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The elevated frequency and severity of maximum climate and local weather occasions may take one million lives and value $1.7 trillion yearly by 2050, in accordance with the Munich Reinsurance Company.
This underscores a important want for correct climate forecasting, particularly with the rise in extreme climate occurrences reminiscent of blizzards, hurricanes and heatwaves. AI and accelerated computing are poised to assist.
Greater than 180 climate modeling facilities make use of sturdy excessive efficiency computing (HPC) infrastructure to crunch conventional numerical climate prediction (NWP) fashions. These embody the European Heart for Medium-Vary Climate Forecasts (ECMWF), which operates on 983,040 CPU cores, and the U.Ok. Met Workplace’s supercomputer, which makes use of greater than 1.5 million CPU cores and consumes 2.7 megawatts of energy.
Rethinking HPC Design
The worldwide push towards power effectivity is urging a rethink of HPC system design. Accelerated computing, harnessing the facility of GPUs, affords a promising, energy-efficient various that accelerates computations.
NVIDIA GPUs have made a big affect on globally adopted climate fashions, together with these from ECMWF, the Max Planck Institute for Meteorology, the German Meteorological Service and the Nationwide Heart for Atmospheric Analysis.
GPUs improve efficiency as much as 24x, enhance power effectivity, and cut back prices and house necessities.
“To make dependable climate predictions and local weather projections a actuality inside energy funds limits, we depend on algorithmic enhancements and {hardware} the place NVIDIA GPUs are an alternative choice to CPUs,” stated Oliver Fuhrer, head of numerical prediction at MeteoSwiss, the Swiss nationwide workplace of meteorology and climatology.
AI Mannequin Boosts Velocity, Effectivity
NVIDIA’s AI-based weather-prediction mannequin FourCastNet affords aggressive accuracy with orders of magnitude higher velocity and power effectivity in contrast with conventional strategies. FourCastNet quickly produces week-long forecasts and permits for the era of enormous ensembles — or teams of fashions with slight variations in beginning circumstances — for high-confidence, excessive climate predictions.
For instance, based mostly on historic information, FourCastNet precisely predicted the temperatures on July 5, 2018, in Ouargla, Algeria — Africa’s hottest recorded day.
Utilizing NVIDIA GPUs, FourCastNet shortly and precisely generated 1,000 ensemble members, outpacing conventional fashions. A dozen of the members precisely predicted the excessive temperatures in Algeria based mostly on information from three weeks earlier than it occurred.
This marked the primary time the FourCastNet staff predicted a high-impact occasion weeks upfront, demonstrating AI’s potential for dependable climate forecasting with decrease power consumption than conventional climate fashions.
FourCastNet makes use of the most recent AI advances, reminiscent of transformer models, to bridge AI and physics for groundbreaking outcomes. It’s about 45,000x quicker than conventional NWP fashions. And when educated, FourCastNet consumes 12,000x much less power to provide a forecast than the Europe-based Built-in Forecast System, a gold-standard NWP mannequin.
“NVIDIA FourCastNet opens the door to the usage of AI for all kinds of functions that can change the form of the NWP enterprise,” stated Bjorn Stevens, director of the Max Planck Institute for Meteorology.
Increasing What’s Attainable
In an NVIDIA GTC session, Stevens described what’s doable now with the ICON local weather analysis software. The Levante supercomputer, utilizing 3,200 CPUs, can simulate 10 days of climate in 24 hours, Stevens stated. In distinction, the JUWELS Booster supercomputer, utilizing 1,200 NVIDIA A100 Tensor Core GPUs, can run 50 simulated days in the identical period of time.
Scientists wish to research local weather results 300 years into the long run, which implies methods have to be 20x quicker, Stevens added. Embracing quicker expertise like NVIDIA H100 Tensor Core GPUs and less complicated code may get us there, he stated.
Researchers now face the problem of placing the optimum stability between bodily modeling and machine studying to provide quicker, extra correct local weather forecasts. A ECMWF blog revealed final month describes this hybrid method, which depends on machine studying for preliminary predictions and bodily fashions for information era, verification and system refinement.
Such an integration — delivered with accelerated computing — may result in important developments in climate forecasting and local weather science, ushering in a brand new period of environment friendly, dependable and energy-conscious predictions.
Study extra about how accelerated computing and AI increase local weather science via these sources:
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