Precipitation forecast estimation applying the change point method and ARIMA

Abstract

In this study, a time series is analyzed with daily historical data from 1989 to December 2021 of the precipitation variable with a total of 12,053 observations, these data are obtained from the Tunguativa weather station located in Paipa a small town in Colombia. For this research, the records of the ‘precipitation’ variable were taken into account. The objective was to analyze the trends, use the data until 31 December 2020, to estimate a forecast for the year 2021. The observed data is provided by the weather station, and the data of the year 2021 are compared with the data forecast by the Arima method and the change point. Finally, statistical tests are carried out to contrast the degree of similarity of the data obtained from the forecasts with the real data produced by the station. This study can be used to estimate precipitation forecasts and avoid environmental damage.

Keywords:

• ARIMA
• change point
• forecast
• precipitation
• time series

Reviewing Editor:

• Qingsong Ai, Wuhan University of Technology, China

Subjects:

• meteorology
• environmental studies
• research methods in environmental studies
• statistics & computing
• general engineering education

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Juan Camilo Valderrama Balaguera

Juan Camilo Valderrama Balaguera, a professional in aeronautical engineering with a postgraduate degree in production and operations management and a master’s degree in industrial engineering. Currently director of the industrial engineering program and member of the LOGyCA research group at the Universidad de Boyacá, Tunja, Colombia. Research areas Logistics, simulation, production and operations planning and scheduling.