Advancements in Hurricane Prediction With NOAA's Next‐Generation Forecast System
Geophysical Research Letters(2019)
摘要
We use the fvGFS model developed at the Geophysical Fluid Dynamics Laboratory to demonstrate the potential of the upcoming United States Next-Generation Global Prediction System for hurricane prediction. The fvGFS retrospective forecasts initialized with the European Centre for Medium-Range Weather Forecasts (ECMWF) data showed much-improved track forecasts for the 2017 Atlantic hurricane season compared to the best-performing ECMWF operational model. The fvGFS greatly improved the ECMWF's poor track forecast for Hurricane Maria (2017). For Hurricane Irma (2017), a well-predicted case by the ECMWF model, the fvGFS produced even lower five-day track forecast errors. The fvGFS also showed better intensity prediction than both the United States and the ECMWF operational models, indicating the robustness of its numerical algorithms. Plain Language Summary When using European Centre for Medium-Range Weather Forecasts initial conditions, a new global weather model built at NOAA's Geophysical Fluid Dynamics Laboratory produces better hurricane forecast skill than the world-leading European model.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络