Michal Švanda

Solar superflares of S‐class (>X10 in soft X‐rays) pose extreme space weather hazards, yet their prediction remains a fundamental challenge owing to their rapid and transient natures and the limitations of conventional event‐based forecasts. We introduce for the first time, a probabilistic spatiotemporal framework designed to identify extended epochs and heliographic zones with heightened superflare likelihood, rather than predicting individual events. Our methodology analyzes nearly five decades of Geostationary Operational Environmental Satellites SXR observations (1975–2025) and introduces two novel components: (a) a cross‐Laplacian diagnostic, derived from the butterfly diagrams of sunspot area and SXR flare density, which identifies photosphere‐corona coupling and pinpoints magnetic energy accumulation sites as preferential zones for S‐flare occurrence; and (b) a temporal model based on the coupled phase states of 1.7‐year and 7‐year oscillations, extracted via wavelet analysis and projected forward using a Bayesian Least‐Squares Support Vector Machine method. Integrating these spatial and temporal diagnostics yields a unified forecast, we identify 2025.7–2026.6 and 2027.2–2027.9 years, as the primary high‐probability windows for S‐class flare activity during Solar Cycle 25, corresponding preferentially to latitudinal bands in the southern (S–S) and northern (N–N) hemispheres, respectively. Subsequent windows are projected for Cycle 26. This physics‐informed, probabilistic approach provides a robust strategy for anticipating periods of extreme solar activity by characterizing the inherent patterns of magnetic energy storage and release in the solar atmosphere.

Context. The SDO/HMI instrument provides continuous full-disk observations with a high temporal cadence but moderate spatial resolution. In contrast, Hinode/SOT-SP observes the Sun with high spatial resolution but at a low temporal cadence and within a limited field of view. Aims. This study seeks to enhance SDO/HMI observations by applying deconvolution techniques, specifically to the continuum intensity and full vector magnetic field in a local reference frame. Hinode datum, used as a training set, helps the model improve the resolution of HMI data to a Hinode-like level. Methods. We use deep residual convolutional neural networks trained on HMI-like and SOT-SP observations. The HMI-like observations utilise the SOT-SP observations and the exact HMI point-spread function and noise realisation. Results. The trained model successfully deconvolves both the intensity and the vector magnetic field. The model predictions and SOT-SP observations show the same level of detail. The root mean square difference between the two is 0.02 quiet-Sun level for intensity and between 40 and 45 G for vector magnetic field that is below the disambiguation noise level. Conclusions. Our model effectively addresses disambiguation noise and enables the deconvolution of the full vector magnetic field. Additionally, the modelled deconvolution provides enhanced results compared to the standard HMI pipeline products.

Norway spruce (Picea abies [L.] Karst.) is the most important economic tree species in Central Europe. It has been affected by extensive windstorms and bark beetle disturbances, which have intensified in recent years. Spruce stands are subject to regular reoccurring disturbances with different intensities. This study examines timber harvests in the Czech Republic and the tree-ring series of Norway spruce from six permanent research plots across the country. The timber harvest shows a cyclical connection with the sunspot number, and of these, the percentage of spruce logging shows a substantial link with the sunspot number while the percentage of salvage logging indicates a relation with Total Solar Irradiance (TSI) and seasonal temperature. The seasonal North Atlantic Oscillation (NAO) indicated a link with logging types as well. However, the connection between TSI and SunSpot Number (SSN) with logging types was statistically significant, while the tree rings were more related to seasonal NAO than timber harvests. The tree Ring Width Index (RWI) series shows reduced growth, which precedes the peak in the timber harvests by 1 year. Timber harvests peak one year after minimum RWI, and they coincide with solar minimum years. In summary, average tree ring series reach predominantly their lowest values one year before the solar minimum, coinciding with increased spruce and salvage logging. Conversely, during the solar maximum, harvests are lower, and tree ring series remain relatively stable. In the spectral analysis, tree-ring series and all types of timber harvests show a quasi-11-year cycle. Spruce trees indicate higher tree-ring growth and lower timber harvests during solar maximum compared to solar minimum and this may be associated with specific meteorological conditions that may be affected by solar variability. European forestry is unfamiliar with the effects of the solar cycle; nevertheless, this phenomenon is present in both spruce tree rings and the aggregate of timber harvests. Further research on this issue will be necessary, but it is already apparent that regularly recurring calamities in spruce stands are likely to be reflected in all of Central Europe.

Context. On 2022 May 4, an M5.7 flare erupted in the active region NOAA 13004, which was the target of a coordinated campaign between GREGOR, IRIS, Hinode, and ground-based instruments at the Ondřejov observatory. A flare kernel located at the edge of a pore was co-observed by the IRIS slit and GREGOR HiFI+ imagers. Aims. We investigated the flare continuum enhancement at different wavelength ranges in order to derive the temperature of the chromospheric layer heated during the flare. Methods. All datasets were aligned to IRIS slit-jaw images. We selected a pixel along the IRIS slit where the flare kernel was captured and evaluated multi-wavelength light curves within it. We defined a narrow IRIS near-UV band that comprises only continuum emission. The method, which assumes that the flare continuum enhancement is due to optically thin emission from hydrogen recombination processes, was applied to obtain a lower limit on the temperature in the layer where the continuum enhancement was formed. Results. We determined a lower limit for the temperature and its time evolution in the chromospheric layer heated during the flare in the range of (3–15) ×10³ K. The mean electron density in that layer was estimated to be ∼1 × 10¹³ cm⁻³. Conlcusions. Multi-wavelength flare co-observations are a rich source of diagnostics. Due to the rapidly evolving nature of flares, the sit-and-stare mode is key to achieving a high temporal cadence that allows one to thoroughly analyse the same flare structure.

Context. Helioseismic inversions largely rely on sensitivity kernels, in which 3D spatial functions describe how the changes in the solar interior translate into the change in helioseismic observables. These sensitivity kernels in most cases come from the forward modelling that is used in the most advanced solar models. Aims. We aim to test the sensitivity kernels by comparing their volume integrals with measured values from helioseismic travel times. Methods. By manipulating the tracking rate, we mimicked the additional zonal velocity in the Dopplergram datacubes. These datacubes were then processed by a standard travel-time measurements pipeline. We investigated the dependence of the east-west travel time averaged over a box around the disc centre on the implanted tracking velocity. The slope of this dependence is directly proportional to the total volume integral of the sensitivity kernel that corresponds to the travel-time geometry that is used. Results. The agreement between measurements and models for travel times that are computed with a ridge filtering is very good to acceptable. The dependence we sought to determine indeed resembles a linear function, and its slope agrees with the expected volume integral from the forward-modelled sensitivity kernel. The agreement is poorer for the phase-speed filtered datacubes. The disagreement is particularly strong for the slowest phase speeds (filters td1–td4). For the higher phase speeds, our result indicates that the measured kernel integrals are systematically larger than expected from the forward modelling. We admit our testing procedure may not be appropriate for high phase speeds and higher radial modes.

Context: Helioseismic inversions rely largely on sensitivity kernels, 3-D spatial functions describing how do the changes in the solar interior translate into the changes of helioseismic observables. These sensitivity kernels come in most cases from the forward modelling utilising state-of-the-art solar models. Aims: We aim to test the sensitivity kernels by comparing their volume integrals with measured values from helioseismic travel times. Methods: By manipulating the tracking rate, we mimic the additional zonal velocity present in the Dopplergram datacubes. These datacubes are then processed by a standard travel-time measurements pipeline. We investigate the dependence of the east--west travel time averaged over a box around the disc centre on the implanted tracking velocity. The slope of this dependence is directly proportional to the total volume integral of the sensitivity kernel corresponding to the used travel-time geometry. Results: We find a very good to acceptable agreement between measurements and models for travel times with ridge filtering applied. The sought dependence indeed resembles a linear function and the slope of it agrees with the expected volume integral from the forward-modelled sensitivity kernel. The agreement is less optimistic for the phase-speed filtered datacubes. A disagreement is particularly large for smallest phase speeds (filters td1--td4), for the larger phase speeds, our result indicate that the measured kernel integrals are systematically larger than expected from the forward modelling. We admit that for large phase-speeds and higher radial modes our testing procedure does not have to be appropriate.

As a result of climate change, Norway spruce (Picea abies [L.] Karst.) is dying across Europe. One of the primary reasons for this is the cultivation of unsuitable spruce provenances and ecotypes. This study deals with the growth and genetics of the ecotypes of Norway spruce, the most important tree species of the Czech Republic. At the study site, namely Cukrák, an experimental site was established in 1964 to plant three basic spruce ecotypes: low-elevation (LE), medium-elevation (ME) and high-elevation (HE) ecotype. A dendrometric inventory, dendrochronological sampling and genetic analyses were carried out on individual trees in 45 to 46 years old spruce stands. The ME ecotype was the most productive in terms of its carbon sequestration potential, while the HE ecotype had the lowest radial growth. All ecotypes exhibited a noteworthy negative correlation between tree-ring growth and seasonal temperature, annual temperature, previous year September to current year August temperature, June to July temperature, as well as individual monthly temperatures from previous May to current August. The relationship of annual and seasonal precipitation to growth was significant only for the LE and ME ecotypes, but precipitation from previous year September to current year August and precipitation from current June to July were the most significant for all ecotypes, where the ME had the highest r value. The HE ecotype does not adapt well to a dry climate and appears to be unsuitable compared to the other ecotypes under the studied conditions. This study also documented intra-population genetic variation within years of low growth, as evidenced by significant clonal heritability. The selection of the appropriate spruce ecotypes is essential for the stability and production of future stands and should become an important pillar of forest adaptation to climate change.

The relative number of sunspots represents the longest evidence describing the level of solar activity. As such, its use goes beyond solar physics, e.g. towards climate research. The construction of a single representative series is a delicate task which involves a combination of observation of many observers. We propose a new iterative algorithm that allows to construct a target series of relative sunspot number of a hypothetical stable observer by optimally combining series obtained by many observers. We show that our methodology provides us with results that are comparable with recent reconstructions of both sunspot number and group number. Furthermore, the methodology accounts for the possible non-solar changes of observers' time series such as gradually changing observing conditions or slow change in the observers vision. It also provides us with reconstruction uncertainties. We apply the methodology to a limited sample of observations by ČESLOPOL network and discuss its properties and limitations.

We investigate the maximum expected magnitudes of the geomagnetically induced currents (GICs) in the Czech transmission power network. We compute a model utilising the Lehtinen–Pirjola method, considering the plane-wave model of the geoelectric field, and using the transmission network parameters kindly provided by the operator. We find that the maximum amplitudes expected in the nodes of the Czech transmission grid during the Halloween storm-like event are about 15 A. For the “extreme-storm” conditions with a 1-V/km geoelectric field, the expected maxima do not exceed 40 A. We speculate that the recently proven statistical correlation between the increased geomagnetic activity and anomaly rate in the power grid may be due to the repeated exposure of the devices to the low-amplitude GICs.Graphical Abstract