Observational data of equatorial circulation pattern confirms that the pattern is weakening, a development with important consequences for future rainfall in the subtropics
Columbia University School of Engineering and Applied Science
News Release 24-Jun-2019
New York, NY–June 24, 2019–For decades, scientists studying a key climate phenomenon have been grappling with contradictory data that have threated to undermine confidence in the reliability of climate models overall. A new study, published today in Nature Geoscience, settles that debate with regard to the tropical atmospheric circulation.
The Hadley circulation, or Hadley cell–a worldwide tropical atmospheric circulation pattern that occurs due to uneven solar heating at different latitudes surrounding the equator–causes air around the equator to rise to about 10-15 kilometers, flow poleward (toward the North Pole above the equator, the South Pole below the equator), descend in the subtropics, and then flow back to the equator along the Earth’s surface. This circulation is widely studied by climate scientists because it controls precipitation in the subtropics and also creates a region called the intertropical convergence zone, producing a band of major, highly-precipitative storms.
The study, headed by Rei Chemke, a Columbia Engineering postdoctoral research fellow, together with climate scientist Lorenzo Polvani, addresses a major discrepancy between climate models and reanalyses regarding potential strengthening or weakening of the Hadley circulation in the Northern Hemisphere as a consequence of anthropogenic emissions.
Historically, climate models have shown a progressive weakening of the Hadley cell in the Northern Hemisphere. Over the past four decades reanalyses, which combine models with observational and satellite data, have shown just the opposite–a strengthening of the Hadley circulation in the Northern Hemisphere. Reanalyses provide the best approximation for the state of the atmosphere for scientists and are widely used to ensure that model simulations are functioning properly.
The difference in trends between models and reanalyses poses a problem that goes far beyond whether the Hadley cell is going to weaken or strengthen; the inconsistency itself is a major concern for scientists. Reanalyses are used to validate the reliability of climate models–if the two disagree, that means that either the models or reanalyses are flawed.
Lead author Chemke, a NOAA Climate and Global Change postdoctoral fellow, explains the danger of this situation, “It’s a big problem if the models are wrong because we use them to project our climate and send our results to the IPCC (Intergovernmental Panel on Climate Change) and policy makers and so on.”
To find the cause of this discrepancy, the scientists looked closely at the various processes that affect circulation, determining that latent heating is the cause of the inconsistency. To understand which data was correct–the models or the reanalyses–they had to compare the systems using a purely observational metric, untainted by any model or simulation. In this case, precipitation served as an observational proxy for latent heating since it is equal to the net latent heating in the atmospheric column. This observational data revealed that the artifact, or flaw, is in the reanalyses–confirming that the model projections for the future climate are, in fact, correct.
The paper’s findings support previous conclusions drawn from a variety of models–the Hadley circulation is weakening. That’s critical to understand, says Polvani, a professor of applied physics and applied mathematics and of earth and environmental sciences who studies the climate system at the Lamont-Doherty Earth Observatory. “One of the largest climatic signals associated with global warming is the drying of the subtropics, a region that already receives little rainfall,” he explained. “The Hadley cell is an important control on subtropical precipitation. Hence, any changes in the strength of the Hadley cell will result in a change in precipitation in that region. This is why it is important to determine if, as a consequence of anthropogenic emission, the Hadley cell will speed up or slow down in the coming decades.”
But these findings resonate far beyond the study in question. Resolving contradictory results in scientific research is critical to maintaining accuracy and integrity in the scientific community. Because of this new study, scientists now have added confidence that models are reliable tools for climate predictions.
###
About the Study
The study is titled “Opposite Tropical Circulation Trends in Climate Models and in Reanalyses.”
Authors are: Rei Chemke (Department of Applied Physics and Applied Mathematics, Columbia Engineering) and Lorenzo M. Polvani (Department of Applied Physics ad Applied Mathematics, Columbia Engineering; Department of Earth and Environmental Science, and Lamont-Doherty Earth Observatory, Columbia University).
The study was supported by the NOAA Climate and Global Change Postdoctoral Fellowship Program, administered by UCAR’s Cooperative Programs for the Advancement of Earth System Science (CPAESS). Lorenzo Polvani is grateful for the continued support of the U.S. Nat. Sci. Foundation.
The authors declare that they have no competing financial interests.
LINKS:
Paper: https://www.nature.com/articles/s41561-019-0383-x
DOI: 10.1038/s41561-019-0383-x
https://www.nature.com/ngeo/
http://engineering.columbia.edu/
https://reichemke.wixsite.com/reichemke
https://engineering.columbia.edu/faculty/lorenzo-polvani
https://apam.columbia.edu/
https://www.ldeo.columbia.edu/
Columbia Engineering
Columbia Engineering, based in New York City, is one of the top engineering schools in the U.S. and one of the oldest in the nation. Also known as The Fu Foundation School of Engineering and Applied Science, the School expands knowledge and advances technology through the pioneering research of its more than 220 faculty, while educating undergraduate and graduate students in a collaborative environment to become leaders informed by a firm foundation in engineering. The School’s faculty are at the center of the University’s cross-disciplinary research, contributing to the Data Science Institute, Earth Institute, Zuckerman Mind Brain Behavior Institute, Precision Medicine Initiative, and the Columbia Nano Initiative. Guided by its strategic vision, “Columbia Engineering for Humanity,” the School aims to translate ideas into innovations that foster a sustainable, healthy, secure, connected, and creative humanity.
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resolving contradictory results ???? no you have to throw out one of your results … and since they can’t throw out the observations (i.e. real world) they instead try to “resolve” the contradiction … which is fraud …
This is the line that gets the laughs: “A new study, published today in Nature Geoscience, settles that debate with regard to the tropical atmospheric circulation.”. It doesnt settle anything. It just means that more studies are needed.
For now it seems that using contradictions between the models and the reanalysis as an argument that the models are wrong should be suspended. With this research, it will be a controversial argument, and thus a weak one, or an incorrect one. Who wants to use weak or incorrect arguments?
They reanalyzed the data and concluded that the data was wrong and the models were right.
More contradictions in a sea of contradictions.
The late Wm Gray said that global warming would speed-up the hydrologic cycle. This battle between reanalysis and GCMs appears to contradict such. Also, the standard assumption is that a heating world produces more moisture in the atmosphere, thus a positive water vapor feedback, but we then learn that climate models show a warming world dries out the subtropics.
I know for certain that where I live the coldest and the hottest air is also the driest. The wettest air is that which comes from particular directions, and usually of modest temperature.
Two related questions: Do GCMs show the poles becoming drier and the tropics becoming wetter?
Their “report” on model reliability is completely unreliable.
To me one fatal flaw in the modelling lies in the confabulation of convection versus the buoyancy inherent in water vapor. The first is driven by temperature difference whereas the second is based on molecular structure of vapor which makes it lighter than dry air. ( see the periodic table and compute the molecular weights.)
The result is that water vapor rises independently of temperature difference and the two should not be equated in the models or calculations.
The image above seems to me to illustrate this point as interspersed within the cloud structure we see columns of vapour rising at specific points. Why this one may well ask?
The description below refers only to convection, ignoring the buoyancy element and this I suggest is where the flaw lies. A flaw that makes my teeth grind in so many of the articles I read, both alarmist and sceptical.
Overall it this buoyancy factor which drives the inherent Latent Heat UPWARDS to the clouds and beyond quite independently of CO2 .
I wonder how many (or few) model grid cells would fit in the lead photograph? I suspect the number is quite small.
And just gets worse with the smushing that the smoothing causes
On intelligent days WUWT is a Mosher free Zone.
The rational approach is just wait until 2030 and see where the data is leading us…except of course certain groups of advocates keep changing the data, and keep wanting to “take action now” to prevent the end-of-the-world as now predicted by (some) advocates in 2031.
(I will state this one more time…you cannot just mix land temperature data and near surface ocean data as if they represent the same measurements, so please stop it!)
Without data that can be trusted, this argument (it sure isn’t a debate) will never end.
If the warming trends remain near or below the predicted lowering warming trends predicted by averaging a set of flawed models, then we should be able to just close this book (of flawed science) and toss it in the rejected bin of history.
Robert of Texas
“… you cannot just mix land temperature data and near surface ocean data as if they represent the same measurements …”
+1
No, Robert: It has been reported that the UN IPCC CMIP6 models will run hotter than the CMIP5 models. They are doubling down in their attempt to force the Western world into suicidal actions before anyone can counter the hysteria.
Buy stock in China and India. The West is proving it cannot make rational decisions.
From the article: “Because of this new study, scientists now have added confidence that models are reliable tools for climate predictions.”
Maybe so but your models don’t establish that CO2 will have anything to do with it. All your models say is that a certain increase in warmth will cause the Hadley circulation to change.
Bingo, Tom!
UN IPCC climate models rely on the continued increasing worldwide temperatures driven by (certain) CO2 increases, with 3X water vapor amplification. Given the Pause, interrupted by a Super El Nino, and the lack of a tropical tropospheric hot spot, one would assume the 3X amplification SWAG is disproved. [SWAG: Stupid Wild-Ass Guess.]
From the article: “One of the largest climatic signals associated with global warming is the drying of the subtropics, a region that already receives little rainfall,” he explained. “The Hadley cell is an important control on subtropical precipitation. Hence, any changes in the strength of the Hadley cell will result in a change in precipitation in that region. This is why it is important to determine if, as a consequence of anthropogenic emission, the Hadley cell will speed up or slow down in the coming decades.”
Well, first of all, I would be interested in how you are going to determine if anthropogenic emissions are causing these actions. I don’t think you can provide any evidence of that and you seem so sure of yourself, but I think you assume too much.
My next question is what did the Hadley circulation look like in the hot decade of the 1930’s? How does the Hadley circulation then, compare to the Hadley circulation now?
Recall the Dust Bowl of the 1930’s in the central U.S., and the high heat all around the globe at the time. The IPCC says this warmth in the 1930’s was mostly caused by Mother Nature, not CO2.
Today’s warmth is supposedly caused, according to the IPCC, mostly by CO2 yet it is no warmer today than in the 1930’s, so being prudent, we should assume Mother Nature is the driver until proven otherwise, and there is no evidence that CO2 is the driver of the climate.
That doesn’t invalidate your work, but you shouldn’t assume current warming is caused by CO2 until you see some evidence of that. Btw, CO2 is climbing but global temperatures have been dropping for the last three years, since. Feb. 2016, down 0.5C since then. I wonder if that shows up in your Hadley circulation study.
+50
“ … toward the North Pole above the equator ”
And Chicago is at the bottom of Lake Michigan.
Once more a paper whose claims don’t fit their actual data. They claim a weakening of the Hadley cycle, yet the TGCP precipitation data shows a significant long-term increase in tropical rainfall, though considerably less than both Reanalysis or CMIP5 estimates. So the Hadley cell is strengthening, as is essentially unavoidable if temperatures are increasing, but only slightly, presumably because temperatures really aren’t increasing much.
As for subtropical precipitation the TGCP data are ambiguous, showing a slight decrease in the northern hemisphere and a slight increase in the southern hemisphere. Neither is probably statistically significant. In this case reanalyses do slightly better than CMIP5.
TGCP also show significantly increasing precipitation around 60 degrees latitude, presumably due to increased moisture transport from lower latitudes. Neither reanalyses or CMIP5 do well there.
It is interesting to see that both CMIP 5 and Reanalyses suffer from “double ITCZ”, I e they model two ITCZ, one on each side of the equator, something that doesn’t happen in the real world.
Please don’t confuse the modelers on both sides of the dispute with data, tty.
Please don’t confuse the modelers on both sides of the dispute with data, tty.
This is why it is important to determine if, as a consequence of anthropogenic emission, the Hadley cell will speed up or slow down in the coming decades.”
settled science
A lot of helpful comments here for those of us trying to make sense of this claim of CMIP5 models coming out more reliable than data, even it is of the “reanalysis” type. I noticed that the issue was specific to NH Hadley Cells, thus concerned with 0 to 30N latitudes: CMIP models tend to say HCs are weakening there while 40 years of reanalysis data says the opposite. Here is a 2018 paper suggesting the discrepancy is complicated:
“Observed trend maps and assessments for annual mean precipitation over 1901–2010 (Fig. 3a) show a preponderance of increasing (wetting) trends, especially in the extratropics. While there is some broad-scale resemblance of the CMIP5 all-forcing ensemble mean trend pattern (Fig. 3b) to the observed trend pattern (Fig. 3a), the modeled pattern clearly shows greater coverage and prominence of decreasing (drying) trends than observations.”
“While our analysis can identify inconsistencies between observed and modeled trends, it cannot determine their causes. Potential causes can include 1) errors in observed trends due to data quality/homogeneity issues (discussed in section 4), 2) errors in specified historical forcings, 3) errors in the model simulated response to the specified forcings, and 4) underestimation of internal variability by the models. The observation–model discrepancies (in terms of precipitation trend maps or zonal mean trends) found for 1901–2010 trends are not as compelling for trends over more recent periods (e.g., 1951–2010 or 1981–2010). The zonal mean trend discrepancies for 1901–2010 are not remedied by using a more constrained atmosphere-only model forced by observed SSTs and climate forcing agents. The observed zonal mean trends are shown to be fairly consistent across three observational datasets, suggesting that observational biases may not be the primary cause of the model–observation discrepancies.”
“We conclude that although inhomogeneities in observed precipitation data may play a role in the observation–model discrepancies in century-scale trends, there is sufficient evidence, based on our preliminary cross-dataset comparisons and the spatial coherence of the trend assessments across large regions, to tentatively suggest that the identified trend bias is real and not simply an artifact of data homogeneity problems.”
Model Assessment of Observed Precipitation Trends over Land Regions
https://journals.ametsoc.org/doi/full/10.1175/JCLI-D-17-0672.1
A further point is that the CMIP ensemble models project quite widely and also use RCP8.5 wild assumptions, leading to a drying bias. Conversely, the outlier INMCM5 Russian model appears also to handle precipitation differently than the others. From recent documentation:
“Precipitation:
In mid-latitudes, the positive precipitation bias over the ocean prevails in winter while negative bias occurs in summer. Compared to the INMCM4, the biases over the western Indian Ocean, Indonesia, the eastern tropical Pacific and the tropical Atlantic are reduced. A possible reason for this is the better reproduction of the tropical sea surface temperature (SST) in the INMCM5 due to the increase of the spatial resolution in the oceanic block, as well as the new condensation scheme. RMS annual mean model bias for precipitation is 1.35mm day−1 for the INMCM5 compared to 1.60mm day−1 for the INMCM4.”
Precipitation, mm/day Observed: 2.5–2.8 [23] INMCM5: 2.97 ± 0.01
Source: https://rclutz.wordpress.com/2018/10/22/2018-update-best-climate-model-inmcm5/
RE: Cover photo from space station.
Interesting as the strongest/highest convection clouds show some clearing around them. Did the strongest convection clear the surrounding area by drawing in its energy/clouds for upward transport OR did open areas allow solar energy to the ocean surface which set up the deep convective towers? Chicken or egg first scenario?
Generally the updrafts in a thunderstorm turn into downdrafts around the storm even though the air is warmed (lower density) and dried (higher density) while in the storm. The air has to go someplace, and that’s down. The downdrafts are too dry to support clouds.
Strong hurricanes are topped by high pressure that helps force the exhaust away from the storm and “make space” for more convection.
Ric,
But what starts the updrafts where they start and what fuels them?
It would be nice to see a time lapse video related to the featured pic, both before and after @ur momisugly 1-2 hour intervals.
The reanalyses are wrong => some model is correct. Really??
Also: “Therefore, a WITCH!!!!”
You see, the fact that the reanalyses are wrong doesn’t preclude the models from being wrong at the same time. It says absolutely NOTHING about the models. This whole article is one big logical fallacy.
One patent flaw in this approach is equating precipitation with net latent heating IN THE ATMOSPHERIC COLUMN. Neither variable is solely the product of geographically local physics. The latent heating takes place where water vapor condenses, which may be hundreds of kilometers away and days after the evaporation took place. The advective displacement of eventual precipitation is often even greater.
Leave it to the brilliant, government-sponsored minds to conclude, on such spurious basis, that model forecasts are actually better than reanalysis hindcasts. Even in the Soviet Union, where only the past was uncertain, such “science” would NOT have earned any awards.
BTW, Michael Mann tells us:
Meanwhile, says Polvani, a professor of applied physics and applied mathematics and of earth and environmental sciences who studies the climate system at the Lamont-Doherty Earth Observatory: “One of the largest climatic signals associated with global warming is the drying of the subtropics, a region that already receives little rainfall…”
Ah, the wonders of “settled science.”
… in the reanalyses–confirming that the model projections for the future climate are, in fact, correct.
Phew! That’s a relief, we can continue receiving our government pay checks.
Torture the data enough and it will tell you what you want.
‘Historically, climate models have shown a progressive weakening of the Hadley cell in the Northern Hemisphere. Over the past four decades reanalyses, which combine models with observational and satellite data, have shown just the opposite–a strengthening of the Hadley circulation in the Northern Hemisphere. ‘
So, the modelleers have known for years that the ‘models’ get a major climate feature completely wrong (not unexpected given the parlous state of the software in them) yet the science is settled, trust us!
Models are useless, mainly because they are written with the naive belief that the computers do arithmetical calculations without any error, but computers are poor at handling numbers except integers, and even then only integers of a limited precision.
”Models are useless, mainly because they are written with the naive belief that the computers do arithmetical calculations without any error, but computers are poor at handling numbers except integers, and even then only integers of a limited precision.”
Agreed. The only way a model of the climate or weather can be accurate is by chance. (impossible) And I use the word ”accurate” very loosely. Enter any of those ”accurate” model outcomes into another model and fault is only compounded. The only reason that some are thought correct is due to the short time span they cover. It can only be this way if you consider some unknown or misunderstood or misrepresented natural cycle or multiple cycles in any of an unlimited range of phases which is not included. I would bet that if you run any climate model for long enough the error would end up being astronomical – which renders it meaningless.
Christopher Essex’ brook-no-nonsense presentation should be required viewing for all who might be tempted to drink the Kool-aid of climate models.
To quote a statement attributed to Professor Freeman Dyson in relation to climate models:
“I have studied the climate models and I know what they can do. The models solve the equations of fluid dynamics, and they do a very good job of describing the fluid motions of the atmosphere and the oceans. They do a very poor job of describing the clouds, the dust, the chemistry, and the biology of fields and farms and forests. They do not begin to describe the real world that we live in.”
I think this statement perfectly explains why climate models will never be able to predict future climates.
“It’s a big problem if the models are wrong because we use them to project our climate and send our results to the IPCC (Intergovernmental Panel on Climate Change) and policy makers and so on.”
–> when the “science based models” are wrong then “the science” must be right.
Never cease to try harder ctm.
In the meantime:
Don’t Pay the Ferryman
Chris de Burgh
It was late at night on the open road,
Speeding like a man on the run,
A lifetime spent preparing for the journey;
He is closer now and the search is on,
Reading from a map in the mind,
Yes there’s the ragged hill,
And there’s the boat on the river.
And when the rain came down,
He heard a wild dog howl,
There were voices in the night, “Don’t do it!”
Voices out of sight, “Don’t do it!
Too many men have failed before,
Whatever you do,
Don’t pay the ferryman,
Don’t even fix a price,
Don’t pay the ferryman,
Until he gets you to the other side”
In the rolling mist, then he gets on board,
Now there’ll be no turning back,
Beware that hooded old man at the rudder,
And then the lightning flashed, and the thunder roared,
And people calling out his name,
And dancing bones that jabbered and a-moaned
On the water.
And then the ferryman said,
“There is trouble ahead,
So you must pay me now, ” “Don’t do it!”
“You must pay me now, ” “Don’t do it!”
And still that voice came from beyond,
“Whatever you do,
Don’t pay the ferryman,
Don’t even fix a price,
Don’t pay the ferryman,
Until he gets you to the other side;
Don’t pay – the ferryman!”
Source: LyricFind
Songwriter: Chris De Burgh
Songtext Don’t Pay the Ferryman © BMG Rights Management