IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v374y2007i1p389-402.html
   My bibliography  Save this article

Statistical linguistic characterization of variability in observed and synthetic daily precipitation series

Author

Listed:
  • Primo, C.
  • Galván, A.
  • Sordo, C.
  • Gutiérrez, J.M.

Abstract

This paper deals with an application of Zipf law in climatology. This analysis allows the extraction of information not available by standard methods. In particular, rainfall temporal aggregation patterns associated with different climates are characterized by means of exponents derived from the resulting scaling laws. The analogy with linguistic analysis is obtained using a particular coding of precipitation as a discrete variable with four states (corresponding to four standard precipitation thresholds); each weekly symbolic sequence of observed precipitation is considered as a “word”, and each local station defines a “language” characterized by the observed words in a period representative of the climatology. To characterize these precipitation languages, we obtained characteristic exponents derived from the Zipf law for a set of representative stations of the main Köppen's climates and subclimates. We found different scaling behaviors for different subclimates, given by a single exponent in the range 0.6 (humid tropical climates) to 1.4 (polar climates); some humid middle-latitude subclimates exhibit a crossover with two different characteristic exponents corresponding to high and low frequency aggregation patterns (no explanation for this behavior is provided).

Suggested Citation

  • Primo, C. & Galván, A. & Sordo, C. & Gutiérrez, J.M., 2007. "Statistical linguistic characterization of variability in observed and synthetic daily precipitation series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 389-402.
    • Handle: RePEc:eee:phsmap:v:374:y:2007:i:1:p:389-402
    DOI: 10.1016/j.physa.2006.06.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437106007333
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2006.06.016?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Gutiérrez, J.M. & Rodrı́guez, M.A. & Abramson, G., 2001. "Multifractal analysis of DNA sequences using a novel chaos-game representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 300(1), pages 271-284.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Humberto Millán & Idalberto Macías & Jakeline Rabelo-Lima, 2022. "Hurst scaling with crossover of a drought indicator: a case study in Belem and Manaus, Brazil," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(1), pages 69-93, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pal, Mayukha & Kiran, V. Satya & Rao, P. Madhusudana & Manimaran, P., 2016. "Multifractal detrended cross-correlation analysis of genome sequences using chaos-game representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 456(C), pages 288-293.
    2. Natsuhiro Ichinose & Tetsushi Yada & Osamu Gotoh, 2014. "Tetrahedral Gray Code for Visualization of Genome Information," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-10, January.
    3. Kosmidis, Kosmas & Hütt, Marc-Thorsten, 2023. "DNA visibility graphs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    4. Pal, Mayukha & Satish, B. & Srinivas, K. & Rao, P. Madhusudana & Manimaran, P., 2015. "Multifractal detrended cross-correlation analysis of coding and non-coding DNA sequences through chaos-game representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 596-603.
    5. Meraz, Monica & Carbó, Roxana & Rodriguez, Eduardo & Alvarez-Ramirez, Jose, 2023. "Fractal correlations in the Covid-19 genome sequence via multivariate rescaled range analysis," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:374:y:2007:i:1:p:389-402. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.