The European Solar Telescope (EST) is a next generation large-aperture solar telescope. This 4-metre telescope will be optimised for studies of the magnetic coupling between the deep photosphere and upper chromosphere. This will require diagnostics of the thermal, dynamic and magnetic properties of the plasma over many scale heights, by using multiple wavelength imaging, spectroscopy and spectropolarimetry. To achieve these goals, the EST will specialize in high spatial and temporal resolution using various instruments simultaneously that can efficiently produce 2D spectral information. EST will be located in Canary Islands, one of the first-class locations for astronomical observations.
A consensus exists among solar astronomers worldwide that a significant increase in observing capability is needed to understand the fundamental processes that control plasma physics in the Sun's outer atmosphere, approaching the following key questions as a priority goal:
EST is interested on the “Prediction of solar wind conditions (speed and magnetic field) at L1” and “Estimated arrival time of Coronal Mass Ejections (CMEs)”. EST aims at improving the predictions for the arrival times of CMEs by combining a phenomenological model (namely the PDBM – Probabilistic Drag Based model) with additional data sources and Machine Learning (ML) approaches.
To EST, ESCAPE is becoming a main portal for all sorts of data and its scientific exploitation in astrophysics, including solar physics. The ESCAPE community is very knowledgeable and readily available for discussions and for solving issues. Not only does ESCAPE provide a comprehensive set of data covering wide topics in astrophysics and particle physics, it also provides the necessary resources to carry out analysis of the data.
ESCAPE allowed EST to join a broader community of data and service providers. With the help of ESCAPE, EST gained more knowledge in presenting its data to users. ESCAPE helped EST to get acquainted with state-of-the-art technology regarding data management and distribution, for example getting to know about Rucio and its implementation to solar data.
The ESCAPE OSSR allows the reuse of databases that have been created for nay scientific purpose. Creating and curating a database is a task that takes time and skill. Spreading the use of existing databases and allowing for their extension with extra information is THE way to make the most from them. The ESCAPE collaboration helped EST in sharing and documenting both the data and the software, in a documented and well-defined environment.
EST created a database of CME characteristics that can be used for both standard and ML approaches to the task of forecasting the CME arrival at Earth. First version of this database was shared with the CWI group coordinated who is leading the development of the ML algorithms to highlight and extract information in the database. The initial database has been recently updated with new sources of information and with the results of PDBM simulations for each entry of the database. EST hopes that this effort will lead to a better definition of the Probability Distribution Function of the parameters of the PDBM simulation, by comparing forward modeling with ML approaches.
By using ESCAPE ESAP, the main scientific objective was the development of high-level data products like the physical parameters (e.g. Doppler velocities, magnetic fields, etc.) of the solar atmosphere, from ground based solar observations and providing them to a broader astrophysical community through the ESCAPE ESAP services.
EST created the data products in a semi-automatic manner for a large set of archived data, which has set the ground work for new and upcoming data. This was a pioneering endeavor for ground-based solar physics. ESCAPE ESAP allows EST to provide access to this data to a broader community for its scientific exploitation.
To strengthen the cross-border and multi-disciplinary environment that has been created with ESCAPE, made by communities with similar challenges of data-driven research. Another aspect is to continue to support the implementation of the EOSC and the open data approach in general.