Search

The solar magnetized corona is responsible for various manifestations with a space weather impact, such as flares, coronal mass ejections (CMEs) and, naturally, the solar wind. Modeling the corona's dynamics and evolution is therefore critical for improving our ability to predict space weather In this work, we demonstrate that generative deep learning methods, such as Denoising Diffusion Probabilistic Models (DDPM), can be successfully applied to simulate future evolutions of the corona as observed in Extreme Ultraviolet (EUV) wavelengths. Our model takes a 12-hour video of an Active Region (AR) as input and simulate the potential evolution of the AR over the subsequent 12 hours, with a time-resolution of two hours. We propose a light UNet backbone architecture adapted to our problem by adding 1D temporal convolutions after each classical 2D spatial ones, and spatio-temporal attention in the bottleneck part. The model not only produce visually realistic outputs but also captures the inherent stochasticity of the system's evolution. Notably, the simulations enable the generation of reliable confidence intervals for key predictive metrics such as the EUV peak flux and fluence of the ARs, paving the way for probabilistic and interpretable space weather forecasting. Future studies will focus on shorter forecasting horizons with increased spatial and temporal resolution, aiming at reducing the uncertainty of the simulations and providing practical applications for space weather forecasting. The code used for this study is available at the following link: https://github.com/gfrancisco20/video_diffusion

We investigate the effect of data-driving on flux rope eruptivity in magnetic field simulations by analysing fully data-driven modelling results of active region (AR) 12473 and AR11176, as well as preforming relaxation runs for AR12473 (found to be eruptive). Here, the driving is switched off systematically at different time steps. We analyse the behaviour of fundamental quantities, essential for understanding the eruptivity of magnetic flux ropes (MFRs). The data-driven simulations are carried out with the time-dependent magnetofrictional model (TMFM) for AR12473 and AR11176. For the relaxation runs, we employ the magnetofrictional method (MFM) and a zero-beta magnetohydrodynamic (MHD) model to investigate how significant the differences between the two relaxation procedures are when started from the same initial conditions. To determine the eruptivity of the MFRs, we calculate characteristic geometric properties, such as the cross-section, MFR height along with stability parameters, such as MFR twist and the decay index. For eruptive cases, we investigate the effect of sustained driving beyond the point of eruptivity on the MFR properties. We find that the fully-driven AR12473 MFR is eruptive while the AR11176 MFR is not. For the relaxation runs, we find that the MFM MFRs are eruptive when the driving is stopped around the flare time or later, while the MHD MFRs show eruptive behaviour even if the driving is switched off one and a half days before the flare occurs. We find that characteristic MFR properties can vary greatly even for the eruptive cases of different relaxation simulations. The results suggest that data driving can significantly influence the evolution of the eruption, with differences appearing even when the relaxation time is set to later stages of the simulation when the MFRs have already entered an eruptive phase., Comment: Accepted for publication at A&A

Solar flare forecasting mainly relies on photospheric magnetograms and associated physical features to predict forthcoming flares. However, it is believed that flare initiation mechanisms often originate in the chromosphere and the lower corona. In this study, we employ deep learning as a purely data-driven approach to compare the predictive capabilities of chromospheric and coronal UV and EUV emissions across different wavelengths with those of photospheric line-of-sight magnetograms. Our findings indicate that individual EUV wavelengths can provide discriminatory power comparable or better to that of line-of-sight magnetograms. Moreover, we identify simple multimodal neural network architectures that consistently outperform single-input models, showing complementarity between the flare precursors that can be extracted from the distinct layers of the solar atmosphere. To mitigate potential biases from known misattributions in Active Region flare catalogs, our models are trained and evaluated using full-disk images and a comprehensive flare event catalog at the full-disk level. We introduce a deep-learning architecture suited for extracting temporal features from full-disk videos.

We present a magnetic flux rope (FR) extraction tool for solar coronal magnetic field modelling data, which builds upon the methodology from Wagner et al. (2023). We apply the scheme to magnetic field simulations of active regions AR12473 and AR11176. We compare the method to its predecessor and study the 3D movement of the newly extracted FRs up to heights of 200 and 300 Mm, respectively. The extraction method is based on the twist parameter and a variety of mathematical morphology algorithms, including the opening transform and the morphological gradient. We highlight the differences between the methods by investigating the circularity of the FRs in the plane we extract from. The simulations for the active regions are carried out with a time-dependent data-driven magnetofrictional model (TMFM; Pomoell et al. (2019)). We investigate the FR trajectories by tracking their apex throughout the full simulation time span. We demonstrate that this upgraded methodology provides the user with more tools and less a-priori assumptions about the FR shape that, in turn, leads to a more accurate set of field lines. The propagation analysis yields that the erupting FR from AR12473 showcases stronger dynamics than the AR11176 FR and a significant deflection during its ascent through the domain. The AR11176 FR appears more stable, though there still is a notable deflection. This confirms that at these low coronal heights, FRs do undergo significant changes in the direction of their propagation even for less dynamic cases. The modelling results are also verified with observations, with AR12473 being indeed dynamic and eruptive, while AR11176 only features an eruption outside of our simulation time window., Comment: Accepted for publication in Astronomy & Astrophysics

Full disc observations of the Sun in the H$\alpha$ line provide information about the solar chromosphere and in particular about the filaments, which are dark and elongated features that lie along magnetic field polarity inversion lines. This makes them important for studies of solar magnetism. Since full disc H$\alpha$ observations have been performed at various sites since 1800s, with regular photographic data having started in the beginning of the 20th century, they are an invaluable source of information on past solar magnetism. In this work we aimed at deriving accurate information about filaments from historical and modern full disc H$\alpha$ observations. We have consistently processed observations from 15 H$\alpha$ archives spanning 1909-2022. Our data processing includes photometric calibration of the data stored on photographic plates. We have constructed also Carrington maps from the calibrated H$\alpha$ images. We find that filament areas are affected by the bandwidth of the observation. Thus, cross-calibration of the filament areas derived from different archives is needed. We have produced a composite of filament areas from individual archives by scaling all of them to the Meudon series. Our composite butterfly diagram shows very distinctly the common features of filament evolution, that is the poleward migration as well as a decrease in the mean latitude of filaments as the cycle progresses. We also find that during activity maxima, filaments on average cover about 1% of the solar surface. We see only a weak change in the amplitude of cycles in filament areas, in contrast to sunspot and plage areas. Analysis of H$\alpha$ data for archives with contemporaneous Ca II K observations allowed us to identify and verify archive inconsistencies, which will also have implications for reconstructions of past solar magnetism and irradiance from Ca II K data., Comment: 21 pages, 14 figures, accepted for publication in A&A

A regression-based model was previously developed to forecast the total electron content (TEC) at middle latitudes. We present a more sophisticated model using neural networks (NN) instead of linear regression. This regional model prototype simulates and forecasts TEC variations in relation to space weather conditions. The development of a prototype consisted of the selection of the best set of predictors, NN architecture and the length of the input series. Tests made using the data from December 2014 to June 2018 show that the PCA-NN model based on a simple feed-forward NN with a very limited number (up to 6) of space weather predictors performs better than the PCA-MRM model that uses up to 27 space weather predictors. The prototype is developed on a TEC series obtained from a GNSS receiver at Lisbon airport and tested on TEC series from three other locations at middle altitudes of the Eastern North Atlantic. Conclusions on the dependence of the forecast quality on longitude and latitude are made., Comment: arXiv admin note: text overlap with arXiv:2201.03477

Studies and reconstructions of past solar activity require data on sunspots as well as faculae/plage and network. Such data are also important for understanding the magnetic activity and variability of the Sun and Sun-like stars. The longest available direct faculae/plage datasets are white-light facular and Ca II K observations going back to 1874 and 1892, respectively. Prior to that time, the only direct data available are for sunspots. We reassess the relationship between plage areas and sunspot records (areas and numbers) since 1892, to allow reconstructions of facular/plage areas which can be employed for studies going further back in time, i.e. over the period when solely sunspot observations are available. We use the plage areas derived from 38 consistently processed Ca II K archives as well as the plage area composite based on these archives. We find the relationship between plage and sunspot areas and numbers to be well represented by a power law function. We further find that the relationships depend on the bandwidth and the solar cycle strength. The reconstructions with a power law relationship are in good agreement with the original plage area series, whereas employment of a cycle-strength-dependent relationship improves the reconstructions only marginally. Performing the same analysis on other previously published plage area series, usually derived from a single archive with diverse processing techniques, returns different results when using different time series. This highlights the importance of applying a consistent processing to the various archives and demonstrates the uncertainties introduced by using previously published series. Our results have implications for past solar activity and irradiance reconstructions as well as for stellar activity studies, which sometimes assume a linear dependence between plage and sunspot areas., Comment: 22 pages, 13 figures, accepted for publication in Astronomy & Astrophysics

The total electron content (TEC) over the Iberian Peninsula was modelled using PCA-MRM models based on decomposition of the observed TEC series using the principal component analysis (PCA) and reconstruction of the daily modes amplitudes by a multiple linear regression model (MRM) using space weather parameters as regressors. The following space weather parameters are used: proxies for the solar UV and XR fluxes, number of the solar flares of different classes, parameters of the solar wind and of the interplanetary magnetic field, and geomagnetic indices. Time lags of 1 and 2 days between the TEC and space weather parameters are used. The performance of the PCA-MRM model is tested using data for 2015, both geomagnetically quiet and disturbed periods. The model performs well for quiet days and days with solar flares but without geomagnetic disturbances. The MAE and RMSE metrics are of the order of 3-3.5 TECu for daytime and about 2 TECu for night-time. During geomagnetically disturbed periods the performance of the model deteriorates but only for daytime: MAE and RMSE are of the order of 4.5-5.8 TECu and can rise to about 13 TECu for the strongest geomagnetic storms., Comment: 5 figures, 12 tables, Supplementary Materials

The present work aims to validate the positions of solar filaments published in the Annals of Coimbra University Astronomical Observatory, currently the Geophysical and Astronomical Observatory of the University of Coimbra, corresponding to years 1929 to 1941. The published Stonyhurst positions were obtained by an original method devised in the early 20th century that used a spherical calculator instrument, a wood-made model of the sun. We used the digital images of the original spectroheliograms to measure the positions of the filaments, and heliographic coordinates were determinate with the routines implemented on python package Sunpy. The correlation coefficients between both sets of coordinates are positive and highly significant. The results validate the method used at the Coimbra observatory and the data published. We conclude that Coimbra solar filaments catalogues are reliable and can therefore be considered for future solar activity studies., Comment: 19 pages, 10 figures, Accepted for publication on Solar Physics

We derive the plage area evolution over the last 12 solar cycles employing data from all Ca II K archives available publicly in digital form known to us, including several as yet unexplored Ca II K archives. We analyse more than 290,000 full-disc Ca II K observations from 43 datasets spanning the period 1892-2019. All images were consistently processed with an automatic procedure that performs the photometric calibration (if needed) and the limb-darkening compensation. The processing also accounts for artefacts plaguing many of the images, including some very specific artefacts such as bright arcs found in Kyoto and Yerkes data. We have produced a plage area time-series from each analysed dataset. We found that the differences between the plage areas derived from individual archives are mainly due to the differences in the central wavelength and the bandpass used to acquire the data at the various sites. We have empirically cross-calibrated and combined the results obtained from each dataset to produce a composite series of plage areas. "Backbone" series are used to bridge all the series together. We have also shown that the selection of the backbone series has little effect on the final plage area composite. We have quantified the uncertainty of determining the plage areas with our processing due to shifts in the central wavelength and found it to be less than 0.01 in fraction of the solar disc for the average conditions found on historical data. We also found the variable seeing conditions during the observations to slightly increase the plage areas during activity maxima. We provide the so far most complete time series of plage areas based on corrected and calibrated historical and modern Ca II K images. Consistent plage areas are now available on 88% of all days from 1892 onwards and on 98% from 1907 onwards., Comment: 23 pages, 19 figures, accepted for publication in A&A

Here we present datasets provided by a SCINDA GNSS receiver installed in the Lisbon airport area from November of 2014 to July of 2019. The installed equipment is a NovAtel EURO4 with a JAVAD Choke-Ring antenna. The data are in an archived format and include the general messages on quality of records (*.msg), RANGE files (*.rng), raw observables as the signal-to-noise (S/N) ratios, pseudoranges and phases (*.obs), receiver position information (*.psn), ionosphere scintillations monitor (ISMRB; *.ism) and ionospheric parameters: total electron content (TEC), rate of change of TEC index (ROTI), and the scintillation index S4 (*.scn). The presented data cover the full 2015 year. The raw data are of 1-minute resolution and available for each of the receiver-satellite pairs. The processing and the analysis of the ionosphere scintillation datasets can be done using a specific "SCINDA-Iono" toolbox for the MATLAB developed by T. Barlyaeva (2019) and available online via MathWorks File Exchange system. The toolbox calculates 1-hour means for ionospheric parameters for each of the available receiver-satellite pairs and averaged over all available satellites during the analyzed hour. Here we present the processed data for the following months in 2015: March, June, October, and December. The months were selected as containing most significant geomagnetic events of 2015. The 1-hour means for other months can be obtained from the raw data using the aforementioned toolbox. The provided datasets are interesting for the GNSS and ionosphere based scientific communities., Comment: arXiv admin note: text overlap with arXiv:1910.04044

The total ionospheric content (TEC) over the Iberian Peninsula was studied using data from two locations obtained both by GNSS receivers and an ionosonde. The principal component analysis applied to the TEC data allowed us to extract two main modes. Each mode is characterized by daily TEC variation of a certain type (PC) and its amplitude for each of the studied day (given by the empirical orthogonal functions, EOF). The variations of these modes as well as the original TEC data were studied in relations to four strongest geomagnetic storms of 2015 and three geomagnetic disturbances of lower amplitude observed during the same months. EOFs were found to correlate well with space weather parameters characterizing solar UV and XR fluxes, number of the solar flares, parameters of the solar wind and geomagnetic indices. Multiple regression models were constructed to fit EOFs using combinations of the space weather parameters with a lag from 0 to 2 days. Combining the regression models of EOFs with the corresponding PCs we reconstructed TEC variations as a function of space weather parameters observed in previous days. The possibility to use such reconstructions for the TEC forecasting was also studied., Comment: 7 figures, 3 tables

Here we present a "SCINDA-Iono" toolbox for the MATLAB. This is a software to analyze ionosphere scintillation indices provided by a SCINDA GNSS receiver. The toolbox is developed in the MATLAB R2018b. This software allows to preprocess the original data and analyze ionosphere scintillations on the 1-minute and 1-hour time scales both for averaged over all available satellites values and separately for each receiver-satellite pair., Comment: 11 pages, 7 figures