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Hispanic Business TV > Business > Tech > How Vital AI Technology Could Advance Hurricane Forecasting
Tech

How Vital AI Technology Could Advance Hurricane Forecasting

HBTV
Last updated: July 6, 2024 10:34 am
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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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