Predicting snowfall levels for an entire geographic area is no easy feat. If it was, every meteorologist would come to the same conclusion. Forecasting the amount of snow, ice and sleet specific areas will get during one storm system is even more difficult. James Hoke, director of the National Oceanic and Atmospheric Administration’s Hydrometeorological Prediction Center, said in an interview with ABC News, “Snow forecasting is arguably the most difficult, most complicated thing for forecasters to predict.”
- when it will start
- when it will stop
- how hard it will snow
- the ground temperatures
- if ground temps will change
- and the temperatures through several layers of atmosphere
These factors determine whether the precipitation falls as rain, snow or sleet as well as whether it will melt or stay frozen once it touches the ground. If the meteorologist has even slightly incorrect data for any one of those factors, his or her forecast could be completely wrong. How’s that for pressure?
A meteorologist uses three general tools to develop a forecast: computer models, radar and satellite imagery. All of which provide a glimpse into the current and previous weather patterns, but none of them are able to predict future weather patterns with 100% accuracy.
Computer programs make equations using giant amounts of data, such as wind direction, strength, barometric pressure, evaporation rates, and temperatures at varying levels. However, since none of those factors are constant, the program continuously computes new data for every single location. It then calculates how the data in one location will affect neighboring area. The result of all of this arithmetic is the weather model that you hear meteorologists discuss. Data is taken from airplane instruments, weather balloons, radar and satellites. There are still many areas that could benefit from more sources, such as areas over the ocean.
To add to the confusion, weather.com states “the equations of upper air motion and the number of atmospheric levels that computer models use in their databases vary from model to model. Due to the differences in programming, one model’s prediction of a weather event may vary greatly from a second model’s.” In other words, one model may show that a winter storm is moving over Kansas while another model shows it going south into Oklahoma. In this case, the forecaster’s intuition and experience dictates the final forecasting decisions.