Networked Digital Earth for Digital Twins of Earth Systems
Abstract
Digital Earth, as defined by former US Vice President Al Gore, is a virtual representation of the Earth that is georeferenced and connected to the world's digital knowledge archives. Toblers first law of geography states that "everything is related to everything else, but near things are more related than distant things. While geographic information sciences are well positioned to represent the natural, engineered, and social systems that constitute our planet Earth in this era of the Anthropocene, there are a few inherent challenges. Weather and climate oscillators such as the El Nino Southern Oscillation influence weather patterns across the globe through climate teleconnections or long-range spatial dependence. The Hurst phenomenon in hydrology is an example of long-memory drought processes in time. Engineered systems, such as interdependent lifelines (e.g., transportation, communication, energy, and water networks), exhibit cascading failures and long-range dependence of topologies and dynamics. Natural systems such as food webs and socio-ecological networks exhibit connected systems. Coupled natural-human processes are often inextricably linked with nonlinear patterns and feedback loops as well as complex chains of causality and uncertainty. Network representations become important, such as for assuring resource allocations and for understanding disruption and recovery pathways. Network science, which has been defined by the US National Research Council as the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena, may offer a possible solution. Here we provide use cases from the literature and best practices, ranging from climate adaptation and resilience engineering to pandemic recovery and supply chain efficiency, which exemplify how digital earth and network science concepts can be broadened, improved, adapted, and integrated to develop digital twins of earth systems.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMSY14A..06W