Derek Brockway, a veteran weather presenter for the BBC, poses a vital question transcending his personal experience: could artificial intelligence (AI) endanger jobs in meteorology? Weather forecasting has long been a cornerstone of daily life, influencing decisions from commuting to crop management. As climate change intensifies, so too does the need for reliable weather predictions. Brockway, who has dedicated nearly 30 years to this craft, acknowledges the increasing sophistication of forecasting technology. He notes that scientists are actively exploring how AI can enhance prediction methods, making them faster, more efficient, and more localized.

The Met Office has taken a significant step in this direction by collaborating with experts from the Alan Turing Institute to develop cutting-edge forecasting systems powered by AI. One such model, FastNet, employs machine learning techniques to refine predictive capabilities. Professor Kirstine Dale, Chief AI Officer at the Met Office, describes AI’s speed as transformative, capable of generating up-to-date forecasts with considerably lower computational and environmental costs. Hyper-local forecasts, tailored to specific postcodes, stand to provide users with critical information, potentially helping mitigate the impacts of severe weather events like storms, floods, and heatwaves.

However, challenges persist, particularly in forecasting rare and extreme weather scenarios. Professor Dale emphasizes the enduring importance of traditional numerical weather prediction (NWP) models, stating that they are essential for understanding the changing dynamics of the climate and generating reliable datasets for AI model training. Dr. Scott Hosking, from the Turing Institute, acknowledges that while AI has demonstrated strengths—particularly in forecasting cyclone tracks—it still struggles with phenomena like high-intensity rainfall, which can lead to flash floods.

While Brockway apprehensively considers the implications of AI for his role, those in the industry urge that human expertise remains invaluable. For instance, Rohit Agarwal, CEO of the Weather Company, asserts that AI must complement human judgment rather than replace it. He describes the collaboration of AI models and human forecasters as a unique synergy that enhances predictive precision. This perspective aligns with findings that AI has improved forecasting capabilities globally, as seen in September 2024, when AI successfully predicted intense rainfall in Europe. Yet, disastrous floods underscored that advanced technology alone cannot eliminate risk; effective communication and preparation are key.

Broader applications of AI in meteorology are becoming evident. The emergence of models like Aardvark Weather has highlighted the potential for AI to provide energy-efficient predictions quickly and with less data reliance than traditional supercomputers. With significant investment from tech companies, the capabilities of AI are expanding, offering the promise of timely, tailored forecasts for diverse sectors, including agriculture and renewable energy production.

Despite this progress, experts caution against an overreliance on AI. As Dr. Huw Morgan from Aberystwyth University indicates, space weather remains a complex domain, necessitating both traditional methods and AI enhancements for robust forecasting. The implications of AI stretch beyond meteorology, influencing approaches to climate change and public safety across various industries.

While the integration of AI into weather forecasting is undeniably transformative, the consensus remains clear: forecasts will likely continue to rely on a collaborative model, marrying human expertise with advanced technology. Embracing this combined future may provide forecasters like Brockway reassurance amid concerns about job security. As one expert aptly noted, “No one wants an AI Derek,” recognising the value of human connection and insight in an increasingly automated world.

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Source: Noah Wire Services