February 27, 2021

Weather News – Road Conditions – weather forecast

Paper about how a new forecast model for hurricanes performed during 2019 released online in Weather and Forecasting – Hurricane Research Division

2 min read


This paper summarizes forecasts from an experimental forecast model called the Hurricane Analysis and Forecast System (HAFS) made during the 2019 Hurricane Season. HAFS is being developed for future use as an operational hurricane model to help forecasters predict what a hurricane is going to do. HAFS forecasts the weather on a set of points called gridpoints.  The version of HAFS discussed in this paper features a nest over the Atlantic Ocean inside a version of the model that covers the entire earth (a global model).  In the global model, the gridpoints are about 3 km apart to forecast large-scale weather; In the nest, the gridpoints are close together (about 3 km apart)  to forecast small-scale details in and around the tropical cyclone. 

The version described here, called HAFS-globalnest, is compared to other forecast models.  These models forecast where the system will go (track) and how strong it will be (intensity).  It also forecasts how large the system will be, and where and how much rain will fall (structure and hazards) using NOAA Hurricane Hunter radar data.  These results from the 2019 season will provide an important basis as HAFS is developed and improved.

Important Conclusions:  

Forecasts from HAFS-globalnest showed promise in predicting tracks, with forecast performance equal to or better than other models (Fig. 1).

The superior forecasts of HAFS-globalnest relative to the operational global model in which it is embedded shows why it is important to have a nest over the tropical cyclone.

NOAA P-3 radar data provided an important tool for evaluating the forecast structure of Hurricane Dorian, Hurricane Humberto, and Hurricane Lorenzo (Fig. 2).

Check out the full study at https://journals.ametsoc.org/view/journals/wefo/aop/WAF-D-20-0044.1/WAF-D-20-0044.1.xml. For more information on this study, contact aoml.communications@noaa.gov.



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