Cluster Ion Spectrometry (CIS) Data Archiving in the CAA

Physics

Scientific paper

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[1912] Informatics / Data Management, Preservation, Rescue, [2794] Magnetospheric Physics / Instruments And Techniques

Scientific paper

The Cluster Active Archive (CAA) aims at preserving the four Cluster spacecraft data, so that they are usable in the long-term by the scientific community as well as by the instrument team PIs and Co-Is. This implies that the data are filed together with the descriptive and documentary elements making it possible to select and interpret them. The CIS (Cluster Ion Spectrometry) experiment is a comprehensive ionic plasma spectrometry package onboard the four Cluster spacecraft, capable of obtaining full three-dimensional ion distributions (about 0 to 40 keV/e) with a time resolution of one spacecraft spin (4 sec) and with mass-per-charge composition determination. The CIS package consists of two different instruments, a Hot Ion Analyser (HIA) and a time-of-flight ion Composition Distribution Function (CODIF) analyser. For the archival of the CIS data a multi-level approach has been adopted. The CAA archival includes processed raw data (Level 1 data), moments of the ion distribution functions (Level 2 data), and calibrated high-resolution data in a variety of physical units (Level 3 data). The latter are 3-D ion distribution functions and 2-D pitch-angle distributions. In addition, a software package has been developed to allow the CAA user to interactively calculate partial or total moments of the ion distributions. Instrument cross-calibration has been an important activity in preparing the data for archival. The CIS data archive includes also experiment documentation, graphical products for browsing through the data, and data caveats. In addition, data quality indexes are under preparation, to help the user. Given the complexity of an ion spectrometer, and the variety of its operational modes, each one being optimised for a different magnetospheric region or measurement objective, consultation of the data caveats by the end user will always be a necessary step in the data analysis.

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