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Statistical analysis of rainfall and temperature (1901–2016) in south-east Asian countries

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Abstract

The present paper investigates the time-series properties of average rainfall and temperature readings of countries in Southeast Asia (Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, Timor-Leste, and Vietnam) using monthly data, spanning from 1901 to 2016. Specifically, we analyze the time trend, persistence, and seasonality properties of the series using I(d) fractional integration framework, an approach that is found to be robust in dealing with climatological series. Antipersistence is observed in the rainfall series of Cambodia, Laos, Myanmar, and Vietnam while long memory is found in the rainfall series of the remaining countries. Thus, those countries with antipersistent rainfall are prone to erratic rainfall distribution which could lead to flooding or drought. Long memory is observed in the distribution of rainfall across all countries with increasing trend found in some cases. Both climatic variables display evidence supporting seasonality with stronger seasonality observed in Cambodia, Laos, Myanmar, Thailand, and Vietnam. Findings in the present paper are of policy relevance to climate monitoring agencies and the government.

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Notes

  1. A tropical climate has a mean temperature above 18 °C, and the temperature is almost constant throughout the year. The climate is characterized by wet and dry seasons with rainfall throughout the year.

  2. https://www.worldatlas.com/articles/what-type-of-climate-prevails-over-the-southeast-asian-region.html.

  3. Monsoon is a seasonal reversing wind that causes changes in atmospheric circulation and precipitation associated with the asymmetric heating of land and sea.

  4. Himalayas is a range of mountains in Asia separating the plains of the Indian subcontinent from the Tibetan Plateau.

  5. https://en.wikipedia.org/wiki/Climate_of_Asia.

  6. See Hamilton (1994) and Gil-Alana (2012) for more details about the specification and estimation of equation (1).

  7. See Bloomfield and Nychka (1992).

  8. The I(d) model is developed in Granger (1980), Granger and Joyeux (1980) and Hosking (1981) as a follow-up work on the seminar papers of Adenstedt (1974) and Robinson (1978).

  9. Hurst (1951) applied the approach in modeling the River Nile overflows.

  10. Note, the SARMA model becomes the SFI model (otherwise called seasonal fractional noise process) when none of the AR and MA parameters is significant.

  11. The factorizations for Yit are given in detail in Beaulieu and Miron (1993).

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Acknowledgments

Comments from the Editor and anonymous reviewers are gratefully acknowledged.

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Authors and Affiliations

  1. Environmental Statistics Unit, Department of Statistics, University of Ibadan, Ibadan, Nigeria

    OlaOluwa S. Yaya

  2. Institute of Business Research, University of Economics Ho Chi Minh City, Ho Chi Minh City, Vietnam

    OlaOluwa S. Yaya

  3. Institute of Business Research & CFVG, University of Economics Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Xuan Vinh Vo

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  1. OlaOluwa S. Yaya
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Correspondence to OlaOluwa S. Yaya.

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Yaya, O.S., Vo, X.V. Statistical analysis of rainfall and temperature (1901–2016) in south-east Asian countries. Theor Appl Climatol 142, 287–303 (2020). https://doi.org/10.1007/s00704-020-03307-z

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