Weather For Dummies. John D. Cox. Читать онлайн. Newlib. NEWLIB.NET

Автор: John D. Cox
Издательство: John Wiley & Sons Limited
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isbn: 9781119811022
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see why.) Look into the history of almanackers and fortune-tellers of the 19th century, and you will realize that people have wanted reliable weather forecasting long before they could get it. Even early scientists who began to understand the weather thought that forecasting its future was out of the question.

      The local forecast may seem easy and breezy, but before it gets to the Internet and the screens of our mobile devices or TVs, a lot of hard science and heavy-duty number-crunching has been going on. My people at the Go Figure Academy of Sciences (GoFAS) tell me that meteorology, the study of the atmosphere, is harder than rocket science. (Check out the sidebar about GoFAS for the real lowdown on this imaginary institution.)

      Think of it this way: When it blasts off its launch pad, the first thing scientists want their rockets to do is get out of the atmosphere, to leave behind all the turbulent mess of swirling gases surrounding Earth. (As you may have noticed, a rocket that doesn’t do this is quickly in big trouble!) As soon as it can, it enters the quiet, predictable vacuum of space.

      And the mathematics, well — let me put it this way: Meteorologists have bigger computers.

      Some of the most powerful supercomputers in the world are devoted to figuring out what the weather is going to be like one day to the next. You wouldn’t believe everything that goes into making a modern, state-of-the-art, accurate weather forecast. But, in this chapter, I’m going to tell you anyway!

      Before the advent of electronic computers in the 1950s, weather forecasting was a much more difficult and, frankly, less accurate service. In those days, weather forecasting developed a reputation for inaccuracy that still haunts the business. Some early television forecasters even used puppets and other light-hearted distractions to ham up their presentations. The idea was that predictions were not expected to be taken too seriously.

      Many forecasters in those days used a method that relied on maps of other days’ weather. They would draw a map locating areas of high and low pressure, warm and cold air masses, and moving storm fronts. Then they would page through big collections of earlier maps in search of patterns that most closely resembled the weather they saw before them. This was standard procedure: The map with the best fit would serve as an analog of what to expect from the current day’s pattern. A certain amount of personal experience and reputation and even “hunches” went into it. After decades of forecasting weather, this was the state of the art. Sometimes this analog method produced a fairly accurate prediction of the day ahead, and sometimes it didn’t.

      Looking back, it is easy to see now that early forecasters were attempting to do something that just wasn’t humanly possible. The problem they were trying to solve was too big for their science. For one thing, their data was too sparse, their picture of the atmosphere was too sketchy. Even if they had more data, they didn’t have a way to manipulate the information fast enough to stay ahead of the passing weather.

      THE GO FIGURE ACADEMY OF SCIENCES

      Weather science can be a complicated and difficult subject, so I figured Weather For Dummies ought to have its very own think tank. So, well … I made one up. It’s the Go Figure Academy of Sciences (GoFAS), and it’s all mine. It can be yours, too, if you want it. I took the best people I could find and put them to work in my own place.

      It looks a little like the World Weather Building that the National Weather Service occupies outside of Washington, D.C. (see figure). It also looks a little like the Massachusetts Institute of Technology, except my dome comes to a sharper point. Anyway, I think it looks pretty great!

      While weather information comes in many voices and forms these days, all forecasting meteorologists begin their days with certain things in common, just a keystroke away.

      On their computer screens are the latest forecasts issued by such major global models as the U.S. Forecast System, the European Model, and perhaps a regional forecast of some local significance. They will see where the models agree and where they differ. Often, they will refer to ensemble forecasts to more closely examine the range of possible outcomes (see “Playing the spread” later in this chapter for more about these types of forecasts). Also available are the latest images from satellites supplied by the United States and other nations and commercial concerns who are owners and operators of satellite fleets.

      Behind the scenes, in the World Weather Building in Camp Springs, Maryland, people who work for the National Weather Service play big roles in the daily weather forecast even if you don’t hear their voices or see their faces. Television meteorologists compete with one another for your viewing pleasure, with their different styles and presentations and engaging personalities. But when it comes to the actual forecast, they are pretty much reading from the same page. They all have the computing and forecasting resources of the National Weather Service on their sides. (And so do you.) It’s not a bad way to begin the day.

The basic tool for making modern weather forecasts is the supercomputer. For the outlook beyond the short range of the next several hours, all savvy meteorologists, private and public alike, check out the forecast data supplied by the national and international Numerical Weather Prediction computer models. Imagine the atmosphere around the world divided into individual squares of air spread out in all directions and stacked one on top of another maybe 10 miles high. Millions of individual cubes of air, all with their own different physical properties impinging on one another. That is how a supercomputer model “sees” the atmosphere. Working out how these different physical properties such as temperature and pressure travel through this vast grid is how these models predict future weather. The output of these incredibly complex models is not seen by you and me when the forecast is delivered, but it is an important part of the forecasting process. But other forecasting techniques still play a role.

       Computer modeling. Day in and day out, the statistics that come out of large and powerful software programs run on supercomputers are the single most important ingredients in the making of the average public weather forecast. The incoming stream of data is constant and from far afield — from the ground, from the sea, from low and high in the atmosphere, and from near and far distant space. At the National Weather Service’s World Weather Building, data is fed into a software program that acts like a virtual, or model, atmosphere.