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SBUV2/NOAA-11 Ozone (O3) Profile and Total Column Ozone Monthly L3 Global 5.0deg Lat Zones V1
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:54:41.000ZThe Solar Backscattered Ultra Violet (SBUV) from NOAA-11 Level-3 monthly zonal mean (MZM) product (SBUV2N11L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 147 months of data from January 1989 through March 2001. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 deg.) 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 deg; large discrepancy between profile total and best total ozone) NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angle where B-Pair total ozone estimate is not as reliable as profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15)
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Population Exposure Estimates in Proximity to Nuclear Power Plants, Country-Level Aggregates
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:36:37.000ZThe Population Exposure Estimates in Proximity to Nuclear Power Plants, Country-Level Aggregates data set consists of country-level estimates of total, urban, and rural populations and land area, country-wide, that are in proximity to a nuclear power plant. This data set was created using a global data set of point locations of nuclear power plants, with buffer zones at 30km, 75km, 150km, 300km, 600km, and 1200km, and the Global Population Count Grid Time Series Estimates, Version 1 to estimate the population within each buffer zone for the years 1990, 2000, and 2010. Global Rural-Urban Mapping Project, Version 1 (GRUMPv1) Land and Geographic Unit Area Grids were used to estimate land area within each buffer zone. The GRUMPv1 Urban Extents Grid was used to further delineate population and land area estimates within urban and rural areas. All grids used for population, land area, and urban mask were of 1 km (30 arc-second) resolution.
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RICAPS On-road Transportation Emissions roll-up
datahub.smcgov.org | Last Updated 2018-06-13T15:39:17.000ZData by city showing transportation contribution to greenhouse gas emissions in the County. This data is part of the Regionally Integrated Climate Action Planning Suite (RICAPS) program. The majority of cities used the “in-boundary” methodology that relies on data from the Highway Performance Monitoring System. The inventories for South San Francisco and Unincorporated County use the “origin-destination” methodology from that relies on data from Metropolitan Transportation Commission (MTC). So, directly comparing vehicle miles traveled (VMT) across all cities is not statistically possible. Each city in San Mateo County has the opportunity to develop its own Climate Action Plan (CAP) using tools developed by C/CAG in conjunction with DNV KEMA https://www.dnvgl.com/ and Hara. http://www.verisae.com/default.aspx. This project was funded by grants from the Bay Area Air Quality Management District (BAAQMD) and Pacific Gas and Electric Company (PG&E). Climate Action Plans developed from these tools will meet BAAQMD's California Environmental Quality Act (CEQA) guidelines for a Qualified Greenhouse Gas Reduction Strategy. For more information, please see the RICAPS site: http://www.smcenergywatch.com/progress_report.html
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An all MMIC Replacement for Gunn Diode Oscillators Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:36:37.000ZWe propose to replace the Gunn Diode Oscillators (GDOs) in NASA?s millimeter- and submillimeter-wave sensing instruments. Our new solution will rely on modern and reliable microwave integrated circuit technology. Specifically our systems will use highly developed microwave oscillators to achieve a low noise and highly stable reference signal in the 10 ? 30 GHz band. Compact amplifiers based on commercial MMIC chips will then increase the signal strength. Finally, our innovative integrated varactor multiplier circuits will be used to increase the frequency to the 60 ? 150 GHz frequency band with high efficiency and minimal added phase noise. With this technology we expect to achieve phase noise and stability comparable to the best Gunn diode oscillators and fundamentally improved output power and frequency agility. The millimeter-wave integrated circuit process and diode technologies are the critical innovative technologies that are required for this research. Through this SBIR project these innovative technologies will be extended to achieve highly compact multipliers for the 60 ? 150 GHz band. These new multipliers will be integrated with highly developed microwave components to achieve a robust and cost efficient replacement for the GDOs presently used in NASA?s Earth Science program.
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Northern Hemisphere Snow Cover Monthly Statistics at 1 Degree Resolution V001 (NHSNOWM) at GES DISC
data.nasa.gov | Last Updated 2022-01-17T05:45:22.000ZThis product is Snow Cover Statistics. The dataset was prepared by Dr. Peter Romanov at Cooperative Institute for Climate Studies(CICS) of the University of Maryland for Northern Eurasia Earth Science Partnership Initiative (NEESPI) program. The product includes the monthly snow statistics (frequency of occurrence) for Northern Hemisphere at 1x1 degree spatial resolution. The dataset covers the time period from January 2000 to November 2014. Monthly data were derived from daily snow cover charts produced at NOAA/NESDIS within Interactive Multisensor Ice Mapping System (IMS).
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SBUV2/NOAA-16 Ozone (O3) Profile and Total Column Ozone 1 Month Zonal Mean L3 Global 5.0 degree Latitude Zones V1 (SBUV2N16L3zm) at GES DISC
data.nasa.gov | Last Updated 2022-01-17T05:51:01.000ZThe Solar Backscattered Ultraviolet (SBUV) from NOAA-16 Level-3 monthly zonal mean (MZM) product (SBUV2N16L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 154 months of data from October 2000 through July 2013. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 degrees). 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 degrees; large discrepancy between profile total and best total ozone). NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angles where the B-Pair total ozone estimate is not as reliable as the ozone profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) Number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) Mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) Mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15).
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Contribution to High Asia Runoff from Ice and Snow (CHARIS) Melt Model Output, 2001 - 2014, Version 1
data.nasa.gov | Last Updated 2022-01-17T05:15:59.000ZThis data set contains input and output data for temperature index (TI) model runs completed for the Contributions to High Asia Runoff from Ice and Snow (CHARIS) project at NSIDC in 2018 and 2019. The input data are the area of snow on land, snow on ice, and exposed glacier ice as well as surface air temperature. These inputs are used to model the volumes of melt runoff from the snow on land, snow on ice, and exposed glacier ice in certain areas of High Mountain Asia.
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2014-2015 Arts Survey Data
data.cityofnewyork.us | Last Updated 2022-05-09T22:23:30.000ZThe Annual Arts in Schools Report includes data about arts teachers, arts budgeting, space for the arts, partnerships with arts and cultural organizations and parent involvement for elementary, middle and high schools. These reports help school administrators, parents, and students understand how their schools are progressing towards offering universal arts education to all students.
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Global Navigation Satellite System (GNSS) Rapid Clock Product (30 second resolution, daily files, generated daily) from NASA CDDIS
data.nasa.gov | Last Updated 2023-02-28T19:25:38.000ZThis derived product set consists of Global Navigation Satellite System Rapid Satellite and Receiver Clock Product (30-second granularity, daily files, generated daily) from the NASA Crustal Dynamics Data Information System (CDDIS). GNSS provide autonomous geo-spatial positioning with global coverage. GNSS data sets from ground receivers at the CDDIS consist primarily of the data from the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS). Since 2011, the CDDIS GNSS archive includes data from other GNSS (Europe’s Galileo, China’s Beidou, Japan’s Quasi-Zenith Satellite System/QZSS, the Indian Regional Navigation Satellite System/IRNSS, and worldwide Satellite Based Augmentation Systems/SBASs), which are similar to the U.S. GPS in terms of the satellite constellation, orbits, and signal structure. Analysis Centers (ACs) of the International GNSS Service (IGS) retrieve GNSS data on regular schedules to produce GNSS satellite and ground receiver clock values. The IGS Analysis Center Coordinator (ACC) uses these individual AC solutions to generate the official IGS rapid combined satellite and receiver clock products. The rapid combination is a daily solution available approximately 17 hours after the end of the previous UTC day. All satellite and receiver clock solution files utilize the clock RINEX format and span 24 hours from 00:00 to 23:45 UTC. For most applications the user of IGS products will not notice any significant differences between results obtained using the IGS Final and the IGS Rapid products.
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The Omnibus Surveys - 2002 Mariner Survey
datahub.transportation.gov | Last Updated 2018-12-19T00:13:39.000ZThe Omnibus Surveys are a convenient way to get very quick input on transportation issues; to see who uses what, how they use it, and how users view it, and what they think about it; and to gauge public satisfaction with the transportation system and government programs.The series of surveys include: A monthly household survey of 1,000 households each month, which collects data on core questions about general travel experiences, satisfaction with the system, and some demographic data. Targeted surveys to address special transportation issues, as the U.S. Department of Transportation (DOT) operating administrations need them