The incorporation of AI technology will significantly enhance the accuracy of weather forecasting.

FREMONT, CA: The rapid development of modern technology has taken weather forecasting a long way, bringing it closer than ever toward accurate science. Furthermore, the emergence of artificial intelligence (AI) companies and machine learning (ML) applications has given new opportunities for innovators, inspiring them to assess their potential of the latest technologies in predicting future weather patterns.

Weather forecasting is a sophisticated process and requires the decoding of massive datasets gathered from thousands of sources, including sensors and weather satellites. Manually identifying the patterns in the data sets to draw predictive insights is a complicated task, which requires extensive time and effort.

The conventional weather forecasting process can be compared to making an educated guess. Meteorologists leverage past and current data to track patterns and predict weather conditions. Although the accuracy of weather forecasts has increased with the incorporation of modern technology, it has not reached the 100 percent mark.

The shorter timescale forecasts offer accuracy of about 90 percent, whereas, anything longer than ten days cannot provide an accuracy of more than 50 percent. Since the atmosphere continuously changes over time, it is almost impossible to predict the weather over more extended periods.

Meteorologists utilize various sensors, satellites, and computer models to predict weather patterns. Radar systems are also leveraged for the measurement of precipitation around the world. The national oceanic and atmospheric administration (NOAA), which operates three types of environmental satellites, also plays a crucial role in monitoring the weather.

The enormous datasets gathered by the satellites comprise data regarding the atmosphere, including clouds and oceans. The massive information is incorporated into the weather models, which help meteorologists in making more accurate weather forecasts.  The weather models need to integrate various factors, including the effect of the sun on the atmosphere, the pressure difference, and the change in phases of water.

The incorporation of AI can significantly enhance the accuracy and reliability of weather forecasting. It can be used to streamline the processing of vast datasets to identify patterns and make a relevant hypothesis. AI-based models can produce more refined and precise results when compared to the conventional methods, and at a fraction of the speed.

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