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Recent achievements in machine learning (Ml) have had a significant impact onvarious fields, including climate science. Climate modeling is very importantand plays a crucial role in shaping the decisions of governments andindividuals in mitigating the impact of climate change. Climate change poses aserious threat to humanity, however, current climate models are limited bycomputational costs, uncertainties, and biases, affecting their predictionaccuracy. The vast amount of climate data generated by satellites, radars, andearth system models (ESMS) poses a significant challenge. ML techniques can beeffectively employed to analyze this data and extract valuable insights thataid in our understanding of the earth climate. This review paper focuses on howml has been utilized in the last 5 years to boost the current state-of-the-artclimate models. We invite the ml community to join in the global effort toaccurately model the earth climate by collaborating with other fields toleverage ml as a powerful tool in this endeavor.

Leveraging machine learning to enhance climate models: a review