Speaker
Description
Even for identical radiation monitors deployed in space on miscellaneous satellites and operated by diverse providers, their data often reside in separate locations, with fragmented, mission specific formats. They are often distinct from the original, instrument related data acquisition protocols. Therefore, getting access to them generally requires unique specialized software. In addition, persistent attempts for employing the existing standards for radiation data format are still ahead of satisfactory, large-scale implementation.
It poses several challenges for the space weather community in terms of collaboration efforts and time-efficient analysis, visibly delaying ongoing research. On the other side, typical database from space radiation monitors, even covering operation periods of decades, is usually of the order of tens of Gigabytes only, allowing for fast and frequent data processing.
To address these issues, we have developed a two-part software solution RADMONQA – Radiation Monitors Quick Analysis tool that, in its current stage, integrates measurements from two space radiation detectors: IREM and RADEM.
The INTEGRAL Radiation Environment Monitor (IREM) conducts permanent observations of energetic protons and electrons along the orbit of the ESA INTErnationalGamma-Ray Astrophysics Laboratory (INTEGRAL) operating continuously for more than two decades. Its science data include regular radiation belt scans, large number of Solar Energetic Particles (SEP) detections as well as numerous Forbush decreases.
The Radiation Hard Electron Monitor (RADEM) was launched in April 2023 onboard ESA Jupiter Icy Moon Explorer (JUICE) mission headed for Jupiter. Its eight years long cruise to the giant planet through the inner and outer solar system allows for continuous detections of SEPs and Forbush decreases using its telescope detectors optimized for measurements of electrons and protons.
RADMONQA real-time web application relies on the InfluxDB platform for making easily accessible database and further services offered by the Grafana visualization platform. Its basic functionality is defined below:
• automatic retrieval and preprocessing of the latest data
• updating and upgrading the database
• exploring and visualization of data through interactive dashboards
• simple data transformations
• straightforward deployment
The second solution of RADMONQA relies on the previously created database and utilizes Python library in form of Jupyter Notebooks. Its basic currently implemented functions are shown below:
• standardized methods for IREM and RADEM data preprocessing
• search and visualization methods for SEP detections
• search and visualization methods for Forbush decrease detections
• search and visualization methods for radiation belt passes
• adding new variables for further correlation analysis:
o satellite position (in various coordinate systems)
o instrument pointing direction
o magnetic field data, etc.
The system is currently deployed at PSI using its internal services. In the next stage we will provide open access to both solutions allowing for a quick-look data visualizations and Python library for fast analysis. Examples of application methodology with the system architecture and workflow will be presented. We will also show standard user tools with selected examples of plots and tables from Jupyter Notebooks applications.
