AI Helps the Meteorological Industry

Artificial intelligence is a valuable partner to the meteorological industry. If in the past, meteorologists analyzed massive amounts of data to make weather predictions and thus were prone to errors and false warnings, today, AI has improved weather forecasting and added a boost of accuracy to meteorological predictions.

While many focus on weather forecasting as a way to decide on what clothes to wear the next day and what to do on the weekends, industries, like agriculture, farming, and even aviation rely on predictions for informed decisions regarding their business. Artificial intelligence has introduced the digital transformation that will help industries improve their activity and plan accordingly.

AI is already an important tool in meteorological predictions

Meteorologists have been working with AI models since the 80s. Artificial intelligence is used to analyze both the weather and climate, applying technology to satellite data processing. AI systems process massive loads of data to discover a pattern and create accurate forecasts. The data is collected with the help of deep space satellites, weather balloons, nowcasting weather warnings, as well as radars and environment analytics.

The traditional methods of weather forecasting work with statistical measures of numeric models. Thus, they will not provide binary answers. Consequently, these data needed to be analyzed by meteorologists to identify the patterns and release predictions. The amount of data received by meteorologists keeps increasing while the atmospheric conditions are changing rapidly. This is where AI can help!

Artificial intelligence tools can reduce the workload of meteorologists and improve the accuracy of weather forecasting. High-performance computers can go through massive amounts of data and deliver more accurate and further-reaching forecasts. Thus, weather forecasting will no longer be limited to a nearby future but would be able to extend to even the next 100 years. Moreover, due to AI tools, extreme events will be predicted long before they are bound to happen for people to take shelter and governments to be able to evacuate settlements affected by tornadoes and hurricanes.

AI provides accuracy in an ever-changing climate

The artificial intelligence system used for weather forecasting uses mathematical problems and computational problem-solving methods to process the colossal amounts of data received from satellites. Combined with machine learning and deep learning, AI systems can recognize patterns. Based on these patterns, supercomputers can predict the weather and help humanity save time and money.

AI-based weather forecasting now includes temperature, wave height, and precipitation. Based on weather satellites and relay stations, AI tools deliver short-term weather forecasts. However, artificial intelligence algorithms are also able to create long-term climate predictions. Until now, scientists have delivered climate change predictions as an average of various results of climate alteration predictions. However, considering how fast the climate is changing, we need more than just average forecasts. We need accuracy!

Climate predictions are imperiously necessary for our future. AI helps evaluate the models used for the calculation of climate change to deliver more accurate results. With better climate change predictions, governments will be able to plan better their policies and make real changes in real time for better odds to avoid extreme weather events and protect our planet.

Some of the AI techniques used by the meteorological industry are the Numeral Weather Prediction, Artificial Neural Network, Radial Basis Function Network, and Ensemble Neural Network. However, scientists work tirelessly to come up with new models and algorithms for improved meteorological predictions.

Scientists at the U.S. National Center for Atmospheric Research (NCAR) are working on a model to forecast hail based on factors like temperatures at different altitudes, wind direction and speed, as well as humidity and updraft. Meanwhile, researchers at École Polytechnique Fédérale de Lausanne, Switzerland, have already created a system that can predict lightning strikes inside a radius of 18.6 miles and with an advance of 10 to 30 minutes before their occurrence. Artificial intelligence plays a vital role in the meteorological industry. If today AI is used for weather forecasting to help agriculture and farming and contribute to efficient disaster management, tomorrow it might very well help us detect storm centers and predict pest seasons.