Performance comparison of filtering methods on modelling and forecasting the total precipitation amount: a case study for Mugla in Turkey

Yozgatlıgil, Ceylan
Condensed water vapor in the atmosphere is observed as precipitation whenever moist air rises sufficiently enough to produce saturation, condensation, and the growth of precipitation particles. It is hard to measure the amount and concentration of total precipitation over time due to the changes in the amount of precipitation and the variability of climate. As a result of these, the modelling and forecasting of precipitation amount is challenging. For this reason, this study compares forecasting performances of different methods on monthly precipitation series with covariates including the temperature, relative humidity, and cloudiness of Mula region, Turkey. To accomplish this, the performance of multiple linear regression, the state space model (SSM) via Kalman Filter, a hybrid model integrating the logistic regression and SSM models, the seasonal autoregressive integrated moving average (SARIMA), exponential smoothing with state space model (ETS), exponential smoothing state space model with Box-Cox transformation-ARMA errors-trend and seasonal components (TBATS), feed-forward neural network (NNETAR) and Prophet models are all compared. This comparison has yet to be undertaken in the literature. The empirical findings overwhelmingly support the SSM when modelling and forecasting the monthly total precipitation amount of the Mula region, encouraging the time-varying coefficients extensions of the precipitation model.


Performance comparison of filtering methods on modelling and forecasting total precipitation amount
Ünal, Ecem; Yozgatlıgil, Ceylan; Department of Statistics (2019)
The performance of condensed water vapour in the atmosphere observed as precipitation on the earth surface with the consequence of gravity. It is hard to observe and measure the amount and concentration of total precipitation with its all types changing over time. This difficulty can be explained by the association between the changing amount of precipitation and the variability in the climate with its both causes and consequences. As a result of these factors, modelling and forecasting of monthly total pre...
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Citation Formats
S. NESLİHANOĞLU, E. ÜNAL, and C. Yozgatlıgil, “Performance comparison of filtering methods on modelling and forecasting the total precipitation amount: a case study for Mugla in Turkey,” JOURNAL OF WATER AND CLIMATE CHANGE, pp. 0–0, 2021, Accessed: 00, 2021. [Online]. Available: