{"slug":"israel-s-meteorological-service-predicts-the-weather-using-nvidia-earth-2","url":"https://findausecase.com/use-cases/israel-s-meteorological-service-predicts-the-weather-using-nvidia-earth-2","title":"Israel's Meteorological Service Predicts the Weather Using NVIDIA Earth-2","description":"The Israel Meteorological Service integrated an AI weather model called F3, powered by NVIDIA Earth-2 and NVIDIA PhysicsNeMo (including the CorrDiff neural network), into its forecasting system to achieve hyperlocal 2.5-kilometer resolution precipitation forecasts. F3 achieved 90 percent lower computational costs compared to running a classic non-AI numerical weather prediction model on a CPU cluster, delivering forecasts in minutes rather than hours, and saved 20-30 percent of the Tel Aviv-Yafo Municipality's preparedness budget for things like urban flood safety. CorrDiff was trained to emulate IMS's regional high-resolution ICON model using low-resolution ECMWF IFS input, enabling four high-resolution forecasts per day. Partners including the Israeli Police, the National Fire and Rescue Authority, the Ministry of Transportation and the National Road Company have adopted the forecasts, and IMS used F3 to issue a high-resolution flood map during a January storm that dropped 150 millimeters of rain in six hours.","company":"Israel Meteorological Service (IMS)","industry":"Government & Public Sector","country":"Israel","aiCapabilities":["Predictive Analytics","Digital Twins & Simulation"],"technology":["NVIDIA Earth-2","NVIDIA PhysicsNeMo","CorrDiff"],"deployment":"On-Premise","problemStatement":"IMS is located in a Mediterranean climate zone with diverse weather patterns, from intense flooding to fire seasons; as the climate continues to change, predicting the weather is becoming increasingly difficult. Traditional, non-AI weather models typically take hours to run using large supercomputing clusters and require a huge amount of compute time to generate predictions.","solutionApproach":"IMS integrated an AI weather model called F3, powered by NVIDIA Earth-2 and NVIDIA PhysicsNeMo (including the CorrDiff Corrector Diffusion neural network), into its forecasting system. CorrDiff was trained to emulate IMS's regional high-resolution ICON model using low-resolution ECMWF IFS input, enabling four high-resolution forecasts per day at hyperlocal 2.5-kilometer resolution. With Earth-2's open source software and open science models, IMS built a full stack across hardware and software that it runs as a sovereign capability.","businessValue":"F3 achieved 90 percent lower computational costs compared to running a classic non-AI numerical weather prediction model on a CPU cluster, delivering forecasts in minutes rather than hours, and saved 20-30 percent of the Tel Aviv-Yafo Municipality's preparedness budget for things like urban flood safety. Partners including the Israeli Police, the National Fire and Rescue Authority, the Ministry of Transportation and the National Road Company have adopted the forecasts. IMS used F3 to issue a high-resolution flood map during a January storm that dropped 150 millimeters of rain in six hours, giving government agencies the ability to shut down roads and avoid casualties.","evidence":{"band":"high"},"sourceUrl":"https://www.nvidia.com/en-us/case-studies/israel-meteorological-service","dates":{"publishedAt":"2026-08-16T00:04:06.052Z","publishedAtSource":"ledger","updatedAt":"2026-08-26T03:55:40.827Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/israel-s-meteorological-service-predicts-the-weather-using-nvidia-earth-2. Bulk republication requires permission."}