Session 5 - Developing new space weather tools: Bridging between the fundamental science and operations

Misha Balikhin (The University of Sheffield, UK), D. Shaun Bloomfield (Northumbria University, UK), Juan V. Rodriguez (University of Colorado CIRES), Didier Mourenas (CEA, DAM, DIF, Arpajon, France)
Tuesday 15/11, 11:00-13:00
Wednesd16/11, 10:00-13:00
Ridderzaal

The field of Space Weather has grown out of the fundamental subjects of solar terrestrial physics and space plasma physics. However, the most important impacts of Space Weather are not in advances in the fundamental problems of related branches of physics but in the development of operational tools that are able to provide the reliable services required by industrial and societal consumers/stakeholders. A substantial number of researchers that are involved in Space Weather have their background in fundamental science. While such a background is advantageous for the development of new space weather forecasting tools, it can also bias their views as to the desirable features of operational tools. For the transformation of a good forecasting/nowcasting space weather model into a successful operational tool it is crucial to take into account needs and requirements of industrial and other stakeholders. It is also important to disseminate recent advances in the fore(now)-casting of space weather to stakeholders in order to receive their feedback for future development. European funding, in particular via FP7 and Horizon 2020 programs, has led to the successful development of various space weather models and forecasting tools. The aim of this session is to provide a platform for stakeholders to express their needs and requirements and to the leading developers of space weather operational tools to explain the state of art and plans for further advances. Particular attention will be given to the limitations of space weather tools arising from fundamental science in fulfilling stakeholder requirements. Contributions from EU-funded Space Weather projects both from model developers and potential stakeholders are strongly encouraged. Presentations from model developers and stakeholders that are not involved in EU projects are also very welcome.

Poster Viewing
Wednesday November 16, 10:00 - 11:00, Poster Area

Talks
Tuesday November 15, 11:00 - 13:00, Ridderzaal
Wednesday November 16, 11:00 - 13:00, Ridderzaal

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Talks : Time schedule

Tuesday November 15, 11:00 - 13:00, Ridderzaal

11:00	Requirements for “ideal” space weather forecasting tools	Jackson, D et al.	Invited Oral
	David Jackson, Mike Marsh and Suzy Bingham
	Met Office
	Space weather forecasting remains challenging, and developments of forecast models, observations (and techniques to assimilate these observations into the models) are topics of considerable and active research. Notwithstanding this, the transformation of existing models into operations must be done in such a way as to give reliable and robust results that meet user needs. In addition, the operational system should be constructed to be flexible enough to continually build in improvements that new research will herald. In this presentation we outline ideal requirements for operational space weather tools. While the ability of the system to receive and assimilate data and run forecasts in a timely manner, and to do so robustly for a range of space weather conditions, is now recognised as clear prerequisites of any system, further awareness needs to be raised of other requirements. These include quality assurance (eg a high standard of code structure, documentation, error handling and version control allowing systematic model management like performing acceptance tests); ability to use operating systems and computer languages that an operational centre can support on a 24/7 basis, and freedom from dependencies on non-standard libraries not under the operational centre control.
11:25	Requirements for the First U.S. National Weather Service Geospace Model	Singer, H et al.	Invited Oral
	Howard J. Singer[1], George Millward[1,2], Christopher Balch[1], Tom Berger[1], Terrance G. Onsager[1], Rodney Viereck[1], Gabor Toth[3], Daniel Welling[3], and Tamas Gombosi[3]
	[1]NOAA Space Weather Prediction Center; [2]University of Colorado, Cooperative Institute for Research in Environmental Sciences (CIRES); [3]University of Michigan, Atmospheric, Oceanic and Space Sciences
	In 2016, NOAA’s Space Weather Prediction Center (SWPC), an organization with the U.S. National Weather Service (NWS) National Centers for Environmental Prediction (NCEP) transitioned the University of Michigan’s Geospace model into operations. This effort was carried out in collaboration with our partners at the University of Michigan and NCEP Central Operations (NCO) that runs the U.S. operational model suite for climate, weather, ocean, space and environmental hazard products. We were also supported in the model selection by Geospace modelers and NASA’s Community Coordinated Modeling Center (CCMC). The Geospace Model is a global model of the Earth’s Geospace environment that extends from the surface of Earth to the interface between the solar wind and Earth’s magnetic field. The Geospace Model utilizes three components of the University of Michigan's Space Weather Modeling Framework (SWMF). These component models are: global magnetosphere, inner magnetosphere, and ionosphere electrodynamics. Included in model predictions are ground magnetic disturbances resulting from Geospace interactions with the solar wind. Such magnetic disturbances induce currents in large-scale electrical conductors, such as the power grid, and have the potential, during disturbed times, to damage such systems. Advanced warning from the model provides power grid operators with situational awareness and allows them time to mitigate the problem and maintain the integrity of the electric power grid. In this presentation, we will describe the various “requirements” for bringing the Geospace model into operations and for future maintenance and improvement. Requirements begin with user needs such as power grid operators, but also involve a broad spectrum of requirements and needs having to do with selecting a science model for operations (Research to Operations), preparing and running the model in an operational setting, producing products for forecasters and customers, and describing the need for future improvements to the science community (Operations to Research). All of these efforts will result in new impact-based decision support services through regional specification and forecasts of geomagnetic activity.
11:50	Forecasting the perfect storm	Pitchford, D et al.	Invited Oral
	Dave Pitchford
	SES
	This talk discusses the needs of Spacecraft Operators for Space Weather forecasting tools and services. The needs of Spacecraft Operators is evolving rapidly as the industry is changing from one focused on the geosynchronous orbit to one where the assets involved are in a wide range of orbits - still GEO but also MEO, LEO and long duration Electric Orbit Raising trajectories. The different needs for tools are outlined, to enable operators to weather the Perfect Storm in the uncharted waters that our space assets are now operating in.
12:15	VNC: Application of Physics and Systems Science methodologies to Forecasting of the Radiation Belt Electron Environment	Walker, S et al.	Oral
	Simon N. Walker[1], Ivan P. Pakhotin[1,2], Yuri Y. Shprits[3]
	[1]ACSE, University of Sheffield, Sheffield, U.K.; [2]Now at University of Alberta, Canada; [3]GFZ, Potsdam, Germany.
	Physics based models, such as the Versatile Electron Radiation Belt (VERB) model, are typically based on the conjugation of models of individual plasma processes. Today, the accuracy of such models is greatly improved by the addition of data assimilation techniques. While achieving excellent past-cast and now-cast results, their ability to forecast is strongly dependent upon accurate forecast of their driving parameters. Systems Science methodologies, such as NARMAX, have the ability to generate models from data alone. Such models possess excellent abilities in forecasting the future evolution of a system. This talk outlines the use of NARMAX forecasts to drive VERB. Example past-casts are discussed and compared to observations from Van Allen Probes.
12:30	15 years of New Zealand Geomagnetically Induced Current observations - working towards operational hazard estimates	Rodger, C et al.	Oral
	Craig J. Rodger[1], Daniel H. Mac Manus[1], Michael Dalzell[2], Alan W. P. Thomson[3], Tim Divett[1], Ellen Clarke[3], Tanja Petersen[4] and Mark A. Clilverd[5]
	[1]University of Otago, New Zealand; [2]Transpower New Zealand Limited, New Zealand; [3]British Geological Survey, United Kingdom; [4]GNS Science, New Zealand; [5]British Antarctic Survey, United Kingdom
	Transpower New Zealand Limited have measured DC currents at transformers in the New Zealand electrical network at multiple South Island locations for many years. The primary reason for the DC measurements has been to monitor the impact of the HVDC system linking the North and South Islands when it is operating in "Earth return" mode. Near continuous archived DC current data exist since 2001, starting with 11 different substations, and expanding from 2012 to include 17 substations. In some cases multiple measurements are made at different transformers inside the same substation. The recent expansion was undertaken to better monitor the Space Weather risk caused by Geomagnetically Induced Currents (GIC). It is recognised that GIC caused the loss of a South Island transformer in November 2001, during a storm that caused multiple alarms across the South Island. The long time period of the monitoring and the relatively dense spatial coverage make this an internationally important dataset for GIC studies. The New Zealand Ministry of Business, Innovation and Employment has recently funded a joint New Zealand-United Kingdom project to investigate the risk posed by GIC to the New Zealand electrical network. Transpower (the transmission system operator) is a key stakeholder in this project. In this talk we will therefore discuss the dataset, our project, and some preliminary analysis undertaken of data measured during large geomagnetic storms. During storms we find some locations report GIC of many tens of amps, but there is strong variation across the South Island. Of particular importance to operators, we find that the GIC magnitude varies inside substations, depending on the local electrical setup. Due to the number of GIC measurements during large geomagnetic storms (e.g., >40 nT/min local magnetic field rate of change) in our dataset we are able to make rough estimates of the extreme GIC values likely in a worst case scenario. As this is many hundred's of amps, GIC is clearly a hazard to the New Zealand electrical transmission system, despite our mid-latitude location. We will also discuss the project goals, which includes developing a New Zealand specific model capable for predicting GIC at the individual transformer level. This model will be validated through the 15 year GIC observational database. We will also consider both extreme events and test the existing Transpower protocols for mitigating the impact of GIC during severe geomagnetic storms.
12:40	Nowcast and forecast of Kp index	Wintoft, P et al.	Oral
	P. Wintoft[1], M. Wik[1], J. Katkalov[1], S.N. Walker[2], H.-L. Wei[2], J. Matzka[3]
	[1]Swedish Institute of Space Physics; [2]University of Sheffield; [3]GFZ German Research Centre For Geosciences
	The Kp index, developed by Bartels (1949) to monitor worldwide magnetic activity, is widely used as a general disturbance indicator and as input for different models, such as satellite drag models and radiation belt models. In this work we present the further developments of prediction algorithms driven by upstream solar wind data. The solar wind can be either measured from spacecraft or predicted from solar wind models. Different verification approaches are applied considering the two modes of operation: observed and modelled solar wind inputs. In the first case the timing of storm onset is crucial as the lead time is of the order of an hour. In the second case the focus is on the storm events, described by measures like magnitude and duration. We also show that high resolution (minutes) solar wind data are necessary to accurately predict the Kp index, a consequence of that Kp measures the range of variation based on high resolution magnetic measurements over a 3-hour interval. The solar wind driven algorithms are also compared to real-time estimates of the Kp index. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302, and the ESA SSA Space Weather ESC contract No 4000113185/15/D/MRP.
12:50	FLARECAST Development Infrastructure: A science-oriented data processing framework	Soldati, M et al.	Oral
	Marco Soldati[1], Samuel von Stachelski[1], Michele Piana[2], D. Shaun Bloomfield[3,4] and the FLARECAST team
	[1]Institute of 4D Technologies, Fachhochschule Nordwestschweiz, Switzerland; [2]Dipartimento di Matematica, Università di Genova and CNR SPIN, Genova, Italy; [3]Trinity College Dublin, College Green, Dublin 2, Ireland; [4]Northumbria University, Newcastle Upon Tyne, NE1 8ST, UK
	The Flare Likelihood And Region Eruption foreCASTing (FLARECAST) project aims to forecast solar flares by applying advanced prediction algorithms to active region properties determined from several data sources. FLARECAST is driven by property-extraction and flare-prediction algorithms developed by multiple science teams in different programming languages and with significantly varying needs of computing resources. Here, we will outline the development infrastructure for FLARECAST that is both flexible and simple. Crucial elements include the use of Docker containers (i.e., lightweight virtual machines) to facilitate multiple programming languages and scalable use on varying computing infrastructures and a well-defined RESTful API for the connection between the algorithms and their dedicated databases. The FLARECAST data model enhances a common relational data model with the flexibility of schema-less, NoSQL data model concepts. This enables the storing of simple data fields (like strings or numbers) as well as complex data structures (such as dictionaries and arrays) within a single data structure. This research was supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 640216 (FLARECAST project).

Wednesday November 16, 11:00 - 13:00, Ridderzaal

11:00	Space Weather Research at AFOSR	Miller, K et al.	Invited Oral
	Kent L. Miller
	European Office of Scientific Research
	Basic research programs at the Air Force Office of Scientific Research (AFOSR) are described. Program officers at AFOSR discover, shape, and champion basic science that profoundly impacts the future US Air Force. In doing so, they also impact civilian science. The AFOSR organization includes four international offices. International program officers have the additional responsibility of acting as liaison officers for all programs of the Air Force Research Laboratory to the international science community. Space weather research sponsored by AFOSR is, for the most part, focused on the understanding of the space environment with a goal to enable and extend operational forecasting. The motivation for this research lies in three major areas: orbit determination and propagation, satellite survivability, and communication and navigation. In its role as a sponsor of basic research, AFOSR does not directly sponsor the development of forecasting tools to meet requirements of the operational Air Force, but program officers must be aware of these requirements to be able to develop relevant research programs.
11:25	From studying electron motion in the electromagnetic fields in the inner magnetosphere to the operational nowcast model for low energy (< 200 keV) electron fluxes responsible for surface charging	Ganushkina, N et al.	Invited Oral
	Natalia Ganushkina[1,2], Stepan Dubyagin[1], Ilkka Sillanpää[1]
	[1]Finnish Meteorological Institute, Helsinki, Finland; [2]University of Michigan, Ann Arbor MI, USA
	The distribution of low energy electrons (10 to few hundreds of keV) is critically important in the inner magnetosphere. They constitute the seed population for radiation belts being further accelerated to MeV energies and they are responsible for surface charging effects. These electrons move from the plasma sheet to inner regions in time-varying electromagnetic fields. The electron flux at these energies varies significantly with geomagnetic activity. It is largely determined by convective and inductive electric fields and varies significantly with substorm activity driven by the solar wind. Studies of the electron motion in the electromagnetic fields in the inner magnetosphere were the base for the developing of the physics-based, research-oriented Inner Magnetosphere Particle Transport and Acceleration model (IMPTAM). IMPTAM is now adapted to be a nowcast model for low energy (< 200 keV) electrons operating online under the completed FP7 SPACECAST project (http://fp7-spacecast.eu) and on-going FP7 SPACESTORM and H2020 PROGRESS projects (imptam.fmi.fi). The nowcast model is driven by the real time solar wind and IMF parameters with 1 hour time shift for propagation to the Earth's magnetopause, and by the real time Dst index. Real time geostationary GOES 13 or GOES 15 (whenever which available) MAGED data on electron fluxes at three energies (40, 75, and 150 keV) are used for comparison and validation of IMPTAM running online. Working online near-real time nowcast of low energy electrons is very important tool and it provides highly valuable output. The research leading to these results was partly funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 606716 SPACESTORM and by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 637302 PROGRESS.
11:50	Data Assimilation for Prediction and Reanalysis of the Radiation Belts	Shprits, Y et al.	Invited Oral
	Yuri Shprits[1,2] and Adam Kellerman[2]
	[1]GFZ, Potsdam; [2]UCLA
	We discuss how data assimilation can be used for the reconstruction of long-term evolution, and use of data assimilation to improve the now-casting and focusing of the radiation belts. We also discuss advanced data assimilation methods such as parameter estimation and smoothing. We present a number of data assimilation applications using the VERB 3D code. The 3D data assimilative VERB allows us to blend together data from GOES, RBSP A and RBSP B. 1) Model with data assimilation allows us to propagate data to different pitch angles, energies, and L-shells and blends them together with the physics-based VERB code in an optimal way. We illustrate how to use this capability for the analysis of the previous events and for obtaining a global and statistical view of the system. 2) The model predictions strongly depend on initial conditions that are set up for the model. Therefore, the model is as good as the initial conditions that it uses. To produce the best possible initial conditions, data from different sources (GOES, RBSP A, B, our empirical model predictions based on ACE) are all blended together in an optimal way by means of data assimilation, as described above. This allows us to make more accurate predictions. Real-time prediction framework operating on our website, based on GOES, RBSP A, B and ACE data, and 3D VERB, is presented and discussed.
12:10	FLARECAST Science: A comprehensive database of solar flare predictors	Georgoulis, M et al.	Oral
	Manolis K. Georgoulis[1], D. Shaun Bloomfield[2,3] and the FLARECAST team
	[1]RCAAM of the Academy of Athens, 11527 Athens, Greece; [2]Trinity College Dublin, College Green, Dublin 2, Ireland; [3]Northumbria University, Newcastle Upon Tyne, NE1 8ST, UK
	The Flare Likelihood And Region Eruption foreCASTing (FLARECAST) project is arguably the most systematic effort dedicated to a reliable prediction of solar X-ray flares. By its conclusion, at the end of 2017, an interactive and operationally-oriented facility will become available to researchers, stakeholders, decision makers, and the general public. In this presentation we glimpse under FLARECAST's hood to probe the collective science of the project's flare predictors, comprising the project's property database. Besides existing predictors, we also present a number of newly implemented ones that have emerged from recent studies either external to, or in the framework of, the project. Concluding, we offer some preliminary project results showcasing the merit of the followed multi-variate flare-prediction approach that is also able to classify between predictors in terms of prediction efficiency. This further enhances our understanding of the fundamental processes of solar magnetism leading to the triggering of solar flares, in particular, and solar eruptions, in general. This research was supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No. 640216 (FLARECAST project).
12:25	Sunspot Group Evolution and Flare Forecasting	Mccloskey, A et al.	Oral
	Aoife E. McCloskey[1], Peter T. Gallagher[1], D. Shaun Bloomfield[1,2]
	[1]Trinity College Dublin, College Green, Dublin 2, Ireland; [2]Northumbria University, Newcastle Upon Tyne, NE1 8ST, UK
	Previously, McIntosh white-light classifications of sunspot groups and their historical flare rates have been used to calculate Poisson probabilities for flare forecasting. Here, we examine the temporal evolution of McIntosh classifications and calculate average flare rates for the following 24-hour periods. The impact that these evolution-dependent flare rates have on the performance of flare forecasts will be presented via the application of standard forecast verification measures. Finally, potential corrective techniques for improving the forecasting performance will be explored.
12:35	Inverting the solar meridional flow and predicting the 11-yr cycle using advanced variational data assimilation techniques	Hung, C et al.	Oral
	Ching Pui Hung[1,2], Allan Sacha Brun[2], Alexandre Fournier[1], Laurène Jouve[2,3], Olivier Talagrand[4]
	[1]IPGP; [2]AIM, CEA Saclay; [3]IRAP, Observatoire Midi-Pyrénées; [4]École normale supérieure, Paris
	We show how a mean field solar dynamo model can be used in conjunction with magnetic observations of the Sun in order to estimate the large-scale meridional circulation and further extended to predict the 11-yr cycle. Our innovative approach rests on variational data assimilation, where the distance between predictions and observations (measured by an objective function) is iteratively minimized by means of an optimization algorithm seeking the meridional flow which best accounts for the data and the integration of an adjoint dynamo model. Closed-loop (also known as twin) experiments using synthetic data demonstrate the validity and accuracy of this technique, for a variety of meridional flow configurations, ranging from unicellular and equatorially symmetric to multicellular and equatorially asymmetric. We find that the method is remarkably robust, leading in most cases to a recovery of the true meridional flow to within better than 1%. We also show that our technique is capable to reconstruct a stochastic, time varying meridional flow and the initial magnetic field at the convection zone within the assimilation window, by ingesting synthetic solar magnetic proxies. These encouraging results are a first step towards using this technique to i) better constrain the physical processes occurring inside the Sun and ii) better predict solar activity on decadal time scales, and with our technique we are currently analyzing the observations of the last 3 solar cycles from Wilcox Solar Observatory to estimate the meridional flow.
12:45	Combining multiple observations into one single composite: toward new Total Solar Irradiance and MgII index composites	Dudok de wit, T et al.	Oral
	T. Dudok de Wit[1], C. Fröhlich[2], M. Haberreiter[2], G. Kopp[3], M. Kretzschmar[1], M. Schöll[1,2], M. Weber[4]
	[1]LPC2E, CNRS and University of Orléans, France; [2]PMOD/WRC, Davos, Switzerland; [3]LASP, University of Colorado, Boulder, USA; [4]IUP, University of Bremen, Germany
	Several key quantities for space weather, such as the sunspot number and the MgII index, critically rely on our ability to combine multiple (and partly overlapping) observations into a single composite record. Currently, most composites are created by using backbones (whereby one preferred record serves as a reference to all others) and/or by daisy-chaining (whereby neighboring records are stitched together by their overlap regions). Both methods have serious shortcomings. We have developed a new approach that stands out by being fully traceable and unbiased, as observations are weighted by their frequency-dependent mode uncertainties. This approach involves a multi-scale decomposition, from which data gaps can be bridged in a natural way. We present results obtained from the creation of new TSI (1980-today) and MgII index (1978-today) composites. Interestingly, for both the uncertainties exhibit a 1/f scaling with frequency, which has important implications on their long-term stability.
12:55	Highlights and results from the FP7 HELCATS (Heliospheric Cataloguing, Analysis and Techniques Service) project	Harrison, R et al.	Oral
	Richard Harrison[1], Jackie Davies[1], David Barnes[1], Chris Perry[1], Christian Moestl[2], Alexis Rouillard[3], Volker Bothmer[4], Luciano Rodriguez[5], Jonathan Eastwood[6], Emilia Kilpua[7], Peter Gallagher[8], Dusan Odstrčil[9]
	[1]RAL Space, United Kingdom; [2]University of Graz, Austria; [3]Paul Sabatier University, France; [4]University of Götingen, Germany; [5]Royal Observatory Belgium, Belgium; [6]Imperial College London, United Kingdom; [7]University of Helsinki, Finland; [8]Trinity College Dublin, Ireland; [9]George Mason University, USA.
	Understanding the evolution of the solar wind is fundamental to advancing our knowledge of energy and mass transport in the solar system, rendering it crucial for space weather applications. The advent of wide-angle heliospheric imaging has revolutionised the study of both transient (Coronal Mass Ejections; CMEs) and background solar wind plasma structures (Stream/Co-rotating Interaction Regions; SIRs/CIRs), by enabling their direct and continuous observation out to 1 AU and beyond. The EU-funded FP7 HELCATS project (May 2014 to May 2017) combines European expertise in heliospheric imaging ─ built up in particular through lead of the Heliospheric Imager (HI) instruments on NASA’s STEREO mission ─ with expertise in solar and coronal imaging as well as in-situ and radio measurements of solar wind phenomena, in a programme of work that is enabling a much broader understanding, and wider exploitation, of heliospheric imaging observations. Of particular relevance here, we emphasise that the HELCATS project is also providing a basis for the future exploitation of heliospheric imagery for operational space weather purposes, not least through the assessment of a number of heliospheric imaging analyses techniques. This is being achieved through an activity that encompasses the cataloguing of CMEs and SIRs/CIRs observed by STEREO/HI in the heliosphere, with the validation of their kinematic properties ─ derived by various modelling methodologies including geometrical and forward modelling ─ using observations of their source regions and their arrivals at various in-situ observatories. HELCATS endeavours also include assessment of the complementarity of heliospheric imaging and radio techniques, in particular the observation of Type II radio bursts and interplanetary scintillation. In this presentation, we review the achievements of the HELCATS project, which is now in its final year ─ particularly in the context of space weather ─ and provide details for those wishing to access the extensive facilities provided by the project.

Posters

Wednesday November 16, 10:00 - 11:00, Poster Area

1	Spatial and temporal properties of chorus emissions observed by THEMIS	Shastun, V et al.	e-Poster
	V. Shastun[1], V. Krasnoselskikh[1], O. Agapitov[2]
	[1]LPC2E CNRS, University of Orleans; [2]Space Science Laboratory, the University of California
	Relativistic electrons in the outer radiation belt can be effectively accelerated and scattered due to interaction with lower-band chorus waves ($0.1 < f/f_{ce} < 0.5$). The waves are often quite localized in local time and radial direction -- thus, the spatial and temporal scales of active region and source region of chorus wave modes play a crucial role in determining the extent of wave-particle interactions and define possible biasing for statistical models, where all measurements are assumed to be statistically independent. Using measurements from THEMIS, we assess the spatial and temporal extent of active chorus regions, and the dependence of these scales on local time, radial distance, and geomagnetic activity. We perform statistical study of THEMIS filter bank spectral data collected during 2008-2014 and show that two regimes can be statistically distinguished depending upon the correlation time of the whistler emissions in lower-band chorus frequency range. In the presence of chorus waves, it is found that the correlation times vary between 200 and 300 s depending upon $L$-shell. In the absence of intense chorus waves, the correlation time drops to around 50 s. The correlation time scales for intense chorus waves increase with increasing of $L$-shell from $\sim200s$ at L = 4 to $\sim300$ s at L = 7. Spatial scales of chorus waves in equatorial plane exhibit clear dependency on $L$-shells. Chorus waves are found to be highly correlated at distances up to 500 km at L = 4 and 1400 km at L = 9 in equatorial plane.
2	Modelling GIC Flow in the South Island Electrical Transmission Grid of New Zealand	Divett, T et al.	e-Poster
	Tim Divett[1], Alan Thomson[2], Malcolm Ingham[3], Craig J. Rodger[1], Ciaran Beggan[2], Gemma Kelly[2]
	[1]University of Otago, New Zealand; [2]British Geological Survey, United Kingdom; [3]Victoria University of Wellington, New Zealand
	Transformers in Transpower New Zealand Ltd's South Island electrical grid have occasionally been impacted by near-DC geomagnetically induced currents (GIC) during geomagnetic events, for example November 2001. In this study an initial model of the South Island's grid has therefore been developed to advance understanding of the impact of space weather on New Zealand's grid. New Zealand's latitude and island setting, mean that modelling approaches successfully applied in the UK in the past can be used. However, deep water (4000 m) near the coast means even stronger spatial gradients of conductance can occur around New Zealand compared to the situation in the UK's shallow continental shelf. This strong gradient poses challenges for the thin-sheet model (of Vasseur and Weidelt) used to model the electric field as a function of magnetic field and conductance. The NZ electrical transmission grid consists of lines carrying 220kV, 110kV and 66kV with multiple earthing nodes at each transformer substation. The relative importance of the 66kV network is explored in this study, in relation to currents induced in the higher voltage lines. Transpower have measured DC earth currents at 17 substations at selected locations in the South Island grid for up to 15 years, including through multiple transformers at the same substation. Different transformers at the same substation can experience quite different GIC during space weather events. Therefore, in this work, each transformer at each substation is modelled separately to compare directly with the measured currents. The sensitivity of induced current in the grid to the direction of an imposed electric field is also explored. Our model will eventually be used as an operational and validated tool to explore the risk to the New Zealand grid from geomagnetic storms. Further, mitigation tactics which could be used to reduce the threat to the electrical grid will be evaluated. Ultimately this study aims to develop a modelling tool that will be used to strengthen New Zealand's grid against the risks of space weather. In particular we will focus at the transformer level where the risk lies, and not at the substation level as has been commonly done to date. As we will validate our model against the extensive Transpower observations, this will be a valuable confirmation of the approaches used by the wider international community.
3	A mid-latitude local geomagnetic index new scaling	Palacios, J et al.	e-Poster
	J. Palacios, A.Guerrero, C.Cid, E. Saiz, Y. Cerrato
	Dpt. of Physics and Mathematics, Universidad de Alcala (UAH)
	Ldi\~n is a mid-latitude local geomagnetic index (patent pending). This index is associated to a scale derived from a new thresholding based on statistical properties of its particular distribution. This scale and the equivalent for the index derivative has been specifically designed for users and applied during the last two years in the own color-coded scales of the Spanish Space Weather Service with adequate results on storm classification and GICs nowcasting.
4	Refining AWDANet performance: a decade of whistlers	Koronczay, D et al.	e-Poster
	Dávid Koronczay[1,2], János Lichtenberger[2,1], Lilla Juhász[2], Péter Steinbach[3,2], Csaba Ferencz[2], Mark Clilverd[4], Craig Rodger[5], Dmitry Sannikov[6], Nina Cherneva[6]
	[1]Geodetic and Geophysical Institute, Hungarian Academy of Sciences, Sopron, Hungary; [2]Department of Geophysics and Space Sciences, Eötvös University, Budapest, Hungary; [3]MTA-ELTE Research Group for Geology, Geophysics and Space Sciences, Hungarian Academy of Sciences, Eötvös University, Budapest, Hungary; [4]British Antarctic Survey (NERC), Cambridge, UK; [5]Department of Physics, University of Otago, Dunedin, New Zealand; [6]Institute of Cosmophysical Research and Radio Wave Propagation, FEB RAS, Paratunka, Russia
	AWDANet is a ground-based network monitoring the plasmasphere by performing automatic whistler detection and inversion. These whistlers, originating on the ground as EM signals of lightning strokes, probe the plasmasphere. In order to refine the performance, here we carry out a thorough analysis of a decade of whistler data from AWDANet and its precursor stations, comparing them with lightning databases such as the WWLLN. We show the typical source regions, diurnal and seasonal activities, and probable propagation types and paths of these whistlers.
5	Simulating, cataloguing and forecasting the background solar wind conditions.	Pinto, R et al.	e-Poster
	R. F. Pinto[1,2], A. Rouillard[1,2]
	[1]Université de Toulouse; UPS-OMP; IRAP; Toulouse, France; [2]CNRS; IRAP; 9 Av. colonel Roche, BP 44346, F-31028 Toulouse cedex 4, France
	The large-scale solar wind speed distribution varies in time in response to the cyclic variations of the strength and geometry of the magnetic field of the corona. Fast wind flows develop exclusively within coronal holes, while the slow solar wind streams typically from the vicinity of the coronal hole boundaries (i.e, around streamers and pseudo-streamers) and/or active regions. Based on this idea, semi-empirical predictive laws for the solar wind speed (such as in the widely-used WSA law) use simple parameters describing the geometry of the coronal magnetic field. In practice, such scaling laws require ad-hoc corrections and empirical fits to in-situ spacecraft data, and a predictive law based solely on physical principles is still missing. I will present a new numerical solar wind model which takes a coronal magnetic field map as input (past data or forecast), and computes a collection of solar wind profiles spanning a region of interest of the solar atmosphere (up to a full synoptic map) at any instant desired in quasi - real time, while keeping a good description the plasma heating and cooling mechanisms. We used this model to estimate full sets of inner boundary conditions for ENLIL (at 21.5 Rsun, see https://stormsweb.irap.omp.eu/doku.php?id=windmaptable), in order to produce detailed maps of the background solar wind in the heliosphere and calibrate them against spacecraft data. These wind maps will be available as HELCATS catalogues (http://www.helcats-fp7.eu/).
6	Observations of Heliospheric Faraday Rotation of a CME Using LOFAR and Space-Based Imaging	Bisi, M et al.	e-Poster
	Mario M. Bisi[1], Elizabeth A. Jensen[2], Charlotte Sobey[3,4,5], Richard A. Fallows[3], Bernard V. Jackson[6], David Barnes[1], Alessandra Giunta[1], P. Paul L. Hick[7,6], Tarraneh Eftekhari[8], Hsiu-Shan Yu[6], Dusan Odstrcil[9,10] and Munetoshi Tokumaru[11].
	[1]STFC-RAL Space, UK; [2]Planetary Science Institute, AZ, USA; [3]ASTRON, NL; [4]Curtain Institute of Radio Astronomy, WA, Australia; [5]CSIRO Astronomy and Space Science, WA, Australia; [6]CASS-UCSD, CA, USA; [7]SDSC-UCSD, CA, USA; [8]University of New Mexico, NM, USA; [9]GMU, VA, USA; [10]NASA GSFC, MD, USA; [11]ISEE, Nagoya University, Japan.
	The most-intense space weather at Earth is driven by geomagnetic storms. Their intensity is determined by the speed, density, and magnetic-field of the incoming plasma from the Sun. The most-important determining factor overall is that of the North-South component of magnetic field (Bz in Geocentric Solar Magnetic - GSM - coordinates). At present, there is no reliable prediction of this magnetic-field component until the incoming plasma from the Sun has reached in-situ monitors around the L1 point and this provides only 15-60 minutes advanced warning. Observations of Faraday rotation (FR) can be used as a remote-sensing method of determining magnetic fields which has been well demonstrated through the corona, ionosphere, and interstellar medium. FR values are obtained via observations of polarised radio sources with well-documented characteristics (astronomical radio sources observed are typically Pulsars). Measurements of the inner corona of the Sun in FR have been shown from both spacecraft beacons and some natural radio sources but at relatively-high radio frequencies. Here we show some initial results of true heliospheric FR using the Low Frequency Array (LOFAR) below 200 MHz to investigate the passage of a coronal mass ejection (CME) across the line of sight. LOFAR is a next-generation low-frequency radio interferometer, and a pathfinder to the Square Kilometre Array (SKA) – LOW telescope. It has wide-ranging radio-astronomy capabilities from imaging to beam forming multiple beams on the sky. We demonstrate preliminary heliospheric FR results through the analysis of observations of pulsar J1022+1001, which commenced on 13 August 2014 at 13:00UT and spanned over 150 minutes in duration. We also show initial comparisons to the FR results via modelling techniques and additional context information to understand the structure of the inner heliosphere being detected. This observation could pave the way to a set of observations and modelling techniques that might be implemented for space-weather purposes eventually leading to a near-global method for determining the magnetic field throughout the inner heliosphere.
7	Development of an Ionospheric Storm-time Index over South African Region	Tshisaphungo, M et al.	e-Poster
	Mpho Tshisaphungo, Lee-Anne McKinnell, John Bosco Habarulema
	South African National Space Agency (SANSA) Space Science, Hermanus, South Africa
	The South African National Space Agency (SANSA) operates the Space Weather Regional Warning Center (RWC) for Africa. The center exists within the SANSA Space Science Directorate located at Hermanus, South Africa. The main space weather service offered by the centre is High Frequency (HF) radio wave propagation predictions and a constant monitoring of the ionospheric conditions over the African region is crucial. It is also important to study the HF propagation conditions and its drivers especially during severe space weather storms. This paper presents the development of an ionospheric storm-time index with the purpose of serving the HF communication users. The index will result into a valuable tool for measuring the complex ionospheric behaviour in an operational space weather monitoring and forecasting environment. The development of an ionospheric storm-time index is based on local (Grahamstown Station, 33.3°S, 26.5°E) measurements of the critical frequency of the F2 layer (foF2) for a period 1996-2014. The progress made towards the development of such index will be presented.
8	Solar wind driven empirical model of electron plasma sheet densities and temperatures beyond geostationary orbit during storm times	Ganushkina, N et al.	p-Poster
	Stepan Dubyagin[1], Natalia Ganushkina[1,2], Andrei Runov[3]
	[1]Finnish Meteorological Institute, Helsinki, Finland; [2]University of Michigan, Ann Arbor MI, USA; [3]Institute of Geophysics and Planetary Physics, University of California, Los Angeles, USA.
	The empirical models of the plasma sheet electron temperature and density on the nightside at distances between 6 and 11 RE are constructed based on THEMIS particle measurements covering the energy range from tens electronvolts up to 300 keV. The equatorial distribution of the electron density reveals a strong earthward gradient and a moderate variation with magnetic local time (MLT) symmetric with respect to the midnight meridian. The electron density dependence on the external driving is parameterized by the solar wind proton density averaged over 4 hours and the southward component of interplanetary magnetic field (IMF BS) averaged over 6 hours. The solar wind proton density is the main controlling parameter but the IMF BS becomes of almost the same importance in the near-Earth region. The density increases with the increase in either input parameter. The correlation coefficient is 0.82, the highest correlation ever obtained for this kind of empirical models. The equatorial distribution of the electron temperature has a maximum in the post-midnight- morning MLT sector, and it is highly asymmetric with respect to the local midnight. The electron temperature model is parameterized by solar wind velocity (averaged over 2 hours), IMF BS (averaged over 45 min), and IMF BN (northward component of IMF, averaged over 2 hours). The solar wind velocity is a major controlling parameter and IMF BS and BN are comparable in importance.The plasma sheet electron temperature increases with the solar wind velocity and IMF BS increase and decreases with the IMF BN increase. The effect of BN manifests mostly in the outer part of the modelled region (r > 8RE). The correlation coefficient between the observed and predicted plasma sheet electron temperature values is 0.76. The obtained empirical model serves as a boundary conditions when modeling keV seed electron population transported from the plasma sheet to inner regions and further accelerated to MeV energies. The research leading to these results was partly funded by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 606716 SPACESTORM and by the European Union’s Horizon 2020 research and innovation programme under grant agreement No 637302 PROGRESS.
9	Transparent Predictive Models for Geomagnetic Indices: NARMAX Methods with a Case Study for Kp Index Modelling	Wei, H et al.	p-Poster
	Hua-Liang Wei
	University of Sheffield
	Kp index is a planetary measure to quantify global disturbances of the terrestrial magnetosphere. This study aims to build mathematical models that characterise the dependent relationship of Kp index on a few solar wind parameters and magnetic field indices, namely, Kp index, solar wind velocity (V), southward interplanetary magnetic field (Bs), solar wind rectified electric field (VBs), and dynamic flow pressure (P). It requires that such models be used to characterise and predict the variation of Kp index for further future analysis. System identification techniques are employed to construct predictive models, merely based upon measurements of these solar wind parameters and magnetic field indices. More specifically, the Nonlinear AutoRegressive Moving Average with eXogenous inputs (NARMAX) model, due to its unique property in terms of transparency, flexibility, robustness and easy-to-compute, is used to represent dependent relationship of Kp index on a few solar wind parameters and magnetic field indices.
10	Electron Flux Models at GEO for GOES MAGED Energies	Boynton, R et al.	p-Poster
	Richard Boynton, Simon Walker
	University of Sheffield
	Forecast models have been developed and implemented online to provide forecasts of the energetic electrons at all energy ranges sampled by the third generation Geostationary Operational Environmental Satellites (GOES). These models are based on Multi-Input Single-Output (MISO) Nonlinear AutoRegressive Moving Average with eXogenous inputs (NARMAX) methodologies. The models use solar wind and geomagnetic indices as input data to produce a forecast of the energetic electrons at Geostationary Earth Orbit (GEO). These models have been running online since July 2015 and are shown to provide accurate forecasts that are capable of warning satellite operators of when the electrons at GEO could cause problems for their spacecraft.
11	Propagation of the solar wind from the Sun to L1	Arber, T et al.	p-Poster
	Tony Arber[1], Keith Bennett[1], Bart van der Holst[2]
	[1]University of Warwick, UK; [2]University of Michigan, USA
	A new coupled simulation tool for predicting plasma conditions at L1 based on GONG data will be presented. This new tool is part of the EU funded PROGRESS project. This model works by coupling magnetograms of the solar surface to coronal physics models (AWSoM – Alfven Wave Solar atmosphere Model from Michigan). These coronal physics simulations will provide the key MHD input parameters to a solar wind inner heliospheric code with the codes coupled at about 30 solar radii. The inner heliospheric codes (SWIFT - Solar Wind Flux Transfer from Warwick) will use two-temperature MHD to transport the magnetic flux and fluid variables in spherical geometry out to L1 and beyond. First results will be presented using GONG time-series to produce L1 characteristics with a variety of physics packages and resolutions.
12	Overview on the Brazilian Space Weather (Embrace) Program	Dal lago, A et al.	p-Poster
	Alisson Dal Lago, Jose R. Cecatto, Joaquim E. R. Costa, Ligia A. da Silva, Marlos Rockenbach, Carlos R. Braga, Rafael R. S. de Mendonça, Odim Mendes Jr., Daiki Koga, Livia R. Alves, Fabio Becker-Guedes, Cristiano Max Wrasse, Hisao Takahashi, Marcelo Banik de Padua, Clezio M. De Nardin
	INPE - National Institute for Space Research, Sao Jose dos Campos, SP, Brazil
	The National Institute for Space Research (INPE, Brazil) was assigned to implement the “Brazilian Study and Monitoring of Space Weather (Embrace)” Program in 2008. The main objective of EMBRACE program is to proceed with data collection and maintenance of Space Weather observation, modeling Sun-Earth processes on a global and regional scale, provide information in real time and make Space Weather forecast, as well as provide diagnostics of their effects on different technology systems through the collection of satellite data, surface and computational modeling. Advantage was taken on the long lasting expertise of the local scientific community, specially regarding local phenomena, such as the equatorial ionosphere and effects of the South American Magnetic Anomaly. Several activities are conducted within the program, from daily space weather reports, weekly briefings, data availability and outreach. Recently a strong effort is being put to add information on the Earth’s external radiation belts, taking advantage of an on going agreement between Brazilian Space Agency and NASA related to the Van Allen Probes. In this work, we present an overview of activities and contributions related to the EMBRACE Program.
13	Predicting AE indices using empirical models	Wik, M et al.	p-Poster
	M Wik, P Wintoft, J Katkalov
	Swedish Institute of Space Physics
	The AU and AL indices, and the joint AE index, is a measure of the auroral electrojet activity in the Northern Hemisphere and indicate the intensity of geomagnetic substorms. These indices are often used in studies related to space weather effects, such as e.g. geomagnetically induced currents (GIC), or in radiation belt models. Here we present the first results from empirical models, driven by solar wind data, predicting the AE indices. In this study we used measured data from ACE, but later predicted solar wind data will be used as well. Due to the high time resolution of the AE index, which is not realistic to be captured by any model, the AE data was resampled using different methods. Various forecast lead times as well as input parameters were compared and analysed. As part of the prediction, the onset of substorms as well as the substorm duration and magnitude were also investigated. The results from the models have been verified against final AE data. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 637302.
14	Multi-thermal Segmentation of Coronal Holes	Garton, T et al.	p-Poster
	Tadhg M. Garton and Peter T. Gallagher
	Astrophysics Research Group, School of Physics, Trinity College Dublin, Dublin 2, Ireland
	Coronal holes (CH) are regions of open magnetic fields that are dark in extreme-ultraviolet and X-ray images of the solar corona. Accurate identification and segmentation of CHs has proven to be challenging due to their irregular morphology and comparable intensity to neighbouring quiet Sun regions. Many previous segmentation methods have relied on single passband images to extract CH information. Here, we present a new algorithm, which uses multi-thermal images from the Atmospheric Image Assembly (AIA) across 6 passbands (94A, 131A, 171A, 193A, 211A, 335A) and line-of-sight magnetic field images from the Helioseismic and Magnetic Imager (HMI) on-board the Solar Dynamics Observatory (SDO) to accurately identify CH boundaries. In addition, our algorithm provides estimates of many CH properties, such as area, position, latitudinal and longitudinal width, mean magnetic field, and many other CH properties. These CH properties can be used in conjunction with solar wind propagation models to more accurately estimate high speed solar wind flows at Earth.
15	A Catalogue of Geometrically-Modelled Coronal Mass Ejections Observed by the STEREO Heliospheric Imagers	Barnes, D et al.	p-Poster
	David Barnes[1], Jackie Davies[1], Richard Harrison[1], Chris Perry[1], Christian Möstl[2], Alexis Rouillard[3], Volker Bothmer[4], Luciano Rodriguez[5], Jonathan Eastwood[6], Emilia Kilpua[7], Peter Gallagher[8]
	[1]STFC-Rutherford Appleton Laboratory; [2]University Graz; [3]Paul Sabatier Université; [4]University of Göttingen; [5]Royal Observatory of Belgium; [6]Imperial College London; [7]University of Helsinki; [8]Trinity College Dublin
	We present a catalogue of the kinematic properties of Coronal Mass Ejections (CMEs) produced by applying geometric fitting techniques to CMEs observed by the Heliospheric Imagers (HIs) on-board both NASA STEREO spacecraft. The catalogue builds on previous work in which 1901 CMEs were identified in HI observations throughout the operational phase of the STEREO mission; 2007-2014. Time-elongation plots are used to track a subset of these CMEs and geometrical models are then applied to determine their speeds, propagation directions and launch times. This new catalogue contains a total of 1353 CMEs, 699 from STEREO-A and 654 from STEREO-B. A further subset of CMEs is identified, which are observable by both spacecraft, and stereoscopic fitting techniques are applied. The statistical properties of the catalogues are discussed and the results compared with those from existing CME catalogues during the same period. This work is carried out as part of the EU FP7 HELCATS (Heliospheric Cataloguing, Analysis and Techniques Service) project.
16	Space weather prediction using roubast dynamical models: identification, optimization, and risk analysis	Yatsenko, V et al.	p-Poster
	Vitaliy Yatsenko
	Space Research Institute of NASU-SSAU
	This paper concentrates on dynamic probabilistic risk analysis of optical elements with complex characterizations for damages using a physical model of solid state lasers and a predictable level of ionizing radiation and space weather. Focusing is given mainly on a solid-state laser model, mathematical models for dynamic probabilistic risk assessment and software for the modeling and prediction of ionizing radiation. The probabilistic risk assessment method for solid-state lasers is presented considering some deterministic and stochastic factors. Probabilistic risk assessment is a comprehensive, structured, and logical analysis method aimed at identifying and assessing risks in solid-state lasers in order to cost-effectively improve their safety and performance. This method is based on the Conditional Value-at-Risk (CVaR) and on the expected loss exceeding Value-at-Risk (VaR). We propose a new dynamical-information approach for the radiation damage risk assessment of laser elements affected by space radiation. Our approach includes the following steps: laser modeling, modeling ionizing radiation influences on laser elements, probabilistic risk assessment methods, and risk minimization techniques. Black-box models of space ionizing radiation influences on laser elements are developed for risk assessment in laser safety analysis. The mathematical model’s inputs are the radiation influences on laser systems and the output parameters are dynamic characteristics of the solid laser.
17	New discoveries in the auroral polarisation, steps toward an operational space weather tool.	Lilensten, J et al.	p-Poster
	Mathieu Barthélémy[1], Jean Lilensten[1], Hervé Lamy[2], Anais James[1], Magnar Johnsen[3], Joran Moen[4], Gérard Besson[5].
	[1]Institut de Planetologie et d'Astrophysique de Grenoble (UGA-CNRS), France; [2]BIRA (Brussels); [3]Tromsø Geophysical Observatory (Norway); [4]Department of Physics, University of Oslo (Norway); [5]Institut Fourier (France)
	For the last years, we have been discovering the polarisation of the auroral red line both in the cusp (Svalbard) and in the auroral oval (Skibotn). We have proven that its Degree of Linear Polarisation (DoLP) varies accordingly to the geomagnetic activity. In the last 2 winters, two major steps have been achieved, that will be reported in this contribution. - The first one is the calibrated determination of the Angle of Linear Polarisation (AoLP) during a winter at Ny Alesund (Svalbard). We have shown that it moves along the magnetic field, giving for the first time a way to monitor its configuration at distance. When there is no activity, the AoLP is exactly parallel to the magnetic field. - With a new instrument, we have been able for the first time to explore the polarisation of the full auroral spectrum in a dedicated campaign in March 2016. We have discovered that not only the 630 nm red line is polarised, but also another atomic oxygen line and a nitrogen one. These two discoveries open a new window on our space environment. In the next future, we envision a series of instruments in order to develop the polarisation as a new space weather tool and to establish a bridge between the this –till now - fundamental science and operations.
18	Monitoring geomagnetic disturbances: the relevance of temporal and spatial resolution	Guerrero, A et al.	p-Poster
	Antonio Guerrero, Consuelo Cid, Elena Saiz, Judith Palacios and Yolanda Cerrato
	Universidad de Alcalá (UAH), Physics and Mathematics Department, Alcalá de Henares, Spain
	The analysis of local geomagnetic disturbances has recently proved to play an important role in space weather research. Localized strong (high intensity) and impulsive (fast developed and fast recovered) geomagnetic disturbances are typically recorded at high latitudes and commonly related to field-aligned currents. This type of disturbances is also recorded, less frequently, at mid and low latitudes, representing an important hazard for technology. In order to accurately nowcast geomagnetic disturbances by geomagnetic indices, a baseline has to be removed from the records at a certain observatory. The baseline is usually determined taking into account geomagnetic secular variation and solar quiet time. At mid-latitudes the shape of the daily solar quiet component presents a strong day-to-day variability that is difficult to predict. In this work we present a new index able to determine the baseline at mid-latitudes which allows us to obtain a high resolution local geomagnetic index with the highest accuracy ever obtained at mid-latitudes.
19	Results of the application of INGV Oblique Ionograms Automatic Scaling Algorithm to the ionograms recorded by Ebro Observatory ionosonde	Scotto, C et al.	p-Poster
	A. Ippolito[1], C. Scotto[1], D. Altadill[2], E. Blanch[2], D. Sabbagh[1,3], V. Sgrigna[3]
	[1]Istituto Nazionale di geofisica e Vulcanologia, Via di Vigna Murata 605, Rome, ITALY; [2]Observatori de l’Ebre, (OE), CSIC - Universitat Ramon Llull, Roquetes, SPAIN; [3]Università Roma Tre, Dipartimento di matematica e Fisica, Via della Vasca Navale 84, Rome
	An algorithm (OIASA, Oblique Ionograms Automatic Scaling Algorithm) for the identification of trace of oblique ionograms has been developed at the INGV. This algorithm allows the determination of the Maximum Usable Frequency (MUF) for communication between the transmitter and receiver, automatically rejecting poor quality ionograms. A test of the algorithm using data from a campaign of oblique soundings between Dourbes (50.1 N, 4.6 E) and Roquetes (40.8 N, 0.5 E) has been performed. The results of these tests demonstrates that the method can be applied to ionograms recorded by different ionosondes.
20	Ionospheric forecasting tools and services: comparative studies of foF2 and TEC storm-time response for further developments	Tsagouri, I et al.	p-Poster
	Ioanna Tsagouri, Anna Belehaki and Panagiotis Elias
	National Observatory of Athens, Greece
	This paper builds the discussion on a comparative analysis of the variations in the peak electron density at F2 layer and the TEC parameter during a significant number of geomagnetic storm events that occurred in the present solar cycle 24. The ionospheric disturbances are determined through the comparison of actual observations of the foF2 critical frequency and GPS-TEC estimates obtained over European locations with the corresponding median estimates, and they are analysed in conjunction to the solar wind conditions at L1 point that are monitored by the ACE spacecraft. The results are build on superposed epoch analyses to reveal similarities and differences in the occurrence of positive and negative storm effects in the two parameters with respect to the solar wind drivers of the storms, as well as the local time and the latitude of the observation point. The aforementioned dependencies drive the storm-time forecasts of the SWIF model (Solar Wind driven autorgressive model for Ionospheric short-term Forecast), which is operationally implemented in the DIAS system (http://dias.space.noa.gr) and extensively tested in performance at several occasions. In its present version, the model provides alerts and warnings for upcoming ionospheric disturbances, as well as single site and regional forecasts of the foF2 characteristic over Europe up to 24 hours ahead. In that respect, this contribution aims to discuss the potentiality of the expansion of the model's capabilities in forecasting the storm-time TEC variation within an operational environment some hours in advance, building on a solid basis of current achievements.
21	Modelling and monitoring the plasmasphere: towards an operational Space Weather tool - advances in the PLASMON project	Lichtenberger, J et al.	p-Poster
	János Lichtenberger[1,2], Anders Jorgensen[3], Balazs Heilig[4],David Koronczay[1,2], Csaba Ferencz[1], Péter Steinbach[5], Mark Clilverd[6], Craig Rodger[7], Dmitry Sannikov[8] and Nina Cherneva[8]
	[1]Department of Geophysics and Space Sciences, Eötvös University, Budapest, Hungary; [2]Geodetic and Geophysical Institute, RCAES, Sopron, Hungary; [3]Electrical Engineering Department, New Mexico Institute of Mining and Technology, Socorro, NM, USA; [4]Geological and Geophysical Institute of Hungary, Budaoest, Hungary; [5]British Antarctic Survey, Cambridge, United Kingdom; [6]Department of Physics, University of Otago, Dunedin, New Zealand; [7]Institute of Cosmophysical Research and Radio Wave Propagation, Paratunka, Russia
	In the PLASMON FP7-Space project (http://plasmon.elte.hu, Lichtenberger et al., Space Weather Space Clim. 3 2013, A23 DOI: 10.1051/swsc/2013045), we have started to develop a global monitoring system of magnetospheric/plasmaspheric electron and plasma densities complemented by a data assimilative model of the plasmasphere. The plasmasphere model is fed by densities measured by two ground based networks: the global Automatic Whistler Detector and Analyzer Network (AWDANet, Lichtenberger et al., J. Geophys. Res., 113, 2008, A12201, doi:10.1029/2008JA013467) that is able to detect and analyze whistlers in quasi-realtime and provides equatorial electron density data and the European quasi-Meridional Magnetometer Array (EMMA) that provides plasma mass densities retrieved from field line resonances. Other data sources for the data assimilative model includes plasma mass density data from American magnetometer chains and in- situ measurements (LANL GEO satellites, Van Allen Probes). Though the PLASMON project was completed in 2014, the team continue the operation of the ground networks, enhanced both the density retrieval methods and the physical model (Dynamic Global Core Plasma Model, Ober and Horwitz, J. Geophys. Res., 102:14595–14602, 1997) in the data assimilative model. We present the latest results here that are leading towards an operational model.
22	A NeQuick-based topside electron density profile estimation for Autoscala program	Scotto, C et al.	p-Poster
	Carlo Scotto[1], Bruno Nava[2], Loredana Perrone[1], Marco Pietrella[1], Alessandro Ippolito[1], Dario Sabbagh[1,3], Vittorio Sgrigna[3], Anton Kashcheyev[2], Muhammad Mubasshir Shaikh[2], Yenca Migoya Orue’[2], Katy Alazo-Cuartas[2]
	[1]Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy; [2]The Abdus Salam International Centre for Theoretical Physics, Trieste, Italy; [3]Università Roma Tre, Dipartimento di matematica e Fisica, Via della Vasca Navale 84, Rome ITALY
	Autoscala is a software for the automatic interpretation of ionograms that is able to estimate the ionosphere bottomside electron density profile Ne(h), including specific parameters like foF2, M3000. Autoscala has been extensively validated and tested at middle latitudes and has demonstrated satisfactory performance. The parameters given by this inversion software can be used as an input for NeQuick model to obtain a real-time estimate of the topside of Ne(h). In this work, the topside part of the electron density profile used in NeQuick-2 model has been implemented in Autoscala. The collocated Champ satellite radio occultation data have been used to test the topside estimation routine implemented in Autoscala with particular focus on the mid-latitude ionospheric stations. As a first extent, the effectiveness of the NeQuick-derived topside implemented in Autoscala has been evaluated by calculating the integrated value of the absolute difference between radio occultation-derived and the corresponding Autoscala profiles. Subsequently, in order to test the performance in terms of total electron content (TEC) of the NeQuick-based topside implemented in Autoscala, GIM maps have been utilized. In particular, experimental topside TEC values have been computed by subtracting Autoscala bottomside TEC from the GIM TEC values, and then compared to the Autoscala-retrieved topside TEC.
23	Geomagnetically Induced Currents in the Irish Power Network during Geomagnetic Storms	Anon, A et al.	p-Poster
	Sean Blake [1], Peter Gallagher [1], Joseph McCauley [1], Alan Jones [2], Colin Hogg [3], Joan Campanya [3], Ciaran Beggan [4], Alan Thomson [4], Gemma Kelly [4], David Bell [5]
	[1] Trinity College Dublin, Ireland, [2] Complete MT Solutions, Ireland, [3] Dublin Institute for Advanced Studies, Ireland, [4] British Geological Survey, UK, [5] EirGrid Plc, Ireland
	Geomagnetically induced currents are a well-known terrestrial space weather hazard. They occur in power transmission networks and are known to have adverse effects in both high and mid-latitude countries. Here, we study the effects of five geomagnetic storms (06-07 March 2016, 20-21 December 2015, 17-18 March 2015, 29-31 October 2003 and 13-14 March 1989) on the power transmission network in Ireland (geomagnetic latitude 54.7-58.5 degrees N). We simulate electric fields using a plane wave method together with a 200 km deep ground resistivity model derived from magnetotelluric measurements, and calculate GICs in the 220, 275 and 400 kV transmission network. During the largest of the storm periods studied, the peak electric field was calculated to be as large as 3.8 V/km, with associated GICs of up to 23 A using our MT model. Using our homogenous resistivity model, those peak values were 1.46 V/km and 36.4 A. We find that the 400 and 275 kV substations are the most likely locations for the Irish transformers to experience GICs.
24	Modeling Coronal Mass Ejections in the Inner Heliosphere using the Gibson-Low flux rope model with EUHFORIA	Verbeke, C et al.	p-Poster
	C. Verbeke[1], J. Pomoell[2], S. Poedts[1]
	[1] KU Leuven, Belgium, [2] University of Helsinki, Finland
	Coronal mass ejections (CMEs) have a important influence on the coronal and interplanetary dynamics. Understanding their origin and evolution still remains a key goal in current space weather research. In this work, we present our first results from the inclusion of a magnetized flux-rope CME into the recently developed inner heliosphere model EUHFORIA. EUHFORIA (‘EUropean Heliospheric FORecasting Information Asset’) is a three-dimensional physics-based forecasting model of large-scale dynamics in the inner heliosphere covering heliocentric distances from 0.1 AU up to 2 AU and beyond. The magnetohydrodynamics-based modeling methodology is able to capture transient structures in the solar wind such as high speed streams, co-rotating interaction regions as well as shocks driven by coronal mass ejections. A key novel feature is to employ a data-driven flux rope model, based on the Gibson and Low CME model. Magnetic field parameters are determined through non-potential coronal modeling while the kinematics have been constrained by fitting to coronagraph observations. We discuss results of the first magnetized flux-rope simulations as well as a comparison with the currently used CME cone model. Finally, we discuss future horizons for our model.