Explaining Weather Models

The Lorentz factor is a theory produced by Edward Lorentz that explains errors can become exponential in time. The term is a factor by which time, length, and mass can change while a certain object is moving.

When forecast models initialize, there are only so many data grid points that a model can pull from. Some are global, and some are specifically for the U.S., and some are even more higher resolution, focusing on certain parameters in the U.S. The point is, because there are not enough grid points for forecast models to pull from , these models interpolate. Interpolation places data in, where data doesn’t exist. From there, a forecast is generated. All forecast model data has some amount of error in the initialization phase.

From day 1 there could be minor errors to day 5 where errors could be exponentially larger, showing 3″ to 5″ of rainfall, when in reality we only picked up 0.5″ total. This graphic shows that the greater time , the more room there is for error. This is also why it’s so important to keep checking back with the forecast, especially during times of active weather. Follow @ABC17Stormtrack on Twitter for the latest changing conditions.