# Towards a Digital Twin Prototype of Alpine Glaciers: Proposal for a Possible Theoretical Framework
## 1 Introduction  
Initially coined and developed by the industrial manufacturing sector, the Digital Twin concept has also landed, in recent years, in academia [1]. Due to its adoption in diverse sectors and disciplines, several definitions exist for Digital Twin (DT). With reference to the scientific research and according to [PERSON] [2] \"A digital twin is a digital replica of a living or non-living physical entity. By bridging the physical and the virtual world, data is transmitted seamlessly allowing the virtual entity to exist simultaneously with the physical entity\". Thus, unlike a three-dimensional model, which is a mathematical representation of a three-dimensional object, the DT is not simply the copy of the physical product but is also closely connected to this by specific relationships. A DT, in fact, consists of three main components [3]: (i) physical entity, (ii) digital entity (virtual representation) and (iii) connections relating physical anddigital entities. Connections work through data that flows from the physical to the digital representation and through the information that is generated from the digital entity to enter the physical environment. Considering that the information generated by the digital twins is driven by use cases [3], related to a wide range of scientific application domains, such connection could enable the (virtual) monitoring of specific processes/entities/ecosystems, depending on the considered use case. Moreover, the DT allows the simulation of different and eventual scenarios, and the analysis of consequent responses of the physical model to which it refers (Figure 1). In short, it serves to test and understand how the analysed system will behave as conditions change. Of course, to achieve such ambitious modelling, the latest technological advances of the IoT (Internet of Things), AI (Artificial Intelligence), ML (Machine Learning), HPC (High Performance Computing) and Big Data analytics have to be exploited. Synergies among these technologies and experts in different discipline, depending on the application type, allow the creation of virtual representations of physical entities and the understanding of their behaviour, anticipating their possible reactions to simulated events. The Digital Twin (DT) is the core of the Destination Earth initiative (DestinE) [4] of the European Commission, aimed at creating, by year 2030, a very high precision digital model of the Earth useful to interactively explore various natural processes and human activities at a local and global level. Since 2021, the development of digital replicas of Earth systems has been initiated in an effort to take care of all involved complexities. Digital twins are implemented and specified according to the thematic domains of the Earth Sciences, such as natural disasters, adaptation to climate change, oceans, and biodiversity. Nevertheless, it is expected that all these digital replicas will be integrated in a single and complete DT, representative for the entire Earth system. Moreover, Destination Earth Digital Twins will be made available through a dedicated platform enabling both modelling and simulation. The platform will be openly accessible and cloud-based, funded as part of the Digital Europe program [5]. The platform will welcome contributions from experts, scientists, policy makers, companies, and private users. Public and private entities will be able to access the system taking advantage of the archived information, scenario analysis capabilities, forecasting and simulation services, with the aim of accelerating the green transition, predicting environmental degradation, and supporting the political choices of EU member states. Implementation of the Earth DT is expected to largely profit from Earth Observation (EO) data and services. These will represent the main source of updated information continuously feeding the DT to ensure adaptation, re-calibration and validation of modelled processes.