The Space Technology Research Grants Program will accelerate the development of "push" technologies to support the future space science and exploration needs of NASA, other government agencies and the commercial space sector. Innovative efforts with high risk and high payoff will be encouraged. The program is composed of two competitively awarded components.

The Space Technology Research Grants Program will accelerate the development of "push" technologies to support the future space science and exploration needs of NASA, other government agencies and the commercial space sector. Innovative efforts with high risk and high payoff will be encouraged. The program is composed of two competitively awarded components.

The NTRS is a valuable resource for researchers, students, educators, and the public to access NASA's current and historical technical literature and engineering results. Over 500,000 aerospace-related citations, over 200,000 full-text online documents, and over 500,000 images and videos are available. NTRS content continues to grow as new scientific and technical information (STI) is created or funded by NASA. The types of information found in the NTRS include: conference papers, journal articles, meeting papers, patents, research reports, images, movies, and technical videos. NTRS is Open Archives Initiative Protocol for Metadata Harvesting (OAI-PMH) enabled

NASA's Physical Sciences Research Program, along with its predecessors, has conducted significant fundamental and applied research in the physical sciences. The International Space Station (ISS) is an orbiting laboratory that provides an ideal facility to conduct long-duration experiments in the near absence of gravity and allows continuous and interactive research similar to Earth-based laboratories. This enables scientists to pursue innovations and discoveries not currently achievable by other means. NASA's Physical Sciences Research Program also benefits from collaborations with several of the ISS international partners—Europe, Russia, Japan, and Canada—and foreign governments with space programs, such as France, Germany and Italy.

In fulfillment of the Open Science model, NASA's Physical Sciences Research Program is pleased to offer the PSI data repository for physical science experiments performed in reduced-gravity environments such as the ISS, Space Shuttle flights, and Free-flyers. PSI also includes data from some related ground-based studies. The PSI system is accessible and open to the public. This provides the opportunity for researchers to data mine results from prior flight investigations, expanding on the research performed. This approach will allow numerous ground-based investigations to be conducted from one flight experiment’s data, exponentially increasing our body of knowledge. PSI is an Open Data initiative.

DISCOVERAQ_Texas_Ground_SmithPoint_Data contains data collected at the Smith Point ground site during the Texas (Houston) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Texas deployment and data collection is complete. Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality. DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS). The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.

The Earth Observing System Data and Information System (EOSDIS) is a major core capability within NASA''s Earth Science Data Systems Program. EOSDIS ingests, processes, archives and distributes data from a large number of Earth observing satellites. EOSDIS consists of a set of processing facilities and Earth Science Data Centers distributed across the United States and serves hundreds of thousands of users around the world, providing hundreds of millions of data files each year covering many Earth science disciplines. In order to serve the needs of a broad and diverse community of users, NASA''s Earth Science Data Systems Program is comprised of both Core and Community data system elements. Core data system elements reflect NASA''s responsibility for managing Earth science satellite mission data characterized by the continuity of research, access, and usability. The core comprises all the hardware, software, physical infrastructure, and intellectual capital NASA recognizes as necessary for performing its tasks in Earth science data system management. Community data system elements are those pieces or capabilities developed and deployed largely outside of NASA core elements and are characterized by their evolvability and innovation. Successful applicable elements can be infused into the core, thereby creating a vibrant and flexible, continuously evolving infrastructure. NASA''s Earth Science program was established to use the advanced technology of NASA to understand and protect our home planet by using our view from space to study the Earth system and improve prediction of Earth system change. To meet this challenge, NASA promotes the full and open sharing of all data with the research and applications communities, private industry, academia, and the general public. NASA was the first agency in the US, and the first space agency in the world, to couple policy and adequate system functionality to provide full and open access in a timely manner - that is, with no period of exclusive access to mission scientists - and at no cost. NASA made this decision after listening to the user community, and with the background of the then newly-formed US Global Change Research Program, and the International Earth Observing System partnerships. Other US agencies and international space agencies have since adopted similar open-access policies and practices. Since the adoption of the Earth Science Data Policy adoption in 1991, NASA''s Earth Science Division has developed policy implementation, practices, and nomenclature that mission science teams use to comply with policy tenets. Data System Standards NASA''s Earth Science Data Systems Groups anticipate that effective adoption of standards will play an increasingly vital role in the success of future science data systems. The Earth Science Data Systems Standards Process Group (SPG), a board composed of Earth Science Data Systems stakeholders, directs the process for both identification of appropriate standards and subsequent adoption for use by the Earth Science Data Systems stakeholders.

This dataset contains along track geo-referenced Sea Surface Height Anomalies (SSHA) from TOPEX/Poseidon, Jason-1 and OSTM/Jason-2 (depending on time period) merged onto a single mean reference orbit. All biases and cross-calibrations have been applied to the data so SSHA are consistent between satellites to form a single climate data record. Altimeter data from the multi-mission Geophysical Data Records (GDRs) are interpolated to a common reference orbit facilitating direct time series analysis of the geo-referenced SSH. The data are in netCDF format in an array based on 3-dimensions (rev#, index, cycle) that permits direct access of individual locations at specific times (i.e., temporal and spatial sub-sampling). The data start at September 1992 and is presently updated to January 2013. The newest data are appended to the file quarterly.

The Public Use Microdata Samples (PUMS) are computer-accessible files containing records for a sample of housing Units, with information on the characteristics of each housing Unit and the people in it for 1940-1990. Within the limits of sample size and geographical detail, these files allow users to prepare virtually any tabulations they require. Each datafile is documented in a codebook containing a data dictionary and supporting appendix information. Electronic versions for the codebooks are only available for the 1980 and 1990 datafiles. Identifying information has been removed to protect the confidentiality of the respondents. PUMS is produced by the United States Census Bureau (USCB) and is distributed by USCB, Inter-university Consortium for Political and Social Research (ICPSR), and Columbia University Center for International Earth Science Information Network (CIESIN).

Advanced Diagnostics and Prognostics Testbed (ADAPT) Project Lead: Scott Poll Subject Fault diagnosis in electrical power systems Description The Advanced Diagnostics and Prognostics Testbed (ADAPT) lab at the NASA Ames Research Center aims to provide a means to assess the effectiveness of diagnostic algorithms at detecting faults in power systems. The algorithms are evaluated using data from the Electrical Power System (EPS), which simulates the functions of a typical aerospace vehicle power system. The EPS allows for the controlled insertion of faults in repeatable failure scenarios to test if diagnostic algorithms can detect and isolate these faults. How Data Was Acquired This dataset was generated from the EPS in the ADAPT lab. Each data file corresponds to one experimental run of the testbed. During an experiment, a data acquisition system commands the testbed into different configurations and records data from sensors that measure system variables such as voltages, currents, temperatures and switch positions. Faults were injected in some of the experimental runs. Sample Rates and Parameter Descriptions Data was sampled at a rate of 2 Hz and saved into a tab delimited plain text file. There are a total of 128 sensors and typical experimental runs last for approximately five minutes. The text files have also been converted into a MATLAB environment file containing equivalent data that may be imported for viewing or computation. Faults and Anomalies Faults were injected into the EPS using physical or software means. Physical faults include disconnecting sources, sinks or circuit breakers. For software faults, user commands are passed through an Antagonist function before being received by the EPS, and sensor data is filtered through the same function before being seen by the user. The Antagonist function was able to block user commands, send spurious commands and alter sensor data. External Links Additional data from the ADAPT EPS testbed can be found at the DXC competition page - https://dashlink.arc.nasa.gov/topic/diagnostic-challenge-competition/ Other Notes The HTML diagrams can be viewed in any brower, but its active content is best run on Internet Explorer.

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Web-Enabled Landsat Data Annual (GWELDYR) Version 3.1 data product provides Landsat data at 30 meter (m) resolution for terrestrial non-Antarctica locations over annual reporting periods for the 1985, 1990, and 2000 epochs. GWELD data products are generated from all available Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data in the U.S. Geological Survey (USGS) Landsat archive. The GWELD suite of products provide consistent data to derive land cover as well as geophysical and biophysical information for regional assessment of land surface dynamics. The GWELD products include Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) for the reflective wavelength bands and to top of atmosphere (TOA) brightness temperature for the thermal bands. The products are defined in the Sinusoidal coordinate system to promote continuity of NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) land tile grid. Provided in the GWELDYR product are layers for surface reflectance bands 1 through 5 and 7, TOA brightness temperature for thermal bands, Normalized Difference Vegetation Index (NDVI), day of year, ancillary angle, and data quality information. A low-resolution red, green, blue (RGB) browse image of bands 5, 4, 3 is also available for each granule. Version 3.1 products use Landsat Collection 1 products as input and have improved per-pixel cloud mask, new quality data, improved calibration information, and improved product metadata that enable view and solar geometry calculations.

The purpose of the Aerospace Technical Facility Inventory is to facilitate the sharing of specialized capabilities within the aerospace research/engineering community primarily within NASA, but also throughout the nation and the entire world. A second use is to assist in answering questions regarding NASA capabilities for future missions or various alternative scenarios regarding mission support to help the Agency maintain the right set of assets.

The Shuttle Radar Topography Mission (SRTM) is a collaborative effort from NASA (National Aeronautics and Space Administration) and NGA (National Geospatial-Intelligence Agency) as well as DLR (Deutsches Zentrum für Luft-und Raumfahrt) and ASI (Agenzia Spaziale Italiana). SRTM was flown aboard the Endeavour space shuttle in February 2000 to provide a high-resolution Digital Elevation Model (DEM). The SRTM instrumentation consisted of the Spaceborne Imaging Radar-C (SIR-C) with an additional antenna to form a 60 meters long baseline. As a result of the SRTM mission, several DEM versions have been released since 2003, which differ in terms of data processing and procedures applied for the filling of voids (areas not or poorly observed by the SRTM radar observations).

SRTM v3.0 (SRTM Plus) is the newest version, published in 2015 by NASA as a part of NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) project, which incorporates topographic data to fill the gaps or voids in earlier versions of SRTM data. For the void filling with the Delta Surface Fill algorithm, ASTER DEMs have been used as auxiliary data source, or interpolations have been applied. Many variants of DEM are available in SRTM v3.0, with SRTMGL1 being one of the key products from SRTM v3.0. ‘GL1’ on its name stands for “Global 1-arc second”. It provides regularly spaced DEM grids of 1 arc-second (approximately 30 meters) and covering 80% of Earth’s landmass, between 60° North and 56° South. This product is divided into 1° x 1° latitude and longitude tiles in “geographic” projection, as shown here.

A typical file of the SRTMGL1 dataset requires 25 MB memory (without compression) and stores exactly one 1°x1° tile; it contains 3,601 lines and 3,601 columns, which sum up to around 100 GB (compressed) and 350 GB (uncompressed) for the global data set of 14297 tiles. Individual tile names refer to the latitude and longitude of southwest (lower left) corner of the tile, e.g., tile N20W030 has lower left corner at 20°N and 30°W, covering area of 20-21°N and 30-29°W. The absolute vertical accuracy for SRTM heights has been found to be ~9 m (90 % confidence) or better (Rodriguez et al. 2005).

Geodetic information: The SRTM GL1 DEMs are vertically referenced to the EGM96 geoid and horizontally referenced to the WGS84 (World Geodetic System 1984).

Further notes: The SRTM DEM represents bare ground elevations only where vegetation cover and buildings are absent. Over most areas, the DEM elevations reside between the bare ground (terrain) and top of canopies (surface), so are technically a mixture of terrain and surface models. Few artefacts, e.g., pits or spikes may still be present in the data set.

Data access: The homepage of SRTM mission is http://www2.jpl.nasa.gov/srtm/. SRTM v3.0 datasets can be searched in MEASURES webpage and acquired freely from USGS website (http://earthexplorer.usgs.gov/) and USGS data pool (http://e4ftl01.cr.usgs.gov/SRTM/).References:Farr, T.G., E. Caro, R. Crippen, R. Duren, S. Hensley, M. Kobrick, M. Paller, E. Rodriguez, P. Rosen, L. Roth, D. Seal, S. Shaffer, J. Shimada, J. Umland, M. Werner, 2007, The Shuttle Radar Topography Mission. Reviews of Geophysics, volume 45, RG2004, doi:10.1029/2005RG000183.NASA, The Shuttle Radar Topography Mission (SRTM) Collection User Guide. Available on https://lpdaac.usgs.gov/sites/default/files/public/measures/docs/NASA_SRTM_V3.pdfRodriguez, E., C.S. Morris, J.E. Belz, E.C. Chapin, J.M. Martin, W. Daffer, S.Hensley, 2005, An assessment of the SRTM topographic products, Technical Report JPL D-31639, Jet Propulsion Laboratory, Pasadena, California, 143 pp. available on http://www2.jpl.nasa.gov/srtm/SRTM_D31639.pdf

The MoonDB is a database of past and present spacecraft in cislunar space, compiled through publicly available sources. It was designed to better understand the rationale behind missions, focusing on their final results, current status, funding agencies and nations. Particular attention has also been given to the surface of the Moon, where landing sites have been identified. The database is mainly based on data collected by NASA in the Master Catalogue of the NASA Space Science Data Coordinated Archive (NSSDCA) [1]. Other sources are also considered, such as the Satellite Catalog (SATCAT) from the Space-Track project [2], created by the US Combined Force Space Component Command (CFSCC). The work by McDowell (2020) [3] has also been considered an inspiration for this work, although the primary source of information has remained the NASA catalogue.

Some structural and logical changes have been introduced to follow the needs of this research project. Following a list provided by the NSSDCA, a certain number of tentative USSR missions were added to the statistics [4]. Most spacecraft were destroyed due to a launch failure and were not disclosed to the public: the available information results from an investigation.

Additional information and a version changelog are provided in the readme file.

This is a selection of the MODIS 8 day mean level 3 mapped 8 day mean ocean products at the two highest resolutions available. It spans from July 2002 onwards and will be augmented by newer data from time to time. The source of the data is NASA at the above reference. This data has been reformatted into 3 dimensional, longitude by latitude by time netcdf files for use by researchers in CSIRO. Initially the following products have been selected: chlorophyll, extinction coefficient (K490) and sea surface temperature. The NASA data are also available in various resolutions. The highest two resolution levels have been chosen, with nominal pixel size of 4 and 9 kilometres. A description of the processing carried out by NASA is at http://oceancolor.gsfc.nasa.gov/DOCS/modis_processing_overview.pdf

The Prediction Of Worldwide Energy Resource (POWER) Project gathers NASA Earth Observation data and parameters related to the fields of surface solar irradiance and meteorology to serve the public in several free, easy-to-access, and easy-to-use methods. POWER helps communities become resilient amid observed climate variability by improving data accessibility, aiding research in renewable energy development, building energy efficiency, and agriculture sustainability. POWER is funded through the NASA Earth Action Program within the Earth Science Mission Directorate at NASA Langley Research Center (LaRC).---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------This monthly radiation service provides time-enabled global Analysis Ready Data (ARD) parameters from 1984 to 2023 for the NASA POWER Project's communities.Time Interval: MonthlyTime Extent: 1984/01/01 to 2023/12/31Time Standard: Local Sidereal Time (LST)Grid Size: 1.0 X 1.0 DegreeProjection: GCS WGS84Extent: GlobalSource: NASA Prediction Of Worldwide Energy Resources (POWER)Radiation Data Sources:NASA's GEWEX/SRB release 4.0 archive (Jan. 1, 1984 – Dec. 31, 2000)NASA's CERES SYN1deg (Jan. 1, 2001 – Dec. 31, 2021)For questions or issues please email: larc-power-project@mail.nasa.govRadiation Data Parameters:ALLSKY_KT (All Sky Insolation Clearness Index): A fraction representing clearness of the atmosphere; the all sky insolation that is transmitted through the atmosphere to strike the surface of the earth divided by the average of top of the atmosphere total solar irradiance incident.ALLSKY_SFC_LW_DWN (All Sky Surface Longwave Downward Irradiance): The downward thermal infrared irradiance under all sky conditions reaching a horizontal plane the surface of the earth. Also known as Horizontal Infrared Radiation Intensity from Sky.ALLSKY_SFC_LW_UP (All Sky Surface Longwave Upward Irradiance): The upward thermal infrared irradiance under all sky conditions.ALLSKY_SFC_PAR_TOT (All Sky Surface PAR Total): The total Photosynthetically Active Radiation (PAR) incident on a horizontal plane at the surface of the earth under all sky conditions.ALLSKY_SFC_SW_DIFF (All Sky Surface Shortwave Diffuse Irradiance): The diffuse (light energy scattered out of the direction of the sun) solar irradiance incident on a horizontal plane at the surface of the earth under all sky conditions.ALLSKY_SFC_SW_DNI (All Sky Surface Shortwave Downward Direct Normal Irradiance): The direct solar irradiance incident to a horizontal plane normal (perpendicular) to the direction of the sun's position under all sky conditions.ALLSKY_SFC_SW_DWN (All Sky Surface Shortwave Downward Irradiance): The total solar irradiance incident (direct plus diffuse) on a horizontal plane at the surface of the earth under all sky conditions. An alternative term for the total solar irradiance is the "Global Horizontal Irradiance" or GHI.ALLSKY_SFC_SW_UP (All Sky Surface Shortwave Upward Irradiance): The upward shortwave irradiance under all sky conditions.ALLSKY_SFC_UV_INDEX (All Sky Surface UV Index): The ultraviolet radiation exposure index.ALLSKY_SFC_UVA (All Sky Surface UVA Irradiance): The ultraviolet A (UVA 315nm-400nm) irradiance under all sky conditions.ALLSKY_SFC_UVB (All Sky Surface UVB Irradiance): The ultraviolet B (UVB 280nm-315nm) irradiance under all sky conditions.ALLSKY_SRF_ALB (All Sky Surface Albedo): The all sky rate of reflectivity of the earth's surface; the ratio of the solar energy reflected by the surface of the earth compared to the total solar energy incident reaching the surface of the earth.AOD_55 (Aerosol Optical Depth 55): The optical thickness at 0.55 um measured vertically; the component of the atmosphere to quantify the removal of radiant energy from an incident beam.AOD_55_ADJ (Adjusted Aerosol Optical Depth 55): The adjusted optical thickness at 0.55 um measured vertically; the component of the atmosphere to quantify the removal of radiant energy from an incident beam.CLOUD_AMT (Cloud Amount): The average percent of cloud amount during the temporal period.CLOUD_AMT_DAY (Cloud Amount at Daytime): The average percent of cloud amount during daylight.CLOUD_AMT_NIGHT (Cloud Amount at Nighttime): The average percent of cloud amount during nighttime.CLOUD_OD (Cloud Optical Visible Depth): The vertical optical thickness between the top and bottom of a cloud.CLRSKY_DAYS (Clear Sky Day): The number of Clear Sky Days if the daytime cloud amount is less than 10 percent.CLRSKY_KT (Clear Sky Insolation Clearness Index): A fraction representing clearness of the atmosphere; the clear sky insolation that is transmitted through the atmosphere to strike the surface of the earth divided by the average of top of the atmosphere total solar irradiance incident.CLRSKY_SFC_LW_DWN (Clear Sky Surface Longwave Downward Irradiance): The downward thermal infrared irradiance under clear sky conditions reaching a horizontal plane the surface of the earth. Also known as Horizontal Infrared Radiation Intensity from Sky.CLRSKY_SFC_LW_UP (Clear Sky Surface Longwave Upward Irradiance): The upward thermal infrared irradiance under clear sky conditions.CLRSKY_SFC_PAR_TOT (Clear Sky Surface PAR Total): The total Photosynthetically Active Radiation (PAR) incident on a horizontal plane at the surface of the earth under clear sky conditions.CLRSKY_SFC_SW_DIFF (Clear Sky Surface Shortwave Downward Diffuse Horizontal Irradiance): The diffuse (light energy scattered out of the direction of the sun) solar irradiance incident on a horizontal plane at the surface of the earth under clear sky conditions.CLRSKY_SFC_SW_DNI (Clear Sky Surface Shortwave Downward Direct Normal Irradiance): The direct solar irradiance incident to a horizontal plane normal (perpendicular) to the direction of the sun's position under clear sky conditions.CLRSKY_SFC_SW_DWN (Clear Sky Surface Shortwave Downward Irradiance): The total solar irradiance incident (direct plus diffuse) on a horizontal plane at the surface of the earth under clear sky conditions. An alternative term for the total solar irradiance is the "Global Horizontal Irradiance" or GHI.CLRSKY_SFC_SW_UP (Clear Sky Surface Shortwave Upward Irradiance): The upward shortwave irradiance under clearsky conditions.CLRSKY_SRF_ALB (Clear Sky Surface Albedo): The clear sky rate of reflectivity of the earth's surface; the ratio of the solar energy reflected by the surface of the earth compared to the total solar energy incident reaching the surface of the earth.MIDDAY_INSOL (Midday Insolation Incident): The total amount of solar irradiance (i.e. direct plus diffuse) incident on a horizontal plane at the earth's surface during the solar noon hour midday period.PW (Precipitable Water): The total atmospheric water vapor contained in a vertical column of the atmosphere.TOA_SW_DNI (Top-Of-Atmosphere Shortwave Direct Normal Radiation): The total solar irradiance incident (direct plus diffuse) on a horizontal plane where oriented to the sun's position at the top of the atmosphere (extraterrestrial radiation).TOA_SW_DWN (Top-Of-Atmosphere Shortwave Downward Irradiance): The total solar irradiance incident (direct plus diffuse) on a horizontal plane at the top of the atmosphere (extraterrestrial radiation).TS_ADJ (Earth Skin Temperature Adjusted): The adjusted average temperature at the earth's surface.

OWLETS1_Pandora_Data_1 is the Ozone Water-Land Environmental Transition Study (OWLETS-1) ozone and nitrogen dioxide data collected by the NASA GSFC Pandora Spectrometer Project located at NASA Langley Research Center, the Chesapeake Bay Bridge Tunnel, SERC Research Vessel, Virginia Commonwealth University (VCU) and Wallops Flight Facility during the OWLETS field campaign. OWLETS was supported by the NASA Science Innovation Fund (SIF). Data collection is complete. Coastal regions have typically posed a challenge for air quality researchers due to a lack of measurements available over water and water-land boundary transitions. Supported by NASA’s Science Innovation Fund (SIF), the Ozone Water-Land Environmental Transition Study (OWLETS) field campaign examined ozone concentrations and gradients over the Chesapeake Bay from July 5, 2017 – August 3, 2017, with twelve intensive measurement days occurring during this time period. OWLETS utilized a unique combination of instrumentation, including aircraft, TOLNet ozone lidars (NASA Goddard Space Flight Center Tropospheric Ozone Differential Absorption Lidar and NASA Langley Research Center Mobile Ozone Lidar), UAV/drones, ozonesondes, AERONET sun photometers, and mobile and ship-based measurements, to characterize the land-water differences in ozone and other pollutants. Two main research sites were established as part of the campaign: an over-land site at NASA LaRC, and an over-water site at the Chesapeake Bay Bridge Tunnel. These two research sites were established to provide synchronous vertical measurements of meteorology and pollutants over water and over land. In combination with mobile observations between the two sites, pollutant gradients were able to be observed and used to better understand the fundamental processes occurring at the land-water interface. OWLETS-2 was completed from June 6, 2018 – July 6, 2018 in the upper Chesapeake Bay region. Research sites were established at the University of Maryland, Baltimore County (UMBC), Hart Miller Island (HMI), and Howard University Beltsville (HUBV), with HMI representing the over-water location and UMBC and HUBV representing the over-land sites. Similar measurements were carried out to further characterize water-land gradients in the upper Chesapeake Bay. The measurements completed during OWLETS are of importance in enhancing air quality models, and improving future satellite retrievals, particularly, NASA’s Tropospheric Emissions: Monitoring of Pollution, which is scheduled to launch in 2022.

The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the NASA Goddard Institute for Space Studies (NASA GISS) GISS-E2-1-G model output for the "low-end scenario reaching 1.9 W m-2, based on SSP1" (ssp119) experiment. These are available at the following frequency: Amon. The runs included the ensemble member: r1i1p1f2. CMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6). The official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record.

The Ozone Monitoring Instrument (OMI) was launched aboard the EOS-Aura satellite on July 15, 2004 (1:38 pm equator crossing time, ascending mode). OMI with its 2600 km viewing swath width provides almost daily global coverage. OMI is a contribution of the Netherlands Space Office (NSO) in collaboration with Finish Meterological Institute (FMI), to the US EOS-Aura Mission. The principal investigator (Dr. Pieternel Levelt) institute is the KNMI (Royal Netherlands Meteorological Institute). OMI is designed to monitor stratospheric and tropospheric ozone, clouds, aerosols and smoke from biomass burning, SO2 from volcanic eruptions, and key tropospheric pollutants (HCHO,NO2) and ozone depleting gases (OClO and BrO). OMI sensor counts, calibrated and geolocated radiances, and all derived geophysical atmospheric products will be archived at the NASA Goddard DAAC. The Sulfer Dioxide Product 'OMSO2' from the Aura-OMI is now publicly available from NASA GSFC Earth Sciences (GES) Data and Information Services Center (DISC) for public access. OMSO2 product contains three values of SO2 Vertical column corresponding to three a-priori vertical profiles used in the retrieval algorithm. It also contains quality flags, geolocation and other ancillary information. The shortname for this Level-2 OMI total column SO2 product is OMSO2 and the algorithm leads for this product are NASA/UMBC OMI scientists Drs. Nikolay Krotkov (nickolay.a.krotkov@nasa.gov),Kai Yang(kai.yang@nasa.gov) and Arlin J. Krueger(krueger@umbc.edu). OMSO2 files are stored in EOS Hierarchical Data Format (HDF-EOS5). Each file contains data from the day lit portion of an orbit (~53 minutes). There are approximately 14 orbits per day. The maximum file size for the OMSO2 data product is about 21 Mbytes. On-line spatial and parameter subset options are available during data download A list of tools for browsing and extracting data from these files can be found at: http://disc.gsfc.nasa.gov/Aura/tools.shtml A short OMSO2 Readme Document that includes brief algorithm description and documents that provides known data quality related issues are available from the UMBC OMI site ( http://so2.gsfc.nasa.gov/docs.php ) For more information on Ozone Monitoring Instrument and atmospheric data products, please visit the OMI-Aura sites: http://aura.gsfc.nasa.gov/ http://so2.gsfc.nasa.gov/ http://www.knmi.nl/omi/research/documents/. For the full set of Aura products and other atmospheric composition data available from the GES DISC, please see the links below. http://disc.sci.gsfc.nasa.gov/Aura/ http://disc.gsfc.nasa.gov/acdisc/

Prognostic performance evaluation has gained significant attention in the past few years.*Currently, prognostics concepts lack standard definitions and suffer from ambiguous and inconsistent interpretations. This lack of standards is in part due to the varied end- user requirements for different applications, time scales, available information, domain dynamics, etc. to name a few. The research community has used a variety of metrics largely based on convenience and their respective requirements. Very little attention has been focused on establishing a standardized approach to compare different efforts. This paper presents several new evaluation metrics tailored for prognostics that were recently introduced and were shown to effectively evaluate various algorithms as compared to other conventional metrics. Specifically, this paper presents a detailed discussion on how these metrics should be interpreted and used. These metrics have the capability of incorporating probabilistic uncertainty estimates from prognostic algorithms. In addition to quantitative assessment they also offer a comprehensive visual perspective that can be used in designing the prognostic system. Several methods are suggested to customize these metrics for different applications. Guidelines are provided to help choose one method over another based on distribution characteristics. Various issues faced by prognostics and its performance evaluation are discussed followed by a formal notational framework to help standardize subsequent developments.

The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the NASA Goddard Institute for Space Studies (NASA GISS) GISS-E2-1-G model output for the "update of RCP2.6 based on SSP1" (ssp126) experiment. These are available at the following frequencies: Amon and day. The runs included the ensemble member: r1i1p3f1. CMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6). The official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record.