There’s no question that weather prediction and forecasting is an essential science. In some regions, alerting people to potentially dangerous events can mean the difference between life and death.

Although weather forecasting is nothing new, recent technological advances have improved the accuracy of predicting future events. Artificial intelligence (AI) and machine learning (ML) are becoming more widely used in all aspects of life, so it’s no surprise that it also has a place in meteorology.

Here’s more about AI and ML in meteorology and their role in predicting weather more accurately.

Understanding the Importance of AI/ML in Meteorology

Today’s weather forecasts are formulated from some of the most powerful machines in the world. These computers sort through millions of calculations, solve equations and make predictions.

According to the National Oceanic and Atmospheric Administration (NOAA), numerical weather prediction models (NWPs) are often used for forecasting. NWPs are essential in weather prediction and rely heavily on current observations and factors such as temperature, precipitation and hundreds of other variables.

However, AI and ML are expected to revolutionize meteorology, as these models are essentially a next-generation version of NWPs. AI and ML models are more advanced than NWPs, as they have more features and capabilities.

AI and ML will play an increasingly important role in weather prediction, especially due to the climate change crisis. Today, various regions are experiencing several indicators of climate change, including:

  • Melting glaciers
  • Rising sea levels
  • Warmer atmospheric and oceanic temperatures
  • Ocean acidification
  • Extreme climate events
  • Changes in birthing times for animal species

Without using AI and ML models, weather experts might find it more challenging to accurately predict weather changes due to climate change. If the task of formulating predictions is inefficient or predictions are inaccurate, it could lead to loss of life.

In 2019, a set of devastating storms tore through Texas for one week. They wreaked havoc on the area – property damage totaled tens of millions of dollars, and historic flooding caught people off-guard. Unfortunately, the storms caused the deaths of three people.

Although AI and ML technologies cannot prevent instances of extreme weather, these models can create faster, more accurate predictions to alert people residing in the areas so they can evacuate more quickly. Speed and accuracy are two essential components of forecasting, and AI and ML are well-suited to improve both factors.

How AI/ML Improve Weather Forecasting Accuracy

There are a few highly anticipated benefits of AI and ML models for weather predictions, but improved accuracy is one of the most prominent. Forecasting is complex, so it’s understandable that achieving accuracy in modern weather prediction is still difficult.

One benefit of leveraging AI/ML capabilities to improve the accuracy of predictions is the use of historical data. A core component of ML is the ability of a model to train with past information to predict future outcomes. Isn’t that a core principle of weather forecasting? An ML model is perfectly suited to predict future weather events.

Recently, a collaboration between the University of Washington (UW) and Microsoft Research focused on building a simple AI model to generate accurate predictions as efficiently as possible. The goal is to analyze 40 years of weather data and examine current patterns to create accurate forecasts.

The research team on this project combined simple, AI-driven techniques with current weather forecasting tools. It also used WeatherBench, a test to assess data-driven forecasts, which was deemed one of the best.

The Future of AI/ML in Weather Prediction

The ultimate goal of any forecaster is to predict future events with complete accuracy. Unfortunately, weather can be highly unpredictable, particularly when climate change is causing significant alterations in weather patterns.

AI and ML models will become increasingly popular in meteorology as time goes on. Soon, these advanced pieces of technology will become indispensable tools for anyone studying weather prediction and forecasting.

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