Weather forecasting | Methods, Importance, & History (2024)

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Written by

John J. Cahir Professor of Meteorology; Associate Dean, College of Earth and Mineral Sciences, Pennsylvania State University, University Park. Coauthor of Principles of Climatology and others.

John J. Cahir

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Key People:
James Martin Stagg
Vilhelm Bjerknes
Alexander Buchan
Jacob Bjerknes
Tor Harold Percival Bergeron
Related Topics:
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medium-range weather forecasting
numerical weather prediction
short-range weather forecasting
persistence

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weather forecasting, the prediction of the weather through application of the principles of physics, supplemented by a variety of statistical and empirical techniques. In addition to predictions of atmospheric phenomena themselves, weather forecasting includes predictions of changes on Earth’s surface caused by atmospheric conditions—e.g., snow and ice cover, storm tides, and floods.

Measurements and ideas as the basis for weather prediction

The observations of few other scientific enterprises are as vital or affect as many people as those related to weather forecasting. From the days when early humans ventured from caves and other natural shelters, perceptive individuals in all likelihood became leaders by being able to detect nature’s signs of impending snow, rain, or wind, indeed of any change in weather. With such information they must have enjoyed greater success in the search for food and safety, the major objectives of that time.

In a sense, weather forecasting is still carried out in basically the same way as it was by the earliest humans—namely, by making observations and predicting changes. The modern tools used to measure temperature, pressure, wind, and humidity in the 21st century would certainly amaze them, and the results obviously are better. Yet, even the most sophisticated numerically calculated forecast made on a supercomputer requires a set of measurements of the condition of the atmosphere—an initial picture of temperature, wind, and other basic elements, somewhat comparable to that formed by our forebears when they looked out of their cave dwellings. The primeval approach entailed insights based on the accumulated experience of the perceptive observer, while the modern technique consists of solving equations. Although seemingly quite different, there are underlying similarities between both practices. In each case the forecaster asks “What is?” in the sense of “What kind of weather prevails today?” and then seeks to determine how it will change in order to extrapolate what it will be.

Because observations are so critical to weather prediction, an account of meteorological measurements and weather forecasting is a story in which ideas and technology are closely intertwined, with creative thinkers drawing new insights from available observations and pointing to the need for new or better measurements, and technology providing the means for making new observations and for processing the data derived from measurements. The basis for weather prediction started with the theories of the ancient Greek philosophers and continued with Renaissance scientists, the scientific revolution of the 17th and 18th centuries, and the theoretical models of 20th- and 21st-century atmospheric scientists and meteorologists. Likewise, it tells of the development of the “synoptic” idea—that of characterizing the weather over a large region at exactly the same time in order to organize information about prevailing conditions. In synoptic meteorology, simultaneous observations for a specific time are plotted on a map for a broad area whereby a general view of the weather in that region is gained. (The term synoptic is derived from the Greek word meaning “general or comprehensive view.”) The so-called synoptic weather map came to be the principal tool of 19th-century meteorologists and continues to be used today in weather stations and on television weather reports around the world.

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Since the mid-20th century, digital computers have made it possible to calculate changes in atmospheric conditions mathematically and objectively—i.e., in such a way that anyone can obtain the same result from the same initial conditions. The widespread adoption of numerical weather prediction models brought a whole new group of players—computer specialists and experts in numerical processing and statistics—to the scene to work with atmospheric scientists and meteorologists. Moreover, the enhanced capability to process and analyze weather data stimulated the long-standing interest of meteorologists in securing more observations of greater accuracy. Technological advances since the 1960s led to a growing reliance on remote sensing, particularly the gathering of data with specially instrumented Earth-orbiting satellites. By the late 1980s, forecasts of the weather were largely based on the determinations of numerical models integrated by high-speed supercomputers—except for some shorter-range predictions, particularly those related to local thunderstorm activity, which were made by specialists directly interpreting radar and satellite measurements. By the early 1990s a network of next-generation Doppler weather radar (NEXRAD) was largely in place in the United States, which allowed meteorologists to predict severe weather events with additional lead time before their occurrence. During the late 1990s and early 21st century, computer processing power increased, which allowed weather bureaus to produce more-sophisticated ensemble forecasts—that is, sets of multiple model runs whose results limit the range of uncertainty with respect to a forecast.

Weather forecasting | Methods, Importance, & History (2024)

FAQs

What is the history of weather forecasting? ›

Ancient forecasting

In 650 BC, the Babylonians predicted the weather from cloud patterns as well as astrology. In about 350 BC, Aristotle described weather patterns in Meteorologica. Later, Theophrastus compiled a book on weather forecasting, called the Book of Signs.

Why is weather forecasting important? ›

But in many ways weather forecasts are absolutely crucial: they can be a matter of life and death. Accurate forecasts can save lives by giving early warnings of storms, heat waves, and disasters. Farmers use them for agricultural management, which can make the difference between a lost harvest or a harvest of plenty.

Why do we need historical weather data? ›

This information could be used to study how and why our climate has changed. Or it could be used to examine "climate catastrophes," such as the Dust Bowl of the 1930s, figure out why they happened, and determine whether they are likely to happen more frequently as the climate changes.

How has weather forecasting improved over time? ›

Advancements in technology have revolutionized how we perceive, understand, and forecast weather patterns. From the early barometers to modern satellites and supercomputers, each innovation has significantly enhanced our ability to predict weather accurately.

What is the history of weather study? ›

The study of meteorology dates back millennia, though significant progress in meteorology did not begin until the 18th century. The 19th century saw modest progress in the field after weather observation networks were formed across broad regions. Prior attempts at prediction of weather depended on historical data.

How has weather changed history? ›

Weather has influenced significant events thorughout human history, whether forced migration or the course of a war. Sometimes these events are tied to climate change, other times they represent anomalies that affected the future of air travel or launched eras of famine and disease.

What is forecasting and why is it important? ›

Forecasting is a method of making informed predictions by using historical data as the main input for determining the course of future trends. Companies use forecasting for many different purposes, such as anticipating future expenses and determining how to allocate their budget.

Why are accurate forecasts so important? ›

Accurate forecasting can have a major impact on various aspects of business, from resource and inventory management to sales, marketing, budgeting, and everything in between. It can help stakeholders make more informed decisions to drive their business forward, allowing it to stay competitive in the global marketplace.

Why is it important to measure and predict the weather? ›

Introduction. Measuring and recording the weather is essential for many reasons: to accumulate an accurate record of the past; to provide a picture of what is happening now and a warning of extreme events; and to give the right starting point for predicting the future, in other words a weather forecast.

What are the benefits of using historical data when forecasting? ›

By using historical data, you can create models that estimate how these variables will affect your future outcomes, such as revenue, costs, or growth. Historical data can also help you validate your assumptions, test your scenarios, and adjust your forecasts based on actual results.

Why is weather data analysis important? ›

Data analysis can help improve the accuracy and reliability of weather predictions by identifying patterns, trends, anomalies, and uncertainties in the data. In this article, you will learn about some of the best data analysis techniques for improving weather forecasting accuracy and how they are applied in practice.

What is the significance of the weather record? ›

Weather records are invaluable in many aspects of daily life. They help ensure safety, optimize productivity, protect public health, and contribute to our understanding of the changing climate.

Why is the weather forecast important? ›

Weather Forecasting is crucial since it helps to determine future climate changes. With the use of latitude, we can determine the probability of snow and hail reaching the surface. We are able to identify the thermal energy from the sun that is exposed to a region.

How reliable is weather forecasting? ›

The Short Answer: A seven-day forecast can accurately predict the weather about 80 percent of the time and a five-day forecast can accurately predict the weather approximately 90 percent of the time. However, a 10-day—or longer—forecast is only right about half the time.

Why is weather forecasting challenging? ›

In principle, if meteorologists know the current weather conditions, such as wind, pressure, and precipitation, they can use these pieces to generate a complete weather forecast; however, these equations are often inadequate, struggling to capture the intricate and ever-changing nature of our planet's weather systems.

How did they predict the weather in the past? ›

They relied on clouds, winds, The Old Farmer's Almanac, past experience in how the seasons flow, animal behavior signs, and their own arthritic bones to make predictions about the weather.

Who was the man who invented the weather forecast? ›

Vice-Admiral Robert FitzRoy founded the Met Office in 1854. FitzRoy was already well-known as the captain of HMS Beagle, from her famous journey around the globe. He would go on to establish the science of weather forecasting, the basis of what we still use today.

How did they predict weather in the 1700s? ›

If the wind followed the sun's movements blowing from east to west the settlers predicted clearing skies. If, however winds were blowing west to east, storms and clouds were predicted. Weathervanes were very important to farmers and others who depended on the weather for their livelihood.

What is the history of numerical weather prediction in the United States? ›

Operational numerical weather prediction in the United States began in 1955 under the Joint Numerical Weather Prediction Unit (JNWPU), a joint project by the U.S. Air Force, Navy, and Weather Bureau. The JNWPU model was originally a three-layer barotropic model, also developed by Charney.

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