Meteorology is the study of the atmosphere, atmospheric phenomena, and weather. Meteorologists observe and measure various aspects of the atmosphere to explain different phenomena and forecast upcoming phenomena. Meteorology includes several different fields, such as climate change, air quality and remote sensing.
Weather forecasters use the field of meteorology to make predictions about the weather. Weather forecasting has a long history. For millennia, scientists have recorded their observations of the weather to try to find patterns and predict what might come next. This field of science has changed as new technology becomes available.
No tech: Scientists observed the weather in person and used reports from people in other locations, recording patterns in logs and notebooks.
Low tech: Between the 1600s and early twentieth century, scientists and engineers invented various tools to measure the weather, such as thermometers, sling psychrometers, and barometers.
Satellites: The first weather satellites were launched during the 1970s, allowing us to obtain comprehensive data about clouds and temperature. Infrared images of clouds allows meteorologists to determine where the tallest, coldest clouds are, which in turn helps them predict storms.
Radar: Although radar was developed early in the twentieth century, a network of radars used for meteorological purposes wasn’t developed until the 1970s. Radar allows scientists to detect rain and snow. Meteorologists combine radar and satellite images in order to study the connections between cloud and precipitation.
Automated Weather Stations: A nation-wide network of these stations was established in the 1990s. Automated weather stations take a lot of the same measurements that the “low tech” tools of previous centuries would take, but they do it automatically at regular intervals.
Computer models: Before the early 2000s, computers weren’t powerful enough to compute all the necessary data to come up with a forecast in a timely fashion. Now that our computers are faster and more powerful, they can process a great deal of information about current weather phenomena, and using complex equations and algorithms, come up with a forecast for what future weather might be like.