José Luís Sánchez (ULE) — Weather forecast for scheduling operations in sectors heavily impacted by adverse conditions (FScheduler)
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Check this Success Story at our LinkedIn: Weather forecast for scheduling operations in sectors heavily impacted by adverse conditions (FScheduler)
💡A story about weather forecasting for businesses' operations scheduling💡
📋"Weather forecast for scheduling operations in sectors heavily impacted by adverse conditions (FScheduler)" led by J.L Sánchez from Universidad de León
Many businesses' performance heavily depend on an effective scheduling of their personnel and equipment across distant locations. But the feasibility of such scheduling in highly sensitive operations can be directly conditioned by weather adverse conditions. That is the case for drone flights or energy generation, and weather conditions can be very different depending on the operating altitude. But extending the forecasting to different altitudes in a wide geographical area (like a whole country) becomes a challenge, as prediction models accurate in one area are not necessarily accurate in another, at least at the business operation level.
🖥️ Thanks to RES supercomputer #MareNostrum5 at Barcelona Supercomputing Center, the team run, simultaneously, 20 prediction models over peninsular Spain and carried the full model selection process with a time-saving of 2-6 years with alternative computing methods. They identified 8 weather forecasting models that can fully cover peninsular Spain with enough accuracy to satisfy empresarial needs of businesses sensible to adverse weather conditions.
📸 The image shows wind speed forecast at multiple altitudes (10 to 125 m) over a 3-day period (July 5–7, 2025), showing how conditions heavily vary with height.
📋"Weather forecast for scheduling operations in sectors heavily impacted by adverse conditions (FScheduler)" led by J.L Sánchez from Universidad de León
Many businesses' performance heavily depend on an effective scheduling of their personnel and equipment across distant locations. But the feasibility of such scheduling in highly sensitive operations can be directly conditioned by weather adverse conditions. That is the case for drone flights or energy generation, and weather conditions can be very different depending on the operating altitude. But extending the forecasting to different altitudes in a wide geographical area (like a whole country) becomes a challenge, as prediction models accurate in one area are not necessarily accurate in another, at least at the business operation level.
🖥️ Thanks to RES supercomputer #MareNostrum5 at Barcelona Supercomputing Center, the team run, simultaneously, 20 prediction models over peninsular Spain and carried the full model selection process with a time-saving of 2-6 years with alternative computing methods. They identified 8 weather forecasting models that can fully cover peninsular Spain with enough accuracy to satisfy empresarial needs of businesses sensible to adverse weather conditions.
📸 The image shows wind speed forecast at multiple altitudes (10 to 125 m) over a 3-day period (July 5–7, 2025), showing how conditions heavily vary with height.