an assistant professor in the department and was promoted to professor in 1962. From 1977 to 1981, Lorenz served as head of the Department of Meteorology at MIT. In 1983, the MIT Department of Meteorology and Physical Oceanography merged with the Department of Geology to become the current MIT Department of Earth, Atmospheric and Planetary Sciences, where Lorenz remained a professor before becoming an emeritus professor in 1987. Atmospheric circulation In the late 1940s and early 1950s, Lorenz worked with Victor Starr on the General Circulation Project at MIT to understand the role the weather system played in determining the energetics of the general circulation of the atmosphere. From this work, in 1967, Lorenz published a landmark paper, titled "The Nature and Theory of the General Circulation of the Atmosphere," on atmospheric circulation from an energetic perspective, which advanced the concept of available potential energy. Numerical weather prediction In the 1950s, Lorenz became interested in and started work on numerical weather prediction, which relied on computers to forecast weather by processing observational data on such things as temperature, pressure, and wind. This interest was sparked, in part, after a visit to the Institute for Advanced Study in Princeton, New Jersey, where he met Jule Charney, then head of the IAS's Meteorological Research Group and a leading dynamical meteorologist at the time. (Charney would later join Lorenz at MIT in 1957 as a professor of meteorology.) In 1953, Lorenz took over leadership of a project at MIT that ran complex simulations of weather models that he used to evaluate statistical forecasting techniques. By the late 1950s, Lorenz was skeptical of the appropriateness of the linear statistical models in meteorology, as most atmospheric phenomena involved in weather forecasting are non-linear. It was during this time that his discovery of deterministic chaos came about. Chaos theory In 1961, Lorenz was using a simple digital computer, a Royal McBee LGP-30, to simulate weather patterns by modeling 12 variables, representing things like temperature and wind speed. He wanted to see a sequence of data again, and to save time he started the simulation in the middle of its course. He did this by entering a printout of the data that corresponded to conditions in the middle of the original simulation. To his surprise, the weather that the machine began to predict was completely different from the previous calculation. The culprit: a rounded decimal number on