Comparison of Ground-Based and Space-Based Longitudinal Magnetograms

We compare photospheric line-of-sight magnetograms from the Synoptic Optical Long-term Investigations of the Sun (SOLIS) Vector Spectro-Magnetograph (VSM) instrument with observations from the 150-foot Solar Tower at Mt. Wilson Observatory (MWO), the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO), and the Michelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO). We find very good agreement between VSM and the other data sources for both disk-averaged flux densities and pixel-by-pixel measurements. We show that the VSM mean flux density time series is of consistently high signal-to-noise ratio with no significant zero offsets. We discuss in detail some of the factors ?C spatial resolution, flux dependence, and position on the solar disk ?C affecting the determination of scaling between VSM and SOHO/MDI or SDO/HMI magnetograms. The VSM flux densities agree well with spatially smoothed data from MDI and HMI, although the scaling factors show a clear dependence on flux density. The factor to convert VSM to HMI increases with increasing flux density (from ??1 to ??1.5). The nonlinearity is smaller for the VSM vs. SOHO/MDI scaling factor (from ??1 to ??1.2).     

Applying an Automatic Image-Processing Method to Synoptic Observations

We used an automatic image-processing method to detect solar-activity features observed in white light at the Kislovodsk Solar Station. This technique was applied to automatically or semi-automatically detect sunspots and active regions. The results of this automated recognition were verified with statistical data available from other observatories and revealed a high detection accuracy. We also provide parameters of sunspot areas, of the umbra, and of faculae as observed in Solar Cycle 23 as well as the magnetic flux of these active elements, calculated at the Kislovodsk Solar Station, together with white-light images and magnetograms from the Michaelson Doppler Imager onboard the Solar and Heliospheric Observatory (SOHO/MDI). The ratio of umbral and total sunspot areas during Solar Cycle 23 is ≈?0.19. The area of sunspots of the leading polarity was approximately 2.5 times the area of sunspots of the trailing polarity.     

Analysis of Supergranule Sizes and Velocities Using Solar Dynamics Observatory (SDO)/Helioseismic Magnetic Imager (HMI) and Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) Dopplergrams

Co-temporal Doppler images from Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) and Solar Dynamics Observatory (SDO)/Helioseismic Magnetic Imager (HMI) have been analyzed to extract quantitative information about global properties of the spatial and temporal characteristics of solar supergranulation. Preliminary comparisons show that supergranules appear to be smaller and have stronger horizontal velocity flows within HMI data than was measured with MDI. There appears to be no difference in their evolutionary timescales. Supergranule sizes and velocities were analyzed over a ten-day time period at a 15-minute cadence. While the averages of the time-series retain the aforementioned differences, fluctuations of these parameters first observed in MDI data were seen in both MDI and HMI time-series, exhibiting a strong cross-correlation. This verifies that these fluctuations are not instrumental, but are solar in origin. The observed discrepancies between the averaged values from the two sets of data are a consequence of instrument resolution. The lower spatial resolution of MDI results in larger observed structures with lower velocities than is seen in HMI. While these results offer a further constraint on the physical nature of supergranules, they also provide a level of calibration between the two instruments.     

Comparison of Line-of-Sight Magnetograms Taken by the Solar Dynamics Observatory/Helioseismic and Magnetic Imager and Solar and Heliospheric Observatory/Michelson Doppler Imager

We compare line-of-sight magnetograms from the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) and the Michelson Doppler Imager (MDI) onboard the Solar and Heliospheric Observatory (SOHO). The line-of-sight magnetic signal inferred from the calibrated MDI data is greater than that derived from the HMI data by a factor of 1.40. This factor varies somewhat with center-to-limb distance. An upper bound to the random noise for the 1′′ resolution HMI 720-second magnetograms is 6.3 Mx?cm^?2, and 10.2 Mx?cm^?2 for the 45-second magnetograms. Virtually no p-mode leakage is seen in the HMI magnetograms, but it is significant in the MDI magnetograms. 12-hour and 24-hour periodicities are detected in strong fields in the HMI magnetograms. The newly calibrated MDI full-disk magnetograms have been corrected for the zero-point offset and underestimation of the flux density. The noise is 26.4 Mx?cm^?2 for the MDI one-minute full-disk magnetograms and 16.2 Mx?cm^?2 for the five-minute full-disk magnetograms observed with four-arcsecond resolution. The variation of the noise over the Sun’s disk found in MDI magnetograms is likely due to the different optical distortions in the left- and right-circular analyzers, which allows the granulation and p-mode to leak in as noise. Saturation sometimes seen in sunspot umbrae in MDI magnetograms is caused by the low intensity and the limitation of the onboard computation. The noise in the HMI and MDI line-of-sight magnetic-field synoptic charts appears to be fairly uniform over the entire map. The noise is 2.3 Mx?cm^?2 for HMI charts and 5.0 Mx?cm^?2 for MDI charts. No evident periodicity is found in the HMI synoptic charts.     

A Multi-wavelength Analysis of Active Regions and Sunspots by Comparison of Automatic Detection Algorithms

Since the Solar Dynamics Observatory (SDO) began recording ≈?1 TB of data per day, there has been an increased need to automatically extract features and events for further analysis. Here we compare the overall detection performance, correlations between extracted properties, and usability for feature tracking of four solar feature-detection algorithms: the Solar Monitor Active Region Tracker (SMART) detects active regions in line-of-sight magnetograms; the Automated Solar Activity Prediction code (ASAP) detects sunspots and pores in white-light continuum images; the Sunspot Tracking And Recognition Algorithm (STARA) detects sunspots in white-light continuum images; the Spatial Possibilistic Clustering Algorithm (SPoCA) automatically segments solar EUV images into active regions (AR), coronal holes (CH), and quiet Sun (QS). One month of data from the Solar and Heliospheric Observatory (SOHO)/Michelson Doppler Imager (MDI) and SOHO/Extreme Ultraviolet Imaging Telescope (EIT) instruments during 12 May?–?23 June 2003 is analysed. The overall detection performance of each algorithm is benchmarked against National Oceanic and Atmospheric Administration (NOAA) and Solar Influences Data Analysis Center (SIDC) catalogues using various feature properties such as total sunspot area, which shows good agreement, and the number of features detected, which shows poor agreement. Principal Component Analysis indicates a clear distinction between photospheric properties, which are highly correlated to the first component and account for 52.86% of variability in the data set, and coronal properties, which are moderately correlated to both the first and second principal components. Finally, case studies of NOAA 10377 and 10365 are conducted to determine algorithm stability for tracking the evolution of individual features. We find that magnetic flux and total sunspot area are the best indicators of active-region emergence. Additionally, for NOAA 10365, it is shown that the onset of flaring occurs during both periods of magnetic-flux emergence and complexity development.     

Time-Series Analysis of Supergranule Characteristics at Solar Minimum

Sixty days of Doppler images from the Solar and Heliospheric Observatory (SOHO) / Michelson Doppler Imager (MDI) investigation during the 1996 and 2008 solar minima have been analyzed to show that certain supergranule characteristics (size, size range, and horizontal velocity) exhibit fluctuations of three?to?five days. Cross-correlating parameters showed a good, positive correlation between supergranulation size and size range, and a moderate, negative correlation between size range and velocity. The size and velocity do exhibit a moderate, negative correlation, but with a small time lag (less than 12 hours). Supergranule sizes during five days of co-temporal data from MDI and the Solar Dynamics Observatory (SDO) / Helioseismic Magnetic Imager (HMI) exhibit similar fluctuations with a high level of correlation between them. This verifies the solar origin of the fluctuations, which cannot be caused by instrumental artifacts according to these observations. Similar fluctuations are also observed in data simulations that model the evolution of the MDI Doppler pattern over a 60-day period. Correlations between the supergranule size and size range time-series derived from the simulated data are similar to those seen in MDI data. A simple toy-model using cumulative, uncorrelated exponential growth and decay patterns at random emergence times produces a time-series similar to the data simulations. The qualitative similarities between the simulated and the observed time-series suggest that the fluctuations arise from stochastic processes occurring within the solar convection zone. This behavior, propagating to surface manifestations of supergranulation, may assist our understanding of magnetic-field-line advection, evolution, and interaction.     

Long-Period Oscillations of Sunspots Observed by SOHO/MDI

We processed magnetograms that were obtained with the Michaelson Doppler Imager onboard the Solar and Heliospheric Observatory (SOHO/MDI). The results confirm the basic properties of long-period oscillations of sunspots that have previously been established and also reveal new properties. We show that the limiting (lowest) eigenmode of low-frequency oscillations of a sunspot as a whole is the mode with a period of 10?–?12 up to 32?–?35 hours (depending on the sunspot’s magnetic-field strength). This mode is observed consistently throughout an observation period of 5?–?7 days, but its amplitude is subject to quasi-cyclic changes, which are separated by about 1.5?–?2 days. As a result, the lower mode with a period of about 35?–?48 hours appears in the power spectrum of sunspot oscillations. But this lowest mode is apparently not an eigenmode of a sunspot because its period does not depend on the magnetic field of the sunspot. Perhaps the mode reflects the quasi-periodic sunspot perturbations caused by supergranulation cells that surround it. We also analyzed SOHO/MDI artifacts, which may affect the low-frequency power spectra of sunspots.     

An Early Diagnostics of the Geoeffectiveness of Solar Eruptions from Photospheric Magnetic Flux Observations: The Transition from SOHO to SDO

In our previous articles (Chertok et al. in Solar Phys. 282, 175, 2013; Chertok et al. in Solar Phys. 290, 627, 2015), we presented a preliminary tool for the early diagnostics of the geoeffectiveness of solar eruptions based on the estimate of the total unsigned line-of-sight photospheric magnetic flux in accompanying extreme ultraviolet (EUV) arcades and dimmings. This tool was based on the analysis of eruptions observed during 1996?–?2005 with the Extreme-ultraviolet Imaging Telescope (EIT) and the Michelson Doppler Imager (MDI) onboard the Solar and Heliospheric Observatory (SOHO). Empirical relationships were obtained to estimate the probable importance of upcoming space weather disturbances caused by an eruption, which just occurred, without data on the associated coronal mass ejections. In particular, it was possible to estimate the intensity of a non-recurrent geomagnetic storm (GMS) and Forbush decrease (FD), as well as their onset and peak times. After 2010?–?2011, data on solar eruptions are obtained with the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO). We use relatively short intervals of overlapping EIT–AIA and MDI–HMI detailed observations, and additionally, a number of large eruptions over the next five years with the 12-hour cadence EIT images to adapt the SOHO diagnostic tool to SDO data. We show that the adopted brightness thresholds select practically the same areas of arcades and dimmings from the EIT 195 Å and AIA 193 Å image, with a cross-calibration factor of 3.6?–?5.8 (5.0?–?8.2) for the AIA exposure time of 2.0 s (2.9 s). We also find that for the same photospheric areas, the MDI line-of-sight magnetic flux systematically exceeds the HMI flux by a factor of 1.4. Based on these results, the empirical diagnostic relationships obtained from SOHO data are adjusted to SDO instruments. Examples of a post-diagnostics based on SDO data are presented. As before, the tool is applicable to non-recurrent GMSs and FDs caused by nearly central eruptions from active regions, provided that the southern component of the interplanetary magnetic field near the Earth is predominantly negative, which is not predicted by this tool.     

A New Sigmoid Catalog from Hinode and the Solar Dynamics Observatory: Statistical Properties and Evolutionary Histories

We present a new sigmoid catalog covering the duration of the Hinode mission and the Solar Dynamics Observatory (SDO) until the end of 2012. The catalog consists of 72 mostly long-lasting sigmoids. We collect and make available all X-ray and EUV data from Hinode, SDO, and the Solar TErrestrial RElations Observatory (STEREO), and we determine the sigmoid lifetimes, sizes, and aspect ratios. We also collect the line-of-sight magnetograms from the Helioseismic and Magnetic Imager (HMI) for SDO or the Michelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO) to measure flux versus time for the lifetime of each region. We determine that the development of a sigmoidal shape and eruptive activity is more strongly correlated with flux cancelation than with emergence. We find that the eruptive properties of the regions correlate well with the maximum flux, largest change, and net change in flux in the regions. These results have implications for constraining future flux-rope models of ARs and gaining insight into their evolutionary properties.     

Coronal Holes and Open Magnetic Flux over Cycles 23 and 24

As the observational signature of the footprints of solar magnetic field lines open into the heliosphere, coronal holes provide a critical measure of the structure and evolution of these lines. Using a combination of Solar and Heliospheric Observatory/Extreme ultraviolet Imaging Telescope (SOHO/EIT), Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA), and Solar Terrestrial Relations Observatory/Extreme Ultraviolet Imager (STEREO/EUVI A/B) extreme ultraviolet (EUV) observations spanning 1996?–?2015 (nearly two solar cycles), coronal holes are automatically detected and characterized. Coronal hole area distributions show distinct behavior in latitude, defining the domain of polar and low-latitude coronal holes. The northern and southern polar regions show a clear asymmetry, with a lag between hemispheres in the appearance and disappearance of polar coronal holes.     

Computer Vision for the Solar Dynamics Observatory (SDO)

In Fall 2008 NASA selected a large international consortium to produce a comprehensive automated feature-recognition system for the Solar Dynamics Observatory (SDO). The SDO data that we consider are all of the Atmospheric Imaging Assembly (AIA) images plus surface magnetic-field images from the Helioseismic and Magnetic Imager (HMI). We produce robust, very efficient, professionally coded software modules that can keep up with the SDO data stream and detect, trace, and analyze numerous phenomena, including flares, sigmoids, filaments, coronal dimmings, polarity inversion lines, sunspots, X-ray bright points, active regions, coronal holes, EIT waves, coronal mass ejections (CMEs), coronal oscillations, and jets. We also track the emergence and evolution of magnetic elements down to the smallest detectable features and will provide at least four full-disk, nonlinear, force-free magnetic field extrapolations per day. The detection of CMEs and filaments is accomplished with Solar and Heliospheric Observatory (SOHO)/Large Angle and Spectrometric Coronagraph (LASCO) and ground-based Hα data, respectively. A?completely new software element is a trainable feature-detection module based on a generalized image-classification algorithm. Such a trainable module can be used to find features that have not yet been discovered (as, for example, sigmoids were in the pre-Yohkoh era). Our codes will produce entries in the Heliophysics Events Knowledgebase (HEK) as well as produce complete catalogs for results that are too numerous for inclusion in the HEK, such as the X-ray bright-point metadata. This will permit users to locate data on individual events as well as carry out statistical studies on large numbers of events, using the interface provided by the Virtual Solar Observatory. The operations concept for our computer vision system is that the data will be analyzed in near real time as soon as they arrive at the SDO Joint Science Operations Center and have undergone basic processing. This will allow the system to produce timely space-weather alerts and to guide the selection and production of quicklook images and movies, in addition to its prime mission of enabling solar science. We briefly describe the complex and unique data-processing pipeline, consisting of the hardware and control software required to handle the SDO data stream and accommodate the computer-vision modules, which has been set up at the Lockheed-Martin Space Astrophysics Laboratory (LMSAL), with an identical copy at the Smithsonian Astrophysical Observatory (SAO).     

Statistical Properties Of Sunspots In 1996–2004: I. Detection, North–South Asymmetry And Area Distribution

The first statistical results in sunspot distributions in 1996–2004 obtained from the Solar Feature Catalogues (SFC) are presented. A novel robust technique is developed for automated identification of sunspots on SOHO/MDI white-light (WL) full-disk solar images. The technique applies image standardization procedures for elimination of the limb darkening and non-circular image shape, uses edge-detection methods to find the sunspot candidates and their edges and morphological operations to smooth the features and fill in gaps. The detected sunspots are verified with the SOHO/MDI magnetograms by strong magnetic fields being present in sunspots. A number of physical and geometrical parameters of the detected sunspot features are extracted and stored in the relational SFC database including umbra/penumbra masks in the form of run-length data encoding of sunspot bounding rectangles. The detection results are verified by comparison with the manual daily detection results in Meudon and Locarno Observatories in 2002 and by correlation (about 96%) with the 4 year sunspot areas produced manually at NOAA. Using the SFC data, sunspot area distributions are presented in different phases of the solar cycle and hemispheres which reveals a periodicity of the north–south asymmetry with a period of about 7–8 years. The number of sunspots increases exponentially with the area decrease with the index slightly increasing from −1.15 (1997) to −1.34 (2001).     

Fractal and Multifractal Properties of Active Regions as Flare Precursors: A Case Study Based on SOHO/MDI and SDO/HMI Observations

Several studies indicate that fractal and multifractal parameters inferred from solar photospheric magnetic field measurements may help assessing the eruptive potential of Active Regions (ARs) and also predicting their flare activity. We further investigate this topic, by exploring the sensitivity of some parameters already used in the literature on data and methods employed for their estimation. In particular, we measured the generalized fractal dimensions D ₀ and D ₈, and the multifractal parameters C _div and D _div, on the time series of photospheric magnetograms of the flaring AR NOAA 11158 obtained with the SOHO/MDI and SDO/HMI. The observations by the latter instrument are characterized by a higher spatial and temporal resolution, as well as higher flux sensitivity, than the ones obtained from SOHO/MDI, which were widely employed in earlier studies. We found that the average and peak values of complexity parameters measured on the two data sets agree within measurement uncertainties. The temporal evolution of the parameters measured on the two data sets show rather similar trends, but the ones derived from the SOHO/MDI observations show larger and spurious variations over time than those deduced from analysis of the corresponding SDO/HMI data. We also found a larger sensitivity of these measurements to characteristics of the data analyzed than reported by earlier studies. In particular, analysis of the higher resolution and higher cadence SDO/HMI data allows us also to detect slight variations of the complexity indicators that cannot be derived from the analysis of the SOHO/MDI data. These variations occur right after the major events in the analyzed AR. They may be the signature of photospheric effects of coronal magnetic field re-arrangement.     

On the Formation Height of the SDO/HMI Fe 6173 ? Doppler Signal

The Helioseismic and Magnetic Imager (HMI) onboard the Solar Dynamics Observatory (SDO) is designed to study oscillations and the magnetic field in the solar photosphere. It observes the full solar disk in the Fe?i absorption line at 6173 Å. We use the output of a high-resolution, 3D, time-dependent, radiation-hydrodynamic simulation based on the CO ⁵ BOLD code to calculate profiles F(??,x,y,t) for the Fe?i 6173 Å line. The emerging profiles F(??,x,y,t) are multiplied by a representative set of HMI filter-transmission profiles R _i (??, 1??i??6) and filtergrams I _i (x,y,t; 1??i??6) are constructed for six wavelengths. Doppler velocities V _HMI(x,y,t) are determined from these filtergrams using a simplified version of the HMI pipeline. The Doppler velocities are correlated with the original velocities in the simulated atmosphere. The cross-correlation peaks near 100 km, suggesting that the HMI Doppler velocity signal is formed rather low in the solar atmosphere. The same analysis is performed for the SOHO/MDI Ni?i line at 6768 Å. The MDI Doppler signal is formed slightly higher at around 125 km. Taking into account the limited spatial resolution of the instruments, the apparent formation height of both the HMI and MDI Doppler signal increases by 40 to 50 km. We also study how uncertainties in the HMI filter-transmission profiles affect the calculated velocities.     

Bimodal Distribution of Magnetic Fields and Areas of Sunspots

We applied automatic identification of sunspot umbrae and penumbrae to daily observations from the Helioseismic Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) to study their magnetic flux density (B) and area (A). The results confirm an already known logarithmic relationship between the area of sunspots and their maximum flux density. In addition, we find that the relation between average magnetic flux density ( $B_{\rm avg}$ ) and sunspot area shows a bimodal distribution: for small sunspots and pores (A≤20 millionth of solar hemisphere, MSH), $B_{\rm avg} \approx 800~\mbox{G}$ (gauss), and for large sunspots (A≥100 MSH), $B_{\rm avg}$ is about 600 G. For intermediate sunspots, average flux density linearly decreases from about 800 G to 600 G. A similar bimodal distribution was found in several other integral parameters of sunspots. We show that this bimodality can be related to different stages of sunspot penumbra formation and can be explained by the difference in average inclination of magnetic fields at the periphery of small and large sunspots.     

Automated McIntosh-Based Classification of Sunspot Groups Using MDI Images

This paper presents a hybrid system for automatic detection and McIntosh-based classification of sunspot groups on SOHO/MDI white-light images using active-region data extracted from SOHO/MDI magnetogram images. After sunspots are detected from MDI white-light images they are grouped/clustered using MDI magnetogram images. By integrating image-processing and neural network techniques, detected sunspot regions are classified automatically according to the McIntosh classification system. Our results show that the automated grouping and classification of sunspots is possible with a high success rate when compared to the existing manually created catalogues. In addition, our system can detect and classify sunspot groups in their early stages, which are usually missed by human observers.     

Time–Distance Helioseismology Data-Analysis Pipeline for Helioseismic and Magnetic Imager Onboard Solar Dynamics Observatory (SDO/HMI) and Its Initial Results

The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) provides continuous full-disk observations of solar oscillations. We develop a data-analysis pipeline based on the time–distance helioseismology method to measure acoustic travel times using HMI Doppler-shift observations, and infer solar interior properties by inverting these measurements. The pipeline is used for routine production of near-real-time full-disk maps of subsurface wave-speed perturbations and horizontal flow velocities for depths ranging from 0 to 20?Mm, every eight hours. In addition, Carrington synoptic maps for the subsurface properties are made from these full-disk maps. The pipeline can also be used for selected target areas and time periods. We explain details of the pipeline organization and procedures, including processing of the HMI Doppler observations, measurements of the travel times, inversions, and constructions of the full-disk and synoptic maps. Some initial results from the pipeline, including full-disk flow maps, sunspot subsurface flow fields, and the interior rotation and meridional flow speeds, are presented.     

Temporal Evolution of Sunspot Areas and Estimation of Related Plasma Flows

The increased amount of information provided by ongoing missions such as the Solar Dynamics Observatory (SDO) represents a great challenge for the understanding of basic questions such as the internal structure of sunspots and how they evolve with time. Here, we contribute with the exploitation of new data, to provide a better understanding of the separate growth and decay of sunspots, umbra, and penumbra. Using fuzzy sets to compute separately the areas of sunspot umbra and penumbra, the growth and decay rates for active regions NOAA 11117, NOAA 11428, NOAA 11429, and NOAA 11430 are computed from the analysis of intensitygrams obtained by the Helioseismic and Magnetic Imager onboard SDO. A simplified numerical model is proposed for the decay phase, whereby an empirical irrotational and uniformly convergent horizontal velocity field interacting with an axially symmetric and height-invariant magnetic field reproduces the large-scale features of the much more complex convection observed inside sunspots.     

Automatic Detection and Extraction of Coronal Dimmings from SDO/AIA Data

The volume of data anticipated from the Solar Dynamics Observatory/Atmospheric Imaging Assembly (SDO/AIA) highlights the necessity for the development of automatic-detection methods for various types of solar activity. Initially recognized in the 1970s, it is now well established that coronal dimmings are closely associated with coronal mass ejections (CMEs), and they are particularly noted as a reliable indicator of front-side (halo) CMEs, which can be difficult to detect in white-light coronagraph data. Existing work clearly demonstrates that several properties derived from the analysis of coronal dimmings can give useful information about the associated CME. The development and implementation of an automated coronal-dimming region detection and extraction algorithm removes visual observer bias, however unintentional, from the determination of physical quantities such as spatial location, area, and volume. This allows for reproducible, quantifiable results to be mined from very large data sets. The information derived may facilitate more reliable early space-weather detection, as well as offering the potential for conducting large-sample studies focused on determining the geo-effectiveness of CMEs, coupled with analysis of their associated coronal dimming signatures. In this paper we present examples of both simple and complex dimming events extracted using our algorithm, which will be run as a module for the SDO/Computer Vision Centre. Contrasting and well-studied events at both the minimum and maximum of solar cycle 23 are identified in Solar and Heliospheric Observatory/Extreme ultra-violet Imaging Telescope (SOHO/EIT) data. A more recent example extracted from Solar and Terrestrial Relations Observatory/Extreme Ultra-Violet Imager (STEREO/EUVI) data is also presented, demonstrating the potential for the anticipated application to SDO/AIA data. The detection part of our algorithm is based largely on the principle of operation of the NEMO software, namely the detection of significant variation in the statistics of the EUV image pixels (Podladchikova and Berghmans in Solar Phys. 228, 265?–?284, 2005). As well as running on historic data sets, the presented algorithm is capable of detecting and extracting coronal dimmings in near real-time.     

The Observed Long- and Short-Term Phase Relation between the Toroidal and Poloidal Magnetic Fields in Cycle 23

The observed phase relations between the weak background solar magnetic (poloidal) field and strong magnetic field associated with sunspots (toroidal field) measured at different latitudes are presented. For measurements of the solar magnetic field (SMF) the low-resolution images obtained from Wilcox Solar Observatory are used and the sunspot magnetic field was taken from the Solar Feature Catalogues utilizing the SOHO/MDI full-disk magnetograms. The quasi-3D latitudinal distributions of sunspot areas and magnetic fields obtained for 30 latitudinal bands (15 in the northern hemisphere and 15 in the southern hemisphere) within fixed longitudinal strips are correlated with those of the background SMF. The sunspot areas in all latitudinal zones (averaged with a sliding one-year filter) reveal a strong positive correlation with the absolute SMF in the same zone appearing first with a zero time lag and repeating with a two- to three-year lag through the whole period of observations. The residuals of the sunspot areas averaged over one year and those over four years are also shown to have a well defined periodic structure visible in every two – three years close to one-quarter cycle with the maxima occurring at − 40° and + 40° and drifts during this period either toward the equator or the poles depending on the latitude of sunspot occurrence. This phase relation between poloidal and toroidal field throughout the whole cycle is discussed in association with both the symmetric and asymmetric components of the background SMF and relevant predictions by the solar dynamo models.