Better
method for forecasting hurricane season
University of Arizona, Science
Daily
A better method for predicting the number of hurricanes in an
upcoming season has been developed by a team of University of Arizona
atmospheric scientists.
The UA team's new model improves the accuracy of seasonal
hurricane forecasts for the North Atlantic and the Gulf of Mexico by 23
percent. The team's research paper was published online in the journal Weather
and Forecasting on March 25.
Hurricanes are storms with maximum wind speeds in excess of 73
mph and are among the most damaging natural disasters in the U.S. The Atlantic
hurricane season lasts from June 1 to Nov. 30.
The UA model can provide its forecast by the start of hurricane
season, which allows people to prepare better for the upcoming season, Davis
said. "Tens of millions of people are threatened by Atlantic hurricanes.
It affects their properties, it affects their lives."
The team developed the new model by using data from the 1950 to
2013 hurricane seasons. They tested the new model by seeing if it could
"hindcast" the number of hurricanes that occurred each season from
1900 to 1949.
"It performed really well in the period from 1949 to
1900," Davis said. "That's the most convincing test of our
model."
Other investigators have estimated that damages from U.S.
hurricanes from 1970 to 2002 cost $57 billion in 2015 dollars -- more than
earthquakes and human-caused disasters combined for the time period.
Better seasonal predictions can help cities and governments in
emergency management planning, said co-author Xubin Zeng, who holds the Agnese
N. Haury Chair in Environment and is a UA professor of atmospheric sciences.
The paper, "A new statistical model to predict seasonal
North Atlantic hurricane activity," by Davis, Zeng and Elizabeth A.
Ritchie, a UA atmospheric sciences professor, is scheduled for print
publication in a future issue of the journal of Weather and Forecasting.
Science Foundation Arizona, the National Science Foundation and NASA funded the
research.
Good forecasts of hurricane seasons have been around only since
the early 1980s, Zeng said. The historical average in the 20th century was six
hurricanes per year.
Until about the late 1990s, the existing models did a good job
of predicting how many hurricanes would occur each year. However, in the 21st
century the number of hurricanes per season became more variable, with 15
occurring in 2005 but only two in 2013.
Zeng wondered why the computer models didn't work well anymore,
and his new graduate student Davis, an actuary, wanted to study natural
disasters because of their impact.
"Xubin steered me into hurricane forecasting," Davis
said.
Zeng challenged Davis to develop a hurricane forecasting model
that surpassed the existing ones.
"It was a tremendous effort -- trying endless combinations
of things, new creative ways of doing things," Davis said.
The other forecasting models relied heavily on the state of the
El Niño climate cycle, a three-to-seven-year cycle that affects weather all
over the globe.
One of the UA team's innovations was using the state of a
longer-term climate cycle called the Atlantic Multidecadal Oscillation to judge
how much influence El Niño has in a particular year.
The AMO affects ocean temperatures, cycling from colder to
warmer and back over a time scale of approximately 40-70 years. The AMO was in
a warm phase from the late 1920s to the early 1960s and started cycling back
toward warm in the late 1990s. Warmer sea surface temperatures generally
generate more hurricanes.
Zeng suggested also including the force of the wind on the ocean
-- an innovation that, to the best of the team's knowledge, no other
statistical model used. Strong winds reduce sea surface temperatures because
they mix the ocean layers, thereby bringing cooler, deeper water to the
surface.
After much trial and error, Davis met Zeng's challenge. The
model Davis developed does a better job of forecasting the Atlantic hurricane
season by incorporating the force of the wind on the ocean and the sea surface
temperature over the Atlantic. The model includes the effect of El Niño only
for years when the AMO is in the cool phase.
Compared with the other models, the UA model de-emphasized the
role of El Niño when the AMO is in the warm phase, as it has been for the past
15 years.
Next the team plans to examine the forecasting models for the
eastern Pacific hurricanes -- the ones that hit Baja California and the western
coast of Mexico and Central America.
Story Source:
The above story is based on materials provided by University of Arizona. The
original article was written by Mari N. Jensen. Note: Materials may be
edited for content and length.
Journal Reference:
Kyle Davis, Xubin Zeng, Elizabeth A. Ritchie. A new
statistical model to predict seasonal North Atlantic hurricane activity. Weather
and Forecasting, 2015; 150325075852004 DOI: 10.1175/WAF-D-14-00156.1
Cite This Page:
University of Arizona. "Better method for forecasting
hurricane season." Science Daily,
31 March 2015. <www.sciencedaily.com/releases/2015/03/150331175912.htm>.
