Model warming projections, forced by increasing greenhouse gases, have a large inter-model spread in both their geographical warming patterns and global mean values. The inter-model warming pattern spread (WPS) limits our ability to foresee the severity of regional impacts on nature and society. This paper focuses on uncovering the feedbacks responsible for the WPS. Here, we identify two dominant WPS modes whose global mean values also explain 98.7% of the global warming spread (GWS). We show that the ice-albedo feedback spread explains uncertainties in polar regions while the water vapor feedback spread explains uncertainties elsewhere. Other processes, including the cloud feedback, contribute less to the WPS as their spreads tend to cancel each other out in a model-dependent manner. Our findings suggest that the WPS and GWS could be significantly reduced by narrowing the inter-model spreads of ice-albedo and water vapor feedbacks, and better understanding the spatial coupling between feedbacks.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7479110 | PMC |
http://dx.doi.org/10.1038/s41467-020-18227-9 | DOI Listing |
Clim Dyn
February 2024
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria.
Unlabelled: We investigate historical simulations of relevant components of the Arctic energy and water budgets for 39 Coupled Model Intercomparison Project Phase 6 (CMIP6) models and validate them against observation-based estimates. We look at simulated seasonal cycles, long-term averages and trends of lateral transports and storage rates in atmosphere and ocean as well as vertical fluxes at top-of-atmosphere and the surface. We find large inter-model spreads and systematic biases in the representation of annual cycles and long-term averages.
View Article and Find Full Text PDFNat Commun
December 2023
Department of Applied Mathematics, University of Washington, Seattle, CA, USA.
Severity of warming predicted by climate models depends on their Transient Climate Response (TCR). Inter-model spread of TCR has persisted at ~ 100% of its mean for decades. Existing observational constraints of TCR are based on observed historical warming response to historical forcing and their uncertainty spread is just as wide, mainly due to forcing uncertainty, and especially that of aerosols.
View Article and Find Full Text PDFThe Arctic Ocean's Beaufort Gyre (BG) is a wind-driven reservoir of relatively fresh seawater, situated beneath time-mean anticyclonic atmospheric circulation, and is covered by mobile pack ice for most of the year. Liquid freshwater accumulation in and expulsion from this gyre is of critical interest due to its potential to affect the Atlantic meridional overturning circulation and due to the importance of freshwater in modulating vertical fluxes of heat, nutrients and carbon in the ocean, and exchanges of heat and moisture with the atmosphere. Here, we investigate the hypothesis that wind-driven sea ice transport into/from the BG region influences the freshwater content of the gyre and its variability.
View Article and Find Full Text PDFSci Total Environ
June 2023
Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology (NUIST), Nanjing 210044, China.
Development of solar energy is one of the key solutions towards carbon neutrality in China. The output of solar energy is dependent on weather conditions and shows distinct spatiotemporal characteristics. Previous studies have explored the photovoltaic (PV) power potential in China but with single models and low-resolution radiation data.
View Article and Find Full Text PDFGlob Chang Biol
May 2023
School of Integrative Plant Science, Cornell University, Ithaca, New York, USA.
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