August 29, 2018
Feature

Decoding the Ocean's Influence on Global Surface Air Temperature Patterns

Study identifies recurrent patterns of temperature response to energy changes at random locations.

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During a two-part study, researchers confirmed that the global mean surface air temperature is far more responsive to ocean heating from high latitudes than from the tropics. 

The Science

When heat is added to the climate system, it can be challenging to determine where and by how much the surface air temperature will increase. A research team including scientists at the U.S. Department of Energy's Pacific Northwest National Laboratory conducted a two-part study that approached this challenge from a unique experimental angle. They constructed the linear response function of surface air temperature intrinsic to Earth's climate system and the associated temperature patterns under random perturbation—called neutral modes. As a result, the research team confirmed that the global mean surface air temperature is far more responsive to ocean heating from high latitudes than from the tropics.

The Impact

This work sheds an important new light on recurrent patterns of global surface air temperatures, such as polar amplification, in which warming is greater at the poles than the global mean warming. It also points to a promising direction for predicting regional climate responses to perturbations of Earth's energy balance.

Summary

In a two-part study, researchers performed a large set of model simulations in which they added ocean heat flux patches one patch at a time to cover the global oceans. These so-called Green's function experiments mimicked the effects of heat absorbed by the ocean. Through the experiments, scientists examined how the global surface air temperature (SAT) responds to random energy perturbations and how atmospheric energy transport compensates for the ocean's influence, or forcing, at different locations. With the total of 106 pairs of numerical experiments, researchers constructed the linear response function of the SAT to ocean heat fluxes—or any forcing to the atmosphere, for that matter.

An analysis of the linear response function revealed the SAT patterns—the neutral modes—that were most excitable due to oceanic forcing. In particular, the first and most dominant neutral mode bore a great resemblance to the pattern of the Interdecadal Pacific Oscillation, a pattern of natural variability at decadal time scales across the Pacific Ocean. Because ocean dynamics were absent from the Green's function experiments with prescribed ocean heat fluxes, the result implies that the pattern of the Interdecadal Pacific Oscillation originates from atmospheric processes.

The experiments also confirmed a result from a previous study—derived from more idealized model configuration—that the global mean SAT is far more responsive to ocean heating from high latitudes than from the tropics. This result stemmed from how cloud, ice albedo (reflectivity), water vapor, and atmospheric temperature profiles responded to ocean heating and influenced the SAT. Meanwhile, the tropics showed more "altruism" in sharing the warming with higher latitudes than the other way around. This was likely due to the high energy transport efficiency of the Hadley overturning circulation in the tropics. Remarkably, regardless of the location of the oceanic forcing, the neutral mode of the SAT response gave rise to recurrent features of climate response, the most prominent being the polar-amplified warming.

Acknowledgments

Part I: The U.S. Department of Energy (DOE) Office of ScienceBiological and Environmental Research supported this study as part of the Regional and Global Climate Modeling program. Computational resources were provided by the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science user facility. F. Liu was supported by a Chinese Scholarship Council visiting student fellowship. X. Wan was supported by NSFC (41576004) and the National Basic Research Program of China (2014CB745001).

Part II: The DOE Office of Science, Biological and Environmental Research supported this study as part of the Regional and Global Climate Modeling program. F.L. was supported by the China Scholarship Council. Y.H. was supported by the Discovery Program of the Sciences and Engineering Council of Canada (RGPIN 418305-13). Y.L. was supported by the National Science Foundation of China (41676002 and 41376009).

References

Part I: F. Liu, J. Lu, O.A. Garuba, Y. Huang, L.R. Leung, Y. Luo, and X. Wan, "Sensitivity of Surface Temperature to Oceanic Forcing Via Q-Flux Green's Function Experiments Part I: Linear Response Function." Journal of Climate 31, 3625-3641 (2018). [DOI: 10.1175/JCLI-D-17-0462.1]

Part II: F. Liu, J. Lu, O.A. Garuba, Y. Huang, L.R. Leung, B.E. Harrop, and Y. Luo, "Sensitivity of Surface Temperature to Oceanic Forcing Via Q-Flux Green's Function Experiments Part II: Feedback Decomposition and Polar Amplification." Journal of Climate 31, 6745-6761 (2018). [DOI: 10.1175/JCLI-D-18-0042.1]

Key Capabilities

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About PNNL

Pacific Northwest National Laboratory draws on its distinguishing strengths in chemistry, Earth sciences, biology and data science to advance scientific knowledge and address challenges in sustainable energy and national security. Founded in 1965, PNNL is operated by Battelle for the Department of Energy’s Office of Science, which is the single largest supporter of basic research in the physical sciences in the United States. DOE’s Office of Science is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science. For more information on PNNL, visit PNNL's News Center. Follow us on Twitter, Facebook, LinkedIn and Instagram.

Published: August 29, 2018

Research Team

Fukai Liu, Yiyong Luo, and Xiuquan Wan, Physical Oceanography Laboratory/Collaborative Innovation Center of Marine Science and Technology, Ocean University of China, and Qingdao National Laboratory for Marine Science and Technology (China)
Jian Lu, Oluwayemi Garuba, L. Ruby Leung, and Bryce E. Harrop, PNNL
Yi Huang, McGill University (Canada)

Research topics