Forecast Modeling and Trend Analysis of Temperature in India

IF 0.7 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES
M. Meena
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引用次数: 0

Abstract

Since historical times, the climate of the earth has been changing. In terms of diversity and population, India is a vast country. Any significant change in its climatic conditions can have an impact on the country’s entire economic and cultural structure. Temperature is the most important variable when focussing on climate change study. This study aims to recognise the changing trend of temperature in India. For this purpose, temperature data from 1901 to 2020 has been analysed. To find out the variability in temperature, various statistical tools were applied. The Mann-Kendall method has been used along with Sen’s slope estimator for determining the trend and slope magnitude. ARIMA modelling is applied to the data series to forecast the temperature trend. The study has shown that variability in temperature is increasing in recent years and the temperature trend is increasing in all the months, especially in the cold months of November, December and January. The average annual temperature of India in the year has increased significantly in the past 120 years. The trend analysis of temperature is tested significantly statistically at a 95% confidence level.
印度气温预测模型及趋势分析
自古以来,地球的气候一直在变化。就多样性和人口而言,印度是一个幅员辽阔的国家。气候条件的任何重大变化都可能对该国的整个经济和文化结构产生影响。在气候变化研究中,温度是最重要的变量。这项研究旨在认识印度温度的变化趋势。为此,分析了1901年至2020年的温度数据。为了找出温度的变化,使用了各种统计工具。Mann-Kendall方法已与Sen斜率估计器一起用于确定趋势和斜率大小。采用ARIMA模型对数据序列进行温度趋势预测。研究表明,近年来气温变异性呈上升趋势,各月份气温变化趋势均呈上升趋势,尤其是11月、12月和1月的寒冷月份。在过去的120年里,印度的年平均气温明显上升。温度的趋势分析在95%的置信水平上进行了显著的统计检验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Climate Change
Journal of Climate Change METEOROLOGY & ATMOSPHERIC SCIENCES-
自引率
16.70%
发文量
18
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