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Temperature variability and soil–atmosphere interaction in South America simulated by two regional climate models

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Abstract

Interannual variability of surface air temperature over South America is investigated and, based on previous studies, thought to be partly the consequence of soil–atmosphere interaction. Annual and monthly averages of surface air temperature, evapotranspiration, heat fluxes, surface radiation and cloud cover, simulated by two regional climate models, RCA4 and LMDZ, were analyzed. To fully reveal the role of soil as a driver of temperature variability, simulations were performed with and without soil moisture-atmosphere coupling (Control and Uncoupled). Zones of large variance in air temperature and strong soil moisture-atmosphere coupling are found in parts of La Plata Basin and in eastern Brazil. The two models show different behaviors in terms of coupling magnitude and its geographical distribution, being the coupling strength higher in RCA4 and weaker in LMDZ. RCA4 also shows greater amplitude of the annual cycle of the monthly surface air temperature compared to LMDZ. In both regions and for both models, the Uncoupled experiment tends to be colder and exhibits smaller amplitude of the interannual variability and larger evaporative fraction than the Control does. It is evidenced that variability of the land surface affects, and is affected by, variability of the surface energy balance and that interannual temperature variability is partly driven by land–atmosphere interaction.

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Acknowledgements

The authors are grateful to Dr. Roberto Suárez-Moreno and two anonymous reviewers for their perceptive comments that greatly contributed to the improvement of the original manuscript. This research was supported by projects LEFE (AO2015-876370, France), PICT 2014 − 0887 (ANPCyT, Argentina), PIP 112-201101-00932 (CONICET, Argentina) and PICT2015-3097 (ANPCyT, Argentina).

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Correspondence to Claudio G. Menéndez.

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Menéndez, C.G., Giles, J., Ruscica, R. et al. Temperature variability and soil–atmosphere interaction in South America simulated by two regional climate models. Clim Dyn 53, 2919–2930 (2019). https://doi.org/10.1007/s00382-019-04668-6

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