Search

The constant improvement of astronomical instrumentation provides the foundation for scientific discoveries. In general, these improvements have only implications forward in time, while previous observations do not benefit from this trend. Here we provide a general deep learning method that translates between image domains of different instruments (Instrument-To-Instrument translation; ITI). We demonstrate that the available data sets can directly profit from the most recent instrumental improvements, by applying our method to five different applications of ground- and space-based solar observations. We obtain 1) solar full-disk observations with unprecedented spatial resolution, 2) a homogeneous data series of 24 years of space-based observations of the solar EUV corona and magnetic field, 3) real-time mitigation of atmospheric degradations in ground-based observations, 4) a uniform series of ground-based Hα observations starting from 1973, 5) magnetic field estimates from the solar far-side based on EUV imagery. The direct comparison to simultaneous high-quality observations shows that our method produces images that are perceptually similar and match the reference image distribution.

A solar spot group with a large area is not a requirement for a great magnetic storm. Nearly half (14/30) of all storms with a minimum Dst value ≤−300 nT from 1932–2014 originated in spot groups with corrected areas ≤1000 millionths of a solar hemisphere (μsh) on the day of the associated eruption. Over the same interval, spot groups with area 3000–4000 μsh were ∼250 times more likely to give rise to a great storm than those with areas from 100–1000 μsh, with the high percentage of great storms originating in small spot groups attributed primarily to the much higher occurrence frequency of such groups. Above ∼3500 μsh, the ability of a spot group to produce a great storm appears to drop abruptly. For the 1932–2014 interval, we find that for the 71 days when a spot group had a measured daily area of 3000–3500 μsh, five great storms were observed versus none for the 67 times when a group spot with an area from 3500 to ∼6000 μsh was observed on the Sun. This is consistent with recent studies indicating that large spot groups on the Sun and stars can suppress coronal mass ejections.

We investigate terrain effects on short-wave radiation measurements at Kanzelhohe Observatory (KSO), a mountainous radiation monitoring site in the Austrian Southern Alps, using three-dimensional (3-D) radiative transfer (RT) modeling and observations. The magnitude of terrain effects on global radiation is experimentally assessed through the comparison of 10-min measurement segments ex−/including terrain reflected radiation. The reflected component is ex−/included in global solar irradiance (GLO) measurements through a horizon shaped metal frame raised/lowered in 10-min intervals. Additionally we assess terrain influence in 3-D RT model simulations performed with an updated version of GRIMALDI, allowing for digital elevation model inclusion. The DEM used for terrain representation is the one arc second Shuttle Radar Topography Mission (SRTM) digital elevation model. For GRIMALDI simulations we consider an area averaged albedo of 0.30 for summer and 0.36 for winter (0.30 for forests and 0.90 for fresh snow), respectively. The influence of the horizon and surface albedo on a grid cell of interest (KSO location) is derived through comparison of the solar irradiance incident on a domain grid cell surface (SI-GCS) with SI-GCS reduced for the reflected component. Applying a 2σ threshold for the significance of terrain effects in GLO measurements, we find no significant influence of the surrounding during summertime. Also during wintertime, we find for the vast majority of observational increments no significant influence of the surrounding. Above a 2σ threshold, exceedances are small, on average 0.2 W m−2. Differences between 3-D RT model simulations including and excluding terrain effects are small during winter conditions, i.e. always below 1% and never exceeding 1 W m−2. Slightly larger differences are found for 3-D RT simulations including/excluding the reflected component during summertime, reaching at solar noon up to 6.1 W m−2. Both observations and model simulations indicate that KSO is well suited for radiation monitoring as terrain effects are small (close to negligible considering instrument specifications) throughout the year.

Forecasting the solar cycle amplitude is important for a better understanding of the solar dynamo as well as for many space weather applications. We demonstrated a steady relationship between the maximal growth rate of sunspot activity in the ascending phase of a cycle and the subsequent cycle amplitude on the basis of four data sets of solar activity indices: total sunspot numbers, hemispheric sunspot numbers from the new catalogue from 1874 onwards, total sunspot areas, and hemispheric sunspot areas. For all the data sets, a linear regression based on the maximal growth rate precursor shows a significant correlation. Validation of predictions for cycles 1-24 shows high correlations between the true and predicted cycle amplitudes reaching r = 0.93 for the total sunspot numbers. The lead time of the predictions varies from 2 to 49 months, with a mean value of 21 months. Furthermore, we demonstrated that the sum of maximal growth rate indicators determined separately for the north and the south hemispheric sunspot numbers provides more accurate predictions than that using total sunspot numbers. The advantages reach 27% and 11% on average in terms of rms and correlation coefficient, respectively. The superior performance is also confirmed with hemispheric sunspot areas with respect to total sunspot areas. The maximal growth rate of sunspot activity in the ascending phase of a solar cycle serves as a reliable precursor of the subsequent cycle amplitude. Furthermore, our findings provide a strong foundation for supporting regular monitoring, recording, and predictions of solar activity with hemispheric sunspot data, which capture the asymmetric behaviour of the solar activity and solar magnetic field and enhance solar cycle prediction methods., 11 pages, 11 figures, accepted for publication in the Astronomy & Astrophysics

Context. In recent decades, solar physics has entered the era of big data and the amount of data being constantly produced from ground- and space-based observatories can no longer be purely analyzed by human observers. Aims. In order to assure a stable series of recorded images of sufficient quality for further scientific analysis, an objective image-quality measure is required. Especially when dealing with ground-based observations, which are subject to varying seeing conditions and clouds, the quality assessment has to take multiple effects into account and provide information about the affected regions. The automatic and robust identification of quality-degrading effects is critical for maximizing the scientific return from the observations and to allow for event detections in real time. In this study, we develop a deep-learning method that is suited to identify anomalies and provide an image-quality assessment of solar full-disk Hα filtergrams. The approach is based on the structural appearance and the true image distribution of high-quality observations. Methods. We employ a neural network with an encoder–decoder architecture to perform an identity transformation of selected high-quality observations. The encoder network is used to achieve a compressed representation of the input data, which is reconstructed to the original by the decoder. We use adversarial training to recover truncated information based on the high-quality image distribution. When images of reduced quality are transformed, the reconstruction of unknown features (e.g., clouds, contrails, partial occultation) shows deviations from the original. This difference is used to quantify the quality of the observations and to identify the affected regions. In addition, we present an extension of this architecture that also uses low-quality samples in the training step. This approach takes characteristics of both quality domains into account, and improves the sensitivity for minor image-quality degradation. Results. We apply our method to full-disk Hα filtergrams from the Kanzelhöhe Observatory recorded during 2012−2019 and demonstrate its capability to perform a reliable image-quality assessment for various atmospheric conditions and instrumental effects. Our quality metric achieves an accuracy of 98.5% in distinguishing observations with quality-degrading effects from clear observations and provides a continuous quality measure which is in good agreement with the human perception. Conclusions. The developed method is capable of providing a reliable image-quality assessment in real time, without the requirement of reference observations. Our approach has the potential for further application to similar astrophysical observations and requires only coarse manual labeling of a small data set.

We create a continuous series of daily and monthly hemispheric sunspot numbers (HSNs) from 1874 to 2020, which will be continuously expanded in the future with the HSNs provided by SILSO. Based on the available daily measurements of hemispheric sunspot areas from 1874 to 2016 from Greenwich Royal Observatory and NOAA, we derive the relative fractions of the northern and southern activity. These fractions are applied to the international sunspot number (ISN) to derive the HSNs. This method and obtained data are validated against published HSNs for the period 1945--2020. We provide a continuous data series and catalogue of daily, monthly mean, and 13-month smoothed monthly mean HSNs for the time range 1874--2020 that are consistent with the newly calibrated ISN. Validation of the reconstructed HSNs against the direct data available since 1945 reveals a high level of consistency, with a correlation of r=0.94 (0.97) for the daily (monthly) data. The cumulative hemispheric asymmetries for cycles 12-24 give a mean value of 16%, with no obvious pattern in north-south predominance over the cycle evolution. The strongest asymmetry occurs for cycle no. 19, in which the northern hemisphere shows a cumulated predominance of 42%. The phase shift between the peaks of solar activity in the two hemispheres may be up to 28 months, with a mean absolute value of 16.4 months. The phase shifts reveal an overall asymmetry of the northern hemisphere reaching its cycle maximum earlier (in 10 out of 13 cases). Relating the ISN and HSN peak growth rates during the cycle rise phase with the cycle amplitude reveals higher correlations when considering the two hemispheres individually, with r = 0.9. Our findings demonstrate that empirical solar cycle prediction methods can be improved by investigating the solar cycle dynamics in terms of the hemispheric sunspot numbers., Comment: Accepted by Astron. Astrophys. 12 pages

In recent decades, automated sensors for sunshine duration (SD) measurements have been introduced in meteorological networks, thereby replacing traditional instruments, most prominently the Campbell-Stokes (CS) sunshine recorder. Parallel records of automated and traditional SD recording systems are rare. Nevertheless, such records are important to understand the differences/similarities in SD totals obtained with different instruments and how changes in monitoring device type affect the homogeneity of SD records. This study investigates the differences/similarities in parallel SD records obtained with a CS and two automated SD sensors between 2007 and 2016 at the Kanzelhohe Observatory, Austria. Comparing individual records of daily SD totals, we find differences of both positive and negative sign, with smallest differences between the automated sensors. The larger differences between CS-derived SD totals and those from automated sensors can be attributed (largely) to the higher sensitivity threshold of the CS instrument. Correspondingly, the closest agreement among all sensors is found during summer, the time of year when sensitivity thresholds are least critical. Furthermore, we investigate the performance of various models to create the so-called sensor-type-equivalent (STE) SD records. Our analysis shows that regression models including all available data on daily (or monthly) time scale perform better than simple three- (or four-) point regression models. Despite general good performance, none of the considered regression models (of linear or quadratic form) emerges as the “optimal” model. Although STEs prove useful for relating SD records of individual sensors on daily/monthly time scales, this does not ensure that STE (or joint) records can be used for trend analysis.

Polar crown filaments (PCFs) are formed above the polarity inversion line, which separates unipolar polar fields and the nearest dispersed fields. They are important features in studying solar polar fields and their cyclical variations. Due to the relatively weak field strength and projection effects, measuring polar magnetic fields is more difficult than obtaining the field strengths concentrated in active regions at lower latitudes. “Rush-to-the-pole” of PCFs represent the progress of unipolar polar fields from the previous solar cycle being canceled by the dispersed fields generated in the current cycle. Such progress is a good indicator of the polarity reversal in the polar areas and a precursor for the solar maximum. In this study, PCFs are identified from a 100 yr archive, covering cycles 16–24. This archive consists of full-disk Hα images obtained from the Kodaikanal Solar Observatory of the Indian Institute of Astrophysics, Kanzelhöhe Solar Observatory, and Big Bear Solar Observatory. The poleward migration speeds are measured and show an obvious asymmetry in the northern and southern hemispheres. In addition, our results show that the PCFs usually reach their highest latitudes first in the northern hemisphere, except cycle 17. Similarly, previous studies show that the magnetic field reversed first at the north pole in six out of nine cycles. We also compare the temporal variations of PCF migration and the latitude gradient factor of the differential rotation, which shows a trend in the southern hemisphere. Moreover, the migration speed of PCFs does not seem to be well correlated with the maximum sunspot numbers.

Sunspot position data obtained from Kanzelh\"{o}he Observatory for Solar and Environmental Research (KSO) sunspot drawings and white light images in the period 1964 to 2016 were used to calculate the rotational and meridional velocities of the solar plasma. Velocities were calculated from daily shifts of sunspot groups and an iterative process of calculation of the differential rotation profiles was used to discard outliers. We found a differential rotation profile and meridional motions in agreement with previous studies using sunspots as tracers and conclude that the quality of the KSO data is appropriate for analysis of solar velocity patterns. By analysing the correlation and covariance of meridional velocities and rotation rate residuals we found that the angular momentum is transported towards the solar equator. The magnitude and latitudinal dependence of the horizontal component of the Reynolds stress tensor calculated is sufficient to maintain the observed solar differential rotation profile. Therefore, our results confirm that the Reynolds stress is the dominant mechanism responsible for transport of angular momentum towards the solar equator., Comment: 14 pages, 6 figures

Polar Crown Filaments (PCFs) form above the magnetic polarity inversion line, which separates the unipolar polar fields and the nearest dispersed fields from trailing part of active regions with opposite polarity. The statistical properties of PCFs are correlated with the solar cycle. Therefore, study of PCFs plays an important role in understanding the variation of solar cycle, especially the prolonged cycle 23 and the current "abnormal" solar cycle 24. In this study, we investigate PCFs using full disk H{\alpha} data from 1973 to early 2018, recorded by Kanzelhohe Solar Observatory (KSO) and Big Bear Solar Observatory (BBSO), in digital form from 1997 to 2018 and in 35 mm film (digitized) from 1973 to 1996. PCFs are identified manually because their segmented shape and close-to-limb location were not handled well by automatical detections in several previous studies. Our results show that the PCFs start to move poleward at the beginning of each solar cycle. When the PCFs approach to the maximum latitude, the polar field strength reduces to zero followed by a reversal. The migration rates are about 0.4 to 0.7 degree per Carrington rotation, with clear N-S asymmetric pattern. In cycles 21 and 23, the PCFs in the northern hemisphere migrate faster than those in the southern hemisphere. However, in the "abnormal" cycle 24, the southern PCFs migrate faster, which is consistent with other observations of magnetic fields and radio emission. In addition, there are more days in cycle 23 and 24 without PCFs than in the previous cycles.

Using a 45.5-h time series of photospheric flow fields generated from a set of high-resolution continuum images (SOHO/MDI) we analyze the dynamics of solar mesogranule features. The series was prepared applying a local correlation tracking algorithm with a 4.8 FWHM window. By computing 1-h running means in time steps of 10 min we generate 267 averaged divergence maps that are segmented to obtain binary maps. A tracking algorithm determines lifetimes and barycenter coordinates of regions of positive divergence defined as mesogranules (MGs). If we analyze features of lifetimes ≥1 h and of areas >5 Mm 2 we find a mean drift velocity of 304 m s -1 (with ±1σ variation of 180 m s -1 ), a mean travel distance of 2.5 ± 1.8 Mm, a mean lifetime of 2.6 ± 1.8 h, and a 1 /e decay time of 1.6 h for a total of 2022 MGs. The advective motion of MGs within supergranules is seen for 50 to 70% of the long-lived (≥4 h) MGs while the short-lived ones move irregularly. If only the long-lived MGs are further analyzed the drift velocities reduce to 207 m s and the travel distances increase to 4.1 Mm on average, which is an appreciable fraction of the supergranular radius. The results are largely independent of the divergence segmentation level.

The presence of a solar background in the phase difference between the intensity and velocity (I − V) p-mode oscillation signals recently has been interpreted in terms of downflows due to convection (Skartlien & Rast 2000) or due to chromospheric explosive events (Moretti et al. 2001a). In support of the latter, we present I and V characteristics of impulsive brightenings observed in the NaI D lines, show that these reproduce the frequency dependence of the I − V modulation back- ground, and show that explanations invoking more frequently occurring phenomena such as seismic events are not likely in low-l modulation data.

Kanzelhöhe Observatory (kso.ac.at) performs regular high-cadence full-disk observations of the solar chromosphere in the Hα and CaIIK spectral lines as well as the solar photosphere in white-light. In the frame of ESA's Space Situational Awareness (SSA) activities, a new system for near real-time Hα image provision through the SSA Space Weather (SWE) portal (swe.ssa.esa.int) and for automatic alerting of flares and erupting filaments is under development. Image segmentation algorithms, based on optical flow image registration, for the automatic detection of solar filaments in real time Hα images have been developed and implemented at the Kanzelhöhe observing system. We present first results of this system with respect to the automatic recognition and segmentation of filaments and filament eruptions on the Sun.

In this paper an overview is given concerning the automatic detection of granules in long time series and the derivation of characteristic parameters.