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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Investigating the Utility of Hyperspectral Sounders in the 9.6 μm Band to Improve Ozone Analyses

Currently, hyperspectral sounder brightness temperatures assimilated in the Goddard Earth Observing System - Atmospheric Data Assimilation System (GEOS-ADAS) are limited to assimilating temperature and moisture. The ozone sensitive 9.6 micron region is sensed by several hyperspectral sounders including AIRS (Atmospheric InfraRed Sounder), IASI (Infrared Atmospheric Sounding Interferometer), and CrIS (Cross-track Infrared Sounder). Direct assimilation of brightness temperatures in the 9.6 micron region have been used previously to improve ozone analyses. This has recently been achieved by ECMWF (European Centre for Medium-Range Weather Forecast) (Dragani and McNally, 2013; Eresmaa et al., 2017), and while every system presents its challenges, it should be possible to take advantage of this spectral region using the GEOS-ADAS. For this study, channels were selected from available operational subsets evaluating information content, and minimizing inter-channel correlation. Additionally, information such as channel selections made by other studies, and vertical sensitivities of ozone and temperature were considered in developing the study. The analyses produced show improvements verified against ozonesondes taken from SHADOZ (Southern Hemisphere Additional Ozonesondes), and WOUDC (World Ozone and Ultraviolet Data Center). The addition of ozone channels does degrade forecast skill in the Tropics, on the border of statistical significance. Overall, the addition of these channels in some form could improve ozone analyses in the GEOS-ADAS.

Karpowicz, Bryan M.↗
NASA NTRS2019

Federated Cloud Challenges in NASA's Earth Science Data Systems (Why So Difficult?)

NASA is presented with a number of opportunities and challenges in federating its Earth Science Data Systems in the burgeoning world of cloud computing. Cloud hosting of Earth Science data provides a new way of bringing data together, at least from a virtual location sense, and is one of the main motives for NASA to host data there. However, NASA is also faced with a Big Data Variety challenge, brought on by the variety of the EO datasets in its archives. This diversity requires many diverse science archives to service the different science communities. As a result, nearly every major function in the Earth Observing System Data and Information System (EOSDIS) must also be federated across its data centers. This pattern is repeated with many of the outside agencies and organizations that EOSDIS federates with, such as the Committee for Earth Observing Satellites, leading to pioneering work on "deep federation" in a joint project with the European Space Agency to develop a Multi-Mission Algorithm and Analysis Platform.

Lynnes, Christopher↗
NASA NTRS2018

Northern Hemisphere Surface Freeze-Thaw Product from Aquarius L-Band Radiometers

In the Northern Hemisphere, seasonal changes in surface freeze–thaw (FT) cycles are an important component of surface energy, hydrological and eco-biogeochemical processes that must be accurately monitored. This paper presents the weekly polar-gridded Aquarius passive L-band surface freeze–thaw product (FT-AP) distributed on the Equal-Area Scalable Earth Grid version 2.0, above the parallel 50 N, with a spatial resolution of 36 km36 km. The FT-AP classification algorithm is based on a seasonal threshold approach using the normalized polarization ratio, references for frozen and thawed conditions and optimized thresholds. To evaluate the uncertainties of the product, we compared it with another satellite FT product also derived from passive microwave observations but at higher frequency: the resampled 37 GHz FT Earth Science Data Record (FTESDR). The assessment was carried out during the overlapping period between 2011 and 2014. Results show that 77.1% of their common grid cells have an agreement better than 80 %. Their differences vary with land cover type (tundra, forest and open land) and freezing and thawing periods. The best agreement is obtained during the thawing transition and over forest areas, with differences between product mean freeze or thaw onsets of under 0.4 weeks. Over tundra, FT-AP tends to detect freeze onset 2–5 weeks earlier than FT-ESDR, likely due to FT sensitivity to the different frequencies used. Analysis with mean surface air temperature time series from six in situ meteorological stations shows that the main discrepancies between FT-AP and FT-ESDR are related to false frozen retrievals in summer for some regions with FT-AP. The Aquarius product is distributed by the U.S. National Snow and Ice Data Center (NSIDC) at https://nsidc.org/data/aq3_ft/versions/5 with the DOI https://doi.org/10.5067/OV4R18NL3BQR.

Prince, Michael↗
NASA NTRS2019

SLR Data: from Station to User

The ILRS provides laser ranging data and products on an operational basis to geodesy analysts as well as a broader scientific community. ILRS is one of four services within the International Association for Geodesy (IAG) supporting space geodesy. IAG established these services to facilitate international cooperation and scientific research: Networks, Data centers, Analysis groups. Services perform successful operations through cooperation of many international organizations, leveraging their respective resources to all levels of service functionality.

Noll, Carey↗
NASA NTRS2019

Improvements to Ozone Analyses Using Hyperspectral Sounders in the 9.6 μm Band

Previously, hyperspectral sounder brightness temperatures assimilated in the Goddard Earth Observing System Atmospheric Data Assimilation System (GEOS-ADAS) were limited to assimilating temperature and moisture. The ozone sensitive 9.6 m region is sensed by several hyperspectral sounders including AIRS (Atmospheric InfraRed Sounder), IASI (Infrared Atmospheric Sounding Interferometer), and CrIS (Cross-track Infrared Sounder). Direct assimilation of brightness temperatures in the 9.6 m region have been operational at ECMWF for several years (Dragani and McNally, 2013; Eresmaa et al., 2017). With this study, similar improvements using the GEOS-ADAS are presented. Channels were selected from available operational subsets evaluating information content and minimizing inter-channel correlation. Additionally, information such as channel selections made by other studies, and vertical sensitivities of ozone and temperature were considered in developing the study. The analyses produced show improvements verified against ozonesondes taken from SHADOZ (Southern Hemisphere Additional Ozonesondes), and WOUDC (World Ozone and Ultraviolet Data Center). Inclusion of inter-channel correlation error to the selected ozone channels are expected to improve ozone analyses further along with improve analyses overall. It is anticipated that inclusion of these ozone sensitive channels will be used to improve NASA GMAO products in the near future.

GEOS-ADAS↗
NASA NTRS2019

Improved Ozone Analyses Using Direct Assimilation of 9.6μm Radiances from Hyperspectral Sounders

Previously, hyperspectral sounder brightness temperatures assimilated in the Goddard Earth Observing System Atmospheric Data Assimilation System (GEOS-ADAS) were limited to assimilating temperature and moisture. The ozone sensitive 9.6 m region is sensed by several hyperspectral sounders including AIRS (Atmospheric InfraRed Sounder), IASI (Infrared Atmospheric Sounding Interferometer), and CrIS (Cross-track Infrared Sounder). Direct assimilation of brightness temperatures in the 9.6 m region have been operational at ECMWF for several years (Dragani and McNally, 2013; Eresmaa et al., 2017). With this study, similar improvements using the GEOS-ADAS are presented. Channels were selected from available operational subsets evaluating information content and minimizing inter-channel correlation. Additionally, information such as channel selections made by other studies, and vertical sensitivities of ozone and temperature were considered. The analyses produced show improvements verified against ozonesondes taken from SHADOZ (Southern Hemisphere Additional Ozonesondes), and WOUDC (World Ozone and Ultraviolet Data Center). While care was taken to minimize inter-channel correlation through channel selection, a key feature available in the GEOS-ADAS is the ability to account for correlated error. The importance of inter-channel correlated error is highlighted by performing assimilation experiments with and without inter-channel correlation in the GEOS-ADAS. It is anticipated that inclusion of these ozone sensitive channels will be used to improve NASA GMAO products in the near future.

Karpowicz, Bryan M.↗
NASA NTRS2016

On-Orbit Manufacturing From Orbital Factories to In Situ Resource Utilization

This webinar will review commercial prospects for manufacturing in orbit. Doing business in space is rapidly becoming more reliable, affordable and accessible. From 2010 to 2015 launch prices went down by a factor of 10 or more, to about $5,000kg while investments into Space 2.0 companies and technologies are closing in on $2.5 Billion (New Space Global). With three commercial suppliers (SpaceX, Orbital ATK and Sierra Nevada Corp) to Earths orbits, mission frequency is improving dramatically. Moreover, private space companies (SpaceX Reusable Dragon Lab; Bigelows B330) are also scouting the opportunities of renting or selling modules as platforms for orbital free-flying facilities; modules that can be used for automated fabrication to manned experiments.Topics addressed in the webinar include: 1. Case studies of unique competitive advantages that can be gained from microgravity and space vacuum: wafer reprocessing, fiber optics, crystal growth;2. Prospective solar power orbital data centers;3. Reuse and recycling of orbital debris as a possible feedstock for robotic 3D fabrication potentially in the vacuum as well as inside facilities;4. The story behind the original WakeShield wafer fabrication facility and its relevance to todays activities;5. Energy needs for on-orbit manufacturing6. Environmental value proposition of on-orbit manufacturing for products with toxic byproducts or excessively large green house gases footprints;7. Longer term scenario of flexible, connected, automated, intelligent and sustainable orbital factories of the future.Opening up a less-appreciated aspect of NewSpace, this webinar will be of high interest to CTOs, Directors and Managers from product development to RD, Innovation Strategy leaders, and investors, across many different industrial verticals (materials, electronics, pharmaceuticals, advanced sustainable manufacturing, bioengineering, etc.)and anyone trying to understand what value space can have for their business in the near and far future.

Cozmuta, Ioana↗
NASA NTRS2019

Lunar Glovebox Balance with Wireless Technology

The most important equipment required for processing lunar samples is a high-quality mass balance for maintaining accurate weight inventory, security, and scientific study. After careful review, a Curation Office memo by Michael Duke in 1978 chose the Mettler PL200 to be used for sample weight measurements inside the gloveboxes (Fig. 3). These commercial off-the-shelf (COTS) balances did not meet the strict accepted material requirements in the Lunar lab. As a result, each balance housing, weighing pan, and wiring was custom retrofitted to meet Lunar Operating Procedure (LOP) 54 requirements [for material construction restrictions]. The original design drawings for the custom housings, readout support stands, and wiring were done by the JSC engineering directorate. The 1977- 1978 schematics, drawings, and files are now housed in the curation Data Center. Per the design specifications, the housing was fabricated from aluminum grade 6061 T6, seamless welds, and anodized per MIL-A-8625 type I, class I. The balance feet were TFE Teflon and any required joints were sealed with Viton A gaskets. The readout display and support stands outside the glovebox were fabricated from 300 series stainless steel with #4 finish and mounted to the glovebox with welded bolts. Wire harnesses that linked the balance with the outside display and power were encapsulated with TFE Teflon and transported through custom Deutsch wire bulk head pass-through systems from inside to outside the glovebox. These Deutsch connectors were custom fabricated with 316L stainless steel bodies, Viton A O-rings, aluminum 6061 with electroless nickel plating, Teflon (replacing the silicone), and gold crimp connectors (no soldering). Many of the Deutsch connectors may have been used in the Apollo program high vacuum complex in building 37 and date to about 1968 to 1970.

Zeigler, Ryan A.↗
NASA NTRS2004

International GPS Service : 2001-2002 technical reports

Applications of the Global Positioning System (GPS) to Earth Science are numerous. The International GPS Service (IGS), a federation of government agencies and universities, plays an increasingly critical role in support of GPS-related research and engineering activities. Contributions from the IGS Governing Board and Central Bureau, analysis and data centers, station operators, and others constitute the 2001 / 2002 Technical Reports.

Feltens, J.↗
NASA NTRS2019

A Web of Data Analytics Services

Cloud Computing has become the ubiquitous approach to our Big Data challenge. However, one will quickly discover that moving (a.k.a. forklifting) existing on-premise data analytics solutions to the Cloud doesn’t always translate to costing saving and performance boost. The Cloud’s elasticity, its availability, and its wide selection of computing options and selections of costing models making Cloud an attractive environment to tackle our Big Data challenge. The fact is Cloud, on its own, is not the silver bullet to our daunting challenge need for analyze and derive scientific inferences through vast collections of multi-sensor measurements. We would like to have all scientific data in one easy to access environment, but getting the world of scientific data in one analytic system is immensely difficult to achieve. This paper describes the data analytics web architecture NASA is developing by infusing instances of Integrated Data Analytics systems next to the data. The goal is to minimize unnecessary data movement through collection of data access and analytics webservices for researchers to interact with and analyze measurements without have to download data to their local computer. These services are RESTful and provisioned by the data centers with the help from subject matter and science experts. These services encapsulate the physical computing infrastructure, which could local computing cluster, on-premise or public Cloud environment.

Huang, Thomas↗
NASA NTRSDate not supplied

A New, Efficient, and Consistent Method for Generating Climate Data Record from Operational Hyperspectral Sounder Instruments on AQUA, S-NPP and NOAA 20

Operational IR sounders such AIRS on NASA Aqua, CrIS on S-NPP and on NOAA 20 satellites provide high quality hyperspectral measurements for weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It can provide fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

Xu Liu↗
NASA NTRSDate not supplied

All-sky Retrieval of Atmospheric Temperature, Water Vapor, Clouds, Trace Gases, and Surface Properties from Operational Hyperspectral IR Sounders

Operational IR sounders such AIRS, CrIS, and IASI provide high quality hyperspectral measurements for weather and climate applications. We will describe a new all-sky Single Field-of-view Sounder Atmospheric Product (SiFSAP). The uniqueness of this product is that it uses all available channels from hyperspectral sounders and the optimal estimation retrieval is done at a single FOV spatial resolution. The SiFSAP includes atmospheric temperature, water vapor, clouds, trace gases, surface skin, and surface emissivity and will be produced operationally at NASA GES DISC. We will describe the core component of the SiFSAP algorithm, which is the Principal Component-based Radiative Transfer Model (PCRTM), and will show example applications of the SiFSAP product for various atmospheric weather and dynamics studies. We also describe a new Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

pcrtm↗
NASA NTRSDate not supplied

20-Years of Atmospheric Temperature, Water Vapor, Cloud, and Surface Temperature Anomalies and Trends Derived From Operational Hyperspectral Ir Sounders

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The SiFSAP retrieval algorithm also uses the same climatology a priori and associated covariances, which makes it ideal for generating high quality products for both weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRSDate not supplied

Two Decades of Atmospheric and Surface Temperature, Water Vapor, and Cloud Trends Derived from Satellite Remote Sensors

Satellite remote sensor such as Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

remote sensing↗
NASA NTRSDate not supplied

Remote Sensing of Atmospheric Temperature, Water Vapor, Trace Gases, Cloud, and Surface Properties on Daily and Decadal Time Scales

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRSDate not supplied

Development of Radiative Transfer Models and Retrieval Algorithms for Satellite Remote Sensors

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. The SiFSAP algorithm performs one retrieval for each FOV using an all-sky optimal estimation approach. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗