### Session 4 - Data-driven modeling of solar atmosphere and solar explosive events

Conveners: Meng Jin (LMSAL), Véronique Delouille (ROB)
Wednesday 31/10, 09:00 - 11:30

We have witnessed rapid increase in solar data especially in the SDO era, which is not only utilized for extensive model validation, but also dramatically facilitates the development of data-driven models across multiple scales and different domains. This session welcomes presentations of all kinds of data-driven modeling efforts to understand the dynamics of the solar atmosphere from convection zone into the heliosphere and the ideas/discussions of the current challenges of data-driven models. In particular, we encourage modeling results which are directly relevant to the forthcoming solar and heliosphere missions (e.g., Parker Solar Probe and Solar Orbiter).

Plenary speaker: Maria Kazachenko (SSL/Berkeley)

### Talks

Wednesday October 31, 09:00 - 10:30
 09:00 Data-driven Models of the Solar Corona Magnetic Fields: Review Kazachenko, M Invited Oral Maria Kazachenko UC Berkeley, CU Boulder, National Solar Observatory The advent of high-cadence, large-scale photospheric vector magnetic field and Doppler velocity measurements from the Solar Dynamics Observatory and progress in the computational techniques facilitated development of the time-dependent data-driven models of the coronal magnetic fields. In this talk I will first review current state and challenges of these models. I will then describe recent progress of the Coronal Global Evolutionary Model (CGEM), a collaborative effort between UC Berkeley, Lockheed Martin and Stanford University that computes electric fields in the photosphere to drive a 3D non-potential model of the solar corona magnetic fields. 09:30 Ellerman bombs and UV bursts: reconnection at different atmospheric layers? Hansteen, V Oral Viggo Hansteen Rosseland Centre for Solar Physics, University of Oslo The emergence of magnetic flux through the photosphere and into the outer solar atmosphere produces, amongst many other phenomena, the appearance of Ellerman bombs (EBs) in the photosphere. EBs are observed in the wings of H(alpha) and are highly likely to be due to reconnection in the photosphere, below the chromospheric canopy. But signs of the reconnection process are also observed in several other spectral lines, typical of the chromosphere or transition region. An example are the UV bursts observed in the transition region lines of Si IV. In this work we analyze high cadence coordinated observations between the 1-m Swedish Solar Telescope and the IRIS spacecraft in order to study the possible relationship between reconnection events at different layers in the atmosphere, and in particular, the timing history between them. High cadence, high resolution H-alpha images from the SST provide us with the positions, timings and trajectories of Ellerman bombs in an emerging flux region. Simultaneous co-aligned IRIS slit-jaw images at 1400 and 1330 A and detailed Si IV spectra from the fast spectrograph raster allow us to study the possible transition region counterparts of those photospheric Ellerman bombs. We complement these observations with numerical models of Ellerman bombs and UV bursts. Our main goal is to study whether there is a temporal and spatial relationship between the appearance of an EB and the appearance of a UV burst. 09:45 The role of small-scale photospheric motions in coronal magnetic energy buildup and explosive release Dahlin, J Oral Joel Dahlin [1][2],Spiro Antiochos [1],C. Richard DeVore [1] [1]NASA GSFC [2]UCAR CMEs/eruptive flares are spectacular examples of explosive solar activity resulting from magnetic self-organization in the corona. Recent theory and modeling studies have demonstrated a mechanism by which small-scale stochastic flows (e.g., photospheric convection) trigger an inverse cascade that concentrates coronal magnetic structure at polarity inversion lines to form highly sheared filament channels. We report on new 3D MHD simulations of an eruptive flare driven by this process of ‘helicity condensation’. Energy buildup occurs in the form of a sheared arcade that explosively erupts via magnetic breakout. Interestingly, the magnetic shear above the PIL undergoes a three-phase evolution: an initial increase in response to the driving followed by a decrease as the magnetic structure expands outward, concluding with a sharp increase upon the onset of flare reconnection and fast downflows. We discuss implications of our results for SDO observations of CMEs/eruptive flares. Our simulations are especially relevant to the many SDO observations of eruptions from circular filament channels. We also discuss future opportunities for data-driven modeling of the magnetic energy build up leading to explosive solar activity, and for possible application to space weather prediction. This work was supported by the NASA LWS, H-SR and ISFM programs. 10:00 Energy transport and heating by torsional Alfven waves in the quiet-Sun atmosphere Soler, R Oral Roberto Soler[1], Jaume Terradas[1], Ramon Oliver[1], Jose Luis Ballester[1] [1]University of the Balearic Islands High-resolution observations with instruments on board SDO have revealed the ubiquitous presence of Alfv\'en waves in the solar atmosphere. These waves are believed to play an important role in the transfer of energy from the photosphere to the overlying corona and solar wind, and in the heating of the partially ionized chromosphere. Here we perform numerical computations to investigate the energy transport and dissipation associated to torsional Alfv\'en waves propagating in magnetic flux tubes that expand from the photosphere to the corona in quiet-Sun conditions. We place a broadband driver at the photosphere that contains a spectrum of frequencies ranging from 0.1 mHz to 300 mHz and injects a wave energy flux of $10^7$~erg~cm$^{-2}$~s$^{-1}$. We consider Ohm's magnetic diffusion and ion-neutral collisions as dissipation mechanisms in the chromosphere. We find that only a small fraction of the driven flux, $\sim 10^5$~erg~cm$^{-2}$~s$^{-1}$, is able to reach coronal heights, but it may be sufficient to partly compensate the total coronal energy loss. The reason for the small energy transmittance is the combined effect of reflection and dissipation. Low wave frequencies are reflected at the transition region, while high wave frequencies are dissipated producing an efficient enough heating to balance chromospheric radiative losses. 10:15 Simulation of dynamics of hot plasma in postflare loops Shestov, S Oral Sergei Shestov[1,2], Andrei Zhukov[1,3], Tom Van Doorsselaere[4] [1]Solar-Terrestrial Centre of Excellence - SIDC, Royal Observatory of Belgium, Brussels, Belgium; [2]Lebedev Physical Institute, Moscow, Russia; [3] Skobeltsyn Institute of Nuclear Physics, Moscow State University, Moscow, Russia; [4] Centre for Mathematical Plasma Astrophysics (CmPA), KU Leuven, Leuven, Belgium We investigate dynamics of hot plasma in postflare coronal loops using state of the art MHD modeling and calculating synthetic images/fluxes in various SDO channels and other spectral bands – GOES and Mg XII 8.42 A spectral line. Our aim is to investigate dynamics of evaporation and condensation/draining of hot plasma in postflare loops. We use 2D and 3D MHD simulations, start with loop-like initial magnetic field and realistic plasma parameters. For the solving of MHD equations we use MPI-AMRVAC code with gravity, thermal conduction and radiative loses. We apply arbitrary heating in the chromosphere which mimic chromospheric heating by the energetic electrons from the reconnection region. The plasma starts to evaporate and soon fills the overlying magnetic loop system. The particular observed characteristics –, temperature, density, flow, and their dynamics strongly depend on applied physical condition. In particular, strength of magnetic field plays important role, as well as heating rate and the size of the heated region. To constrain the possible range of parameters we calculate synthetic images/fluxes in various EUV and X-ray channels with the use of FoMo code. We compare calculated images with observational data (we chose one large-scale and one small-scale loop associated with ~B-class flares) and identify the most probable physical conditions, in which synthetic data match observations. We were able to find heating regimes to match the observations; beside we see several interesting features that can be revealed only in 2D or 3D modeling.

Wednesday October 31, 11:00 - 11:30
 11:00 Variation of Doppler velocity with non-thermal line width in a gravitationally stratified plasma Pant, V Oral Vaibhav Pant[1], Norbert Magyar[1], Tom Van Doorsselaere[1], Richard Morton[2] [1]Centre for mathematical Plasma Astrophysics (CmPA), KU Leuven, [2]Northumbria University Magnetohydrodynamic (MHD) waves are ubiquitous in the solar atmosphere. These waves play an important role in the heating of solar corona. Recently, an apparent discrepancy is observed in the Alfvénic wave amplitudes measured by the Coronal Multi-channel Polarimeter (CoMP) compared to those measured by the Hinode and the Solar Dynamics Observatory (SDO). This discrepancy was attributed to a large line-of-sight superposition and low spatial resolution of the CoMP, which may lead to low wave amplitudes and large non-thermal line widths. A wedge-shape correlation is also observed between root mean square Doppler velocity and mean non-thermal line width. We investigate this scenario by performing a 3D MHD simulation of a gravitationally stratified transversely inhomogenous plasma subjected to the unidirectionally propagating MHD waves. Here, we present the results of this simulation forward modelled with the FoMo for Fe XIII (10747~\AA) emission line to study the variation of Doppler velocities with non-thermal line widths. We perform the random integration over different line-of-sights angles across and along the simulation box. We degrade the spatial resolution of the simulation box to the spatial resolution of the CoMP and compare Doppler velocities and non-thermal line widths at different heights. We compare our results with previous studies as well as with observations made by the CoMP and find a fairly good match between them. 11:15 Understanding Heating Properties of Active Region Loops through Forward Modeling and Machine Learning Barnes, W Oral Will Barnes[1], Stephen Bradshaw[1], Nicki Viall[2], Stuart Mumford[3] [1]Rice University, [2]NASA Goddard Space Flight Center, [3]University of Sheffield Understanding how loops in active regions are heated is a critical step in solving the coronal heating problem. In particular, constraining the frequency at which individual strands are reenergized can shed light on what mechanism releases energy from the highly-stressed magnetic field into the coronal plasma (Klimchuk, 2015). To address this problem, we forward model time-dependent AIA intensity maps for active region NOAA 1158 using a combination of loop hydrodynamics (Bradshaw & Cargill, 2013), potential field extraplations derived from HMI magnetograms, and detailed atomic physics. We model the AIA intensity for a range of heating frequencies and constrain the total energy input based on both observed active region flux and the magnetic field strengths derived from the field extrapolation. We then apply the timelag method of Viall & Klimchuk (2012) to compute cross-correlations for all possible channel pairs for every pixel in our synthesized active region. For a given channel pair, the delay which maximizes the cross-correlation provides a proxy for the cooling time between the two channels in a given pixel. We apply this same technique to twelve hours of AIA observations of NOAA 1158. To make meaningful comparisons between our synthetic and observed data, we train a random forest classifier on the synthesized timelags and apply it to our observed timelags in order to classify the heating frequency in each pixel of the active region. This approach allows us to easily and efficiently incorporate every channel pair in deciding which heating model is most consistent with our observed timelags in the context of our model. We also compute emission measure distributions from our modeled and observed intensities using the method of Hannah & Kontar (2012), as any successful heating model should be able to reproduce multiple observational signatures. Furthermore, we apply this analysis to several more active regions from the catalog compiled by Warren et al. (2012). In order to efficiently analyze this large time-dependent, multi-wavelength data, we use the Dask Python library (Dask Development Team, 2016) for out-of-core data processing in order to take advantage of multiple computing cores when preparing and analyzing the data. Such an approach provides a pipeline for processing a many hours of full-disk, level 1 images into a series of timelag maps in a matter of a few hours. This novel combination of distributed and parallel data processing, detailed forward modeling, and machine learning allows us to survey active region heating properties at an unprecedented scale.