EGU23-10933, updated on 26 Feb 2023
https://doi.org/10.5194/egusphere-egu23-10933
EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

User-driven climate model data streaming for climate adaptation

Francisco Doblas-Reyes1, Christian Steger2, Sami Niemelä3, Jenni Kontkanen4, Barbara Früh2, Bjorn Stevens5, Heikki Tuomenvirta3, Roberto Chavez6, Aleksander Lacima6, Miguel Castrillo6, and Katherine Grayson6
Francisco Doblas-Reyes et al.
  • 1ICREA & Barcelona Supercomputing Center (BSC), Barcelona, Spain
  • 2Deutscher Wetterdienst (DWD)
  • 3Finnish Meteorological Institute (FMI)
  • 4CSC - IT Center for Science (CSC)
  • 5Max Planck Institute for Meteorology (MPI)
  • 6Barcelona Supercomputing Center (BSC)

The Destination Earth Climate Adaptation Digital Twin (Climate DT) will design and implement a climate information system running on pre-exascale high-performance computing platforms to support climate adaptation efforts. An overview of the overall Climate DT will be given by Kontkanen et al. (this session).

The Climate DT will provide global climate data for both the historical period and the near-term future with unprecedented spatial and temporal resolution. The downstream applications will access the full model state vector (MSV) at runtime. This will lead to an interactive system where applications harnessing the MSV can be added, removed, or modified as required by the user. The climate MSV, which contains both the prognostic and a large number of diagnosed variables, will be continuously streamed (understood as all the user-requested variables being available in a federated and curated repository for a limited period of time before being erased) at both high frequency and native resolution. The applications will be able to consume this data at runtime as it is streamed. This is equivalent to applications using all the model data they require in a similar manner as one observes a physical system with all the necessary detail to satisfy specific requirements. Additional functionalities will be provided to help the data consumers access relevant statistics, to speed up the data processing and facilitate the data reduction (e.g., on-the-fly bias adjustment). This approach reduces the entry-level requirements for applications to participate in this completely new approach to access climate information data sources. The applications have the possibility of not only interacting with the model to extract the required climate data and indicators on real time, but also iteratively contribute to the design of the experimental set up and request additional variables and indicators.

To illustrate the broadest possible applicability of the Climate DT concept, five different pilot use cases were selected for the co-design, implementation, user feedback and evaluation of the Climate DT. The selected use cases focus on wildfires, urban climate, river discharge, wind energy, and hydrometeorological applications. Another consumer of the MSV will be the climate model evaluation. Furthermore, the use cases will present technical recipes for users to access the data and link their applications or impact models to the digital twin.

Each use case has identified specific key users. A close exchange with these key users is foreseen to meet the user requirements. To ensure transferability of the work to other users, an exchange with a wider circle of users is foreseen at a more advanced phase at dedicated stakeholder meetings.

An overview of the use cases, the technical concepts and the ongoing user engagement and co-design activities will be given to demonstrate the novelty, potential and advantages the digital twin offers. The use cases will illustrate the progress beyond current practices that is possible with these new climate simulation workflow compared to the traditional way of delivering climate simulation.

How to cite: Doblas-Reyes, F., Steger, C., Niemelä, S., Kontkanen, J., Früh, B., Stevens, B., Tuomenvirta, H., Chavez, R., Lacima, A., Castrillo, M., and Grayson, K.: User-driven climate model data streaming for climate adaptation, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10933, https://doi.org/10.5194/egusphere-egu23-10933, 2023.

Supplementary materials

Supplementary material file