A modern, four day weather forecast, obviously relies on more than simply the current observations of the sky. What are the factors that help meteorologists make this forecast? What methods were used to make the predictions?

Weather forecasting is not an exact science. It ranges from weather folktale simplicity to elaborate computer simulations that rely on a variety of methods to produce their results.

In attempting a forecast, forecasters rely on a series models. Each model uses a different set of programmed parameters for analyzing upper air data, so readout between them is often different. Confidence in the long-range forecast is much higher when the models are in synchronization , or basically "agree" on what's going to happen.

GFS   This is the "Aviation" portion of the Global Spectral Model, also sometimes called the "Global Forecast System" or GFS. AVN looks outward fifteen days, but confidence in accuracy is low beyond eight or ten.

ETAMOS   Pronounced "mezzo AY-tuh", this is a short-range model. It looks ahead three days, and is the only model that includes terrain as one of the parameters. When you live near mountains and oceans, terrain is a factor.

NGMMOS  (Nested Grid model) (Model Output Statistics) which are statistically derived surface conditions for particular cities. This model gives forecast information out to 48 hours

Numerical Weather Prediction:
Numerical Weather Prediction (NWP) uses the power of computers to make a forecast. Complex computer programs, also known as forecast models, run on supercomputers and provide predictions on many atmospheric variables such as temperature, pressure, wind, and rainfall. A forecaster examines how the features predicted by the computer will interact to produce the day's weather.

The NWP method is flawed (not exact but close) in that the equations used by the models to simulate the atmosphere are not precise. This leads to some error in the predictions. In addition, the are many gaps in the initial data since we do not receive many weather observations from areas in the mountains or over the ocean. If the initial state is not completely known, the computer's prediction of how that initial state will evolve will not be entirely accurate.

Despite these flaws, the NWP method is probably the best at forecasting the day-to-day weather changes. Very few people, however, have access to the computer data but you don't need to when you can get your forecast from exact weather. The data is allready compiled and analyzed by the National Weather Service.

Other Forecasting Methods climatology, analogue and numerical weather prediction

The Climatology Method is another simple way of producing a forecast. This method involves averaging weather statistics accumulated over many years to make the forecast. For example, if you were using the climatology method to predict the weather for New York City on July 4th, you would go through all the weather data that has been recorded for every July 4th and take an average. If you were making a forecast for temperature and precipitation, then you would use this recorded weather data to compute the averages for temperature and precipitation.

If these averages were 87 degrees with 0.18 inches of rain, then the weather forecast for New York City on July 4th, using the climatology method, would call for a high temperature of 87 degrees with 0.18 inches of rain. The climatology method only works well when the weather pattern is similar to that expected for the chosen time of year. If the pattern is quite unusual for the given time of year, the climatology method will often fail.

Analog Method:
The Analog Method is a slightly more complicated method of producing a forecast. It involves examining today's forecast scenario and remembering a day in the past when the weather scenario looked very similar (an analog). The forecaster would predict that the weather in this forecast will behave the same as it did in the past.

For example, suppose today is very warm, but a cold front is approaching your area. You remember similar weather conditions one last week, also a warm day with cold front approaching. You also remember how heavy thunderstorms developed in the afternoon as the cold front pushed through the area. Therefore, using the analog method, you would predict that this cold front will also produce thunderstorms in the afternoon.

The analog method is difficult to use because it is virtually impossible to find a perfect analog. Various weather features rarely align themselves in the same locations they were in the previous time. Even small differences between the current time and the analog can lead to very different results. However, as time passes and more weather data is archived, the chances of finding a "good match" analog for the current weather situation should improve, and so should analog forecasts.

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