ALBERT

Description: Helmet streamers on the sun were observed to be the site of coronal mass ejections, dynamic events that eject coronal plasma and magnetic fields into the solar wind. A two dimensional (azimuthally symmetric) helmet streamer configuration was developed by computing solutions of the time dependent magnetohydrodynamic (MHD) equations, for a specified magnetic flux distribution on the sun. The helmet streamer is not symmetric about the equator. The evolution of the configuration, when differential rotation is applied, was investigated. It was found that after many rotations the configuration does not reach a steady state, but disrupts recurrently with the ejection of a plasmoid. These results suggest that differential rotation may be one of the mechanisms by which mass ejections are initiated.

Description: The ground-based observing facilities of the National Solar Observatory (NSO) are reviewed from the perspective of joint observations with SOHO. A specific proposal is presented for observations of the HE-I 1083.0 nm line with the NASA/NSO spectromagnetograph and He 10830 video filtergraph/magnetograph in coordination with ultraviolet sensitive instruments on SOHO. The first task will be to look for associations of low-temperature transition-region lines with He 1083 nm absorption to investigate Andretta's conjecture, i.e. that the He 1083 nm line is formed in two layers where extreme ultraviolet radiation produced both in the low-temperature transition region (the upper layer) and in the surrounding corona products - a lower layer of absorption in the upper chromosphere.

Description: The white light coronograph (WLC) on Skylab provided an opportunity to study the corona at high spatial and temporal resolution. The spatial resolution of the instrument was approximately 25 cm with images taken approximately one per min. One set of images taken over a 10 min period was digitized, providing ten high spatial resolution images for analysis. The progress in data processing techniques available at the time was not sufficient to permit a reliable study of the fine structure in these images. Using current techniques an investigation of the sizes and lifetimes of the smallest scale features in the data was carried out. A preliminary analysis of an area between 2 and 3 Ro was completed. The results show that very narrow rays extend from at least 2 to 3 Ro. The narrowest of these rays has a thickness of approximately 75 cm. The contrast is so low that they are very close to the noise limit of the data. Most of the rays observed become unrecognizable after 10 min, although some remain visible over the entire time. Some notion seems to be detectable in the fine structure rays, but analysis of more frames will be needed to quantify these results.

Description: Filaments, flare sprays, prominences and 'post-flare' loops are familiar to H alpha observers in their frequent appearances 'in absorption', dark against the chromospheric background or plages. Observations of the X-ray corona are generally interpreted as due to emission via optically thin thermal bremsstrahlung. Several cases of X-ray coronal structures in Yohkoh images, due to high opacity, absorbing matter in coronograph loops, are presented. The presence of the absorbing matter, mixed with emitting matter, complicates inference of physical parameters such as emission measures in X-ray sources. In the case of well defined features, absorption provides an opportunity to infer density. Quantitative estimates of the attenuation due to the absorption in example features are presented.

Description: The causal association of major solar particle events seen at earth with coronal mass ejections (CME's), and not with solar flares, is discussed. Evidence that led to the demise of the flare dominated paradigm for major solar energetic particle events are described. The possibility of distinguishing particles from impulsive and gradual events using only observations is described. Particle acceleration at the CME level is discussed. Multi-spacecraft observations of CME events are described. Concerning the interplanetary CME, bidirectional proton events are discussed. Conclusions from progress in understanding the characteristics of solar energetic particles and their relation to the physical mechanisms of acceleration are given.

Description: Two dimensional magnetohydrodynamic simulations of the distortion of a magnetic flux tube, accelerated through ambient solar wind plasma, are presented. Vortices form on the trailing edge of the flux tube, and couple strongly to its interior. If the flux tube azimuthal field is weak, it deforms into an elongated banana-like shape after a few Alfven transit times. A significant azimuthal field component inhibits this distortion. In the case of magnetic clouds in the solar wind, it is suggested that the shape observed at 1 AU was determined by distortion of the cloud in the inner heliosphere. Distortion of the cloud beyond 1 AU takes many days. It is estimated that effective drag coefficients slightly greater than unity are appropriate for modeling flux tube propagation. Synthetic magnetic field profiles as would be seen by a spacecraft traversing the cloud are presented.

Description: Since radio propagation measurements using either natural or spacecraft radio signals are used for probing the solar wind in the vicinity of the sun, they represent a key tool for studying the interplanetary consequences of solar structure and dynamic phenomena. New information on the near sun consequences was obtained from radio scintillation observations of coherent spacecraft signals. The results covering density fluctuations, fractional density fluctuations, coronal streamers, heliospheric current sheets, coronal mass ejections and interplanetary shocks are reviewed. A joint ICE S-band (13 cm wavelength) Doppler scintillation measurement with the SOHO white-light coronograph (LASCO) is described.

Description: The use of hyperspectral data to determine the abundance of constituents in a certain portion of the Earth's surface relies on the capability of imaging spectrometers to provide a large amount of information at each pixel of a certain scene. Today, hyperspectral imaging sensors are capable of generating unprecedented volumes of radiometric data. The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), for example, routinely produces image cubes with 224 spectral bands. This undoubtedly opens a wide range of new possibilities, but the analysis of such a massive amount of information is not an easy task. In fact, most of the existing algorithms devoted to analyzing multispectral images are not applicable in the hyperspectral domain, because of the size and high dimensionality of the images. The application of neural networks to perform unsupervised classification of hyperspectral data has been tested by several authors and also by us in some previous work. We have also focused on analyzing the intrinsic capability of neural networks to parallelize the whole hyperspectral unmixing process. The results shown in this work indicate that neural network models are able to find clusters of closely related hyperspectral signatures, and thus can be used as a powerful tool to achieve the desired classification. The present work discusses the possibility of using a Self Organizing neural network to perform unsupervised classification of hyperspectral images. In sections 3 and 4, the topology of the proposed neural network and the training algorithm are respectively described. Section 5 provides the results we have obtained after applying the proposed methodology to real hyperspectral data, described in section 2. Different parameters in the learning stage have been modified in order to obtain a detailed description of their influence on the final results. Finally, in section 6 we provide the conclusions at which we have arrived.

Description: During the last several years, a number of airborne and satellite hyperspectral sensors have been developed or improved for remote sensing applications. Imaging spectrometry allows the detection of materials, objects and regions in a particular scene with a high degree of accuracy. Hyperspectral data typically consist of hundreds of thousands of spectra, so the analysis of this information is a key issue. Mathematical morphology theory is a widely used nonlinear technique for image analysis and pattern recognition. Although it is especially well suited to segment binary or grayscale images with irregular and complex shapes, its application in the classification/segmentation of multispectral or hyperspectral images has been quite rare. In this paper, we discuss a new completely automated methodology to find endmembers in the hyperspectral data cube using mathematical morphology. The extension of classic morphology to the hyperspectral domain allows us to integrate spectral and spatial information in the analysis process. In Section 3, some basic concepts about mathematical morphology and the technical details of our algorithm are provided. In Section 4, the accuracy of the proposed method is tested by its application to real hyperspectral data obtained from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imaging spectrometer. Some details about these data and reference results, obtained by well-known endmember extraction techniques, are provided in Section 2. Finally, in Section 5 we expose the main conclusions at which we have arrived.

Description: This report describes the transitional activities of the JPL Analysis Center.