How weather forecasts are created. There are three important stages to a weather forecast: Knowing what the weather is doing now Calculating how this will change in future Using meteorological expertise to refine the details In order to know what the weather will do in the future, we first need to know accurately what it is doing now.
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The result is a "forecast" of the present, which helps fill the data gaps, completing a snapshot of the current weather at every point on the imaginary global grid. It's generated with the same computer tools that allow meteorologists to look into the future—an approach called numerical modeling. The time machine is a computer model of the atmosphere, built not from air and water vapor but from data and equations.
The equations describe the key processes that govern weather, such as airflow, evaporation, Earth's rotation, and the release of heat as water condenses or freezes. When meteorologists plug in data on atmospheric conditions, then run the equations, the model predicts how the atmosphere will evolve.
It lets forecasters ask: If this is what the atmosphere is doing now, what will it be doing in one minute? And then again one minute after that? At each step, the model computes weather conditions at all points on that imaginary global grid. The process lets meteorologists generate a full picture of current conditions, then carry it forward in time to create a forecast.
Some models push as far as 16 days into the future, though by that point the accuracy is so diluted that about all they can say is whether the temperature will be above or below the normal monthly average.
Even baby-stepping into the future takes bruteforce computing. But early computers couldn't run a model fast enough for useful predictions. NCEP's computer center in Gaithersburg, Maryland, now crunches numbers in one of the most powerful weather-forecasting engines in the world, a supercomputer called Blue. A backup, housed elsewhere, is called White, and researchers refine their models on a third machine called Red.
Resembling a warehouse filled with high-tech filing cabinets, the new machine isn't running at full speed yet. But by it will handle 8. Yet even the most sophisticated computer models drastically simplify the real atmosphere. Most track conditions at points tens of miles apart, even though actual weather can vary widely within only a couple of miles—the size of a thunderstorm.
The models also have biases: Some do better with hurricanes, while others are better at predicting winter weather, such as ice storms. Forecasters try to compensate by consulting different models, like patients getting second opinions.
All that means extra number crunching. Something called the butterfly effect adds to the burden. In Ed Lorenz, a meteorologist at MIT, used the atmosphere to illustrate chaos theory—the idea that tiny fluctuations can, over time, have outsize effects. He suggested that the gentlest breeze from a butterfly closing its wings on one side of the planet could cause a storm on the other.
It's an exaggeration, with a measure of truth: Factors so small that they get lost—in measurement gaps or errors, or in the models' shortcuts—can make a major difference in the weather. A small wind shift, for example, might send a storm veering miles from its predicted course.
In winter "a difference of a fraction of a degree can make all the difference in the world as to whether you get all rain, or all snow, or freezing rain, or sleet," Hoke says.
To address the butterfly effect, forecasters rely on a strategy called ensemble forecasting. Starting with one basic set of initial conditions, they run multiple forecasts—as many as 50 at the European Centre for Medium-Range Weather Forecasts, the world leader in ensemble forecasting.
Each begins with a slightly different "perturbation"—a change in wind speed, a degree in temperature, a percentage point in humidity. The forecast becomes statistical: In, say, 43 of the 50 computer runs snow develops, while in seven it rains. That's why so many forecasts use words such as "possible" or "likely," and speak of the percentage probability of precipitation.
Computers don't have the last word. After the models have their say, their output is converted to user-friendly graphics and, in the U. There flesh-and-blood meteorologists second-guess the machines. One fall day Bruce Terry was the lead forecaster on duty, sitting at a workstation flanked by computer screens. The windows were shaded to keep out glare, hiding the weather outside. All the action was on the screens. On one a radar readout showed a blue-green smear curving up from the southern plains states toward the Ohio Valley; another displayed a satellite view of the same region, veiled in gray cloud.
On that particular day Terry's job was to decide where the rain would fall, and how much. Forecasting precipitation, he said, is one of his greatest challenges. At least it wasn't summer, when thunderstorms, too small for the computer models to capture, deliver most of the rain. Precipitation forecasts are easier in the cool seasons, when weather systems tend to be large and well organized, like this one.
He stared at the screen some more. Right now, comparing the rain on the screen with model forecasts, Terry sensed a bias was at work. A patch of low pressure was lingering over the southern Rockies, drawing wet air from the Gulf of Mexico and supercharging the storm with moisture. The computer had given him its best guess, but now it was time to follow his instincts. He frowned and used his computer drafting tool to sketch in corrected precipitation estimates, calling for heavier rain.
What did people do before all those tools were invented, though? Check out Old Fashioned Ways To Predict the Weather to learn more about some interesting ways people use their powers of observation to predict the weather!
Have you ever seen a badger on the nightly newscast? Although that might sound silly, every Groundhog Day, people look to a furry forecaster to tell them whether there'll be an early spring or six more weeks of winter. Can any other animals predict the weather? What about wooly worms? Jump online to read through 8 Animals Thought To Predict the Weather for more information on some potential forecasters from the animal kingdom!
Have you ever watched a weather forecast on television? Cool graphics overlaid on maps show the potential for weather systems moving through your area. If you're up for a challenge, explore the Make a Weather Forecast activity to learn more about forecasting symbols.
With a bit of online research, you can put together your own custom weather map! Did you get it? Test your knowledge. What are you wondering? Wonder Words idea guess data front tool buoy future equip accurate local pattern radar temperature potentially precipitation complicated observation psychrometer Take the Wonder Word Challenge.
Join the Discussion. Nov 6, Nov 11, G's Wonder Monsters Sep 27, We learned that scientists put thermometers on buoys in the ocean. We learned that meteorologists use space stations and radars to predict our weather. We liked this wonder a lot - we have been studying weather in science. We are meteorologists! We are wondering how scientists made all those tools to collect data on the weather on our planet!
Dont know my name Nov 6, Sep 27, RD Nov 30, The people who predict the weather are sometimes right about the weather that is going to happen. How many weather stations are there in the U. David Mar 19, Dec 7, Great question, RD! AL Nov 30, Anemometers, wind vanes, thermometers, and the weather men keep track of the weather. I want to know more about how anemometers are made. Brooklynn olivia. Oct 19, G's Classroom Monsters Oct 19, We learned about barometers with this article.
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