Tucson Standard

The University of Arizona's hurricane forecasting team has predicted an especially active hurricane season for 2024. The team, led by Professor Xubin Zeng from the Department of Hydrology and Atmospheric Sciences, forecasts five major hurricanes and 21 named storms over the North Atlantic basin. This area includes the Gulf of Mexico and the East Coast but excludes the eastern Pacific.

Last year's hurricane season was influenced by El Niño, which leads to higher sea surface temperatures in the eastern Pacific. In contrast, this year is expected to experience a La Niña climate pattern, characterized by cooler sea surface temperatures in the same region. Although La Niña occurs in the Pacific, it can still impact weather patterns in the Atlantic Ocean by weakening upper-level winds, thereby favoring stronger hurricanes.

Zeng's team anticipates that among these hurricanes, five could reach Category 3 or higher on the Saffir-Simpson scale. Such storms are marked by wind speeds exceeding 157 mph and can cause significant damage and loss of life. Additionally, six Category 1 or 2 hurricanes are predicted, bringing the total number of hurricanes to 11—well above the historical average of seven per year. The prediction also includes 21 tropical storms compared to a historical average of 14.

With a potentially severe hurricane season ahead, Zeng advises government agencies to prepare for emergency management efforts. He also cautions potential home buyers against purchasing properties near the Atlantic coast due to increased risks associated with hurricane activity.

"You need to rethink in terms of the risks associated with the quality of the property after it gets affected by hurricane activities," Zeng stated. "The risks could emerge in the long run if not immediately."

The UArizona forecasting model has been operational since 2014 and is recognized as one of America's most accurate models for predicting hurricanes. Each April, Zeng's group makes forecasts using data from seasonal predictions provided by Europe's Center for Medium-Range Weather Forecasts and processes this information through machine learning tools.

These predictions will be updated again in June when forecasters incorporate observational data collected from March through May into their model output.

"We have done amazingly well for our April prediction in past years," noted Zeng about their forecasting success.