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As a meteorologist, the holiday season is often filled with gripes and light-hearted ribbing about how I can be employed in a profession where I can provide the public with wrong information and still retain my job.

"Those lousy weathermen don't know what they're talking about!" said one of my aunts. "Just this past summer the TV said 'twenty percent chance of showers and thunderstorms' and then it rained on my picnic!"

Well, my dear aunt, the rain your picnic is the reason why the weatherman said there would be a twenty percent chance of showers and thunderstorms. Technically, the forecast was correct. If the weatherman had forecasted a zero percent chance of any precipitation, then that would be a poor forecast.

The major problem concerning the public misconception of the true quality of weather forecasts is that the overwhelming tendency is to remember what is considered a failed forecast, and not what is considered a correct forecast. In general, weather forecasts provide very useful information that the public can use to go ahead and plan their days successfully, but those times when it rains on their picnic are remembered much more readily than the days when everyone in their neighborhood was outside mowing their lawns on a correctly forecasted sunny day.

That being said, I would hedge a bet that there will never be a perfect weather forecast in my lifetime. And as far as I am concerned, I have a lot of living left to do. Why would I say such a thing, when I just spent the last minute or so saying that the public has a distorted view of reality? Quite simply, the atmosphere that surrounds our planet is an extremely complex system that evolves based on the solutions of mathematical equations that cannot be solved completely with current computing power.

You might say, "Well the National Weather Service has huge supercomputers that can run complicated models in a matter of minutes! Why can't they use these to predict the weather in my back yard?"

This begs for an explanation of what a numerical weather model really is, and what it can provide a meteorologist who may be making a forecast for your back yard.

First, let's imagine that we want to make a weather forecast for a location somewhere in the continental United States. Picture this map in your mind. Now put a big rectangular box around it. We will call this the model "domain." A very fast, and very sophisticated computer will create a forecast for this area. Now one thing

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