Abstract

While modern sensing and communication technologies are enabling the observations of geophysical processes at unprecedented spatiotemporal resolutions, the development of these technologies is significantly outpacing their actual use across the geosciences. This is particularly true of real-time ... Show moreWhile modern sensing and communication technologies are enabling the observations of geophysical processes at unprecedented spatiotemporal resolutions, the development of these technologies is significantly outpacing their actual use across the geosciences. This is particularly true of real-time data systems, which are now permitting the streaming and analysis of data at the instant of their measurement. Though the use of real-time scientific data is limited, their importance is ever increasing, particularly in mission critical scenarios where informed decisions must be made rapidly. Beyond applications tied to disaster resilience (earthquake prediction, flood forecasting, etc.), now more than ever there is potential to leverage real-time data to fundamentally change how scientific experiments are conducted. For example, in many geoscientific experiments, faulty sensors are often only detected too late, forcing experiments to be repeated. In settings where mobile sensor nodes are used, or where sampling frequencies need to be adjusted to capture events of interest, few tools are available to adaptively guide the experimental process. This often results in missed observations and wasted experimental investments, but can be remedied rapidly by enabling means to analyse and respond to streaming data. While real-time data stand to enable a paradigm-shift in geoscientific experimentation, they rarely, if ever, form the first step in a geoscientific workflow. The vast majority of existing data platforms are inherently tuned to nonreal-time applications, where data are often stored in large databases for retrospective analysis and visualization. The few existing real-time data platforms, however, are either proprietary, feed into mission-specific tools, or are otherwise not available to broader stakeholders within the geosciences. While the complexity of these platforms presents a major barrier to the broader adoption of real-time data systems, there are also a number of technical challenges that must be addressed before the use of real-time data becomes commonplace across the geosciences. Show less