
This record contains the article "Forecasting Atmospheric CO2 Concentrations Using SARIMA Models: Insights from Time-Series Analytics" by Hemanth Kori. The paper analyses weekly CO2 concentrations at Mauna Loa Observatory (1958-2001) using a seasonal ARIMA model. The time series is decomposed into trend, seasonal and residual components, and the model is trained on 1958-1997 data and tested on 1998-2001. Forecasts achieve mean absolute error of about 1.07 ppm and RMSE of about 1.20 ppm, and two-year projections suggest levels above 370 ppm by the end of 2003. The study discusses the relevance of classical time-series methods amid emerging AI-driven analytics. Figures and code for the analysis are included.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
