Preprints
https://doi.org/10.5194/esd-2016-12
https://doi.org/10.5194/esd-2016-12

  19 Apr 2016

19 Apr 2016

Review status: this discussion paper is a preprint. It has been under review for the journal Earth System Dynamics (ESD). The manuscript was not accepted for further review after discussion.

Identifying global patterns of stochasticity and nonlinearity in the Earth System

Fernando Arizmendi1, Marcelo Barreiro1, and Cristina Masoller2 Fernando Arizmendi et al.
  • 1Instituto de Física, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo, Uruguay
  • 2Departament de Física, Universitat Politecnica de Catalunya, 08222 Terrassa, Barcelona, Spain

Abstract. By comparing time-series of surface air temperature (SAT, monthly reanalysis data from NCEP CDAS1 and ERA Interim) with respect to the top-of-atmosphere incoming solar radiation (the insolation), we perform a detailed analysis of the SAT response to solar forcing. By computing the entropy of SAT time-series, we also quantify the degree of stochasticity. We find spatial coherent structures which are characterized by high stochasticity and nearly linear response to solar forcing (the shape of SAT time-series closely follows that of the isolation), or vice versa. The entropy analysis also allows to identify geographical regions in which there are significant differences between the NCEP CDAS1 and ERA Interim datasets, which are due to the presence of extreme values in one dataset but not in the other. Therefore, entropy maps are a valuable tool for anomaly detection and model inter-comparisons.

Fernando Arizmendi et al.

 
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Status: closed
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Fernando Arizmendi et al.

Fernando Arizmendi et al.

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Short summary
Understanding how surface air temperature (SAT) is controlled by the incoming solar radiation is a fundamental and challenging problem in climate dynamics. Here we analyze the response of monthly-averaged SAT to solar forcing, and we also quantify the level of randomness of SAT variability. We find coherent spatial patterns which can be interpreted in terms of known climate phenomena.
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