How Weather Forecasting Has Become Better and More Innovative Over the Last Few Years

Weather forecasting has only gotten better over the last decade or so. Modern satellites, better software, and utilization of machine learning and AI are credited for this development. 

So, how have these technologies improved the way we monitor and assess weather conditions? Let’s find out.

Utilization of Close-to-Ground Weather Sensors

Weather forecasts don’t just depend on satellites and globally distributed radars. They also depend on systems that are much more local and closer to the ground. These include everything from cellphone towers and IoT devices to sensors located at embassies and government offices.

For instance, you’re in Winnipeg, Canada, and you open your weather app to see the latest weather forecast. The update you receive will come from the Winnipeg weather radar data. Like the progression of a storm, additional information will come from weather satellites. That way, you’ll get timely updates as they come.

Another example of this could be how weather apps utilize close-to-ground sensors. The US Embassies in different countries install air-quality monitoring systems within their compounds. The data from these sensors is used by many weather apps and websites worldwide. 

Read: Best free weather websites for accurate forecast

Better Accuracy from Weather Satellites and Imaging 

Over the years, satellite technology has improved a lot. With that, so has our capability to interpret satellite data more efficiently. The result of all this advancement in weather technology is that we’re now getting better accuracy from these satellites. 

The GOES-16 and GOES-17 satellites are currently in orbit and monitoring our weather 24×7. These satellites take high-resolution images of our atmosphere and send them back for further processing. 

The GOES-T (launched March 1) is set to revolutionize the existing GOES satellite technology by implementing even more advanced technology and imaging. That will help capture more accurate snaps of our land and oceans. It’ll also provide us with better insights regarding the weather. 

Introduction of Weather Intelligence and AI-Based Insights

Businesses have been using AI-based insights and suggestions for a while now. The most common application of this technology is seen in stock market predictions, alongside large manufacturing plants, supply chain management, and so on. The goal here is to use data and AI to predict an outcome that will help businesses or users make crucial business decisions.

For instance, the war in Ukraine has led to sanctions against Russian businesses and companies. Hence, the AI-based insights from your national stock market will tell you to avoid investing in these businesses and companies.

With sufficient present and historical data, the AI can further predict how low the prices or points will fall off these stocks and how long they might take to recover.

Weather intelligence also uses data and AI to predict outcomes and provide suggestions accordingly. 

Suppose it’s going to rain tomorrow, and you know that you have to carry an umbrella to work. However, the AI will ask you not to use an umbrella but wear a raincoat instead.

That’s because the AI knows that there will be heavy winds along with rain. So, it’ll be difficult for you to carry an umbrella, which is why the AI will recommend a raincoat instead.

In real-life, these weather-based AI algorithms are more complex. Like many other prediction and recommendation algorithms, they work with massive datasets of both present and real-time data and past or historical data.

Read: Why is my Phone Charging So Slow and How to Fix it?

Real-Time Weather Updates

Weather surveillance technology has come a long way, making real-time weather updates much more feasible. One of the many advantages of using high-resolution satellites with modern weather radars includes fewer delays in weather detection. That means you can now get instant updates even about the most sudden and unexpected changes in weather conditions. 

Modern weather satellites capture and generate images with 30-second intervals or less. Meteorologists use these images to visualize the weather better. Such technology has made it possible to track a storm’s progression and keep the respected authorities posted about it.

Weather apps have also adopted the latest technologies to facilitate better updates and communication with their users and clients. That’s why you’ll see weather apps these days that will ask you to keep your mobile data or WiFi on alongside your GPS.

In doing so, you’re enabling it to fetch the latest updates from the app servers. Your geolocation coordinates will further allow the app to retrieve weather data that is relevant and specifically relevant to you.

With time, we’ll see more development in this sector. Newer satellites, better cameras and sensors, and advanced algorithms will further revolutionize our weather forecasting capabilities.

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