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Temporal, Spatial Characteristics and Prediction of Precipitation in Guangzhou Based on the SARIMA Model
- 1 Henan University, Kaifeng, China
* Author to whom correspondence should be addressed.
Abstract
This article obtains nearly 18 years of precipitation data for Guangzhou from the National Centers for Environmental Information (NCEI) under the National Oceanic and Atmospheric Administration (NOAA) and conducts visualization analysis and modeling predictions using R software.Using the classic SARIMA model (the ARIMA model with seasonal components) as well as regression and residual ARIMA models to build and simulate the precipitation series.We also used Basic-bootstrap prediction, which involves resampling the residuals of the fitted model with replacement, using historical values to predict the future and obtain a model parameter, as well as Full-bootstrap prediction (which assumes that the residuals have uncertainty and that the estimated model coefficients themselves also have uncertainty).Therefore, not only are reasonable model residuals obtained through the bootstrap method, but multiple model parameters are also derived from this method to determine more reasonable model parameters, which are then used to forecast the next 12 periods for the fitted model. Comparing the results of the four prediction models, the Full-bootstrap model under the regression model showed the best predictive performance. The study found that there is no significant trend in precipitation changes over time, but short-term fluctuations still exist. Although some extreme values appeared, they remain within a predictable range.Therefore, the relevant city government departments prone to extreme rainfall can make reasonable adjustments to drainage facilities based on local precipitation forecasts
Keywords
SARIMA model, precipitation, bootstrap method, seasonality, regression and residual ARIMA model, R language
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Cite this article
Yang,R. (2025). Temporal, Spatial Characteristics and Prediction of Precipitation in Guangzhou Based on the SARIMA Model. Theoretical and Natural Science,87,52-61.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 4th International Conference on Computing Innovation and Applied Physics
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