The map above shows the average afternoon cloud cover across the globe compiled from daily measurements acquired by the Aqua satellite between 2002 and 2015. Below are similar images for each month of the year. 

The monthly images contain an entrancing record of the annual cycles of the weather. In them, we can watch the development of summer convection across the U.S. Plains, the evolution of the India and China monsoons, the onset of “The Wet” in Australia, the annual cycle of the Intertropical Convergence Zone (ITCZ) and many other seasonal changes as recorded in the cloud record.

These maps are constructed using data acquired by the Aqua satellite using its MODIS sensor. MODIS collects satellite visible and infrared radiances and uses complex algorithms to automatically infer clouds and their properties around the globe. Data collected are normally used for climatological studies, and have proved valuable for astronomical pursuits for over two decades.

Clouds are not always easily detected from satellites. In the tropics and over the bulk of the oceans they are the white things in the image. Over Canada in winter, the white stuff is frequently snow and ice. Infrared temperatures can be fooled by clouds in winter can can be both warmer or colder than the ground while at the same time, blending into the white stuff on the ground in visible wavelengths. The same applies to mountains, where white bits in the visible-light image can also be snow or ice, even in summer. Nevertheless, by examining the ground in many different wavelengths, a reliable detection of cloudy, partly cloudy, and clear skies can usually be made.

The data in these maps have a resolution of 1 degree in latitude and longitude. The cloud cover values are an average of available data, from 2002 through 2015, from both daytime and nightime satellite passes. Images on this site are composed from the afternoon ascending pass of the polar-orbiting satellites and corresponds to approximately 2 p.m. local time.

These maps should be used cautiously, as satellite-based cloud datasets have several known biases. Use them for comparative purposes, rather than as absolute values of cloudiness. Or, use them for entertainment and education.

By assembling these images into a movie file, we can see the annual cycle of clouds around the globe. Note in particular, the shift of the Intertropical Convergence Zone (ITCZ) north and south during the year, the changes in North American cloudiness (especially the Southwest monsoon in the summer), the monsoon cycles over India and China, and so on.