Intelligent Analytics for Environmental Sustainability and Energy Optimization Predictive Analytics for Climate Change Mitigation

Climate change is a global phenomenon characterized by significant warming trends, changed precipitation patterns, melting glaciers, extreme weather events, and rising sea levels. These changes are particularly influenced by human activities such as emission of greenhouse gases from fossil fuel combustion, deforestation, and industrial processes. The Arctic regions are experiencing temperature increase at nearly double the global average, affecting hydrological systems. The decade from 2012 to 2021 was approximately 2°F (1.1°C) warmer than the pre-industrial period (1850–1900). The increasing frequency and intensity of extreme weather events, such as heatwaves, hurricanes, and wildfires, further exemplify current climate trends. For instance, the recent wildfires in Los Angeles have caused significant devastation. Climate changes significantly affect both the environment and human society. These changes impact through changes in weather patterns, biodiversity loss, and socio-economic challenges. The economic burden of climate changes is unevenly distributed, with those least responsible and vulnerable populations facing the most severe consequences. Predictive analytics serves as the essential factor for successful risk and opportunity assessment of climate-related matters. Several obstacles exist which prevent the analysis of climate data to evaluate predictive analytics opportunities. Efficient processing and integration of many data sources are necessary due to the massive amounts of data being generated. The volume of climate data frequently exceeds terabytes and petabytes, making analysis and storage challenging. Inadequate data management approaches make it clear that advanced solutions must be developed to solve the existing problem. Modern systems need to be established as a means to facilitate effective data management.