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A New Weather Forecasting Idea

Think better weather forecasting requires a degree in meteorology? Maybe a degree in statistical analysis would help more. Here is a new way to forecast the weather with more accuracy and less knowledge.

February 2, 2007 - Canon City, Colorado. I brought in my Canon City Daily Record from the porch when it arrived, at about 3 in the afternoon. I opened the newspaper to the page with the weather forecast, wondering how cold it would be the following day.

The projected high temperature was 13 degrees Fahrenheit. I knew this was way too low. Forecasts on television and on the internet said that we would reach 23 or 27 degrees the following day. I knew they were also too low, and I told my wife it would be in the 30s at least. The actual high temperature the next day was 53 degrees Fahrenheit.

By the way, that's not a typo. The weather forecasting "experts" were off by as much as 40 degrees - and that was for a simple 24-hour forecast. How could they be so far off? And how could I be better than them at forecasting the weather?

I can't really answer the first question. Weather here is more unpredictable than in most places I've been. And perhaps they follow there computer models too slavishly, even when their experience and intuition tell them to adjust the forecast.

I can answer the second question. I did better than them because they were so consistent in the way they made their errors. Around this time, I remember counting something like 15 out of 20 days when all the various weather forecasts predicted a high temperature that was 5 degrees or more too low. All I had to do was take the highest temperature forecast and add five degrees.

A New Forecasting Model

The consistency in their errors was the key to this. They weren't forecasting too high one day and too low the next. They were wrong in the same ways over and over.

I'm not sure if the errors are as consistent in other parts of the country, but that could be determined by looking at the statistics. Check the forecast highs and lows for the last 365 days, and check the actual temperatures for those days. See what the predicted probabilities of rain or snow were, and what actually happened.

Let's suppose that of the 24 last times a given forecaster predicted a 50% chance of rain, it actually rained 18 times. He may have the best data, but he may be too conservative in how he uses it. Suppose this was not a fluke - which can be determined by doing more statistical analysis. You could know nothing about weather forecasting and provide a more accurate forecast simply by saying "A 75% chance of rain tomorrow" every time he said there was a 50% chance, right?

This is the basis for my new forecasting model. You start by gathering the statistical information on the forecasts of several weather forecasting services or meteorologists. You compare this to the actual weather that happened, and look for any consistencies in the inaccuracies. Then you create a computer program. As you enter each of these forecasts into it, they are adjusted for known tendencies. The result is a more accurate forecast.

For example, if Forecaster A has managed over the last year to forecast a high that averages 4 degrees over the actual high, the computer adjusts for that. More sophisticated analysis might show that Forecaster B is consistently predicting a higher probability of rain than there is in the fall, but a lower probability of rain than there actually is in the spring. The computer can take this into account. Finally, it may work best if the adjusted forecasts of three or more sources are then averaged.

There is no need to know anything at all about weather forecasting for this to work. It is based on the idea that even when experts have all the best knowledge and data, they sometimes apply it incorrectly, and do so in consistent ways. Don't be surprised if soon some television stations get rid of their meteorologists and take advantage of this new forecasting idea.

"And now, your electronic weather forecast, from our Statistical Analysis Weather Machine."

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Weather Forecasting Idea