Forecasting AI's Impact on Weather 🌞👾

How will AI improve weather forecasting?

December 28, 2023

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How will AI improve weather forecasting?

Today we delve into how artificial intelligence might enhance our ability to predict weather patterns with greater precision. Here’s what you need to know:

  • 🌩️ Smarter Predictions Ahead: AI stands poised to revolutionize weather forecasting by processing vast data sets more efficiently than traditional methods. Learning from historical weather patterns, AI can detect nuanced correlations that elude human analysis, leading to more accurate predictions. As computational power and algorithm sophistication increase, we can expect short-term weather forecasts to become highly precise, potentially down to the minute and local neighborhood.

    • Look no further than Google DeepMind's AI-powered climate forecasting program, GraphCast, which outperforms existing prediction tools and accurately predicted Hurricane Lee's trajectory well ahead of landfall and earlier than traditional approaches.

  • 🛰️ Data Deluge Decoded: The increasing number of Earth observation satellites generates a torrent of data that's overwhelming for human meteorologists. AI, however, thrives on big data, using it to continuously refine its models. In the future, AI algorithms will be key to translating this data into actionable insights, enabling timely decisions in scenarios like severe weather events and agricultural planning.

    • Data + AI in action: DHI GRAS, a Danish advisory and research organization, has already developed an AI-based solution using vast amounts of thermal and optical satellite data combined with meteorological data which aids farmers in reducing water consumption by advising them on the correct amount of water they need to use.

  • 🔮 Long-term Gets Shorter: While AI will substantially improve short-term weather forecasting, enhancing long-term forecasts is an ambitious next step. AI's ability to analyze climate patterns could lead to improved season-to-season and year-to-year predictions. Yet the unpredictable complexity that governs weather patterns may never truly be able to look too far into the future.

    • Consider a doctoral student at the Sustainability and Data Sciences Laboratory of Northeastern University, Puja Das, who is collaborating with river management and forecasting professionals with a joint aim to develop an improved method for forecasting severe rainstorms utilizing a generative AI. This research initiative is supported by a financial grant provided by NASA.

  • 🔋 Supercharged Compute Capacity Needed: While AI has the potential to revolutionize weather prediction, it requires immense computational power, raising concerns about the energy footprint of such operations. As we move forward, balancing the need for precision in forecasting with sustainable computing practices will be a significant challenge, potentially curbing the speed at which AI can be implemented on a global scale.

  • 🚧 Stormy Challenges: Despite the promise of AI, there are hurdles in its path to forecasting supremacy. Data biases, computational errors, and unexpected "black swan" events can lead to AI inaccuracies. Efforts must include rigorous model testing, validation against real-world outcomes, and development of protocols for interpreting and acting on AI-driven forecasts.

What do the experts say?

"The ability to rerun these forecasts multiple times in just a few minutes could create a radical improvement in allowing models to incorporate and adjust to incoming changing weather data. This could vastly improve forecasts over just a few hours as initial conditions change."

— Paul Huttner, from Is AI coming to a weather forecast near you? in MPR News

"One concern… is that while the prediction of extreme weather is important in a world plagued by climate change, using energy-deficient computers to generate this data could also be doing potential harm."

"It's very early days but this trial shows that AI could be a powerful tool, enabling forecasters to spend less time trawling through ever growing piles of prediction data and instead focus on better understanding the implications of their forecasts. This will be integral for mitigating the adverse effects of climate change today, supporting adaptation to changing weather patterns and potentially saving lives."

— Shakir Mohamed of Google DeepMind, from AI can predict if it will rain in two hours' time in BBC

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