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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.

The sun’s magnetic field drives the 11-year solar cycle, and predicting its strength has practical importance for many space weather applications. Previous studies have shown that analysing the solar activity of the two hemispheres separately instead of the full sun can provide more detailed information on the activity evolution. However, the existing Hemispheric Sunspot Number data series (1945 onwards) was too short for meaningful solar cycle predictions. Based on a newly created hemispheric sunspot number catalogue for the time range 1874-2020 (Veronig et al. 2021, http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/652/A56) that is compatible with the International Sunspot Number from World Data Centre SILSO, we investigate the evolution of the solar cycle for the two hemispheres and develop a novel method for predicting the solar cycle amplitude. We demonstrate a steady relationship between the maximal growth rate of activity in the ascending phase of a cycle and its subsequent amplitude and form a 3rd order regression for the predictions. Testing this method for cycles 12-24, we show that the forecast made by the sum of the maximal growth rate from the North and South Hemispheric Sunspot number is more accurate than the same forecast from the Total Sunspot Number: The rms error of predictions is smaller by 27%, the correlation coefficient r is higher by 11% on average reaching values in the range r = 0.8-0.9 depending of the smoothing window of the monthly mean data. These findings demonstrate that empirical solar cycle prediction methods can be enhanced by investigating the solar cycle dynamics in terms of the hemispheric sunspot numbers, which is a strong argument supporting regular monitoring, recording, and analysing solar activity separately for the two hemispheres.

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

The 11-Year solar cycle is driven by the sun's magnetic field. The sunspot number is the most-common long term index of solar activity and prediction of its amplitude can help to understand the physics of the solar dynamo and the effects of space weather. Previous studies have shown that analysing the solar activity of the two hemispheres separately instead of the full suncan provide more detailed information on the activity evolution. However, the existing Hemispheric Sunspot Number data series (1945 onwards) is too short for the purpose of solar cycle predictions. Based on a newly created hemispheric sunspot number catalogue for the time range 1874-2020 (Veronig et al. 2021) that is compatible with the International Sunspot Number from World Data Center SILSO, we investigate the evolution of the solar cycle for the two hemispheres, and demonstrate that empirical solar cycle prediction methods can be enhanced by investigating the solar cycle dynamics in terms of the hemispheric sunspot numbers. We develop a method for predictingthe solar cycle amplitude based on the peak growth rate in the ascending phase of the cycle using the Hemispheric Sunspot numbers for cycles 12-24. We show that using this technique, the sum of the predictions (North+South) of the two hemisphere give better estimates of the cycle amplitude than the Total Sunspot Numbers. In addition, we estimate the cycle peaks with 1st order and 3rd order regressions and find that the hemispheric sunspot numbers provide better estimates of cycle peak than total sunspot numbers for both the cases with the obtained correlations lying in the range r =0.8 to 0.9 depending on the applied smoothing window

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

The accuracy of solar radiation measurements, for direct (DIR) and diffuse (DIF) radiation, depends significantly on the precision of the operational Sun-tracking device. Thus, rigid targets for instrument performance and operation have been specified for international monitoring networks, e.g., the Baseline Surface Radiation Network (BSRN) operating under the auspices of the World Climate Research Program (WCRP). Sun-tracking devices that fulfill these accuracy requirements are available from various instrument manufacturers; however, none of the commercially available systems comprise an automatic accuracy control system allowing platform operators to independently validate the pointing accuracy of Sun-tracking sensors during operation. Here we present KSO-STREAMS (KSO-SunTRackEr Accuracy Monitoring System), a fully automated, system-independent, and cost-effective system for evaluating the pointing accuracy of Sun-tracking devices. We detail the monitoring system setup, its design and specifications, and the results from its application to the Sun-tracking system operated at the Kanzelhöhe Observatory (KSO) Austrian radiation monitoring network (ARAD) site. The results from an evaluation campaign from March to June 2015 show that the tracking accuracy of the device operated at KSO lies within BSRN specifications (i.e., 0.1° tracking accuracy) for the vast majority of observations (99.8 %). The evaluation of manufacturer-specified active-tracking accuracies (0.02°), during periods with direct solar radiation exceeding 300 W m−2, shows that these are satisfied in 72.9 % of observations. Tracking accuracies are highest during clear-sky conditions and on days where prevailing clear-sky conditions are interrupted by frontal movement; in these cases, we obtain the complete fulfillment of BSRN requirements and 76.4 % of observations within manufacturer-specified active-tracking accuracies. Limitations to tracking surveillance arise during overcast conditions and periods of partial solar-limb coverage by clouds. On days with variable cloud cover, 78.1 % (99.9 %) of observations meet active-tracking (BSRN) accuracy requirements while for days with prevailing overcast conditions these numbers reduce to 64.3 % (99.5 %).

Context. Kanzelhöhe Observatory for Solar and Environmental Research (KSO) provides daily multispectral synoptic observations of the Sun using several telescopes. In this work we made use of sunspot drawings and full disk white light CCD images. Aims. The main aim of this work is to determine the solar differential rotation by tracing sunspot groups during the period 1964–2016, using the KSO sunspot drawings and white light images. We also compare the differential rotation parameters derived in this paper from the KSO with those collected from other data sets and present an investigation of the north – south rotational asymmetry. Methods. Two procedures for the determination of the heliographic positions were applied: an interactive procedure on the KSO sunspot drawings (1964–2008, solar cycles Nos. 20–23) and an automatic procedure on the KSO white light images (2009–2016, solar cycle No. 24). For the determination of the synodic angular rotation velocities two different methods have been used: a daily shift (DS) method and a robust linear least- squares fit (rLSQ) method. Afterwards, the rotation velocities had to be converted from synodic to sidereal, which were then used in the least-squares fitting for the solar differential rotation law. A comparison of the interactive and automatic procedures was performed for the year 2014. Results. The interactive procedure of position determination is fairly accurate but time consuming. In the case of the much faster automatic procedure for position determination, we found the rLSQ method for calculating rotational velocities to be more reliable than the DS method. For the test data from 2014, the rLSQ method gives a relative standard error for the differential rotation parameter B that is three times smaller than the corresponding relative standard error derived for the DS method. The best fit solar differential rotation profile for the whole time period is omega(b) = (14.47+-0.01) - (2.66 +- 0.10) sin^2(b) (deg/day) for the DS method and omega(b) = (14.50 +- 0.01) - (2.87 +- 0.12) sin^2(b) (deg/day) for the rLSQ method. A barely noticeable north – south asymmetry is observed for the whole time period 1964–2016 in the present paper. Rotation profiles, using different data sets, presented by other authors for the same time periods and the same tracer types, are in good agreement with our results. Conclusions. The KSO data set used in this paper is in good agreement with the Debrecen Photoheliographic Data and Greenwich Photoheliographic Results and is suitable for the investigation of the long-term variabilities in the solar rotation profile. Also, the quality of the KSO sunspot drawings has gradually increased during the last 50 yr.

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.

Kanzelh\"ohe Observatory (KSO) was founded during World War II by the "Deutsche Luftwaffe" (German Airforces) as one station of a network of observatories, which should provide information on solar activity in order to better assess the actual conditions of the Earth's ionosphere in terms of radio wave propagation. The solar observations began in 1943 with photographs of the photosphere, drawings of sunspots, plage regions and faculae, as well as patrol observations of the solar corona. At the beginning all data was sent to Freiburg (Germany). After WWII international cooperation was established and the data was sent to Zurich, Paris, Moscow and Greenwich. Relative sunspot numbers are derived since 1944. The agreement between relative sunspot numbers derived at KSO and the new International Sunspot Number (ISN) \citep{SIDC} lies within $\sim10\%$. However, revisiting the historical data, we also find periods with larger deviations. The reasons for the deviations were twofold: (1) On the one hand a major instrumental change took place during which a relocation and modification of the instrument happened. (2) On the other hand, a period of frequent replacement of personnel caused significant deviations, i.e. stressing the importance of experienced observers. On long-term, the instrumental improvements led to better image quality. Additionally we find a long term trend towards better seeing conditions since the year 2000. We may speculate that this is related to climatic changes., Comment: 24 pages, 15 figures

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.

Kanzelh\"ohe Observatory (KSO) regularly performs high-cadence full-disk imaging of the solar chromosphere in the H$\alpha$ and CaIIK spectrallines as well as the solar photosphere in white-light. In the frame of ESA's Space Situational Awareness (SSA) programme, a new system for real-time H$\alpha$ data provision and automatic flare detection was developed at KSO. The data and events detected are published in near real-time at ESA's SSA Space Weather portal (http://swe.ssa.esa.int/web/guest/kso-federated). In this paper, we describe the H$\alpha$ instrument, the image recognition algorithms developed, the implementation into the KSO H$\alpha$ observing system and present the evaluation results of the real-time data provision and flare detection for a period of five months. The H$\alpha$ data provision worked in $99.96$% of the images, with a mean time lag between image recording and online provision of 4s. Within the given criteria for the automatic image recognition system (at least three H$\alpha$ images are needed for a positive detection), all flares with an area $\ge$50 micro-hemispheres and located within $60^\circ$ of the Sun's center that occurred during the KSO observing times were detected, in total a number of 87 events. The automatically determined flare importance and brightness classes were correct in $\sim$85%. The mean flare positions in heliographic longitude and latitude were correct within $\sim$1$^\circ$. The median of the absolute differences for the flare start times and peak times from the automatic detections in comparison to the official NOAA (and KSO) visual flare reports were 3 min (1 min)., Comment: 29 pages, 15 figures, 5 tables; Accepted for Solar Physics, Nov 2014

We study spectroscopic observations of chromospheric evaporation mass flows in comparison to the energy input by electron beams derived from hard X-ray data for the white-light M2.5 flare of 2006 July 6. The event was captured in high cadence spectroscopic observing mode by SOHO/CDS combined with high-cadence imaging at various wavelengths in the visible, EUV and X-ray domain during the joint observing campaign JOP171. During the flare peak, we observe downflows in the He\,{\sc i} and O\,{\sc v} lines formed in the chromosphere and transition region, respectively, and simultaneous upflows in the hot coronal Si~{\sc xii} line. The energy deposition rate by electron beams derived from RHESSI hard X-ray observations is suggestive of explosive chromospheric evaporation, consistent with the observed plasma motions. However, for a later distinct X-ray burst, where the site of the strongest energy deposition is exactly located on the CDS slit, the situation is intriguing. The O\,{\sc v} transition region line spectra show the evolution of double components, indicative of the superposition of a stationary plasma volume and upflowing plasma elements with high velocities (up to 280~km~s$^{-1}$) in single CDS pixels on the flare ribbon. However, the energy input by electrons during this period is too small to drive explosive chromospheric evaporation. These unexpected findings indicate that the flaring transition region is much more dynamic, complex, and fine-structured than is captured in single-loop hydrodynamic simulations., Astrophys. Journal (2010, in press); 14 figures; 4 movies (not included in arxiv.org)

Context. Recent RHESSI observations indicate an apparent altitude decrease of flare X-ray loop-top (LT) sources before changing to the commonly observed upward growth of the flare loop system. Aims. We performed a detailed study of the LT altitude decrease for one well observed flare in order to find further hints on the physics of this phenomenon and how it is related to the magnetic reconnection process in solar flares. Methods. RHESSI X-ray source motions in the 2003 November 3, X3.9 flare are studied together with complementary data from SXI, EIT, and Kanzelhohe Ha. We particularly concentrate on the apparent altitude decrease of the RHESSI X-ray LT source early in the flare and combine kinematical and X-ray spectral analysis. Furthermore, we present simulations from a magnetic collapsing trap model embedded in a standard 2-D magnetic reconnection model of solar flares. Results. We find that at higher photon energies the LT source is located at higher altitudes and shows higher downward velocities than at lower energies. The mean downward velocities range from 14 km s -1 in the RHESSI 10-15 keV energy band to 45 km s -1 in the 25-30 keV band. For this flare, the LT altitude decrease was also observed by the SXI instrument with a mean speed of 12 km s -1 . RHESSI spectra indicate that during the time of LT altitude decrease the emission of the LT source is thermal bremsstrahlung from a superhot plasma with temperatures increasing from 35 MK to 45 MK and densities of the order of 10 10 cm -3 . The temperature does not significantly increase after this early (pre-impulsive superhot LT) phase, whereas the LT densities increase to a peak value of (3-4) x 10 11 cm -3 . Conclusions. Modeling of a collapsing magnetic trap embedded in a standard 2D magnetic reconnection model can reproduce the key observational findings in case that the observed emission is thermal bremsstrahlung from the hot LT plasma. This agrees with the evaluated RHESSI spectra for this flare.

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.

Kanzelh\"ohe Observatory for Solar and Environmental Research (KSO) of the University of Graz (Austria) is in continuous operation since its foundation in 1943. Since the beginning its main task was the regular observation of the Sun in full disc. In this long time span covering almost seven solar cycles, a substantial amount of data was collected, which is made available online. In this paper we describe the separate processing steps from data acquisition to high level products for the different observing wavelengths. First of all we work out in detail the quality classification, which is important for further processing of the raw images. We show how we construct centre-to-limb variation (CLV) profiles and how we remove large scale intensity variations produced by the telescope optics in order to get images with uniform intensity and contrast. Another important point is an overview of the different data products from raw images to high contrast images with heliographic grids overlaid. As the data products are accessible via different sources we also present how to get information about the availability and how to obtain these data. Finally, in an appendix, we describe in detail the information in the FITS headers, the file naming and the data hierarchy., Comment: 39 pages, 21 figures, 3 tables