Climate and Simulation
This is an advance summary of a forthcoming article in the Oxford Research Encyclopedia of Climate Science. Please check back later for the full article.
In the mid-1950s, the geophysicist Norman Phillips computed a general circulation model on John von Neumann’s IAS computer at the Institute for Advanced Studies (IAS) at Princeton. His two-level quasi-geostrophic model predicted the main global circulation patterns for one hemisphere and the poleward transport of energy. Phillips’ computations are considered to be the very first climate simulation and the crucial experiment for testifying that numerical flow can represent large-scale dynamic patterns of the atmosphere. It is high-speed computing, as Phillips pointed out in his conclusion, which will overcome the main obstacle of meteorology, namely the difficulty of solving the nonlinear hydrodynamic equations. Thus, computations will advance the physical understanding of the atmosphere.
Simulation as the numerical approach to scientific problems requires not only high-speed computing, but also a view of meteorology as dynamical meteorology, which was developed in the late 19th and early 20th centuries. Originating as a way to address the problem of weather forecasting, the dynamical approach turned meteorology into the physics of the atmosphere. This view detached the experience of climates into average weather, defined by the World Meteorological Organization as the mean and variability of relevant quantities of variables such as temperature, precipitation, or wind over a period of time of at least 30 years. Today, simulated climate has become a prominent topic in public discourse due to the environmental and societal problem of anthropogenic climate change. However, understanding climate and simulation requires understanding the three major transformations of meteorology: from weather to climate, from synopsis to numerics, and from measurements to projections.