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A short-term solar flare prediction model is built using predictor teams rather than an individual set of predictors. The information provided by the set of predictors could be redundant. So it is necessary to generate subsets of predictors which can keep the information constant. These subsets are called predictor teams. In the framework of rough set theory, predictor teams are constructed from sequences of the maximum horizontal gradient, the length of neutral line and the number of singular points extracted from SOHO/MDI longitudinal magnetograms. Because of the instability of the decision tree algorithm, prediction models generated by the C4.5 decision tree for different predictor teams are diverse. The flaring sample, which is incorrectly predicted by one model, can be correctly forecasted by another one. So these base prediction models are used to construct an ensemble prediction model of solar flares by the majority voting rule. The experimental results show that the predictor team can keep the distinguishability of the original set, and the ensemble prediction model can obtain better performance than the model based on the individual set of predictors.

The running cross-correlation coefficient between solar-cycle amplitudes and rise times at a certain cycle lag is found to vary in time, when using the smoothed monthly-mean sunspot group numbers available for 1610 – 1995. It may be negative or positive for different periods of time. The Waldmeier effect (in which the rise times decrease with amplitude) is also found to be very weak for some cycles. This result represents an observational constraint on solar-dynamo models and can help us better understand the long-term evolution of solar activity.

Solar flares are powered by the energy stored in magnetic fields, so evolutionary information of the magnetic field is important for short-term prediction of solar flares. However, the existing solar flare prediction models only use the current information of the active region. A sequential supervised learning method is introduced to add the evolutionary information of the active region into a prediction model. The maximum horizontal gradient, the length of the neutral line, and the number of singular points extracted from SOHO/MDI longitudinal magnetograms are used in the model to describe the nonpotentiality and complexity of the photospheric magnetic field. The evolutionary characteristics of the predictors are analyzed by using autocorrelation functions and mutual information functions. The analysis results indicate that a flare is influenced by the 3-day photospheric magnetic field information before flare eruption. A sliding-window method is used to add evolutionary information of the predictors into machine learning algorithms, then C4.5 decision tree and learning vector quantization are employed to predict the flare level within 48 hours. Experimental results indicate that the performance of the short-term solar flare prediction model within the sequential supervised learning framework is significantly improved.

High frequency acoustic waves have been suggested as a source of mechanical heating in the chromosphere. In this work the radial component of waves in the frequency interval 22mHz to 1mHz are investigated. Observations were performed using 2D spectroscopy in the spectral lines of Fe I 543.45nm and Fe I 543.29nm at the Vacuum Tower Telescope, Tenerife, Spain. Speckle reconstruction has been applied to the observations. We have used Fourier and wavelet techniques to identify oscillatory power. The energy flux is estimated assuming that all observed oscillations are acoustics running waves. We find that the estimated energy flux is not sufficient to cover the chromospheric radiative losses.

From a large number of SOHO/MDI longitudinal magnetograms, three physical measures including the maximum horizontal gradient, the length of the neutral line, and the number of singular points are computed. These measures are used to describe photospheric magnetic field properties including nonpotentiality and complexity, which is believed to be closely related to solar flares. Our statistical results demonstrate that solar flare productivity increases with nonpotentiality and complexity. Furthermore, the relationship between the flare productivity and these measures can be well fitted with a sigmoid function. These results can be beneficial to future operational flare forecast models.

We report here on the present state-of-the-art in algorithms used for resolving the 180° ambiguity in solar vector magnetic field measurements. With present observations and techniques, some assumption must be made about the solar magnetic field in order to resolve this ambiguity. Our focus is the application of numerous existing algorithms to test data for which the correct answer is known. In this context, we compare the algorithms quantitatively and seek to understand where each succeeds, where it fails, and why. We have considered five basic approaches: comparing the observed field to a reference field or direction, minimizing the vertical gradient of the magnetic pressure, minimizing the vertical current density, minimizing some approximation to the total current density, and minimizing some approximation to the field's divergence. Of the automated methods requiring no human intervention, those which minimize the square of the vertical current density in conjunction with an approximation for the vanishing divergence of the magnetic field show the most promise.

Magnetogram data of 517 bipolar active regions are analyzed to study latitude, magnetic flux, polarity separation dependence of tilt angle of the active regions with well-defined bipolar magnetic configurations. The data were obtained at Huairou Solar Observing Station in Beijing during 1988 to October 2001. By statistical analysis, it is found: (1) The tilt angle (ψ) is a function of the latitude (θ). Our observed result, sinψ=0.5 sin θ, is in good agreement with that obtained by Wang and Sheeley (1991). (2) The tilt angle is a function of the magnetic flux. The tilt angle increases (decreases) with flux increasing when the flux is smaller (larger) than 5×1021 Mx. (3) The tilt angle is a function of the magnetic polarity separation. The tilt angle increases (decreases) with the separation increasing when the separation is smaller (larger) than 8×109 cm. (4) The magnetic flux (φ in 1020 Mx) is correlated to the magnetic polarity separation (d in Mm), following φ20∼d 1.15. The result is close to the observed result of Wang and Sheeley (1989), φ20∼d 1.3. (5) The tilt fluctuations are independent of the latitude, but depend slightly on the separation, which is similar to the result obtained by Fisher, Fan, and Howard (1995). (6) The distribution function of the ratio of net magnetic flux to total magnetic flux is almost centered around zero net flux. The imbalance of magnetic flux is lower than 10% for 47% of our samples; 31% of active regions are in imbalance of the magnetic flux between 10% and 20%.

The photospheric vector magnetic fields, Hα and soft X-ray images of AR 7321 were simultaneously observed with the Solar Flare Telescope at Mitaka and the Soft X-ray Telescope of Yohkoh on October 26, 1992, when there was no important activity in this region. Taking the observed photospheric vector magnetic fields as the boundary condition, 3D magnetic fields above the photosphere were computed with a new numerical technique. Then quasi-separatrix layers (QSLs), i.e., regions where 3D magnetic reconnection takes place, were determined in the computed 3D magnetic fields. Since Yohkoh data and Mitaka data were obtained in well-arranged time sequences during the day, the evolution of 3D fields, Hα features and soft X-ray features in this region can be studied in detail. Through a comparison among the 3D magnetic fields, Hα features and soft X-ray features, the following results have been obtained: (a) Hα plages are associated with the portions of QSLs in the chromosphere; (b) diffuse coronal features (DCFs) and bright coronal features (BCFs) are morphologically confined by the coronal linkage of the field lines related to the QSLs; (c) BCFs are associated with a part of the magnetic field lines related to the QSLs. These results suggest that as the likely places where energy release may occur by 3D magnetic reconnection, QSLs play an important role in the chromospheric and coronal heating in this active region.

Longitudinal components of highly stressed magnetic fields in the active region NOAA 7640 on 26 December, 1993 have been studied. A physical parameter is suggested for describing the longitudinal components recorded in longitudinal magnetograms obtained before and after a 1N/M1.5 flare. By means of this parameter, quantitative comparisons among the pre-flare magnetograms, the post-flare magnetograms, and filtergrams (in Hβ) have been executed. The main results are as follows: firstly, the areas with high values of the parameter are near the regions with newly emerging magnetic flux. Secondly, the maximum values of the parameter in the areas and the sizes of the areas are evidently decreased after the flare. Finally, the original bright point of the flare is near the areas and the flare kernels cover the areas when the flare is growing. According to these results, we conclude that the variation of the parameter is connected with that of highly stressed magnetic fields in the region and directly related to the flare.

In this paper we introduce a new parameter, the shear angle of vector magnetic fields, Δψ, to describe the non-potentiality of magnetic fields in active regions, which is defined as the angle between the observed vector magnetic field and its corresponding current-free field. In the case of highly inclined field configurations, this angle is approximately equal to the ‘angular shear’, Δφ, defined by Hagyardet al. (1984). The angular shear, Δφ, can be considered as the projection of the shear angle, Δψ, on the photosphere. For the active region studied, the shear angle, Δψ, seems to have a better and neater correspondence with flare activity than does Δφ. The shear angle, Δψ, gives a clearer explanation of the non-potentiality of magnetic fields. It is a better measure of the deviation of the observed magnetic field from a potential field, and is directly related to the magnetic free energy stored in non-potential fields.