Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Atmos. Chem. Phys., 16, 12925-12944, 2016
https://doi.org/10.5194/acp-16-12925-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
19 Oct 2016
How can we understand the global distribution of the solar cycle signal on the Earth's surface?
Kunihiko Kodera1, Rémi Thiéblemont2, Seiji Yukimoto3, and Katja Matthes4,5 1Institute for Space-Earth Environmental Research, Nagoya University, Nagoya, 464-8601, Japan
2Laboratoire Atmosphères Milieux Observations Spatiales, 78280 Guyancourt, France
3Meteorological Research Institute, Tsukuba, 305-0052, Japan
4Research Division Ocean Circulation and Climate, GEOMAR Helmholtz Centre for Ocean Research, 24105 Kiel, Germany
5Christian-Albrechts Universität zu Kiel, 24105 Kiel, Germany
Abstract. To understand solar cycle signals on the Earth's surface and identify the physical mechanisms responsible, surface temperature variations from observations as well as climate model data are analysed to characterize their spatial structure. The solar signal in the annual mean surface temperature is characterized by (i) mid-latitude warming and (ii) no overall tropical warming. The mid-latitude warming during solar maxima in both hemispheres is associated with a downward penetration of zonal mean zonal wind anomalies from the upper stratosphere during late winter. During the Northern Hemisphere winter this is manifested by a modulation of the polar-night jet, whereas in the Southern Hemisphere, the upper stratospheric subtropical jet plays the major role. Warming signals are particularly apparent over the Eurasian continent and ocean frontal zones, including a previously reported lagged response over the North Atlantic. In the tropics, local warming occurs over the Indian and central Pacific oceans during high solar activity. However, this warming is counterbalanced by cooling over the cold tongue sectors in the southeastern Pacific and the South Atlantic, and results in a very weak zonally averaged tropical mean signal. The cooling in the ocean basins is associated with stronger cross-equatorial winds resulting from a northward shift of the ascending branch of the Hadley circulation during solar maxima. To understand the complex processes involved in the solar signal transfer, results of an idealized middle atmosphere–ocean coupled model experiment on the impact of stratospheric zonal wind changes are compared with solar signals in observations. Model integration of 100 years of strong or weak stratospheric westerly jet condition in winter may exaggerate long-term ocean feedback. However, the role of ocean in the solar influence on the Earth's surface can be better seen. Although the momentum forcing differs from that of solar radiative forcing, the model results suggest that stratospheric changes can influence the troposphere, not only in the extratropics but also in the tropics through (i) a downward migration of wave–zonal mean flow interactions and (ii) changes in the stratospheric mean meridional circulation. These experiments support earlier evidence of an indirect solar influence from the stratosphere.

Citation: Kodera, K., Thiéblemont, R., Yukimoto, S., and Matthes, K.: How can we understand the global distribution of the solar cycle signal on the Earth's surface?, Atmos. Chem. Phys., 16, 12925-12944, https://doi.org/10.5194/acp-16-12925-2016, 2016.
Publications Copernicus
Short summary
The spatial structure of the solar cycle signals on the Earth's surface is analysed to identify the mechanisms. Both tropical and extratropical solar surface signals can result from circulation changes in the upper stratosphere through (i) a downward migration of wave zonal mean flow interactions and (ii) changes in the stratospheric mean meridional circulation. Amplification of the solar signal also occurs through interaction with the ocean.
The spatial structure of the solar cycle signals on the Earth's surface is analysed to identify...
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