IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v549y2020ics0378437120301114.html
   My bibliography  Save this article

Multifractal analysis of air temperature in Brazil

Author

Listed:
  • da Silva, Hérica Santos
  • Silva, José Rodrigo Santos
  • Stosic, Tatijana

Abstract

In view of current concerns over global warming and climate change, in order to contribute to a better geographically explicit understanding of complexity of temperature dynamics over the territory of Brazil over the last three decades, in this work we investigate multifractal properties of daily means of air temperature recorded at 265 meteorological stations, by using multifractal detrended fluctuation analysis. All series exhibit persistent long-term correlations (indicated by a Hurst exponent larger than 0.5), and multifractality with dominance of small fluctuations (indicated by right skewed multifractal spectrum). Northern and northeastern parts of this continental size country (that belong to tropical and semi-arid climate zone) exhibit stronger persistency and weaker multifractality, while southern part of the country (that belongs to sub-tropical climate zone) exhibits opposite characteristics, weaker persistency and stronger multifractality. This study contributes to a better understanding of the stochastic processes that generate air temperature variability in Brazil over the last decades.

Suggested Citation

  • da Silva, Hérica Santos & Silva, José Rodrigo Santos & Stosic, Tatijana, 2020. "Multifractal analysis of air temperature in Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    • Handle: RePEc:eee:phsmap:v:549:y:2020:i:c:s0378437120301114
    DOI: 10.1016/j.physa.2020.124333
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120301114
    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.2020.124333?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. Fabio Marin & James Jones & Abraham Singels & Frederick Royce & Eduardo Assad & Giampaolo Pellegrino & Flávio Justino, 2013. "Climate change impacts on sugarcane attainable yield in southern Brazil," Climatic Change, Springer, vol. 117(1), pages 227-239, March.
    2. Lin, Guangxing & Fu, Zuntao, 2008. "A universal model to characterize different multi-fractal behaviors of daily temperature records over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 573-579.
    3. Kavasseri, Rajesh G. & Nagarajan, Radhakrishnan, 2005. "A multifractal description of wind speed records," Chaos, Solitons & Fractals, Elsevier, vol. 24(1), pages 165-173.
    4. Stošić, Darko & Stošić, Dusan & Stošić, Tatijana & Stanley, H. Eugene, 2015. "Multifractal analysis of managed and independent float exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 13-18.
    5. Mark Maslin & Patrick Austin, 2012. "Climate models at their limit?," Nature, Nature, vol. 486(7402), pages 183-184, June.
    6. Telesca, Luciano & Lovallo, Michele & Mammadov, Samir & Kadirov, Fakhraddin & Babayev, Gulam, 2015. "Power spectrum analysis and multifractal detrended fluctuation analysis of Earth’s gravity time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 426-434.
    7. Kantelhardt, Jan W. & Zschiegner, Stephan A. & Koscielny-Bunde, Eva & Havlin, Shlomo & Bunde, Armin & Stanley, H.Eugene, 2002. "Multifractal detrended fluctuation analysis of nonstationary time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 87-114.
    8. Jiang, Lei & Zhang, Jiping & Liu, Xinwei & Li, Fei, 2016. "Multi-fractal scaling comparison of the Air Temperature and the Surface Temperature over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 783-792.
    9. Telesca, Luciano & Lovallo, Michele & Kanevski, Mikhail, 2016. "Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions," Applied Energy, Elsevier, vol. 162(C), pages 1052-1061.
    10. Monetti, Roberto A. & Havlin, Shlomo & Bunde, Armin, 2003. "Long-term persistence in the sea surface temperature fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 320(C), pages 581-589.
    11. Kalamaras, N. & Philippopoulos, K. & Deligiorgi, D. & Tzanis, C.G. & Karvounis, G., 2017. "Multifractal scaling properties of daily air temperature time series," Chaos, Solitons & Fractals, Elsevier, vol. 98(C), pages 38-43.
    12. de Lucena, André Frossard Pereira & Szklo, Alexandre Salem & Schaeffer, Roberto & de Souza, Raquel Rodrigues & Borba, Bruno Soares Moreira Cesar & da Costa, Isabella Vaz Leal & Júnior, Amaro Olimpio P, 2009. "The vulnerability of renewable energy to climate change in Brazil," Energy Policy, Elsevier, vol. 37(3), pages 879-889, March.
    13. Baranowski, Piotr & Gos, Magdalena & Krzyszczak, Jaromir & Siwek, Krzysztof & Kieliszek, Adam & Tkaczyk, Przemysław, 2019. "Multifractality of meteorological time series for Poland on the base of MERRA-2 data," Chaos, Solitons & Fractals, Elsevier, vol. 127(C), pages 318-333.
    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. Gómez-Gómez, Javier & Carmona-Cabezas, Rafael & Ariza-Villaverde, Ana B. & Gutiérrez de Ravé, Eduardo & Jiménez-Hornero, Francisco José, 2021. "Multifractal detrended fluctuation analysis of temperature in Spain (1960–2019)," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    2. Jessica B. Moraes & Henderson S. Wanderley & Rafael C. Delgado, 2023. "Areas susceptible to desertification in Brazil and projected climate change scenarios," 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. 116(2), pages 1463-1483, March.
    3. Nurulkamal Masseran, 2022. "Multifractal Characteristics on Temporal Maximum of Air Pollution Series," Mathematics, MDPI, vol. 10(20), pages 1-15, October.
    4. da Silva, Antonio Samuel Alves & Stosic, Tatijana & Arsenić, Ilija & Menezes, Rômulo Simões Cezar & Stosic, Borko, 2023. "Multifractal analysis of standardized precipitation index in Northeast Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 172(C).
    5. Farhang Rahmani & Mohammad Hadi Fattahi, 2021. "A multifractal cross-correlation investigation into sensitivity and dependence of meteorological and hydrological droughts on precipitation and temperature," 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. 109(3), pages 2197-2219, December.
    6. Gómez-Gómez, Javier & Carmona-Cabezas, Rafael & Sánchez-López, Elena & Gutiérrez de Ravé, Eduardo & Jiménez-Hornero, Francisco José, 2022. "Multifractal fluctuations of the precipitation in Spain (1960–2019)," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    7. Milena Kojić & Petar Mitić & Marko Dimovski & Jelena Minović, 2021. "Multivariate Multifractal Detrending Moving Average Analysis of Air Pollutants," Mathematics, MDPI, vol. 9(7), pages 1-17, March.

    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. Santos, Fábio Sandro dos & Nascimento, Kerolly Kedma Felix do & Jale, Jader da Silva & Stosic, Tatijana & Marinho, Manoel H.N. & Ferreira, Tiago A.E., 2021. "Mixture distribution and multifractal analysis applied to wind speed in the Brazilian Northeast region," Chaos, Solitons & Fractals, Elsevier, vol. 144(C).
    2. Méndez-Gordillo, Alma Rosa & Cadenas, Erasmo, 2021. "Wind speed forecasting by the extraction of the multifractal patterns of time series through the multiplicative cascade technique," Chaos, Solitons & Fractals, Elsevier, vol. 143(C).
    3. Jiang, Lei, 2018. "Mean wind speed persistence over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 211-217.
    4. Delbianco, Fernando & Tohmé, Fernando & Stosic, Tatijana & Stosic, Borko, 2016. "Multifractal behavior of commodity markets: Fuel versus non-fuel products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 573-580.
    5. Gómez-Gómez, Javier & Carmona-Cabezas, Rafael & Sánchez-López, Elena & Gutiérrez de Ravé, Eduardo & Jiménez-Hornero, Francisco José, 2022. "Multifractal fluctuations of the precipitation in Spain (1960–2019)," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    6. Wang, Jian & Huang, Menghao & Wu, Xinpei & Kim, Junseok, 2023. "A local fitting based multifractal detrend fluctuation analysis method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    7. Darko Stosic & Dusan Stosic & Irena Vodenska & H. Eugene Stanley & Tatijana Stosic, 2021. "A new look at calendar anomalies: Multifractality and day of the week effect," Papers 2106.06164, arXiv.org.
    8. Zunino, Luciano & Figliola, Alejandra & Tabak, Benjamin M. & Pérez, Darío G. & Garavaglia, Mario & Rosso, Osvaldo A., 2009. "Multifractal structure in Latin-American market indices," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2331-2340.
    9. Lu, Feiyu & Yuan, Naiming & Fu, Zuntao & Mao, Jiangyu, 2012. "Universal scaling behaviors of meteorological variables’ volatility and relations with original records," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4953-4962.
    10. Tzanis, Chris G. & Kalamaras, Nikolaos & Philippopoulos, Kostas & Deligiorgi, Despina, 2022. "The multifractal nature of dew point," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    11. Zhang, Xiaonei & Zeng, Ming & Meng, Qinghao, 2018. "Multivariate multifractal detrended fluctuation analysis of 3D wind field signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 513-523.
    12. Nagarajan, Radhakrishnan & Kavasseri, Rajesh G., 2005. "Minimizing the effect of periodic and quasi-periodic trends in detrended fluctuation analysis," Chaos, Solitons & Fractals, Elsevier, vol. 26(3), pages 777-784.
    13. Stosic, Tatijana & Telesca, Luciano & Stosic, Borko, 2021. "Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    14. Guan, Sihai & Wan, Dongyu & Yang, Yanmiao & Biswal, Bharat, 2022. "Sources of multifractality of the brain rs-fMRI signal," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    15. de Benicio, Rosilda B. & Stošić, Tatijana & de Figueirêdo, P.H. & Stošić, Borko D., 2013. "Multifractal behavior of wild-land and forest fire time series in Brazil," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6367-6374.
    16. Thiago B. Murari & Aloisio S. Nascimento Filho & Marcelo A. Moret & Sergio Pitombo & Alex A. B. Santos, 2020. "Self-Affine Analysis of ENSO in Solar Radiation," Energies, MDPI, vol. 13(18), pages 1-17, September.
    17. Zhang, Guofu & Li, Jingjing, 2018. "Multifractal analysis of Shanghai and Hong Kong stock markets before and after the connect program," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 611-622.
    18. Jiang, Lei & Zhang, Jiping & Liu, Xinwei & Li, Fei, 2016. "Multi-fractal scaling comparison of the Air Temperature and the Surface Temperature over China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 783-792.
    19. Zeng, Yayun & Wang, Jun & Xu, Kaixuan, 2017. "Complexity and multifractal behaviors of multiscale-continuum percolation financial system for Chinese stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 364-376.
    20. Garnier, Josselin & Solna, Knut, 2019. "Chaos and order in the bitcoin market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 708-721.

    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:549:y:2020:i:c:s0378437120301114. 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.