EUV-ML solar physics dataset from STEREO + SOHO, 2 solar cycles

A unified ML-ready dataset of all SOHO EIT and STEREO EUVI EUV images, aligned and set to 512x512 pixels, are available via the NASA TOPS ODR in HelioCloud at s3://gov-nasa-hdrl-data1/contrib/euvml/ (inside of AWS, and with free egress via https).  We also provide the software used to create it via a public github repository, and a sample Python Jupyter Notebook (in this Zenodo link, and in the HelioCloud sample tutorials) for accessing them via the 'cloudcatalog' Python client.We

We created a full set of ML-ready EUV data from 1995 to present, accessible via the cloud, by bringing in historical restoration of the STEREO/SOHO era into a machine-learning (ML) -ready dataset. This work will enable research on events, evolution of solar irradiance, segmentation approaches, 360 degree maps of the sun, and other research topics as well as for use with space weather.  The reduced dataset is 6TB in size. The data will be freely available to scientists both within the AWS cloud and for downloading for local use on their laptops. The creation of this dataset had several steps, starting with the mechnical ingest stage (get the raw data), an analysis of best approach to create the ML-ready set, bulk processing, uploading the cloud, and dissemination and promotion. The task also required determination best approaches for cadence matching, interpolation, and effective spans of contiguous data for ML applications.

Work was funded under NASA Heliophysics 21-LWSTM21_2-0018, award number 80NSSC22K0643.