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At least 361 records · Page 20

Planetary Boundary Layer Height from AIRS and MERRA-2 Products at NASA GES DISC, and Insights from Data Intercomparison

The Atmospheric Infrared Sounder (AIRS) is the hyperspectral infrared sounder onboard NASA's Aqua satellite, launched in 2002. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the Aqua AIRS mission and the subsequent Suomi-National Polar-orbiting Partnership Cross-track Infrared Sounder (CrIS) mission. The Planetary Boundary Layer (PBL) Height is a new variable added in the AIRS Version 6 support product. It is derived based on gradients of the retrieved atmospheric thermodynamic profile, and gives the pressure at the top of PBL over the ocean. The GES DISC also provides services for the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) product generated by the Goddard Earth Observing System Model, Version 5 (GEOS-5) data assimilation system. The monthly PBL Height variable has been available in the Giovanni system, which is a Web-based application developed by the GES DISC providing a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data. In this work, we will present the monthly PBL Height data from AIRS and MERRA-2 and the services to support data intercomparison, such as access, plotting, subsetting, re-gridding, and generation of a multi-year monthly mean. We will also show intercomparison results, and evaluate whether (over the ocean) AIRS can observe PBL features similar to the reanalysis product at monthly and longer-term scales.

AIRS↗

Temperature Anomalies from the AIRS Product in Giovanni for the Climate Community

The Atmospheric Infrared Sounder (AIRS) mission began with the launch of Aqua in 2002. Over 15 years of AIRS products have been used by the climate research and application communities. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding Suomi National Polar-Orbiting Partnership (SNPP) Cross-track Infrared Sounder (CrIS) mission. We generated a Multi-year Monthly Mean and Anomaly product using 14 years of AIRS standard monthly product. The product includes Air Temperature at the Surface and Surface Skin Temperature, both in Ascending/Daytime and Descending/Nighttime mode. The temperature variables and their anomalies are deployed to Giovanni, a Web-based application developed by the GES DISC. Giovanni provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. It is also a powerful tool that stakeholders can use for decision support in planning and preparing for increased climate variability. In this presentation, we demonstrate the functions in Giovanni with use cases employing AIRS Multi-year Monthly Mean and Anomaly variables.

Giovann↗

Data and Code for: Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits

This repository contains the simulation outputs and processing scripts associated with the study of winter wheat traits across the United States, utilizing the Ecosys agroecosystem model. The dataset includes model results for both rainfed and irrigated winter wheat systems, supporting the findings presented in the manuscript titled "Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits." Data includes the original Ecosys simulation outputs (archived in .db format within the compressed .zip files) and extracted analysis data (stored in .pkl files for efficient processing). Python code for data processing and figure generation is provided in a Jupyter notebook. External Observational Datasets should refer to the following official repositories for the input and validation data used in this study. The eddy covariance data from the AmeriFlux network (https://ameriflux.lbl.gov/). Climate-forcing data of NLDAS-2 from NASA LDAS (https://ldas.gsfc.nasa.gov/nldas/nldas-2-forcing-data). Soil data from the Gridded Soil Survey Geographic Database (gSSURGO), available at (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database). Crop yields, planting and harvest dates from the USDA public databases (https://quickstats.nass.usda.gov/; https://webapp.rma.usda.gov/apps/actuarialinformationbrowser/CropCriteria.aspx). Satellite-derived SLOPE GPP data from ORNL DAAC (https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1786). Land use and crop progress information from the USDA Crop Data Layer and Crop Progress and Condition Gridded Layers (https://www.nass.usda.gov/Research_and_Science/). The Ecosys model code is available online at https://github.com/jinyun1tang/ECOSYS.

Wheat↗

Cosmic Ray Energetics and Mass (CREAM)

The CREAM instrument was flown on a Long Duration Balloon in Antarctica in December 2004 and January 2005, achieving a flight duration record of nearly 42 days. It detected and recorded cosmic ray primary particles ranging in type from hydrogen to iron nuclei and in energy from 1 TeV to several hundred TeV. With the data collected we will have the world's best measurement of the energy spectra and mass composition of nuclei in the primary cosmic ray flux at these energies, close to the astrophysical knee . The instrument utilized a thin calorimeter, a transition radiation detector and a timing charge detector, which also provided time-of-flight information. The responsibilities of our group have been with the timing charge detector (TCD), and with the data acquisition electronics and ground station support equipment. The TCD utilized fast scintillators to measure the charge of the primary cosmic ray before any interactions could take place within the calorimeter. The data acquisition electronics handled the output of the various detectors, in a fashion fully integrated with the payload bus. A space-qualified flight computer controlled the acquisition, and was used for preliminary trigger information processing and decision making. Ground support equipment was used to monitor the health of the payload, acquire and archive the data transmitted to the ground, and to provide real-time control of the instrument in flight.

Coutu, Stephane↗

Astrophysics science operations in the Great Observatories era

Plans for Astrophysics science operations during the decade of the nineties are described from the point of view of a scientist who wishes to make a space-borne astronomical observation or to use archival astronomical data. 'Science Operations' include the following: proposal preparation, observation planning and execution, data collection, data processing and analysis, and dissemination of results. For each of these areas of science operations, we derive technology requirements for the next ten to twenty years. The scientist will be able to use a variety of services and infrastructure, including the 'Astrophysics Data System.' The current status and plans for these science operations services are described.

Riegler, Guenter R.↗

The Ultra-Soft X-ray Background: A Probe of the Hot Interstellar Medium and the Local Bubble - ADP-99

The Ultra-Soft X-ray Telescope (UXT) was a sounding rocket mission flown three times in 1984 - 1986. At the beginning of the project, the data existed solely in form of raw telemetry data stored on 9 track tapes. The primary goal of this proposal has been to extract event files from the raw telemetry stream and to create instrument response models and calibrated spectra from it. We have completed this project, and the data will soon be available to all via the HEASARC archive of high-energy data at Goddard Space Flight Center. We are in the process of combining the results with the ALEXIS and DXS observations of the Local Bubble in modelling the 72 eV iron line (recently observed by the X-ray Quantum Calorimeter) and the carbon emission lines that are uniquely visible in this dataset. Our results agree with the XQC observation which predicts a maximum emission in the 72 eV iron lines that is below the limit observable with UXT. However, this leaves an open question as to what lines were responsible for the observed Be-band emission. The answer to this question will likely require more observations of soft X-rays with the Chandra LETGS and new atomic data models of potentially emitting ions.

Smith, Randall↗

Science Operations with the James Webb Space Telescope

The James Webb Space Telescope (JWST) will be a powerful space observatory whose four science instruments will deliver rich imaging and multiplexed spectroscopic datasets to the astronomical and planetary science communities. The ground segment for JWST, now being designed and built, will carry out JWST's science operations. The ground segment includes: (1) software that the scientific community will use to propose and specify new observations; (2) software that will schedule both science and calibration observations in a way that optimizes observing efficiency while managing the accumulation of momentum; (3) the infrastructure to regularly measure and maintain the telescope's wavefront; (4) orbit determination, ranging, and tracking; (5) communication via the Deep Space Network to command the observatory and retrieve scientific data; (6) onboard scripts that execute each observing program in an event-driven fashion, with occasional interruptions for targets of opportunity or time-critical observations; and (7) a system that processes and calibrates the data into science ready products, automatically recalibrates when calibrations improve, and archives the data for timely access by the principal investigator and later worldwide access by the scientific community. This ground system builds on experience from operating the Hubble Space Telescope, while solving challenges that are unique to the James Webb Space Telescope. In this paper, we describe the elements of the JWST ground system, how it will work operationally from the perspective of the observatory itself, and how a typical user will interact with the system to turn his/her idea into scientific discovery.

Rigby, Jane↗

Fireballs in the Sky: An Augmented Reality Citizen Science Program

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000 by 36 megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million square kilometers. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

Day, Brian↗

Collaborative Data Curation to Support the Multi-Mission Algorithm and Analysis Platform (MAAP)

Upcoming space-borne missions will offer unprecedented data about Earth but will also feature exponentially high data volumes. These high data volumes will change the way the scientific community works with data and will also create a unique need for improved data sharing and collaboration. NASA and ESA are working together to address these issues by collaboratively developing the Multi-Mission Algorithm and Analysis Platform (MAAP) to improve the understanding of global aboveground terrestrial carbon dynamics. The MAAP will support ESA’s BIOMASS mission, NASA’s GEDI mission and NASA/ISRO’s NISAR mission. The MAAP will be developed in two phases: a pilot phase and a full production phase. The pilot phase will demonstrate collaboration and basic capabilities. The pilot phase will focus on biomass relevant airborne and field campaign data. Two NASA teams are supporting the development of the MAAP. The MAAP engineering team is responsible for the development, maintenance and operations of the MAAP system while the MAAP data team ensures the ongoing quality of the data, metadata and other information provided in the MAAP. The MAAP data team also supports the ingest and archive of identified data to the MAAP platform. This poster describes the use case development process for the pilot MAAP and the data curated in support of those use cases. Additionally, this presentation will outline the pilot MAAP data ingest process and metadata curation effort along with efforts to ensure interoperability between ESA and NASA data and metadata.

Bugbee, Kaylin↗

Analyses and forecasts with LAWS winds

Horizontal fluxes of atmospheric water vapor are studied for summer months during 1989 and 1992 over North and South America based on analyses from European Center for Medium Range Weather Forecasts, US National Meteorological Center, and United Kingdom Meteorological Office. The calculations are performed over 20 deg by 20 deg box-shaped midlatitude domains located to the east of the Rocky Mountains in North America, and to the east of the Andes Mountains in South America. The fluxes are determined from operational center gridded analyses of wind and moisture. Differences in the monthly mean moisture flux divergence determined from these analyses are as large as 7 cm/month precipitable water equivalent over South America, and 3 cm/month over North America. Gridded analyses at higher spatial and temporal resolution exhibit better agreement in the moisture budget study. However, significant discrepancies of the moisture flux divergence computed from different gridded analyses still exist. The conclusion is more pessimistic than Rasmusson's estimate based on station data. Further analysis reveals that the most significant sources of error result from model surface elevation fields, gaps in the data archive, and uncertainties in the wind and specific humidity analyses. Uncertainties in the wind analyses are the most important problem. The low-level jets, in particular, are substantially different in the different data archives. Part of the reason for this may be due to the way the different analysis models parameterized physical processes affecting low-level jets. The results support the inference that the noise/signal ratio of the moisture budget may be improved more rapidly by providing better wind observations and analyses than by providing better moisture data.

Wang, Muyin↗

The Earth Radiation Budget (ERB) experiment - An overview

The development of ERB observational systems is traced from its beginnings in the late 1950's through to the current ERB on the Nimbus 7 satellite. The instruments comprising the current 22-channel ERB experiment are described in some detail. Noteworthy are the inclusion in one solar channel, of a self-calibrating cavity to measure the solar constant and the use of biaxial scanning telescopes to determine the angular reflection and emission model required for processing the narrow-angle radiometric data. A fairly detailed description of the prelaunch and in-flight calibrations is given along with an analysis of the radiometric performance of the instruments. The data processing system is traced with the aid of a schematic flow diagram showing the steps required to produce the many tape and microfilm products archived. Future plans for improving the quality and accuracy of the data products are discussed. Finally, the upcoming Earth Radiation Budget Experiment (ERBE) is briefly mentioned. It will be capable of simultaneously measuring the radiation budget from three satellites, each having a different equator crossing time and angle.

Jacobowitz, H.↗

Surface Biology & Geology Pathfinder Data Analysis Pipeline

NASA's future global orbital mission, currently in development as the Surface Biology and Geology (SBG) Designated Observable study, will acquire relatively high resolution solar-reflected spectroscopy and thermal infrared observations. Innovative processes must be utilized for handling the high volume of data anticipated to be collected, which is anticipated to exceed 100 terabytes/day, greater than NASA's total extant airborne hyperspectral data collection. Collecting, processing/re-processing, disseminating, and exploiting this volume of data presents new challenges. To begin addressing them, NASA is drawing upon the expertise developed from its astrophysics programs to address Earth science and applications. Specifically, NASA is adapting the science processing operations technology developed for the Kepler and TESS planet-hunting missions for imaging spectroscopy data processing. This technology development has been the foundation for the remarkable scientific successes of Kepler and TESS. The Kepler/TESS data processing technology provides a scalable architecture for robust, repeatable, and replicable science and application products while enabling the Earth science community to develop, test, and implement new algorithms. Our effort to leverage this existing capability has begun by ingesting data and applying workflows from the EO-1/Hyperion 17-year mission archive that provides globally sampled visible through shortwave infrared spectra that are representative of SBG data types and volumes. This pathfinding data processing system will help define the solutions to processing SBG data volumes and will enable the scientific community to interact with the data and processing pipeline to create new science products.

Jenkins, Jon↗

ARM Lead Mentor Selection Process

The Atmospheric Radiation Measurement (ARM) Program was created in 1989 with funding from the U.S. Department of Energy (DOE) to develop several highly instrumented ground stations to study cloud-formation processes and their influence on radiative transfer. This scientific infrastructure provides for fixed sites, mobile facilities, an aerial facility, and a data archive available for use by scientists worldwide through the ARM Climate Research Facility—a scientific user facility. The ARM Climate Research Facility currently operates more than 300 instrument systems that provide ground-based observations of the atmospheric column. To keep ARM at the forefront of climate observations, the ARM infrastructure depends heavily on instrument scientists and engineers, known as Mentors. Mentors must have an excellent understanding of instrumentation theory and operation for their instrument areas and have comprehensive knowledge of critical scale-dependent atmospheric processes. They must also possess the technical and analytical skills to develop new data retrievals that provide innovative approaches for creating research-quality data sets. The ARM Facility seeks the best overall qualified candidate, or team when appropriate, that can fulfill Mentor requirements in a timely manner. The roles and responsibilities of the ARM Instrument Operations Manager are provided in Appendix A. The key role and responsibilities and detailed responsibilities of ARM Lead Mentors are provided in Appendix B and Appendix C, respectively.

47 OTHER INSTRUMENTATION↗

Image-data-processing for earth resources - An overview

A total remote-sensing system comprises four distinct operations: data-acquisition, archiving, production, and dissemination of individual products, and extraction of the required information. The Landsat satellite system acquires data in several spectral bands, with a ground resolution of 80 meters (currently) or 30 meters (future). Radiometric and geometric corrections are normally applied, after which the data may be enhanced for photointerpretation or analyzed by computer. The accuracy of the analysis model for either is important. The extraction of information from remotely sensed data will generally be dependent on the use of it with other data such as maps or, perhaps, weather information. Methods are being developed to use the various data together in geographic data systems. The availability of remotely sensed data has encouraged the development of new models or analysis procedures for the use of this information.

Billingsley, F. C.↗

NASA Johnson Space Center Life Sciences Data System

The Life Sciences Project Division (LSPD) at JSC, which manages human life sciences flight experiments for the NASA Life Sciences Division, augmented its Life Sciences Data System (LSDS) in support of the Spacelab Life Sciences-2 (SLS-2) mission, October 1993. The LSDS is a portable ground system supporting Shuttle, Spacelab, and Mir based life sciences experiments. The LSDS supports acquisition, processing, display, and storage of real-time experiment telemetry in a workstation environment. The system may acquire digital or analog data, storing the data in experiment packet format. Data packets from any acquisition source are archived and meta-parameters are derived through the application of mathematical and logical operators. Parameters may be displayed in text and/or graphical form, or output to analog devices. Experiment data packets may be retransmitted through the network interface and database applications may be developed to support virtually any data packet format. The user interface provides menu- and icon-driven program control and the LSDS system can be integrated with other workstations to perform a variety of functions. The generic capabilities, adaptability, and ease of use make the LSDS a cost-effective solution to many experiment data processing requirements. The same system is used for experiment systems functional and integration tests, flight crew training sessions and mission simulations. In addition, the system has provided the infrastructure for the development of the JSC Life Sciences Data Archive System scheduled for completion in December 1994.

Rahman, Hasan↗

A Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) Determined from Phased Microphone Arrays

Current processing of acoustic array data is burdened with considerable uncertainty. This study reports an original methodology that serves to demystify array results, reduce misinterpretation, and accurately quantify position and strength of acoustic sources. Traditional array results represent noise sources that are convolved with array beamform response functions, which depend on array geometry, size (with respect to source position and distributions), and frequency. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method removes beamforming characteristics from output presentations. A unique linear system of equations accounts for reciprocal influence at different locations over the array survey region. It makes no assumption beyond the traditional processing assumption of statistically independent noise sources. The full rank equations are solved with a new robust iterative method. DAMAS is quantitatively validated using archival data from a variety of prior high-lift airframe component noise studies, including flap edge/cove, trailing edge, leading edge, slat, and calibration sources. Presentations are explicit and straightforward, as the noise radiated from a region of interest is determined by simply summing the mean-squared values over that region. DAMAS can fully replace existing array processing and presentations methodology in most applications. It appears to dramatically increase the value of arrays to the field of experimental acoustics.

Brooks, Thomas F.↗

A Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) Determined from Phased Microphone Arrays

Current processing of acoustic array data is burdened with considerable uncertainty. This study reports an original methodology that serves to demystify array results, reduce misinterpretation, and accurately quantify position and strength of acoustic sources. Traditional array results represent noise sources that are convolved with array beamform response functions, which depend on array geometry, size (with respect to source position and distributions), and frequency. The Deconvolution Approach for the Mapping of Acoustic Sources (DAMAS) method removes beamforming characteristics from output presentations. A unique linear system of equations accounts for reciprocal influence at different locations over the array survey region. It makes no assumption beyond the traditional processing assumption of statistically independent noise sources. The full rank equations are solved with a new robust iterative method. DAMAS is quantitatively validated using archival data from a variety of prior high-lift airframe component noise studies, including flap edge/cove, trailing edge, leading edge, slat, and calibration sources. Presentations are explicit and straightforward, as the noise radiated from a region of interest is determined by simply summing the mean-squared values over that region. DAMAS can fully replace existing array processing and presentations methodology in most applications. It appears to dramatically increase the value of arrays to the field of experimental acoustics.

Brooks, Thomas F.↗

NASA SETI microwave observing project: Sky Survey element

The SETI Sky Survey Observing Program is one of two complimentary strategies that NASA plans to use in its microwave Search for Extraterrestrial Intelligence (SETI). The primary objective of the sky survey is to search the entire sky over the frequency range of 1.0 to 10.0 GHz for evidence of narrow band signals of extraterrestrial intelligent origin. Frequency resolutions of 30 Hz or narrower will be used across the entire band. Spectrum analyzers with upwards of ten million channels are required to keep the survey time approximately 6 years. Data rates in excess of 10 megabits per second will be generated in the data taking process. Sophisticated data processing techniques will be required to determine the ever changing receiver baselines, and to detect and archive potential SETI signals. Existing radio telescopes, including several of NASA's Deep Space Network (DSN) 34 meter antennas located at Goldstone, CA and Tidbinbilla, Australia will be used for the observations. The JPL has the primary responsibility to develop and carry out the sky survey. In order to lay the foundation for the full scale SETI Sky Survey, a prototype system is being developed at the JPL. The system will be installed at the new 34-m high efficiency antenna at the Deep Space Station (DSS) 13 research and development station, Goldstone, CA, where it will be used to initiate the observational phase of the NASA SETI Sky Survey. It is anticipated that the early observations will be useful to test signal detection algorithms, scan strategies, and radio frequency interference rejection schemes. The SETI specific elements of the prototype system are: (1) the Wide Band Spectrum Analyzer (WBSA); a 2-million channel fast Fourier transformation (FFT) spectrum analyzer which covers an instantaneous bandpass of 40 MHz; (2) the signal detection processor; and (3) the SETI Sky Survey Manager, a network-based C-language environment that provides observatory control, performs data acquisition and analysis algorithms. A high level description of the prototype hardware and software systems will be given and the current status of the system development will be reported.

Klein, M. J.↗