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There’s a ‘ghost hurricane’ in the forecast. It could help predict a real one анальный секс зрелых A scary-looking weather forecast showing a hurricane hitting the Gulf Coast in the second half of June swirled around social media this week—but don’t panic. It’s the season’s first “ghost hurricane.” Similar hype plays out every hurricane season especially at the beginning: A cherry-picked worst-case-scenario model run goes viral but more often than not will never come to fruition. Unofficially dubbed “ghost storms” or “ghost hurricanes” these tropical systems regularly appear in weather models — computer simulations that help meteorologists forecast future conditions — but never seem to manifest in real life. The model responsible this week was the Global Forecast System also known as the GFS or American model run by the National Oceanic and Atmospheric Administration. It’s one of many used by forecasters around the world. All models have known biases or “quirks” where they tend to overpredict or underpredict certain things. The GFS is known to overpredict tropical storms and hurricanes in longer-term forecasts that look more than a week into the future which leads to these false alarms. The GFS isn’t alone in this — all models struggle to accurately predict tropical activity that far in advance — but it is notorious for doing so. For example the GFS could spit out a prediction for a US hurricane landfall about 10 days from now only to have that chance completely disappear as the forecast date draws closer. This can occur at any time of the year but is most frequent during hurricane season — June through November. It’s exactly what’s been happening over the past week as forecasters keep an eye out for the first storm of the 2025 Atlantic hurricane season. Why so many ghosts? No weather forecast model is designed in the exact same way as another and that’s why each can generate different results with similar data. The reason the GFS has more false alarms when looking more than a week out than similar models – like Europe’s ECMWF Canada’s CMC or the United Kingdom’s UKM – is because that’s exactly what it’s programmed to do according to Alicia Bentley the global verification project lead of NOAA’s Environmental Modeling Center. The GFS was built with a “weak parameterized cumulus convection scheme” according to Bentley. In plain language that means when the GFS thinks there could be thunderstorms developing in an area where tropical systems are possible – over the oceans – it’s more likely to jump to the conclusion that something tropical will develop than to ignore it. Other models aren’t built to be quite as sensitive to this phenomenon and so they don’t show a tropical system until they’re more confident the right conditions are in place which usually happens when the forecast gets closer in time. The western Caribbean Sea is one of the GFS’ favorite places to predict a ghost storm. That’s because of the Central American gyre: a large disorganized area of showers and thunderstorms that rotates over the region and its surrounding water.
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There’s a ‘ghost hurricane’ in the forecast. It could help predict a real one анальный секс зрелых A scary-looking weather forecast showing a hurricane hitting the Gulf Coast in the second half of June swirled around social media this week—but don’t panic. It’s the season’s first “ghost hurricane.” Similar hype plays out every hurricane season especially at the beginning: A cherry-picked worst-case-scenario model run goes viral but more often than not will never come to fruition. Unofficially dubbed “ghost storms” or “ghost hurricanes” these tropical systems regularly appear in weather models — computer simulations that help meteorologists forecast future conditions — but never seem to manifest in real life. The model responsible this week was the Global Forecast System also known as the GFS or American model run by the National Oceanic and Atmospheric Administration. It’s one of many used by forecasters around the world. All models have known biases or “quirks” where they tend to overpredict or underpredict certain things. The GFS is known to overpredict tropical storms and hurricanes in longer-term forecasts that look more than a week into the future which leads to these false alarms. The GFS isn’t alone in this — all models struggle to accurately predict tropical activity that far in advance — but it is notorious for doing so. For example the GFS could spit out a prediction for a US hurricane landfall about 10 days from now only to have that chance completely disappear as the forecast date draws closer. This can occur at any time of the year but is most frequent during hurricane season — June through November. It’s exactly what’s been happening over the past week as forecasters keep an eye out for the first storm of the 2025 Atlantic hurricane season. Why so many ghosts? No weather forecast model is designed in the exact same way as another and that’s why each can generate different results with similar data. The reason the GFS has more false alarms when looking more than a week out than similar models – like Europe’s ECMWF Canada’s CMC or the United Kingdom’s UKM – is because that’s exactly what it’s programmed to do according to Alicia Bentley the global verification project lead of NOAA’s Environmental Modeling Center. The GFS was built with a “weak parameterized cumulus convection scheme” according to Bentley. In plain language that means when the GFS thinks there could be thunderstorms developing in an area where tropical systems are possible – over the oceans – it’s more likely to jump to the conclusion that something tropical will develop than to ignore it. Other models aren’t built to be quite as sensitive to this phenomenon and so they don’t show a tropical system until they’re more confident the right conditions are in place which usually happens when the forecast gets closer in time. The western Caribbean Sea is one of the GFS’ favorite places to predict a ghost storm. That’s because of the Central American gyre: a large disorganized area of showers and thunderstorms that rotates over the region and its surrounding water.
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