Results for “spatial data visualization” — Page 12

NASA NTRS1977

Resampling study

The author has identified the following significant results. The nearest neighbor and cubic convolution resampling algorithms were applied to a variety of images extracted from LANDSAT MSS data. A comparison of the results demonstrated that (1) cubic convolution can cause spreading of small features and can introduce noticeable overshoot (ringing) into the data; (2) cubic convolution attenuates the high spatial frequencies compared to the original and nearest neighbor resampled data; and (3) cubic convolution generally produces photographic products of superior visual quality. The effects of the resampling algorithms on multispectral classification were not conclusively determined due to the small number of images tested.

Ferneyhough, D. G.↗

NASA NTRS1984

Anaysis of the quality of image data required by the LANDSAT-4 Thematic Mapper and Multispectral Scanner

The spatial, geometric, and radiometric qualities of LANDSAT 4 thematic mapper (TM) and multispectral scanner (MSS) data were evaluated by interpreting, through visual and computer means, film and digital products for selected agricultural and forest cover types in California. Multispectral analyses employing Bayesian maximum likelihood, discrete relaxation, and unsupervised clustering algorithms were used to compare the usefulness of TM and MSS data for discriminating individual cover types. Some of the significant results are as follows: (1) for maximizing the interpretability of agricultural and forest resources, TM color composites should contain spectral bands in the visible, near-reflectance infrared, and middle-reflectance infrared regions, namely TM 4 and TM % and must contain TM 4 in all cases even at the expense of excluding TM 5; (2) using enlarged TM film products, planimetric accuracy of mapped poins was within 91 meters (RMSE east) and 117 meters (RMSE north); (3) using TM digital products, planimetric accuracy of mapped points was within 12.0 meters (RMSE east) and 13.7 meters (RMSE north); and (4) applying a contextual classification algorithm to TM data provided classification accuracies competitive with Bayesian maximum likelihood.

Colwell, R. N.↗

NASA NTRS1993

Design and test of an object-oriented GIS to map plant species in the Southern Rockies

Elevational and latitudinal shifts occur in the flora of the Rocky Mountains due to long term climate change. In order to specify which species are successfully migrating with these changes, and which are not, an object-oriented, image-based geographic information system (GIS) is being created to animate evolving ecological regimes of temperature and precipitation. Research at the Earth Data Analysis Center (EDAC) is developing a landscape model that includes the spatial, spectral and temporal domains. It is designed to visualize migratory changes in the Rocky Mountain flora, and to specify future community compositions. The object-oriented database will eventually tag each of the nearly 6000 species with a unique hue, intensity, and saturation value, so their movements can be individually traced. An associated GIS includes environmental parameters that control the distribution of each species in the landscape, and satellite imagery is used to help visualize the terrain. Polygons for the GIS are delineated as landform facets that are static in ecological time. The model manages these facets as a triangular irregular net (TIN), and their analysis assesses the gradual progression of species as they migrate through the TIN. Using an appropriate climate change model, the goal will be to stop the modeling process to assess both the rate and direction of species' change and to specify the changing community composition of each landscape facet.

Morain, Stanley A.↗

NASA NTRS2016

National Climate Assessment - Land Data Assimilation System (NCA-LDAS) Data and Services at NASA GES DISC

The National Climate Assessment-Land Data Assimilation System (NCA-LDAS) is an Integrated Terrestrial Water Analysis, and is one of NASAs contributions to the NCA of the United States. The NCA-LDAS has undergone extensive development, including multi-variate assimilation of remotely-sensed water states and anomalies as well as evaluation and verification studies, led by the Goddard Space Flight Centers Hydrological Sciences Laboratory (HSL). The resulting NCA-LDAS data have recently been released to the general public and include those from the Noah land-surface model (LSM) version 3.3 (Noah-3.3) and the Catchment LSM version Fortuna-2.5 (CLSM-F2.5). Standard LSM output variables including soil moistures temperatures, surface fluxes, snow cover depth, groundwater, and runoff are provided, as well as streamflow using a river routing system. The NCA-LDAS data are archived at and distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The data can be accessed via HTTP, OPeNDAP, Mirador search and download, and NASA Earth data Search. To further facilitate access and use, the NCA-LDAS data are integrated into the NASA Giovanni, for quick visualization and analysis, and into the Data Rods system, for retrieval of time series of long time periods. The temporal and spatial resolutions of the NCA-LDAS data are, respectively, daily-averages and 0.125x0.125 degree, covering North America (25N 53N; 125W 67W) and the period January 1979 to December 2015. The data files are in self-describing, machine-independent, CF-compliant netCDF-4 format.

data assimiliation↗

NASA NTRS2017

Challenges in Obtaining and Visualizing Satellite Level 2 Data in GIS

Satellite data products are important for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if the satellite data are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite data products provided by NASA and other organizations. One way to help users better understand the satellite data is to provide data along with Images, including accurate pixel coverage area delineation, and science team recommended quality screening for individual geophysical parameters. However, there are challenges of visualizing remote sensed non-gridded products: (1) different geodetics of space-borne instruments (2) data often arranged in a long-track and a cross-track axes (3) spatially and temporally continuous data chunked into granule files: data for a portion (or all) of a satellite orbit (4) no general rule of resampling or interpolations to a grid (5) geophysical retrieval only based on pixel center location without shape information. In this presentation, we will unravel a new Goddard Earth Sciences Data and Information Services Center (GES DISC) Level 2 (L2) visualization on-demand service. The service's front end provides various visualization and data accessing capabilities, such as overlay and swipe of multiply variables and subset and download of data in different formats. The backend of the service consists of Open Geospatial Consortium (OGC) standard-compliant Web Mapping Service (WMS) and Web Coverage Service. The infrastructure allows inclusion of outside data sources served in OGC compliant protocols and allows other interoperable clients, such as ArcGIS clients, to connect to our L2 WCS/WMS.

GI↗

NASA NTRS2021

PIXLISE-C: Exploring The Data Analysis Needs of NASA Scientists for Mineral Identification

NASA JPL scientists working on the micro x-ray fluorescence (microXRF) spectroscopy data collected from Mars surface perform data analysis to look for signs of past microbial life on Mars. Their data analysis workflow mainly involves identifying mineral com- pounds through the element abundance in spatially distributed data points. Working with the NASA JPL team, we identified pain points and needs to further develop their existing data visualization and analysis tool. Specifically, the team desired improvements for the process of creating and interpreting mineral composition groups. To address this problem, we developed an interactive tool that enables scientists to (1) cluster the data using either manual lasso-tool selection or through various machine learning clustering algorithms, and (2) compare the clusters and individual data points to make informed decisions about mineral compositions. Our preliminary tool supports a hybrid data analysis workflow where the user can manually refine the machine-generated clusters.

Davidoff, Scott↗

NASA NTRS1994

New Perspectives on Active Tectonics: Observing Fault Motion, Mapping Earthquake Strain Fields, and Visualizing Seismic Events in Multiple Dimensions Using Satellite Imagery and Geophysical Data Base

By rapidly alternating displays of SPOT satellite images acquired on 27 July 1991 and 25 July 1992 we are able to see spatial details of terrain movements along fault breaks associated with the 28 June 1992 Landers, California earthquake that are virtually undetectable by any other means.

fields↗

DOE OSTI2015

TU-AB-204-04: Advances in CBCT for Breast Imaging

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both the likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

TU-AB-204-02: Advances in C-Arm CBCT for Cardiac Interventions

This symposium highlights advanced cone-beam CT (CBCT) technologies in four areas of emerging application in diagnostic imaging and image-guided interventions. Each area includes research that extends the spatial, temporal, and/or contrast resolution characteristics of CBCT beyond conventional limits through advances in scanner technology, acquisition protocols, and 3D image reconstruction techniques. Dr. G. Chen (University of Wisconsin) will present on the topic: Advances in C-arm CBCT for Brain Perfusion Imaging. Stroke is a leading cause of death and disability, and a fraction of people having an acute ischemic stroke are suitable candidates for endovascular therapy. Critical factors that affect both the likelihood of successful revascularization and good clinical outcome are: 1) the time between stroke onset and revascularization; and 2) the ability to distinguish patients who have a small volume of irreversibly injured brain (ischemic core) and a large volume of ischemic but salvageable brain (penumbra) from patients with a large ischemic core and little or no penumbra. Therefore, “time is brain” in the care of the stroke patients. C-arm CBCT systems widely available in angiography suites have the potential to generate non-contrast-enhanced CBCT images to exclude the presence of hemorrhage, time-resolved CBCT angiography to evaluate the site of occlusion and collaterals, and CBCT perfusion parametric images to assess the extent of the ischemic core and penumbra, thereby fulfilling the imaging requirements of a “one-stop-shop” in the angiography suite to reduce the time between onset and revascularization therapy. The challenges and opportunities to advance CBCT technology to fully enable the one-stop-shop C-arm CBCT platform for brain imaging will be discussed. Dr. R. Fahrig (Stanford University) will present on the topic: Advances in C-arm CBCT for Cardiac Interventions. With the goal of providing functional information during cardiac interventions, significant effort has been expended to improve the quantitative accuracy of C-arm CBCT reconstructions. The challenge is to improve image quality while providing very short turnaround between data acquisition and volume data visualization. Corrections for x-ray scatter, view aliasing and patient motion that require no more than 2 iterations keep processing time short while reducing artifact. Fast, multi-sweep acquisitions can be used to permit assessment of left ventricular function, and visualization of radiofrequency lesions created to treat arrhythmias. Workflows for each imaging goal have been developed and validated against gold standard clinical CT or histology. The challenges, opportunities, and limitations of the new functional C-arm CBCT imaging techniques will be discussed. Dr. W. Zbijewski (Johns Hopkins University) will present on the topic: Advances in CBCT for Orthopaedics and Bone Health Imaging. Cone-beam CT is particularly well suited for imaging of musculoskeletal extremities. Owing to the high spatial resolution of flat-panel detectors, CBCT can surpass conventional CT in imaging tasks involving bone visualization, quantitative analysis of subchondral trabecular structure, and visualization and monitoring of subtle fractures that are common in orthopedic radiology. A dedicated CBCT platform has been developed that offers flexibility in system design and provides not only a compact configuration with improved logistics for extremities imaging but also enables novel diagnostic capabilities such as imaging of weight-bearing lower extremities in a natural stance. The design, development and clinical performance of dedicated extremities CBCT systems will be presented. Advanced capabilities for quantitative volumetric assessment of joint space morphology, dual-energy image-based quantification of bone composition, and in-vivo analysis of bone microarchitecture will be discussed, along with emerging applications in the diagnosis of arthritis and osteoporosis and assessment of novel therapies. Finally, Dr. J. Boone (UC Davis) will present on the topic: Advances in CBCT for Breast Imaging. Breast CT has been studied as an imaging tool for diagnostic breast evaluation and for potential breast cancer screening. The breast CT application lends itself to CBCT because of the small dimensions of the breast, the tapered shape of the breast towards higher cone angle, and the fact that there are no bones in the breast. The performance of various generations of breast CT scanners developed in recent years will be discussed, focusing on advances in spatial resolution and image noise characteristics. The results will also demonstrate the results of clinical trials using both computer and human observers. Learning Objectives: Understand the challenges, key technological advances, and emerging opportunities of CBCT in: Brain perfusion imaging, including assessment of ischemic stroke Cardiac imaging for functional assessment in cardiac interventions Orthopedics imaging for evaluation of musculoskeletal trauma, arthritis, and osteoporosis Breast imaging for screening and diagnosis of breast cancer. Work presented in this symposium includes research support by: Siemens Healthcare (Dr. Chen); NIH and Siemens Healthcare (Dr. Fahrig); NIH and Carestream Health (Dr. Zbijewski); and NIH (Dr. Boone)

60 APPLIED LIFE SCIENCES↗

NASA NTRS2016

Simultaneous Boundary-Layer Transition, Tip Vortex, and Blade Deformation Measurements of a Rotor in Hover

This paper describes simultaneous optical measurements of a sub-scale helicopter rotor in the U.S. Army Hover Chamber at NASA Ames Research Center. The measurements included thermal imaging of the rotor blades to detect boundary layer transition; retro-reflective background-oriented schlieren (RBOS) to visualize vortices; and stereo photogrammetry to measure displacements of the rotor blades, to compute spatial coordinates of the vortices from the RBOS data, and to map the thermal imaging data to a three-dimensional surface grid. The test also included an exploratory effort to measure flow near the rotor tip by tomographic particle image velocimetry (tomo PIV)an effort that yielded valuable experience but little data. The thermal imaging was accomplished using an image-derotation method that allowed long integration times without image blur. By mapping the thermal image data to a surface grid it was possible to accurately locate transition in spatial coordinates along the length of the rotor blade.

Rotorcraft↗

NASA NTRSDate not supplied

Examining 18 Years of Journal Publications to Characterize Usage Modes of Giovanni, a Versatile Earth Science Data Web Service

Introduction to Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) Giovanni … is a Web-based visualization and analysis system that provides 22 different visualization and analysis options, operating on thousands of Earth science data variables generated by satellite instrument observations and from related model datasets Giovanni … was originally conceived as a data exploration tool, but its ease-of-use, analytical capabilities (spatial and temporal subsetting, multi-period averaging, data mapping and time-series, and more) have led to its use as a multi-discipline research tool Giovanni … provided unprecedented access to NASA Earth science data for many different disciplines, AND is still providing a simple way to find, analyze, visualize, and utilize such data for a wide spectrum of research topics

James Acker↗

NASA NTRS2018

GMI-IPS: Processing & Visualization Software Used in ATom DC-8 Aircraft Studies

NASA's Atmospheric Tomography Mission (ATom) deployed in each of the four seasons during 2016-2018, the DC-8 aircraft in order to establish global-scale datasets intended to improve the representation of chemically reactive gases in global atmospheric chemistry models (ACMs). The Global Modeling Initiative (GMI) executed simulations for each ATom flight using the GMI Chemistry Transport Model (GMI-CTM) to provide species concentrations of chemical gases along the DC-8 flight transects. To solve the problem of translating the GMI-CTM simulation data to the unique spatial resolutions of each ATom flight, the GMI ICARTT Processing Software (GMI-IPS) was developed.The GMI-IPS is written in Python and provides data processing, flight extraction, and visualization support for aircraft research projects using ICARTT format, which is a standard format for airborne instrument data. Additionally, the GMI-IPS interpolates global gridded model data from Hierarchical Data Format (HDF) to ICARTT compatible flight transects. Software classes for instruments and collections provided by the ATom DC-8 aircraft such as MER10, MMS, etc. are derived from a common base class. Other functionality provided by the GMI-IPS are: deriving missing flight entries along a transect, reading ICARTT entries from file, and providing Python data structures for storing flight and model information, and more.The GMI-IPS is GIT source controlled, has approximately 30,000 lines of code, and supports parallelization across data collections. It delivered GMI-CTM data for more than forty distinct DC-8 aircraft flights that took place under ATom. The output ICARTT files adhere to format standard V1.1, and pass the scan utility provided by NASA LaRC Airborne Science Data for Atmospheric Composition. This presentation will include a software and methods overview, and results from ATom, including assessments using the GMI-CTM showing how well observations from ATom flight transects represent a broader region.

Damon, M. R.↗

NASA NTRS2004

Experimental Test-Bed for Intelligent Passive Array Research

This document describes the test-bed designed for the investigation of passive direction finding, recognition, and classification of speech and sound sources using sensor arrays. The test-bed forms the experimental basis of the Intelligent Small-Scale Spatial Direction Finder (ISS-SDF) project, aimed at furthering digital signal processing and intelligent sensor capabilities of sensor array technology in applications such as rocket engine diagnostics, sensor health prognostics, and structural anomaly detection. This form of intelligent sensor technology has potential for significant impact on NASA exploration, earth science and propulsion test capabilities. The test-bed consists of microphone arrays, power and signal distribution modules, web-based data acquisition, wireless Ethernet, modeling, simulation and visualization software tools. The Acoustic Sensor Array Modeler I (ASAM I) is used for studying steering capabilities of acoustic arrays and testing DSP techniques. Spatial sound distribution visualization is modeled using the Acoustic Sphere Analysis and Visualization (ASAV-I) tool.

Solano, Wanda M.↗

NASA NTRS2006

Spatial and Temporal Coherence of SeaWiFS Chlorophyll Concentration Anomalies in the North Atlantic Bloom (1998-2005) Examined with Giovanni

The availability of climatological chlorophyll-a concentration data products from the SeaWiFS mission spanning the eight-year mission period allowed the creation of a climatological anomaly analysis function in Giovanni, the GES DISC Interactive Online Visualization and ANalysis Infrastructure. This study utilizes the Giovanni anomaly analysis function to examine mesoscale anomalies in the North Atlantic Ocean during the springtime North Atlantic Bloom. This examination indicates that areas exhibiting positive anomalies and areas exhibiting negative anomalies are coherent over significant spatial scales, with relatively abrupt boundaries between areas with positive and negative anomalies. Year-to-year variability in anomaly "intensity" can be caused by either variability in the temporal occurrence of the bloom peak or by variability in the peak chlorophyll concentration in a particular area. The study will also discuss the feasibility of combining chlorophyll anomaly analysis with other data types.

Acker, James G.↗

DOE OSTI2026

Urban Parameters Los Angeles County 100m version 2

132 Urban parameters based on building physical dimensions and location were generated for the city of Los Angeles at 100m resolution using the NATURF model. To use the binary file with WRF, the binary file and the index file must be placed in their own directory in WRF_GEOG and accessed in the same way NUDAPT44 would be accessed. The kmz file can be visualized on Google Earth.

Sweet-Breu, Levi [Baylor University]↗

NASA NTRS1998

Efficient Encoding and Rendering of Time-Varying Volume Data

Visualization of time-varying volumetric data sets, which may be obtained from numerical simulations or sensing instruments, provides scientists insights into the detailed dynamics of the phenomenon under study. This paper describes a coherent solution based on quantization, coupled with octree and difference encoding for visualizing time-varying volumetric data. Quantization is used to attain voxel-level compression and may have a significant influence on the performance of the subsequent encoding and visualization steps. Octree encoding is used for spatial domain compression, and difference encoding for temporal domain compression. In essence, neighboring voxels may be fused into macro voxels if they have similar values, and subtrees at consecutive time steps may be merged if they are identical. The software rendering process is tailored according to the tree structures and the volume visualization process. With the tree representation, selective rendering may be performed very efficiently. Additionally, the I/O costs are reduced. With these combined savings, a higher level of user interactivity is achieved. We have studied a variety of time-varying volume datasets, performed encoding based on data statistics, and optimized the rendering calculations wherever possible. Preliminary tests on workstations have shown in many cases tremendous reduction by as high as 90% in both storage space and inter-frame delay.

CODING↗

DOE OSTI2023

Molecular-Weight-Dependent Infiltration and Adsorption of Polymers into Nanochannels

The mesoporous silica shell coating hydrogenolysis nano-catalysts alters the molecular weight distributions of cleaved polymer chains compared to catalysts without a shell. The shell, composed of radially aligned narrow cylindrical nanopores, reduces the formation of low-valued gaseous products and increases the median molecular weight of the product, thus enhancing the value of the products for polymer upcycling. Here, to understand the role of the mesoporous shell, we have studied the spatial distribution of polystyrene chains, used as a model polymer, in the nanochannels in both the melt phase and solution phase. In the melt, we observed from small-angle X-ray scattering experiments that the infiltration rate of the polymer into the nanochannels is inversely proportional to the molecular weight, which is consistent with theory. In theta solution experiments using UV–vis spectroscopy, we found that the shell significantly enhances polymer adsorption compared to nanoparticles without pores. In addition, the degree of polymer adsorption is not a monotonic function of molecular weight but initially increases with the molecular weight before eventually decreasing. The molecular weight for the peak adsorption increases with the pore diameter. This adsorption behavior is rationalized as resulting from a balance between the mixing entropy gain by surface adsorption and the conformational entropy penalty incurred by chains confined in the nanochannels. The spatial distribution of polymer chains in the nanochannels is visualized by energy-dispersive X-ray spectroscopy (EDX), and inverse Abel-transformed data reveals a less uniform polymer distribution along the primary pore axis for longer chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

THE BLOB CONNECTION: SEARCHING FOR LOW CORONAL SIGNATURES OF SOLAR POST-CME BLOBS

Bright linear structures, thought to be indicators of a current sheet (CS), are often seen in Large Angle and Spectrometric Coronagraph (LASCO) on the Solar and Heliospheric Observatory (SOHO) white-light data in the wake of coronal mass ejections (CMEs). In a subset of these post-CME structures, relatively bright blobs are seen moving outward along the rays. These blobs have been interpreted as consequences of the plasmoid instability in the CS, and can help us to understand the dynamics of the reconnection. We examine several instances, taken largely from the SOHO /LASCO CME-rays Catalog, where these blobs are clearly visible in white-light data. Using radially filtered, difference, wavelet enhanced, and multiscale Gaussian normalized images to visually inspect Solar Dynamics Observatory /Atmospheric Imaging Assembly (AIA) data in multiple wavelengths, we look for signatures of material that correspond both temporally and spatially to the later appearance of the blobs in LASCO/C2. Constraints from measurements of the blobs allow us to predict the expected count rates in DN pixel{sup −1} s{sup −1} for each AIA channel. The resulting values would make the blobs bright enough to be detectable at 1.2 R {sub ⊙}. However, we do not see conclusive evidence for corresponding blobs in the AIA data in any of the events. We do the same calculation for the “cartwheel CME,” an event in which blobs were seen in X-rays, and find that our estimated count rates are close to those observed. We suggest several possibilities for the absence of the EUV blobs including the formation of the blob higher than the AIA field of view, blob coalescence, and overestimation of blob densities.

79 ASTRONOMY AND ASTROPHYSICS↗