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Temperature Trend Analysis and Investigation on a Case of Variability Climate

Author

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  • Pietro Monforte

    (I.R.S.S.A.T. Institute for Research, Development and Experimentation on the Environment and the Territory, Via del Fornaio 7, 95033 Biancavilla, Italy
    These authors contributed equally to this work.)

  • Maria Alessandra Ragusa

    (Dipartimento di Matematica e Informatica, Universita di Catania, Viale Andrea Doria 6, 95125 Catania, Italy
    These authors contributed equally to this work.)

Abstract

Climate change is now evident on a global scale. In some regions, the phenomenon is especially amplified, generating different consequences for man and the environment. Sicily is one of the Mediterranean regions, the biggest in terms of area, where climatic variations produce significant effects. In this study, temperature trends on monthly time scales are examined in the time frame 1925–2015. The cluster analysis technique (Ward’s method) was used to homogenize the temperature series. The results show four statistically significant clusters, confirming the presence of climatic variability in the region. The non-parametric Mann–Kendall test was used to determine temperature trends. The non-parametric estimator Sen’s slope was used to quantify the variation of trends. The results showed the presence of statistically significant trends. A worrying and unexpected increase in temperatures was found during the winter period. This scenario was presented in three clusters, highlighting a mutation in the winter season, attributable to the climatic changes in progress rather than to territorial factors. If the trends maintain an increasing monotone character, in the coming decades there will be, in many areas of Sicily, a constant loss of fertile soil for the agricultural sector and the advancement of phenomena such as drought and desertification, to which the island is already predisposed. All of this will have serious socio-economic repercussions. Considering that a large part of the region’s economy is based on the agricultural sector, these repercussions will be followed by serious environmental implications that will negatively affect the ecological sustainability of the region.

Suggested Citation

  • Pietro Monforte & Maria Alessandra Ragusa, 2022. "Temperature Trend Analysis and Investigation on a Case of Variability Climate," Mathematics, MDPI, vol. 10(13), pages 1-13, June.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:13:p:2202-:d:846748
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    References listed on IDEAS

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    1. Sugar, Catherine A. & James, Gareth M., 2003. "Finding the Number of Clusters in a Dataset: An Information-Theoretic Approach," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 750-763, January.
    2. Mojtaba Shadmani & Safar Marofi & Majid Roknian, 2012. "Trend Analysis in Reference Evapotranspiration Using Mann-Kendall and Spearman’s Rho Tests in Arid Regions of Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(1), pages 211-224, January.
    3. Daniel Huppmann & Joeri Rogelj & Elmar Kriegler & Volker Krey & Keywan Riahi, 2018. "A new scenario resource for integrated 1.5 °C research," Nature Climate Change, Nature, vol. 8(12), pages 1027-1030, December.
    4. E. Arnone & Marco Cucchi & Sara Dal Gesso & Marcello Petitta & Sandro Calmanti, 2020. "Droughts Prediction: a Methodology Based on Climate Seasonal Forecasts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(14), pages 4313-4328, November.
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    Cited by:

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    5. Jinmeng Lee & Xiaojun Yin & Honghui Zhu & Xin Zheng, 2023. "Geographical Detector-Based Research of Spatiotemporal Evolution and Driving Factors of Oasification and Desertification in Manas River Basin, China," Land, MDPI, vol. 12(8), pages 1-20, July.

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