METEOROLOGIST JEFF HABY
If it is 40 degrees F at 100 miles south of your remote location and 30 degrees 100 F at miles
north of your location and
then you reason it is 35 degrees at your location, you have used linear interpolation to find the temperature.
Interpolation is the main element that makes forecasting challenging. It makes forecasting challenging because it
is an estimation of the unknown. However, an educated meteorological guess can be made. Every model, every analysis
chart, and every chart with isopleths has the
isopleths formed by interpolation.
Interpolation is an educated guess
of a meteorological parameter. Computers are best at interpolating since they can make the best educated guess (often
in a 3-D field) and are not subjected to human error asumming the data has no human error. Suppose you had
a temperature sensor at the exact location an
isopleth is located. Will it be the exact temperature of the isopleth? The answer is sometimes yes and sometimes no.
This is where the mystery of the atmosphere occurs. Isopleths are educated guesses; they may have some error. In
fact, the smaller the number of observations the more likely there is going to be error. If you had to interpolate
isotherms with only 1/4th the number of data points, the temperature interpolation would look different. Errors with
interpolation grow with time. This is the primary reason forecast model data becomes increasingly inaccurate with
time, especially if the initial data is suspect. The phrase "garbage in equals garbage out" applies well to this
statement. This is especially true over ocean surfaces and isolated mountain and desert terrain where surface
and upper air observations are lacking. This is the reason
forecast models have difficulty
initializing storms off the West Coast of the U.S. and in Mexico.