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NASA NTRSDate not supplied

Laying the Foundations for FAIR-er Science: ISA and the LSDA Data Submission Process in NASA's Evolving Data Management Environment

The Life Sciences Data Archive (LSDA) archives data resulting from research on the effects of spaceflight on humans and the development of countermeasures to mitigate spaceflight hazards. Archivists work with researchers to ensure that unique and high value data products and their metadata are preserved and managed to support current and future research. Currently, LSDA is updating its procedures and data submission requirements in response to the evolving data preservation environment at NASA. LSDA is implementing best practices for research data management through the establishment of clear data submission guidelines, integration of the FAIR (Findability, Accessibility, Interoperability, Reusability) principles, and use of the ISA (Investigation, Study, Assay) research metadata framework for data discoverability and transparency into the data management processes. These changes directly impact LSDA’s requirements for research data submissions. The newly revised Research Data Submission Agreement (RDSA), formerly the Data Submission Agreement (DSA), introduces ISA-compatible metadata collection standards to LSDA’s process. Adherence to LSDA’s data submission guidelines enhances the FAIR-ness of the repository’s collections for future users. This presentation will discuss (1) how submission of research data and associated metadata are impacted by current data management policies, (2) benefits of the adoption of FAIR principles and the ISA metadata framework for retrospective studies utilizing existing LSDA datasets and historic data collections, and (3) the support LSDA will provide to researchers during this transition.

LSDA↗

NASA NTRSDate not supplied

The Future of NASA Earth Science in the Commercial Cloud: Challenges and Opportunities

NASA produces a large volume and variety of data products that are used every day to support research, decision making, and education. The widespread use of NASA’s Earth Science data is enabled by NASA’s Earth Science Data System (ESDS) program, which oversees the archiving and distribution of these data and invests in the development of new data systems and tools. However, NASA’s current approach to Earth Science data distribution — based on distributed institutional archives with individual on-premises high-performance computing capabilities — faces some significant challenges, including massive increases in data volume from upcoming missions, a greater need for transdisciplinary science that synthesizes many different kinds of observations, and a push to make science more open, inclusive, and accessible. To address these challenges, NASA is aggressively migrating its Earth Science data and related tools and services into the commercial cloud. Migration of data into the commercial cloud can significantly improve NASA’s existing data system capabilities by (1) providing more flexible options for storage and compute (including rapid, as-needed access to state-of-the-art capabilities); (2) by centralizing and standardizing data access, which gives all of NASA’s institutional data centers access to all of each other’s datasets; and (3) by facilitating “analysis-in-place”, whereby users can bring their own computational workflows and tools to the data rather than having to maintain their own copies of NASA datasets. However, migration to the commercial cloud also poses some significant challenges, including (1) managing costs under a “pay-as-you-go” model; (2) incompatibility with existing tools and data formats with object-based storage and network access; (3) vendor lock-in; (4) challenges with data access for workflows that mix on-premise and cloud computing; and (5) standardization for highly diverse data as is present in NASA’s data archive. I conclude with two examples of recent NASA activities showcasing capabilities enabled by the commercial cloud: An interactive analysis and development platform for analyzing airborne imaging spectroscopy data, and a new collection of tools and services for data discovery, analysis, publication, and data-driven storytelling (Visualization, Exploration, and Data Analysis, VEDA).

Alexey N Shiklomanov↗

NASA NTRS2024

Completion of Dragonfly PPF Testing in the NFAC 80x120-Foot Wind Tunnel

The Dragonfly entry, descent, and landing team (JHU-APL, NASA Langley Research Center, NASA Ames Research Center, Sikorsky Aircraft) recently completed testing in the National Full-Scale Aerodynamics Complex (NFAC) 80x120-Foot Wind Tunnel. The facility is located at NASA Ames Research Center and is operated by the U.S. Air Force's Arnold Engineering Development Complex. The test was designed to simulate conditions of Preparation for Powered (PPF), an approximately 10-minute period during which the Lander is posed in front of the Backshell at low subsonic airspeeds, all under the main parachute, and the rotors are used to null residual Lander yaw rates prior to release i. e. de-spin. The Lander (approximately 50% scale) that previously was tested in the NASA Langley 14x22 Wind Tunnel in 2023 was used for the NFAC test with a new Backshell designed and fabricated specifically for NFAC. This memorandum summarizes execution of the test: objective, facility and models, instrumentation and data products, test procedure, and completed test matrix. Other future documents will include a test report (JHU-APL) and documentation of data processing/analysis and computational fluid dynamics (CFD) comparisons to test data (Sikorsky).

Dragonfly↗

NASA NTRS1999

Current and Future Plans of the NASA Data Assimilation Office (DAO)

The mission of the Data Assimilation Office (DAO) is to advance the state of the art of data assimilation and produce research-quality assimilated data sets which make optimal use of space-based observations. Development efforts over the last few years have focused on delivering a production data assimilation system in support of NASA's Terra platform. That system, called the Goddard Earth Observing System - version 2 or GEOS-2, represents a major upgrade to the baseline GEOS-1 system employed in NASA's first reanalysis effort. GEOS-2 includes a physical-space three dimensional variational analysis algorithm (the Physical-space Statistical Analysis System or PSAS) and numerous improvements to the general circulation model. The latter include a Soil-Vegetation-Atmosphere Transfer (SVAT) land surface scheme, a level 2.5 moist turbulence scheme and new Short Wave (SW) and Long Wave (LW) radiation code. The system also includes an off-line ozone assimilation system, and the capability to assimilate scatterometer surface winds, and TIROS Operational Vertical Sounder (TOVS) and Special Sensor Microwave Imager (SSM/I) moisture data. GEOS-2 is currently run at 1 degree horizontal resolution and 48 levels extending to O.Olmb. Experimental versions of GEOS-2 are run with a global stretched grid allowing enhanced (e.g. 1/4 deg) regional resolution. Other capabilities being developed include, the assimilation of Tropical Rainfall Measuring Mission (TRMM) precipitation and Global Positioning System (GPS) data, an off-line land surface assimilation system, and a retrospective analysis scheme. The DAO is also engaged in a number of collaborative efforts to help accelerate the development of the next generation data assimilation system. These include, a joint modeling effort between the DAO and NCAR/CGDD to develop a new Global Circulation Model (GCM), and a Department of Energy Lawrence Livermore National Laboratory (DOE/LLNL) collaboration on model parallelization. Plans for the next reanalysis will be discussed in the context of current and near term system quality and computing capabilities, and the need for multiple reanalysis products.

Atlas, Robert↗

NASA NTRS2010

Aerosol Mapping From Space: Strengths, Limitations, and Applications

The aerosol data products from the NASA Earth Observing System's MISR and MODIS instruments provide significant advances in regional and global aerosol optical depth (AOD) mapping, aerosol type measurement, and source plume characterization from space. These products have been and are being used for many applications, ranging from regional air quality assessment, to aerosol air mass type identification and evolution, to wildfire smoke injection height and aerosol transport model validation. However, retrieval uncertainties and coverage gaps still limit the quantitative constraints these satellite data place on some important questions, such as global-scale long-term trends and direct aerosol radiative forcing. Major advances in these areas seem to require a different paradigm, involving the integration of satellite with suborbital data and with models. This presentation will briefly summarize where we stand, and what incremental improvements we can expect, with the current MISR and MODIS aerosol products, and will then elaborate on some initial steps aimed at the necessary integration of satellite data with data from other sources and with chemical transport models.

Kahn, Ralph↗

NASA NTRS2012

Estimation and Bias Correction of Aerosol Abundance using Data-driven Machine Learning and Remote Sensing

Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies.

Malakar, Nabin K.↗

NASA NTRS2003

Data Assimilation Office (DAO) Operational Analyses and Reanalyses for Coordinated Enhanced Observing Period (CEOP)

The DAO operational assimilation system has produced and archived gridded data since 1998, and will continue through the CEOP period. However, major system upgrades and new assimilation variables will significantly affect the surface energy balance and data product. These changes will be discussed and the prospects for a CEOP reanalysis will be presented. W e will also review the data currently available and describe how to access the data.

Bosilovich, M.↗

NASA NTRS2018

Systems and Methods for Advanced Rapid Imaging and Analysis for Earthquakes

Many embodiments provide a hybrid data processing system (HySDS) of an end-to-end geodetic imaging data system enabling near-real-time science, assessment, response, and rapid recovery. The HySDS may be an operation data processing system that integrates data from many different geodetic data sources and/or sensors, including interferometric synthetic aperture radar (InSAR), GPS, pixel tracking, seismology, and/or modeling, and processes the data to generate actionable high quality science data products. The HySDS may provide for an automated imaging and analysis capabilities that is able to handle the imminent increases in raw data from new and existing geodetic monitoring sensor systems.

Owen, Susan Ethel↗

NASA NTRSDate not supplied

An Overview of NASA’s Airborne and Field Data Resource Center

A key recommendation from NASA’s 2022 Airborne and Field Data Workshop called for the development of a virtual Resource Center for all stakeholders across the data lifecycle of airborne and field Earth observations. The agency’s Earth Science Data and Information System (ESDIS) Project and Airborne Data Management Group (ADMG) have worked in concert to establish the newly launched NASA Airborne and Field Data Resource Center (AFDRC) to provide a single entry point for a wide assortment of information on and the effective, responsible stewardship of non-satellite observational data. The AFDRC compiles access to many existing resources, but does so in a newly organized way that integrates availability to increase efficiency and holistic understanding while simplifying users’ experience. Initially launched in fall of 2023, the AFDRC is a NASA Earthdata domain website that clarifies several previously disparate resources and provides newly updated information, including: Learning Resources: Educational resources to broaden understanding of the role airborne and field observations play in advancing understanding of our planet and NASA’s role in collecting and archiving these data. Support for data users to Find and Access Data: Advanced contextual browse/search capabilities that efficiently link researchers to data products suitable for their science objectives - this includes linking to NASA’s Catalog of Archived Suborbital Earth Science Investigations (CASEI). Working with Data: Tools specific to individual types of suborbital Earth Science data and their (inter-)disciplinary communities to provide access as well as guidance for their application. Stewardship Responsibilities: Resources for data producers with to lessen requirement burdens at the time of data transfer, and information for data stewards with consistent, authoritative guidance on best practices and agency- and/or community- specific archival procedures. This presentation will give an overview of the motivation for NASA’s AFDRC, approach for the design and content, iterative community-driven improvements, promote the use of the AFDRC, and solicit additional feedback from airborne and field data user communities.

Sara Lubkin↗

NASA NTRSDate not supplied

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral instruments produce high-resolution and information-dense radiance spectra, thus offering the opportunity to reduce uncertainties in retrieval products. An optimal estimation-based cirrus cloud optical and microphysical product retrieval is under development for the NASA Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the Earth Surface Mineral Dust Source Investigation (EMIT) instruments, and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder). The spectral coverage of all three instruments includes the ultraviolet, visible, and near-infrared. In this study a very fast radiative transfer model, the Principal Component-based Radiative Transfer Model in the solar spectral region (PCRTM-Solar), is used for forward modeling computations. This will reduce the computational burden in the forward radiance and Jacobian calculations as the cost function is minimized, enabling the entire AVIRIS, EMIT, and CLARREO-Pathfinder spectral range to be used in the optimal estimation framework. Using the entire spectrum will maximize the information content, resulting in a more robust and more accurate retrieval. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water. Preliminary results will be shown.

Jeffrey Mast↗

NASA NTRSDate not supplied

Towards an Optimal Estimation Retrieval of Cirrus Cloud Optical and Microphysical Properties Using Hyperspectral Shortwave Instruments and A Fast Radiative Transfer Algorithm

Cirrus cloud retrieval products (here, cloud optical depth, effective particle size, and cloud top height) are important inputs into numerical weather and climate models. Uncertainties in such retrieval products, as a matter of course, propagate downstream, impacting model calculations. Improvements in high-quality global cirrus cloud optical and microphysical data products from satellite observations are needed to understand and reduce retrieval uncertainties. Hyperspectral shortwave instruments produce high-resolution and information-dense spectra, thus offering the opportunity to reduce uncertainties in retrieval products. We are in the process of developing a retrieval that uses the very fast Principal Component Radiative Transfer Model in the solar spectral region (PCRTM-Solar) in the forward model calculations. This retrieval will use measured reflectances from the NASA Earth Surface Mineral Dust Source Investigation (EMIT) and the forthcoming Climate Absolute Radiance and Refractivity Observatory Pathfinder (CLARREO-Pathfinder) instruments. In this manuscript we present progress towards a reference retrieval employing a widely used, verified, accurate, yet computationally slower radiative transfer modeling technique. The reference retrieval, while too slow for using the complete hyperspectral measurement, will allow us to study the behavior of retrieval products and help us verify results from our in-development fast retrieval. Both retrievals will use the optimal estimation retrieval framework. In this manuscript we present results from an uncertainty analysis considering three uncertainty sources for a cirrus cloud retrieval in the form of error covariance matrices: reflectance uncertainty due to water vapor, the reflectance uncertainty due to ice crystal scattering assumptions, and the instrument measurement uncertainty. Results show that the uncertainty due to habit selection is the largest, while that due to water vapor is at most 0.6% relative to channel reflectance. As a first step, the retrieval is being designed for single layer ice clouds over open ocean water.

Cirrus cloud↗

NASA NTRS2021

SNPP VIIRS Day Night Band: Ten Years of On-Orbit Calibration and Performance

Aboard the polar-orbiting SNPP satellite, the VIIRS instrument has been in operation since launch in October 2011. It is a visible and infrared radiometer with a unique panchromatic channel capability designated as a day-night band (DNB). This channel covers wavelengths from 0.5 to 0.9 µm and is designed with a near-constant spatial resolution for Earth observations 24 h a day. The DNB operates at 3 gain stages (low, middle, and high) to cover a large dynamic range. An onboard solar diffuser (SD) is used for calibration in the low gain stage, and to enable the derivation of gain ratios between the different stages. In this paper, we present the SNPP VIIRS DNB calibration performed by the NASA VIIRS characterization support team (VCST). The DNB calibration algorithms are described to generate the calibration coefficient look up tables (LUTs) for the latest NASA Level 1B Collection 2 products. We provide an evaluation of DNB on-orbit calibration performance. This activity supports the NASA Earth science community by delivering consistent VIIRS sensor data products via the Land Science Investigator-led Processing Systems, including the SD degradation applied for DNB calibrations in detector gain and gain ratio trending. The DNB stray light contamination and its correction are highlighted. Performance validations are presented using comparisons to the calibration methods employed by NOAA’s operational Interface Data Processing Segment. Further work on stray light corrections is also discussed.

VIIRS↗

NASA NTRS2016

The Geoscience Spaceborne Imaging Spectroscopy Technical Committees Calibration and Validation Workshop

Calibration is the process of quantitatively defining a system's responses to known, controlled signal inputs, and validation is the process of assessing, by independent means, the quality of the data products derived from those system outputs [1]. Similar to other Earth observation (EO) sensors, the calibration and validation of spaceborne imaging spectroscopy sensors is a fundamental underpinning activity. Calibration and validation determine the quality and integrity of the data provided by spaceborne imaging spectroscopy sensors and have enormous downstream impacts on the accuracy and reliability of products generated from these sensors. At least five imaging spectroscopy satellites are planned to be launched within the next five years, with the two most advanced scheduled to be launched in the next two years [2]. The launch of these sensors requires the establishment of suitable, standardized, and harmonized calibration and validation strategies to ensure that high-quality data are acquired and comparable between these sensor systems. Such activities are extremely important for the community of imaging spectroscopy users. Recognizing the need to focus on this underpinning topic, the Geoscience Spaceborne Imaging Spectroscopy (previously, the International Spaceborne Imaging Spectroscopy) Technical Committee launched a calibration and validation initiative at the 2013 International Geoscience and Remote Sensing Symposium (IGARSS) in Melbourne, Australia, and a post-conference activity of a vicarious calibration field trip at Lake Lefroy in Western Australia.

Ong, Cindy↗

NASA NTRS2012

Multi-Satellite Synergy for Aerosol Analysis in the Asian Monsoon Region

Atmospheric aerosols represent one of the greatest uncertainties in environmental and climate research, particularly in tropical monsoon regions such as the Southeast Asian regions, where significant contributions from a variety of aerosol sources and types is complicated by unstable atmospheric dynamics. Although aerosols are now routinely retrieved from multiple satellite Sensors, in trying to answer important science questions about aerosol distribution, properties, and impacts, researchers often rely on retrievals from only one or two sensors, thereby running the risk of incurring biases due to sensor/algorithm peculiarities. We are conducting detailed studies of aerosol retrieval uncertainties from various satellite sensors (including Terra-/ Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, SeaWiFS, and Calipso-CALIOP), based on the collocation of these data products over AERONET and other important ground stations, within the online Multi-sensor Aerosol Products Sampling System (MAPSS) framework that was developed recently. Such analyses are aimed at developing a synthesis of results that can be utilized in building reliable unified aerosol information and climate data records from multiple satellite measurements. In this presentation, we will show preliminary results of. an integrated comparative uncertainly analysis of aerosol products from multiple satellite sensors, particularly focused on the Asian Monsoon region, along with some comparisons from the African Monsoon region.

Ichoku, Charles↗

NASA NTRS1971

Infrared spectrometry studies: Spectral digital data acquisition system (1971 version)

The construction of the Stanford Spectral Digital Data Acquisition System is described. The objective of the system is to record both the spectral distribution of incoming radiation from the rock samples measured by the spectroradiometer (Exotech Model 10-34 Circular Variable Filter Infrared Spectroradiometer) together with other weather information. This system is designed for both laboratory and field measurement programs. The multichannel inputs (8 channels) of the system are as follows: Ch 1 the Spectro-radiometer, Ch 2 the radiometer (PRT-5), and Ch 3 to Ch 8 for the weather information. The system records data from channel 1 and channel 2 alternately for 48 times, before a fast sweep across the six weather channels, to form a single scan in the scan counter. The operation is illustrated in a block diagram, and the theory of operation is described. The outputs are written on a 7-track magnetic tape with IBM compatible form. The format of the tape and the playback computer programs are included. The micro-pac digital modules and a CIPHER model 70 tape recorder (Cipher Data Products) are used. One of the major characteristics of this system is that it is externally clocked by the spectroradiometer instead of taking data at intervals of various wavelengths by using internal-clocking.

Lu, L.↗

NASA NTRS1974

Nineteen hundred seventy three significant accomplishments

Data collected by the Skylab remote sensing satellites was used to develop applications techniques and to combine automatic data classification with statistical clustering methods. Continuing research was concentrated in the correlation and registration of data products and in the definition of the atmospheric effects on remote sensing. The causes of errors encountered in the automated classification of agricultural data are identified. Other applications in forestry, geography, environmental geology, and land use are discussed.

Source record↗

NASA NTRS1984

SAGE and SAM II measurements of global stratospheric aerosol optical depth and mass loading

Several volcanic eruptions between November 1979 and April 1981 have injected material into the stratosphere. The SAGE and SAM II satellite systems have measured, with global coverage, the 1-micron extinction produced by this material, and examples of the data product are shown in the form of global maps of stratospheric optical depth and altitude-latitude plots of zonal mean extinction. These data, and that for the volcanically quiet period in early 1979, have been used to determine the changes in the total stratospheric mass loading. Estimates have also been made of the contribution to the total aerosol mass from each eruption. It has been found that between 1979 and mid-1981, the total stratospheric aerosol mass increased from a background level of approximately 570,000 metric tons to a peak of approximately 1,300,000 metric tons.

Kent, G. S.↗

NASA NTRS2005

CEDAR/TIMED: Thermospheric Vertical Wind Observations from Three Sites in the Northern Auroral Zone

The objective of this project was to operate ground based Fabry-Perot Interferometers at several points under the auroral zone to analyze and quantify the vertical wind in the thermosphere. These measurements were made in conjunction with TIMED, especially GUVI data, to relate the observed wind to the resulting mixing and compositional changes in the thermosphere. The ground based wind measurements were obtained from a scanning Doppler imager (SDI) in Poker Flat, and a vertically aligned Fabry Perot Imager (FPI) in Inuvik. A third FPI at Eagle, Alaska, was operated for a brief overlapping period as well. The SDI at Poker Flat had been in operation for several years, and was continued to run with little support from this grant. The much more expensive operation, maintenance, and data acquisition of the remote Inuvik FPI was made possible with funds from this project. During the 2003/2004 and 2004/2005 seasons, we operated the Inuvik FPI from September to April during hours of darkness. Two trips to service the instrument were required per year, and a local caretaker was funded to help keep the instrument going during the winter seasons. The data were transfered via modem and phone line to Poker Flat and were then analyzed to obtain wind and temperature at the altitude of the auroral green line OI(557.7 nm). The final data product was archived and transferred to the GEDDS system at Poker Flat were it is available on the web: http://gedds.pfrr.alaska.edu/. The data set is also available from the CEDAR data base: http://cedarweb.hao.ucar.edu/.

Lummerzheim, D.↗