How is weather forcast? Do patterns follow fractal Chaos relationship?

[shunyadragon]

In a previous thread, not related, the methods and expectations of how good weather forecasting should be were questioned and much misinformation was presented. There are a number of models current run in Europe and the USA use computer models that use atmospheric, ocean temperatures and currents, history of weather patterns and cycles, and fractal chaos modeling to forecast weather on the short term (3 and 7 day) and long term up to one year.

The following is an example of how this modeling is used to forecast weather.

Hurricane Forecast Computer Models

By Dr. Jeff Masters, Director of Meteorology

The behavior of the atmosphere is governed by physical laws which can be expressed as mathematical equations. These equations represent how atmospheric quantities such as temperature, wind speed and direction, humidity, etc., will change from their initial current values (at the present time). If we can solve these equations, we will have a forecast. We can do this by sub-dividing the atmosphere into a 3-D grid of points and solving these equations at each point. These models have three main sources of error:

1) Initialization: We have an imperfect description of what the atmosphere is doing right now, due to lack of data (particularly over the oceans). When the model starts, is has an incorrect picture of the initial state of the atmosphere, so will always generate a forecast that is imperfect.

2) Resolution: Models are run on 3-D grids that cover the entire globe. Each grid point represents of piece of atmosphere perhaps 40 km on a side. Thus, processes smaller than that (such as thunderstorms) are not handled well, and must be "parameterized". This means we make up parameters (fudge factors) that do a good job giving the right forecast most of the time. Obviously, the fudge factors aren't going to work for all situations.

3) Basic understanding: Our basic understanding of the physics governing the atmosphere is imperfect, so the equations we're using aren't quite right.

Weather forecasting is improving, but it will always be limited by the natural fact that all natural events follow fractal chaotic models. The more further into the future you try and forecast the weather the more variable the weather will turn out. Today we have reasonable three day forecasting, and ok but less reliable seven day forecasts.

One advantage of contemporary models is that they are developing whole world models, which has improved forecasting.

Later in this thread I will discuss long range forecasting, and the problems it presents.