Spatial and Temporal Trend Analysis for Maximum and Minimum Temperature Using Non-Parametric Techniques
DOI:
https://doi.org/10.23910/1.2023.3371aKeywords:
Non-parametric test, season, spatio-temporal variation, temperature, trend analysisAbstract
A study on annual and seasonal (winter, spring, summer, and autumn) trend analysis of maximum and minimum temperature at the spatial and temporal scales had been carried out during January, 1981 to December, 2020 for agro-climatic zone-III of Bihar, India. Non-parametric statistical techniques viz. Mann-Kendall (MK) test with Sen’s slope estimator, and Pettitt Mann–Whitney (PMW) test had been carried out to examine the annual and seasonal trends at 5% level of significance. The monthly air temperature (°C) from the period January, 1981 to December, 2020 had been recorded for the spatial and temporal trend analysis. The results of the nonparametric tests showed statistically significant increasing trends in summer, autumn, and spring seasons for minimum temperature at most the spatial horizons while the trends for maximum temperature showed statistically non-significant decreasing trends at all the spatial horizons. The rate of change of the minimum temperature obtained from Sen’s slope estimator was found to be higher in summer (0.021°C year-1), autumn (0.054°C year-1), and spring (0.041°C year-1) seasons at Bhojpur district. In case of the maximum temperature, the rate of change of temperature was observed to be higher in annual (-0.020°C year-1), winter (-0.012°C year-1), summer (-0.019°C year-1), and autumn (-0.013°C year-1) seasons. The most probable year of changes in the observed temperature were occurred in between 1992–2010. In conclusion, it was clear that the magnitudes of the minimum temperature trends and variability is greater than the maximum temperature for all 6 spatial horizons.
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