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New climatic zones in Iran: a comparative study of different empirical methods and clustering technique

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Abstract

Recently in agricultural and industrial sectors, researchers have started to classify the climate of a region using empirical methods and clustering. This study aims to compare four empirical approaches to climate classification (Thornthwaite and Mather, De Martonne, the Extended De Martonne, and the IRIMO (I.R. of Iran Meteorological Organization)) with Ward’s hierarchical agglomerative clustering applied to the climate of Iran. The dataset used in this study comprises maximum and minimum temperatures and precipitation data of 356 weather stations extracted from IRIMO’s databases. Thirty-five synoptic weather stations are selected among 356 stations. These stations are selected regarding the best uniform distribution, elevation, windward and leeward sides of the mountain ranges, and availability of a continuous 50-year data (1966–2015). Compared with the other three empirical reference methods of climate classification, the Thornthwaite and Mather method emphasizes the role of water bodies and air masses in determining the climate type of a region. Highlighting these two factors is identified as the main advantage of this method over the other three. This advantage is the most noticeable for the highlands/mountainous regions, in the vicinity of the Zagros Mountains, and in the western regions of Iran. As a case in point, while in the De Martonne and the Extended De Martonne methods, the Zagros storm cell is climatically classified similar to patchy areas in Caspian Sea coastal zone, this cell is correctly identified as a separate zone in the Thornthwaite and Mather method. The results also reveal that the clusters obtained from Ward’s algorithm are comparable to those of empirical climate classifications, particularly Thornthwaite and Mather method.

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The data that support the findings of this study are available on request from the corresponding author.

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Acknowledgements

The authors gratefully acknowledge the I.R. of Iran Meteorological Organization (IRIMO) for providing meteorological data from synoptic stations.

Funding

This research was supported by Iran National Science Foundation (INSF) by grant No. 2016/95838893.

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Authors and Affiliations

  1. Agricultural Climatology, Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran

    Faezeh Abbasi

  2. Department of Physical Geography, Faculty of Geography, University of Tehran, Tehran, Iran

    Saeed Bazgeer

  3. Iran Meteorological Organization (IRIMO), Tehran, Iran

    Parviz Rezazadeh Kalehbasti & Masoud Haghighat

  4. Department of Agricultural Meteorology, Atmospheric Science and Meteorological Research Center, Tehran, Iran

    Ebrahim Asadi Oskoue

  5. Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA

    Pouya Rezazadeh Kalehbasti

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  1. Faezeh Abbasi
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Contributions

Material preparation and data collection were performed by Faezeh Abbasi and Saeed Bazgeer. The statistical analysis was done by Saeed Bazgeer, Ebrahim Asadi Oskoue, and Masoud Haghighat. The first draft of the manuscript was prepared by Faezeh Abbasi, Saeed Bazgeer, and Parviz Rezazadeh Kalehbasti. The interpretation of the maps was done by Saeed Bazgeer, Parviz Rezazadeh Kalehbasti, Ebrahim Asadi Oskoue, and Masoud Haghighat. The final version of manuscript was written by Saeed Bazgeer, Parviz Rezazadeh Kalehbasti, and Pouya Rezazadeh Kalehbasti.

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Correspondence to Saeed Bazgeer.

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The original online version of this article was revised: The author name Pouya Rezazadeh Kalehbasti was incorrectly written as Pouya Rezazadeh Kalebasti.

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Abbasi, F., Bazgeer, S., Kalehbasti, P.R. et al. New climatic zones in Iran: a comparative study of different empirical methods and clustering technique. Theor Appl Climatol 147, 47–61 (2022). https://doi.org/10.1007/s00704-021-03785-9

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