Enhancing Climate Analysis with Integrated Data and Transparent AI Methods via Stochastic Processes

Climate change studies can help predict the future of Earth's ecosystems more accurately. This study introduces a new paradigm for climate analysis by combining stochastic processes with open-source artificial intelligence (AI) technologies and integrating data from several sources. We can combine weather stations, satellites, and other data sources to create a more comprehensive picture of climatic trends and their inherent variability. To capture the inherent uncertainty in climate systems, the AI model incorporates stochastic processes to describe future climate projection uncertainty. Additionally, AI methods that are open and honest about the reasoning behind their decisions make it easy to understand how the model arrived at its decisions. This integrated approach will improve the reliability and efficiency of climate analysis, allowing policymakers to better prepare for and respond to climate change.