Early civilizations attempted to observe, forecast and even influence the weather. However, the Greek philosopher Aristotle is often credited as the founder of meteorology. The word meteorology comes from the Greek word “meteoron,” which means “any phenomenon in the sky.” Aristotle wrote the first major treatise on the atmosphere, Meteorologica, around 350 BCE and it remained an authority on the subject for nearly 2,000 years.

During the 17th century, meteorology experienced a scientific revolution as French philosopher, scientist and mathematician René Descartes applied his scientific method to the topic. Despite being relatively deductive due to a lack of accurate meteorological instruments, Descartes' theories solidified meteorology as a legitimate branch of physics.

The 18th century inventions of the barometer and thermometer marked a major shift in meteorology. These devices allowed scientists to measure two important atmospheric variables: air pressure and temperature. During this time, scientists also developed mathematical models to make more accurate weather predictions.

By the 19th century, innovations such as the telegraph allowed meteorologists to share information by using Morse code, which led to the development of the first modern weather maps. These maps provided a large-scale view of global weather patterns and allowed for more accurate weather forecasting.

In the 20th century, advances in atmospheric physics led to the foundation of modern numerical weather predictions. Norwegian meteorologists discovered the concept of air masses and fronts, which are building blocks for today’s weather forecasting.

Scientists during the World Wars advanced meteorology as military operations increasingly depended on understanding and predicting weather conditions. Even radar, which was originally invented to track the direction and speed of aircrafts and ships, was repurposed to track the direction and speed of weather patterns.

By the 1950s and 1960s, satellites and computer models could observe atmospheric pressure on a global scale and run data-driven simulations—all of which led to more accurate weather forecasting. Modern meteorology uses advanced versions of these technologies to observe and predict the weather in near-real time.

Businesses rely on weather forecasts for risk management. The aviation industry, for instance, uses weather data such as wind speed and precipitation to inform flight planning and tracking. Organizations with fleets of vehicles take weather information into account to ensure they’re not sending out their fleet into a storm. And utility companies rely on weather prediction location intelligence tools such as LiDAR to manage power grids, forecast electrical loads and prevent potential wildfires.

Meteorologists can help predict and mitigate the adverse effects of severe weather events. This comes at a time when damage from global natural disasters totaled USD 380 billion in economic losses in 2023.¹

Using global climate models, meteorologists can also track ongoing climate trends such as the Earth’s temperature. According to the Task Force on Climate-related Financial Disclosures (TCFD), changing climate conditions have the potential to impact various aspects of the environment, business and society. Understanding these climate risks and building climate resilience is crucial as the world’s nations work together to combat climate change and achieve net zero.

Microscale phenomena range in size from a couple of centimeters to a few kilometers. They have short time scale, typically less than a day. These phenomena affect small geographic areas and impact the temperatures and terrains of those regions. Examples of microscale meteorology include the transfer of heat between soil and vegetation, the movement of air pollutants and air quality.

Mesoscale phenomena range from a few kilometers to nearly 1,000 kilometers and can last from less than a day to several weeks. They consist of two phenomena: mesoscale convective complexes (MCC) and mesoscale convective systems (MCS). Water vapor turns into precipitation and manifests as a singular cloud system that produces heavy rainfall, classified as an MCC, or a smaller cluster of thunderstorms, classified as an MCS.

Synoptic-scale phenomena cover an area of several hundreds to thousands of kilometers and can persist for up to 28 days. They’re made up of high- and low-pressure systems. In a low-pressure system, wind and moisture are sucked up into the high-pressure system, which accelerates convection and produces more severe weather conditions. High-pressure systems have a downward vertical motion and typically produce drier, less inclement weather.

Global scale phenomena refer to the flow of wind, heat and moisture from the tropics to the poles. Global atmospheric circulation (GAC) is the large-scale pattern that distributes heat across Earth's surface. Each hemisphere contains three types of convection currents, or cells: Hadley cells, Ferrell cells and polar cells. Meteorologists often focus on Hadley cells as they have the biggest impact on GAC and can dictate the flow of trade winds used by ships.

Radar dishes can be fixed to weather balloons, planes, boats and more. They use sensors to transmit radio waves, which collect information such as the dimension, speed and direction of clouds. Dual-polarization radar deploys horizontal and vertical wave pulses, providing better weather prediction capabilities. These insights can be valuable when analyzing climate risks to improve safety measures in the airline industry, for instance.

Satellites play a crucial role in observing atmospheric changes and predicting global-scale weather phenomena. The National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA) are two organizations that operate Geostationary Operational Environmental Satellites. These satellites collect valuable geospatial data that can be visualized by using geographic information systems. Beyond weather patterns, these satellites also provide remote sensing capabilities to help farmers manage crops and improve water usage. 

Today, computer modelling is one of the most reliable and accurate ways for meteorologists to predict weather patterns. Computer models are made up of various codes and algorithms, which process large swaths of meteorological data and convert it into projections known as weather models. These models change according to certain inputs, allowing meteorologists to adjust their forecast as needed. Public health officials can also use similar techniques for disease forecasting and surveillance.