Climate change forecasting in Ranohira, southern of Madagascar, using linear and ARIMA models
- 1National Institute of Nuclear Science and Technology (INSTN- Madagascar), P.O 3901Antananarivo-101, Madagascar
- 2National Institute of Nuclear Science and Technology (INSTN- Madagascar), P.O 3901Antananarivo-101, Madagascar
- 3National Institute of Nuclear Science and Technology (INSTN- Madagascar), P.O 3901Antananarivo-101, Madagascar and Mention Physics and Applications, Faculty of Sciences - University of Antananarivo, Madagascar
- 4National Institute of Nuclear Science and Technology (INSTN- Madagascar), P.O 3901Antananarivo-101, Madagascar and Mention Physics and Applications, Faculty of Sciences - University of Antananarivo, Madagascar
- 5National Institute of Nuclear Science and Technology (INSTN- Madagascar), P.O 3901Antananarivo-101, Madagascar
- 6National Institute of Nuclear Science and Technology (INSTN- Madagascar), P.O 3901Antananarivo-101, Madagascar
Int. Res. J. Environment Sci., Volume 7, Issue (12), Pages 12-20, December,22 (2018)
The purpose of this work is to analyze the behavior of temperature and rainfall in Ranohira, southern of Madagascar, using climate data from 1961 to 2016 in order to predict future trend. Modeling and Forecasts have been performed using the ARIMA (Auto-Regressive Integrated Moving Average) model. The predictions concern the next 50 years. The data have been subdivided into 13 groups corresponding to each month of the year and the 13th group is the annual average. Before the application of the ARIMA modeling, we performed linear regressions to have a general view of the trends. Results showed that the average annual temperature is strictly increasing with a linear growth rate of about 0.2°C per decade. The mean of the average annual temperatures from 1961 to 2016 is 21.77°C. Total annual rainfall trend shows a decrease of about 47.2 mm per decade. The mean of annual precipitation from 1961 to 2016 is 917.26mm. Concerning the ARIMA modeling, each of the time series corresponding to the 13 groups of data can be fitted in ARIMA form model(1,1,1)(1,1,1)^S. The seasonal part of the model was exploited to have a good description of the fluctuations and the value of S was chosen to obtain the best model for each series. Forecast for the next 50 years permits to predict a significant increase of the average annual temperature which is expected to be equal to 23.94°C in 2066. The mean of the average annual temperatures between 2017 and 2066 is predicted to be equal to 22.8°C. The forecast also shows a decrease of 22.19 % in the mean annual precipitation for the 50 next years compared to the average of the observation years. The dry season, from April to September, will be the most affected, with a deficit of up to 90%. It is predicted that in 2066, the annual rainfall would be 470.18 mm against 605.9mm in 2016. The economic development of the Ihorombe region eventually requires strategies to deal with these future changes, especially in the water sector, which would be the most affected.
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