Climate change is a slowly emerging problem and requires advanced technologies to monitor its effects as well as to address them appropriately. Through compilation and analysis of climate change data the AGI and deep learning in drones will be addressed in this chapter. An autonomous system uses GPUs to handle large and complex data sets, a factor that makes deep learning crucial in analyzing complex climate databases. Drones equipped with AGI or intelligence capabilities provide a major leap forward in the ability to use real-time data gathering and analytical methods to measure the state of environments on different surfaces. The considerations made by the study focus on the concept of deep neural networks and the roles of different layer and activation functions in terms of climate data. It remains a necessary element for these networks to identify patterns and forecast when changes will take place for purposes of weather forecasting among other things, environmental monitoring. In addition, the chapter also elaborates on maintaining data quality and homogeneity, which is very important when analyzing climate information data. The integration of deep learning and AGI in drone technology promotes not only high degrees of accuracy in predictions but immediate actionable intelligence, all central to the formulation of reactive countermeasures against climate change effects.