tions agree (or come close to) the real data collected from the system, then we can
determine its accuracy. In fact, the set of equations and models are only “valid” as long
as the two sets of data are close. If a model result leads to conclusions that are not
close to the real-world scenario, then the equations are further modified to correct for
the discrepancies as much as possible.
For example, in weather prognostication, meteorologists use various numerical
models to make long-term predictions of weather systems (for more information
about models and weather prediction, see “Math in the Natural Sciences”). It is inter-
esting to see how meteorologists use a combination of several of the weather models
to forecast the weather in certain spots around the United States and the world—
mainly because no weather forecasting model has all the right answers. Every day,
researchers are tweaking their respective weather models (based on more collected
data) in hopes of eventually understanding our weather a bit better.What is a simulation?
A simulation is an imitation of some real event or device. It is often used interchange-
ably with the word modeling (as in modeling of natural systems). A simulation tries to
represent certain features (or behaviors) of a complex physical system based on the
268 underlying computational models of the phenomenon, environment, or experience.
Many different types of data, including air pressure, temperature, humidity, and so on, must be taken into
account when constructing computer models of hurricanes. The Image Bank/Getty Images.