Solar flares can have devastating impacts on our daily life; therefore it is very important to develop an accurate flare prediction system that can help us to take preventative measures to mitigate flare impacts. In this work we developed a flare prediction system based on active region properties. 21 active region properties generated by SMART (Solar Monitor Active Region Tracking) system at Trinity College Dublin are used for determining their relations to flaring. Active regions for solar cycle 23 are associated with solar flares that were occurred during the same time period. Machine learning methods, developed at the University of Bradford, are applied on the associated data to investigate flare prediction performance of extracted property set. The initial results shows very high flare prediction performance in general and when compared to our previous Automated Solar Activity Prediction (ASAP) tool. These results will indicate the active region properties that are most significant to flare occurrence and therefore will help us to develop an better automated flare prediction system.

The main objectives of the ESA Solar Energetic Particle Environment Modelling (SEPEM) project have been to create new engineering models and tools to address current and future needs, as well as simulate past events and future scenarios. Both statistical and physical modelling techniques have been addressed, covering SEP environments ranging from 0.2AU to 1.7AU. Essential supporting elements also developed within the framework of SEPEM have been the creation of a standard solar energetic particle dataset and a user-friendly webserver with access to the models being developed under this project and a number of industry standards. SEPEM moves beyond mission integrated fluence statistics to peak flux statistics and durations of high flux periods. Furthermore SEPEM has integrated effects tools to allow calculation of single event upset rate and radiation background for a variety of engineering scenarios. In this paper we highlight the models that have been developed during the SEPEM project. The full release of the SEPEM application server is taking place during ESWW7 and will be presented during the splinter meeting.

The transition of space weather models or of information derived from space weather models to space weather forecasting is the last step of the chain from model development to model deployment in forecasting operations. As such, it is an extremely important element of the quest to increase our ability to forecast and mitigate space weather hazards. It involves establishing customer requirements, and analyses of available models, which are, in principle, capable of delivering the required product. Models will have to be verified and validated prior to a selection of the best performing model, accounting for the short model development time scale in the rapidly evolving field. Further considerations include operational hardware, and the evolving availability of data streams to drive the model. The final steps include the education of forecasters and customers. This presentation will provide a discussion of experiences and opportunities for rapid progress from the viewpoint of the Space Weather Laboratory.

Data Assimilation through Kalman filtering [1,2] is a powerful statistical tool which allows to combine modeling and observations to increase the degree of knowledge of a given system. We apply this technique to the forecast of solar wind parameters (proton speed, proton temperature, absolute value of the magnetic field and proton density) at 1 AU, using the model described in Ref. [3] and ACE data as observations. The model, which relies on GOES 12 observations of the percentage of the meridional slice of the sun covered by coronal holes, grants 1-day and 6-hours in advance forecasts of the aforementioned quantities in quiet times (CMEs are not taken into account) during the declining phase of the solar cycle and is tailored for specific time intervals. We show that the application of data assimilation generally improves the quality of the forecasts during quiet times and, more notably, extends the periods of applicability of the model, which can now provide reliable forecasts also in presence of CMEs and for periods other than the ones it was designed for.
[1] R. Kalman, J. Basic Eng. 82, 35 (1960).
[2] G. Welch and G. Bishop, Technical Report TR 95-041, University of North Carolina, Department of Computer Science (2001).

The research leading to these results has received funding from the European Commission's Seventh Framework Programme (FP7/2007-2013) under the grant agreement SOTERIA (project n° 218816, www.soteria-space.eu).
[3] B. Vrsnak, M. Temmer, and A. Veronig, Solar Phys. 240, 315 (2007).

The solar electromagnetic emission (the solar irradiance) is the main source of energy for the ionized and neutral components of the highly coupled atmospheric/oceanic system. Its variability determines the structure and evolution of this system on time-scales ranging from days to millennia. In this way, the real-time monitoring of the solar electromagnetic emission is fundamental for weather and space weather prediction models. Space-based instruments on board of spacecrafts during the last decades have allowed quantitative investigations of the variability of the total and spectral irradiance. However, the systematic monitoring of the solar irradiance employing space-based instruments requires complex calibrations through the lifetime of the instruments/spacecrafts that limits the assessment of long-term trends of the solar irradiance. For the period prior to direct observations, several models based on the physical and statistical relationships between solar irradiance and other solar parameters have been developed. These models are based on the assumption that the evolution of the solar irradiance is determined by the magnetic structure of the solar atmosphere. These concepts can be employed to produce near-real-time reconstructions of the solar irradiance. Here we present a procedure to compute the evolution of the solar total and spectral irradiance based on solar disk magnetograms employing a neural network model. In this work, we employ full disk magnetograms from the MDI and HMI instruments on board of the SOHO and SDO spacecrafts, respectively. The preliminary results, uncertainties and operational issues are discussed in details.

At low- to mid-latitudes the Earth's magnetic field usually shields the upper atmosphere and spacecraft in low Earth orbit from solar energetic particles (SEPs). During severe geomagnetic storms distortion of the Earth's field suppresses geomagnetic shielding giving SEPs access to Earth's mid-latitudes. Significant variations in geomagnetic shielding can occur on timescales of an hour or less in response to changes in solar wind dynamic pressure and interplanetary magnetic field. Magnetic shielding of energetic ions is quantified in terms of cutoff rigidity. Cutoff rigidities computed in a geomagnetic field model can be used to obtain an estimate of SEP and cosmic ray fluxes in the Earth's upper atmosphere from observed or modeled interplanetary spectra. The Center for Integrated Space Weather Modeling (CISM)-Dartmouth geomagnetic cutoff model is being used in conjunction with the High Energy and Charge Transport code (HZETRN) at the NASA/Langley research center to develop a real-time data-driven model of radiation exposure at commercial airline altitudes. The geomagnetic cutoff model provides a dynamic outer boundary condition for the HZETRN atmospheric transport code. Two advancements in recent years that have made a real-time global cutoff calculation a possibility are (1) increased computer power, and (2) the development of accurate dynamic geomagnetic field models that respond to changes in Dst, solar wind dynamic pressure and interplanetary magnetic field. A numerical model capable of a real time geomagnetic cutoff prediction will be presented along with some initial results.

The Solar Shield project was a collaborative effort between the Electric Power Research Institute (EPRI) and NASA Goddard Space Flight Center (GFSC). The central objective of the project that was funded by the NASA Applied Sciences Program was to utilize state-of-the-art space physics models in experimental forecasting of geomagnetically induced currents (GIC) in the North American high-voltage power transmission system. In Solar Shield, an extensive pool of coupled space physics models hosted at the Community Coordinated Modeling Center (CCMC) at NASA GSFC was used. The utilized models propagate information obtained from the remote solar observations to the interplanetary medium, from the interplanetary medium to the Earth's magnetosphere and ionosphere and eventually all the way down to the surface of the Earth and GIC. The two-level forecasting system provides both 2-3 day lead-time and 30-60 minute lead-time forecasts. The Solar Shield final report was provided to the NASA Applied Sciences Program on April 1, 2010.

In this paper, an overview of the Solar Shield project is given. In particular, new advances such as the generation of tailored first-principles-based 2-3 lead-time forecasts and extension of the global MHD-based forecasts to low-latitude locations are discussed. EPRI carried out comprehensive analysis of the economic impacts of large GIC events, which was used to quantify the value of the established forecasting system. Also the economic aspects of the Solar Shield project are briefly discussed. The experimental system has been generating forecasts now for more than two years and the team has accumulated wealth of experience and learned number of important lessons in operating the system. Challenges and future prospects associated with these lessons are discussed.

The Yamal peninsula is located in the Russian Arctic and contains the biggest gas reserves on the planet. Indeed, the GASPROM pipeline Yamal-Europe has an annual capacity of about 33 billion cubic meters of natural gas. The tube operates as a long conductor, has corrosion cathode protection and therefore is able to protect itself against the external influence of induction currents which originate due to ionosphere and magnetosphere currents. External current sources have maximum values in the auroral zone so their influence is most effective in this region. For observation points placed in the middle latitudes such an influence decreases up to 10 times and more. However, during global magnetic storms, when the near-Earth space is occupied by strong magnetosphere currents, the induction effects in middle latitudes will reach values comparable with those in the auroral zone.

In the case of the Yamal peninsula we have the situation when induction currents (telluric currents in the terms of gas personnel) might exceed the regulated cathode currents and lead to extreme corrosion conditions. In the coming decade new pipelines will be constructed from Yamal (Bovanenkovo deposit) to Europe, including the Nord Stream pipeline. The Gasprom-Dobycha-Yamburg company is responsible for the production and transport of gas in the Yamal region, so it plans to take into account all factors which might affect the pipelines. First of all they plan to use magnetometers as control tools for the external influence of magnetic disturbances on the pipelines.

For the proper operation of the pipelines we will need a real-time information system concerning the state of Earth?s magnetic field. Such an initiative is currently under realization and we present here the first results of our work in establishing a warning system based on the magnetometer recordings. We will search for expected conditions which might be considered as those necessary to induce space weather effects on the new built pipelines. In view of the upcoming increase in solar activity in the next decade this work will be invaluable.

As a result of propagation through ionosphere electron density irregularities, transionospheric radio signals may experience amplitude and phase fluctuations. In equatorial regions, these signal fluctuations specially occur during equinoxes, after sunset, and last a few hours. They are more intense in periods of high solar activity. These fluctuations result in signal degradation from VHF up to C band. The corresponding errors are the most prominent errors for Global Navigation Satellite Systems (GNSS).

The signal fluctuations, referred as scintillations, are created by random fluctuations of the medium's refractive index, which are caused by inhomogeneities inside the ionosphere. These inhomogeneities (or bubbles) develop under several deionization instability processes. These processes start after sunset when the sun ionization drops to zero, consequently at nighttime. Several instability processes can be identified leading to the development of bubbles: gradient drift, Rayleigh-Taylor, Kelvin-Helmholtz, gravitational dependency, ... The way they develop depends on the altitude and they give rise to different characteristic dimensions. In addition, the magnetic field plays an important role which results in elongated bubbles in that direction and consequently an anisotropic medium. The medium's drift velocity and its direction are also important parameters to be considered.

This paper presents the basis of a multiple phase screen theoretical model allowing reproducing the signal modifications due to propagation through ionosphere and generating time series at receiver level. The basis of this model is a resolution of the parabolic equation. The ionosphere medium and in particular the fluctuating medium characteristics strongly influences the result. The corresponding data will be presented together with the sensitivity of the results to these characteristics.

Figure below shows two examples of scintillation maps obtained with the model. The left panel is a global map corresponding to vertical observations. It shows the extent of the fluctuating region. The right panel shows a local map of observations from a ground station located in Indonesia. Comparison with measurements which will be presented concurrently shows a very reasonable argument.

Those two examples have been obtained for a monochromatic signal corresponding to L1 GPS frequency. The case of large bandwidth signals will in addition be presented, corresponding either to radar observations or to pulse propagation. The parabolic equation is then written as a second order equation in order to get higher moments of the transmitted signal.

We have developed climate-chemistry-ionosphere model SOCOL which is based on a general circulation model and includes complete representation of the chemistry of neutral and ionized species in the atmosphere from the ground up to the mesopause. To validate the model we have simulated the response of the neutral and charged species in the middle atmosphere to the short-term increase of the solar UV irradiance in January 2004 and severe solar proton events in October-November 2003 and January 2005. The results of the simulations were compared with the available measurements with satellite and ground based instruments. Reasonable agreement of the simulated results with observations confirms the applicability of the model for the nowcasting of the neutral and charged species in the middle atmosphere using the near-real time solar spectral irradiance data. The model functioning in the nowcasting mode will be illustrated using specially designed visualization software. For the demonstration purposes the model will be driven by the real time solar spectral irradiance calculated with solar radiation code COSI using the sun surface magnetic field observed in October-November 2010.