How Do Scientists Predict Where a Hurricane Will Go?
In short: How physics, satellites, falling dropsondes and ensembles shape a hurricane track forecast, what the forecast cone really shows, and why a storm's strength is harder to predict than its path.
A 1:26 short film in the series “Invisible Atmosphere”, narrated by intellect_voice_01.
Sources used in this film: Department of Meteorology, University of Reading, “Fundamentals of Meteorology - Department of Meteorology, University of Reading”; NOAA Office of Marine and Aviation Operations (OMAO), “From Dropsondes to Minisondes: Advancing Atmospheric Research | Office of Marine and Aviation Operations”; European Centre for Medium-Range Weather Forecasts (ECMWF), “Using ECMWF ensemble forecasts for operational observation targeting”; Scientific American, “When a Hurricane Is Raging, Here’s What the Forecast Actually Means”; NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML), “Determining uncertainty: hurricane intensity forecasts - NOAA/AOML”; npj Climate and Atmospheric Science (Springer Nature); study by Chih, Wu and Huang, National Taiwan University and Academia Sinica, “Beyond a single rapid intensification threshold: a continuous intensification rate index for tropical cyclones using vortex-scale machine learning - npj Climate and Atmospheric Science”.
Sources used in this film
- Department of Meteorology, University of Reading — Fundamentals of Meteorology - Department of Meteorology, University of Reading · View →
- NOAA Office of Marine and Aviation Operations (OMAO) — From Dropsondes to Minisondes: Advancing Atmospheric Research | Office of Marine and Aviation Operations · View →
- European Centre for Medium-Range Weather Forecasts (ECMWF) — Using ECMWF ensemble forecasts for operational observation targeting · View →
- Scientific American — When a Hurricane Is Raging, Here’s What the Forecast Actually Means · View →
- NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML) — Determining uncertainty: hurricane intensity forecasts - NOAA/AOML · View →
- npj Climate and Atmospheric Science (Springer Nature); study by Chih, Wu and Huang, National Taiwan University and Academia Sinica — Beyond a single rapid intensification threshold: a continuous intensification rate index for tropical cyclones using vortex-scale machine learning - npj Climate and Atmospheric Science · View →
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Sources
- Summary by Intellect · source: Department of Meteorology, University of Reading: Fundamentals of Meteorology - Department of Meteorology, University of Reading
- Also: NOAA Office of Marine and Aviation Operations (OMAO): From Dropsondes to Minisondes: Advancing Atmospheric Research | Office of Marine and Aviation Operations
- Also: European Centre for Medium-Range Weather Forecasts (ECMWF): Using ECMWF ensemble forecasts for operational observation targeting
- Also: Scientific American: When a Hurricane Is Raging, Here’s What the Forecast Actually Means
- Also: NOAA Atlantic Oceanographic and Meteorological Laboratory (AOML): Determining uncertainty: hurricane intensity forecasts - NOAA/AOML
- Also: npj Climate and Atmospheric Science (Springer Nature); study by Chih, Wu and Huang, National Taiwan University and Acade: Beyond a single rapid intensification threshold: a continuous intensification rate index for tropical cyclones using vortex-scale machine learning - npj Climate and Atmospheric Science
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