By P Gosselin on 19. February 2021
Many climate policies are based on scenarios generated by models. Depending what these models churn out, actions and costly regulations get enacted to mitigate the worst consequences. So we hope that the modelers get it right. Unfortunately they are still shooting in the dark. Even short term models!
TWC forecast a basket case
It turns out most models are junk grade when it comes to forecast quality. For example, The Weather Channel here not long ago issued it’s winter outlook up through March:
The area of the US now being hit by one of the most vicious cold waves in the last 100 years was indeed forecast to be “way above normal” or “much above normal”. So far the exact opposite has happened.
We have to wonder what it takes to be issued a license to practice weather forecasting nowadays, and we have to feel sorry for those businesses and industries that relied on these botched forecasts.
Yet, these are the type of outlooks that policymakers insist we need to heed and take immediate (costly) action. “Follow the science,” activists and policymakers like to say.
Potsdam Institute’s El Nino debacle
Another example of short to midterm forecasting involves the El Nino events, which have a global impact. Having the ability to predict these events accurately would be a very valuable tool.
And not long ago the Potsdam Institute for Climate Impact Research (PIK) in Germany claimed to have developed a model that could predict the events with 80% probability. A PIK November 2019 press release in fact boasted that its team of renowned researchers had developed a new, far better model – which in November 2019 said was capable of forecasting a late 2020 El Niño event a year in advance.
Today in February, 2021, the results are in and they are ugly: The equatorial Pacific 3.4 region is near La Nina conditions, thus in complete contradiction to the warm forecasts of the Potsdam Institute. The “pioneering” PIK model, which in part was developed by Prof. Hans-Joachim Schellnhuber, is a complete failure and totally wrong:
The ECMWF graph above shows ENSO forecasts for the period July 2020 to January 2021 (many thin red lines) compared to measured SSTA in Nino area 3.4 (blue dotted line).
The ECMWF forecasts were on average about one degree Celsius too warm. There have been La Niña conditions since August 2020 with measured values of -0.5°C deviations and colder.
“Model rubbish”
“The ‘pioneering’ PIK model produced model rubbish and disgraced German ‘climate science’ worldwide. Moreover, it currently looks as if the cold La Niña wants to cool us down further until 2022,” reported Schneefan here.
Well, the solution is obvious: Raise the blue dotted line. [h/t Karl and Mears for the idea.]
Modelling has been the death of proper, old style forecasting which relied on the experience and intuition of experts in the interpretation of observations based on earlier precedents.
It was by that method that the decision was taken as to when to invade France in WW2. The forecaster made a difficult judgment call and was proved right.
Unfortunately, that approach gives only about 3 days ahead with any utility so models were supposed to do better and they do up to about 5 days out.
Beyond 5 days they become overwhelmed by weather system instability and despite vast amounts of investment over decades have failed to improve on that.
Look at any modelled forecast for 7 days ahead and it will be adjusted substantially as one approaches days 6 and 7.
Proper recognition of that sad fact would destroy the weather modelling industry.
Channel 7 in Melbourne Australia has a Meteorologist/Presenter, Jane Bunns, who does an 8 day forecast. Originally she did try for 14 days but the vast majority of the viewers did not take much notice of the 14 day forecast. This will give an indication of why that is the case:
I was hoping that she’d give the forecast for Bundanyabba, but it looks like she didn’t get that high up on the map.
I think she has a lot of assets. I am not sure I would care about the correctness of her forecasts if she wore the right dresses.
Modelling is the death of any science. Empirical (observation based) data and observations are discounted and model results are presented as God-given truths, commonly in pretty colours to seduce the eye.
I think the problem is that some have forgotten that the model is a tool.
They rely on it too much then they forget what they’ve learned.
Sort of like people using calculators so much they forget how to do the math themselves.
They do 5 days instead of only 3 because of the increased amount of data observations
The Farmer’s Almanac is more accurate predicting the weather for a 12-16 month period than the computer models.
1) If they had to bear the cost of failed predictions would they predict so many abnormal conditions?
2) I wonder if all they need to do to improve the accuracy of their predictions is multiply predicted temperature deviations from ‘normal’ by -1, and change their % likelihood values by subtracting them from 100%.
This is far more important than blaming the power generators for lack of capacity in Texas..how could they have gas plants on standby when the forecast is for higher than average temperatures.
Same thing happened in my city, the models said the rainfall was going to be average or above average over summer and did it again the next year, the reality was lowest rainfall over 6 months for the first year was was exceeded by even lower for the second year. The water storage was marginal for a time but OK in the big picture . This only happens because the models can’t be useful 3 months out, yet they are being used to predict decades ahead at a scale that is far to fine to be worthwhile 2 weeks ahead . Overuse of around average or above or below average is letting them get away with forecasts that exibit no skill what so ever.
A few years ago, climate warmists convinced local councils that snow and ice would be less and less. They reasonably reduced the budget for snow removal and supplies. Of course, they got far more snow and ice than average in the following year.
Roads went unplowed and unsalted. Accidents went up, and people died. Relying on these forecasts have real life consequences, and those who demand we act on them should be held accountable for the damages they may cause.
The above took place in the UK.
We are far, far away from the models capable of predicting events shorter than one year. The coldness of this year is a weather phenomenon.
What is for me much more interesting is what are the temperatures of IPCC’s simple model from the year 2001 to 2020. They are pretty ugly.
You can take your pick. The Chinese FGOALS will keep you as you were in 2001 if you are not warmed by homogenisation. The EU MIROC6 is a tad closer to hell.
All data from KNMI Climate Explorer apart from CMRW-21, which is a reliable physics based model of the ocean/atmosphere energy balance.
These are all forecasts for the CMIP6 ensemble of models that will be used for AR6 due in 2021. So right up to date.
Too bad the actual value on your chart stops in 2019. We are probably back to starting value with the big drop the last few weeks.
Why are they using USHCN which is crap instead of the USCRN which is unmodified to match their agenda?
You will never see last week’s forecast back on any channel: keeping the model-forecasting illusion alive for $$$$$$$ $ake.
The British MET officee has added lots of new stuff based on Climate in place of weather to its model, and the results are now usually wrong more than 2 or 3 days out. Previously they were fairly good up to a week out. Temperatures are particularly miles out, similar to climate models. All very foolish.
I live in west-central Argentina and my twin brother lives in Eugene, Oregon. We converse every day via skype. There is a large difference between the accuracy of Argentina and Oregon weather forecasts, with forecast events a week ahead of time common. Whereas, in Oregon the forecast even a few days out is mixed results. So, given that both forecasts have access to the same data, it appears to me that some combination of ocean and atmospheric currents produces more even flow of weather events than other combinations which are more chaotic. Now stretch weather time-wise out into climate and the predictions get to a ridiculous stage, might even call it a model.
Forecasting in Argentina is probably easier than in Oregon. The weather systems in the southern hemisphere move much more predictably since they are much less affected by topography. Essentially they just circle endlessly round and round Antarctica:
https://argo.nullschool.net/#current/wind/surface/level/orthographic=2.10,-86.82,261
it is way more irregular at the other end:
https://argo.nullschool.net/#current/wind/surface/level/orthographic=-31.52,83.98,261
Weather models are improving. The best we are able to forecast into the future with and skill is about 7 to 10 days. 30 years ago, the best was 5 days.
7 to 10 days? Complete nonsense. You made that up. Studies have shown that weather forecasts degrade significantly in accuracy beyond 5 days and by 14 days have dropped to random for even simple things like will future temperatures be above or below normal. Forecasting based on finding a historical weather pattern that best matches current conditions and progressing the predictions based on the historical patterns that followed the matched pattern routinely beat weather models.
Loy-dodo with his little evidence -free fantasies, as always
So funny hat he/she/it continues to expose the complete idiocy and ignorance that comes with ACDS (Anit-CO2 Derangement Syndrome),
… making a mockery of the AGW cult in the process.
No, I’ve hear this said by a couple of different meteorologists.
“The best we are able to forecast into the future with and skill is about 7 to 10 days. 30 years ago, the best was 5 days.”
An innocuous enough statement but you go straight to the acrimonious abuse.
This one happens to be a direct quote of Anthony Watts from yesterday: https://wattsupwiththat.com/2021/02/19/friday-funny-nature-makes-a-mockery-of-month-ahead-model-forecasts/
He’s exposing his “little evidence -free fantasies and complete idiocy and ignorance” too is he? Knee-jerk much?
That is Loy-dodo’s idea of EVIDENCE… roflmao. !!
You are a MORON, Loy !!
You make a mockery of all ACDS sufferers.
You are correct! Improving at abject failure, just like you.
Thankfully many industry sectors and even municipalities have quit relying on climate and weather forecasts produced by government agencies and instead have switched to paid private services from forecasters who have a demonstrated track record for accuracy much superior to that of the government agencies.
If this were not the case, companies like Weather bell Analytics, of which there are several, would not be in business.
The private weather services have skin in the game. If they had the accuracy record of the government agencies they’d go out of business.
Proving once again that capitalism works and is superior to socialism.
People forget that a model is nothing more than a hypothesis put into code. It can be no better than the understanding the modeler (or modelers) have, and—as we see—that understanding is flawed.
Until a model is validated, repeatedly, it should be treated as no better than someone’s opinion.
You’ve hit on the big reason climate models are so bad. They don’t correctly model the interface between the surface and the atmosphere. There are probably reasonable atmospheric models and oceanic models but when they try to tie these together they fail.
It is at this interface that the greenhouse model diverges from reality. The difference in heat capacity allows the added energy generated by greenhouse gases to be radiated to space every night.
You are absolutely right. Moreover, when the predictions fail to match observations, the hypotheses MUST be discarded or modified – it has been disproven. One more thing – the model must be able to answer past observations. Clearly they don’t (MWP, RWP in particular) and fail at that also.
Tie their paychecks to their failures and you would see A. far fewer people on TV/Print spewing this stupidity and 2. far more accurate short term weather forecasts. As long as telling lies pays lies are all they will tell.
The divergence of all of those red lines occurs very quickly, therefore the model is utterly worthless. A coin toss would be just as good and much cheaper.
I have posted this before, its about Covid and yet another pathetic excuse to go after Mr Trump.That’s a large part of this climate thing also, school-playground politics
Anyway, what about my ‘fix’
Covid-19: Climate Models: Social mruder, they wrote—elected, unaccountable, and unrepentantIs anyone here going to object?
Would something like it, wake a few folks up?
Unmitigated blather.
IF — and I use that IF advisedly – IF these twits actually spent a little time in the area where I live, the WEATHER is normal winter AND the TEMPERATURE has dropped from COLD to NEARLY BITTER COLD. This is rather normal around here.
I would love to pile them into a vehicle and drag their ridiculous personages up to one of my favorite hiking spots – dunes area near restless, testy Lake Michigan shore – and just leave them there overnight. But that’s just me.
My snowfall total so far is just shy of 20 inches. Measured it, took pictures, and assessed it as normal winter. Now the National Weather Service forecast for the end of next week is mid to upper 20s and maybe some low to mid-30s: NORMAL WINTER WEATHER here in the Upper Midwest. Chicago got hit harder than we did, which is fine with me.
I have some really cool photos and the birds have returned to my feeding station: many sparrows, some juncos and two cardinals and a gorgeously marked female red-bellied woodpecker. My life is pretty darned good.
Something is really out of wack here in northeast Indiana, it was 9F this morning and I saw a robin red breast outside. Today I have to go up on my roof to move the heat tape so the ice dams don’t cause a leak into the house.
Here in central Indiana I have a couple red bellied woodpeckers at my feeder. Also Hairy and Downy woodpeckers, Nuthatches, Tufted tit mice, several species of sparrows, cardinals, blue jays, cow birds, black capped chickadees and too many damned European starlings. Had a red headed woodpecker last summer but haven’t seen it since then.
I put out two large seed blocks in cages hanging from a double shepherds hook outside a dining room window. During the winter months I also have a squirrel proof feeder that holds 8 lb. of seed hanging from a low branch on the spruce tree, The really flock to both and especially so when there is snow covering the ground or very cold weather is coming in.
One blue jay showed up this afternoon. I expect to see the Hairy and Downy woodpeckers before long. Have not had the starlings show up at all. Grackles will come along in the spring, as will the redwinged blackbrids. Looking forward to Spring!!!!
Are any climate models described in detail along with the code? I suppose it could all be described well in a flow diagram- but I’ve yet to see one anywhere. It’ll be easier to deconstruct them if we can see the logic or failure of logic.
https://www.sciencemag.org/news/2020/07/missed-wind-patterns-are-throwing-climate-forecasts-rain-and-storms
A quote from the end of the reference:
•“But until modelers figure out how to confidently forecast changes in the winds, Smith says, “We can’t take the models at face value.” “
Even with this, they still cling to their CO2 obsession.
One can understand why owners of Texas electricity generating plants did not freeze protect them. Why spend the money when tomorrow is going to be warm anyways? This is a prime example of very bad public policy created by bad science.
They should have got the hint during the ice storms around the 2011 Superbowl.
It will be interesting to see where we go from here. CFSR has planet Earth close to the late 20th century average.
Models might only be missing a few key elements that cause them to fail spectacularly.
Assuming this trend continues with the La Nina in place, think of all the papers that were set to be released, but will not be released before the Scotland COP in November. What a waste of resources. I am prepared for a slew of reports claiming that cooling was caused by the global shutdown to combat COVID.
Looks very like a long-term cooling trend to me.
No, they have so many degrees of freedom that get “tuned” separately to match the adjusted temps of the past that they can’t separate the coffee beans from the rat turds.
Heavy frost in the Great Lakes region causes them to freeze quickly.
Currently, La Niña is doing quite well.
http://www.bom.gov.au/archive/oceanography/ocean_anals/IDYOC007/IDYOC007.202102.gif
https://www.longpaddock.qld.gov.au/soi/
The forecast of a warm winter was an easy one to make. A strong La Nina had formed. This usually means a warm, dry southern US. The further west the bulk of the cold, the warmer it is. And the bulk of the cold was closer to Australia. That was one big signal of warmth there. Then there is the PDO, Pacific Decadal Oscillation. PDO- amplifies La Nina (and mutes El Nino) but PDO+ mutes La Nina (and amplifies El Nino). PDO- is a warm blob surrounded by a horseshoe shaped cool pool near Alaska. Well, the PDO is currently negative.
So, all the major weather drivers said warm and dry. But, there are many weather drivers. You can research all these: Madden-Julian Oscillation, Eastern Pacific Oscillation, Arctic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation, Global Atmospheric Angular Momentum, Pacific/North American teleconnection, Pacific Meridional Mode, North Pacific Oscillation, North American Dipole. And I’m sure I left some out. Weather and climate are very complex. These other drivers had other ideas.
There will always be exceptions. I have noticed this winter that even the European model is having a very hard time with it. You just need to be humble enough to admit that 150 years of weather data ain’t enough to fully understand the weather. I’m not sure 5000 years of weather data would be enough either. The best thing you can do is not pretend you and your complex computers are all-wise but be willing to admit there is much to learn.
Still, by January 19 when that forecast was made the SSW over the Arctic was already in full swing:
https://argo.nullschool.net/#2021/01/19/1500Z/wind/isobaric/70hPa/overlay=temp/orthographic=-108.66,77.07,261
And that almost always means cold weather, I certainly foresaw it in late January, it is actually one of the few situations when a multi-week forecast is possible.
How do the folks who live and die by models want the output to be used?
I think the myth of German engineering was exploded by the T34 tank.
It’s arguable the lack of speciality materials caused German manufacturers and consequently the Wehrmacht etc. to significantly underperform. Blithering bureaucracy and cronyism also had a serious role in that underperformance.
You might find some enlightenment in this webminar
Perhaps the modelers should consult with Farmers Almanac.
Yep. So far, in my AO, they’ve been quite close to the real results.
Farmers almanac actually incorporates solar influences into their model predictions. IPCC should include their model as a base case.
If it hasn’t already been done, why doesn’t someone develop a “model” that wouldn’t forecast the weather but search for past weather patterns that match the current patterns then report what happened next?
Seems to this Layman that such a tool might prove useful.
Joe Bastardi does that, manually + computer files.
I’m sure the good ones do.
We have facial recognition software to match a face in a crowd with the name of a face on file.
Why not software to match a current weather pattern with a past weather pattern?
Some years ago, I tracked the Weather Channel 5 day and 10 day forecasts for a year and compared it with actual temperatures. For comparison, I took the spread of record low/record high for each day and randomly picked a temperature. The 5 day was a little (but not much) better than my random approach. The 10 day was actually inferior that year to a random number.
When I looked at the data, one feature stood out. Often, the 10 day forecast was off a LOT, but the reason was subtle. The error was more often in timing than in kind of event. For example, the 10 day correctly picked that a strong cold front was coming but missed it by 2-3 days. This throws the long term temperature forecast way off even though the model had the basic idea of coming weather systems.
There is what is called “Persistence Forecasting” – the weather tommorw will be the same as today. Depending on how “tight” you want to measure (temp, wind, cloudiness), you’ll probably be right more often than not.
Anyone know what The Old Farmer’s Almanac predicted? I’d bet it’s prognostications are at least, if not more, accurate.
Correct me if I am wrong, but didn’t they basically forecast every every possible temperature variation from the given starting temperature?