Nav: Home

Machine learning may be a game-changer for climate prediction

June 19, 2018

New York, NY--June 19, 2018--A major challenge in current climate prediction models is how to accurately represent clouds and their atmospheric heating and moistening. This challenge is behind the wide spread in climate prediction. Yet accurate predictions of global warming in response to increased greenhouse gas concentrations are essential for policy-makers (e.g. the Paris climate agreement).

In a paper recently published online in Geophysical Research Letters (May 23), researchers led by Pierre Gentine, associate professor of earth and environmental engineering at Columbia Engineering, demonstrate that machine learning techniques can be used to tackle this issue and better represent clouds in coarse resolution (~100km) climate models, with the potential to narrow the range of prediction.

"This could be a real game-changer for climate prediction," says Gentine, lead author of the paper, and a member of the Earth Institute and the Data Science Institute. "We have large uncertainties in our prediction of the response of the Earth's climate to rising greenhouse gas concentrations. The primary reason is the representation of clouds and how they respond to a change in those gases. Our study shows that machine-learning techniques help us better represent clouds and thus better predict global and regional climate's response to rising greenhouse gas concentrations."

The researchers used an idealized setup (an aquaplanet, or a planet with continents) as a proof of concept for their novel approach to convective parameterization based on machine learning. They trained a deep neural network to learn from a simulation that explicitly represents clouds. The machine-learning representation of clouds, which they named the Cloud Brain (CBRAIN), could skillfully predict many of the cloud heating, moistening, and radiative features that are essential to climate simulation.

Gentine notes, "Our approach may open up a new possibility for a future of model representation in climate models, which are data driven and are built 'top-down,' that is, by learning the salient features of the processes we are trying to represent."

The researchers also note that, because global temperature sensitivity to CO2 is strongly linked to cloud representation, CBRAIN may also improve estimates of future temperature. They have tested this in fully coupled climate models and have demonstrated very promising results, showing that this could be used to predict greenhouse gas response.
-end-
About the Study

The study is titled "Could Machine Learning Break the Convection Parameterization Deadlock?"

Authors are: P. Gentine1 , M. Pritchard2 , S. Rasp3 , G. Reinaudi1, and G. Yacalis2 (1Earth and Environmental Engineering, Columbia University, New York, NY, USA, 2Earth System Science, University of California, Irvine, CA, USA, 3Faculty of Physics, LMU Munich, Munich, Germany).

M. P. acknowledges funding from the DOE SciDac and Early Career Programs (DE-SC0012152 and DE-SC00-12548) as well as the NSF (AGS-1734164). Stephan Rasp was funded by the German Research Foundation (DFG) Transregional Collaborative Research Center SFB/TRR 165 "Waves to Weather". Computational resources for our SPCAM3 simulations were provided through the NSF Extreme Science and Engineering Discovery Environment (XSEDE) under allocation TG-ATM120034.

The authors declare no financial or other conflicts of interest.

LINKS:

Paper: https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2018GL078202

DOI: 10.1029/2018GL078202

https://engineering.columbia.edu/faculty/pierre-gentine

http://eee.columbia.edu/

http://engineering.columbia.edu/

Columbia Engineering

Columbia Engineering, based in New York City, is one of the top engineering schools in the U.S. and one of the oldest in the nation. Also known as The Fu Foundation School of Engineering and Applied Science, the School expands knowledge and advances technology through the pioneering research of its more than 200 faculty, while educating undergraduate and graduate students in a collaborative environment to become leaders informed by a firm foundation in engineering. The School's faculty are at the center of the University's cross-disciplinary research, contributing to the Data Science Institute, Earth Institute, Zuckerman Mind Brain Behavior Institute, Precision Medicine Initiative, and the Columbia Nano Initiative. Guided by its strategic vision, "Columbia Engineering for Humanity," the School aims to translate ideas into innovations that foster a sustainable, healthy, secure, connected, and creative humanity.

Columbia University School of Engineering and Applied Science

Related Global Warming Articles:

A new study provides a solid evidence for global warming
The new study allows a more accurate assessment of how much heat has accumulated in the ocean (and Earth) system.
Global warming hiatus disproved -- again
UC Berkeley scientists calculated average ocean temperatures from 1999 to 2015, separately using ocean buoys and satellite data, and confirmed the uninterrupted warming trend reported by NOAA in 2015, based on that organization's recalibration of sea surface temperature recordings from ships and buoys.
Report reassesses variations in global warming
Experts at the European Centre for Medium-Range Weather Forecasts (ECMWF) have issued a new assessment of temperature trends and variations from the latest available data and analyses.
Clouds are impeding global warming... for now
Lawrence Livermore National Laboratory researchers have identified a mechanism that causes low clouds -- and their influence on Earth's energy balance -- to respond differently to global warming depending on their spatial pattern.
Global warming's next surprise: Saltier beaches
Batches of sand from a beach on the Delaware Bay are yielding insights into the powerful impact of temperature rise and evaporation along the shore that are in turn challenging long-held assumptions about what causes beach salinity to fluctuate in coastal zones that support a rich network of sea creatures and plants.
Could global warming's top culprit help crops?
A new study tries to disentangle the complex question of whether rising amounts of carbon dioxide in the air might in some cases help crops.
Evaporation for review -- and with it global warming
The process of evaporation, one of the most widespread on our planet, takes place differently than we once thought -- this has been shown by new computer simulations carried out at the Institute of Physical Chemistry of the Polish Academy of Sciences in Warsaw.
Researchers reveal when global warming first appeared
Human caused climate change is increasingly apparent today through multiple lines of evidence.
1,800 years of global ocean cooling halted by global warming
Prior to the advent of human-caused global warming in the 19th century, the surface layer of Earth's oceans had undergone 1,800 years of a steady cooling trend, according to a new study in the Aug.
Global sea levels have risen 6 meters or more with just slight global warming
A new review analyzing three decades of research on the historic effects of melting polar ice sheets found that global sea levels have risen at least six meters, or about 20 feet, above present levels on multiple occasions over the past three million years.

Related Global Warming Reading:

Best Science Podcasts 2019

We have hand picked the best science podcasts for 2019. Sit back and enjoy new science podcasts updated daily from your favorite science news services and scientists.
Now Playing: TED Radio Hour

Jumpstarting Creativity
Our greatest breakthroughs and triumphs have one thing in common: creativity. But how do you ignite it? And how do you rekindle it? This hour, TED speakers explore ideas on jumpstarting creativity. Guests include economist Tim Harford, producer Helen Marriage, artificial intelligence researcher Steve Engels, and behavioral scientist Marily Oppezzo.
Now Playing: Science for the People

#524 The Human Network
What does a network of humans look like and how does it work? How does information spread? How do decisions and opinions spread? What gets distorted as it moves through the network and why? This week we dig into the ins and outs of human networks with Matthew Jackson, Professor of Economics at Stanford University and author of the book "The Human Network: How Your Social Position Determines Your Power, Beliefs, and Behaviours".