Our planet is undergoing rapid transformation before our very eyes. To adequately prepare for the climate challenges of the future, we must develop new capabilities to understand these changes and predict what lies ahead.
Global climate changes are escalating the frequency and severity of life-threatening extreme weather events, including cyclones, floods, heat waves, storms, fires, and dust storms. Climate research has made significant strides in recent decades, with precise measurements of various pertinent "ground truth" parameters from numerous locations worldwide, coupled with remote sensing measurements from both ground and space. Models portraying global climate changes have also grown more sophisticated and accurate, yielding valuable data.
Predictive models based on machine learning are central to climate change research. With modern AI techniques, a new generation of models must go beyond current capabilities and amalgamate diverse datasets to improve our understanding of the physics underpinning extreme weather events and how their dynamics are evolving as the entire environment is shifting toward conditions we have never observed before.
Some challenges in employing artificial intelligence in climate research are common to other fields, such as the need to make predictions and forecasts based on very little prior experience, through extrapolation, and without the ability to perform experiments. This underlines the need to peer into the AI 'black box' and develop "explainable AI" to comprehend the science behind complex environmental dynamics in a way that can be used for reliable extrapolations.
Some challenges are more unique to this field. Climate scientists need to understand how to instruct computers to bridge the timescales between slow-moving weather events, such as atmospheric depressions, and rapidly evolving extreme weather events. Data augmentation presents a unique challenge when modifying the parameters of a phenomenon can drastically alter its geographic and physical significance.
Overcoming these challenges and leveraging AI to better understand and predict the evolution of extreme weather events in the short, medium, and long term will prove invaluable in our pursuit of a sustainable future. This knowledge will empower humanity to prepare more effectively for future changes and potentially mitigate disasters.