Is it possible to make valid climate
predictions that go beyond weeks, months, even a year? University of California,
Los Angeles atmospheric scientists report they have now made long-term climate
forecasts that are among the best ever—predicting climate up to 16 months in
advance, nearly twice the length of time previously achieved by climate
scientists.
Forecasts of climate are much more general
than short-term weather forecasts; they do not predict precise temperatures in
specific cities, but they still may have major implications for agriculture,
industry, and the economy, says Michael Ghil, a distinguished professor of
climate dynamics in the UCLA Department of Atmospheric and Oceanic Sciences and
senior author of the research.
The study is currently available online in
the Proceedings of the National Academy of Sciences (PNAS).
“Certain climate features might be
predictable, although not in such detail as the temperature and whether it will
rain in Los Angeles on such a day two years from
now,” says Ghil, who is also a member of UCLA’s Institute of Geophysics
and Planetary Physics. “These are averages over larger areas and longer
time spans.”
Long-term climate forecasts could help
predict El Niño events more than a year in advance. El Niño is a climate
pattern characterized by the warming of equatorial surface waters, which
dramatically disrupts weather patterns over much of the globe and strikes as
often as every second year, as seldom as every seventh year or somewhere in
between.
A major issue addressed by Ghil and his
colleagues in the PNAS research is
the difficulty of separating natural climate variability from human-induced
climate change and how to take natural variability into account when making
climate models.
For the study, Ghil and his UCLA colleagues
Michael Chekroun and Dmitri Kondrashov of the department of atmospheric and
oceanic sciences analyzed sea-surface temperatures globally. To improve their
forecasts, they devised a new algorithm based on novel insights about the
mathematics of how short-term weather interacts with long-term climate. Weather
covers a period of days, while climate covers months and longer.
As is customary in this field, Ghil and his
colleagues used five decades of climate data and test predictions
retrospectively. For example, they used climate data from 1950 to 1970 to make
“forecasts” for January 1971, February 1971 and beyond and see how
accurate the predictions were. They reported achieving higher accuracy in their
predictions 16 months out than other scientists achieved in half that time.
Extreme climate, extreme events
Ghil also led a separate, three-year
European Commission–funded project called “Extreme Events: Causes and Consequences”
involving 17 institutions in nine countries. In a recent paper on extreme
events, published in Nonlinear Processes
in Geophysics, Ghil and colleagues addressed not only extreme weather and
climate but extreme events such as earthquakes and other natural catastrophes,
and even extreme economic events. Their study included an analysis of the
macro-economic impact of extreme events.
“It turns out, surprisingly, that it is
worse when catastrophes occur during an economic expansion, and better during a
recession,” Ghil says. “If your roof blows off in a hurricane, it’s
easier to get somebody to fix your roof when many people are out of work and
wages are depressed. This finding is consistent with, and helps explain,
reports of the World Bank on the impact of natural catastrophes.”
