Study helps narrow down one reason why clouds are hard to model
From the DOE/PACIFIC NORTHWEST NATIONAL LABORATORY
A key problem is that we generally do not have data on clouds from the preindustrial era, before there was pollution, for comparison with the clouds of today. Because clouds are a key part of Earth’s climate system, working out how they behaved before the Industrial Age might ultimately help us better determine how much the world will eventually warm up.
The study points to at least two ways to potentially improve how the clouds are simulated in climate models. One is to better differentiate cloud types in models to account for their variability. Another would be to study clouds that are not influenced by the pollution that humans have been putting out since the Industrial Age started.
“We might have to find clouds far away from civilization,” said study author Steve Ghan of the Department of Energy’s Pacific Northwest National Laboratory. “But, there are parts of the world that are pretty darn clean.”
Cloudy affect
One of the toughest questions dogging climate scientists is how much the earth will warm from all the greenhouse gases humans are putting into the atmosphere. Computer models put out a range of possibilities, and the smaller the range, the more sure scientists can be of the result.
For example, scientists use models to calculate a property called climate sensitivity — or how easy it is to warm the earth with additional greenhouse gases. Ultimately, climate sensitivity will tell us the temperature we will end up at so we don’t have to wait until the earth adjusts to the added gases, allowing us to prepare for or impede climate change.
Conceptually, climate sensitivity would be straightforward to estimate if one focused on just a few limited components of the Earth system — namely, greenhouse gases in the atmosphere, sunlight hitting the earth, and Earth bouncing some of the sunlight back to space. Under this greatly simplified model, scientists could be pretty confident in their climate sensitivity value: the earth will most likely warm about three-fourths of a degree Celsius for every unit of the sun’s energy trapped in the atmosphere, with a possible range of a quarter of a degree more or less.
But the sunlight bouncing off the Earth’s atmosphere is complicated by the presence of clouds that change in ways that are poorly understood. Climate scientists want to incorporate all the pieces that make up the earth system to nail down a value for overall climate sensitivity. For their part, Ghan and colleagues have been exploring the contribution of clouds and the tiny aerosol particles that influence cloud properties.
“It’s not enough to have particle emissions and solar energy balance alone because a lot is going on in between,” said Ghan.
Cloudy complexity
Currently, when scientists use models to calculate the extent to which aerosols — through clouds — affect the earth’s climate, they get a much, much wider range and greater uncertainty than for greenhouse gases.
Why? Clouds are complex — their properties are influenced by tiny aerosol particles called cloud condensation nuclei that cloud droplets form around; a greater number of particles leads to more cloud droplets which in turn affects the cloud brightness and lifetime, since small cloud droplets hang around for hours, and larger water droplets are more prone to come down as rain, if they’re heavy enough. The physics and chemistry underlying these and other components mean scientists have to represent daunting complexity in models.
Also, clouds are ephemeral creatures. The measurements of clouds that scientists now take have no counterpart in the geologic record, unlike greenhouse gases that are preserved in bubbles in ice cores. Between ice cores, rocks, trees, and fossils, researchers have a good idea how much carbon dioxide existed in the pre-industrial atmosphere. But they can’t tell how often dinosaurs cavorted under cloudy skies.
To see how well cloud and aerosol measurements are represented in models, Ghan and colleagues compared different models to each other and to measurements and examined how they re-created the past and present. They did this by essentially taking apart the simulations and testing the pieces.
Comparing models
A climate model is like a train barreling through a tunnel — scientists put data on the train at one end and the train delivers a view of the climate out the other. In a perfect world, the simulated climate would take a smooth ride through that tunnel. But it’s possible that a rollercoaster resides within, taking the simulation through twists and turns that don’t resemble reality.
To compare the different models, the team looked at the rides taken by the individual components of the equations that make up the simulations. The relationship between the pre-industrial and present day values of any given component, say, the changes in the concentrations of cloud droplets resulting from a change in aerosols, should be the same across the nine different computer models they tested and should be reflected in data from observations.
The team found, however, that pre- and post-industrial values didn’t agree, and in some cases the there was even a difference in sign (that is, one model yielded a positive value while another yielded a negative one).
That indicated they could not model pre-industrial clouds using measurements that have been collected in a post-industrial world.
“It’s very curious. With greenhouse gases, climate sensitivity doesn’t change over eight hundred thousand years. It works. Why don’t clouds?” Ghan said.
Additional research is needed to figure out why pre-industrial clouds differ from today’s clouds. But Ghan said there are several potential directions to go.
One, clouds may be more complex than currently represented in models. For example, clouds could have layers that scientists haven’t accounted for in models that complicate the transfer of sunlight in and out of the system. In this case, old and present-day clouds would actually be the same, but it would mean the models are missing essential complexity needed to simulate how aerosols and clouds interact.
Two, today’s clouds in regions of the world where observations are made are never as clean as they were in pre-industrial times.
“Present day variability doesn’t apply to pre-industrial times because everything’s different now that we’ve been putting greenhouse gases and pollutants in the air for so long,” said Ghan.
Scientists can explore this option by studying clouds in pristine regions of the world, such as in the southern hemisphere between the latitudes of 40 and 50 degrees.
A third explanation could be that the equations used to represent the cloud-aerosol interaction aren’t quite right and need to be revisited. In the future, distinguishing between these options may help scientists shine light on cloud modeling’s cloudy history.
###
This work was supported by the US Department of Energy Office of Science, the National Natural Science Foundation of China, the Austrian Science Fund, the Swiss National Supercomputing Centre, the UK Natural Environment Research Council, the UK European Research Council, Japan’s Ministry of the Environment, the Japan Society for the Promotion of Science, and the US National Science Foundation.
Reference: Steven Ghan, Minghuai Wang, Shipeng Zhang, Sylvaine Ferrachat, Andrew Gettelman, Jan Griesfeller, Zak Kipling, Ulrike Lohmann, Hugh Morrison, David Neubauer, Daniel Partridge, Philip Stier, Toshihiko Takemura, Hailong Wang, and Kai Zhang. Challenges in Constraining Anthropogenic Aerosol Effects on Cloud Radiative Forcing Using Present-day Spatiotemporal Variability, Proc Natl Acad Sci U S A, Early Edition, February 22, 2016, DOI: 10.1073/pnas.1514036113.
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Clouds are conscious entities, I know this because they occasionally make faces at you. I’ll need 150K in grant money for my cloud psychology program, oh did I mention that when there’s too much CO2 clouds get angry.
On a more serious note, from the standpoint of a climate laypersons, if you cannot understand the formation and morphology of a cloud how can you understand differences in climate?
“Clouds are conscious entities, I know this because they occasionally make faces at you. I’ll need 150K in grant money for my cloud psychology program, … “
Since it is most probable that clouds control temperature variation to a large degree, perhaps you can talk to the clouds and get them to hold the earth’s temperature to the exact value everyone wants!
Wait, … do we know what temperature everyone wants the planet’s thermostat set at? I can’t even get agreement inside my own house.
Feminist clouds go negative rather easily.
… although, in general and overall, the female clouds are the ones that are the hardest to model/forecast/project what they will do.
They not only make faces at you, they know when you wash your car (they are paying attention). And they know when you plan on mowing your lawn (not quite omniscient, but somewhat psychic).
I looked for it … and found it.
“…Ghan and colleagues compared different models to each other and to measurements and examined how they re-created the past and present.”
Which “measurements”? The actual data & proxies, or the “adjusted-to-prove AGW” ones?
Likewise, which “past and present”? The one that actually existed, or the “adjusted” one they want so dearly to believe in?
If you use your “desired outcome” as input data, it’s likely you’ll get it as an output.
Little wonder they are having trouble modeling clouds, because every single cloud that has ever formed is unique. No two clouds are ever exactly the same. The only real way you can hope to understand the weather from the past beyond written records. ls to try understand what the climate conditions were in the past, and then try to understand what the weather must have been doing at the time to allow these conditions to happen.
I call BS!
You are using logic, common sense, scientific reasoning, and other forbidden things. My god man, this is climate science. We don’t use logic here!
@ur momisugly Taxed I agree with mark, 5 minutes for interference a game misconduct and we’ll see you Head office Monday morning to see how many games you are suspended!
I think you have way too much respect for taxed….
Some really good comments in this thread. Gary Pearse: “I have never seen such a diffuse, chatty type of speculative discussion of what is supposed to be a scientific research project.“. Here is just one example of that diffuse chatty style – “[..] if one focused on just [..] greenhouse gases in the atmosphere, sunlight hitting the earth, and Earth bouncing some of the sunlight back to space [..] the earth will most likely warm about three-fourths of a degree Celsius for every unit of the sun’s energy trapped in the atmosphere“. Well, greenhouse gases don’t trap the sunlight bouncing back. And then there’s this 3/4 of a degree for one unit. What unit? By using the chatty discussion style they can obfuscate while pumping an unsupported message. Not good science. Kev-in-UK: “it seems strange that anyone would consider it possible to model clouds within a climate model. [..]. I would have thought the best they could do is estimate the albedo and the average percentage of cloud cover (for say, given regions), and that’s about it. Expecting to be able to anything more is pure fantasy in my opinion, as clouds are a part of the chaotic non-linear system!“. Exactly. And Evan Jones points out one of the places where the fantasy originates: “the bottom-to-top spaghetti. For anyone who doesn’t know what that is, please read my http://wattsupwiththat.com/2015/11/08/inside-the-climate-computer-models/
Their chief obfuscation is, of course, when they say that man-made aerosols make it difficult for them to model clouds. The very simple reality is that they have no idea how clouds work. That they refuse to face up to this reality is demonstrated in another bit of their obfuscating chatty discussion: “clouds may be more complex than currently represented in models“. That is a mind-blowing statement – after all these years of not knowing how clouds work, of not being able to model clouds, of not even knowing whether clouds have an overall cooling or warming effect, they say clouds “may be” more complex than they have allowed for in their models. What do they mean, “may be“!!!?????
Mike, fabulous comment that is right to the point. Thanks.
MJ, plus many. Great soundbite.
Mike Jonas — in addition, now the albedo has changed drastically due to land use changes and land land cover changes & water use change and water cover. One of the cover on land water is the filth — like plastics, oil contamination in oceans —.
Dr. S. Jeevananda Reddy
Supposedly the global average cloud cover according to NASANOAA is 60%.
The actual plastic and oil filth in the oceans is a drop in the bucket. I have never seen ANY of any such thing while flying over the oceans, and I have never seen a photo from space, that shows any such thing in the oceans.
You would have quite a time trying to find significant land use changes that have either an effect on the grey body radiation properties of the earth or the albedo of the earth, which is mostly due to cloud cover.
G
George e. smith — I am not looking at “supposedly” but the real issue which is not accounted in albedo and as well in absorption.
The radiation reaching the Earth’s surface through the atmosphere, albedo of the surface and absorptive capacity of the surface all play important role. Filth and land-use and land cover drastically change these factors. This will change with the time. When we are dealing with local and regional studies, they play vital role.
About filth in ocean, though it is a drop in bucket, a drop of poison in a bucket is dangerous. In the previous posts here, commentators posted the plastic coverage in oceans. This needs more study. Oil spills and waste water dumping by ships and oil & gas drilling/operations all count significant areas. Gulf Mexico turned into dead zone with pollution – chemicals & oils. When we are dealing with 0.1 oC of global warming, all these are important.
Dr. S. Jeevananda Reddy
Well I would submit that 0.1 degree of global warming is of no concern to anyone, given that at any ordinary midsummer afternoon in northern latitudes, the total range of observable Temperatures on earth will be at least 100 deg. C, and could be as much as 150 deg, C, and according to Galileo, Galilei, every temperature between those extremes will be found at some place on earth; actually an infinity of such places, somewhere along any continuous line connecting the extreme end points, and there’s no limit to how many such lines one can draw.
So miniscule anomalies that could/might/may/can/whatever alter a totally negligible figure, while possibly important problems in themselves (junk in the ocean) they are of no great climate consequence. We have a feedback system that regulates earth’s Temperature very well.
G
“…For anyone who doesn’t know what that is, please read my http://wattsupwiththat.com/2015/11/08/inside-the-climate-computer-models/….”
Worth following that up with a visit here http://climateaudit.org/2016/02/27/gerry-browning-in-memory-of-professor-heinz-kreiss/#comments
Surely they only need to look at Luke Howard’s writings which gave the various cloud types the names we still use today. I believe he supplied numerous drawings of what he was seeing over 200 years ago.
What utter balderdash.
Their premise is that we can’t model the clouds we have with the data we have, so the secret is to study clouds we don’t have, and (conveniently) about which we have no data.
This is nothing more than a long complicated request for funding to make it seem logical to study clouds we don’t have instead of studying the clouds we do have.
Can I get a government grant to buy a new fisheye lens and some extreme wide angle lenses for my Nikon, to map these new kinds of clouds, in the roaring forties region.
g
Ah, the delights… and grants of modelology !
You’ve heard of cooling the past. Let’s try clouding it, too. Okay?
Please allow me to summarize for clarity.
1) We don’t have the foggiest notion on how to model the physics and mechanisms of cloud formation.
2) Our GCMs are woefully inadequate in addressing pan-regional spacial and temporal response to climate drivers, particularly for oceans and ocean currents.
3) However, with a sufficient number of made up boundary conditions (e.g., aerosols), and annual re-initialization, and with a sufficient number of dials (e.g., amplification), we can obtain an approximate match to one relatively meaningless parameter (i.e., global temperature) crudely derived from past data for dozens of models, each using different assumptions.
4) Therefore, it only makes sense to add additional layers of complexity to GCMs. This will increase the number of dials, and improve the ability to model and make projections of the historical data.
I am not a climate scientist but I play one on the blogosphere. I am however open to corrections on the above.
Over complicating things when we can just measure the warming we don’t have. One thing we do actually know is that all models starting with the premise that CO2 causes warming of X amount are wrong. In any normal field of inquiry, this would lead the inquierers to suspect that something might be wrong with the foundation. Here, not so much!
My thought: The most important metric, and one I think can be modeled in terms of ocean heat that would later be discharged, is the amount of solar energy that penetrates the equatorial band. We have developed a pretty good understanding of what clouds do and where they form under the different ENSO conditions. It may even be the case that only the Pacific equatorial band needs to be considered. At that point in time, different ENSO scenarios can be run that we would be able to put into play to predict warming given current ENSO circumstances. AGWers can add their CO2 enhancements or whatever, to see if humans are acting to warm the planet beyond what clouds, or lack of clouds do.
Pamela Gray – very good point – new base lines needed.
— That pretty much describes the way some business models work. Take people’s performances at different tasks on different projects; collate their stated project plan and actual performance over years; put theirs and all other employees and projects and type of projects into a model, refine it, and you can develop a continually adjusted model that predicts revenue and profit by quarter. With a good project management system, you get a pretty good idea of how people perform on projects and you can look out months, even years ahead at times to get a pretty good handle on revenue and profit margin.
Not sure why simple climate models can’t start out with simple know conditions and variable and test against actuals. Maybe my engineering and financial experience with successful modelling that gave pretty good results along with warnings of when things were going astray were just too simple and had too many knowns. But don’t you have to start with the knowns? Then you apply what ifs, and new information, along with adjustments over time and compare it to the next time period actual results.
Sure I know I know climate modelling is complex. But so are people and we can get a really good hand on their abilities to delivery projects on budget. Water networks can be very complex also, but you can test them and we know most of the unknowns. And the ones that give bad results can be field tested and adjusted to reality.
Not sure that can be done with climate. The above paragraph had a 7 figure cost in my company. Compared to climate complexity, a spit in a bucket.
But still, a simple model built up over time by adding layers of complexity tested against reality should be able to get some idea of what might happen.
Unfortunately, the longer the model runs, the more iterations, the more likely the model will become unstable. How many iterations before climate models are simply spitting out meaningless numbers due to internal instabilities? Do they monitor the individual feed backs for signs of instabilities? The spaghetti plots look like there are considerable instabilities in the models. Appears they need to start over with a fresh look and reconsider their assumptions and variables. It looks. like some climate researchers are. Good for them.
ristivan: Sometimes a bunch of SWAGs works. Least it did for me for many years. Well, they were Informed Wild Ass Guesses.
How quaint. It’s almost as if they think they are doing actual science.
“We’d be right, if it weren’t for those damn clouds throwing us off. I know; let’s model them, the same way we did with CO2! Yeah, that’s the ticket!”
“Today’s clouds might not be the same as pre-industrial ones”
–> Testable? –> Not so much –> Humans again? –> Indubitably! –> Publish! –> Thanks!
http://www.internet-maerchen.de/images/guckluft.gif
/s
Regarding the testing of cloud formation and the lack of response:
“The interior volume of the building is so vast that it has its own weather, including “rain clouds form[ing] below the ceiling on very humid days”,[8] which the moisture reduction systems are designed to minimize.” https://en.wikipedia.org/wiki/Vehicle_Assembly_Building
wiki has a piece on the Vertical Assembly Building (VAB). The quote above demonstrates that large/tall buildings can have weather systems.
The VAB with a temporary inner plastic skin, should provide isolation to the outside and variable world, and provide a means of determining the functionality of cloud formation and sensitivity to all aerosols than man can muster.
With sufficient instrumentation, it should be possible to determine current cloud unknowns.
I once heard a chap relate to another that his mom was so fat, she had her own weather system.
Is there some specific reason why nobody in the above discussion has even casually referred to the existence of the CERN CLOUD experiment.
I find myself reading comments suggesting that an experiment could conceivably by conducted by building a sealed chamber and exactly controlling the internal conditions.
“Cloud formation being influenced by aerosols is crying out for a physical experiment.” – comment above.
Are we supposed to pretend that the CLOUD experiment does not exist?
Does its mention immediately spark a cosmic ray cloud connection hypothesis dispute/war?
Anyway, for the record, there is an experiment studying the effects of aerosol generation and cloud formation. And it’s result have so far been confirmatory with regard to the disputed hypothesis.
And yet, we must draw no conclusions from that.
Since the IPCC would like to maintain their confident assertion that cosmic rays play only a minimal or quite completely irrelevant role. Which they assert on the basis of minimal evidence, yet with high confidence and high agreement – as is usual for topics relating to the enforced climate consensus.
I’d like to see a building that contains a 45k ft CB top and high level cirrus topping off via internal latitudinally and seasonally variable jetstream, with Deluxe Coriolis effect. I’d settle for indoor towering cumulous congestus though. But given the topic is “Cloudy modelling problems”, and a pithy claim that, “Today’s clouds might not be the same as pre-industrial ones”. Maybe with a TARDIS and sonic screwdriver?
But it kinda assumes humans are a ‘climate’ problem, and are even attacking the poor clouds now! Please fund me and I’ll find fault with humans.
Thus instantly reeking of an overpowering bovine fragrance, evoking dodgy conceited prejudice and limited views of both life and planet, in their proper context.
A bigger cloud chamber is not a test of the claim, and is not going to constrain the models realistically. The models are crap, and so is the untestable assertion humans are to blame for observed weather cycles.
And if we are?
Show me a beaver that’s not radically altering the environment.
Can we backhandedly imply a condemnation of beavers too?
Or are they just being ‘natural’ … and we’re not? … because we can do, well, what we evolved to do?
Tell me when you have something testable, that actually means climate models will ever be more than bovine fecal matte and useless graphical fluff, pretending to be ‘science’.
Science is, above all else, testable.
Let me see if I get this right, the models are unable to adequately predict the impact of clouds and it’s not the models it’s the clouds fault?
I’m surprised that Ghan seems to think that aerosols are the big issue with clouds. He says that modern-day pollution is to blame for increased aerosols. I would argue that the change in cloud has come about because from the late 1970’s onward mankind made a deliberate attempt – probably its first attempt in history – to reduce the emissions of micro-particles. In Europe and individual countries this was due to government legislation but in “developing countries” the change came later and was probably due to a switch away from burning dung and wood towards using bottled gas.
What difference do micro-particles make? They form the nuclei of clouds, giving water vapour something to condense onto and form droplets. And the impact of their removal? When London banned the burning of coal for domestic heating the pea-soup fogs that had been so common during winter disappeared.
I’m amazed and amused that supposed experts don’t accept that reducing micro-particle emissions will cause a change in cloud cover. It’s like cleaning a dirty window and then wondering why the room looks brighter.