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Analyzing WSTP trend: a new method for global warming assessment

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Abstract

This paper tries to introduce a time-series of temperature parameters as a potential method for studying the global warming. So, we investigated the spatial–temporal variations of warm-season temperature parameters (WSTP), including start time, end time, length of season, base value, peak time, peak value, amplitude, large integrated value, right drive, and left drive, using a database of 30 years’ period in different climates of Iran. We used daily temperature data from 1989 to 2018 over Iran to extract the parameters by TIMESAT software. We studied the trend analysis of WSTP through the Mann–Kendall method. Then, we considered the Pearson correlation coefficient to calculate the correlation between WSTP and time. We assessed the trends of the slope using a simple linear regression method. Then, we compared the results of the WSTP trend analysis in climatic zones. Our results accused the hyper-arid climatic zone has the longest warm season (194.89 days a year). The warm season in this region starts earlier than other regions and increases with moderate speed (left drive, 0.19 °C day−1). Then, it reaches a peak value (31.3 °C) earlier than the different climatic zones. On the other hand, the humid regions’ warm season starts with the shortest length and ends later than the other climatic zones (112.1 and 297.5 days a year for start and end times, respectively). We detected that the trend of the start time parameter has decreased by 98.02% of the study area during the last 30 years. The base value, length, and large integrated value parameters have an increasing trend of 66.47%, 80.11%, and 92.95% in Iran. The highest correlation coefficient with time was for start time and large integrated value parameters. Hence, the start time and large integrated value parameters have almost the most negative (< − 0.5) and positive (> 5) trend slope, among other parameters, respectively. In general, these results demonstrate that the studied region has faced global warming impacts over time by increasing the warm season and thermal energy, especially in arid and hyper-arid. We highlight the necessity of planning the land use under the high natural vulnerability of the studied local, especially in this new age of global warming.

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Notes

  1. - International Panel on Climate Change.

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Acknowledgements

The authors are grateful to the Iran Meteorological Organization (IRIMO) for providing the meteorological data and the Forests, Range and Watershed Management Organization of Iran for giving the climatic map of Iran for this study.

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Authors and Affiliations

  1. Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Tehran, Iran

    Esmail Heydari Alamdarloo, Ehsan Moradi, Mahsa Abdolshahnejad, Yalda Fatahi & Hassan Khosravi

  2. Department of Environmental Engineering, Institute of Sciences and Technology of Sorocaba, São Paulo State University (UNESP), Sorocaba, SP, Brazil

    Alexandre Marco da Silva

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  1. Esmail Heydari Alamdarloo
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  2. Ehsan Moradi
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  3. Mahsa Abdolshahnejad
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  4. Yalda Fatahi
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  5. Hassan Khosravi
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  6. Alexandre Marco da Silva
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Contributions

Formal analysis: EHA. Methodology: EHA, EM. Resources: MA, YF. Software: EHA, EM, YF. Supervision: HK. Writing—original draft: MA. Writing—review and editing: HK, AMdS.

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Correspondence to Hassan Khosravi.

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Heydari Alamdarloo, E., Moradi, E., Abdolshahnejad, M. et al. Analyzing WSTP trend: a new method for global warming assessment. Environ Monit Assess 193, 806 (2021). https://doi.org/10.1007/s10661-021-09600-2

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