Our weather would be rather boring if it weren’t for air pollution.
Aerosols, both natural (like desert dust and sea salt) and human-made (like soot), play a fundamental role in forming clouds. Water vapor can’t spontaneously condense into droplets at the pressures and temperatures we experience on Earth. It’s aerosol particles that mediate condensation.
By modifying clouds, aerosols indirectly but powerfully affect the climate. Clouds forming in polluted environments with more particles tend to have a higher concentration of droplets than clouds in cleaner air. Given the same amount of water available for condensation, the polluted cloud’s droplets must be smaller on average; the combination of smaller and more numerous droplets makes those clouds brighter. Furthermore, smaller droplets may suppress the development of precipitation and drizzle, thereby extending the lifetime of a cloud. The formation of clouds that are both bright and long-lived results in more sunlight reflected over longer periods of time.
Because of this pollution-triggered phenomenon, scientists suspect that aerosols are responsible for a cooling effect that has masked quite a lot of the greenhouse-gas warming that has occurred over the 20th century. That realization logically leads to two important follow-up questions: How much cooling have aerosols contributed since the pre-industrial era? And how will future changes in aerosol emissions contribute to global climate change?
Climate modelers are not yet certain about the answers to those questions. But recent research by myself and other scientists has helped determine how aerosol-rich clouds affect the amount of solar radiation that reaches Earth’s surface. Aircraft and satellite observations of cloud microphysics could supply the missing data.
Because we don’t know the amount and composition of atmospheric aerosols during the pre-industrial era, much remains uncertain about aerosols’ contribution to climate. To make headway, we can try to simulate the physics and chemistry of aerosols and clouds as accurately as possible in global climate models.
Those simulations reveal the droplet activation process as a basic, but key, determiner of aerosols’ indirect effects. As a parcel of air rises into the base of a cloud, it cools, driving relative humidity toward saturation. Eventually the air parcel reaches the supersaturation threshold (usually a relative humidity of 100.1–100.3%) needed to condense water onto particles. However, as soon as condensation begins, latent heat is released, which warms the air parcel and offsets some of the cooling. The higher the supersaturation, the more particles will be able to take up water.
Ultimately, as illustrated in the left panel of figure 1, the parcel will achieve maximum supersaturation before the humidity relaxes back to saturation. The end result is a split in the aerosol population: The particles in the parcel with the highest affinity for taking on condensate will “activate” into proto-cloud-droplets and freely grow (like the sea salt particles in the right panel of figure 1), while the rest will equilibrate with the cloudy environment, forming haze.
In previous generations of climate models, we used very simple heuristics to relate the number of aerosols in the atmosphere to the number of droplets that would form in clouds. Modern climate models, though, incorporate simplified versions—parameterizations—of the specialized model used to create figure 1. We recently developed one such parameterization and incorporated it into a global aerosol–climate model to study the role that activation plays in modulating aerosols’ overall climatic effect. Surprisingly, the role turned out to be quite large.
Activation schemes galore
Although most activation schemes translate similar aerosol and meteorological inputs into similar cloud properties’ outputs, some behave idiosyncratically. For instance, some schemes are more sensitive than others to the presence of aerosol particles that are a micron or larger, such as dust grains from deserts and sea salt from the open ocean. As a result, when we use different activation schemes in our model, we generate simulations that have significantly different average cloud properties.
The diverging results of models using various activation schemes motivated my team to incorporate many schemes into one model. We then used the model to simulate the climate under different emissions scenarios—including one with pre-industrial emissions and another with present-day emissions. Figure 2 illustrates how the number of droplets at the tops of clouds changes when we use different emissions scenarios and activation schemes.
The composition of cloud tops affects how radiation propagates through the atmosphere. So by analyzing the differences in the cloud radiative effect when we run the model with various aerosol emissions, we can estimate the total aerosol climatic effect.
In figure 3, I’ve taken the cloud radiative effect, averaged it for each climate model simulation, and then plotted the averages with the cloud-top droplet number concentration from figure 2. A very strong, linear relationship results: the fewer cloud droplets simulated in a pre-industrial climate scenario, the stronger the indirect effect of aerosols on climate. The same result approximately occurs if we use a present-day scenario.
At first glance, the results seem counterintuitive. If you have fewer cloud droplets, you would expect a smaller cloud radiative effect—your clouds shouldn’t be as bright. However, a small change in droplet number can have a large impact on a cloud’s brightness if the cloud started out with very few droplets. If you impose a change in droplet number on a cloud that already has a lot of droplets, the cloud’s brightness doesn’t respond as strongly. Hence, the impact of aerosols on clouds is buffered.
Although we haven’t yet been able to make headway in constraining the magnitude of aerosols’ climate impact, our work points to some meaningful areas of future work and investment. The most important research focus is to observe cloud microphysical properties from cloud regimes across the globe, especially in ocean regimes located far from sources of pollution. Those areas could be natural laboratories that mimic the conditions in which clouds formed in the pre-industrial, pre-human pollution era. Satellite observations may be useful too. New instruments have achieved unprecedented access into the inner workings of clouds. Such new datasets will give us an opportunity to better tune our models against observations.
For now, scientists must begrudgingly accept that aerosols cloud our forecasts of future climate change.
Daniel Rothenberg is a doctoral candidate in MIT’s department of earth, atmospheric, and planetary sciences. His work focuses on the application of various modeling tools and techniques to investigate the character of aerosol–cloud interactions and their potential impact on the climate system.