- Wednesday, Oct 29th, 2025
International Journal of Advanced Research in Arts, Science, Engineering & Management (IJARASEM)
(A High Impact Factor, Monthly, Peer Reviewed Journal)
(A High Impact Factor, Monthly, Peer Reviewed Journal)
| TITLE | Statistical Analysis of Historical Global Temperature Data for Future Projection |
|---|---|
| ABSTRACT | Climate change and global warming are among the most pressing challenges facing humanity today. Accurate forecasting of temperature trends is essential for understanding climate dynamics and informing policy decisions. This paper presents a data-driven approach using Singular Spectrum Analysis (SSA) to analyse and forecast the Land Average Temperature (LAT) time series. SSA is a powerful non-parametric technique that decomposes a time series into interpretable components such as trends, periodicities, and noise, enabling effective noise reduction and improved forecasting accuracy. We apply SSA to the Global Temperatures dataset, which contains monthly land temperature records spanning over two centuries. The methodology involves constructing a trajectory matrix, performing singular value decomposition, grouping elementary matrices based on their w-correlation, and reconstructing the time series components. We then use the reconstructed components to forecast future temperature values. Experimental results demonstrate that SSA effectively captures the underlying temperature dynamics and seasonal patterns, providing reliable short-term forecasts. The SSA-based forecast outperforms naive persistence models in terms of mean squared error, highlighting its potential for climate data analysis and forecasting. This study contributes to the growing body of literature on SSA applications in environmental science and offers a robust framework for analysing complex, noisy climate time series. |
| AUTHOR | Dr.S.Gnanapriya, Prasya.P Assistant Professor, Department of Computer Applications, Nehru College of Management, Coimbatore, Tamil Nadu, India Student of II MCA, Department of Computer Applications, Nehru College of Management, Coimbatore, Tamil Nadu, India |
| PUBLICATION DATE | 2025-10-27 |
| VOLUME | 12 |
| ISSUE | 5 |
| 19_Statistical Analysis of Historical Global Temperature Data for Future Projection.pdf | |
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