Abstract

Predictive modeling has transformed the way climate change is being approached, especially in Africa, where the climate impacts are already extreme. Integrating climatic data with machine learning and modern models has helped the researchers of the climate modeling science to come up with efficient predictions about weather. Such predictions also help in food security and development of renewable energy in Africa. These models combine information from many disciplines and have brought about many significant changes. The application of the predictions is vast. For example, weather prediction in Africa based on past climatic data and machine learning is very challenging due to many climatic zones, from arid land to humid tropics.Traditional models fail because of lack of information, but machine learning could detect anomalies in data which were hard to find out traditionally. Therefore accurate short and long range predictions can be done to help agriculture, infrastructure and resource management and even in predicting weather events like flood, drought, heat waves etc. Climate models can also predict effects of climate change on agriculture and food security. African agriculture is extremely vulnerable to climatic variations and is the sole means of survival for millions in Africa. Climate modeling helps simulate conditions under a range of scenarios which can aid in planning for such situations and also help the agriculture community adapt by planting climate resilient crops and managing resources effectively. Early warning systems have also been developed on the principles of weather modeling, which can warn against frequent disasters like floods and droughts that often result in loss of lives. The weather modeling helps collect vital information such as the amount of rainfall and hydrological factors that help predict the event with some time prior notice, enabling efficient preparation and planning to counter it.Lastly the effect of weather pattern on renewable energy sources like hydro, solar and wind is very high and as we all know Africa is rich in all these sources. The prediction modeling has the potential to determine the best possible conditions that are required for maximum output from these sources, even in changing climate, hence optimizing future energy production planning and hence promoting green energy, the need of the hour.