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Published March 2015 | Erratum + Published
Journal Article Open

Physics of Changes in Synoptic Midlatitude Temperature Variability


This paper examines the physical processes controlling how synoptic midlatitude temperature variability near the surface changes with climate. Because synoptic temperature variability is primarily generated by advection, it can be related to mean potential temperature gradients and mixing lengths near the surface. Scaling arguments show that the reduction of meridional potential temperature gradients that accompanies polar amplification of global warming leads to a reduction of the synoptic temperature variance near the surface. This is confirmed in simulations of a wide range of climates with an idealized GCM. In comprehensive climate simulations (CMIP5), Arctic amplification of global warming similarly entails a large-scale reduction of the near-surface temperature variance in Northern Hemisphere midlatitudes, especially in winter. The probability density functions of synoptic near-surface temperature variations in midlatitudes are statistically indistinguishable from Gaussian, both in reanalysis data and in a range of climates simulated with idealized and comprehensive GCMs. This indicates that changes in mean values and variances suffice to account for changes even in extreme synoptic temperature variations. Taken together, the results indicate that Arctic amplification of global warming leads to even less frequent cold outbreaks in Northern Hemisphere winter than a shift toward a warmer mean climate implies by itself.

Additional Information

© 2015 American Meteorological Society. Manuscript received 11 September 2014, in final form 2 December 2014. We thank Erich Fischer and James Screen for helpful comments on this work. The research was supported by the National Science Foundation (Grants ARC-1107795 and AGS-1049201). Many calculations presented here were performed using the Geophysical Observation Analysis Tool (GOAT), a freely available MATLAB-based tool for retrieval, analysis, and visualization of geophysical data (http://www.goat-geo.org). We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP, the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.


Corrigendum Tapio Schneider, Tobias Bischoff, and Hanna Płotka J. Climate, 29(9), p. 3471 DOI: http://dx.doi.org/10.1175/JCLI-D-16-0096.1

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Erratum - jcli-d-16-0096.1.pdf


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