But recently, two scientists realized that those clouds themselves can actually reveal a surprising amount about life on Earth below.
While working together at Yale, researchers Adam Wilson and Walter Jetz stitched together 15 years' worth of satellite images into a massively detailed cloud database. This allowed them to create maps showing seasonal fluctuations in cloud cover around the world. In this psychedelic map, the different colors correspond to the month of peak cloudiness:
In some areas, like the eastern United States or the rain forests around the equator, there's not much variation in cloud cover from month to month. By contrast, places like India, southern Africa, or northern Australia experience massive swings in cloudiness throughout the year.
The maps are just plain cool to look at. But as Wilson, who is now a geographer at the University at Buffalo, explained to me (and wrote about with Jetz in a recent paper in PLoS Biology), this cloud atlas can also be quite useful for understanding life.
Want to figure out where species live? Look at the clouds.
If we want to protect threatened species, we first have to know where they're actually located. But this is often tricky. People can directly document the range of butterflies in the United Kingdom. But we have far fewer observations of butterfly species in, say, the Amazon rainforest.
So, for these areas, biologists tackle the problem through indirect mapping, using the fact that individual species tend to stick to particular climatic ranges. Typically, researchers use temperature and precipitation data as proxies to predict where a particular tree or bird might spread to. But this is a crude metric: In places like the Amazon, weather stations are relatively scarce. Scientists can miss subtle variations in local climates within a mountain range or valley, leading to flawed biodiversity maps.
That's where cloud maps come in. Scientists have long studied the ways in which cloud cover can heavily influence the shape of ecosystems on land below. Clouds, after all, affect everything from the amount of sunlight that plants receive to the wetness of leaves to the reproductive success of reptiles.
So, in theory, if we had detailed data on cloud cover, that could help us create even more precise biodiversity maps.
To test this, Wilson and Jetz created two different models for predicting the range of species: one that only used temperature and precipitation, and another that also incorporated cloud cover. They then tested these models on two species: the montane woodcreeper, a songbird in the cloud forests of South America; and the king protea, a shrub that thrives in semi-arid parts of South Africa.
In both cases, the cloud model was much more precise in predicting the range of the woodcreeper and the king protea. (Wilson and Jetz determined this by comparing the models against known sightings of both species.) Further testing will be needed, but it's a promising new tool for biologists and conservationists.
That's not all the cloud atlas can do. Data on cloud cover can more accurately predict the distribution of cloud forests — high-elevation tropical or subtropical forests that feature consistently heavy cloud cover all year round and are teeming with biodiversity — in the Andes, the Congo River Basin, and Southeast Asia. Like so:
This is valuable because satellites can transmit cloud data much more quickly than ground-based stations can. This could help conservationists keep closer track of these forests — and the species in them — and perhaps provide an early warning system if anything seems awry.
Solar power? Vacations? What else can this cloud atlas do?
I asked Wilson what else we might be able to do with the cloud atlas. "The exciting thing is that we don't know yet what people will come up with," he says. "That's why we're making it publicly available." (You can find the data, along with interactive maps, on the EarthEnv page.)
He threw out a few possible ideas: Utilities and energy companies could conceivably use the cloud data in planning locations for solar arrays. Solar developers already use detailed computer models to assess things like solar radiation, light scattering, and so on. But this new database provides an even finer resolution for cloud cover — with each pixel representing just 1 square kilometer.
Climate scientists could one day use the database to test how their computer models handle clouds, still a source of frustration in better understanding global warming. More frivolously, vacation-goers might be interested in the data to see how overcast it might get at their planned destination. (The EarthEnv page doesn't currently offer instantaneous updates, but in theory this is possible: NASA shares its satellite data nearly in real time.)
I asked Wilson what surprised him most about the cloud maps, and he said he was stunned to see such detailed variability in cloud cover. "For instance, you might have clouds form to the east of a mountain range, and then you'd see them wrap around to the south of the mountain rather than the north."
Those subtle cloud movements, in turn, could affect ecosystems on those mountains. If you only looked at temperature and precipitation, you'd assume both sides of the mountain had similar ecosystems. But the clouds can tell us otherwise.
Further reading: This is an incredible visualization of the world's shipping routes