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, said 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?” said 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,” said 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 these historical climate records and compared their results to the actual climate change observed between then and now.
“We wanted to know at what scales the climate models the IPCC uses are reliable,” said 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 added. “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.”
