How Vital AI Technology Could Advance Hurricane Forecasting

With the National Oceanic and Atmospheric Administration (NOAA) having predicted an ‘above-normal’ Atlantic hurricane season for 2024, greater awareness is being placed on continually improving forecasting technology. 

A significant example of an ‘above-normal’ hurricane is the recent Hurricane Beryl, which has significantly impacted the Caribbean and Central America in July 2024 and is on course to threaten more countries as it continues to progress as a storm.

More storms like Beryl are being forecast, with the BBC suggesting that the frequency of category 4 and 5 hurricanes is likely to increase. In line with this, NOAA has predicted an 85% chance of an above-normal hurricane season, with reasons cited being rising ocean temperatures and other impacts of climate change. 

A major driver of warming oceans worldwide, climate change is leading to an increase in abnormal storms.

With this in mind, Technology Magazine examines some of the new technologies that hurricane centres are using to track these storms and how they can be developed in the future to mitigate threats to life.

Leveraging disruptive technologies to help with weather reporting

The hurricane season runs from June until November, with most activity occurring between August and October. Typically, forecasters will use a range of technology-based tools to anticipate when and where a hurricane will emerge and if it will cause land damage.

During hurricane season, national hurricane centres will be monitoring weather events and tracking hurricanes with aircraft, satellites, drones and unmanned aerial vehicles (UAVs). Now, forecasters are starting to use artificial intelligence (AI) and other disruptive technologies to better analyse and project tropical storms.

As climate change leads to increasingly extreme weather conditions, the advancement of AI, 5G predictions and the Internet of Things (IoT) are being leveraged to analyse big data from current sensors, in addition to previous hurricanes, to generate faster and more accurate predictions. Gaining more data means more results, which can work to help areas remain as safe as possible. 

Moving forward, ensuring that this data remains as clear as possible is vital to keep people informed. A deeper understanding leads to better preparedness. As discussed in the above video, big tech companies like Nvidia, Huawei and Google DeepMind which have successfully forecasted weather accurately.

Similarly, in 2023, Google Research partnered with American Airlines to use AI to develop contrail forecast maps to test if pilots can avoid creating contrails and thereby lessen their environmental impact.

Can climate change be combated with technology?

With their computing knowledge, technology companies could help national institutions to accurately predict and forecast natural disasters. In fact, edge computing advances by these companies too can help with processing the data from these technologies, enabling researchers and scientists to gain greater insights from their analysis.

“AI meteorology allows us to achieve a new standard of accuracy and detail and performance,” comments Alex Levy, co-founder and CEO of Atmo.

Digital transformation could be set to continue in this sector. According to the IEEE, researchers are also investigating if digital twins could be used for hurricane prediction. This could be developed by using a combination of data from ground sensors and aerial imagery, with digital models of geographical areas being formed and updated in real time.

Technology at this level could not only help monitor current weather conditions, but also run simulations based on past storms to collect more information to use in future predictions.

Strategies like this could become more necessary as climate change continues to cause greater impact, if weather is to become increasingly volatile. As storms rapidly change and become more abnormal, the conditions that past forecasting models were based on no longer apply. This makes predictions more difficult, leading to organisations intensifying their focus on data analysis to hopefully improve forecasting moving forward.

As these areas are reshaped, it will be interesting to see how the role of technology will play its part.

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