Trend analysis and SARIMA forecasting of mean maximum and mean minimum monthly temperature for the state of Kerala, India

• Autorzy: Kabbilawsh P. , Sathish Kumar D. , Chithra N. R.

Identyfikatory

DOI

10.1007/s11600-020-00462-9

• Języki publikacji: EN

Abstrakty

EN

The development of temperature forecasting models for the state of Kerala using Seasonal Autoregressive Integrated Moving Average (SARIMA) method is presented in this article. Mean maximum and mean minimum monthly temperature data, for a period of 47 years, from seven stations, are studied and applied to develop the model. It is expected that the time-series datasets of temperature to display seasonality (and hence non-stationary), and a possible trend (due to the fact that the data spans 5 decades). Hence, the key step in the development of the models is the determination of the non-stationarity of the temperature time-series, and the transformation of the non-stationary time-series into a stationary time-series. This is carried out using the Seasonal and Trend decomposition using Loess technique and Kwiatkowski–Phillips–Schmidt–Shin test. Before carrying out this process, several preliminary tests are conducted for (1) fnding and flling the missing values, (2) studying the characteristics of the data, and (3) investigating the presence of the trend and seasonality. The non-stationary temperature time-series are transformed to stationary temperature time-series, by one seasonal diferencing and one frstorder diferencing. This information, along with the original time-series, is further utilized to develop the models using the SARIMA method. The parsimonious and best-ft SARIMA models are developed for each of the fourteen variables. The study revealed that SARIMA(2, 1, 1)(1, 1, 1)12 as the ideal forecasting model for eight out of the fourteen time-series datasets.

Słowa kluczowe

EN

autocorrelation function; ACF; partial autocorrelation function; Sen’s slope estimator; SARIMA; Mann–Kendall trend test; seasonal autoregressive integrated moving average; PACF

PL

funkcja autokorelacji; ACF; funkcja częściowej autokorelacji; estymator nachylenia Sena; SARIMA

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2020
• Tom: Vol. 68, no. 4
• Strony: 1161--1174
• Opis fizyczny: Bibliogr. 25 poz.

Twórcy

autor

Kabbilawsh P.

• Department of Civil Engineering, NIT Calicut, Calicut 673601, India

autor

Sathish Kumar D.

• Department of Civil Engineering, NIT Calicut, Calicut 673601, India

autor

Chithra N. R.

• Department of Civil Engineering, NIT Calicut, Calicut 673601, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021)