Enhanced Climate Forecasting in Northeastern Bangladesh using Hybrid SARIMA-ANN Models

This study is highly significant as it introduces an advanced hybrid seasonal ARIMA-ANN model to forecast climatic variables—rainfall, and temperature —in the Sylhet and Sreemongol region of Bangladesh. Accurate and reliable climate forecasts are critical for a variety of industries, particularly agriculture, public health, and disaster management, which are directly impacted by weather patterns. The hybrid model’s ability to capture both linear and nonlinear trends is an important advantage over standard forecasting methods. This study supports sustainable agricultural practices by giving precise forecasts, allowing farmers to better organize their activities and prevent potential losses due to severe weather conditions. Enhanced weather predictions also allow for better planning for extreme weather occurrences, lowering the danger to human lives and infrastructure. Furthermore, the insights acquired from this study will assist policymakers, enabling them build effective adaptation and mitigation plans to climate change. Overall, the study’s findings will enhance socio-economic resilience and promote sustainable development in Sylhet and Sreemongol regions, ensuring that communities are better equipped to handle the challenges posed by climate change.