Artificial intelligence for Climate Change, Biodiversity and Earth System Models

How to make an accurate prediction of climate change and greenhouse carbon emissions with artificial intelligence? We are experimenting with several AI models for climate change and global warming. Sri Amit Ray explains the hybrid system of process-based earth system models and the deep learning networks of artificial intelligence. 

As climate change and global warming have become the most urgent issues for human survival, researching ways to improve climate change and earth system models has become of the utmost importance.

Artificial intelligence (AI), specifically deep learning algorithms, has the ability to make decisive interpretations of large amounts of complex data. Moreover, modern machine learning techniques appear as the most effective tool for the analysis and understanding of ocean, earth, ice formations, CO2 emissions, biodiversity, and atmospheric data for situation and target specific dynamic prediction. One of the strengths of machine learning tools such as convolutional neural network is its capacity to combine a variety of methods.

Earth system models: An overview 

Earth system models (ESMs) are primarily based on general circulation models (GCMs). They are largely used in current climatic studies that take into account features such as biogeochemical cycles and atmospheric chemistry. Earth system models can integrate the influence of human decisions, making them excellent tools for planning infrastructure, energy production and consumption, and landscape use.… Read more..

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