The Science of Weather Data Collection

When we want to know whether to pack sunscreen or an umbrella, or we have to decide if we should get out the snow shovel on Christmas Eve, we turn to weather forecasts to see how likely a certain weather event will be in our area. However, you may never truly consider how that information gets onto your friendly weather app, including how scientists are able to so accurately predict what will happen with the atmosphere several days in advance. 

Meteorology is a fascinating field of study, one with enormous impacts on the health and safety of every living thing, and the precision of weather forecasts has improved exponentially in the last 40 years. But how has it advanced so much, and what exactly goes into collecting and presenting that data? Let’s take a look at the processes underneath your five-day forecast.

Instruments on the ground and in the atmosphere work together to generate thousands of data points

There are numerous forms of collection instruments with varying levels of precision and complexity; all of them gather different types of information about the environment, which are blended together to develop an overview of the current and future weather.

The most common type of collection instrument is called a weather station, which gathers information related to temperature, humidity, barometric pressure, wind speed and direction, and precipitation. These are often located at airports and schools, placed in an unobtrusive spot on the roof. 

You’d think that something which captures all this information would be enormous, but the average weather station is actually quite petite: you may not even notice this multi-pronged antenna if you don’t know what to look for. More advanced weather stations, such as those housed by TV stations and federal agencies, have their own radar systems that use radio waves to detect precipitation, which helps them determine the severity of weather systems passing through.

Higher above the earth, there are weather balloons and satellites, which each have their own purpose in gathering weather information. Balloons have instruments called radiosondes, which measure temperature, humidity, and atmospheric pressure, while satellites can capture data about cloud cover and ocean temperature. Similarly, most commercial aircraft are equipped with weather sensors to help pilots and air traffic controllers make smart decisions about flight patterns, and this information is often shared with weather agencies.

Meteorological agencies assimilate the information, then share it with developers and the general public

As you can see, there’s an enormous amount of data generated about weather from numerous different agencies and devices, all of which need to be arranged and interpreted for the general public. This form of data science relies upon supercomputers that can aggregate the information into a highly precise, uniform output. 

Of course, most people don’t just want to know what the weather is right now: they want to have an idea of what they can expect in the common hours and days, which can’t be determined just from real-time data. These forecasts are made by using millions of data points, past and present, to predict the future; incredibly complicated algorithms can look at trends over long periods of time to give probabilities for certain weather events. By performing data assimilation – in other words, putting the new information into the simulation – meteorologists can improve the accuracy of their forecasting, to the point where it can predict the weather in 15-minute segments. 

Because weather information is so incredibly important to the lives and livelihoods of everyone, meteorological agencies make their information publicly available through the use of an Application Programming Interface (API). An API gathers all the organized weather data from a number of different sources, and those who sign up for the service can request the information on a continuous basis for real-time weather tracking on their app. 

Many companies might consider implementing weather API software, including agricultural companies that need to make plans for harvesting and growing; solar and wind farms that must estimate output and determine when to make repairs; and even trucking companies, who might decide to divert their drivers from a certain area based on weather reports. Weather APIs are an incredibly useful tool across nearly every industry, and they are increasingly being included in industry-specific software packages.

Meteorological data is an underappreciated but essential aspect of modern life

Everyone wants to know what the weather is like; many of us have weather-telling widgets on our desktops or phones, always available at a single glance. However, not everyone realizes the amount of sophisticated hardware and calculation that goes into bringing that information to you on a real-time basis. From weather stations to APIs, numerous systems come together to allow media outlets and software developers access to vital data that can protect your property or just save your picnic from a sudden burst of rain.