- Technical report
- Open Access
The ERG Science Center
- Yoshizumi Miyoshi1Email authorView ORCID ID profile,
- Tomoaki Hori1,
- Masafumi Shoji1,
- Mariko Teramoto1,
- T. F. Chang1,
- Tomonori Segawa1,
- Norio Umemura1,
- Shoya Matsuda2,
- Satoshi Kurita1,
- Kunihiro Keika3,
- Yukinaga Miyashita4,
- Kanako Seki3,
- Yoshimasa Tanaka5,
- Nozomu Nishitani1,
- Satoshi Kasahara3,
- Shoichiro Yokota2,
- Ayako Matsuoka2,
- Yoshiya Kasahara6,
- Kazushi Asamura2,
- Takeshi Takashima2 and
- Iku Shinohara2
© The Author(s) 2018
- Received: 4 September 2017
- Accepted: 23 May 2018
- Published: 15 June 2018
The Exploration of energization and Radiation in Geospace (ERG) project investigates radiation belt and geospace storm dynamics. The ERG (Arase) satellite was launched in December 2016 and began observations in March 2017. The satellite includes nine scientific instruments that provide various types of data for measuring plasma and particles over a wide energy range, as well as fields and waves over wide frequency ranges (Miyoshi et al. 2018).
However, for a comprehensive geospace investigation, ground-based observations and multi-point observations from the satellite are equally important. The ERG project, therefore, includes both satellite and ground-based observation teams. Ground-based observations are obtained from Super Dual Auroral Radar Network (SuperDARN) high-frequency (HF) radars, European Incoherent Scatter Scientific Association (EISCAT) radar, magnetometers, very low-frequency (VLF)/ELF (extremely low-frequency) loop antennas, riometers, VLF/low-frequency (LF) radio wave receivers, and optical imagers (Shiokawa et al. 2017).
Comparing simulations with observations is important to determine causal relationships and increase our quantitative understanding of various geospace phenomena. Hence, the project also involves a team that manages simulation and integrated studies (Seki et al. 2018).
However, it is not always easy to employ multiple datasets to their full potential, because it is difficult to learn the different types of data file formats and develop the necessary tools to access and process the relevant data for detailed analysis. Using common data formats and analysis tools can solve this problem. For example, the National Aeronautics and Space Administration (NASA)/Common Data Format (CDF) has standardized data storage and data access considerably. The solar–terrestrial physics community has developed common data analysis software, including the Space Physics Environment Data Analysis Software (SPEDAS), to analyze different data types for integrated studies. SPEDAS was originally developed for the Time History of Events and Macroscale Interactions during Substorms (THEMIS) mission and was known as the THEMIS Data Analysis Software (TDAS) (Angelopoulos 2008). This software is a suite of scientific analysis routines written in the Interactive Data Language (IDL). To promote accessibility for the space research community, other satellite projects, including the Magnetospheric Multiscale (MMS) mission (Burch et al. 2016) and Van Allen probes (Mauk et al. 2013), provided their own programs as SPEDAS plug-ins, by developing and customizing the SPEDAS code to enable seamless collaborative data sharing among missions.
Considering these advantages, the ERG project has archived its project data in CDF format and made these files accessible on the Internet. The ERG project has cooperated with the Inter-university Upper Atmosphere Global Observation NETwork (IUGONET) (Hayashi et al. 2013; Tanaka et al. 2013) to develop SPEDAS plug-ins for ground-based observation data. It has also cooperated with the THEMIS project to develop SPEDAS plug-ins to serve as common data analysis software across project teams (Hori et al. 2015). These include not only software to download data files from the remote data server, but also several tools to aid in data analysis, such as plasma dispersion solvers.
In order to coordinate observations made by the ERG satellite, on the ground, and by other satellites, it is necessary to properly organize the observation modes of the ERG satellite. The plasma wave experiment (PWE)/waveform capture (WFC) (Kasahara et al. 2018b; Matsuda et al. 2018) and Software-type wave –particle interaction analyzer (S-WPIA) (Katoh et al. 2017; Hikishima et al. 2018) have intermittently performed waveform observations along a satellite orbit. Waveform data of plasma waves are important for studying wave–particle interactions through detailed comparisons with the ground-based optical and wave observations (Shiokawa et al. 2017). The waveform data would accumulate more than 6 GB if always recorded along a satellite orbit. As a nominal case, the possible downlink budget available for the waveform data is approximately 700 Mb per day. Therefore, it is necessary to strategically select limited periods of waveform observations, taking into account the satellite orbit, conjunction periods with ground-based observations and other satellites, size of the data recorder, and the telemetry downlink plan.
Over the course of the data production pipeline described above, data are categorized into several predefined processing levels. Raw packet data received from the satellite and archived on SIRIUS are referred to as Level-0. Level-1 data are converted to regular files on the reformatting system at ISAS. Level-1 data carry time labels converted to Coordinated Universal Time (UTC), while observed data values are stored in instrument-dependent units. Further processes at the ERG-SC, including data calibration, generate Level-2 data. Unlike Level-1 data, Level-2 data have been assigned standard physical units as well as some geophysical coordinates. Data up to Level-2 are generated solely from Level-1 data of a single instrument. Level-3 data are the merged products of multiple Level-2 data points from different instruments. A typical example is pitch angle distributions of particle fluxes, which merges particle flux data from a particle instrument and magnetic field data from the magnetic field experiment (MGF) (Matsuoka et al. 2018). Another example is electron density data that are deduced using frequency traces of upper hybrid resonance observed by the PWE instrument (Kasahara et al. 2018b; Kumamoto et al. 2018) and MGF data. Level-3 particle data also go through inter-instrument calibrations to produce particle flux and phase space density data of electrons over a combined energy range of ~ 20 eV to more than 10 MeV. These data are referred to as Level-4 data.
Level-2 and higher-level data are archived as CDF data files (Hori et al. 2015). CDF supports various data types and data structures and allows data files to carry various forms of metadata. It also guarantees inter-operability independent of operating system and endian type of variables. In addition to its functionality, another benefit of archiving the project data in CDF is that CDF has become one of the de facto standard file formats of the solar–terrestrial physics community and the data in CDF are easily available in several software programs.
The ERG-SC has defined the standardized contents of data variables and metadata for data files archived in CDF. These standardized contents are used for both satellite observation data and ground-based observation data. In the past, many projects used their own data formats and data variable structures, which made it difficult for data users to combine data from different types of instruments in their data analyses. For example, the time label format often varies from project to project, and different observational data carry numerical values in different forms and are grouped into data files with different lengths. In fact, ERG satellite data and ground-based observational data were also provided in different formats/styles/granularity according to each instrument and observation team. In order to overcome this difficulty, the time label format is standardized by CDF epoch and data values are converted to the physical unit that can be directly used for data analysis. Moreover, the data format is rearranged in a simple and straightforward sequential order. The ERG-SC has unified them into our standardized data format and added common metadata. As a result, the data files contain ancillary information as metadata that are necessary for not only SPEDAS data analysis but other data analysis software. On the basis of discussions with the instrument and observation teams, the ERG-SC identified necessary ancillary information and defined the common metadata list to accommodate all necessary information. The designed metadata list was partly reported by the literature (Hori et al. 2015). Metadata also include information on the names of the original data and the programs with version ID to generate the CDF files. This information guarantees the traceability of the data version for both data users and the data archive center. Hence, these unified data archives, with the integrated data analysis tools described in the next section, allow data users to combine and analyze different types of data in a truly seamless way.
In general, the data center must overcome common difficulties, such as data file preservation and data transfer issues. For the ERG project data, the total size of possible data from both satellite and ground-based network observations is expected to be several tens of TB, and they can be processed without serious difficulty by utilizing commonly used computers and disk systems. Furthermore, the speed of commonly installed inter-university networks such as the Science Information NETwork (SINET) is not a bottleneck for data transfer from the ERG-SC to other universities and institutes.
As mentioned, the ERG-SC archives many types of data files and should control the version of the data file. For example, the number of satellite data product types is more than hundred, and the number of ground-based observation data product types is several hundreds. Because these data are irregularly transferred to the ERG-SC from each instrument and observation team, it is not easy to manage, archive, and deliver such various files of data to users. In order to overcome these difficulties, the ERG-SC developed a system to automatize the process of data production to the maximum extent possible. As discussed in Fig. 3, we have developed and connected many modules of data processing into a pipeline system which can facilitate all data processing from the raw observation data of each instrument and observation team to the scientific data files. The actual implementation of the system is made as much as possible with common routines of SPEDAS and IDL. Use of the single software language, which has also been widely used for scientific data analyses, enables efficient development of program codes and contributes to substantially reducing the time spent on development and maintenance work.
For data file preservation, a standardized data file containing all types of necessary information can contribute to this issue because a single data file carries all the necessary information for scientific analysis. The practical information contained in data files, such as file names with version numbers of the source data files, and computer codes to generate data files, enables automatic processing of data files in many tasks for maintenance of the data archive. In addition to these efforts, the data files are synchronized between the ERG-SC at Nagoya University and ISAS/JAXA for redundancy.
The ERG satellite operates nine science instruments for nominally observing plasma/particles and fields/waves as the nominal observations. Each instrument has several observation modes that are appropriately selected depending on various factors such as L-shell, magnetic latitude of the satellite position, so that planning of the science operation based on the predicted orbit is necessary. In addition to the nominal observations, the ERG satellite has burst mode operation modes for PWE/WFC and S-WPIA. Data from the burst observations of PWE/WFC and S-WPIA are first stored in the mission data recorders (MDR) and subsequently downloaded to the ground through the system data recorder (SDR) (Takashima et al. 2018). Note that the size of MDR and SDR is 32 GB and 2 GB, respectively.
The observation schedules for the ERG satellite are first drafted by the ERG-SC using information on the satellite orbit, the Earth’s shadowing, and the electric power available onboard. The sampling frequency for PWE and MGF instruments and the time resolution of particle instruments vary for each orbit. Intermittent chorus and EMIC burst observations of PWE/WFC and S-WPIA are also conducted, and plans are scheduled for the burst mode operations.
Besides the default observation schedules, conjugate observations with ground-based instruments and other satellites such as Van Allen Probes are often planned, in which PWE/WFC and S-WPIA are included. The drafted schedule files are reviewed by the instrument teams and then the finalized files are sent to the satellite tracking center in ISAS where they are converted to a command plan used to operate the satellite. If any problem is found in the schedule files, they are updated to satisfy the feasible operation conditions.
The possible data size for MDR to SDR transfer depends on the downlink plan from the satellite to the ground; therefore, the selection of burst observations of PWE/WFC and S-WPIA has to consider actual estimates of the downlink data size. Occasionally, the potential amount of downlink data for the waveform observations is small, less than 500 MB per day. If the downlink data amount can be estimated before uploading the schedule file to the satellite, we can reduce the operation periods for WFC and S-WPIA in the schedule file. On the other hand, if we know the possible downlink data amount after uploading the schedule file to the satellite, observations of WFC and S-WPIA are made and stored in MDR. In this case, because the potential amount of downlink data to the ground is smaller than the typical amount, careful data selection is required by looking at the PWE/OFA data and deleting some wave form data from MDR.
This paper provides an overview of the ERG-SC. The tasks of the ERG-SC include: (1) archiving data from the ERG satellite, ground-based instruments, and modeling/simulation; (2) developing SPEDAS plug-in software for data analysis and visualization of various data file types; and (3) scheduling observations and data downlinks from the satellite.
The data processing pipelines in this system employ commonly used software/languages, such as IDL, C, and UNIX shell. Thus, implementing these processes in various cloud-computing systems is technically feasible. In fact, the Center for Integrated Data Analysis Science (CIDAS), ISEE, Nagoya University, has been operating a cloud system in which users can use SPEDAS to analyze the ERG satellite data, ground-based observations, and other satellite data by connecting from their remote terminals. Use of a cloud system has great merit for users in that they do not need computer resources with large memory and a high CPU clock speed. Thus, cloud systems will be a useful computer environment for the large data quantity and varied data types included in the ERG-SC data archive.
The ERG-SC works as a hub for the ERG project by unifying management of data CDF files for different observations and modeling/simulation and integrated data analysis software to seamlessly visualize and analyze different types of data. As integrated data analysis is a key for a comprehensive understanding of phenomena that occur simultaneously at different locations, which are observed by several satellites and ground-based instruments, the ability to develop tools for such analyses is essential.
Because SPEDAS is a standard software package used across the space physics community, SPEDAS plug-ins contribute to providing a seamless data analysis environment across different projects. The ERG project has collaborated with the THEMIS team to develop and enhance SPEDAS by generating plug-in software that allows researchers to not only download files from the ERG project, but also perform advanced analysis, such as ISEE_3D and KUPDAP. It is worth mentioning science centers of other geospace projects. As an example of related geospace missions, the NASA/Van Allen Proves mission comprises science operation centers (SOC) for each instrument, and each SOC provides its own database and software for data analysis (e.g., Kletzing et al. 2013; Spence et al. 2013). Similar to the ERG-SC, science data files are archived in CDF format and these CDF files can be accessed via the internet, so that users can use appropriate software for their analysis. This is a good example of the benefits of using standardized data files. Software like SPEDAS can read and manipulate data in CDF files from both the ERG project and Van Allen Probes, which is helpful for analyzing phenomena from various angles by integrating different types of data. The developed software, combining different data types, will be an important legacy for future space science missions. The ERG-SC thus contributes to achieving the scientific objectives of the ERG project, providing new insights into the dynamics of radiation belts and the inner magnetosphere.
YM is the manager of the ERG-SC and the project scientist of the geospace exploration project ERG. TH is the sub-manager of the ERG-SC and takes a lead of the development of CDF files for HEP, MEPs and Super Dual Auroral Radar Network (SuperDARN) and related ground-based data and development of SPEDAS plug-in. MS is a member of the ERG-SC and takes a lead of the development of CDF files for PWE, KUPDAP, and simulation data. MT is a member of the ERG-SC and takes a lead of XEP and MGF. TC is a member of the ERG-SC and takes a lead of LEP-e and the orbit/attitude files. TS and NU are engineers at the ERG-SC to develop several tools and operate computer resource. SM is a member of the ERG-SC and develops tools for plasma waves analysis and the data manager of ERG/PWE. SK is a member of the ERG-SC and supports to develop CDF files for Arase and ground-based data. KK is a member of the ERG-SC and takes a lead of development for ISEE_3D and CDF files for MEP and orbit file. YM was a member of the ERG-SC and took a lead of development of MGF and XEP and CEF. KS is a member of the ERG-SC and supports to develop tools. YT is a member of IUGONET and has collaborated with the ERG-SC. SK is the PI of MEP-e. SY is the PI of MEP-i. AM is the PI of MGF. YK is the PI of PWE. NN is a member of the ERG-SC and suggests developing CDF files. KA is a member of the ERG-SC and the lead manager of the science instruments of the Arase satellite. TT is a member of the ERG-SC and the mission manager of the Arase project. IS is a member of the ERG-SC and the project manager of the Arase project. All authors read and approved the final manuscript
We thank to all members of the ERG project to their great efforts to realize this mission for many years. This work was also supported by JSPS Grants-in-Aid for Scientific Research (15H05815, 15H05747, 16H06286, 16H04056, 16H01172). The authors thank Vassilis Angelopoulos and the THEMIS team for developing SPEDAS. The authors also thank the IUGONET project for collaborations on development of SPEDAS.
The authors declare that they have no competing interest.
Availability of data and materials
All science data of the ERG project are distributed by the ERG-SC (https://ergsc.isee.nagoya-u.ac.jp/index.shtml). MMS data are provided from MMS Science Data Center (https://lasp.colorado.edu/mms/sdc/public/). The AE index is provided from WDC for Geomagnetism, Kyoto (http://wdc.kugi.kyoto-u.ac.jp/aedir/).
Ethics approval and consent to participate
The ERG Science Center is operated by ISAS/JAXA and ISEE/Nagoya University.
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