A constellation of spacecraft located between 0.4 and 1AU currently provides in-situ measurements of the solar wind (STEREO, ACE, Wind, Venus Express, Messenger). These measurements are complemented with unprecedented remote-sensing observations of the Sun and the solar wind from the photosphere to 1AU (SDO, STEREO, SMEI). They permit accurate and comprehensive monitoring of the evolution of Coronal Mass Ejections (CMEs) and the background solar wind from the Sun to 1AU. We can now track the formation and longitudinal/latitudinal structure of Corotating Interaction Regions (CIRs) as high-speed streams from coronal holes sweep up the small (blobs) and large (CMEs) disturbances that are continually released in the slow solar wind. These combined white-light and in-situ observations have provided clues on the nature and likely origin of one source of variability of the slow solar wind. We can now also observe the formation of coronal and heliospheric shocks in extreme ultraviolet light and in white-light images, track their evolution in the interplanetary medium and, by combining these observations with numerical models and in-situ measurements, derive the expected shock properties (geometry, compression ratio,...) in the lower and upper corona. We can now compare/interpret the timing and spectral properties of solar energetic particle events in terms of (inferred) basic shock parameters with more confidence. Despite all these major advances, many puzzles still remain unanswered such as the exact nature of the mechanisms accelerating particles to high energy or heating the background solar wind. To answer these fundamental questions, a new constellation of missions armed with exceptional instrumentation will be launched over the next decade. They will return to the inner heliosphere and enter yet unexplored regions of the solar atmosphere well inside 20 solar radii. We will argue that, based on the instrumental design and orbital characteristics of these future missions and especially the synergy between these missions, they will provide the critical information necessary to discriminate between the various theories of solar wind acceleration and energetic particle acceleration. We will also present the new tools currently being developped, as a synergy between data centers, to facilitate comparisons of imagery and in situ datasets taken by Solar Orbiter and Solar Probe +.

Magnetohydrodynamic (MHD) simulations are now routinely used to produce models of the solar corona and inner heliosphere for specific time periods. These models typically use magnetic maps of the photospheric magnetic field built up over a solar rotation, available from a number of ground-based and space-based solar observatories. Two well-known problems arise from the use of these "synoptic" maps. First, the synoptic maps contain data that is as much as 27 days old. The Sun's magnetic flux is always evolving, and these changes in the flux affect coronal and heliospheric structure. Second, the line-of-sight field at the Sun's poles is poorly observed, and the polar fields in these maps are filled with a variety of interpolation/extrapolation techniques. Flux evolution models can in principle alleviate both these difficulties. They can estimate the likely state of the photospheric magnetic field on unobserved portions of the Sun. By augmenting Earth-based observations with Solar Orbiter observations from other vantage points in the heliosphere, sequences of "synchronic" maps can be developed that can drive time-dependent models of the corona and solar wind. The Air Force Data Assimilative Photospheric flux Transport (ADAPT) model (Arge et al. 2010), which incorporates data assimilation techniques into the Worden and Harvey (2000) flux evolution model, is especially well-suited for this purpose. Flux evolution models like ADAPT can also provide physical approximations for the polar fields that may be more accurate than the extrapolations presently used. In the later phases of the mission, out-of-the ecliptic observations from Solar Orbiter will allow testing of the model's predictions for the polar fields and a better understanding of the overall flux evolution process. Research supported by AFOSR, NASA, and NSF.

We present a new method for estimating the column mass (the mass contained within a pixel) of non-fully ionised hydrogen and helium (H I, He I and He II) using the properties of the bound-free photo-absorption cross section at multiple wavelengths. Until now, such estimates have not been reliable with imaging-only techniques, but the near-simultaneity of the images taken by the Solar Dynamics Observatory Advanced Imaging Assembly means that we can now estimate the opacity due to erupting filament material that passes through a previously unobscured patch of Sun. To test this idea, we use data from the spectacular filament eruption that was seen on 2011 June 07, when visual inspection of the erupting material indicated that the material returning to the Sun’s surface was highly opaque. The best-fit maps column density and filling factor reveal both high hydrogen column densities in the centre of this test blob, in line with the higher end of measurements previously made, and suggest that the filling factor of this material approaches unity. The technique converges quickly and we plan to extend it to measuring both the full filament mass and the mass of non-erupting filaments on the Sun.

Dust particles are ubiquitous in the interplanetary medium. Their properties (chemical composition, mass distribution, flux) are widely studied at an astronomical unit from the Sun and further away from the Sun (in particular in the vicinity of the giant planets). But these properties are poorly known closer to the Sun, since the only Helios mission performed in-situ dust measurements in the inner Solar system. Recently, a method has been developped to measure in-situ dust fluxes with radio instruments. Similarly to classical dust detector, this method is based on the impact ionization phenomena occurring during a high-velocity dust impacts a solid target. The electric charges generated during an impact on the spacecraft produce an electric field that can be detected by the radio antennas of the spacecraft. A modelization of this phenomena makes possible to link the amplitude of the observed voltage pulse to the mass of the impinging dust grain. Here I will expose the method and the results of its application to the S/WAVES data onboard the STEREO spacecraft. Then I will discuss the possibility of its application to the Solar Orbiter mission.

Forecasting of major solar flares, that are most commonly associated with fast, wide-angle coronal mass ejections, is of central importance to the evolving discipline of space weather forecasting. Over the last decade, solar-flare forecasting has witnessed notable progress, with the arguable highlight being that prediction is more efficient when measures of morphological magnetic complexity are employed, either independently or in groups through combinatorial metrics. On the other hand, multiscaling (multifractal) measures are not as efficient flare predictors. Key questions that remain to be answered are, first, which complexity parameters, or set of parameters, are more efficient predictors and, second, whether flare forecasting will remain inherently probabilistic over a prediction window, rather than achieving more definitive, "meteorological" predictions.

The envisioned contribution of Solar Orbiter (SolO) data to securing progress made and to tackling existing challenges in flare forecasting will be discussed in detail. SolO's full-disk imaging vector magnetograph (PHI) will enable detailed processing of all Earth-facing solar active regions at once. This goal will be further assisted by SolO's EUV and X-ray imagers, EUI and STIX, respectively. Equally importantly, SolO's variable heliocentric distance should enable fine-tuning, or "calibration", of flare-prediction parameters that often depend on the spatial resolution of the observing instrument, among other factors. This will help produce "universal" statistics for important prediction parameters at a reference heliocentric distance that will be largely insensitive to the observing instrument and will contribute to standardizing both flare prediction and the associated performance metrics.

The next generation of heliophysics missions, Solar Orbiter and Solar Probe Plus, will focus on exploring the linkage between the Sun and the heliosphere. These new missions will collect unique data that will allow us to study the coupling between macroscopic physical processes to those on kinetic scales, the generation of solar energetic particles and their propagation into the heliosphere and the origin and acceleration of solar wind plasma. Within a few years, the scientific community will have access to petabytes of multi-dimensional remote-sensing and complex in-situ observations from different vantage points, complemented by petabytes of simulation data. Answering overarching science questions like'How do solar transients drive heliospheric variability? ' will only be possible if the community has the necessary tools at hand. As of today, there is an obvious lack of capability to both visualize these data and assimilate them into sophisticated models to advance our knowledge.

A key piece needed to bridge the gap between observables, derived quantities like vector fields and model output is a tool to routinely and intuitively visualize 3D time-dependent data. While a few tools exist to visualize 3D data sets for a small number of time steps, the scientific community is lacking the equipment to do this (i) on a routine basis, (ii) for complex multi-dimensional data sets from various instruments and vantage points and (iii) in an extensible and modular way that is open for future improvements and interdisciplinary usage.

In this contribution, we will present recent progress in visualizing the Sun and its magnetic field in 3D using the open source JHelioviewer framework, which is part of the ESA/NASA Helioviewer Project. In addition, we will show new results from the application of methods from volume rendering and flow visualization to 3D solar magnetic fields, as well as the interactive browsing of time-dependent image data and 1D time series.

Heliophysics is a new research field that explores the Sun-Solar System Connection. It requires the joint exploitation of solar, heliospheric, magnetospheric and ionospheric observations from a variety of ground- and space-based instruments. The Heliophysics Integrated Observatory (HELIO) is a key component of a worldwide effort to integrate heliophysics data and is coordinating closely with international organizations to exploit synergies with complementary domains. Here, we use HELIO to study i) a coronal mass ejection that intersect both Earth and Mars, ii) a solar energetic particle event that crosses the orbit of Earth, and iii) a high-speed solar wind stream produced by a coronal hole that is observed in situ at Earth. Tools such as HELIO will be essential to the interpretation of data from Solar Orbiter, in conjunction with data from a multitude of other instruments distributed across the Solar System.

Solar Orbiter, being a deep space mission, has a very restricted telemetry rate that makes on-board data compression a necessity to achieve the mission's science goals. Missions like the Solar Dynamics Observatory and future ground-based telescopes as the ATST, on the other hand, face the challenge of making petabyte-sized solar data archives accessible to the solar community. New compression standards such as JPEG2000 make this possible by providing efficient, highly flexible and selective compression schemes adaptable to user requirements. In this study we analyze solar images from Hinode and SDO with the aim to optimize the compression bit rates for solar images with respect to the science content of the data. We employ several methods as quality measures for the compressed images and determine moreover their suitability in assessing solar image quality for different purposes (e.g. science quality vs. browse quality). The structural similarity index (SSIM), for example, is a quality measure optimized for the human eye conception and was chosen as a large part of solar research still relies on the visual inspection of solar data and manual event selection as a first step. In addition, we perform tests to validate the scientific use of the compressed images by applying feature identification and tracking algorithms and analysis methods such as Fourier power spectrum analysis. We present the determined bit rates for the various cases that result in no significant loss to the scientific output.

Solar Orbiter's (SO) projected archive will be blissfully small compared with current solar observatories such as SDO and soon ATST. Access to the data can easily be provided by a few redundant on-line archives, with the redundancy only needed to guarantee the data's survival. Because of the nature of SO's instruments much of the scientific research will be focused on space weather events, and that requires easy and instantaneous access to the heterogeneous data from various SO instruments, as well as to the data from other simultaneous missions. A data access mechanism much like the Virtual Solar Observatory will be well suited for that. But there is much more to SO than the analysis of space weather events: SO will also study the internal motions in the convection zone, and, from its unique vantage point, magnetic flux transport near the poles. Automated magnetic feature tracking codes, such as the ones developed for SDO by the Feature Finding Team, can be adapted to carry out that task without a problem, and the data volume will be easily dealt with after analyzing HMI data. In my presentation I will review current data and metadata access methods, as well as already existing feature finding modules, such a SWAMIS. Five years down the road that software may have been long superseded by much better modules, so there is no need for SO to commit to any methodology now. However, it is clear that with what is already in existence SO data can be accessed and analyzed with ease, as long as the data system architecture is conducive to that.