Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-445
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Technical note
13 Sep 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Hydrology and Earth System Sciences (HESS).
An improved Grassberger-Procaccia algorithm for analysis of climate system complexity
Chongli Di1, Tiejun Wang1, Xiaohua Yang2, and Siliang Li1 1Institute of Surface-Earth System Science, Tianjin University, Tianjin, 300072, P. R. China
2State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, P. R. China
Abstract. Understanding the complexity of natural systems, such as climate systems, is critical for various research and application purposes. A range of techniques have been developed to quantify system complexity, among which Grassberger-Procaccia (G-P) algorithm has been mostly used. However, the use of this method is still not adaptive and relies heavily on subjective criteria. To this end, an improved G-P algorithm was proposed, which integrated the normal-based K-means clustering technique and Random Sample Consensus algorithm (RANSAC) for computing correlation dimensions. To test its effectiveness for computing correlation dimensions, the proposed algorithm was compared with traditional methods using the classical Lorenz and Henon chaotic systems. The results revealed that the new method outperformed traditional algorithms in computing correlation dimensions for both chaotic systems, demonstrating the improvement made by the new method. Based on the new algorithm, the complexity of precipitation and air temperature in the Haihe River Basin (HRB) in northeast China was further evaluated. The results showed that there existed considerable regional differences in the complexity of both climatic variables across the HRB. Specifically, precipitation was shown to become progressively more complex from the mountainous area in the northwest to the plain area in the southeast; whereas, the complexity of air temperature exhibited an opposite trend with less complexity in the plain area. Overall, the spatial patterns of the complexity of precipitation and air temperature reflected the influence of the dominant climate system in the region.

Citation: Di, C., Wang, T., Yang, X., and Li, S.: An improved Grassberger-Procaccia algorithm for analysis of climate system complexity, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-445, in review, 2017.
Chongli Di et al.
Chongli Di et al.
Chongli Di et al.

Viewed

Total article views: 318 (including HTML, PDF, and XML)

HTML PDF XML Total BibTeX EndNote
279 36 3 318 3 3

Views and downloads (calculated since 13 Sep 2017)

Cumulative views and downloads (calculated since 13 Sep 2017)

Viewed (geographical distribution)

Total article views: 318 (including HTML, PDF, and XML)

Thereof 314 with geography defined and 4 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 21 Nov 2017
Publications Copernicus
Download
Short summary
The original Grassberger-Procaccia algorithm for complex analysis was modified by incorporating the normal-based K-means clustering technique and the RANSAC algorithm. Calculation accuracy of the proposed method was shown to outperform traditional algorithms. The proposed algorithm was used to diagnose climate system complexity in the Haihe River Basin. The spatial patterns of the complexity of precipitation and air temperature reflected the influence of the dominant climate system.
The original Grassberger-Procaccia algorithm for complex analysis was modified by incorporating...
Share