DailyAI
Google unveiled NeuralGCM, a hybrid weather prediction model that combines machine learning with traditional forecasting techniques and has surprising benefits. Weather prediction has enjoyed dramatic improvements in forecast accuracy but traditional techniques require vast computing resources to run increasingly complex algorithms. General circulation models (GCMs) form the basis of the climate and weather predictions that let you know whether you’ll need an umbrella tomorrow. GCMs are physics-based simulators that use mathematical equations based on the laws of physics to simulate how air, water, and energy move around the planet. Typical GCMs divide Earth’s surface into a grid of cells up
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Google unveiled NeuralGCM, a hybrid weather prediction model that combines machine learning with traditional forecasting techniques and has surprising benefits.
Weather prediction has enjoyed dramatic improvements in forecast accuracy but traditional techniques require vast computing resources to run increasingly complex algorithms.
General circulation models (GCMs) form the basis of the climate and weather predictions that let you know whether you’ll need an umbrella tomorrow.
GCMs are physics-based simulators that use mathematical equations based on the laws of physics to simulate how air, water, and energy move around the planet.
Typical GCMs divide Earth’s surface into a grid of cells up to 100 kilometers like a giant chessboard. The algorithm processes each square in a step-wise approach to predict how the atmospheric conditions are likely to change.
The equations behind GCMs are incredibly complex and keep some of the world’s biggest supercomputers busy.
Machine learning (ML) models for weather prediction have shown significant potential but they are primarily data-driven.
An ML weather prediction model has a great idea of historical weather data but lacks the inherent understanding of the physical laws governing the atmosphere that are modeled in a GCM.
ML models are fast and can provide accurate short-term forecasts, but they often struggle with long-term stability and rare extreme weather events or future climate scenarios.
NeuralGCM developed by a team at Google Research combines the accuracy and long-term prediction capabilities of traditional GCMs with the improved resolution, efficiency, and speed of ML models.
Published: 2024-07-23T13:12:56
