Amalgamating Weather-related Indigenous Knowledge into Modern Forecasting Knowledge Adopted by Farmers on Climate Prediction

Abstract

Extreme climate change makes farming harder, especially in developing countries, and farmers use traditional and scientific forecasts to decide what to do in their agriculture industries. This work aims to outline farmers' weather forecasting knowledge systems for climate prediction. In addition, the incorporation of indigenous knowledge into modern weather forecasting methods used for agricultural planning is also interpreted. The ambient, natural, astronomical, and relief features could all be utilized to help predict the weather over short- and long-term timescales. Animal and insect behavior was considered good weather predictors, and astronomical features were used to forecast weather, notably rain, in a limited time frame. Generally, only some peers are familiar with traditional weather prediction methods. Traditional weather forecasting becomes less accurate as a result. Some variables influence meteorological unreliability using scientific methods and new details that will be filled with traditional approaches to achieving precise weather prediction. This study reveals that modern and traditional methods have pros and cons, which suggests that they can be used together to make more accurate weather forecasts for consumers. The disparity between weather forecasting techniques needs more advanced studies to comprehend how they have been incorporated into existing technical frameworks. The limitations of the advanced weather prediction approach and the vigor that indigenous knowledge methods can be elicited.