Session 16 - Novel approaches for space weather forecasting
Juan Sebastian Cervantes Villa (GFZ); Ludger Scherliess (Utah State Univ.)
Friday 22/11, 11:15-12:30 & 14:00-15:15
Forecasting techniques that range from first principles modeling, to machine learning, to merging data with models have long been used in many areas of science and engineering. More recently they have successfully been applied for specifications and forecasts of the space environment spanning from the Sun to the Earth, largely due to the rapid increase in the number of ground- and space-based observations. In order to use these methods for space weather applications, a rigorous examination of the available data, the applied techniques, and the statistical properties of the system is necessary.
Contributions dealing with data sources, data quality issues, and forecasting techniques and models are welcome. Special emphasis will be given to contributions that describe novel approaches that can be used for space weather applications.
Friday November 22, 11:15 - 12:30, Rogier
Friday November 22, 14:00 - 15:15, RogierClick here to toggle abstract display in the schedule
Talks : Time scheduleFriday November 22, 11:15 - 12:30, Rogier
Friday November 22, 14:00 - 15:15, Rogier
|11:15||Enhancing space weather predictions using coronal dimmings ||Veronig, A et al.||Oral|
| ||Astrid M. Veronig, Karin Dissauer, Tatiana Podladchikova, Manuela Temmer|
| || Institute of Physics & Kanzelhöhe Observatory, University of Graz, Austria,  Skolkovo Institute of Science and Technology, Moscow, Russia|
| ||Coronal mass ejections (CMEs) are the major sources for strong geomagnetic storms and space weather consequences at Earth and other planets. The determination of decisive CME parameters, like direction, speed, width and mass are thus of high importance for accurate predictions of CME arrival and speed. Ironically, these parameters are most uncertain in case of Earth-directed events, observed as halo CMEs by coronagraphs on spacecraft in the Sun-Earth line. We will present new physical insight and new approaches to use coronal dimmings to provide better estimates of CME speed and mass for Earth-directed events as well as to advance the lead time of these determinations.
Coronal dimmings are localized regions that undergo an abrupt reduction in the solar Extreme-Ultraviolet (EUV) and/or soft X-ray emission, co-temporal with the launch of a CME. The reduced emission in coronal dimmings is a result of a density depletion caused by the expansion and evacuation of coronal plasma due to the erupting CME, with density reductions up to 70% within some 10 minutes from the CME launch and associated mass flows (Vanninathan et al. 2018, Veronig et al. 2019). In addition, for a set of 62 Earth-directed CMEs well covered by multi-point observations, we present statistical relations between parameters of the coronal dimmings observed against the solar disk by SDO/AIA and the kinematics and mass of the associated CME, which is simultaneously observed close to the limb by at least one STEREO spacecraft. The most distinct relations are obtained between the CME mass and the dimming area, magnetic flux and intensity, as well as between the CME speed and dynamic dimming quantities, like area change rate and flux change rate, with the CME velocity (Dissauer et al. 2018, 2019). Multiple linear regression analysis is applied to find optimized parameter combinations that can be used to provide estimates of the speed and mass of Earth-directed CMEs from the dimming observations, resulting in correlations up to 0.7 along the 1:1 correspondence line. The relevance of these results and their potential toward real-time implementations to enhance space weather predictions is discussed.|
|11:30||On the Drag parameter of CME propagation models||Del moro, D et al.||Oral|
| ||Dario Del Moro, Francesco Berrilli, Raffaello Foldes, Alice Cristaldi, Roberta Forte, Luca Giovannelli, Gianluca Napoletano, Ermanno Pietropalo|
| || University of Rome "Tor Vergata",  University of L'Aquila|
| ||ICME (Interplanetary Coronal Mass Ejection) are violent phenomena of solar activity that affect the whole heliosphere and the prediction of their impact on different solar system bodies is one of the primary goals of the planetary space weather forecasting. The travel time of ICME from the Sun to the Earth can be computed through Drag Based Model (DBM) approach, which is based on a simple equation of motion for the ICME that defines the acceleration as a=-Γ(v-w)|v-w|, where a and v are the CME acceleration and speed, w is the ambient solar-wind speed and Γ is the so-called drag parameter (Vršnak et al., 2013). In this framework, Γ depends on the ICME mass and cross-section, on the solar-wind density and, to a lesser degree, on other parameters. The typical working hypothesis for DBM implies that both Γ and w are constant far from the Sun. To run the codes, forecasters use empirical input values for Γ and w, derived by pre-existent knowledge of solar-wind condition and by solving the “inverted problem” (where the ICME travel time is known and the unknowns are Γ and/or w). In the 'Ensemble' approaches (Dumbovich et al., 2018; Napoletano et al. 2018), the uncertainty about the actual values of such inputs are rendered by Probability Distribution Functions (PDFs), accounting for the values variability and our lack of knowledge. Among those PDFs, that of Γ is poorly defined due to the relatively scarce statistics of recorded values.
We are running a set of simulations of an ICME structure into the solar-wind fluid, relaxing the hypotheses of isotropic solar-wind expansion, radial propagation and self-similar ICME expansion, to reproduce the ICME kinematics in a controlled environment and interpret the results in the framework of the DBM simple interaction. This allows us to define an effective Γ parameter for each different ICME simulation, and explore how it depends on the physical parameters of the simulation, verifying and extending the work in Vršnak et al. (2010). This leads to a more robust definition of the PDF of the drag parameter Γ (up to defining different PDFs depending on measured parameters) that could be used in the various DBM approaches to real-time ICME travel time forecasting.|
|11:45||Solar flare forecasting algorithms: R and D values for SDO/HMI and MOTH LoS magnetograms||Berrilli, F et al.||Oral|
| ||Francesco Berrilli, Domenico Cicogna, Stuart Jefferies[2,3], Neil Murphy, Dario Del Moro, Luca Giovannelli, Daniele Calchetti|
| ||(1) University of Rome Tor Vergata, I-00133, Roma, Italy; (2) Georgia State University, GA 30303, USA; (3) University of Hawaii, HI 96768, USA (4) Jet Propulsion Laboratory, CA 91109, USA|
| ||An important and pursued focus in Solar Physics and Space Weather fields is to predict the probability of flaring in solar active regions. In this work we present the calibration of the R value (Schrijver, 2007) for magnetograms acquired by the Helioseismic and Magnetic Imager (HMI) instrument on board the Solar Dynamics Observatory (SDO) satellite. We adjust the parameters of the R value in the Schrijver algorithm to adapt them to the higher spatial resolution of HMI and we calculate the "adjused" R values for the whole sample of solar flaring regions observed by HMI/SDO during solar cycle 24. Finally, we compare the results of our statistical analysis with the results of the statistical analysis performed by Schrijver (2007) on cycle 23 MDI/SOHO magnetograms.
Moreover, we introduce a new forecasting algorithm based on the calculation of a novel topological descriptor of magnetic region, i.e., the D value. This value is aimed to automatically identify and count the number of magnetic polarity inversion lines (PILs), in a LoS magnetogram, within the same solar active region.
The statistical analysis, based on flaring regions of cycle 24 observed with HMI/SDO, shows that both R and D values are good descriptors of the behavior of a solar AR and, when coupled, useful tools for flare forecasting. The time evolution of D value is also applied to MOTH (Full Disk multi-lines observations) magnetograms acquired during the Antarctic observations of 2017.|
|12:00||Early detection of solar flares using GOES/SUVI data ||Krista, L et al.||Oral|
| ||Larisza D. Krista[1,2], Daniel Seaton[1,2], Paul Lotoaniu[1,2]|
| || University of Colorado,  NOAA/NCEI|
| ||The timely detection of solar flares is of primary importance to space weather forecasting efforts that are critical to infrastructure services, remote sensing, space exploration and navigation. Currently, solar flare forecasting methods primarily rely on X-ray irradiance data without any visual imagery. Our goal is to take advantage of the new, high-sensitivity, real-time, low-latency data available from the GOES/Solar Ultraviolet Imager (SUVI) instrument in order to identify not only the time of the flare occurrence, but its location as well - a property that can influence the magnitude of the corresponding space weather effects. Furthermore, the new tool is capable of giving over ten minutes of advance warning before detrimental space weather effects occur. The high-sensitivity extreme ultraviolet data available to us is uniquely suitable to identify early signs of a flare development using our novel, robust and fast flare detection tool. By analyzing the flare development process the algorithm could also gain insight into how early ultraviolet signatures are related to flare magnitudes. It also provides a brand new insight into the deeper physics of flares and the ways in which energy is released and plasma is heated during the evolution of energetic solar eruptions. Studying the temporal development of flares in different wavelengths allows us to better understand how the initiation happens and what different physical environments and processes lead to instabilities in flaring regions and how it relates to the magnitude of severe space weather disturbances. |
|12:15||The Probabilistic Solar Particle Event foRecasting (PROSPER) Model||Papaioannou, A et al.||Oral|
| ||Athanasios Papaioannou, Rami Vainio, Osku Raukunen, Anastasios Anastasiadis, Angels Aran, Miikka Paassilta, Sotirios A.Mallios, Piers Jiggens|
| || Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing (IAASARS), National Observatory of Athens, I. Metaxa & Vas. Pavlou St., GR-15236, Penteli, Greece,  Department of Physics and Astronomy, University of Turku, 20014 Turku, Finland,  Dep. Física Quàntica i Astrofísica, Institut de Ciències del Cosmos (ICCUB), Universitat de Barcelona, Barcelona, Spain,  ESA Space Environments & Effects section (TEC-EES), ESA-ESTEC, Keplerlaan 1, 2201 AZ Noordwijk, Netherlands|
| ||A solar eruptive event (e.g. solar flare, coronal mass ejection - CME) that has been marked on the Sun may give rise to an upcoming Solar Energetic Particle (SEP) event. Therefore, it is critical to know which of the specific solar parameters (e.g. solar flare magnitude and location; CME width and velocity) point to a higher probability of SEP occurrence. Additionally, from a subset of solar flares and CMEs that do produce SEP events, one should further infer the SEP characteristics (e.g. peak flux). In this work, we present a novel data driven approach that resulted in the Probabilistic Solar Particle Event foRecasting (PROSPER) model. We utilize: (i) CME characteristics (e.g. width, speed); (ii) solar flare characteristics (e.g. longitude, magnitude) and - for the first time - (iii) combinations of solar flare and CME characteristics. For each case and for a set of integral proton energies (i.e. E>10-; >30; >100; >300 MeV) we derive the probability of SEP occurrence (with corresponding confidence intervals), as well as, the expected peak proton flux (with lower and upper limits). The outputs of the PROSPER model have been incorporated in the new operational Advanced Solar Particle Event Casting System (ASPECS) tool [http://tromos.space.noa.gr/aspecs/].
Acknowledgement. This research received funding through the ESA activity “Solar Energetic Particle (SEP) Advanced Warning System (SAWS)”. ESA Contract No. 4000120480/NL/LF/hh.
|14:00||The HESPERIA real-time Solar Energetic Particle prediction tools ||Malandraki, O et al.||Oral|
| ||Olga Malandraki, Bernd Heber, Patrick Kuehl, Marlon Núñez, Arik Posner, Michalis Karavolos, Nikos Milas|
| || National Observatory of Athens, IAASARS, Athens, Greece,  Christian-Albrechts-University of Kiel, Kiel, Germany,  Universidad de Málaga, Málaga, Spain,  Heliophysics, NASA Headquarters, Washington, DC, USA|
| ||Solar Energetic Particles (SEPs), ranging in energy from tens of keV to a few GeV, constitute an important con-tributor to the characterization of the space environment. SEP radiation storms may have durations from a period of hours to days or even weeks and have a large range of energy spectrum profiles. They pose a threat to mod-ern technology strongly relying on spacecraft and are a serious radiation hazard to humans in space, and are additionally of concern for avionics and commercial aviation in extreme cases. The High Energy Solar Particle Events forecasting and Analysis (HESPERIA) project, supported by the HORIZON 2020 programme of the Eu-ropean Union, has furthered our prediction capability of high-energy SEP events by developing new European capabilities for SEP forecasting and warning, while exploiting novel as well as already existing datasets. The HESPERIA UMASEP-500 tool makes real-time predictions of the occurrence of >500 MeV and Ground Level Enhancement (GLE) events from the analysis of soft X-ray flux and high-energy differential proton flux measured by the GOES satellite network. Regarding the prediction of GLE events for the period 2000-2016, this tool had a Probability of Detection (POD) of 53.8% and a False Alarm Ratio (FAR) of 30.0%. For this period, the tool obtained an Advanced Warning Time (AWT) of 8 min taking as reference the alert time from the first NMstation; using the time of the warning issued by the GLE Alert Plus tool for the aforementioned period as reference, the tool obtained an AWT of 15 min (Núñez et al. 2017). Based on the Relativistic Electron Alert System for Exploration (REleASE) forecasting scheme (Posner, 2007), the HESPERIA REleASE tools generate real-time predictions of the proton flux (30-50 MeV) at the Lagrangian point L1, making use of relativistic electrons (v>0.9c) and near-relativistic (v<0.8c) electron measurements provided by the SOHO/EPHIN and ACE/EPAM experiments, respectively. Analysis of historic data from 2009 to 2016 has shown the HESPERIA REleASE tools have a low FAR (∼30%) and a high POD (63%). Both HESPERIA tools are operational through the project’s website (http://www.hesperia.astro.noa.gr) at the National Observatory of Athens and presented in the recently published book on 'Solar Particle Radiation Storms Forecasting and Analysis, The HESPERIA HORIZON 2020 Project and Beyond', edited by Malandraki and Crosby, Springer, Astrophysics and Space Sciences Library, 2018, freely available at https://www.springer.com/de/book/9783319600505. The HESPERIA tools have been selected as a top priority internationally by NASA/CCMC to be included in the simulations of the manned-mission to Mars by Johnson Space Center (ISEP project). The National Observatory of Athens participates in the ISEP project with a relevant contract.|
|14:15||Stochastic parameterizations in Space Weather models: Application to Earth’s Radiation Belts||Watt, C et al.||Oral|
| ||Clare Watt, Rhys Thompson, Sarah Bentley, Paul Williams, I. Jonathan Rae, Hayley Allison, Kyle R. Murphy, Nigel Meredith, Sarah Glauert, Richard Horne, Chandra Anekallu, Colin Forsyth|
| ||(1) Department of Meteorology, University of Reading, (2) Department of Mathematics, University of Reading, (3) Mullard Space Science Laboratory, University College London, (4) GFZ German Research Centre for Geosciences, (5) University of Maryland, (6) British Antarctic Survey|
| ||In many space weather applications, the use of physics-based models is desirable. These types of models not only provide scientific insight into the processes governing space weather phenomena but can sometimes be more confidently used to model extreme events that have no precedent in the data record. It is often the case, however, that there are physical processes occurring in our models that are “sub-grid”, i.e. that occur on length and time scales that are not resolved by the physics-based model. Typically, these processes are parameterized so that they may be included.
There will always be uncertainty in our parameterizations. This uncertainty may stem from lack of knowledge of the sub-grid process, from the use of observations to constrain the parameterization, or indeed from natural variability of the process that cannot be captured in a deterministic model. In this presentation, we borrow ideas of “stochastic parameterization” often used in numerical terrestrial weather prediction, climate and hydrology modelling to describe how uncertainty and natural variability of sub-grid processes can be rigorously included in physics-based models.
We choose for an application the wave-particle interactions that drive acceleration, transport and loss in Earth’s Radiation Belts. These wave-particle interactions occur on time and length scales that are orders of magnitude less than the typical grid size and time step size of a diffusion-based radiation belt model such as the British Antarctic Survey Radiation Belt Model (BAS-RBM: https://www.bas.ac.uk/science/research-models/bas-radiation-belt-model-bas-rbm/). We highlight the additional set of unknowns that must be characterized in a stochastic parameterization: the size of the variability of the process, the nature of the distribution of the sub-grid process (i.e. it can be non-Gaussian), and the appropriate time and length scales of that variability. We use observations to indicate the variability of wave-particle interactions in Earth’s Radiation Belts, and show how parameterizations can be improved to reduce variance. We demonstrate simple numerical experiments that show how length and timescales, as well as the size and nature of the variability, affect the results of a model. Where appropriate, we will highlight reviews and literature in other fields that may help attendees apply these ideas in their own modelling research.
|14:30||Forecasting GOES >2 MeV fluxes using geomagnetic indices and solar wind data||Forsyth, C et al.||Oral|
| ||Colin Forsyth, Clare Watt, Michaela Mooney [1,3], Jonathan Rae, Samuel Walton , Richard Horne|
| ||UCL Mullard Space Science Lab., Dorking, United Kingdom, University of Reading, Reading, United Kingdom,  Met Office, Exeter, United Kingdom, British Antarctic Survey, Cambridge, United Kingdom|
| ||The GOES spacecraft continuously monitor the conditions in the outer radiation belt. Data from the GOES spacecraft are regularly used by space weather forecasters at SWPC and MOSWOC to alert spacecraft operators when there is an increased risk to spacecraft due to enhanced radiation belt fluxes. Empirical and physics-based models of the fluxes in the radiation belt can provide relatively short-term (1-3 day) predictions of the fluxes in the radiation belts but are often limited by the input data required. Short-term (<1 day) variations in the radiation belt fluxes may be driven by solar wind variability whereas geomagnetic activity may drive increases in the fluxes over longer periods. In this study, we propose that a simple forecast of the likelihood of the GOES >2 MeV fluxes exceeding either their median or 95th percentile levels can made by examining the amount of time various input parameters (AL, SYM-H and solar wind measurements) exceed a set threshold within a prior window of time and examine how skilful such forecasts are against persistence and climatology models. We provide forecasts between 1 and 10 days. Of the tested input parameters, we find that AL provides the best deterministic forecasts, with ROC scores up to 0.90, and the best probabilistic forecasts, with Brier Scores as low as 0.11, although persistence forecasts of electron flux exceeding the median level are better. The ROC scores remain high and Brier Scores remain low even up to forecasts covering 10 days. This demonstrates that relatively simple forecasts based on geomagnetic activity can provide useful indications of high electron fluxes in the radiation belts in the event that in-situ monitoring is not available.|
|14:45||The system identification development of local time dependent electron flux models for geostationary orbit||Boynton, R et al.||Oral|
| ||Richard Boynton, Michael Balikhin |
| ||University of Sheffield|
| ||A set of Nonlinear AutoRegressive Moving Average eXogenous (NARMAX) models were developed to model the electron fluxes at geosynchronous orbit (GEO). The electron fluxes vary not only in time but also spatially throughout GEO. To model the spatiotemporal fluxes data from the GOES 13, 14 and 15 spacecraft are binned by MLT and a separate model for each MLT is deduced via NARMAX machine learning methodology. This was done for 7 energy ranges measured by the GOES 13, 14 and 15 spacecraft.|
|15:00||Forecasting ionospheric Total Electron Content at global level one day in advance ||Cesaroni, C et al.||Oral|
| ||Claudio Cesaroni, Luca Spogli L.[1,2], Angela Aragon-Angel, Michele Fiocca, Varuliator Dear, Giorgiana De Franceschi, Vincenzo Romano[1,2] |
| ||Istituto Nazionale di Geofisica e Vulcanologia, Italy SpacEarth Technology, Italy European Commission, Joint Research Centre (JRC), Italy Independent Researcher, Italy National Institute of Aeronautics and Space, Indonesia |
| ||We introduce a novel empirical approach to forecast, 24 hours in advance, the Total Electron Content (TEC) at a planetary scale. The technique leverages on the Global Ionospheric Map (GIM), provided by the International GNSS Service (IGS), and applies a nonlinear autoregressive neural network with external input (NARX) to given selected GIM grid points for the 24 hours single-point TEC forecasting, taking into account the actual and forecasted geomagnetic conditions. To extend the forecasting at a planetary scale, the technique makes use of both the NeQuick2 Model and an effective sunspot number R12 (R12eff), estimated by minimizing the root mean square error (RMSE) between NARX output and NeQuick2 applied at the same grid points of the GIM map. The novel approach is able to reproduce the features of the planetary ionosphere revealing its peculiarity at low-equatorial latitudes due to the Equatorial Ionosphere Anomaly (EIA). The performance of the forecasting approach is extensively tested under different geospatial conditions, against both post processing TEC maps products by UPC (Universitat Politècnica de Catalunya) and independent TEC data from the dual frequency altimeter on board of Jason-3 spacecraft. The testing results are very satisfactory in terms of root mean square errors that ranges between 3 and 5 TECu. RMSE depend on the latitude sectors, time of the day, geomagnetic conditions, and provide a statistical estimation of the accuracy of the 24-hours forecasting technique even oven the oceans as well at low latitudes and under stormy events. This 24-hours empirical approach is currently implemented on the Ionosphere Prediction Service (IPS), a prototype platform to monitor and forecast the ionospheric effects on the performance of GNSS systems at service level for several classes of users. Moreover, this is one of the high priority poduct in the PECASUS consortium portfolio for ICAO space weather service. |
|1||Complex flare forecast program using data of sunspots and line-of-sight magnetic fields||Ludmány, A et al.||p-Poster|
| ||András Ludmány , Tünde Baranyi , Judit Muraközy |
| ||Research Center for Astronomy and Earth Sciences, Hungarian Academy of Sciences|
| ||A three step system of flare forecast procedures is developed in a recent project. The inputs of the methods are sunspot data taken from the Debrecen sunspot databases, the most detailed existing datasets of sunspots and the flare datasets of GOES satellites. The three steps are consecutive techniques of different quicknesses and difficulties, all of them focus on the role of horizontal magnetic gradients. The first method assesses the flare productivity from the presence of a delta configuration, the sunspot umbrae of opposite polarities within a common penumbra. The second method applies quantities describing the entire solar active region, these are numerical versions of the earlier simple classification schemes. The third step is the most difficult but most informative approach, it tracks the dynamics of the internal magnetic gradient nodes, the possible sources of flares. Comparative evaluation of the techniques is presented. The project is supported by ESA.
|2||A Study about the Correlation Between Interplanetary Shock and Geomagnetic Disturbance||Zhitao, L et al.||p-Poster|
| ||Zhitao Li, Yanhong Chen, Qiuzhen Zhong|
| || National Space Science Center, Chinese Academy of Sciences|
| || Interplanetary shock is an important transient nonlinear structure in solar wind, which is a kind of strong discontinuous surface with mass flow entropy. Interplanetary shock has a strong space weather effect, most interplanetary shock is a precursor to rapid ICME, and rapid ICME is one of the main factors of catastrophic space weather events. It is of great significance for space weather science to study the propagation and evolution of interplanetary shock.
Geomagnetic storm is a kind of bad space weather phenomenon, which has a great influence on the global geomagnetic morphology and can cause strong changes in the magnetosphere, ionosphere and middle and upper atmosphere environment. The geomagnetic storm is caused by the southward component of the interplanetary magnetic field being re-linked with the sunny side magnetic field, thus allowing the energy and particles in the solar wind to be injected into the inner layer of the magnetosphere. During the maximum year of solar activity, large magnetic storm events occur frequently, and ICMEs and its driven shock become the main interplanetary origins that cause geomagnetic storms.
In this study, we obtained the characteristics of interplanetary shock in advance from the solar wind data observed by L1 point satellite, and carried out the precursor prediction study of geomagnetic storm event. Based on the data of interplanetary magnetic field and solar wind observation in ACE satellite, the characteristic parameters of typical shock of the solar cycle 23-24 are extracted from the point of view of statistical analysis, including: downstream magnetic field, upstream and downstream ratio of magnetic field, downstream southward magnetic field, upstream and downstream ratio of southward magnetic field, downstream velocity, solar wind speed jump, Density ratio, temperature ratio, etc., to establish an autonomous shock samples. The geomagnetic disturbance status of different intensity and duration caused by shock events at different levels is analyzed quantitatively, and the response time, maximum strength and continuous disturbance time of different shock characteristic parameters are discussed.
The results show that there is no complete positive correlation between the size of different parameters of shock, the response time and maximum value of geomagnetic storm. It is also necessary to further add the cumulative size of the parameters to the analysis and to explore the cumulative size value of the geomagnetic storm caused.|
|3||MUF(3000) prediction as operation space weather product ||Perrone, L et al.||p-Poster|
| ||L. Perrone , A.V. Mikhailov[2,1] and P. Bagiacchi|
| ||(1)Istituto Nazionale di Geofisica e Vulcanologia (INGV), (2)Pushkov Institute of Terrestrial Magnetism, Ionosphere and Radio Wave Propagation (IZMIRAN) |
| ||Pan-European Consortium for Aviation Space weather User Services (PECASUS) is one of the three global Space Weather Centers for aviation space weather user services designed by the International Civil Aviation Organization(ICAO).
The MUF(3000) predicted 1- 24 hours ahead is one of the operational space weather product inserted in PECASUS.
MUF(3000) depends on two ionospheric parameters foF2 and M(3000):
foF2 is predicted by EUROMAP model and M(3000) is taken from the IRI.
The method has been applied to Europe where there are ionospheric stations with long (for some solar cycles) historical data and current real-time foF2 observations. A mapping procedure applied to the European stations provides MUF(3000) short-term prediction over the whole area.
The following five storm periods have been analysed :four storms occurred during solar cycle 24
(09/2017-03/2015-05/2015-03/2012) and one occurred during solar cycle 23.
A comparison between MUF(3000) predicted and MUF(3000) derived from ionosonde stations is presented.
|4||Space Weather Service Network Preliminary Product Validation for the Period of Heightened Activity Observed in September 2017||Burley, S et al.||p-Poster|
| ||Sophie Burley, Alexi Glover, Juha-Pekka Luntama, Jesse Andries,Claudia Borries, Manolis Georgoulis, Guram Kervalishvili, Ioanna Tsagouri, Peter Wintoft, Federico Da Dalt, Gabor Facsko, Ralf Keil|
| ||ESA, ROB, DLR, RCAAM, GFZ, NOA/IAASARS, IRF, RHEA System GmbH for ESA|
| ||The European Space Agency’s Space Situational Awareness (SSA) Space Weather (SWE) Portal provides users with access to space weather services built upon a large variety of products, tools and alerts, together with expert user support and guidance. Understanding the performance of the different service elements under a range of space weather conditions is essential to providing reliable information to end users. In the frame of SSA Period 3 activities, an initial set of ‘Guidelines for common validation in the SSA SWE Network’ have been developed by a working group consisting of representatives of the SWE Expert Service Centres aiming to provide an agreed-on baseline for future validation campaigns. This poster presents preliminary results from application of recommended techniques and metrics on a sample of products available via the SWE Portal for the period of heightened space weather activity observed in September 2017. The cross-domain project demonstrates the applicability of the suggested validation techniques, whilst also identifying any ambiguities in the terminology used within the guidelines themselves. As a result of these tests, information on the performance of the selected products during this heightened period of space weather activity is also provided.|
|5||Pulsars track space weather||Tiburzi, C et al.||p-Poster|
| ||Caterina Tiburzi|
| ||The dispersive delay of the Solar wind introduces excess noise in high-precision pulsar-timing, which must be removed in order to achieve the accuracy needed to detect, e.g., low-frequency gravitational waves with pulsar timing array experiments. New, highly-sensitive test-bed for Solar wind effect in pulsar timing can be provided by low-frequency observations. In addition to this, the magnetic field of the Solar wind also modifies the polarization properties of pulsars through Faraday rotation.
However, this allows us to exploit pulsars to probe the Solar wind in both its electron and magnetic content. |
|6||EUHFORIA in the ESA Virtual Space Weather Modelling Centre ||Poedts, S et al.||p-Poster|
| ||Stefaan Poedts|
| ||CmPA/Dept. of Mathematics, KU Leuven , Belgium|
| ||The goal of the ESA ITT project AO-1-8384-15-1-NB VSWMC-Part 2 is to further develop the Virtual Space Weather Modelling Centre (VSWMC), building on the Phase 1 prototype system and focusing on the interaction with the ESA SSA SWE system. The objective and scopes of this project include:
1. The efficient integration of new models and new model couplings, including a first demonstration of an end-to-end simulation capability.
2. The further development and wider use of the coupling toolkit and the front-end GUI which will be designed to be accessible via the SWE Portal.
3. Availability of more accessible input and output data on the system and development of integrated visualization tool modules.
The consortium that took up this challenge involves: 1) the Katholieke Universiteit Leuven (Prime Contractor, coordinator: Prof. S. Poedts); 2) the Belgian Institute for Space Aeronomy (BIRA-IASB); 3) the Royal Observatory of Belgium (ROB); 4) the Von Karman Institute (VKI); 5) DH Consultancy (DHC); 6) Space Applications Services (SAS); 7) British Antarctic Survey (BAS).
The VSWMC-Part 2 project started on 17 February 2016. At the time of the ESWW15 meeting, Phase 2 will be finished, which means that all models (EUHFORIA, CTIM, CTAN2, BAS-RBM, COOLFluiD, GUMICS, etc.) and model couplings will be installed and operational in the VSWMC. Hence, it will be demonstrated how easy the models can be run and how easy model couplings can be set up and used. For instance, EUHFORIA can be run and coupled to Gumics-4 and Geo-effects models (Kp-index, bow shock stand-off distance,…). Moreover, visualization tools are installed as models and can thus be coupled to the models to get directly plots and/or video’s as output of a run. Several of such coupling have been established and the system is continuously being test and upgraded.
The VSWMC system is being developed under ESA's Space Situational Awareness (SSA) Programme. A first, limited version went operational on 28 May 2019 under the H-ESC umbrella on the ESA SSA SWE Portal. It is also being tested by the Heliospheric ESC.
|7||Optimising space weather forecasting capabilities of EUHFORIA: assessment of the WSA model||Asvestari, E et al.||p-Poster|
| ||Eleanna Asvestari,, Stephan Heinemann, Manuela Temmer, Jens Pomoell, Emilia Kilpua, Jasmina Magdalenic, Stefaan Poedts|
| ||University of Graz, Austria, [University of Helsinki, Finland, Royal Observatory of Belgium University KU Leuven, Belgium|
| ||For reconstructing the magnetic field and plasma conditions in the solar corona, the semi-empirical Wang-Sheeley-Arge (WSA) model is the most commonly used and has been adopted for the forecasting tool EUHFORIA (EUropean Heliospheric FORecasting Information Asset). In our study we aim to improve the space weather forecasting capabilities of EUHFORIA, focusing in optimising the parameters involved in the WSA model. We concentrate on two of these parameters that play a crucial role in modelling high speed streams and open magnetic flux. These are the source surface height (Rss) and the height of the inner boundary of the Schatten Current Sheet model (Ri), a key compound of the WSA for reconstructing plasma and magnetic field configuration in the outer corona. To optimise these paired heights we compare modelled coronal hole areas to boundaries obtained by remote sensing EUV observations using CATCH (Collection of Analysis Tools for Coronal Holes). We vary Rss within the interval [1.4, 3.2]Rsun, and Ri within the interval [1.3, 2.8]Rsun, both with step of 0.1Rsun. We conclude that values lower than the canonical pair, [2.3,2.6]Rsun, show an improved agreement with remote sensing observations which can lead to better forecasting of high speed solar wind streams.|
|8||A new approach for short-term and super-short-term space weather forecast||Velinov, P et al.||p-Poster|
| ||Yordan Tassev, Peter I. Y. Velinov, Alexander Mishev, Dimitrinka Tomova|
| || Institute for Space Research and Technology, Bulgarian Academy of Sciences, Sofia;  Space Climate Research Unit, University of Oulu, Finland;  Sofia University, Faculty of Mathematics and Informatics, Sofia, Bulgaria |
A new approach for space weather short-term forecasting (not greater than 48 hours in advance) and super-short-term forecasting (from several hours to 24 hours) is presented. The introduction of this terminology uses the analogy between meteorology and space weather.
As an example is considered the helio-active period from 6 to 17 May 2019 and occurred during this period events on the Sun and space weather, including the biggest storm in 2019, namely the G3 Strong geomagnetic storm on May 14, 2019. The appearance of active regions on the Sun, and their development in a period of deep solar minimum, followed by series of Coronal Mass Ejections (CMEs) has been analyzed.
The occurred two geomagnetic storms are explained: on May 11 and 14, 2019, as well as those predicted by SWPC NOAA, but unrealized geomagnetic storms on May 16 and 17, 2019. Two new heuristic methods for explaining and predicting geomagnetic activity are proposed.
We use the solar wind parameters (velocity V, density or concentration N, temperature Tp and intensity of the magnetic field B from measurements by ACE and DSCOVR spacecrafts in the Lagrange equilibrium point L1 between Sun and Earth. We make calculations for the kinetic (dynamic) energy density Ek, thermal energy density Et and magnetic energy density Em during the investigated period May 06-17, 2019.
We found two interesting phenomena in the investigated period: 1) tunnel effect in the Earth environment, and 2) speciﬁc distribution of the solar wind energy density during and after the CME. It is likely that both kinetic and magnetic energies can be used as predictors of geomagnetic storms.
In this work, we present two heuristic approaches to forecasting the state of space weather. We show their use in operational order in a specific situations by confirming the solar activity geoeffectiveness. Here the most important contributions are:
a) The conditions for the occurrence of a prediction effect were determined using the three energy densities (kinetic Ek, thermal Et and magnetic Em) to forecast weak G1, mean G2 and strong G3 geomagnetic storms.
b) A new interpretation of the tunnel effect has been made. A new mechanism is proposed - a hypothesis for the formation of this effect.
These contributions to our novel approaches can be used for different space weather applications.
|9||SWx TREC: An Emerging Community Resource for Integrative Space Weather Data Access and Model/Algorithm R2O Promotion||Pankratz, C et al.||p-Poster|
| ||Christopher K. Pankratz, Thomas Baltzer, Greg Lucas, James Craft, Jennifer Knuth, Thomas Berger, Eric Sutton, Daniel N. Baker, Allison Jaynes|
| ||University of Colorado, Boulder, Laboratory for Atmospheric and Space Physics (LASP),  University of Colorado, Boulder, Space Weather Technology, Research, and Education Center (SWx TREC),  University of Iowa|
| ||The Space Weather Technology, Research and Education Center (SWx TREC) is an emerging national center of excellence in cross-disciplinary research, technology, innovation, and education, intended to facilitate evolving space weather research and forecasting needs. SWx TREC is positioned to facilitate breakthrough research advances, innovative missions, and data and computing technologies that directly support the needs of the operational forecasting enterprise to ensure 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 is serving many of these needs, including 1) implementation of an interoperable data portal intended to more effectively serve the needs of the Space Weather research community and 2) implementing a community-accessible testbed environment to support development, testing, transition, and use of new models and algorithms. In this presentation, we will outline the motivating factors for effective space weather data access and modeling support, describe a new testbed environment for supporting model, algorithm, and visualization testing/incubation needs, and demonstrate a new Space Weather Data Portal, designed to meet the data management and access needs of the disparate communities who require space weather data and information. |
|10||SWiFT-FORECAST: real time physics-based solar wind forecasts||Pinto, R et al.||p-Poster|
| ||Rui F. Pinto, Alexis P. Rouillard, Vincent Génot, Matthieu Alexandre|
| ||IRAP, Université de Toulouse III, CNRS, CNES, Toulouse, France|
| ||We present the real-time solar wind forecasting pipeline SWiFT (Solar Wind Flux-Tube)-FORECAST developed at IRAP. SWiFT-FORECAST is meant to perform quick and robust simulations (forward modelling) of the whole chain of processes that determine the state of the solar wind from the surface of the Sun to the heliosphere (much faster than full 3D MHD models). The pipeline couples a series of modules derived from mature research models: determination of the background coronal magnetic field, computation of many individual solar wind acceleration profiles (1 to 90 solar radii), propagation across the heliosphere and formation of CIRs (up to 1 AU or more), estimation of synthetic diagnostics (white-light and EUV imaging, in-situ time-series) and comparison to observations and spacecraft measurements. SWiFT-FORECAST can combine different magnotograms sources (WSO, SOLIS, GONG, ADAPT), coronal field reconstruction methods (PFSS, NLFFF), wind models (MULTI-VP), and heliospheric propagation models (CDPP/AMDA 1D MHD, ENLIL, EUHFORIA). I will discuss an implementation of this modeling chain and of a web-based service able provide continuously a full set of bulk physical parameters (wind speed, density, temperature, magnetic field, phase speeds) of the solar wind up to 6-7 days in advance, at a time cadence compatible with space weather applications.|
|11||SWx TREC Testbed: Facilitating Model/Algorithm R2O and O2R Development within a Cloud Computing Environment||Lucas, G et al.||p-Poster|
| ||Greg Lucas, James Craft, Christopher K. Pankratz, Thomas Baltzer, Eric Sutton, Thomas Berger|
| || LASP,  University of Colorado|
| ||The Space Weather Technology, Research and Education Center (SWx TREC) is an emerging national center of excellence in cross-disciplinary research, technology, innovation, and education, intended to facilitate evolving space weather research and forecasting needs. Within this center, we are developing a Space Weather Testbed environment to facilitate the research to operations (R2O) and operations to research (O2R) pipelines. The Testbed leverages cloud computing to provide a managed computational environment for independent science teams to deploy their processing software into an operational-like system. Using cloud computing for the environment enables traditional defined-cadence (daily, hourly) model runs to be scheduled while also providing the ability to submit on-demand runs during storm times with no additional bulk hardware purchases that would otherwise sit idle most of the time.
In this poster, we will discuss the technologies that are being used in producing the Space Weather Testbed and demonstrate several ways that the testbed is currently being utilized. First, in the R2O pipeline, we have implemented code from the USGS to produce electric field maps at a set cadence to demonstrate that the code can be run in an operational mode. Second, in the O2R pipeline, we are taking an operational code, the NOAA Whole Atmosphere Model (WAM), and enabling researchers to investigate new data assimilation techniques that can supplement and enhance current operational code capabilities. Finally, we demonstrate the use of cloud resources to generate automatic flare forecasts from satellite images. The Space Weather TREC Testbed is utilizing modern computer architectures and software practices to facilitate researchers and forecasters bridge the R2O and O2R gaps.||