This article (excerpt, gift link) says we don’t know very much about cloud dynamics. Is our understanding really so nebulous? Over the years we must have accumulated some knowledge deeper than what colour sky delights sailors?
“I find clouds are beautiful to watch,” [cloud expert Yang] said. “If I take an airplane, and I can see clouds down below or far away, I’m always fascinated by how rich the cloud organizations are. How they interact with each other …” He trailed off. Clouds are complex and ephemeral, which makes them difficult to fully understand. Yang listed for me key aspects of clouds for which we still lack comprehensive understanding: how they form, what determines their spatial scale, how long they can last. “Those sound like simple questions,” he said, “but they are actually at the forefront of the field.”
The cloud problem has [persistently plagued] (Clouds and climate | Nature Geoscience)climate models. Although these models do many jobs extraordinarily well—understanding the energy balance of the planet, describing a trajectory of warming from human-made greenhouse-gas pollution—they can’t seem to get clouds right. Models will sometimes produce cloud-related projections that are simply incorrect, and some models “run hot,” meaning they predict catastrophic warming, possibly because of cloud dynamics.
One major stumbling block is the resolution of climate models, or how finely or coarsely they represent the Earth; to represent individual clouds, which can be the size of a minivan or the state of Minnesota, would require models at a resolution finer than the current finest model. Climate modelers have recently begun to produce fine-scale models at the regional level, where they can zoom in on the individual details of clouds. But, Yang told me, stitching such snapshots together into a picture of the whole globe would exceed the capacity of the largest existing supercomputer.
Even if computers did have the capacity to do these analyses, scientists would need more tools to understand the results. For that, Yang said, we need more cloud theory. “Without theoretical understanding, we would not be able to interpret the model results,” he told me. “Without these first-principal-based understandings, we don’t really know whether the model is accurate.”
This feels a little to me like saying we can’t predict what will come up if we roll a die, therefore we don’t understand how dice roll.
We have a decent understanding of how clouds form in general, but we are nowhere close to being able to predict how any specific cloud will behave because of the practically infinite number of variables. Turbulence is certainly one part of that.
In the context of climate change, we don’t understand 'em very well either. But we do know a few really important things. One is that there’s no evidence that climate change is driving any significant changes in cloud formation. This is partly because although rising air temperature increases specific humidity, relative humidity remains fairly constant.
Another factor is that, somewhat counter-intuitively, climate models show that clouds on balance don’t have a large effect on climate. It’s true that low-level clouds contribute to warmer nights by radiating back surface heat, but they actually contribute to overall cooling by reflecting solar radiation back into space. High-altitude cirrus clouds, OTOH, somewhat contribute to warming by doing more to re-radiate heat back to the surface than to block solar insolation. On balance, climate models suggest that clouds are a small net positive feedback, but nothing more. Unlike water vapour, for instance, which is a strong but self-limiting positive feedback that greatly amplifies the climate forcing of CO2.
When younger, I remember learning that Venus was so hot because of its clouds (and carbon dioxide, always brought up when someone discussed Greenhouse Gases). Recently, I rewatched The Planets from public television. They said the first probe to Venus was designed so it could survive a drop into liquid water. This seems optimistic given Venus’ temperature must have been known. Of course you must prepare for many scenarios.
The cloud expert (above) says we don’t know: how they form, what determines their spatial scale, how long they can last.
Nephology (the study of cloud and fog formation and dynamics) is a very active area of atmospheric physics, and presents one of the largest uncertainties in the radiation balance for global climate circulation models. It might seem like clouds are simple and easy to observe but in fact the thermofluid dynamics, electrodynamics, thermochemistry, and hydrology of clouds. It should be understood first that “clouds” are not all one thing; like planets or rocks, they present a multitude of very different characteristics which can be only roughly delineated into defined categories, but each is a unique and highly dynamic system which evolves over a relatively short timeframe even by human timescales, which makes them more complicated to study than planetology and geology, whose subjects are relatively static (generally speaking) over periods much longer than a human lifespan. It is also very difficult to directly study a cloud up close; cloud field researchers have to wait for conditions favorable for cloud formation, the fly up into an obscured field to no small hazard in order to sample cloud conditions and constituents often as the cloud is dispersing or moving in a direction the pilot doesn’t want to go. It’s like studying dentistry on live wild tigers except also in mid-air.
It is important to understand what a cloud is; most people think it is just “water vapor”, but in fact a cloud is some combination of water vapor, water at a saturation point (quasi-liquid droplets), ice crystals and snow, ionized particles, and condensation nuclei/contaminants like sulfur, so it exists in multiple phases and states of matter. Clouds will have certain behaviors and visible structures depending on their composition, altitude, wind shear, and incoming radiation, and they have a manifest affect upon the incoming solar radiation as well as infrared re-radiation emitted by land masses and the oceans. Clouds are bearers of large masses of water, and in fact many clouds weight many thousands of tons but are just diffuse enough to be buoyant. As noted, clouds are almost inherently turbulent structures, but the regimes of turbulence can vary widely even within a cloud and certainly between different types of clouds, so while we have good models and tools for studying turbulence in different regimes, multi-regime dynamics makes this very complicated to simulate. Clouds can also contain enormous amounts of electrical charge and large thermal energy gradients which further complicates any attempt to make predictive models. Depending on the density of the cloud compared to the nearby ambient air, it can produce very fast moving streams and even be part of an ‘atmospheric river’ moving as much water in the jet stream as a major river does across the land.
As noted above, clouds have a massive effect on heat transfer within the climate system, both in terms of radiation and convection (and of course are formed by evaporation), but because they are on a scale that is generally a fraction of the element size of general climate models and because of how dynamic they are it is difficult to implement a validated cloud model with confidence, and especially if you account for interactions of different types of cloud systems. Fortunately they are a relatively minor impact on overall energy balance but cloud formation can have significant local effects on microclimates which impact the local hydrology and biome. The prediction of cloud behavior in shorter term weather models is much better, and in fact this is a major reason why weather models have gotten so much better in the past couple of decades. But there are still a lot of unknowns when trying to model or predict cloud behavior.
Wouldn’t it be fair to say that at a very high level, it’s a piece or an outgrowth of the fact that meteorological simulation and prediction becomes more and more fiendishly complex as you go outward from “right here, at this very moment” in both distance and time?