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Space Communications Emulation Facility

Establishing space communication between ground facilities and other satellites is a painstaking task that requires many precise calculations dealing with relay time, atmospheric conditions, and satellite positions, to name a few. The Space Communications Emulation Facility (SCEF) team here at NASA is developing a facility that will approximately emulate the conditions in space that impact space communication. The emulation facility is comprised of a 32 node distributed cluster of computers; each node representing a satellite or ground station. The objective of the satellites is to observe the topography of the Earth (water, vegetation, land, and ice) and relay this information back to the ground stations. Software originally designed by the University of Kansas, labeled the Emulation Manager, controls the interaction of the satellites and ground stations, as well as handling the recording of data. The Emulation Manager is installed on a Linux Operating System, employing both Java and C++ programming codes. The emulation scenarios are written in extensible Markup Language, XML. XML documents are designed to store, carry, and exchange data. With XML documents data can be exchanged between incompatible systems, which makes it ideal for this project because Linux, MAC and Windows Operating Systems are all used. Unfortunately, XML documents cannot display data like HTML documents. Therefore, the SCEF team uses XML Schema Definition (XSD) or just schema to describe the structure of an XML document. Schemas are very important because they have the capability to validate the correctness of data, define restrictions on data, define data formats, and convert data between different data types, among other things. At this time, in order for the Emulation Manager to open and run an XML emulation scenario file, the user must first establish a link between the schema file and the directory under which the XML scenario files are saved. This procedure takes place on the command line on the Linux Operating System. Once this link has been established the Emulation manager validates all the XML files in that directory against the schema file, before the actual scenario is run. Using some very sophisticated commercial software called the Satellite Tool Kit (STK) installed on the Linux box, the Emulation Manager is able to display the data and graphics generated by the execution of a XML emulation scenario file. The Emulation Manager software is written in JAVA programming code. Since the SCEF project is in the developmental stage, the source code for this type of software is being modified to better fit the requirements of the SCEF project. Some parameters for the emulation are hard coded, set at fixed values. Members of the SCEF team are altering the code to allow the user to choose the values of these hard coded parameters by inserting a toolbar onto the preexisting GUI.

Hill, Chante A.↗

Platform for Postprocessing Waveform-Based NDE

Taking advantage of the similarities that exist among all waveform-based non-destructive evaluation (NDE) methods, a common software platform has been developed containing multiple- signal and image-processing techniques for waveforms and images. The NASA NDE Signal and Image Processing software has been developed using the latest versions of LabVIEW, and its associated Advanced Signal Processing and Vision Toolkits. The software is useable on a PC with Windows XP and Windows Vista. The software has been designed with a commercial grade interface in which two main windows, Waveform Window and Image Window, are displayed if the user chooses a waveform file to display. Within these two main windows, most actions are chosen through logically conceived run-time menus. The Waveform Window has plots for both the raw time-domain waves and their frequency- domain transformations (fast Fourier transform and power spectral density). The Image Window shows the C-scan image formed from information of the time-domain waveform (such as peak amplitude) or its frequency-domain transformation at each scan location. The user also has the ability to open an image, or series of images, or a simple set of X-Y paired data set in text format. Each of the Waveform and Image Windows contains menus from which to perform many user actions. An option exists to use raw waves obtained directly from scan, or waves after deconvolution if system wave response is provided. Two types of deconvolution, time-based subtraction or inverse-filter, can be performed to arrive at a deconvolved wave set. Additionally, the menu on the Waveform Window allows preprocessing of waveforms prior to image formation, scaling and display of waveforms, formation of different types of images (including non-standard types such as velocity), gating of portions of waves prior to image formation, and several other miscellaneous and specialized operations. The menu available on the Image Window allows many further image processing and analysis operations, some of which are found in commercially-available image-processing software programs (such as Adobe Photoshop), and some that are not (removing outliers, Bscan information, region-of-interest analysis, line profiles, and precision feature measurements).

Roth, Don↗

Flux Cancelation: The Key to Solar Eruptions

Solar coronal jets are magnetically channeled eruptions that occur in all types of solar environments (e.g. active regions, quiet-Sun regions and coronal holes). Recent studies show that coronal jets are driven by the eruption of small-scare filaments (minifilaments). Once the eruption is underway magnetic reconnection evidently makes the jet spire and the bright emission in the jet base. However, the triggering mechanism of these eruptions and the formation mechanism of the pre-jet minifilaments are still open questions. In this talk, mainly using SDOAIA and SDOHIM data, first I will address the question: what triggers the jet-driving minifilament eruptions in different solar environments (coronal holes, quiet regions, active regions)? Then I will talk about the magnetic field evolution that produces the pre-jet minifilaments. By examining pre-jet evolutionary changes in line-of-sight HMI magnetograms while examining concurrent EUV images of coronal and transition-region emission, we find clear evidence that flux cancelation is the main process that builds pre-jet minifilaments, and is also the main process that triggers the eruptions. I will also present results from our ongoing work indicating that jet-driving minifilament eruptions are analogous to larger-scare filament eruptions that make flares and CMEs. We find that persistent flux cancellation at the neutral line of large-scale filaments often triggers their eruptions. From our observations we infer that flux cancelation is the fundamental process from the buildup and triggering of solar eruptions of all sizes.

Panesar, Navdeep K.↗

Flux Cancelation: The Key to Solar Eruptions

Solar coronal jets are magnetically channeled eruptions that occur in all types of solar environments (e.g. active regions, quiet-Sun regions and coronal holes). Recent studies show that coronal jets are driven by the eruption of small-scale filaments (minifilaments). Once the eruption is underway magnetic reconnection evidently makes the jet spire and the bright emission in the jet base. However, the triggering mechanism of these eruptions and the formation mechanism of the pre-jet minifilaments are still open questions. In this talk, mainly using SDO/AIA and SDO/HMI data, first I will address the question: what triggers the jet-driving minifilament eruptions in different solar environments (coronal holes, quiet regions, active regions)? Then I will talk about the magnetic field evolution that produces the pre-jet minifilaments. By examining pre-jet evolutionary changes in line-of-sight HMI magnetograms while examining concurrent EUV images of coronal and transition-region emission, we find clear evidence that flux cancellation is the main process that builds pre-jet minifilaments, and is also the main process that triggers the eruptions. I will also present results from our ongoing work indicating that jet-driving minifilament eruptions are analogous to larger-scale filament eruptions that make flares and CMEs. We find that persistent flux cancellation at the neutral line of large-scale filaments often triggers their eruptions. From our observations we infer that flux cancellation is the fundamental process for the buildup and triggering of solar eruptions of all sizes.

Panesar, Navdeep K.↗

Flux Cancelation: The Key to Solar Eruptions

Solar coronal jets are magnetically channeled eruptions that occur in all types of solar environments (e.g. active regions, quiet-Sun regions and coronal holes). Recent studies show that coronal jets are driven by the eruption of small-scare filaments (minifilaments). Once the eruption is underway magnetic reconnection evidently makes the jet spire and the bright emission in the jet base. However, the triggering mechanism of these eruptions and the formation mechanism of the pre-jet minifilaments are still open questions. In this talk, mainly using SDOAIA and SDOHIM data, first I will address the question: what triggers the jet-driving minifilament eruptions in different solar environments (coronal holes, quiet regions, active regions)? Then I will talk about the magnetic field evolution that produces the pre-jet minifilaments. By examining pre-jet evolutionary changes in line-of-sight HMI magnetograms while examining concurrent EUV images of coronal and transition-region emission, we find clear evidence that flux cancelation is the main process that builds pre-jet minifilaments, and is also the main process that triggers the eruptions. I will also present results from our ongoing work indicating that jet-driving minifilament eruptions are analogous to larger-scare filament eruptions that make flares and CMEs. We find that persistent flux cancellation at the neutral line of large-scale filaments often triggers their eruptions. From our observations we infer that flux cancelation is the fundamental process from the buildup and triggering of solar eruptions of all sizes.

Panesar, Navdeep K.↗

High-Resolution Gridded Level 3 Aerosol Optical Depth Data from MODIS

The state-of-art satellite observations of atmospheric aerosols over the last two decades from NASA's MODIS instruments have been extensively utilized in climate change and air quality research and applications. The operational algorithms now produce level 2 aerosol data at varying spatial resolutions (1, 3, and 10 km) and level 3 data at 1 degree. The local and global applications have been benefited from the coarse resolution gridded data sets (i.e., level 3, 1 degree), as it is easier to use since data volume is low and, several online and offline tools are readily available to access and analyze the data with minimal computing resources. At the same time, researchers who require data at much finer spatial scales have to go through a challenging process of obtaining, processing, and analyzing larger volumes of data sets that require high-end computing resources and coding skills. Therefore, we have created a high spatial resolution (HRG, 0.1x0.1 degree) daily and monthly aerosol optical depth (AOD) product by combining two MODIS operational algorithms, namely Deep Blue (DB) and Dark Target (DT). The new HRG AODs meets the accuracy requirements of level 2 AOD data and provide either the same or more spatial coverage on daily and monthly scales. The data sets are provided in daily and monthly files through open Ftp server with python scripts to read and map the data. The reduced data volume with an easy to use format and tools to access the data will encourage more users to utilize the data for research and applications.

aerosol↗

The kinematics of dense clusters of galaxies. 3: Comparison with cosmological models

We compare the combined distribution of 31 group and 25 cluster velocity dispersions with the ensemble of 32 models for the formation and evolution of large-scale structure examined by Weinberg & Cole (1992). The models include Gaussian and non-Gaussian initial fluctuations, different power law spectra (n = -1, n = 0, n = -2, 'pancake'), flat (Omega = 1) and open (Omega = 0.2) cosmologies, and unbiased (b(sub 8) = 1) and biased (b(sub 8) = 2) galaxy formation. The set of initial conditions we test, although limited, samples enough parameter space to indicate which general classes of models are consistent with the data. The two Gaussian, n = -1 models which best approximate the standard and open Cold Dark Matter (CDM) models do not match the observed distribution of velocity dispersions; models with b(sub 8) = 2 and Omega = 1 ('standard') or b(sub 8) = 1 and Omega = 0.2 ('open') predict too large a ratio of low to high velocity dispersion systems. A 'COBE-normalized' CDM model with b(sub 8) = 1 and Omega = 1 produces clusters with velocity dispersions higher than those measured. All three models overestimate the total abundance of systems.

Zabludoff, Ann I.↗

Gamma rays and the case for baryon symmetric big-bang cosmology

The baryon symmetric big-bang cosmologies offer an explanation of the present photon-baryon ratio in the universe, the best present explanation of the diffuse gamma-ray background spectrum in the 1 to 200 MeV range, and a mechanism for galaxy formation. In the context of an open universe model, the value of omega which best fits the present gamma-ray data is omega equals approx. 0.1 which does not conflict with upper limits on Comptonization distortion of the 3K background radiation. In regard to He production, evidence is discussed that nucleosynthesis of He may have taken place after the galaxies were formed.

Stecker, F. W.↗

HAPI: An API Standard for Accessing Heliophysics Time Series Data

Heliophysics data analysis often involves combining diverse science measurements, many of them captured as time series. Although there are now only a few commonly used data file formats, the diversity in mechanisms for automated access to and aggregation of such data holdings can make analysis that requires intercomparison of data from multiple data providers difficult. The Heliophysics Application Programmer's Interface (HAPI) is a recently developed standard for accessing distributed time series data to increase interoperability. The HAPI specification is based on the common elements of existing data services, and it standardizes the two main parts of a data service: the request interface and the response data structures. The interface is based on the REpresentational State Transfer (REST) or RESTful architecture style, and the HAPI specification defines five required REST endpoints. Data are returned via a streaming format that hides file boundaries; the metadata is detailed enough for the content to be scientifically useful, e.g., plotted with appropriate axes layout, units, and labels. Multiple mature HAPI-related open-source projects offer server-side implementation tools and client-side libraries for reading HAPI data in multiple languages (IDL, Java, MATLAB, and Python). Multiple data providers in the US and Europe have added HAPI access alongside their existing interfaces. Based on this experience, data can be served via HAPI with little or no information loss compared to similar existing web interfaces. Finally, HAPI has been recommended as a COSPAR standard for time series data delivery.

Robert S. Weigel↗

Open-Source Science-led Development of the AOS Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David M. Giles↗

Open-Source Science-led Development of the Atmosphere Observing System (AOS) Mission Science Data System (SDS)

The Earth System Observatory (ESO) Atmosphere Observing System (AOS) mission will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The AOS Science Data System (SDS) will be a system of systems developed within the Cloud to manage the research and operational processing of AOS mission orbital and suborbital sensors and curate these data for reprocessing (e.g., in near real-time or by collection) and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage. Further, AOS SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The AOS mission follows NASA’s lead in making a commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the AOS SDS system components will be developed with open-source concepts including components of SDS itself as well as AOS mission algorithms. Further, the AOS SDS assumes the role to lead and facilitate OSS activities for the AOS mission. This presentation describes the framework of the AOS SDS and its integral part in facilitating OSS within the AOS mission.

David Giles↗

Aerodynamic characteristics of sixteen electric, hybrid, and subcompact vehicles

An elementary electric and hybrid vehicle aerodynamic data base was developed using data obtained on sixteen electric, hybrid, and sub-compact production vehicles tested in the Lockheed-Georgia low-speed wind tunnel. Zero-yaw drag coefficients ranged from a high of 0.58 for a boxey delivery van and an open roadster to a low of about 0.34 for a current four-passenger proto-type automobile which was designed with aerodynamics as an integrated parameter. Vehicles were tested at yaw angles up to 40 degrees and a wing weighting analysis is presented which yields a vehicle's effective drag coefficient as a function of wing velocity and driving cycle. Other parameters investigated included the effects of windows open and closed, radiators open and sealed, and pop-up headlights. Complete six-component force and moment data are presented in both tabular and graphical formats. Only limited commentary is offered since, by its very nature, a data base should consist of unrefined reference material. A justification for pursuing efficient aerodynamic design of EHVs is presented.

Kurtz, D. W.↗

NASA Power: Global Solar Insolation, Meteorological Parameter Data, and Web Services to Support Sustainable Building Design and Operations

The buildings industry is currently striving to adopt green solutions to make infrastructure more energy-efficient in order to meet the 2050 net-zero climate goals. This planning requires reliable environmental datasets that are crucial in designing, building, and maintaining our world’s-built environment, as well as other energy-related processes and investments. This webinar for the National Institute of Building Sciences provides an overview of NASA’s Prediction Of Worldwide Energy Resources (POWER) Project that informs decision-making and development for sustainable building design and operations by enabling public open discovery, efficient access, and convenient distribution of NASA’s Earth Observations and global atmospheric model datasets. POWER’s datastore is comprised of solar radiation and surface meteorology parameters, spanning nearly 40 years of hourly data, that are easily accessible via several access methods and tools to support three focus areas: 1) renewable energy deployment and management, 2) sustainable infrastructure, and 3) agroclimatology applications. POWER and NASA Earth Science both plan future data parameters, updated tools, and improved observations that could directly support U.S. and international sustainable development goals, climate strategies, and building information modeling. To this end, solar data from several NASA projects and meteorological data from NASA assimilation models have already been reformatted and disseminated to the public via a user-friendly web GIS-enabled based data portal through the POWER Project. POWER data is analysis-ready and accessible through an Application Programming Interface (API), ArcGIS Image Services, and the project’s Data Access Viewer enhanced (DAVe), an interactive online tool. The POWER DAVe also features data consistent with ASHRAE Climate Design Conditions and has developed web image services showing Building Climate Zones and their variability. Through those tools, the data can be downloaded into multiple formats that support the infrastructure community, including CSV and Energy Plus Weather (EPW). POWER’s entire data product catalog is available through Amazon Web Services (AWS) Open Data Registry (ODR) via a free and publicly accessible Simple Storage Service (S3). This webinar provides a full overview of the NASA POWER Project's data and services developed in collaboration with the sustainable infrastructure community. Examples of how the renewable energy and building communities have utilized POWER data products to make decisions and a preview of future data product expansion, including climate projections, and web services will also be provided. Additionally, use case stories from our broad community of users will be presented.

Paul W. Stackhouse↗

Stoichiometry of the large conductance bacterial mechanosensitive channel of E. coli. A biochemical study

MscL, a 15 kDa transmembrane protein, is the only component involved in the formation of a 3 nS channel in the inner membrane of Escherichia coli that opens in response to mechanical or osmotic stress. While previous data had suggested that the functional MscL complex might be a hexamer, a recent crystallographic study of the MscL homologue from M. tuberculosis reveals a pentameric structure. The present work further examines the stoichiometry of the E. coli MscL using a variety of biochemical approaches. Detergent-purified 6His-MscL in solution and MscL in the membrane could be chemically crosslinked with the products displaying ladderlike patterns on SDS gels. Three crosslinking agents (EDC, DMS, and DMA) used at saturating concentrations invariably generated pentamers as the largest product. DSS produced additional bands corresponding to larger complexes although the pentamer band appeared to be the predominant product at high levels of crosslinker. It is not clear whether these extra bands reflect a difference in the crosslinking chemistry of DSS or whether its spacer arm is the longest of those used, or a combination of both facts. For the detergent-solubilized 6His-MscL both sedimentation equilibrium and gel chromatography showed the presence of multiple species. Thus the longer spacer arm could permit both intra- and intercomplex linkages. Nonetheless, the patterns obtained with all agents are consistent with and strongly suggest a pentameric organization for the MscL channel. Expression of MscL as genetically engineered double or triple subunit tandems yields low numbers of functional channels as compared to expressed monomers. The double-tandem assemblies must have an even number of subunits and crosslinking in the membrane confirmed hexamerization. Gel chromatography clearly demonstrated that the channels formed from the double tandems were larger than those formed from WT MscL, consistent with the native channel being pentameric. The observation that both double and triple tandems form channels of normal conductance implies that the pentameric assembly is to some degree independent of the number of subunit repeats in the polypeptide precursor. The channel is thus a pentameric core with the 'extra' subunits left out of the functional complex. From sedimentation equilibrium and size-exclusion chromatography, we also conclude that MscL complexes are not in a dynamic equilibrium with monomers, but are pre-assembled; and thus, their gating properties must result from changes in the conformation of the entire complex induced by the mechanical stress.

NASA Discipline Cell Biology↗

The Okhotsk Sea Kashevarov Bank Polynya: Its Dependence on Diurnal and Fortnightly Tides and its Initial Formation

Open water areas within the sea ice (polynyas) are sources of intense heat exchange between the ocean and the atmosphere. In this paper, we used microwave and visible/infrared satellite data together with a sea ice model to investigate the polynya opening mechanisms. The satellite data and the model show significant agreement and prove that tides play an active role in the polynya dynamics.

Martin, Seelye↗

Data Access Services that Make Remote Sensing Data Easier to Use

This slide presentation reviews some of the processes that NASA uses to make the remote sensing data easy to use over the World Wide Web. This work involves much research into data formats, geolocation structures and quality indicators, often to be followed by coding a preprocessing program. Only then are the data usable within the analysis tool of choice. The Goddard Earth Sciences Data and Information Services Center is deploying a variety of data access services that are designed to dramatically shorten the time consumed in the data preparation step. On-the-fly conversion to the standard network Common Data Form (netCDF) format with Climate-Forecast (CF) conventions imposes a standard coordinate system framework that makes data instantly readable through several tools, such as the Integrated Data Viewer, Gridded Analysis and Display System, Panoply and Ferret. A similar benefit is achieved by serving data through the Open Source Project for a Network Data Access Protocol (OPeNDAP), which also provides subsetting. The Data Quality Screening Service goes a step further in filtering out data points based on quality control flags, based on science team recommendations or user-specified criteria. Further still is the Giovanni online analysis system which goes beyond handling formatting and quality to provide visualization and basic statistics of the data. This general approach of automating the preparation steps has the important added benefit of enabling use of the data by non-human users (i.e., computer programs), which often make sub-optimal use of the available data due to the need to hard-code data preparation on the client side.

Lynnes, Christopher↗

Passive Microwave Signatures and Retrieval of High-Latitude Snowfall Over Open Oceans and Sea Ice: Insights From Coincidences of GPM and CloudSat Satellites

This article studies changes in microwave signals of oceanic snowfall in response to the formation of snow-covered sea ice using active and passive coincident data from the radar and radiometer onboard the CloudSat and the global precipitation measurement satellites. Using reanalysis data of liquid and ice water path as well as satellite retrievals of sea ice snow-cover depth, spectral regions are determined over which the snowfall signatures are likely to be obscured or falsely detected. Relying on an a priori database populated with the active–passive coincidences, a Bayesian snowfall retrieval algorithm is presented that links a k -nearest neighbor matching with the inverse Gaussian estimator used in the Goddard profiling algorithm. Without relying on any ancillary data of air temperature, the results demonstrate that over open oceans (sea ice), we can passively retrieve the CloudSat active snowfalls with a true positive rate of 92 (85%) and the root mean squared error of 0.24 (0.15) mm per h.

Sajad Vahedizade↗

How GES DISC is Opening Doors to Open Science

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of 12 NASA Earth Observing System data centers that document, process, archive, and distribute data from Earth science missions and related projects. GES DISC hosts numerous Earth Science products through various data formats and supports their access with several programming and website tools. The User Needs team at GES DISC is responsible for producing tutorials and resources to teach these tools, collecting and engaging with user feedback, and collaborating with other NASA data centers to enable science creation for everyone. This poster presentation outlines how GES DISC, and the User Needs team, are committed to enabling open science.

Christopher Battisto↗