Climate-prediction models show skills in forecasting climate trends over
time spans of greater than 30 years and at the geographical scale of
continents, but they deteriorate when applied to shorter time frames and
smaller geographical regions, a new study has found.

Published in the Journal of
Geophysical Research-Atmospheres, the study is one of the first to
systematically address a longstanding, fundamental question asked not only by
climate scientists and weather forecasters, but the public as well: How good
are Earth system models at predicting the surface air temperature trend at
different geographical and time scales?

Xubin Zeng, a professor in the University of Arizona Department of
Atmospheric Sciences who leads a research group evaluating and developing
climate models, says the goal of the study was to bridge the communities of
climate scientists and weather forecasters, who sometimes disagree with respect
to climate change.

According to Zeng, who directs the UA Climate Dynamics and Hydrometeorology
Center, the weather forecasting community has demonstrated skill and progress
in predicting the weather up to about two weeks into the future, whereas the
track record has remained less clear in the climate science community tasked
with identifying long-term trends for the global climate.

“Without such a track record, how can the community trust the
climate projections we make for the future?” says Zeng, who serves on the Board
on Atmospheric Sciences and Climate of the National Academies and the Executive
Committee of the American Meteorological Society. “Our results show that
actually both sides’ arguments are valid to a certain degree.”

“Climate
scientists are correct because we do show that on the continental scale, and
for time scales of three decades or more, climate models indeed show predictive
skills. But when it comes to predicting the climate for a certain area over the
next 10 or 20 years, our models can’t do it.” 

To test
how accurately various computer-based climate prediction models can turn data
into predictions, Zeng’s group used the “hindcast” approach.

“Ideally,
you would use the models to make predictions now, and then come back in say, 40
years and see how the predictions compare to the actual climate at that time,”
says Zeng. “But obviously we can’t wait that long. Policymakers need
information to make decisions now, which in turn will affect the climate 40
years from now.”

Zeng’s
group evaluated seven computer simulation models used to compile the reports
that the Intergovernmental Panel on Climate Change, or IPCC, issues every six years.
The researchers fed them historical climate records and compared their results
to the actual climate change observed between then and now.

“We wanted
to know at what scales are the climate models the IPCC uses reliable,” says
Koichi Sakaguchi, a doctoral student in Zeng’s group who led the study. “These
models considered the interactions between the Earth’s surface and atmosphere
in both hemispheres, across all continents and oceans and how they are coupled.”

Zeng said
the study should help the community establish a track record whose accuracy in
predicting future climate trends can be assessed as more comprehensive climate
data become available.

“Our goal
was to provide climate modeling centers across the world with a baseline they
can use every year as they go forward,” Zeng adds. “It is important to keep in
mind that we talk about climate hindcast starting from 1880. Today, we have much
more observational data. If you start your prediction from today for the next
30 years, you might have a higher prediction skill, even though that hasn’t
been proven yet.”

The skill
of a climate model depends on three criteria at a minimum, Zeng explains. The
model has to use reliable data, its prediction must be better than a prediction
based on chance, and its prediction must be closer to reality than a prediction
that only considers the internal climate variability of the Earth system and
ignores processes such as variations in solar activity, volcanic eruptions,
greenhouse gas emissions from fossil fuel burning and land-use change, for
example urbanization and deforestation.

“If a
model doesn’t meet those three criteria, it can still predict something but it
cannot claim to have skill,” Zeng says.

According
to Zeng, global temperatures have increased in the past century by about 1.4 F
or 0.8 C on average. Barring any efforts to curb global warming from greenhouse
gas emissions, the temperatures could further increase by about 4.5 F (2.5 C)
or more by the end of the 21st century based on these climate models.

“The
scientific community is pushing policymakers to avoid the increase of temperatures
by more than 2 C because we feel that once this threshold is crossed, global
warming could be damaging to many regions,” he says.

Zeng says
that climate models represent the current understanding of the factors
influencing climate, and then translate those factors into computer code and
integrate their interactions into the future.

“The
models include most of the things we know,” he explains, “such as wind, solar
radiation, turbulence mixing in the atmosphere, clouds, precipitation, and
aerosols, which are tiny particles suspended in the air, surface moisture, and
ocean currents.”

Zeng
describes how the group did the analysis: “With any given model, we evaluated
climate predictions from 1900 into the future—10 years, 20 years, 30 years, 40
years, 50 years. Then we did the same starting in 1901, then 1902 and so forth,
and applied statistics to the results.”

Climate
models divide the Earth into grid boxes whose size determines its spatial
resolution. According to Zeng, state of the art is about one degree, equaling about
60 miles (100 km). 

“There has
to be a simplification because if you look outside the window, you realize you
don’t typically have a cloud cover that measures 60 miles by 60 miles. The
models cannot reflect that kind of resolution. That’s why we have all those
uncertainties in climate prediction.”

“Our
analysis confirmed what we expected from last IPCC report in 2007,” says
Sakaguchi. “Those climate models are believed to be of good skill on large
scales, for example predicting temperature trends over several decades, and we
confirmed that by showing that the models work well for time spans longer than
30 years and across geographical scales spanning 30 degrees or more.”

The
scientists pointed out that although the IPCC issues a new report every six
years, they didn’t see much change with regard to the prediction skill of the
different models.

“The IPCC
process is driven by international agreements and politics,” Zeng says. “But in
science, we are not expected to make major progress in just six years. We have
made a lot of progress in understanding certain processes, for example airborne
dust and other small particles emitted from surface, either through human
activity or through natural sources into the air. But climate and the Earth
system still are extremely complex. Better understanding doesn’t necessarily
translate into better skill in a short time.”

“Once you
go into details, you realize that for some decades, models are doing a much
better job than for some other decades. That is because our models are only as
good as our understanding of the natural processes, and there is a lot we don’t
understand.”

Source: University of Arizona