Modeling and predicting the patterns of seasonal rainfall in Tamil Nadu, India 1951–2017: an UCM approach

Arabian Journal of Geosciences(2020)

引用 5|浏览7
暂无评分
摘要
The main objective of the paper is to investigate the behavior, modeling, and predicting the patterns of the seasonal rainfall in Tamil Nadu using the unobserved components model (UCM) with the concealed components drift, seasonal, cyclical, and irregular. The India Meteorological Department (IMD) has provided the seasonal rainfall data of Tamil Nadu (TN), and the analysis has been done for winter, pre-monsoon, monsoon, and post-monsoon seasons. The UCM with deterministic components drift, cycle, and trigonometric seasonal and stochastic irregular component is selected for predicting the patterns of seasonal rainfall in TN from the parsimonious models based on the significant tests of free parameters and components, information criteria, and statistical fit. The maximum likelihood estimation is used for the model parameters, and the validity of the chosen model is resolved through normal and correlation diagnostics. The patterns of seasonal rainfall are predicted with 95% confidence interval during the years 2018–2020 in virtue of selected UCM. The identified UCM forecasts the winter rainfall around 11.12 mm in 2018, 8.57 mm in 2019, and 19.3 mm in 2020; pre-monsoon rainfall will be 132.72 mm in 2018, 116.74 mm in 2019, and 107.62 mm in 2020; monsoon rainfall will be 354.16 mm in 2018, 349.52 mm in 2019, and 334.65 mm in 2020; post-monsoon rainfall will be 440.84 mm in 2018, 454.68 mm in 2019, and 457.1 mm in 2020.
更多
查看译文
关键词
Rainfall,Information criteria,Normal and correlation diagnostics
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要