Guest Post by Willis Eschenbach
Thanks to Nick Stokes, who pointed me to the University of Melbourne Computer Model Intercomparison Project 6 (CMIP6) data repository, I got data on rainfall from the CMIP6 computer climate models. There were 12 models for which they had data covering the entire period 1850 – 2100. Let me start with the average of all twelve models.
Figure 1. Average global annual precipitation as shown by 12 CMIP computer climate models, one run per model.
I swear, results like that make me question the sanity of climate scientists. I mean, does anyone seriously think that after a hundred and fifty years of little change in global rainfall, around 2020 it suddenly started skyrocketing to new highs? (Note that the issue I’m addressing is not the amount of the change, which is not that great, but the shape of the change—level for 150 years, then within the space of only a couple years, suddenly increasing almost vertically. What changed?)
Really? Yes, I know that “negation through incredulity” is merely circumstantial evidence, but we’re getting to “trout in the milk” levels here …
… “trout in the milk”?? Seems that in 1849 there was a dairyman’s strike, during which there was suspicion that the milk was being watered down to increase profits. However, at the time it was hard to prove. Regarding the strike, Henry David Thoreau famously said …
Sometimes circumstantial evidence is very strong, as when you find a trout in the milk.
That’s where I find myself regarding Figure 1. Nor is this the only problem. Here are the rainfall results from the 12 models, smoothed so we can see the differences.
Figure 2. Precipitation results from 12 computer model runs, one from each model. Each is a LOWESS smooth of the original data.
As you can see, the largest results in the 1800’s are no less than 15-20% higher than the lowest result. I can understand models getting the future wrong … but when they get the past wrong, I get very nervous.
In addition, the amount of rise in future precipitation over the period is quite variable. To illustrate this, here is the data in Figure 2, expressed as an anomaly around each result’s 1850-1879 mean.
Figure 3. As in Figure 2, precipitation results from 12 computer model runs, one from each model, but expressed as an anomaly around the 1850-1879 mean value.
Note that although they start at the same level, by 1995 they differ by ~ 20 mm per year, with some increasing and some decreasing. And as you can see, the projected increase in rainfall varies from +20 mm to 60+ mm, a factor of three to one. In that regard a recent article, in Science magazine no less, pointed out that …
Projections rely largely on climate models, and the factor of three variation in predicted warming from these models amounts to tens of trillions of dollars of societal costs. Thus, most models must be significantly wrong about impact. Does that sound like “the science is settled?”
And to add insult to injury, this is not a factor of three variation between the least and most extreme scenarios. This is a factor of three variation in one scenario, the ssp126 scenario which projects the smallest increase in greenhouse gases.
Simple undeniable fact. The current crop of climate models is far from ready for prime time when that entails using them to make trillion-dollar decisions.
Finally, I took a different look at the rainfall results. I keep hearing claims that according to the models, the wet areas are supposed to get wetter, and the dry areas are supposed to get drier. Fortunately, the University of Melbourne has regional results for the precipitation, divided up into the following regions.
Figure 4. Regions used by the CMIP6 models.
So I averaged out the 12 models region by region, and I looked at both the average values and the average trends for each region. IF it were true that the “wet areas are getting wetter and the dry areas are getting dryer”, this should show up in a scatterplot of the two datasets. To start with, here are the results, but without labels, so you can see that there’s no statistically significant relationship between the trend and the mean.
Figure 5. Scatterplot, modeled average rainfall versus modeled decadal trend in rainfall, by region. Dotted lines intersect at the global average values for mean and trend.
And here is the same figure with the areas labeled.
Figure 6. As in Figure 5, but with each point labeled
You can see the driest areas of the Sahara (SAH), the Gobi Desert of Eastern Central Asia (ECA), and the Arabian Peninsula (ARP) at the left … not changing much toward either wetter or drier.
And on the right are the wettest areas of South America (NWS), East Indian Ocean (EIO) and Southeast Asia (SEA), again showing little common change.
So it seems that the models are not sufficiently alarming for the promoters of climate alarmism, and as a result, even the model results are being misrepresented to jack up the fear …
And here on our forested hill?
Rain. Glorious rain, the fairest and most egalitarian of phenomena, for as the prophet said,
… he maketh
his sun to rise on the evil and on the good,
and sendeth rain on the just and on the unjust.
Ah, dear friends, could we ask for a more marvelous and entrancing world?
Best to all,
w.
PS: Look, there are enough misunderstandings on the intarwebs. To keep the number down, please quote the exact words you are discussing, so we can all be clear just who and what you are referring to. For example, on my last post someone wrote “Really? You all are still trying to pretend away climate science with your pseudo-scientific clap-trap? What a disgrace to our nation.”
Seriously? Who was he referring to? Me? Someone else? What “pseudo-scientific clap-trap” is he talking about? Such comments go nowhere. Please, quote the exact words you are referring to.
Willis
“PS: Look, there are enough misunderstandings on the intarwebs”
Did you mean: interwebs
Maybe “intrawebs” instead? Like a collection of interconnected webs. 🙂
I took that as a possible allusion to the figurative “tarring and feathering” as a normal mode of operation. Probably not an ungenerous allusion to the numerous “tards” who “live” there.
Nah, it was deliberate …
w.
Surely these BoM and Melb Uni researchers aren’t wasting time and taxpayers $$$$s producing average rainfall numbers for the entire Australian continent?
Why not include the moon – the end results would be just as enlightening about what goes in the real world of rainfall.
The rain data is in Oz, but CMIP6 involves about 100 global models from modeling centers around the world. CMIP is run by the UN World Climate Research Program and administered by the US Dept of Energy.
https://pcmdi.llnl.gov/CMIP6/
Australia has three latitudinal bands. The middle band includes Sydney, Alice Springs and Carnarvon. Somehow I doubt that all locations in one band could be classed as dry or wet.
For those who don’t know: Alice Springs – desert, Sydney – temperate, Carnarvon – the gorge is hot and wet, the surrounding plains hot and a lot less wet !
I think you have the wrong Carnarvon, what gorge?
One is on the WA west coast, the other (the gorge) is in Qld
The amphitheatre in the Carnarvon Gorge is lovely and cool.
(of course, you’re dripping sweat from the humidity by the time you trek there)
And on the other side of the world, they have the mountains of Scotland and Norway in the same geographic zone as the plains of Ukraine. And “ENA” extends from the Florida Keys almost to Hudson Bay.
Not what you’d call climatically homogeneous areas.
Very ingenious. They can’t model clouds, but they model rain.
Yet, rain comes from individual clouds. That is one of the weak points in weather forecasting. The forecasting service may identify clouds that are capable of providing rain, but they can’t predict exactly when or where the cloud(s) will be when they release their rain. Thus, it may well be raining somewhere in the forecast area, but not where you are. If they can’t model clouds, then the future rain projections should be suspect.
I have previously read that the regional projections for precipitation are often contradictory between different models. That doesn’t sound like settled science.
But a machine smoothing of an ensemble of model outputs predicts the future and past with near and fading skill.
I know when clouds are going to produce rain –
the moment I step outside without my raincoat on.
That’s 97% settled weather behavior.
As I think I noted before, a few years back, the UK Wet Office predicted a weather forecast for an upcoming Bank Holiday weekend, it was so dreadful that for the Dorset town of Bournemouth, thousands of potential visitors stayed away as a result. It turned out to be one of the loveliest Bank Holiday weekends in the towns history. Local businesses lost tens of thousands of pounds in trade as a result!!! UK Wet Office not held accountable – as usual, yet they still demanded squillions more ££££!!! in their annual budget for yet another “improved” puter so that they could get their weather forecasts wrong that much faster in a more spectacular way!!!! I have met several former Wet Office scientists who once retired on a nice taxpayer funded pension, ever so quietly recant their AGW views, usually in the form of, “I was never actually in favour of the official view on AGW/Climate Change!”. How does the saying go? “It is very difficult to get someone to understand something, when their position, status, salary, & pension, are dependent upon them not understanding it!”.
The graphs are killers.
The models are worse than we thought.
WIllis –
I learn something from every one of your posts. Thank you!
The scatterplots are proof positive that there is no inherent bias in the models and thus they can be trusted completely. I’m going out to Walmart to buy some galoshes.
Two inches more per year? Ooh, be afraid, be very afraid.
So not only are the models demonstrably useless, but their predictions (so-called “projections”) are benign and likely beneficial to most places.
More waste of our taxpayer money.
Two inches per year more rain and no end in sight.
Be afraid, be very afraid.
The sky is falling.
And so forth …
“The sky is falling”.
Yes literally
As rain
Better get Noah building again
This time, can you please get him to leave mosquitoes, fleas, ticks, all roaches, crocodiles/alligators and scorpions off the danged Ark? Thanks.
PS It’d be great if he’d leave skunks off, too, or make sure the dogs he takes have the sense to never bother a skunk again after the first time they’ve been sprayed instead of never learning.
With a “Greening” of the environment, this means more shifting sands and less roots to anchor them… more bambis, minows, bluebirds displaced. That said, go green, emit for life.
“That said, go green, emit for life.”
The car is extremely environmentally friendly.
It emits plant food.
For example, on my last post someone wrote “Really? You all are still trying to pretend away climate science with your pseudo-scientific clap-trap? What a disgrace to our nation.”
For example, on my last post some IDIOT wrote…
Fixed it.
Good timing.
Has to be Barry Anthony,
I see both of those responses on Twitter all the time ad nauseum. I seriously believe a lot of these posters are paid trolls, probably with multiple accounts under different names who all have been given a written script to follow. None of them strike me as very bright nor with having any knowledge of any science, let alone of the nebulous, so-called climate science. They act and argue like telemarketers except most telemarketers don’t get mad and insulting like trolls do.
I swear, results like that make me question the sanity of climate scientists. I mean, does anyone seriously think that after a hundred and fifty years of little change in global rainfall, around 2020 it suddenly started skyrocketing to new highs?
So how come we have had 4 truly exceptional rain events – Germany, china, w Canada and Australia in the last year?
UK rainfall has definitely increased (Met Office measurement).
Hey, Griff. It’s called weather. And in every one of the four locations you cite for last year it has not only happened before, it has also happened WORSE before.
You need to up your game if you want to play in this league.
SE Queensland and NE NSW had a much bigger rain event in 1893. The site of the highest daily rainfall recorded in Australia ( Crohamhurst recording 914 mm in a 24 hour period.) has been shut so it’s hard to compare with the recent rain event, but that record was not broken. The flooding then was 3 inches less than in 1841 when little rainfall data was collected.
Germany had one of its worst floods in 1892 and Canada had a once in 500 year flood in 1894.
Here, a history of flooding in Lismore NSW
Well said, Sir!!!
He’d need to up his game to play on Romper Room.
Weather, dear boy.
Weather.
Come back after another 30 years.
Yes, griff, UK rainfall has increased. But what it has NOT done is to run level with no change from 1850 to ~ 2000 and then suddenly increased.
w.
Global rainfall should roughly trend with Total Water Vapor Column, which should roughly follow SST average temp at 7% increase per deg. increase. But locally 7% in a century just isn’t going to show on the -70%/+270% annual local variations.
I would like to see the MET estimating method. There is no way to actually measure the total rainfall over the U.K. in a given year. There are various ways to estimate it, which give different results. The basic problem is that you need records from random locations, because statistical sampling theory is based on probability theory.
All we have is what is called a “convenience sample” and sampling theory says no valid inference about the entire population, in this case the average of rain at all places combined, can be drawn from a convenience sample.
So there is no way to accurately estimate U.K. rainfall. These so-called measurements are just poor estimates.
Picky David….We know approximately close enough from 300 years worth of rain gauge readings, or we wouldn’t be able to size a storm drain.
I think you miss Wojick’s point, so I think your example of sizing a storm drain is irrelevant.
Every storm drain is placed somewhere, so historical rainfall records for a nearby location are relevant to sizing the drain.
Were you to size an imaginary drain large enough to capture all the rain on the entire U.K., all existing rainfall measurements combined provide an estimate only.
Generally speaking, an “average” is the most useful statistic available for an assemblage of readings of any given phenomenon that has an expectation of reoccurring. I was just pointing out the flaw in David’s “no way to measure” logic…
But we do not have readings that have “an expectation of reocurring.” Instead, we have isolated readings from various sample locations, from which we need an “average” (or sum) of “all locations” in the area;— so we need to “invent” or infer readings for the un-sampled locations (which are a majority of all locations).
Thus we need interpolation (Kriging or something similar).
Interpolation must be done first, for some specific time interval; then if you want averages, you have some data you can average.
(but you still must rely on some assumptions that may not obtain).
And in the case of storm drains, we don’t care about average rainfall, we want to know maximum rainfall (excluding, e.g., once-in-a-century events.)
Sad truth is that sizing of stormwater drains was done a long time ago before urbanisation … and they haven’t improved.
Really ? It was just guesswork prior to establishment of the Civil Engineering Society in 1854, after which calculation methods were published which saved much useless government expenditure….
Most of the places affected by floods are flood plains, griff.
How do you think these areas got to be flood plains in the first place?
(Hint – it wasn’t because they never ever got any serious rain events in their regions)
A few years back on WUWT there was an excellent few articles on some floods in the UK … turned out that the cause was the ‘environmentalista’ banning dredging of the local waterways leading to flooding, not excess rainfall.
They are still at it though, even though the locals were very grateful flooding was now avoided: https://www.bbc.co.uk/news/uk-england-hereford-worcester-60677143
Yes it did.
The Met Office moved the weather stations
Most notable was one which, with extreme Eagle Eyes and some decent bins, I could have seen from my old place in Cumbria
It was about half way up a Cumbrian mountain in the Lake District. A place noted for rain.
I once ventured to ask, concerning The Lake District:
Did rain make The Lakes or do The Lakes make the rain?
No answer forthcame.
Certainly the weather station was already at or very near England’s most rainy place, even just halfway
“Oop yonder t’ill”
as the locals might have said but due to Global Warming, some urge was felt to move the Really Rainy Station to:
tootoppa t’owld ‘ill
and thus the shock horror quelle surprise of everyone (‘cept the sheep) Cumbrian Rainfall was found to have increased
Yes, they really did hold a cigarette lighter under the thermometer.
…..and turn a fire-hose onto the rain gauge
edit to PS – I think it was the station at or near a place name of Shap
In my old Cumbrian village they said if you could see Black Coombe it will rain, and if you can’t see it, it’s raining.
A simpler version of my fathers ‘weather string’ (he got USAF paid for at UCLA double masters in meteorology and weather radar in 1947). The outside the window weather string:
What’s the difference between “dry rain” and “wet rain”?
With “dry rain”, you stay dry when you use an umbrella.
With “wet rain” it comes through the umbrella!
Experienced by those living in monsoon impacted mountains.
When a typhoon makes its way inland, you can get 23″ of rain in 36 hours!
Seattle has a rain they called dry rain. It’s known as a squib, if memory serves. It was a frequent event interspersed with wet rains and very occassionally sun or cloud breaks. You really did not get wet in it. It was a very fine, mist like rain and evaporated when or just before it fell on you.
It’s been 30 years since we lived there. They have all kinds of names for different rains, sunshine and clouds.
I can’t remember them all but I was amazed by number when I lived there.
I was delighted with the Seattle rains when I moved there as a grad student in 1996 from coastal NW England. Not only was the rain slightly warmer, but it came down vertically.
The other students, from different parts of the US, were talking about ending it all because of the constant cloudage.
You forgot to say the rain is 6% wetter too.
He, also, forgot to say it’s getting wetter there twice as fast as everywhere else!
“So how come we have had 4 truly exceptional rain events”
Weather meets floodplain. It’s that combination needed to get headlines and only in retrospect will we be able to see if rain in those areas had significantly increased. I expect it may have slightly increased but slightly doesn’t make a flood. It really is weather Griff.
Griff,
Record weather events occur with expected regularity somewhere on earth (short record period, myriad of locations). But it takes a committed “Texas sharpshooter” to draw a bullseye around an event and declare that the “sky is falling”.
Hey Griff, can you say la Nina ? It wets the eastern seaboard of Australia.
As noted, the Bc rain event was a recent record.
Of course, native knowledge says these evens have occurred in the past but there is no interest in native knowledge if it doesn’t support the narrative.
Anyway, according to settled alarmism 2021 was only the 7th hottest year EVER so that means it was caused by global cooling.
Which not coincidentally matches history.
That may be the case, but it doesn’t show a long-term trend, UK rainfall over the last 150 years is a flat line, BUT, I fully accept that the data does show that some years are wetter than others, & some years are drier than others – go figure that phenomenon!!! Those truly exceptional rain events appear to have happened on a global scale, suggests to me that weather affects all parts of the world at some point, haven’t bothered to check but were any of those rain events classified as to periodicity, e.g. the worst in 20/30/40/50/60 years etc, in most of not all cases, it has happened before, however people like you Griffy-baby don’t like to mention such trivial details as it shoots your arguments in the foot!!!
griff,
If I was not familiar with you, I swear, I would think your comment was satire and give you an up-vote for humor. However, since I am, I know it is not humor but serious. You poor soul. All the time you spend on here and you’ve learned nothing.
Do you work at remaining ignorant or, are you one of those Carbon Brief (or, similar outfit’s) paid trolls and this is your job?
Increased since when? By how much?
More importantly, is it still increasing?
The figures since 1836 are here:
https://www.metoffice.gov.uk/pub/data/weather/uk/climate/datasets/Rainfall/date/UK.txt
As far as Scotland is concerned it is difficult to see any upward trend since 1994:
https://www.statista.com/statistics/367888/scotland-annual-rainfall/
In 15 of the years since 1994, rainfall was lower than it was in 1994. And in 9 years it was higher. Rainfall has been lower than the 2011 figure in every year since 2011.
Incidentally the temperature reached 19 degrees C in Ayrshire last Saturday.
I’ve often wondered if the “Green” politicians wanted this to happen (wouldn’t want an event where nothing bad happened): https://www.netzerowatch.com/the-real-reason-for-germanys-flood-disaster-amonumental-failure-of-the-warning-system/
Are you sure that MET Office measurement isn’t totally reliant on the relatively recently installed rain gauge on the Honister Pass halfway up a mountain in the Lake District?
Nothing exceptional; all of it happened before
Its only natural that average rainfall will increase rapidly in computer models as CO2 warming reaches the tipping point.
The global warming theory says clouds are a positive feedback and the CO2 heating will evaporate more water causing even more heating causing more evaporation and so more rainfall.
Nobody being paid to write computer programs is going to program them with different functions that defeat that.
but there’s till no hot spot !
Precipitation is a negative feedback
Do we have the actual average global rainfall amounts for the past twenty five years to see if there has already been a ~25mm increase?
Or perhaps I should be asking, is the data you plotted only models, or did they use actual rainfall data for the 20th century before their prediction models of a jump in rainfall over the 21st century?
We have precipitation data for land, but only since ARGO estimates for the oceans. So no, it’s only models being plotted.
Nor can we accurately estimate global rainfall from the data we have. It is just a convenience sample.
What we have here then is an all-too-typical untestable hypothesis.
And ARGO only gets to the surface every 10 days so the data is relatively sparse.
I’m sceptical about its ability to measure rainfall with any accuracy. Mixing down would quickly homogenise a salinity signal very quickly after rain so the only salinity signal that might persist would be where evaporation occurs in an area being measured but the rain falls elsewhere. And that’s assuming the converse hadn’t happened ie evaporation elsewhere and rain fell in the area being measured. 10 days is a long time….
Tim, read my guest from years ago ‘ARGO-fit for purpose?’. ARGO infers ocean rainfall from salinity, so is effectively continuous even tho you are correct about its 10 day cycle. The ARGO experimental three part design goal called this part the ‘ocean fresh water reservoir’.
ARGO spends all its time well below the mixed layer. Its only when it surfaces every 10 days that it could measure the salinity so why do you say its continuous?
Because, per the design intent documents, the salinity measured every 10th day reflects the salinity diluting rainfall for the previous nine. Now, I admit the little fly in that ointment is the ARGO float is by design Not in the same spot as when it surfaced ten days prior. But it is all we got. And still showed CMIP5 models underestimated ocean rainfall by 2x. See following clouds comment. Regards.
Minus the salinity concentrating evaporation. Plus, as you say, its not even in the same location.
I remain highly sceptical the data has useful accuracy.
“I remain highly sceptical the data has useful accuracy.”
Tim, is there anything that would suggest the folks doing these things want accuracy or, perhaps, prefer a certain amount of inaccuracy to use for their fudge factors? Just a thought.
I would guess that to “accurately” measure the oceans would require at least 100x ARGO with a great number of them tethered to give spatially consistent readings. I think the reality is they were hamstrung by their budget. I doubt there is any malice there. Not intentionally at any rate.
Last time I looked there was, on average, 1 Argo buoy every 93,000 sq. km.
And even more sparse in the Southern Hemisphere.
There was/is a significant effort to monitor global freshwater runoff from land. The effort to measure stream flow peaked globally a while back and there is now a mixture of actual measurement and modelling to arrive at a monthly global number.
GRDC does the work of determining freshwater runoff:
https://www.bafg.de/GRDC/EN/03_dtprdcts/31_FWFLX/freshflux_node.html
It has declined globally in the last 50 years.
This paper goes into much more detail on the global precipitation:
https://hess.copernicus.org/articles/24/3899/2020/
And arrives at the same conclusion that freshwater runoff has declined.
“And arrives at the same conclusion that freshwater runoff has declined.”
Rick, do they ever do checks for land use changes or other things that would effect runoff?
The second paper goes into some detail on the various factors that contribute.
It is indeed silly, but your first graph is truncated making the increase look outlandish. It is just a 4.5% increase overall, by my reckoning. From 1090 to 1140.
The doubtful part is not the size of the change. It’s the shape of the change—no change for 150 years, then within the space of a couple years going almost vertical.
Doesn’t pass the laugh test.
w.
Or this test –
Yes I said it was silly, a tipping point with no empirical basis. They do the same thing with temperature. We are about 40% through with doubling CO2, with a supposed warming of around one degree. But many of the CMIP6 models now predict over 5 degrees when CO2 doubles. This clearly requires a massive takeoff soon.
An artefact of tuning (ie fitting the clouds) through the strong El Nino years at the turn of the century is my guess.
“..no change for 150 years, then within the space of a couple years going almost vertical.”
That’s child’s play Willis. The world’s greatest climate scientist proved that the earth’s temperature gently declined for about 1,000 years before going almost vertical
I want to thank Nick Stokes for providing Willis with the link to another waste of taxpayer money.
Climate scientists would not be allowed to waste such huge amounts of taxpayer money if they didn’t keep the taxpayer and their representatives in fear of coming climate-change catastrophes. Scientists are just as human as everyone else. And if the fear of climate change keeps the grants and funding rolling in, then stoking that fear will always be a high priority for them. When the predicted climate catastrophes do not materialize over the next few decades, they will extend the dates out as far as they can and then blame it on faulty climate models. They will never apologize for their roll in deceiving us.
They’ve already been practicing this form of marketing (catastrophising) for more than thirty years. It sells wind and solar. People are only just starting to work out that the product is not fit for purpose.
We demand a refund!
Certainly sporting of Nick to provide a link. I, for one, would like to know if he thinks there’s anything ‘odd’ about Figure 1.
If the IPCC was honest and worked with good intent, this and other magnificent failings of the settled science would be openly scrutinized in IPCC assessment reports and prominent journals.
To not discuss, openly, such results from the only things we have that predict the catastrophic climate change – the computer models – is corrupt and dishonest, not to mention, scientific malpractice. This must be a collective intent to not reveal important contradictory information and is one of several revealed here at WUWT.
How can you make progress if you do not examine the core failings of the billion-dollar tools being used to investigate the purported existential threat?
Kudos to Willis and Nick S for bringing this to the light.
An observation with interesting consequences. Models don’t get rain credibly ‘right’, even in the lowest emission scenario.
Rain comes from clouds, which means they don’t get clouds right.
According to AR5 and AR6, clouds produce both albedo and cloud feedback. Which means CMIP6 cannot possibly have either of those right.
Which means CMIP6 cannot possibly have either resultant AGW or ECS right.
Which means CMIP6 is essentially worthless.
Which we already knew since only the the INM models do not produce an observationally non-existent tropical troposphere hot spot. See my comment to Andy May’s recent post here on that topic for details. And only the 2 INM models produce an ECS ‘close’ to observational EBM ECS of ~1.6-1.7. INM CM4.8 produced 1.8, while CM5.0 produced 1.9. Both therefore say cancel the alarm.
AR6 cannot allow that outcome. So IPCC got CMIP6 to increase the average model ECS from 3.4 in CMIP5 to 4.4 in CMIP6. Even worse divergence from EBM observational methods, which itself forced AR5 to explicitly not give a central estimate because of the 1:2 discrepancy between observations and models.
In Spain?
It went mainly down the drain.
The cellar’s flooded
The rain,
he ‘splained,
is not to be disdained.
Here is the 30 year precipitation record for Vancouver airport; a wet region but not getting wetter.
The modelled rain
In modelled Spain
Falls mainly in the modelled plain
Figure one has to be the product of a mind or two on ayahuasca.
I’m surprised you gave this the time of day. I have to assume there was fun in it somewhere.
And we should throw the models down the drain…..again.
Regards,
Bob
I recall that it seemed to fall in Maine rather than Spain in one of those proxy fiascoes.
The rain it raineth on the just,
And also on the unjust fellah,
But chiefly on the just because
The unjust steals the just’s umbrella.
Best to all.
Hey, Seadog, always happy to hear your voice, and that bit of doggerel is just too good.
My best to you and yours,
w.
Ogden Nash
Thanks, I couldn’t remember who it was.
Charles Bowen
We stand corrected.
Thanks.
And I
A hypothesis built on a hypothesis propagating beyond the point of probable return.
This plotting of anomalies on an exaggerated scale to show an inconsequential change is to my mind a form of dishonesty. The change as presented looks monstrous, when in reality it is tiny. The same as is done with temperature records. If plotted against the actual temperature range our planet experiences, the variation in global temperature averages is covered by a straight line the width of a pencil lead. If anomalies on a hyped-up scale are published, it ought to be required that a rational presentation should also be graphed along side the anomaly graph.
Again I say, the oddity is not the magnitude of the change.
It is the shape of the change, running totally level for 150 years and then suddenly skyrocketing.
w.
You can’t expect a “rational presentation” from the entirely irrational elites who have been pushing climate hysteria for 30 years. Irrational exuberance & hysteria are their only tools.
These numbers make no sense at all—what does “global rainfall” even mean? Integrated somehow?
Seems like if you take annual precip averages for a lot of locations around the globe and add them up, the total will be a lot more than 100 cm.
Figure 2 is astounding Willis! I have been tracking CMIP from its beginning and never heard about this SNAFU. If the models disagree this much on the past they are truly useless.
Ironically, CMIP was originally developed by skeptics at the US Energy Dept, to show that the models contradict one another. Your figures do that very well. As we say in the mountains, what goes around comes around.
DW, Judith Curry posted something similar for CMIP5 hindcasts. Used absolute temps rather than anomalies. Spread from 12C to over 15C and NO convergence from 1850 to 2000. AR5 hid this by using anomalies, as WE figure 3 does. She got her figure from Mauritsen et al 2013 ‘Tuning the climate of a global model’ in J. Adv. Modeling Earth Systems. I reproduced her figure in essay Models all the way down’ in ebook Blowing Smoke.
Aren’t researchers held to any standard? Is there any way that the first graph could be legitimately justified? I don’t appreciate my scarce resources being misused by these knuckleheads.
“Aren’t researchers held to any standard?”
Er…no. Not government employees anyway. They’re just paid to come up with information that supports the agenda, no matter how ludicrous.
I second your question.
The crime of bad scientists is not making a mistake. It’s refusing to look for them, let alone refusing to acknowledge that a mistake was made.
I reckon that plot is an example of dog’s balls floating in the milk. It just can’t be the result of a small mistake that was missed in the modelling.
All climate models start with the false premise that “greenhouse gasses” control earth’s energy balance and therefore climate.
The culprit that is responsible for earth’s energy balance is actually solid water – not any gas. Whether it is in the form of cloud that limits tropical oceans to an annual maximum of 30C or sea ice that limits the minimum ocean temperature to -1.8C.
Both these ice forming processes have tremendous power in regulating the energy balance. With regard the upper limit, tropic clouds will make the surface perpetually dark if it was possible for the surface of open ocean to reach 32C; knocking out 90% of the incoming insolation before it is thermalised. With regard the lower limit, if the nuclear reactors in the sun and Earth stopped today, it would take 35,000 years before the top 2000m was frozen. Sea ice 0.9m thick halves the radiating power of the water just below it.
The terms of reference for IPCC is about mathematical modelling.
UNFCC / IPCC modeling is done under the assumption that ecodynamic water cycle effects are so dominant that we couldn’t possibly have an influence on it. Additionally, it is assumed that water is so variable in time and space that it is impossible to model mathematically. This is why the problem has been reduced to CO2.
It is built in that water dynamical effects are not attempted to be simulated. So, the outputs of precipitation for the purpose of CMIP greenhouse effects should be presented with a warning that they will have no relation to the real precipitation regime. It has been an error to present the outputs as containing any actionable information.
Freshwater runoff from land is a direct result of latent heat transfer from ocean to release over land. The net radiative heat loss from land in the two hemispheres is accurately described by:
Net Radiation = (ToA Insolation) * 0.52 – 185 in W/sq.m
Adding and integrating the Net Radiation for both SH and NH land masses gives global net radiation over land, which can be directly related to global freshwater runoff simply allowing for the latent heat of evaporation.
On this basis, net precipitation has been declining for the last 12,000 years as the sun’s most intense view has shifted from NH to the water dominated SH and reached its minimum around 1600 for the current precession cycle. It will rise at about half the rate it fell over the next 9,000years. January rainfall will increase by 10% over that period and will increasingly fall as snow over the northern land masses.
Can you explain more.
Naturally, latent heat flux is a manifestation of the water cycle. It is the variable in question.
You are like IPCC. You assume the ratio of sensible and latent heat flux is fixed and a no-brainer. plain wrong. ‘Simply’ plug-in the known value, right? Easy to predict runoff in 9000 years…at hemispheric scale, no less. very useful indeed.
In reality, there are innumerable biogeochemical changes influencing these processes. It is why it is glazed over.
Afghanistan was once like the alps, with little Heidi’s running around in the fertile forested landscape. Today it is desert wasteland with eroded and dry river channels, like the rest of the ‘fertile crescent’. Record smashing wet-bulb temps with no way for air to precipitate.
How’s the latent heat flux going there? How is western australia going with the wheat fields? California?
I look forward to your empiricism and simple runoff projections.
WRONG – IPCC is based on modelling fantasy that has no bearing on physical reality.
The simple correlation I provide is consistent for both hemispheres with significantly different solar exposure for land and oceans in both hemisphere for the CERES era. It has regression coefficients of 97% for land, including sea ice, and 94% for sea ice free oceans.
The equation for oceans is:
Net Radiation = Insolation * 0.71 – 230
The land alone is sufficient to determine freshwater runoff.
Interpreting these simple equations, the land masses absorb 52% of the incoming insolation and require 185W/sq.m to be in thermal equilibrium.
Oceans absorb 71% of incoming insolation and require 230W/sq.m for thermal equilibrium.
The range of insolation for these regressions is not trivial. NH land masses insolation varies from 151W/sq.m in December to 472W/sq.m in June. SH land 140W/sq.m to 496W/sq.m. NH oceans 264 to 454; SH oceans 225 to 490.
So the ranges for the regression are quite large. The slightly loopy nature of the ocean curves indicates a slight delay between insolation and heat absorption. The land has very little time delay.
Something very few people appreciate is that the South Pole has the highest daily insolation of any location on Earth in the present era.
By dividing the planet into hemispheres and water and land surfaces we can already build a very good picture of how Earth responds to changing solar forcing.
Net Radiation = (ToA Insolation) * 0.52 – 185 in W/sq.m
Here you are quantifying the average net radiation over the CERES period over land. Thank you.
You then vary ToA insolation to make predictions.
You are pointing out that net radiation = total heat flux.
This based on a CERES vertical profile forced to balance; it’s no bother.
In reality, especially over land, the 0.52 factor absorbed will vary over time.
The net radiation may well depart from your ToA insolation curve.
The 185W tells us nothing about the partitioning of surface flux into latent heat and sensible heat over the CERES period.
We know, only, that there is average 185W m-2 heat flux at the surface.
So, we do not have a predictor of latent flux, and certainly not precipitation over land.
We have no idea what clouds are doing. Only an average net SW over CERES period.
So, we do not have information to predict partitioning of the radiation into net SW and LW budget over time from ToA insolation.
Overall, you assume the ratio of solar absorbed, net LW, latent heat, and sensible heat is fixed to ToA insolation based on fitting the CERES averages.
You are then projecting this ratio into the future based on a ToA curve, correct?
By far the most significant role of cloud is regulating the upper SST limit to 30C. That role dominates the function of clouds from the perspective of the energy balance. Providing there is enough sunlight to create an excess, the average ocean temperature is fixed to a very narrow range.
I calculate the ToA insolation based on the orbital geometry by latitude in degrees for each month and apply a land/ocean mask for each month in both hemispheres to determine the average insolation over the four nominated portions of the globe.
The differences between the NH and SH are significant in terms of the distribution of water and yet both hemispheres reduce to almost identical regression lines for the land and ocean portions.
I am able to predict the net radiation for both ocean and land in both hemispheres. So I can determine the energy balance and the amount of latent heat transfer from oceans to land to avoid the land going cold. Consequently, I can predict, with some accuracy, the net evaporation from oceans and freshwater runoff from land.
The big factor that will change will be glaciation producing ice mountains. That will lower the average surface temperature of land and probably reduce the 0.52 factor for land – I am banking on it for my scenario for Afghanistan getting wetter. Keep in mind that there are already two substantial ice mountains on the globe that are influencing the amount of absorbed sunlight on land.
The major changes that will occur in the region of Afghanistan in the coming millennia will be driven by increasing boreal summer sunlight and reducing boreal winter sunlight.
The monsoon of the Arabian see will continue later into the year. The Mediterranean Sea will achieve higher surface temperature as well as the 45mm of precipitable water needed to go into cyclic convective instability thereby generating monsoon in the Mediterranean. So there will be more atmospheric water in the vicinity of Afghanistan in summer than now.
December, January and February will remain the period of greatest ocean heat uptake but more of the resulting precipitation will fall as snow in Europe, North America and Asia get colder during the boreal winter. The increasing snow and advancing glaciers will reduce the early summer heat uptake in Afghanistan so it will become a moist air convergence zone for the increasing atmospheric water in the boreal summer from increasing monsoon. The conditions now observed in India will advance northward as the peak insolation advances northward.
Bold, and sounds bad. The soil retains no organics anymore, and there are rarely any precipitation nuclei. Only humid microdrop hazes and rock flour. It’s bad.
The water vapor just passes right on through.
Hopefully the ToA radiation will fix it, as you seem to suggest, considering your latent heat flux from land is fixed to ToA..
TPW already reaches its maximum in July when the latent heat uptake is at its minimum and ocean surface temperature regulation is near its peak. Afghanistan currently gets warmer than the Arabian Sea as it moves into monsoon in May and never becomes a convergence zone. It is a perpetual low pressure region.
As winter snowfall increases, that will delay the rate of surface warming and moisture from the Arabian Sea will converge.
Central Australia is mostly a divergent zone during during the austral summer but in periods of double dip La Nina phases such as just experienced, the moisture builds to levels that triggers cyclic convective instability and then the centre becomes a convergent zone and gets massive amount of rain coming in from the surrounding ocean. A similar situation will occur in Afghanistan once snow builds sufficiently to delay summer warming
We are already seeing the land masses greening. This is mostly due to getting CO2 above biomass survival level however there should already be contribution from the precession cycle shifting the intensity of the seasons as I have explained.
The boreal summer solar intensity peaks in 9,500 years and the boreal winter will reach its minimum in the present cycle about then. That is when snow accumulation peaks.
In the last four periods of glaciation, glaciation deepened for three or four precession cycles before the atmospheric dust was sufficient to lower the snow albedo and bring the melt during the next precession cycle.
In terms of geological timescale, biomass recovery is a blink in time.
The parallels to IPCC in your logic are quite apparent. You both boil down to climate to a simple forcing curve. You both believe the hydrological cycle is bound to your forcing curve. And you use your assumptions to downscale projections in specific small regions. In your case, however, the claims can never be verified.
My principle claims are upper and lower limit on open ocean surface temperature. That can be verified on every day of every year through existing measurement systems:
https://earth.nullschool.net/#current/ocean/surface/currents/overlay=sea_surface_temp/orthographic=-230.86,-14.31,315/loc=155.769,-9.633
My other claim is that orbital mechanics drive the long term climate trends and they are already apparent in the modern records.
The main claims prohibit runaway global warming or cooling. But the next period of glaciation is already upon the planet.
These bounds are merely a consequence of surface pressure. This subject is not permitted on WUWT. Your ocean limits allow swings from snowball earth to hothouse, depending on the proportion of ocean surface reaching your limits. Quite a wide range. Besides, our food system and cities exist on the continents, so you might give some thought to land surface energy budget.
I do not believe this is new or disputed by IPCC. They superimpose their greenhouse enhancement hypothesis upon your orbital mechanics.
Before you dart off in another direction, take some time to consider your thoughts.
The period of interest for climate policy is 100s of years, not 1000s. Nobody will be willing to wait and see if the monsoons arrive in thousands of years. They first need to understand why their landscape has aridified and be offered practical solutions. Without understanding the mechanisms they will resort to wild policy choices such as banning CO2. This is because radiation physicists appear to be the only ones offering solutions (right or wrong).
You should understand your notion of latent heat flux from ocean arriving over land has no bearing on latent heat flux from land, i.e. the primary cooling mechanism of the surface. You have not adequately demonstrated an understanding of latent heat flux because you are dealing in statistics over a 20 year period. The land both needs to retain moisture and deliver latent heat flux aloft to cool. Receiving latent heat from elsewhere is useless. The latent heat needs to be delivered aloft, and originate from the land surface.
Evaporation from ocean does not necessarily result in precipitation over land. There is much more to it than that. Your ocean moisture arriving over land simply slams the IR window shut for longer if it can’t precipitate. It is biotic precipitation nuclei that gives a smooth and predictable precipitation regime, and fog drips. Under your scenarios we could go months between rain events followed by erosive inundations once condensation density sufficiently builds and breaks through the high pressure domes.
Your ocean limiting factor has no bearing on continental temperature or precipitation. Some of the most inhospitable places on Earth are near coastlines, not to mention the interior. Hypothetically (unlikely), we could all starve in humid deserts while your ocean limiting factor is still in play. This argument has no bearing on practical climate discussions.
There is more going on than you appear to realize. Destroying the biosystem and stable soil carbon organics certainly has consequences, like it or not.
Pointing out such simple, local solutions, puts us much closer to getting off the CO2 will kill us train than your global average CERES statistics, I’m afraid.
Willis,
Thanks for the interesting article confirming exactly what we all feel about models.
More importantly, many thanks for the glorious photo at the top…is that from the Solomons?
Lake Tanganyika.
w.
Gosh…not even close!
It’d be a great photo for a science textbook…classic example of a picture being worth a thousand words. All you ever needed to know about rainbows and their origin.
“Thanks to Nick Stokes, who pointed me to the University of Melbourne Computer Model Intercomparison Project 6 (CMIP6) data repository,”
Well if so much questionable science came out of looking at the CERES data, I can only imagine what’s going to happen now…
The first graph looks alarming. The projected rainfall in 2100 appears to be many times higher than that in 2000. But the graph is deceptive because the y axis doesn’t start at zero. So we have to look at the numbers. The projected rainfall in 2100 is approximately 1140mm. In 2000 it is about1090mm. So the increase is 50 mm or about 4.6%. That doesn’t seem alarming at all. It certainly is not an “existential threat”.
Deceptive? I look at the “numbers” whenever I look at a graph. If the graph doesn’t have numbers, then I might be thinking there some deception going on.
The Chinese FGOALS model is inevitibly the least scary. Its other output variables like surface temperature are also less scary. It has struck me as being plausible, but on close examination is the same claptrap as all the other models, just not as sensitive to CO2.
The easiest way to test the validity of a model is if it has a cooling trend in the Nino34 region over the last 4 decades as actually occurred or if any ocean surface exceeds 30C over an annual average. FGOALS is close on the first criteria without the sufficient excursions to create El Nino or La Nina phases but achieves a warming trend for the second test by cooling the present substantially.
The rain it raineth on the Just,
And also on the Unjust fella,
But mainly on the Just, because
The Unjust stole the Just’s umbrella….
Willis, you are carrying away pseudo ‘climate science’ with real science and they do not like it at all.
Can someone tell me why the increase in temperature from 1900 to 1940 caused no change in modelled rainfall and yet the same temperature rise going forward from 2020 causes bucketfuls of the stuff?
And can someone who knows Flannery (“the rain that falls won’t fill our dams”) ask for his comments on this – he could clear up a lot of unresolved issues and calm a lot of sceptics if he lucidly explained his projections here?
That’s an easy one. The warming 1900 – 1940 was natural, therefore nothing bad happened.
But the warming post-1950s was man-made, so its a different kind of warming that makes everything bad and worse than before.
I don’t need the /sarc do I?
These climate modelers really are short sighted idiots with no idea how the physics works or the ability to make back of the envelope calculations.
The rain in Spain stays mainly plane
Figure 1 shows rainfall is expected to rise by some 45 mm or 4.1 percent. All rain has to be evaporated first. Surface evaporative cooling was already 80 W/m2 (link graphic below) and has to rise by 4.1% = 3.3 W/m2.
The surface should be cooling in 2100.
https://www.researchgate.net/figure/The-global-annual-mean-earths-energy-budget-for-2000-2005-W-m-2-The-broad-arrows_fig1_257564838
This.
I’m genuinely amazed at how many people who really ought to know better see things in terms of “heat” (ie its hotter therefore more evaporation) and not energy. They must believe that energy returns somehow after its released into the atmosphere as clouds form. More likely they dont even get as far as understanding the issue at all.
The most forgotten word in climate discussions is the word ‘initial’. Carbon dioxide has an initial warming effect. Immediately after atmospheric absorption of surface radiation and consequent warming of the immediate surroundings of the absorbing molecule, cooling processes start. Evaporation is one of them. By convection, latent and sensible heat is brought to elevations from where radiation is effective in reaching space. Extra convection cools in the second instance the surface and from the top of the clouds and above them, effective radiation into space takes place. The surface and the Earth are both cooled and initial warming is diminished, if not completely eradicated.
A collective blind spot.
People get so fixated on the global temperature anomaly and try to claim models do a good job of matching the temperature record.
Even if they did…all of the other data that generates those results is @%#%$@# on a regional level and usually on a global scale as well.
Adding up a bunch of garbage to get a global value that looks close to being right is BS, like the kid on his test who does the problem wrong but gets the right answer and expects full credit.
It’s dishonest and unethical for the IPCC, climate modeling community, and others to stand behind the model results.
Haven’t gotten through the entire post yet, but my first reaction was, “Wow! How to make a 10% increase look HUGE”.
I fear that like others, you’ve missed the point. It’s not the amount of the increase. It’s the shape of the increase—pretty much dead level for ~150 years, then within a few years going straight vertical.
I’ll add a note to the head post to clarify that.
w.
Thanks again to Willis and I presume that Nick Stokes agrees with Willis’ summary of the data.
But thanks to Nick as well.
SOOOO. Should I buy a raincoat and umbrella????? Living in CNA.
I think this article is a little disingenuous. First, I grant that the relative stability with the sudden increase is surprising. But when I look at total rainfall level moving from 1090 mm to 1140 mm per year I read that as a 5 percent increase in precipitation forecast over the next 100 years. That is a much less agregious increase than talking about a three fold increase. You are basically talking about an increase projected of between 1.8 percent to 5.4 percent depending on the model. My guess is that is below the ability of the models’ accuracy. While I believe that the hype of climate change alarmism is ridiculous and I am quite sure the alarmist pointed at the sharp increase in the first graph as cause for alarm; it is neither a sharp increase or cause for alarm.
Who said that the 5% projected increase in precipitation is alarming? Alarming is the fact that in some quarters, these model outputs are taken seriously. One could say the same about an increase in global temperature by 1K which would be about 0.3% on the Kelvin scale. You can’t even feel the 1K difference but it’s purported to be a climate emergency. Willis is merely pointing out the interesting and suspect behaviour of these models as he had to reiterate a number of times in the comments.
Its a very stark change starting in the late 90s. More than a bit odd, wouldn’t you say?
Why not 1950 when the IPCC claims we started detecting AGW? It actually decreased around that time.
The first graph look scary it’s not 4 or 5 % increase predicted but compared to the history even that is ridiculous more spin
“the largest results in the 1800’s are no less than 15-20% higher than the lowest result. I can understand models getting the future wrong … but when they get the past wrong, I get very nervous”
It’s not clear to me how well we really know the global precipitation, even today. However, for what data that is available, there seems to be a significant increase in global precipitation post 1950 compared with earlier periods. It is notable that most of the models show a pronounced dip in precipitation around 1950, contrary to the available data. The models are clearly getting something badly wrong.
See e.g.:
https://www.epa.gov/climate-indicators/climate-change-indicators-us-and-global-precipitation
for historical global precipitation data.
The story for modelled precipitation seems to parallel the situation for global absolute temperatures – the models were all over the place for absolute temperatures, while supposedly getting the temperature anomalies bang-on!
“The rain it raineth on the just. And also on the unjust fella; But chiefly on the just, because. The unjust hath the just’s umbrella.” ― Charles Bowen.
If climate models were based on physics, we would only need one model.
They are nothing more than the opinions of scientists who have no underlying physical model to describe what they have coded. They should start with understanding the physics before attempting to build a model of it.
“If climate models were based on physics, we would only need one model.”
This is a succinct way of putting it.
So, the relatively dry Mediterranean is going to get even drier, putting paid to that old adage: ‘The modelled rain in Spain falls mainly on the modelled plain’.
Australia has lots of rain data Look at this site https://www.longpaddock.qld.gov.au/rainfall-poster/ The rain in Australia clearly has nothing to do with CO2 but lots do do with SOI and IPO variations as shown in the posters. Same goes for cyclones and cyclone tracks.I have nearly 130 years of daily and monthly rainfall data for my area. The heaviest rainfall period was in the 1890s. but in total of the 130years there is no trend in rainfall only periodic oscillation between heavy (floods) and light (droughts)
w. ==> There are way too many nuttinesses in the CMIP6 results to mention all of them.
#1 — The top graph is Global Annual Rainfall in mm. What the heck is that when it gets up in the morning? There is no such thing in the physical world as Global Annual Rainfall. Averaged by square km? evenly spread out where? Nonsensical (far worse than Global Surface Temperature). The total difference between the early part of the record to the recent portion is only 2 inches of rainfall. That is not exactly a “skyrocket” — we often have a far greater range year to year and decade to decade in my region of the world. We would not notice such a change in a single year.
You are right of course, there is something wacky about the CMIP6 output — the tiniest oddity in the coding could produce that small of a change — right at the turn of the century? some kind of Y2K thing? (almost a joke….)
Overall, this is meaningless (except being yet another demonstration of the foolishness of using chaotic climate models to make international policy).
It also really seems quite hard to reconcile with permanent and/or mega drought claims issued in parallel.
dk_ ==> It is, in general, nutty (a very scientific term, to be sure). There is no real world average global rainfall. A better metric might be square km in ranges of drought and the same for areas with exceptional rainfall.
Kip: I asked this same question above and no one could provide any answers or information.
Carlo ==> any your question is the very point to be made out of all this. And, I do not believe there is a reasonable answer to why anyone would even try to calculate such a single number for global annual rainfall. It isn’t. It does not exist in reality (though it seems to exist as a number).
Willis, is there a graph available for world-wide actual rainfalls? I’m sure it would be laughably incomplete, but since we’re 2 years past the start of panic time according to the models, it might be instructive to make the comparison. I took a quick Google, but didn’t find anything meaningful.
These are the (reanalysis) Data of ERA5 for the global rain. Note the divison of the abszissa with a change of 0.2 mm/day at max.!
What is ERA5? The comment on the graph says it is total world rain, but how is it determined? Ref?
“What is ERA5?” Google is your freind.
It’s a “reanalysis”, which is a climate model which is constantly nudged back on course by feeding it whatever data is available. Better than nothing … sometimes, worse than nothing other times.
w.
Willis, nice to explain such “google-able” facts. However, who follows such “deep questions” to this point … it’s too much to demand to answer those questions for himself instead of posting it? best Frank and thanks for this enlightining post!
Unfortunately, Mr Johnson only gets shown Figure 1 which justifies Carrie Antoinette and his actions.
There is a lot of uncertainty but the rain increase roughly coincides with the increase in water withdrawal; mostly for irrigation. Assessment of world sources of water vapor increase is at Section 9 of http://globalclimatedrivers2.blogspot.com
A four percent increase in global precipitation means an increase of 3,1 W/m2 in negative feedback, right? (4% of trenberth diagram 78 w/m2 for evapo-precip)