Predicting hurricane trajectories with multi-source meteorological data

Hurricanes, typhoons, and other tropical storms can be devastating for coastal communities. Forecasting the trajectories of these storms is crucial for alerting endangered regions as early as possible, to minimize damage and loss of life.

Feng and Xu developed a new model to predict the paths of hurricanes and typhoons, testing it on 57 historical storms in the North Atlantic.

Many current storm models use previous typhoon track data to estimate the trajectory of a typhoon track center. This approach fails to consider the impact of changing meteorological data. In contrast, the authors developed an inversion model informed by multiple sources of ocean forecasting data, such as wind fields, wave fields, and atmospheric pressure to iteratively predict the location of the typhoon center.

“The model extends outward from the current typhoon track center, creating a grid within a fixed range of latitudes and longitudes, and populates it with future ocean environmental information to effectively identify the next center point of the trajectory,” said author Hang Xu.

In their tests, the team’s model showed total error ranges of 76 km for 24-hour forecasts and 188 km for 48-hour forecasts. This is a 6.3% reduction in error for 24-hour forecasts and a 33.3% reduction for 48-hour forecasts, compared with existing models.

“This accuracy is vital for timely warnings to coastal communities and maritime operations, facilitating better planning for evacuations, infrastructure reinforcement, and resource allocation,” said Xu.

The authors plan to continue to refine their model to improve its accuracy, incorporating wind speed information from multiple pressure layers and inputting data from additional ocean regions.

Source: “Typhoon track tracking and forecasting algorithm based on multi-source information,” by Xiao-Chen Feng and Hang Xu, Physics of Fluids (2025). The article can be accessed at https://doi.org/10.1063/5.0253675 .