Abstract

For representative observational stations on the globe, rank-size analyses are made for vectors arising from sequences of the monthly distributions of temperatures and precipitations. The ranking method has been shown to be useful for revealing a statistical rule inherent in complex systems such as texts of natural languages. Climate change is detectable through the rotation angle between two 12-dimensional vectors. The rankings of the angle data for the entire station are obtained and compared between the former (from 1931 to 1980) and the latter (from 1951 to 2010) period. Independently of the period, the variation of the angles is found to show a long tail decay as a function of their ranks being aligned in descending order. Furthermore, it is shown that for the temperatures, nonlinearities in the angle-rank plane get stronger in the latter period, confirming that the so-called snow/ice-albedo feedback no doubt arises. In contrast to the temperatures, no sign of a feedback is found for the precipitations. Computed results for Japan show that the effect is consistent with the global counterpart.

Highlights

  • All the governments in the world are currently confronted with the difficult problem of both mitigating climate change and maintaining sustainable development

  • Research articles of climate change have grown substantially in number, even if we restrict our attention within interdisciplinary physics [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19]

  • Besides conventional techniques that have been adopted in statistical physics, novel approaches have been attempted such as wavelet transformation methods [9,10,11,12,13], multiscale entropy analysis [10], convergent cross mapping (CCM) [12], a method using Minkowski distance functions [18], and the vectorial rotation method [19]

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Summary

INTRODUCTION

All the governments in the world are currently confronted with the difficult problem of both mitigating climate change and maintaining sustainable development. Of the climate change impacts [1,2,3], in particular, global warming has become the most serious problem necessary to be dealt with urgently in cooperation with the developed and developing countries. No attempt has been made to apply the rank-size methodology to the study of climate change impacts. Through specific numerical results we can examine whether, along with conventional applications to complex systems, the rank-size approach is useful for revealing climate change impacts both in the global and in the regional scale

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