IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v39y2009i4p1764-1789.html
   My bibliography  Save this article

Wavelet based correlation coefficient of time series of Saudi Meteorological Data

Author

Listed:
  • Rehman, S.
  • Siddiqi, A.H.

Abstract

In this paper, wavelet concepts are used to study a correlation between pairs of time series of meteorological parameters such as pressure, temperature, rainfall, relative humidity and wind speed. The study utilized the daily average values of meteorological parameters of nine meteorological stations of Saudi Arabia located at different strategic locations. The data used in this study cover a period of 16 years between 1990 and 2005. Besides obtaining wavelet spectra, we also computed the wavelet correlation coefficients between two same parameters from two different locations and show that strong correlation or strong anti-correlation depends on scale. The cross-correlation coefficients of meteorological parameters between two stations were also calculated using statistical function. For coastal to costal pair of stations, pressure time series was found to be strongly correlated. In general, the temperature data were found to be strongly correlated for all pairs of stations and the rainfall data the least.

Suggested Citation

  • Rehman, S. & Siddiqi, A.H., 2009. "Wavelet based correlation coefficient of time series of Saudi Meteorological Data," Chaos, Solitons & Fractals, Elsevier, vol. 39(4), pages 1764-1789.
    • Handle: RePEc:eee:chsofr:v:39:y:2009:i:4:p:1764-1789
    DOI: 10.1016/j.chaos.2007.06.054
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077907004328
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2007.06.054?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. Patrice Abry & Darryl Veitch & Patrick Flandrin, 1998. "Long‐range Dependence: Revisiting Aggregation with Wavelets," Journal of Time Series Analysis, Wiley Blackwell, vol. 19(3), pages 253-266, May.
    2. Razdan, Ashok, 2004. "Wavelet correlation coefficient of ‘strongly correlated’ time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 333(C), pages 335-342.
    3. Chang, Ching-Cheng, 2002. "The potential impact of climate change on Taiwan's agriculture," Agricultural Economics, Blackwell, vol. 27(1), pages 51-64, May.
    Full references (including those not matched with items on IDEAS)

    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. Soltani, Shiva & Mosavi, Seyed Habibollah & Saghaian, Sayed H. & Azhdari, Somayeh & Alamdarlo, Hamed N. & Khalilian, Sadegh, 2023. "Climate change and energy use efficiency in arid and semiarid agricultural areas: A case study of Hamadan-Bahar plain in Iran," Energy, Elsevier, vol. 268(C).
    2. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    3. Ahmad, Munir & Nawaz, Muhammad & Iqbal, Muhammad & Javed, Sajid, 2014. "Analysing the Impact of Climate Change on Rice Productivity in Pakistan," MPRA Paper 72861, University Library of Munich, Germany.
    4. Kung, Chih-Chun & Wu, Tao, 2021. "Influence of water allocation on bioenergy production under climate change: A stochastic mathematical programming approach," Energy, Elsevier, vol. 231(C).
    5. Vasile Brătian & Ana-Maria Acu & Camelia Oprean-Stan & Emil Dinga & Gabriela-Mariana Ionescu, 2021. "Efficient or Fractal Market Hypothesis? A Stock Indexes Modelling Using Geometric Brownian Motion and Geometric Fractional Brownian Motion," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    6. Das, Debojyoti & Bhowmik, Puja & Jana, R.K., 2018. "A multiscale analysis of stock return co-movements and spillovers: Evidence from Pacific developed markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 379-393.
    7. Severen, Christopher & Costello, Christopher & Deschênes, Olivier, 2018. "A Forward-Looking Ricardian Approach: Do land markets capitalize climate change forecasts?," Journal of Environmental Economics and Management, Elsevier, vol. 89(C), pages 235-254.
    8. Sarker, Md. Abdur Rashid & Alam, Khorshed & Gow, Jeff, 2012. "Exploring the relationship between climate change and rice yield in Bangladesh: An analysis of time series data," Agricultural Systems, Elsevier, vol. 112(C), pages 11-16.
    9. Abul Quasem Al-Amin & Walter Leal Filho, 2014. "A return to prioritizing needs: Adaptation or mitigation alternatives?," Progress in Development Studies, , vol. 14(4), pages 359-371, October.
    10. Zhou, Li & Turvey, Calum G., 2014. "Climate change, adaptation and China's grain production," China Economic Review, Elsevier, vol. 28(C), pages 72-89.
    11. Kung, Chih-Chun & Cao, Xiaoyong & Choi, Yongrok & Kung, Shan-Shan, 2019. "A stochastic analysis of cropland utilization and resource allocation under climate change," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    12. Chih-Chun Kung & Meng-Shiuh Chang, 2015. "Effect of Agricultural Feedstock to Energy Conversion Rate on Bioenergy and GHG Emissions," Sustainability, MDPI, vol. 7(5), pages 1-15, May.
    13. Chih-Chun Kung & Bruce A. McCarl & Chi-Chung Chen, 2014. "An Environmental and Economic Evaluation of Pyrolysis for Energy Generation in Taiwan with Endogenous Land Greenhouse Gases Emissions," IJERPH, MDPI, vol. 11(3), pages 1-19, March.
    14. Zeenatul Islam & Mohammad Alauddin & Md. Abdur Rashid Sarker, 2017. "Farmers’ perception on climate change-driven rice production loss in drought-prone and groundwater-depleted areas of Bangladesh: An ordered probit analysis," Discussion Papers Series 579, School of Economics, University of Queensland, Australia.
    15. Kung, Chih-Chun & Mu, Jianhong E., 2019. "Prospect of China's renewable energy development from pyrolysis and biochar applications under climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    16. Azari, Lotfali & Naji Meidani, Aliakbar & Salehnia, Narges, 2024. "Predicting the Impact of Climate Conditions on the Economic Production of Iranian Provinces with The Approach of Random Forest Algorithm," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 11(2), pages 1-34, September.
    17. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    18. Chiu, Mei-Shiu, 2013. "Tensions in implementing the “energy-conservation/carbon-reduction” policy in Taiwanese culture," Energy Policy, Elsevier, vol. 55(C), pages 415-425.
    19. Dan Wang & Yu Hao & Jianpei Wang, 2018. "Impact Of Climate Change On China’S Rice Production — An Empirical Estimation Based On Panel Data (1979–2011) From China’S Main Rice-Producing Areas," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 63(03), pages 535-553, June.
    20. Chebil, Ali & Mtimet, Nadhem & Tizaoui, Hassen, 2011. "Impact du changement climatique sur la productivité des cultures céréalières dans la région de Béja (Tunisie)," African Journal of Agricultural and Resource Economics, African Association of Agricultural Economists, vol. 6(2), pages 1-11, September.

    More about this item

    Statistics

    Access and download statistics

    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:chsofr:v:39:y:2009:i:4:p:1764-1789. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.