6 Dealing with Cloudy Data

Looking up, it’s easy to spot the clouds. The white fluff is strikingly contrasted by the blue sky. It’s not so easy from space, especially above the Earth’s poles. The clouds blend in against the vast expanses of snow and ice. This is a problem for scientists who use satellites to study clouds and climate. Recently though, UC Berkeley statistician Bin Yu, her graduate student Tao Shi, and their collaborators have devised a new algorithm that detects clouds even when the poles play tricks on the satellites’ electronic eyes. Professor Bin Yu’s research is supported by National Science Foundation grants and by a Miller Research Professorship in 2004. Understanding clouds is essential for scientists to computationally model Earth’s current climate and make projections about the future. Historically, uncertainties about how clouds interact with radiation from the sun and the Earth have added to the difficulty of making accurate forecasts. “Clouds have a cooling effect by reflecting the sun’s radiation, but they also warm the Earth’s surface by acting like a blanket,” Yu says. “The tradeoff between cloud heating and cooling depends mainly on their thickness and height above the surface. So if you don’t know where the clouds are and, as a result, the way they feedback on the global climate, the climate models don’t really work.” Today’s cloud detection systems that sift through mountains of satellite measurements are notoriously error-prone when it comes to the polar regions. The detection schemes usually rely upon visual or thermal contrast between the clouds and the surfaces below them. But conventional approaches fail if such contrasts are lacking. This commonly happens in the polar regions, where the ground may be as bright and as cold as the cloud above it. NASA’s Earth Observing System (EOS) Terra satellite, launched in 1999, carries a suite of nextgeneration instruments that aim to revolutionize cloud detection from space. One of these devices is the Multi-Angle Imaging Spectroradiometer (MISR) that views Earth across several bands of the electromagnetic spectrum using cameras pointed at nine different angles. No data like MISR’s have ever been collected from space before, opening up possibilities for new cloud detection approaches. For example, the heights of reflecting surfaces can be derived from the multi-angle “stereo” views, and compared with the known elevation of the terrain below. If a surface is measurably higher than the terrain, it’s classified as a cloud. When clouds are close to the ground though, as they often are at high latitudes, other approaches must be used. Yu and Shi, in collaboration with Pennsylvania State University meteorologist Eugene Clothiaux Prof. Bin Yu, whose work with cloudy data is described in this article, has recently been named to the Chang Jiang Chair Professorship at Peking University.