**1. Introduction**

Geoscience, as an interdisciplinary field, is dedicated to revealing the operational mechanisms and evolutionary patterns of the Earth system. Geoscience is very important to enhancing our understanding of the Earth, including its life, resources, and environment. In recent years, the rapid development of high-performance computing and artificial intelligence technologies has presented unparalleled opportunities and challenges to geoscience research. This book aims to explore the significance of high-performance computing and artificial intelligence research in advancing our understanding of geosciences.

High-performance computing provides powerful computational capabilities for geoscience research. The Earth's system encompasses vast amounts of data and intricate interrelationships, including atmospheric dynamics, seismic activities, and ocean circulation, among others. Traditional data processing and modeling methods often struggle to meet the demands of these complex systems. However, the development of high-performance computing technologies has enabled scientists to leverage tools such as parallel computing and supercomputers to process large-scale datasets and conduct more precise simulations and predictions. Through high-performance computing, scientists can enhance their understanding of the dynamical processes within the Earth system, resulting in the improved accuracy and timeliness of weather forecasting, climate simulations, earthquake early warning systems, and more.

Artificial intelligence technology has introduced novel ideas and methodologies into geoscience research. The investigation of geosciences often necessitates the extraction of valuable information from extensive datasets to show the inherent patterns within the Earth system. Machine learning and deep learning algorithms in artificial intelligence are able to process intricate data and discern patterns. They autonomously learn and extract features from massive datasets, aiding scientists in uncovering hidden patterns and trends embedded within the data. For instance, in climate change research, artificial intelligence can analyze climate models and observational data to offer more precise predictions and evaluations. Moreover, artificial intelligence has practical applications in geological exploration and resource surveys, thereby enhancing the efficiency and accuracy of resource exploration.
