Displays

Daedalus is a new satellite mission concept for studying the lower thermosphere-ionosphere (LTI). The mission is currently undergoing Phase 0 studies, funded by ESA as one of three missions that are candidates for becoming its Earth Explorer 10 mission (EE10).

Using an elliptical orbit with a very low perigee (140 km and lower), the mission will make comprehensive in-situ measurements, including local density, composition, temperature and velocities of both the neutral and charged particles. An option of having two Daedalus satellites is being studied to allow better separation of temporal and spatial variability, and to better measure the strong vertical gradients and wave activity that occur in the LTI. The complete suite of instruments on Daedalus will allow the computation of higher level products such as local collision frequencies, conductivities and heating rates, along the orbit. The unique complementarity of instrumentation and orbit sampling over a large range of altitudes will be extremely valuable in advancing the science of the LTI region, which is a key region for many space weather phenomena.

High quality visualizations of models and data are very important during the definition of the mission. They allow both experts and newcomers to the field to better comprehend the physics of the LTI region, how it couples with other regions and systems, as well as how Daedalus will be able to sample this region from its unconventional orbit. The presentation will showcase 2D and 3D visuals that were developed during the phase 0 studies, and that make use of empirical and physics-based models of the thermosphere-ionosphere, Earth's magnetic field and simulated satellite orbits.

How to cite: Doornbos, E., Sarris, T., Tourgaidis, S., Pirnaris, P., Buchert, S., Liu, H., Lu, G., and Gasperini, F.: Visualizing models and observations of the thermosphere-ionosphere in support of the ESA EE10 candidate mission Daedalus, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7386, https://doi.org/10.5194/egusphere-egu2020-7386, 2020.

An open-ended, high cadence, Kp-like geomagnetic index, called Hp index, is developed within the H2020 project SWAMI (Space Weather Atmosphere Models and Indices). The traditional Kp index is an excellent measure for energy input by the solar wind and is widely used in space weather science and applications. The new planetary index Hp resembles the Kp index by having a similar derivation scheme and a nearly identical frequency distribution of index values. Hp is available from 1995 onward with different time resolutions, e.g., 30 minutes and 60 minutes, and thus provides a higher temporal resolution than the 3-hourly Kp index. Additionally, events with Hp > 9- were further subdivided using an open-ended scale (9o, 9+, 10-, 10o, 10+, 11-, ...) to represent the highest levels of geomagnetic activity with higher resolution.

How to cite: Matzka, J., Kervalishvili, G., Rauberg, J., Stolle, C., and Yamazaki, Y.: Open-ended, high cadence, Kp-like geomagnetic index Hp, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6646, https://doi.org/10.5194/egusphere-egu2020-6646, 2020.

An intriguing aspect of the 2 September 1859 geomagnetic disturbance (or Carrington event) is the horizontal magnetic dataset measured in Colaba, India (magnetic latitude approximately 20 degrees N). This dataset exhibits a sharp decrease of over 1600 nT and a quick recovery of about 1300 nT, all within a few hours during the solar daytime. The mechanism behind this has previously been attributed to magnetospheric processes, ionospheric processes or a combination of both. In this talk, we outline our efforts to recreate this low-latitude magnetic dataset using the Space Weather Modelling Framework (SWMF). By simulating an array of extremely high pressure solar wind scenarios, we can recreate the low-latitude surface magnetic signal at Colaba. We find that the position of the magnetopause is an important factor for such quick deviations and recoveries in dayside surface magnetic measurements. In addition, we find that scenarios which accurately recreated surface magnetic field observations during the Carrington event had minimum Dst values of only -610 nT.

How to cite: Blake, S., Pulkkinen, A., Schuck, P., and Glocer, A.: Recreating the Carrington Event Magnetic Field Measurements using Extremely High Pressure Solar Wind Scenarios and the Space Weather Modelling Framework, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22086, https://doi.org/10.5194/egusphere-egu2020-22086, 2020.

Many of the modern Low-Earth-Orbiting satellites are now equipped with dual-frequency GPS receivers for Radio Occultation (RO) and Precise Orbit Determination (POD). The space-borne GPS measurements can be successfully utilized for ionospheric climatology and space weather monitoring. The combination of GPS measurements, which include RO observations and POD measurements from the upward-looking GPS antenna, provides information about electron density distribution (profile) below the satellite orbit and an integrated Total Electron Content (TEC) above the satellite representing an important data source for electron density climatology above the F2 layer peak on a global scale. We demonstrate the advantages of using space-borne LEO GPS measurements, both RO and upward-looking, for Space Weather activity monitoring including specification of ionospheric plasma density structures at different altitudinal domains of the ionosphere in quiet and disturbed conditions. After the great success of the COSMIC-1 (Constellation Observing System for Meteorology, Ionosphere, and Climate) mission operating since 2006, the six COSMIC-2 satellites were launched into a 24 deg inclination orbit in June 2019. The COSMIC-2 scientific payloads with the advanced Tri-GNSS Radio-Occultation Receiver System provide multiple observation types including multi-GNSS TEC (limb and overhead), RO electron density profiles, amplitude/phase scintillation indices, in-situ ion densities and velocities. The COSMIC-2 advanced instruments allow detection of ionospheric plasma density structures of various scales, and the monitoring of high-rate amplitude and phase scintillations both above and below a satellite orbit. The COSMIC-2 multi-instrumental observations will contribute to a better understanding of the equatorial ionosphere morphology and future forecasting of ionospheric irregularities and radio wave scintillations that harmfully affect satellite-to-Earth communication and navigation systems. We present results of post-event analyses for severe space weather events demonstrating a great potential and contribution of the COSMIC-1/2 missions in combination with the ground-based GNSS receivers and other LEO missions like C/NOFS, DMSP, MetOp, TerraSAR-X, and Swarm for monitoring the space weather effects in the Earth’s ionosphere.

How to cite: Zakharenkova, I., Cherniak, I., Sokolovskiy, S., Schreiner, W., Wu, Q., and Braun, J.: Low-Earth-Orbit observations for space weather and space climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12209, https://doi.org/10.5194/egusphere-egu2020-12209, 2020.

Nowcast and forecast of ring current electron dynamics are crucial for space weather applications since the elevated fluxes of the ring current electrons may lead to surface charging of satellites that operate in the inner magnetosphere. Physics-based models of ring current electron dynamics contain uncertainties in boundary conditions, electric and magnetic fields, electron scattering rates, and plasmapause and magnetopause locations. The accuracy of the models can be improved by correcting the model predictions given the information obtained from in-situ satellite measurements by means of data assimilation techniques.

The scarcity of in-situ measurements may complicate the application of data assimilation methods for ring current electrons. The effect of data assimilation methods can be localized in time in space due to the multidimensionality of the ring current models and spatial and temporal limitations of spacecraft measurements. In this work, we investigate whether the Kalman filter can be used to improve ring current model predictions given only sparse satellite measurements. We blend the convection part of the four-dimensional Versatile Electron Radiation Belt code with the Van Allen Probe data, using the log-normal Kalman filter. By using synthetic data, we show that the Kalman filter is capable of correcting errors in model predictions associated with uncertainties in electron lifetimes, boundary conditions, and convection electric fields. We demonstrate that reanalysis retains features that cannot be fully reproduced by the convection model such as storm-time earthward propagation of the electrons down to 2.5 Earth’s radii. The Kalman filter can adjust model predictions to satellite measurements even in regions where data are not available. Our results demonstrate that data assimilation can improve the performance of ring current models, better quantify model uncertainties, and help us to improve the nowcast and forecast of the dynamics of the particles in the inner magnetosphere.

How to cite: Aseev, N. and Shprits, Y.: Reanalysis of ring current electron phase space densities using Van Allen Probe observations, convection model, and log-normal Kalman filter, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17747, https://doi.org/10.5194/egusphere-egu2020-17747, 2020.

Most if not all terrestrial weather prediction services today are based on data assimilation and numerical weather prediction models. Space Weather services are expected to follow a similar path towards data assimilation. However, the application of data assimilation in Space Weather requires a different implementation compared to terrestrial weather because space systems tend to be strongly forced and because the amount of data available for assimilation is critically small. In this paper we review the implementation of an ensemble Kalman filter data assimilation system based on the Space Weather Prediction Center operational Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model. We present assimilation results for neutral mass density during geomagnetically quiet and disturbed conditions and discuss the future use of data assimilation for the thermosphere ionosphere system. 

How to cite: Codrescu, M., Codrescu, S., Fedrizzi, M., and Borries, C.: On Space Weather Data Assimilation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9196, https://doi.org/10.5194/egusphere-egu2020-9196, 2020.

In order to estimate the potential hazard to technological systems from space weather, it is necessary to understand the spatiotemporal evolution of the geoelectric field during geomagnetic disturbances. Once the geoelectric field is quantitively estimated, geomagnetically induced currents can be calculated from the geometry of transmission lines and system design parameters. To address the complex problem of the ground electromagnetic (EM) field modelling due to space weather events, it is necessary to consider the spatiotemporal structure of the source of the EM induction in a realistic way and take into account a realistic three‐dimensional (3‐D) distribution of the Earth's electrical conductivity.

In this work we compare three approaches to the geoelectric field modelling. All approaches are based on the numerical solution of Maxwell's equations in Earth's models with 3-D conductivity distribution. The difference between them lies in different setting of the EM induction source. In the first two methods the source is represented by a laterally varying sheet current flowing above the Earth. The current in the first approach is computed on the base of 3-D magnetohydrodynamic simulation of near-Earth space. In the second one the source is constructed using ground-based magnetometers' data. In the third approach the geoelectric field is calculated using plane wave excitation. We carry out geoelectric field modellings for Kola Peninsula and Karelia using these three approaches. In our simulations we utilise the 3-D conductivity model of Fennoscandia (SMAP). The geoelectric field is computed using 3-D EM forward modelling code extrEMe based on a contracting integral equation method. We compare modelling results to EM field observations and discuss advantages and disadvantages of the considered approaches.

How to cite: Marshalko, E., Kruglyakov, M., Kuvshinov, A., Sokolova, E., Pilipenko, V., and Kozyreva, O.: Comparing three approaches to the ground geoelectric field modelling due to space weather events, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7702, https://doi.org/10.5194/egusphere-egu2020-7702, 2020.

We present observational evidence of mirror waves in the dayside inner magnetosphere as measured with instrumentation on the dual NASA Van Allen Probes spacecraft.  While mirror waves near the dayside bow shock have been reported from several spacecraft missions (e.g. Cluster, THEMIS, MMS), their presence in the dayside inner magnetosphere has not been reported.  We speculate that the mirror modes are associated with direct dayside injections under negative Bz conditions, and drift to lower L-shells.  The analyzed event coincides with the main phase of a CME shock-induced space weather storm, with high solar wind speeds in excess of 700 km/s and a sudden drop in Dst occurring approximately eight hours prior to the event.  The highest plasma beta values were measured by spacecraft B at 12:24 at magnetic noon at L ~ 4.5-5.5.  Spacecraft A later measured a similar feature at 13:00 local magnetic time.  The potential presence of such mirror waves would indicate dayside sources of anisotropy inside the magnetopause, or the penetration of bow shock particles into the dayside inner L-shells.  To our knowledge, this is the first time such waves have been reported in the inner magnetosphere.

How to cite: Cooper, M., Gerrard, A., Lanzerotti, L., Perry, G., and Soto-Chavez, R.: Dispersionless and Weakly Dispersed Injections in the Dayside Magnetosphere with Evidence of Mirror Wave Signatures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2696, https://doi.org/10.5194/egusphere-egu2020-2696, 2020.

It is an important method to study solar wind speed through observation of Interplanetary Scintillation (IPS). There are two big antenna with multi- frequency channels simultaneous observing interplanetary scintillation in Miyun Observatories NAOC. The aperture of the antenna is 40 meters and 50 meters respectively. There are two dual-frequency channels available in these systems: 327/611 MHz and 2300/8400 MHz. We will carriy out a comparison of these method using the normalized cross-spectrum and dual- frequency IPS measurement to observing the solar wind speed. Dual-Antenna Interference system have better sensitivity and time resolution. It can observe more weak radio sources one by one around the Sun. We can obtain more solar wind information on the Solar-Terrestrial distribution. 

How to cite: Liu, D.: Observing Interplanetary Scintillation with Dual-Antenna Interference , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6373, https://doi.org/10.5194/egusphere-egu2020-6373, 2020.

Available space weather forecasts mainly use data from the Sun and upstream interplanetary monitoring, to provide the early warning. Although the accuracy is improving, it cannot provide onset timing and actual strength of the substorm and its propagations better than 1 hour. A higher-accuracy forecast requires monitoring of the ionosphere (e.g., aurora and geomagnetic field). In this sense, it is also necessary to develop a value-based nowcast based on such monitoring. In EGU 2018, Yamauchi et al. has proposed simple index showing aurora and geomagnetic conditions using 1-minute resolution values from Kiruna. This study improved in the following directions:

(1) We used 1-sec resolution data and optimized the indices above: By using 1-sec values, the products representing variation (standard deviation and peak-to-peak variation) can be obtained every minute and improved, whereas combination of ∑L³ (or ∑L*exp(L)) and area of aurora found to be the best in representing the aurora activity, where L is luminosity of each pixel defined by HLS color code. Using these values, we confirmed that the intensity of the aurora was different for the same magnetic variation between before and after the strongest aurora (substorm onset). Therefore, it is necessary to add a condition of "increasing trend" of both aurora and magnetic variation from the viewpoint of forecasting.

(2) We compared the results from two different places (Abisko and Kiruna in Sweden) that are 89 km apart in linear distance. Our Abisko camera system (DASC, Digital All Sky Camera) is in operation since March 2014. When the aurora was observed at both sites, the shapes of the aurora at both sites are sometimes quite different at the same time. In addition, the timing of the brightest aurora (∑L³ or ∑L*exp(L) is maximum) was different between both sites. These results confirm that the aurora had a three-dimensional structure, which has been known for many years.

(3) Using superposed epoch analysis, we also took statistics of last 10 minutes before the largest aurora (in the index mentioned above) occurred.

How to cite: Sugihara, K., Yamauchi, M., Kobayashi, M., Koichi, S., and Nishi, M.: Evaluation of Aurora Activity Obtained from Abisko and Kiruna Ground Based Observation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7474, https://doi.org/10.5194/egusphere-egu2020-7474, 2020.

The PECASUS Consortium (European Consortium for Aviation Space weather User Services) provides targeted space weather services focusing on the dissemination of warning messages, called 'advisories', towards aviation actors. PECASUS services corresponds to extreme space weather events with impact on aviation GNSS systems, HF communication and radiation levels at flight altitudes. In November 2018 ICAO (International Civil Aviation Organization) designated three global space weather service centers. These centers acre operated by the European PECASUS consortium, by United States and by the consortium of Australia, Canada, France and Japan.

PECASUS was set-up as a consortium bringing together a number of European partners with proven space weather service capabilities. The PECASUS consortium is coordinated by FMI (Finland) who is also the ultimate responsible for communications towards the aviation sector. The Advisory Messages are produced by STCE (Belgium) on the basis of expert interpretation and data streams produced by DLR (Germany), INGV (Italy), Seibersdorf Laboratories (Austria), STCE (Belgium), SRC (Poland) and FU (Cyprus). In addition, the MetOffice (UK) will act as a resilience node in case of a major failure in the network, while the KNMI (The Netherlands) will take care of user liaison and monitor the PECASUS performance.

The PECASUS Consortium was audited in February 2018 by space weather and operational management experts, nominated by the World Meteorological Organisation (WMO). The audit addressed a broad spectrum of criteria under Institutional, Operational, Technical and Communication/ Dissemination categories. PECASUS was declared fully compliant in all ICAO/WMO criteria with no areas for improvement identified.

Our presentation we will describe the coordinated actions of three ICAO Space Weather Centers, PECASUS network and its operations, and the vision of the PECASUS team to move forward. User interactions such as education and training, user feedback at ESWW, product and performance verification are part of PECASUS operations.

How to cite: Haukka, H., Harri, A.-M., Kauristie, K., Andries, J., Gibbs, M., Beck, P., Berdermann, J., Perrone, L., van den Oord, B., Berghmans, D., Bergeot, N., De Donder, E., Latocha, M., Dierckxsens, M., Haralambous, H., Stanislawska, I. M., Wilken, V., Romano, V., Kriegel, M., and Österberg, K.: PECASUS - ICAO Designated Space Weather Service Network for Aviation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7650, https://doi.org/10.5194/egusphere-egu2020-7650, 2020.

This study investigates the effect of selecting different simulation configurations of the Space Weather Modeling Framework (SWMF) on the predictions of ground magnetic perturbations. A historic geomagnetic storm, the St. Patrick Storm 2015, is simulated with several different model configurations. The objective is to investigate how the different configurations affect the prediction performance regarding ground magnetic perturbations. For each simulation, the modeled ground magnetic perturbations are compared to the measured perturbations from several ground magnetometer stations located at sub-auroral, auroral and polar cap latitudes. Among the magnetometer stations are the Norwegian and Greenland magnetometer chains. The comparison is based on metrics for both ΔB and dB/dt. The SWMF configurations investigated include variations in grid resolution and integration schemes for the MHD equations, and different settings for the inner magnetosphere, the ionosphere electrodynamics, and the magnetosphere-ionosphere coupling.

How to cite: Kwagala, N. K., Hesse, M., M. Jorgensen, T., Tenfjord, P., Norgren, C., Toth, G., Gombosi, T., M. Kolstø, H., and F. Spinnangr, S.: Effect of selecting different simulation configurations on the prediction performance of the Space Weather Modeling Framework regarding ground magnetic perturbations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7933, https://doi.org/10.5194/egusphere-egu2020-7933, 2020.

The Disturbance storm time (Dst) index is derived using the H-component perturbation on magnetometers from four observatories (Hermanus, Kakioka, Honolulu, and San Juan) near the Sq focus. The Dst index is a quantitative measure of geomagnetic activity (major disturbances are negative) that monitors the intensity of the magnetospheric ring current and it is derived and maintained by WDC Kyoto. The local nowcast index presented here is a geomagnetic index that is derived similarily to the Dst index for the each of the following low and mid-latitude observatories: Tristan da Cunha (South Atlantic, TDC), St. Helena (South Atlantic, SHE), Keetmanshoop (Namibia, KMH), Vassouras (Brazilian, VSS), Gan (Maldives, GAN) and Panagjurishte (Bulgaria, PAG). This local index is developed within the ESA’s SSA SWE G-ESC activity. Here, we assess the influence of the quiet-time Sq estimation on the local ring current index and the correlation of the index with other solar and geophysical parameters.

How to cite: Kervalishvili, G., Stolle, C., and Matzka, J.: Development of a local nowcast magnetospheric ring current index based on geomagnetic observatory data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11371, https://doi.org/10.5194/egusphere-egu2020-11371, 2020.

The Polar Cap (PC) indices are derived from the magnetic variations generated by the transpolar convection of magnetospheric plasma and embedded magnetic fields driven by the interaction with the solar wind. The PC indices are potentially very useful for Space Weather monitoring and forecasts and for related research. However, the PC index series in the near-real time and final versions endorsed by the International Association for Geomagnetism and Aeronomy (IAGA) have been proven unreliable (Stauning, 2013, 2015, 2018a,b,c, 2020). Both versions include solar wind sector (SWS) effects in the calculation of the reference levels from which magnetic disturbances are measured. The SWS effects are caused by current systems in the dayside Cusp region related to the Y-component, BY, of the Interplanetary Magnetic Field (IMF). However, the IAGA-endorsed handling of SWS effects may generate unfounded PC index changes of up to 3 mV/m at the nightside away from the Cusp. For the real-time PCN and PCS indices, their cubic spline-based reference level construction may cause additional unjustified index excursions of more than 3 mV/m with respect to the corresponding final index values. Noting that PC index values above 2 mV/m indicate geomagnetic storm conditions, such unjustified contributions are considered to invalidate the IAGA-endorsed PC index series. The presentation shall include a description of alternative derivation methods shown to provide more consistent index reference levels for both final and real-time PC indices, to reduce their unfounded excursions, and to significantly increase their reliability (Stauning, 2016, 2018b,c).

References. Stauning, P. (2020): The Polar Cap (PC) index: invalid index series and a different approach. Space Weather, 2020SW002442 (submitted).

Stauning, P. (2013). Comments on quiet daily variation derivation in “Identification of the IMF sector structure in near-real time by ground magnetic data” by Janzhura and Troshichev (2011). Annales Geophysicae, 31, 1221-1225. https://doi.org/10.5194/angeo-31-1221-2013 .

Stauning, P. (2015). A critical note on the IAGA-endorsed Polar Cap index procedure: effects of solar wind sector structure and reverse polar convection. Annales Geophysicae, 33, 1443-1455. https://doi.org/10.5194/angeo-33-1443-2015 .

Stauning, P. (2016). The Polar Cap (PC) Index.: Derivation Procedures and Quality Control. DMI Scientific Report SR-16-22. Available at: https://www.dmi.dk/fileadmin/user_upload/Rapporter/TR/2016/SR-16-22-PCindex.pdf .

Stauning, P. (2018a). A critical note on the IAGA-endorsed Polar Cap (PC) indices: excessive excursions in the real-time index values. Annales Geophysicae, 36, 621–631. https://doi.org/10.5194/angeo-36-621-2018 .

Stauning, P. (2018b): Multi-station basis for Polar Cap (PC) indices: ensuring credibility and operational reliability. Journal of Space Weather and Space Climate, 8, A07. https://doi.org/10.1051/swsc/2017036 .

Stauning, P. (2018c). Reliable Polar Cap (PC) indices for space weather monitoring and forecast

How to cite: Stauning, P.: Unreliable IAGA-endorsed Polar Cap (PC) index series and a different approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10195, https://doi.org/10.5194/egusphere-egu2020-10195, 2020.

Working under the Space Weather Technology, Research and Education Center (SWx-TREC https://www.colorado.edu/spaceweather/).  The Laboratory for Atmospheric and Space Physics (LASP) is developing a Space Weather (SWx) Data Portal to provide unified access to disparate datasets to help close the Research to Operations (R2O) and Operations to Research (O2R) gap. 

LASP is building the SWx Portal leveraging technologies developed in support of spacecraft operations (WEBTCAD), Irradiance Dataset viewing and downloading (LISIRD: http://lasp.colorado.edu/lisird/ ) and the MAVEN and MMS Science Data Portals.  The primary technologies include a data model and software library that enables data interoperability known as LaTiS (https://github.com/latis-data) and the LASP Extended Metadata Repository (LEMR) which is developed as ontologies that not only represent the datasets, but also the front-end elements which are used to display them.  Additionally, we have developed a JavaScript science data display technology that leverages off LaTiS server instances to allow for consistent and straightforward display of datasets.  These technologies together facilitate a common interface to myriad datasets and formats which will enable us to expand the offerings quickly and provide consistent visualization, access to metadata, and download capabilities across them.

This presentation will discuss advancements in the portal development in the last year to both in terms of available datasets and in terms of new functionality.  We will also provide a demonstration of the released system that will include datasets demonstrating a solar event, its progression toward Earth and its Earth affect perspective of Space Weather Data centering on the 2015 St. Patrick’s day storm.

How to cite: Baltzer, T., Lucas, G., Pankratz, C., Knuth, J., and Lindholm, D.: SWx TREC: Further Developments on an Integrative Space Weather (SWx) Data Portal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22188, https://doi.org/10.5194/egusphere-egu2020-22188, 2020.

The Space Weather Technology, Research and Education Center (SWx TREC) is a center of excellence in cross-disciplinary research, technology, innovation, and education, intended to facilitate evolving space weather research and forecasting needs.  SWx TREC facilitates research advances, innovative missions, and data and computing technologies that directly support the needs of the SWx community to advance understanding and support closure of the Research to Operations (R2O) and Operations to Research (O2R) loop. Improving our understanding and prediction of space weather requires coupled Research and Operations. SWx-TREC is working to provide new research models, applications and data for use in operational environments, improving the Research-to-Operations (R2O) pipeline.  Advancement in the fundamental scientific understanding of space weather processes is also vital, requiring that researchers have convenient and effective access to a wide variety of data sets and models from multiple sources. The space weather research community, as with many scientific communities, must access data from dispersed and often uncoordinated data repositories to acquire the data necessary for the analysis and modeling efforts that advance our understanding of solar influences and space physics in the Earth’s environment. The University of Colorado (CU) is a leading institution in both producing data products and advancing the state of scientific understanding of space weather processes, and we are now hosting both an interoperable data portal providing streamlined, centralized, and event-based access to a wide variety of disparate data sets and also a community-accessible, Cloud-based testbed environment to support development, testing, transition, and use of new models, visualizations, algorithms, and forecast products.  In this presentation, we will describe our community-accessible testbed environment and demonstrate the Space Weather Data Portal.

How to cite: Pankratz, C., Baltzer, T., Lucas, G., Craft, J., Berger, T., Baker, D., Knuth, J., and Jaynes, A.: The SWx TREC Integrative Space Weather Data Portal and Model/Algorithm Testbed Environment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22144, https://doi.org/10.5194/egusphere-egu2020-22144, 2020.

The use of satellite data allows us to study the variability of ionospheric plasma parameters globally without references to ground stations or receivers in different regions of the Earth. The Swarm mission, which was launched in 2014 and is still operational, allows us to investigate the effects of decreasing solar activity on the ionospheric variability. In our study we use the Swarm in-situ measurements of the electron density and derived parameters. This dataset provides characteristics of the plasma variability along the orbit and gives information on plasma density structures in the ionosphere in terms of their amplitudes, gradients and spatial scales. We analyze the variability of these parameters in the contexts of the northern and southern hemispheres, specific latitudinal regions, and the solar activity level. Understanding of the distribution of such parameters in the context of the solar activity level and selected ionospheric regions can have implications for the development of new satellite instruments and for the accuracy of GNSS precise positioning.

How to cite: Kotova, D., Jin, Y., and Miloch, W.: Variability of ionospheric parameters by the Swarm satellites for different solar activity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20318, https://doi.org/10.5194/egusphere-egu2020-20318, 2020.

We have developed and tested a scheme for forecasting severe space weather (SvSW) that caused all known electric power outages and telecommunication system failures since 1957 and the Carrington event of 1859. The SvSW events of 04 August 1972 has puzzled the scientific community as it occurred during a moderate storm (DstMin = -124 nT) while all other SvSW events occurred during super storms (DstMin ≤ -250 nT). The solar wind velocity V and IMF Bz measured by ACE satellite at the L1 point since 1998 are used. For the earlier SvSW events such as the Carrington event of 1859, Quebec event of 1989, and the events in February 1958 and August 1972 we used the information from the literature. The coincidence of high ICME front (or shock) velocity ΔV (sudden increase in V over the background by over 275 km/s) and sufficiently large Bz southward at the time of the ΔV increase is associated with SvSW; and their product (ΔV×Bz) is found to exhibit a large negative spike at the speed increase. Such a product (ΔV×Bz) exceeding a threshold seems suitable for forecasting SvSW, with a maximum forecasting time of 35 minutes using ACE data. However, the coincidence of high V (not containing ΔV) and large Bz southward does not correspond to SvSW, indicating the importance of the impulsive action of high ΔV and large Bz southward coming through when they coincide. The need for the coincidence is verified using the CRCM.

How to cite: Nanan, B.: A scheme for forecasting severe space weather, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1692, https://doi.org/10.5194/egusphere-egu2020-1692, 2020.

Intense solar radio bursts (SRBs) emitted at L-band frequencies are a source of radio frequency interference for Global Navigation Satellite Systems (GNSS) by inducing a noise increase in GNSS measurements, and hence degrading the carrier-to-noise density (C/N₀). Such space weather events are critical for GNSS-based applications requiring real-time high-precision positioning.

Since 2015, the Royal Observatory of Belgium (ROB) monitors in near real-time the C/N₀ observations from the European Permanent Network (EPN). The monitoring allows to detect accurately the general fades of C/N₀ due to SRBs over Europe as from 1 dB-Hz. It provides in near real-time a quantification of the GNSS signal reception fade for the L1 C/A and L2 P(Y) signals and notifies civilian single and double frequency users with a 4-level index corresponding to the potential impact on their applications. This service is part of the real-time monitoring service of the PECASUS project of the International Civil Aviation Organization (ICAO) which started end of 2019.

Results of this 5-year monitoring will be discussed, including the 3 SRBs of 2015 and 2017, together with the new developments toward a global index using the International GNSS Service (IGS) network. In addition, we will show how the SRB monitoring is sometimes interfered by GPS flex power campaigns on the satellites from blocks IIR-M and IIF, and how it is mitigated . The routine and transient GPS flex power campaigns will be presented in terms of C/N₀ variations for the EPN and IGS networks.

How to cite: Chevalier, J.-M., Bergeot, N., Defraigne, P., Marque, C., and Pinat, E.: Solar radio burst interference index dedicated to GNSS single and double frequency users, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15904, https://doi.org/10.5194/egusphere-egu2020-15904, 2020.

The near-Earth radiation environment is a force to contend with when designing satellites and their instruments. Solar storms can accelerate and transport energetic particles closer to Earth, populating Earth’s radiation belts and increasing a satellite’s radiation dosage. A major application to the field of space weather is therefore knowing and understanding the near-Earth radiation environment. We use Van Allen Probe data throughout mission lifetime to look at electron fluxes at different energies, pitch angles, and L shells, creating a daily average flux model that can be used to deduce what fluences were observed by any satellite that flew within Van Allen Probe’s seven-year mission. We supplement Van Allen Probe fluxes with THEMIS statistical fluxes at higher L shells. This model can be applied to better understand satellite degradation issues related to the radiation environment. It is an improvement from previous empirical models in this regard by virtue of the fact that actual fluxes from a specific storm (or storms) can be deduced and compared to real satellite degradation data.

How to cite: Gabrielse, C., Roeder, J., Lee, J., Claudepierre, S., Turner, D. L., O'Brien, T. P., Fennell, J., and Blake, J. B.: An Empirical Model of Electron Flux from the Seven-Year Van Allen Probe Mission, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12084, https://doi.org/10.5194/egusphere-egu2020-12084, 2020.

The Global Navigation Satellite System (GNSS) radio occultation and topside sounder provide materials for the validation of a mathematical description of the topside ionosphere up to satellite altitude. An attempt to represent the topside electron density profile is using α-Chapman function with a continuously varying scale height. In this study, the Vary-Chap scale height profiles are obtained based on Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) electron density profiles from 1 January 2008 to 31 December 2013 and fitted by a shape function composed of two weighted patterns representing the ion and electron contributions of lower and higher altitudes. The topside profiles of ISIS-1 data are used to define the transition height of different ions. The associated fitting parameters are analyzed to reveal their temporal and spatial features and variations along with enhancement of solar activity. Their prominent dependence on latitudes, longitudes, the local time, the season, and the solar cycle facilitates modeling of the Vary-Chap scale height in constructing empirical topside ionospheric models.

How to cite: Wu, M.: New topside ionosphere model based on Vary-Chap function using radio occultation and topside sounder data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12822, https://doi.org/10.5194/egusphere-egu2020-12822, 2020.

Mid latitudes around 40 degree are influenced by effects typically found at both high and low latitudes. Moreover, the focus of the Solar Quiet ionospheric current system, drifts around these mid-latitudes. Consequently they have been considered as a complicated place to infer the geospace state from the ground and also complicated for practical procedures to generate geomagnetic indices. 
The procedure designed at the University of Alcala specially focused on removing solar regular variations at mid-latitudes is delivering a geomagnetic Local Disturbance index (LDi) in realtime. The same procedure can be used to produce global geomagnetic indices when applied to several geomagnetic stations at these latitudes. 
We present in this work the high-resolution (one minute) realtime production of ring current and auroral indices (MID-R, MID-E, MID-U and MID-L) similar to the well known Dst and AE indices for mid-latitudes which will help in the understanding of the complex physical processes that emerge at these latitudes. At the same time they fill a gap in the current operational space weather products available for these latitudes.

How to cite: Guerrero, A., Saiz, E., and Cid, C.: Realtime geomagnetic indices for mid-latitudes. MID-R, MID-E, MID-U and MID-L, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18174, https://doi.org/10.5194/egusphere-egu2020-18174, 2020.

This study presents experiments of driving a physics-based thermosphere model (TIE-GCM) by assimilating radio occultation electron density (Ne) profiles from the COSMIC (Constellation Observing System for Meteorology, Ionosphere and Climate) mission using an ensemble Kalman filter. This study not only helps to gauge the accuracy of the assimilation, to explain the inherent model bias, and to understand the limitations of the framework, but it also demonstrates the capability of the assimilation technique to forecast the highly dynamical thermosphere in the presence of realistic data assimilation scenarios.

Experiments cover both solar minimum (March 2008) and solar maximum (June 2014) periods. The results show that data assimilation improves the model state. Here the improvement is shown with comparisons to Ne and neutral density data from Swarm-A, Swarm-C, CHAMP, and GRACE-A satellite missions. The root mean squared error (RMSE) of Ne is reduced in the Ne-guided lower thermosphere more than that of the higher altitudes (e.g. 1.7×10⁴ electrons/cm³ at 200 km vs 2.9×10⁴ electrons/cm³ at 400 km). The average RMSE in the forecasted Ne is approximately 1.3×10⁵ electrons/cm³ at altitudes between 200 and 400 km, and  drops to 0.7×10⁵ electrons/cm³ at 500 km. The study also reveals that only a limited number of bonafide Ne profiles are available for assimilation tasks in the experiments. These results also provide insights into the biases inherent in the physics-based model. The systematic biases that this study highlight could be an indication that the specification of plasma-neutral interactions in the model needs further adjustments.

How to cite: Kodikara, T.: Forecasting of the Upper Atmosphere via Assimilation of Electron Density Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13024, https://doi.org/10.5194/egusphere-egu2020-13024, 2020.

Space weather can be the source of severe disturbances in the ionosphere, which can influence the performance and reliability of GNSS (Global Navigation Satellite Systems) technology and applications. In order to forecast and minimize these effects, accurate corrections need to be provided. This goal can be achieved by employing a precise model to describe the complex chain of space weather processes and the non-linear spatial and temporal variability of the Vertical Total Electron Content (VTEC) within the ionosphere, as well as, to include a forecast component considering space weather events in order to provide an early warning system. This is a challenging but important task of high interest for the GNSS community.

Artificial intelligence applications, such as Machine Learning (ML), are able to find and learn patterns from historical data to solve problems, which are too complex and/or too vast for humans. To develop an effective and high performance ML algorithm special consideration needs to be given to the selection of the input data. Data need to be selected in order to have sufficient information to describe and predict ionosphere VTEC variability accurately. Therefore, the study of space weather impacts for the integration of space weather information in forecast ionosphere models is of crucial importance.

In this study, the relationship between various indices, describing space weather and space climate, and ionosphere VTEC variability in different latitudes during longer time periods within the solar cycle 24 is examined. Conditions in space weather are described by solar wind, the magnetic field and plasma data, energetic proton fluxes, geomagnetic and solar activity indices provided by worldwide distributed observatories. VTEC data are derived from GNSS measurement from permanent stations, belonging to the EPN (EUREF Permanent Network) and the IGS (International GNSS Service) networks and selected in latitudinal range from 0° to 60°N. The period from year 2014 to year 2017 is used to relate space weather indices to VTEC variability, as well as, to train the ML model. In addition, periods of intense geomagnetic storms caused by different sources (coronal mass ejections and high-speed streams of solar wind from coronal holes), occurred during different seasons in this period are analyzed. The evolution and severity of storms are investigated in relation to the conditions in the solar activity, solar wind speed, interplanetary magnetic field and geomagnetic field together with their impact on the ionosphere VTEC. Obtained results of this investigation will be presented, as well as the methodology, goals and challenges for ML model development including preliminary results of an initial ML model.

How to cite: Natras, R. and Schmidt, M.: Relationship Between Ionosphere VTEC and Space Weather Indices for Machine Learning-based Model Development, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18978, https://doi.org/10.5194/egusphere-egu2020-18978, 2020.

The MAG-GIC project has as a main goal to produce the chart of Geomagnetically Induced Currents (GIC) risk hazard in the distribution power network of Portugal mainland.

The study of GICs is important as they represent a threat for infrastructures such as power grids, pipelines, telecommunication cables, and railway systems. A deeper insight into GICs hazard may help in planning and designing more resilient transmission systems and help with criteria for equipment selection.

GICs are a result of variations in the ionospheric and magnetospheric electric currents, that cause changes in the Earth's magnetic field. The Coimbra magnetic observatory (COI) is one of the oldest observatories in operation in the world and the only one in Portugal mainland. It has been (almost) continuously monitoring the geomagnetic field variations since 1866, and in particular, it has registered the imprint of geomagnetic storms during solar cycle 24. Besides the geomagnetic storm signal, which represents the GICs driver, the crust and upper mantle electrical conductivities determine the amplitude and geometry of the induced electric fields.

To present a better approximation of the Earth's conductivity structure below the Portuguese power network, we initiated a campaign to acquire magnetotelluric (MT) data in a grid of 50x50 km all over the territory. Nonetheless, there already exist enough MT data to create a realistic 3D conductivity model in the south of Portugal.

The other important input is the electric circuit for the network grid. We benefit from the collaboration of the Portuguese high voltage power network (REN) company, in providing the grid parameters as resistances and transformer locations, thus allowing us to construct a more precise model. In particular, we implement in our model the effect of shield wires and shunt reactors resistances.

In this study, we present the results of GIC calculations for the south of Portugal for some of the strongest geomagnetic storms in the 20015-17 period recorded at COI during solar cycle 24. We will focus on the sensitivity of results concerning two different conductivity models and different values of the shielding circuit parameters and shunt reactors devices.

How to cite: Alves Ribeiro, J., Pais, M. A., J. G. Pinheiro, F., Monteiro Santos, F. A., and Soares, P.: MAG-GIC: Geomagnetically Induced Currents risk hazard in the Portuguese power network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1002, https://doi.org/10.5194/egusphere-egu2020-1002, 2020.

Data assimilation has been used in Numerical Weather Prediction models with great success, and it can be seen that the improvement of data assimilation methods has gone hand-in-hand with improvements in weather forecasting skill. The implementation of data assimilation for solar wind forecasting is still in its infancy and is still underused in the field. Hence, it is important to investigate the optimal implementation of these methods to improve our understanding of the solar wind.

To do this, we have generated a variational data assimilation scheme for use with a steady-state solar wind speed model based upon the Burger equation. This relatively simple scheme has the advantage of updating the inner-boundary conditions of the solar wind model allowing the updates to persist and improve the solar wind estimates throughout the whole domain.

To this effect, we present numerical experiments using our data assimilation scheme with STEREO and ACE data to improve estimates and forecasts of the solar wind in near-Earth space. Particular focus will be applied to assimilating data when the satellites are 60 degrees apart, such that they simulate Earth-L5 forecasting scenarios.

How to cite: Lang, M., Owens, M., and Lawless, A.: Improving solar wind forecasts using data assimilation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10909, https://doi.org/10.5194/egusphere-egu2020-10909, 2020.