How accurate are weather forecasts beyond 48 hours in many parts of the world despite supercomputers, large computer models, satellites etc.?
How much of an improvement of weather forecasting will machine learning & AI make? Fact is that the science of weather and climate are still full of unknowns! Climate/Weather are very complex natural phenomena.
"It’s a truism almost as old as modern weather prediction: Any forecast beyond 2 weeks will fall apart because of the way tiny perturbations compound in the atmosphere. The 2-week limit, grounded in chaos theory and notions of the “butterfly effect” from the 1960s, has been handed down from generation to generation, says Peter Dueben, head of earth system modeling at the European Centre for Medium-Range Weather Forecasts, the world’s leading forecaster. “It’s basically a God-given rule.”
But even the gods can be wrong.
Using an artificial intelligence (AI) weather model developed by Google, atmospheric scientists have found that forecasts of 1 month or more into the future might be possible. “We haven’t found a limit to how far you can go out,” says Trent Vonich, a doctoral student at the University of Washington (UW) who led the work, released late last month as a preprint on arXiv. “We ran out of memory first.” ..."
From the abstract:
"Atmospheric predictability research has long held that the limit of skillful deterministic weather forecasts is about 14 days. We challenge this limit using GraphCast, a machine-learning weather model, by optimizing forecast initial conditions using gradient-based techniques for twice-daily forecasts spanning 2020. This approach yields an average error reduction of 86% at 10 days, with skill lasting beyond 30 days. Mean optimal initial-condition perturbations reveal large-scale, spatially coherent corrections to ERA5, primarily reflecting an intensification of the Hadley circulation.
Forecasts using GraphCast-optimal initial conditions in the Pangu-Weather model achieve a 21% error reduction, peaking at 4 days, indicating that analysis corrections reflect a combination of both model bias and a reduction in analysis error. These results demonstrate that, given accurate initial conditions, skillful deterministic forecasts are consistently achievable far beyond two weeks, challenging long-standing assumptions about the limits of atmospheric predictability."
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