The relentless pace of climate extremes is demanding a rethinking of traditional norms. From catastrophic floods in Australia’s eastern regions to scorching droughts in the south, these anomalies are no longer the exception but increasingly common.
Our reliance on 30-year averages to determine climate conditions is being challenged by the rapid onset of these “flash” events. Machine learning offers a solution by analyzing complex data to pinpoint the drivers of these changes. Recent research shows that factors such as the El Niño-Southern Oscillation, the Southern Annular Mode, and the Indian Ocean Dipole, combined with rising global temperatures, significantly influence extreme weather events.
This innovative approach could help redefine what is “normal” for specific regions, enabling more accurate forecasts and better preparedness. As global warming accelerates, understanding these changes is vital to mitigating its impacts.
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