Handling intensities of data, computation, concurrent access, and spatiotemporal patterns

The Earth and its belongings evolve in a four dimensional (4D) world. Geosciences study the patterns and possible trends of this evolution of specic or integrated phenomena, such as dust storms and climate change. The grand challenges facing us in the 21st century are inevitably related to this 4D evolution, and addressing the challenges that require us to understand the principles and relationship behind the evolution and to predict potential future evolution based on different factors for different user communities. For example, we need to integrate the domains of land, ocean, and atmosphere processes to better understand how the climate is changing. This human knowledge pursuant to the application process involves large amounts of data (e.g., for climate change), signicant computing requirements to process increasing volumes of data and complex algorithms (e.g., for social media processing), and large numbers of simultaneous connections to the knowledge and computing (e.g., for emergency response to tsunamis and earthquakes). The three intensities of data, computation, and concurrent access are all based on spatiotemporal intensity, which we have to deal with on a variety of scales and resolutions. These intensities naturally match the characteristics of cloud services, such as scalable computing resources for concurrent access, virtually unlimited computing power for computing intensity, and global, available data centers by cloud providers for distributed locations of data (Yang et al. 2011a). This chapter reviews and discusses the future research directions of using cloud services to address these intensities.