  Recent achievements in machine learning (Ml) have had a significant impact on
various fields, including climate science. Climate modeling is very important
and plays a crucial role in shaping the decisions of governments and
individuals in mitigating the impact of climate change. Climate change poses a
serious threat to humanity, however, current climate models are limited by
computational costs, uncertainties, and biases, affecting their prediction
accuracy. The vast amount of climate data generated by satellites, radars, and
earth system models (ESMS) poses a significant challenge. ML techniques can be
effectively employed to analyze this data and extract valuable insights that
aid in our understanding of the earth climate. This review paper focuses on how
ml has been utilized in the last 5 years to boost the current state-of-the-art
climate models. We invite the ml community to join in the global effort to
accurately model the earth climate by collaborating with other fields to
leverage ml as a powerful tool in this endeavor.
