Global Ionospheric Radio Observatory (GIRO)
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Digisonde ionospheric sounders installed at 80+ locations in the world have gradually evolved their generally independent existence into a Global Ionospheric Radio Observatory (GIRO) portal. Today GIRO provides public access to 30+ million records of ionospheric measurements collected at 64 locations, of which 42 provide realtime feeds, publishing their measurement data within several minutes from their completion. GIRO databases holding ionogram and Doppler skymap records of high-frequency ionospheric soundings have registered connections from 123 organizations in 33 countries. Easy access to the global state of the ionospheric plasma distribution given in accurate and fine detail by the ionosonde measurements has inspired a number of studies of the ionospheric response to space weather events. Availability of GIRO data with minimal latency allows for the assimilation of the ionogram-derived data in real-time models such as the real-time extension planned for the International Reference Ionosphere.
Key wordsDigisonde network ionospheric database real-time IRI GIRO
Accurate global modeling of Earth’s ionosphere requires data from around the globe, and for a long time the data coverage has been inadequate. A quiet revolution in sensor network technologies started in the late 1990s with the advent of low-cost information technology solutions that permitted researchers and engineers to acquire, archive, and access their sensor data “without time or distance barriers” (NSF, 2003). Soon thereafter, a suite of virtual observatories (VxO) started to emerge, with the task of registering a multitude of new data providers and their datasets in a uniform fashion under the framework of the SPASE metadata model (King et al., 2008). The new community of interoperable data providers has since then sustained its standalone operations at various host institutions, complementing the activities of the larger science data warehouses operated by governmental agencies, such as NASA and NSF in the United States, and international archives like the World Data Centers.
Three main system developments have enabled the GIRO evolution: (1) database organization of the GIRO data at a central location with remote public access for both reading and writing; (2) custom software solutions that support GIRO operations in its multiple scenarios, ranging from expert ionogram interpretation to real time assimilation of ionogram-derived products, and that monitor the GIRO state of health; and (3) new installations of Digisonde-4D sounders (Reinisch et al., 2009), increasing the number of fielded instruments.
GIRO comprises three components: (1) the network of Digisonde stations providing online and offline data; (2) two master GIRO databases, the Digital Ionogram Data Base (DIDBase) and the DriftBase for skymap/drift measurements; and (3) associated software capable of automatic and interactive data analysis and the derivation of higher order data products for end user applications (Galkin et al., 2008b; Khmyrov et al., 2008; Kozlov and Paznukhov, 2008). The greatest operational impact has come through the single-point availability of the global network’s realtime and retrospective data to both scientists and computer algorithms, free from handling tapes, cartridges, CDs, etc., a much-needed capability.
2. Background: HF Sounding of the Ionosphere
Extraction and interpretation of the signal traces in recorded ionogram images is an intelligent, machine-hard problem of feature recognition. The GIRO provides access to the Automatic Real-Time Ionogram Scaler with True height (ARTIST) software, an “autoscaler” of ionogram traces that uses the heritage of algorithm development going back to the 1980s (Reinisch and Huang, 1983; Galkin et al., 2008b). About 7% of available GIRO ionograms underwent a labor-intensive process of manually validating the autoscaling results. As of November 3, 2010 the DIDBase repository holds 733,516 records of expert-level manual ionogram scaling.
3. GIRO Research Projects
A prototype of the GIRO infrastructure was deployed in 2001 at the University of Massachusetts Lowell (UML) and, recognizing its utility in aiding ionospheric research, UML has continued its operation since then. The cornerstones of GIRO operations are the Digital Ionogram Data Base (DIDBase) with a Web portal access at http://ulcar.uml.edu/DIDBase/, and the expert-level platform-independent software client “SAO Explorer” with read/write access to DIDBase over the Internet. The first in-depth usage of the GIRO capability was made by the Aerospace Corporation, whose calibration and validation (CalVal) study (Paxton et al., 2002) of the UV instrumentation on DMSP satellites (Huffman, 1994) demanded accurate knowledge of the EDPs during the spacecraft passes over contributing GIRO locations. Orbit propagator software generated 20,524 coincidence time intervals for which manually validated EDPs were requested from the DIDBase. This required the manual editing of 113,202 ionograms; i.e., four to five ionograms per station over-flight (over 5,000 man-hours!). The third CalVal campaign began in March 2010 and will continue to the end of 2011.
Easy access via GIRO to the globally distributed measurements of the ionospheric plasma has also inspired a number of studies of the ionospheric response to space weather events (e.g., Abdu et al., 2008; Lei et al., 2008; Paznukhov et al., 2009; Zong et al., 2010; Stanislawska et al., 2010).
4. Real-time GIRO Applications
Use of real-time ARTIST-derived data as input to ionospheric models and associated algorithms such as ray tracing and optimal frequency allocation started in 1988 when the USAF Weather Agency (AFWA) established a network of 18 Digisondes (Buchau et al., 1995). The real-time data streams from these instruments were provided for assimilation into ICED/PRISM (Daniell et al., 1990, 1993) and later to GAIM (Schunk et al., 2004; Scherliess et al., 2006). Since then, other agencies have built similar networks: the Digital Atmospheric Server (DIAS) (Belehaki et al., 2005) became operational in 2004 with 6 contributing Digisondes located in Europe; and the Jindalee Operational Radar Network of the Australian government installed 11 Digisondes (Gardiner-Garden, 2006) to provide data to their real time ionospheric model RTIM (Wheadon et al., 1994; Barnes et al., 2000). GIRO data have also been used to update the Boeing Plasma Interaction Model (PIM) (Barsamian et al., 2003) in support of spacewalk scheduling for the International Space Station.
5. Public Access to GIRO Repositories
In 1997, the embedded computers in the Digisonde ionospheric sounders started web-publishing three data products: the latest ionogram measurement image, the 2-week history of ionogram measurements, and the complete historic record of ionogram-derived autoscaled data at a station. The original enthusiasm of the 1990s, however, wore off a decade later because of concerns that exposure to the hazards of the internet may compromise the instruments. A growing number of Digisondes closed their site to direct access, and instead the web portal became a new paradigm of centralized management of the Digisonde data. Such a portal can provide one-stop access to all Digisonde-related functions, including data visualization and expert ionogram interpretation using the interactive SAO Explorer and Drift Explorer tools (Khmyrov et al., 2008; Kozlov and Paznukhov, 2008). The GIRO Web Portal, http://giro.uml.edu/, provides a common point for data providers (62 locations in 27 countries) and data users (123 organizations with 153 read-only and 34 expert read-write accounts). Increasing attention is drawn to the latest ionogram images from contributing stations, including 24-hour up-to-date composite GIRO ionogram movies at http://giro.uml.edu/IonogramMovies/.
6. Future Development
Recently, the International Reference Ionosphere (IRI) science team started developing a real-time IRI extension that will depend on GIRO streams. By design, IRI belongs to a class of empirical models (Bilitza, 2001, 2004, 2009) that represent direct ionospheric measurements, thus avoiding the uncertainties of the evolving theoretical understanding of ionospheric processes and their coupling to processes in the magnetosphere, interplanetary space, and lower atmosphere. As such, IRI captures very well the prominent features of the plasma behavior, such as the day/night changeover, the Appleton anomaly, and seasonal climatology that persists over long periods of time. While the IRI model is often anecdotally portrayed as the “best” ionospheric background model, it has had only limited success in representing ionospheric responses to various short-term events, observed during periods of storm activity (Araujo et al., 2005) or the impact of gravity waves coupling the ionosphere to the lower atmosphere. Ingestion of real time GIRO and other data into IRI is now being considered with the aim of “updating” the IRI electron density distribution while preserving the overall integrity of its representation of typical ionospheric features.
An initial approach to the IRI assimilation task could be for GIRO to determine an “effective” solar activity index (R12) value as a function of time to be used instead of the predicted R12 value for the month of interest. The index R12 is the only independent parameter in IRI and can be manipulated to minimize the cumulative discrepancy between the model and available observations similar to the methods reported by Hernandez et al. (2002) and Zolesi et al. (2004). Such single parameter approach will likely not be fully satisfactory for global coverage of the model. It will be better to expand the assimilation algorithm by evaluating and minimizing varying global differences between model and observations, rather than assuming a constant bias. Using the capability of the GIRO to store sensor measurements in the database, the assimilation algorithm would analyze the latest 24-hour history of differences between the IRI prediction and the ionogram-derived characteristics to mitigate those differences. The Galileo correction model is based on similar techniques (e.g., Rogers et al., 2005).
GIRO provides a one-point access to a global network of digital ionosondes many of which feed their data in real time to the GIRO data depositories. The steadily increasing use of DIDBase and DriftBase by scientists, engineers, students, and radio amateurs across the globe, especially from developing countries, suggests that the GIRO Portal is a desirable service to the ionosphere and space weather community.
The initial DIDBase repository was established with support from the USAF Research Laboratory through contract # F19628-02-C-0092. The authors acknowledge Digisonde owner organizations and international ionogram scaling teams for their good will in continuing uploads of their data to GIRO for public dissemination.
- Abdu, M. A. A., E. R. de Paula, I. S. Batista, B. W. Reinisch, M. Matsuoka, P. Camargo, O. Veliz, C. M. Denardini, J. H. A. Sobral, E. A. Kherani, and P. Sequeira, Abnormal evening vertical plasma drift and effects on ESF and EIA over Brazil-South Atlantic sector during the October 30, 2003 super-storm, J. Geophys. Res., 113 (A7), A07313, doi: 10.1029/2007JA012844, 2008.Google Scholar
- Barnes, R. I., R. S. Gardiner-Garden, and T. J. Harris, Real time ionospheric models for the Australian Defence Force, Proc. WARS-2000, 122–135, 2000.Google Scholar
- Barsamian, H., R. Mikatarian, J. Alred, J. Minnow, and S. Koontz, ISS Plasma Interaction: Measurements and modeling, 8th Spacecraft Charging Technology Conference, Huntsville, AL, 2003.Google Scholar
- Belehaki, A., L. Cander, B. Zolesi et al., DIAS project: The establishment of a European digital upper atmosphere server, J. Atmos. Sol.-Terr. Phys., 1092–1099, 2005.Google Scholar
- Buchau, J., T. W. Bullett, A. E. Ronn, K. D. Scro, and J. L. Carson, The Digital Ionospheric Sounding System network of the US Air Force Weather Service, WDC-A for Solar-Terr. Phys., Report UAG-104, pp. 16–20, 1995.Google Scholar
- Daniell, R. E., D. T. Decker, D. N. Anderson, J. R. Jaspers, J. J. Sojka, and R. W. Schunk, A Global Ionospheric Conductivity and Electron Density (ICED) Model, in Proceedings of the Ionospheric Effects Symposium, edited by J. M. Goodman, 1–3 May 1990, 1990.Google Scholar
- Daniell, R. E., W. G. Whartenby, and L. D. Brown, Parameterised Real Time Ionospheric Specification Model, PRISM version 1.2, Computational Physics, Inc., 385 Elliot St, Newton, MA 02164, USA, 1993. PRISM version 1.2Google Scholar
- Gardiner-Garden, R. S., Ionospheric variability in sounding data from JORN, Proc. WARS 2006, Leura, NSW, Australia, 2006.Google Scholar
- King, T., J. Merka, R. Walker, S. Joy, and T. Narock, The architecture of a multi-tiered virtual observatory, Earth Sci. Inf., 1, doi: 10.1007/s12145-008-0006-3, 2008.
- Kozlov, A. and V. V. Paznukhov, Digisonde drift analysis software, in Radio Sounding and Plasma Physics, AIP Conf. Proc., 974, 167–174, 2008.Google Scholar
- Lei, J., W. Wang, A. G. Burns, S. C. Solomon, A. D. Richmond, M. Wiltberger, L. P. Goncharenko, A. Coster, and B. W. Reinisch, Observations and simulations of the ionospheric and thermospheric response to the December 2006 geomagnetic storm: Initial phase, J. Geophys. Res., 113 (A1), A01314, doi: 10.1029/2007JA012807, 2008.Google Scholar
- NSF Program Solicitation 03-512, Sensors and Sensor Networks, March 2003, 2003.Google Scholar
- Paxton, L. J., D. Morrison, Y. Zhang, H. Kil, B. Wolven, B. S. Ogorzalek, D. C. Humm, and C.-I. Meng, Validation of remote sensing products produced by the Special Sensor Ultraviolet Scanning Imager (SSUSI): a far UV-imaging spectrograph on DMSP F-16, Proc. SPIE, 4485, 338–348, 2002. 10.1117/12.454268CrossRefGoogle Scholar
- Rogers, N., J. E. N. Field, P. S. Cannon, and M. J. Angling, An assessment of the Galileo single-frequency ionospheric correction model, www.ursi.org/Proceedings/ProcGA05/pdf/GP1G02.6(01296).pdf, 2005.
- Scherliess, L., R. W. Schunk, J. J. Sojka, D. C. Thompson, and L. Zhu, Utah State University Global Assimilation of Ionospheric Measurements Gauss-Markov Kalman filter model of the ionosphere: Model description and validation, J. Geophys. Res., 111, A11315, doi: 10.1029/2006JA011712, 2006.CrossRefGoogle Scholar
- Wheadon, N. S., J. C. Whitehouse, J. D. Milsom, and R. N. Herring, Ionospheric Modeling and Target Coordinate Registration for HF Sky-wave radars, HF Radio Systems and Techniques, No 392, 4–7, 1994.Google Scholar
- Zong, Q.-G., B. W. Reinisch, P. Song, Y. Wei, and I. Galkin, Dayside ionospheric response to the intense interplanetary shocks/solar wind discontinuities: Observations from the digisonde global ionospheric radio observatory, J. Geophys. Res., 115, A06304, doi: 10.1029/2009JA014796, 2010.Google Scholar