2020
DOI: 10.1038/s41598-020-57917-8
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Analyzing changes in the complexity of climate in the last four decades using MERRA-2 radiation data

Abstract: the energy balance of the earth is controlled by the shortwave and longwave radiation emitted to space. Changes in the thermodynamic state of the system over time affect climate and are noticeable when viewing the system as a whole. In this paper, we study the changes in the complexity of climate in the last four decades using data from the Modern-era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). First, we study the complexity of the shortwave and longwave radiation fields independ… Show more

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Cited by 26 publications
(13 citation statements)
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“…Radiation fluxes depend strongly and nonlinearly on the diurnal variations of cloud properties (Bergman and Salby 1997;Delgado-Bonal et al, 2020b), with the amount of radiation reflected to space depending on how cloud fraction changes during daytime correlate with the cycle of solar insolation. On the thermal infrared side, cloud height is also a major controlling factor of the planet's energy balance since low and high clouds have different impacts on the greenhouse effect.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…Radiation fluxes depend strongly and nonlinearly on the diurnal variations of cloud properties (Bergman and Salby 1997;Delgado-Bonal et al, 2020b), with the amount of radiation reflected to space depending on how cloud fraction changes during daytime correlate with the cycle of solar insolation. On the thermal infrared side, cloud height is also a major controlling factor of the planet's energy balance since low and high clouds have different impacts on the greenhouse effect.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…After demonstrating its capabilities for time signal analysis [ 98 ], it was used for physiological signal processing [ 45 , 46 , 99 , 100 ]. To date, it has been used in several fields such as climate forecasts [ 101 , 102 ], finance [ 103 ], image encryption authentication [ 89 , 104 ], and fault diagnosis [ 105 , 106 ]. The approximate entropy (AppEn) basically quantifies the regularity and unpredictability of the analyzed signal by comparing sliding vectors from the original signal.…”
Section: Theoretical Background: Classic and Entropy Indicatorsmentioning
confidence: 99%
“…Pincus introduced approximate entropy (ApEn) [131] in an attempt to adapt the entropy measures of Kolmogrorov, Sinai, and Oseledets [131] to practical (limited in size) data sets. ApEn is measure of complexity that applications in physiology [132], finance [133], and climatology [134].…”
Section: Entropymentioning
confidence: 99%