Learning meteorology weather conditions and such

Interested in learning meteorology weather conditions, some of the big picture and a little history?

How can we predict the conditions of the atmosphere? Some might say we can't. To that, I say "very funny".

People have used various methods and folklore to make weather predictions. Sometimes with success, sometimes not. So we needed to progress.

Modern scientific forecasting relies on objective data first and foremost. That is why we use radiosondes, satellites, radar and other instruments to gather it. These things provide many types of data which are used for special purposes.

The facts gathered gives us a good picture of the actual state of the atmosphere, such as where various temperatures and winds are located. We use a well researched and standard set of principals, the science of meteorology, to make sense of this information.

Some changes are predictable. Things like advection, horizontal transportation of things by the wind, are quite obvious, but other elements like chaos are not. We can only guess at the effects from more disordered influences using statistical methods such as ensemble forecasting. This complexity limits the amount of time good forecasts can be made for.

What is the difference between Weather and Climate? Weather usually means the immediate effects, a day or two, of atmospheric conditions. Climate refers to annual or even multi-year averages.

What is meteorology?

They took the appearance of mathematical relations of fluid dynamics for instance. Examples of how math relates to meteorology include the Navier-Stokes equations of the geostrophic equation. They were and remain a source of controversy, and are hard to apply systematically. Researchers continued for something more systematic.

In the 21st century, computers play a central role in forecasting. Research early in the 1900's gave us this possibility. The idea was that the air could be dealt with in small packages. Each represented by one or more numbers.

The more of these packets you used, the higher your resolution and the better could be your predictions. The problem is, the computers needed to do this were not available in 1922 when a key research paper was first published on this topic. The scientists of the day would have to wait several decades.

When they did appear, it turned out the machines could handle simple jobs competently. But many more developments in the research and computing power were needed to handle the finer intricacies of prediction.

And Now?

Further reading