SARIMA Model-Based Maximum Temperature Forecasting in Bangladesh: A Data-Driven Evaluation from 1981 to 2024

Bangladesh is a tropical nation where there are notable seasonal temperature changes. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model is used in this study to forecast Bangladesh's maximum temperature from 2023 to 2042. The objective is to assess how rising temperatures can affect public health, energy consumption, and agriculture. Autocorrelation and partial autocorrelation analysis will be used to improve the model. Analysis was done using historical maximum temperature data spanning from 1981 to 2022. Forecasts were produced using the SARIMA model, whose parameters were chosen in accordance with plots of the autocorrelation function (ACF) and partial autocorrelation function (PACF). The model SARIMA (1,1,2)(0,0,1) is selected based on AIC. In order to account for forecast uncertainty, forecasts were created for the years 2023–2042. 95% prediction ranges were then calculated. Bangladesh's maximum temperatures are predicted by the SARIMA model to rise gradually, from roughly 33.75°C in 2023 to 34.17°C in 2042. With some degree of uncertainty, the 95% prediction intervals show a steady increasing trend between 33.53°C and 34.51°C. The anticipated increase in the highest temperatures has major consequences for Bangladesh. These results highlight how crucial it is to create adaptation plans and laws in order to lessen the effects of warming temperatures and increase resilience.

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Publication Details

Journal
American Journal of Biological and Environmental Statistics
Published
2024-10-18
DOI
https://doi.org/10.11648/j.ajbes.20241004.11
Citations
2
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
0.42
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article

SARIMA Model-Based Maximum Temperature Forecasting in Bangladesh: A Data-Driven Evaluation from 1981 to 2024

NHM. A. Azim, Sofi Mahmud Parvez, Mumtahin Taharima, Md. Rudman
2 citations
American Journal of Biological and Environmental Statistics
Energy Load and Power Forecasting
0.42
article

SARIMA Model-Based Maximum Temperature Forecasting in Bangladesh: A Data-Driven Evaluation from 1981 to 2024

NHM. A. Azim, Sofi Mahmud Parvez, Mumtahin Taharima, Md. Rudman
article en
2 citations

Abstract

Bangladesh is a tropical nation where there are notable seasonal temperature changes. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model is used in this study to forecast Bangladesh's maximum temperature from 2023 to 2042. The objective is to assess how rising temperatures can affect public health, energy consumption, and agriculture. Autocorrelation and partial autocorrelation analysis will be used to improve the model. Analysis was done using historical maximum temperature data spanning from 1981 to 2022. Forecasts were produced using the SARIMA model, whose parameters were chosen in accordance with plots of the autocorrelation function (ACF) and partial autocorrelation function (PACF). The model SARIMA (1,1,2)(0,0,1) is selected based on AIC. In order to account for forecast uncertainty, forecasts were created for the years 2023–2042. 95% prediction ranges were then calculated. Bangladesh's maximum temperatures are predicted by the SARIMA model to rise gradually, from roughly 33.75°C in 2023 to 34.17°C in 2042. With some degree of uncertainty, the 95% prediction intervals show a steady increasing trend between 33.53°C and 34.51°C. The anticipated increase in the highest temperatures has major consequences for Bangladesh. These results highlight how crucial it is to create adaptation plans and laws in order to lessen the effects of warming temperatures and increase resilience.

American Journal of Biological and Environmental StatisticsVol. 10(4)
Noakhali Science and Technology University (BD), Southeast University (BD)
Affordable and clean energy
Openalex Percentile: Top 37%
Energy Load and Power Forecasting
0.42
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