Clouds, pollution and the summer monsoon
Pollution can cause fundamental changes in cloud behaviour and precipitation patterns
THE INDIAN summer monsoon season begins when the land surface becomes hot enough to drive a powerful rising motion of air in the atmosphere, producing heavy precipitation. Cooler, humid air over the Arabian Sea flows inland to compensate for the rising air. Air in this compensating circulation encounters the surface heating and also rises, perpetuating the cycle. This simple thermodynamic system is associated with a cloud response that varies in scale from microns to thousands of kilometres, simulated by some of the most powerful supercomputers ever made, and observed by a massive network of weather stations and dozens of advanced satellites.
At the smallest scales, an increase in tiny particles in the atmosphere can shade the land surface while absorbing sunlight aloft, causing a reduction in the heat that reaches the surface. This weakens the rising motion of air that drives the precipitation response to the monsoon. Clouds that do form in these polluted environments are less likely to rain and more likely to persist because the droplets are smaller. These longerlived clouds further cool the surface and weaken the circulation.
The extent to which pollution affects clouds, precipitation, and, therefore, agriculture in India is still an open question and an active area of research. This work is carried out by dozens of institutions globally, each using advanced models and extremely powerful computers to simulate the billions of microscopic processes occurring every second.
At larger scales, the microscopic processes obtained in cloud models show how chang- es in pollution lead to changes in the types of clouds. Weather observers across India have for years provided observations to show a significant reduction in the cloud types associated with a strong monsoon, accompanying an increase in pollution. The number, quality and consistency of these observations have contributed to one of the longest cloud records ever produced. This record is the result of decades of continuous observations with no change in observing procedures, and years of meticulous data processing, filtration and statistical analysis carried out by research groups globally.
At even larger scales, the amount of heat and moisture moved by the Indian monsoon is significant enough to change the large-scale planetary waves that drive weather globally. Other tropical circulations have been shown to have significant effects as well. A global network of weather stations as well as cloud-observing satellites have shown that the Indian monsoon alone is significantly correlated with changes in cloudiness over six continents.
The range of cloud response to the Indian monsoon shows how the cloud record is a powerful tool to study climate change. Recent studies have shown that clouds associated with the midlatitude storm track (routes of stormy planetary winds seen in the middle latitudes) have, on an average, been displaced poleward. The mean location of the storm track is sensitive to the temperature gradient between the equator and the poles, and a poleward shift would be consistent with a reduction in this gradient, which has indeed happened because of the disproportionate
warming of the polar regions. This is an ominous sign of global warming shown using two completely independent data sources, one based on satellite cloud observations, the other from surface weather stations.
Lower-level clouds are sensitive to largescale circulations and local changes in temperature and pollution. Apart from the above example regarding pollution possibly affecting the monsoon, low clouds over the tropical oceans are sensitive to the temperature of the sea surface. A warming ocean is more likely to reduce the atmospheric stability that supports the existence of large-scale stratiform cloud decks (which are low-hanging clouds that grow horizontally on a semi-uniform base). It also drives a decline in cloud cover, an increase in sunlight reaching the ocean surface and further warming of the ocean in an example of a positive feedback cycle. However, an increase in pollution could have a competing effect, increasing the lifetime of clouds.
Profoundly complicated
The single phenomenon of the Indian monsoon well represents the complexity of the physical systems associated with clouds and the challenges faced by the communities observing and modelling clouds. Each community contributes to a different, essential understanding of the system.
Cloud models provide a picture of the internal workings of clouds and how cloud droplets interact with one another, which cannot be seen by observers at the surface or from satellites. Aircraft data are also used to test cloudmodelling results, but are currently in short supply. Surface observers and long-lived satellites contribute to a record that is long enough to distinguish trends in cloud cover from changes that are driven by cyclical variability in the system. Satellites offer a valuable, but lower-resolution view of systems like the Indian monsoon over the entire planet, many in places where observations from the surface are lacking.
Each branch within the cloud climatology community relies on the other to advance the science. Simulated processes need to be compared to real-world observations to verify results. Observed phenomena require not only physical explanations tested in cloud models, but independent verification between observing platforms.
The above examples outline how the cloud record can be used to study atmospheric changes on scales ranging from microscopic to global, from the surface to the stratosphere. The most difficult work going forward will be in improving our understanding of how clouds will interact with a changing atmosphere and whether changes in cloud cover will act to exacerbate or offset global warming. It is essential that we continue to maintain the current observing platforms in order to better diagnose changes in the atmosphere, while simultaneously, we must continue to invest in improved cloud modelling to better understand the causes and effects of cloud changes.