The Icosahedral Nonhydrostatic (ICON) weather and climate model is a modelling framework for numerical weather prediction and climate simulations. ICON is implemented mostly in Fortran 2008 with the GPU version based mainly on OpenACC. ICON is used on a large variety of hardware, ranging from classical CPU cluster to vector architecture and different GPU systems.

An ICON model configuration developed for km-scale climate simulations is used as a scientific prototype for the digital twin of the Earth for climate adaptation with in the Destination Earth program of the European Comission. Here we focus on our effort to run these coupled ICON configurations at km-scale on LUMI, a HPE Cray EX system with a GPU partition based on AMD MI250x’s.

We present the model configuration, performance results and scalability of the simulation system on Lumi and compare it with results on other GPU and CPU based systems.

How to cite: Enkovaara, J., Frauen, C., Klocke, D., Kluft, L., Kornblueh, L., Kosukhin, S., Lunttila, T., Redler, R., and Schnur, R.: Enabling km-scale coupled climate simulations with ICON on GPUs, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18293, https://doi.org/10.5194/egusphere-egu24-18293, 2024.

In the context of advancing towards high resolution climate projections (1km, sub-hourly) and the consequently large memory requirements, we are reaching the point that not all of the data produced can be stored. In this work, we present the technical infrastructure developed in the context of the Destination Earth ClimateDT project, in order to consume the data produced by the core engines as soon as it is available,  a method known as “data streaming”. This mechanism consists of three main steps that are included in an integrated workflow: the run of the climate models themselves , the applications (which convert the model output to actionable information) and the mechanism that links both sides. This solution is designed to be scalable; different applications can be run simultaneously and with as many different variables and statistics as needed,  in order to fully utilize the output  from the digital twin. The flexibility of the workflow allows different applications to run at their optimal frequency in a seamless way. Last but not least,  the workflow integrates statistical streaming   algorithms, allowing integrated applications to generate on-demand online statistics from streamed data, minimizing the memory footprint. 

How to cite: Roura-Adserias, F., Gaya i Avila, A., Arriola i Mikele, L., Andrés-Martínez, M., Beltran Mora, D., Gonzalez Yeregui, I., Grayson, K., De Paula Kinoshita, B., Ahmed, R., Lacima-Nadolnik, A., and Castrillo, M.: The data streaming in the Climate Adaptation Digital Twin: a fundamental piece to transform climate data into climate information, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2164, https://doi.org/10.5194/egusphere-egu24-2164, 2024.

Destination Earth initiative (DestinE), driven by the Exploitation of Meteorological Satellites (EUMETSAT), the European Space Agency (ESA) and the European Centre for Medium-Range Weather Forecasts (ECMWF) aims to create a highly accurate replica or Digital Twin of the Earth. The first two Digital Twins describe weather-induced and geophysical extremes, as well as climate change adaptation, but the number of Digital Twins will continue to grow. To develop new models, there is a high need to gain access to data and dedicated services. One of the three key components of DestinE is the Destination Earth Data Lake (DEDL) which provides discovery, access, and big data processing services.

DEDL facilitates data storage and access through three primary types of data entry points: the Fresh Data Pool (FDP), Federated Datasets (FED), and the Digital Twins Data Warehouse. DEDL offers big data processing which allows near-data processing and by this conceptually supports ML/AI applications executed on the DEDL. The DestinE data lake federates with existing data holdings as well as with complementary data from diverse sources like in-situ, socio-economic, or data-space data. Thanks to DEDL, it is possible to get immediate access to data like Sentinel-1/2/3/5P missions. What is more, all this data is provided as a full archive immediately available to the user. With instant access to current Earth Observation (EO) data, researchers and other users can conduct time-sensitive analyses without the delays associated with data ordering. Moreover, having a comprehensive archive of EO data enables trend analysis and the investigation of long-term changes.

In this presentation we will demonstrate how to use Harmonized Data Access (HDA) – one of the tools developed within the DEDL. We will present the available datasets provided through HDA and guide you on how to use it to search collections and products. as Additionally, we will demonstrate how to obtain these datasets for use in your own environment. As SpatioTemporal Asset Catalogs (STAC) is used as a metadata standard, discovery and work with data provided by DEDL is user-friendly. Thanks to HDA it is possible to use a single account to explore data across tens of collections and petabytes of products.

The DestinE Data Lake is an initiative that revolutionizes the handling of Earth Observation data, improving capabilities in climate research, and supporting sustainable development efforts. The principles behind the DEDL will enable data harmonization and federation on a scale beyond current capabilities. 

How to cite: Grzybowski, P., Ziółkowski, M., Lambare, A., Le Carvennec, A., Reimer, C., and Schick, M.: Destination Earth Data Lake (DEDL) Service – Access and discovery data through the Harmonized Data Access (HDA) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19669, https://doi.org/10.5194/egusphere-egu24-19669, 2024.

How to cite: Koubarakis, M., Corsi, M., Leoni, C., Pasquali, G., Pratola, C., Tilia, S., Kefalidis, S.-A., Plas, K., Pollali, M., Tsokanaridou, M., Hackstein, J. H., Sümbül, G., and Demir, B.: A Digital Assistant for Digital Twin Earth, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21564, https://doi.org/10.5194/egusphere-egu24-21564, 2024.

Destination Earth (DestinE) program develops high-precision digital twins (DTs) of the Earth to support decision making in Europe and thus enable more sustainable development and increased resilience against environmental changes. Climate Change Adaptation Digital Twin (Climate DT in brief) is one of the first priority DTs developed within DestinE. It will provide capabilities supporting climate change adaptation at regional and national levels at multi-decadal time scales. We introduce here the first prototype of Climate DT developed during Phase 1 of DestinE.

The Climate DT system is built around three one-kilometer-scale Earth-system models (ESMs); ICON, IFS-NEMO and IFS-FESOM. The ESMs have been adapted to run on the fastest supercomputer in Europe, EuroHPC LUMI that is in operation in Kajaani, Finland. The Climate DT system will also harness another state-of-the-art EuroHPC system, MareNostrum 5 that will become operational during 2024 in Barcelona, Spain. The extreme computing capacities provided by these systems enable Climate DT to perform global climate simulations at an unprecedented scale: multi-decadal simulation on 5 km global meshes. This enables providing globally consistent climate information at local levels.  

Climate DT introduces a novel approach where ESMs and impact-sector applications operate as part of the same workflow and the output of the ESMs is streamed to applications on real-time in a standardized form called generic state vector (GSV). This approach enables users to access the full model state as soon as it has been produced by the ESMs. It also makes the system scalable across an unlimited number of applications and solves a technical challenge of handling huge amounts of data. Most importantly, this new climate information system enables transforming climate data to actionable information. During Phase 1 of DestinE, this approach is demonstrated through five impact-sector applications that provide information on (1) wind energy supply and demand, (2) wildfire risk and emissions (3) river flows and fresh water availability, (4) hydrometeorological extreme events, and (5) heat stress in urban environments.  

In this presentation, we will present the overview of the first prototype of Climate DT, including technical design of the system, performed simulations and implications for the users. We will also discuss the plans for the future development of the system.

How to cite: Kontkanen, J., Manninen, P., Acosta, M., Bretonnière, P.-A., Castrillo, M., Davini, P., Doblas-Reyes, F., Früh, B., von Hardenberg, J., Jung, T., Järvinen, H., Klocke, D., Naraynappa, D., Niemelä, S., Sievi-Korte, O., and Thober, S.: Climate Adaptation Digital Twin transforming climate data to actionable information, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17334, https://doi.org/10.5194/egusphere-egu24-17334, 2024.

Rapid open-source physics-based flood and impact models are critical resources for adaptation planning. Due to their complexity, these models often remain inaccessible to users who rely on them for decision-making. An advanced level of technical knowledge is required to set up and run the models. This body of work aims to develop an adaptation modelling framework that automates model pre-processing, workflows, and post-processing and allows non-technical end-users to access these modelling advances, empowering government agencies, practitioners, and researchers to evaluate meaningful “what-if” scenarios, such as specific events, future conditions, or protective measures.

Via engagement with potential and current users from municipalities, regional governments, European agencies such as EEA and EC, research institutes, and communities closely linked to the EU Mission on Climate Adaptation, the research team will build upon years of research and development on the adaptation modelling framework FloodAdapt. The project will deliver a design, user documentation and demonstrator of a flexible, modular, expandable, and transferable adaptation modelling framework that can automatically modify and execute state-of-the art and open-source flood and impact models to simulate, visualize, and assess compound flood scenarios, impacts, and risk for a wide variety of end users in different demographic and physical contexts. End users of the adaptation modelling framework will ultimately be able obtain quality flood and impact maps, equity-focused visuals, and informative metrics to support their planning needs and facilitate genuine stakeholder engagement, . The framework will also be generalized to enable other scientific disciplines to benefit from the adaptation modelling framework, extending the impact of the project.

How to cite: Wright, S., Backeberg, B., and Roscoe, K.: Developing a generic Adaptation Modelling Framework for Destination Earth grounded in Flood Risk Management, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20023, https://doi.org/10.5194/egusphere-egu24-20023, 2024.

Understanding tropical precipitation extremes is crucial for capturing the complexities of global climate dynamics. In this study, we employ a novel methodology to examine these extremes in spatial and temporal resolutions that have not previously been explored in global climate modeling.

High-resolution data from nextGEMS Cycle 3 and preliminary DestinE simulations are our primary sources. We thoroughly analyzed advanced models from different historical periods, including ICON, IFS-FESOM, and IFS-NEMO. The research also includes a range of observational data sources, such as the MSWEP, ERA5, and EMERG datasets, to create a robust framework for comparison. Our methodological approach includes zonal mean analysis and probability distribution functions (PDFs), applied to data re-gridded to both standard 1° monthly and finer high-resolution 0.1° scales. This dual-resolution strategy is key for revealing detailed patterns and extremes in tropical precipitation.

The study uncovers notable alignments and discrepancies between model simulations and observational data. Some models show a high degree of accuracy in reflecting real-world observations, whereas models like ICON demonstrate significant biases, especially in extreme precipitation rates. Such variations in precipitation peaks and rates across different models underscore the need for adjusting simulation parameters to enhance accuracy.

How to cite: Nazarova, N., von Hardenberg, J., Davini, P., Nurisso, M., Caprioli, S., and Ghinassi, P.: Evaluating Tropical Precipitation Extremes: Insights from first simulations from nextGEMS and Destination Earth Climate Digital Twin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11498, https://doi.org/10.5194/egusphere-egu24-11498, 2024.

The NOrdic CryOSphere Digital Twin (NOCOS DT) project aims to explore and pilot digital twin technology opportunities and showcase how output from key initiatives such as the Destination Earth (DestinE) Climate Change Adaptation Digital Twin (Climate DT) could be leveraged for key sea-ice impact sectors in the Arctic and Baltic.

By enabling simulations at an unprecedented scale and resolution, DestinE and Climate DT aim to provide a more detailed representation of the Earth system. While awaiting the Climate DT data, NOCOS DT has done preparatory work using existing data sets in order to calculate novel navigational risk indicators, user-relevant  sea-ice climatologies and modeling of sea ice breakup and ridges. Additionally, the project looks at the potential use of this new information system and other climate data in marine spatial planning. NOCOS DT provides a Nordic perspective and insight that can inform Destination Earth in its future phases.

The presentation provides an overview of the project and its main outcomes with informative animations. It hopes to spark open conversation around further ways to benefit from emerging digital twin technologies and ways to leverage international initiatives such as Destination Earth for specific impact sector needs in the Baltic Sea area.

CSC – IT Center for Sciences coordinates the NOCOS DT consortium which brings together the Danish Meteorological Institute (DMI), the Finnish Meteorological Institute (FMI), the Norwegian Meteorological Institute (MetNo), the Swedish Meteorological and Hydrological Institute (SMHI) together with Tallinn University of Technology, Department for Marine Systems (TalTech). The project is funded by the Nordic Council of Ministers.

How to cite: Liinamaa, I., Aalto, T., Haapala, J., Zhang, X., Rasmussen, T., Wang, K., Arneborg, L., Carlstedt, L., Uiboupin, R., and Maljutenko, I.: Case studies towards cryosphere digital twin applications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1971, https://doi.org/10.5194/egusphere-egu24-1971, 2024.

Coastal deltas are extremely susceptible to flooding from sea, rivers, heavy rain and even more severe combinations thereof. Many coastal deltas are densely populated, and flood risk forms a serious threat that will likely increase in the future. There are two main mechanisms to reduce the devastating impacts of these floods; (1) adaptation to the increasing climate risks and (2) improved early warning and emergency response. We will present the Destination Earth digital twin on coastal compound flood inundation forecasting and climate adaptation that provide information  to support reducing of impacts.

Examples for 5 use cases are presented showing flood inundation and flood impact maps resulting from compound combinations of surge, waves, heavy rain and riverine flooding. The results are based on an automated complex but generic workflow that takes the high resolution meteorological forcing from Extremes DT or Climate DT as input to the high resolution hydrological model (Wflow_sbm), the hydrodynamic model (Delft3D-FM) and the wave models (hurrywave and snap wave). Those models provide the boundary condition of the 2D flood inundation model SFINCS. Based on the calculated flood maps, impacts (in flood damage and people affected) are being calculated with Delft-FIAT. Results of the modelling chain and model validation will be to end user. The insights we obtained from our end users will provide valuable inputs for design of the compound flood digital twin.

How to cite: Yan, K., Weerts, A., Bovenschen, T., Cunningham, A., Muis, S., Roelvink, F., Sperna Weiland, F., and Zijlker, T.: Compound flood forecasting and climate adaptation Destination Earth digital twin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7534, https://doi.org/10.5194/egusphere-egu24-7534, 2024.

The transition towards clean energy consists a fundamental challenge in most recent EU policies as well as the 2030 Agenda for Sustainable Development and Paris Agreement on climate change. However, the dependency of renewable energy systems from climate and weather, renders it into a quite challenging task. Besides a number of factors that need to be initially taken into account and relate to the efficiency of the systems and their resilience to climate-related factors, the day-to-day energy market requires accurate and detailed information on solar and wind availability in different spatial scales, as energy users range from roof top private owners to regional and large-scale facilities. This kind of information can only be provided through a fusion of numerical models and satellite based earth observation platforms.

In order to accommodate this need and act as a decision support system, a Hybrid Renewable Energy Forecasting System (HYREF) is developed for solar and wind forecasting, under the framework of Destination Renewable Energy (DRE), a European Space Agency (ESA) funded project. The HYREF utilises outputs from high resolution forecasting models, Destination Earth (DestinE) Digital Twin forecast data and Data Lake data (e.g. Global Ocean 1/12° Physics Analysis and Forecast, Vegetation Indices, CORINE Land Cover, and Global 10-daily Fraction of Vegetation Cover, data from the Weather-induced extremes Digital Twin among others) as well as end-user provided historical and real-time data that allow for specific site adaptation through probabilistic models and statistical post processing. The service will use the newly established Service Platform (DESP) that is supported by the DestinE initiative. The HYREF software is flexible, will provide spatial upscaling options based on the DESP data coverage and, as a user-driven service, will evolve gradually through continuous interaction and feedback from the end-users with additional direct engagement of market stakeholders. The final product is expected to increase energy efficiency and cater the needs of a broad spectrum of renewable energy users from private owners to large-scale facilities, industrial users, up to transmission and distribution national operators.

How to cite: Kontoes, C., Papadopoulou, D., Bartsotas, N. S., Kazadzis, S., Koutalieris, G., Stathopoulos, C., Salta, F. N., Patlakas, P., Papachristopoulou, K., Fountoulakis, L., Delkos, A., Symeonidis, S., and Sinnis, V.: The development of a Hybrid Renewable Energy Forecasting System under the Destination Earth initiative., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18891, https://doi.org/10.5194/egusphere-egu24-18891, 2024.

Events of extreme air pollution pose threats to humans and the environment. To investigate air quality under extreme atmospheric situations, the DestinE air quality use case developed a comprehensive user interface that enables high-resolution air quality forecasts with diverse analysis options. The user interface encapsulates the two state-of-the-art approaches that are physics-based numerical simulations with the chemistry transport model EURAD-IM (European Air pollution Dispersion – Inverse Model) and data-driven machine learning forecasts with MLAir (Machine Learning on Air data). The EURAD-IM simulations are coupled to the meteorological output of the DestinE digital twin for weather extremes, which provides high-resolution information (~4.4 km). An additionally implemented machine learning based postprocessing even allows for the downscaling of the EURAD-IM forecast output to a resolution of 1 km. MLAir produces 4-day point forecasts at station sites using data from the Tropospheric Ozone Assessment Report (TOAR) data base. The developed system is complemented by an efficient module that enables emission scenario simulations to investigate and develop air pollution mitigation strategies for future extreme events under realistic conditions.
The established user interface is demonstrated by two selected air quality extreme events in early 2017 and summer 2018. It aims to provide a new quality of air pollution information that supports the core users, i.e., environment agencies, in decision making. For the near future, it is planned to fully embed the system to the Destination Earth Service Platform (DESP) such that it will be available to a wider community. Besides assisting policy making, the air quality products help to answer scientific questions on air quality and atmospheric chemical processes under extreme weather conditions that are expected to increase in future. 

How to cite: Lange, A. C., Schröder, S., Franke, P., Langguth, M., Friese, E., and Schultz, M. G.: Applying the DestinE Extremes digital twin to air quality forecasts and emission scenario simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19153, https://doi.org/10.5194/egusphere-egu24-19153, 2024.

Gradient boosting-based soil wetness for forestry climate adaptation in HarvesterSeasons service -training a model to forecast soil water index SWI from a comprehensive set of IFS model predictors in Destination Earth was an exercise that clearly improved a crucial part of the forestry climate service HarvesterSeasons.com. Forestry in nordic countries has to adapt to good and sustainable winter conditions being less and less available. Dry summer conditions are being looked for to compensate for weak winter times.

We present our service, the machine learning method for the new product and the validation of the new product. For machine learning Xtreme Gradient was used to train the Earth Observation product Soil Water Index from ERA5-Land, soilgrids.org and other features. Predicting is then enabled from Destination Earth Extremes and Climate Adaptation Digital Twins.

How to cite: Strahlendorff, M., Kröger, A., Kosmale, M., Prakasam, G., Moisander, M., Ovaskainen, H., and Poikela, A.: Gradient boosting-based soil wetness for forestry climate adaptation in HarvesterSeasons service -training a model to forecast soil water index SWI from a comprehensive set of IFS model predictors in Destination Earth, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17836, https://doi.org/10.5194/egusphere-egu24-17836, 2024.

DestinE is the EC’s ambitious initiative to develop a digital twin of the Earth’s system to enable users to monitor and simulate natural and human activities to support environmental policies and decision-making processes at European and global scales, including the green transition of the European Union, aligning with the goals set out in the EC’s Green Deal and Digital Strategy.

RHEA is leading the Destination Earth Use Cases project consortium to select a set of use cases to be developed and integrated within DESP, which will act as a gateway to the other DestinE components, namely the Destination Earth Data Lake, led by EUMETSAT, and the Digital Twins and Engine, which are the responsibility of ECMWF. This use cases will be developed using an Agile framework and a co-design approach with their reference community to enable a validation of the DestinE infrastructure and its evolution.

Five projects started in November 2023:

• Global Fish Track System (GFTS), whose objective is to develop a fully functional Decision Support Tool for establishing essential fish habitat conservation areas under different scenarios.
• DestinE Sea Ice Decision Enhancement (DESIDE), which aims to meet the needs of policy and decision makers who require information on the past, current, and forecasted sea ice and other relevant conditions for operational purposes in the Baltic Sea, European Arctic Ocean, and the rest of the polar regions.
• CITINEXUS, which is modelling environmental, social, and economic impacts of interventions in road networks, mobility, and urban fabric, using High Frequency Location Based data and evaluating baseline conditions for human mobility, including key performance indicators like air quality, population distribution, public health, and service accessibility.
• DestinE Renewable Energy (DRE), which aims to support evidence-based policy-making in the transition towards green energy by integrating new decision-making tools for renewable energy source (RES) producers.
• UrbanSquare project, which is developing a tool to assess the urban climate risks, namely: Urban heat, flooding forecast, storm surges, sea level rise, air pollution, deterioration of infrastructure and increased demand on resources.

The presentation will include and overview of each selected project as well as a list of opportunities to contribute to DestinE in the future.

How to cite: Patruno, J., Romeo, A., Vitolo, C., Wiesmann, D., Arthurs, D., Fratini, S., Papadopoulou, T., and Habib, T.: Destination Earth Core Service Platform Use Cases: A Collaborative approach for DestinE validation and evolution, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20322, https://doi.org/10.5194/egusphere-egu24-20322, 2024.

The DestinE Use Cases Project, executed by a Consortium led by RHEA Group with the Aristotle University of Thessaloniki and Trust-IT, regards the selection and implementation of a first set of Use Cases meant to demonstrate the ability of the DestinE infrastructure in general, and the DestinE Service Platform (DESP) in particular, to provide actionable information and decision support to its end-users. The project aims also at actively engaging the broad community of DestinE stakeholders, gathering their requirements, and encouraging their direct involvement and guidance in the continuous evolution of the DestinE infrastructure towards the future Phases of the Initiative.

The DestinE Community leads the establishment of a network that fosters continuous interactions among users, developers, stakeholders, and partners, with the aim of enhancing DestinE capabilities and catalyzing cross-sectoral collaborations. The community serves as a platform for open and transparent opportunities for ongoing exchange. By incorporating multiple perspectives, opinions, experiences, and expertise, DestinE community members can advance their knowledge, gain value-driven experiences, and contribute to their professional growth.

Currently boasting over 1,000 members representing diverse stakeholders, the DestinE community is committed to contributing to the design and development of the initiative and its components through a co-design process. This approach ensures that the system is responsive to real user needs and introduces innovations compared to existing operational environments. Community feedback plays a crucial role in understanding user needs and preferences, determining the importance of features or functions, testing and validating developed features with end users, and fostering collaboration among individuals from varied backgrounds, leading to innovative ideas and approaches in DESP development.

To support community building, a range of activities, both online and physical, are underway. These activities aim to actively engage and involve DestinE user communities in co-design, development, co-evolution, and use of DestinE capabilities, applications, and solutions. They also facilitate gathering stakeholders' needs and recommendations, encouraging their direct involvement and guidance in the continuous evolution of DestinE infrastructure and capabilities towards future phases of the initiative. Additionally, these activities serve to demonstrate the DestinE infrastructure's capabilities through a first set of use cases.

Meetings and open discussions with key stakeholders of DestinE, especially those related to DESP, have already resulted in early recommendations. These recommendations will be translated into system requirements for the DESP platform as part of the ongoing collaborative efforts within the DestinE Community.

How to cite: Karachaliou, E., Stylianidis, E., Bakousi, A., Tsifodimou, Z.-E., Bissas, C., Romeo, A., Patruno, J., Carrillo, R., and Smith, Z.: The DestinE Community's Journey, From User Engagement to Recommendations gathering, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20343, https://doi.org/10.5194/egusphere-egu24-20343, 2024.

The integration of lava flow forecasting models with satellite remote sensing techniques marks a significant advancement in quantitative hazard assessment for effusive volcanic eruptions. Within the framework of the DT-Geo project, we are developing a lava flow workflow that harnesses High-Performance Computing (HPC) capabilities, aiming to improve hazard assessment through ensemble-based and data assimilation methods.

At the core of the workflow is the VLAVA code, which simulates the lava flow propagation, with temperature-dependent viscosity over a complex topography, erupting from one or more vents. The simulation runs for a given time period (order of one or more days), after which the simulated deposit is compared to the observed  lava flow field and, eventually, the observations are assimilated into the model for a further simulation. The measured data include changes of the eruption source parameters and/or the extension and temperature of the lava flow field. These are derived from direct observations on the field or by remote sensing from airborne, drones or satellites (e.g.: Pléiades, EOS-ASTER, SEVIRI, MODIS, VIIRS, Landsat, Sentinel, etc.). Data assimilation is conducted using PDAF, a dedicated software offering various approaches, including ensemble-based Kalman filters, nonlinear filters, and variational methods.

The model output provides the potentially impacted area by lava flows, including thickness and temperature distribution, for both a single scenario (utilized for estimating the impact of a lava flow) and an ensemble of weighted scenarios (for generating probabilistic hazard maps). We present the overarching concept of the workflow and share preliminary results obtained for historical eruptions of Mount Etna.

How to cite: Costa, A., Cordrie, L., Macedonio, G., Ganci, G., Cappello, A., and Zuccarello, F.: Leveraging High-Performance Computing for Enhanced Lava Flow Forecasting Workflow, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16329, https://doi.org/10.5194/egusphere-egu24-16329, 2024.

Climate change represents one of the most urgent challenges facing society today, with rising sea levels, increasing ocean acidification, more frequent and intense extreme events such as floods, heat waves and droughts, impacting across different sectors, ecosystems, and endangering human lives and property. Population growth is also expected to amplify current pressures on critical resources such as freshwater and food, intensify the stress on land and marine ecosystems, and increase environmental pollution, impacting health and biodiversity.  

The latest advances in Earth Observation (EO) science and R&D activities are opening the door to a new generation of EO data products, novel applications and scientific breakthroughs offering a novel, advanced and holistic view of the Earth system, its processes, and its interactions with human activities and ecosystems. These emerging capabilities offer unique opportunities for an enhanced and extensive use of EO technology in the development of digital twins. In particular, those EO developments together with new advances in sectorial modelling, computing capabilities, AI and digital technologies offer excellent building blocks to realise novel EO-based Digital Twin Components (EO DTCs) that may contribute and maximise the impact of EO satellite technology in the design and implementation of future operational Digital Twins

The ESA Digital Twin Earth programme aims at developing and demonstrating, to a pre-operational stage, a set of EO-based DTCs as advanced replicas of key components of the Earth system including their interactions with human activities and ecosystems. These EO DTCs shall be designed to serve a wide variety of users and with a strong focus on valorising the role of EO capabilities. With this presentation, we highlight ESA’s basic principles and functional design elements for the development of EO-based DTCs, provide a scientific and technical roadmap for the development of future DTCs, along with their interaction with the DestinE initiative. Furthermore, we will highlight the eight priority thematic domains for DTC development, based on feedback from the scientific community, and highlight the tasks to be undertaken to achieve DTC demonstrators. This includes, allowing users to access, analyse, visualise and interact with advanced EO-data, represent Earth system processes and feedbacks, scientifically sound integration of EO-data, models, AI, hybrid methods to generate high spatial and temporal resolution datasets, and facilitating what-if scenarios.

How to cite: Malina, E., Wearing, M., and Fernandez, D.: Earth Observation Based Digital Twin Components of the Earth System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20503, https://doi.org/10.5194/egusphere-egu24-20503, 2024.