Jet stream and are predictable by WeatherAction’s revolutionary Solar-
Lunar-Action-Technique (SLAT) months ahead..." (from the pdf)

I realize that Corbyn is not required to say how SLAT works, unless he decides to publish it in a journal. But don't you wonder? Aren't you kind of curious?

Solar-observing satellites have been up since about 1969, so there is a lot of opportunity to hindcast weather &climate. If I were confident in SLAT and also that CO2 has no effect, that's what I would do. Make those hindcasts significantly better than the bad old mainstream models and BAM! you are a winner.

In that sense, Corbyn's zeal seems incomplete.

 

all i know is, it's been miserable around her for two weeks and no end in site.

 

I would say lets compare results of the predictions of Corbyn versus the climate models for July. That would be the sensible thing. Maybe we should have 10 monkeys throw darts and have them predict July too. Let's see which of the 12 is most accurate. If its the monkyes, the null hypothesis is shown, and corbyn and IPCC don't predict any better than random.

If Corbyn does best, it doesn't show anything about ghg, as these are already likely in his model via historical data. I have no care about Corbyn's methods unless they are predictive. IF they are, lets get them in some of the IPCC models, that would be what scientific method would lead you to do.

 

Climate models are not weather forecasts! Until Corbyn shows his methodology, he will be suspect.

Icarus

 

As long as climate bloggers like real climate and people like hansen and politicians like gore claim that extreme weather is caused by ghg, we will ask that the climate models acurately predict these extreme events. If they fail, then I am rather skeptical, especially when scientists at NOAA claim that tornadoes and huricanes are not.

If the climate models incorrectly predict these events, we must reject the hypothesis. It fails scientific method when climate models do weather forecasting, but we do not check whether they are accurate.

 

On the short time scale, we were first offered here Corbyn 2013 July (the pdf) The biggest feature (driven by the strongest solar 'expectation' was for July 7-9, intense low over north central and northeast. Well, this is the time and the 'CONUS synoptic' does not look like that

http://www.hpc.ncep.noaa.gov/sfc/90fwbg.gif

July 13 to 17/18 was also presented with high confidence. We'll have to check that one later. Good luck.

 

I would rather compare frequency distributions of extreme rain, temps, etc. during defined past intervals, to the present. There are objective tests for whether they are different, and significance.

None is that attribution (to infrared forcing or solar forcing). It's a pickle, we must use some sort of model to separate effects, to arrive at attribution. Which sort of model? I suppose that is open to discussion.

 

What I object to is the rhetorical hindsight claims of causation.

We need hypothesis - predictions - followed by a test against the null hypothesis. What can not happen is a prediction that climate will change, and any change after the fact attributed. It seems fashionable in some circles to find exeptional data after the fact, then simply claim attribution.

We can take these corbyn preditions and check them against actual whether. For the methods to be verified we need to do this over long periods of time, say a decade, not just a month, but we don't need to know the hypothesis - methods to predict - to determine if the predictions are better than the null hypothesis.

 

Quite so, being accurate or not over a month is not quite the point. But this thread is about how good Corbyn 2013 July is, so I linked to the current synoptic chart. Just that. On July 15 or 16, let's look at another synoptic chart. Heck, why not, they're free.

I also think that if whatever Corbyn sees in the sun really does affect weather, there are solar-output records of high detail since 1970 or so. Also, some notable extreme events during the same time. So we have two sets of things that 'happened', and it would be informative if somebody put them together. That is the longer-range view, it would get much closer to establishing causality.

 

I read the other day that La Nina can be predicted with good results up to 3 months into the future, and not bad results out to 6 months.

Now, a question: if I nail 28/31 days in July to within one degree, but am off by 3 degrees for two days and one day I am off by 10 degrees, do I have a good model ?

 

(Humor first) - If you model is your programmable thermostat and the data is you house temperature, it's a great model except for the two days when the system was broke.

(More serious) - Depends on what lead times you need for the model. If all the input data was from weeks ago, you might be onto something. If every day's prediction used previous day data, then it's rather worthless. Apply the same question to a hurricane track prediction. If I match the hurricane track from week old data, that eye opening since few models do that consistently (or even inconsistently). If I calculate the hurricane track from yesterday's data, then every model is going to be in fairly close agreement.