Science Symposium: Lewis Fry Richardson

Pedro Cena

Meteorology 

Block 2

                                       Lewis Fry Richardson

    Lewis Fry Richardson was a British mathematician, physicist, and meteorologist who pioneered modern mathematical techniques of weather forecasting.  He began making these major contributions to meteorology using physics from 1913 to 1922. When World War I began in 1914, he worked for a meteorological office as the superintendent of the Eskdalemuir Observatory. During his studies at the office, he became the first person to apply mathematics to predict the weather which was published in his book named Weather Prediction by Numerical Process. He became fascinated by the use of computer sciences, he organized a group of many individuals who used supercomputers( not the powerful computers we use today) and used mathematical equations to detect weather patterns and other oceanic and natural patterns. This process they used led to the development of the Richardson number. 

    The Richardson Parameter can be used to predict the occurrence of fluid turbulence and the destruction of density currents in water or air. This number was defined by Richard Fry Richardson whom it is named after. The number is essentially the ratio of the density gradient ( the change in density with depth) to the velocity gradient. There are several variants of the Richardson number which have practical importance in weather forecasting and in investigating density and turbidity currents in oceans, lakes, and reservoirs. The different variants of the Richardson number as followed:

Aviation- The Richardson number is used as a rough measure of expected air turbulence

Thermal Convection: THe number represents the importance of natural convection relative to the forced convection

Oceanography: the Richardson number has a more general form which takes stratification into account. It is a measure of the relative importance of mechanical and density effects in the water column. The number defined is always positive.