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NLDAS Secondary Forcing Data L4 Monthly Climatology 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:55:49.000ZThis data set contains the monthly climatology data of the secondary forcing data for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing. The temporal resolution is monthly, ranging from January to December. The NLDAS-2 monthly climatology data are the monthly data averaged over the thirty years (1980 - 2009) of the NLDAS-2 monthly data. The file format is WMO GRIB-1. Brief description about the NLDAS-2 hourly and monthly primary forcing data can be found from the GCMD DIFs for GES_DISC_NLDAS_FORB0125_H_V002 and GES_DISC_NLDAS_FORB0125_M_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_FORB0125_H_V002 and http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_FORB0125_M_V002. Details about the generation of the NLDAS-2 forcing datasets can be found in Xia et al. (2012). The NLDAS-2 monthly climatology land surface forcing fields are grouped into two GRIB files, "File A" and "File B". "File B" is the secondary (optional) forcing file and contains ten fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_FORB_monthly.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For more information, please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf.
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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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Blocking Filters with Enhanced Throughput for X-Ray Microcalorimetry Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:24:13.000ZX-ray microcalorimeters have developed to provide unprecedented energy resolution and signal sensitivity. To take maximum advantage of the microcalorimeter's performance, a new and improved blocking filter stack is needed to further enhance low level sensitivity and mission throughput. The innovation proposed, high transmission polyimide support mesh fabricated using photolithography, will replace the nickel mesh used in previous blocking filter designs. The proposed mesh will be thinner than known comparable supports and will be produced freestanding such that it can be readily combined with filter foils of all types. The polyimide mesh will demonstrate at least 10% higher transmission than nickel at all energies, and will become essentially transparent above 3 keV. Mesh structures will be fabricated using three different photolithographic processes and compared both freestanding and in combination with filter foils to determine feasibility. The proposed innovation along with thinner materials will improve mission throughput and effective area significantly for microcalorimeter payloads on proposed Small Explorer missions, NeXT, and Spectrum-X-Gamma in the near term as well as Constellation ?X.
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GPM Level 3 IMERG Monthly 0.1 x 0.1 degree V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:01:54.000ZThis Directory Interchange Format (DIF) describes a collection of fields for the GPM Level 3 IMERG *Final* Monthly 0.1 x 0.1 degree V03 (GPM_3IMERGM) at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). The Integrated Multi-satelliE Retrievals for GPM (*IMERG*) is the unified U.S. algorithm that provides the Day-1 multi-satellite precipitation product for the U.S. GPM team. The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2014 version of the Goddard Profiling Algorithm (GPROF2014), then gridded, intercalibrated to the GPM Combined Instrument product, and combined into half-hourly 0.1°x0.1° fields. These are provided to both the Climate Prediction Center (CPC) Morphing-Kalman Filter (CMORPH-KF) Lagrangian time interpolation scheme and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Cloud Classification System (PERSIANN-CCS) re-calibration scheme. In parallel, CPC assembles the zenith-angle-corrected, intercalibrated “even-odd” geo- IR fields and forward them to PPS for use in the CMORPH-KF Lagrangian time interpolation scheme and the PERSIANN-CCS computation routines. The PERSIANN-CCS estimates are computed (supported by an asynchronous re-calibration cycle) and sent to the CMORPH-KF Lagrangian time interpolation scheme. The CMORPH-KF Lagrangian time interpolation (supported by an asynchronous KF weights updating cycle) uses the PMW and IR estimates to create half-hourly estimates. The IMERG system is run twice in near-real time • “Early” multi-satellite product ~4 hr after observation time and • “Late” multi-satellite product ~12 hr after observation time, and once after the monthly gauge analysis is received • “Final” satellite-gauge product ~2 months after the observation month. The baseline is for the (near-)real-time Early and Late half-hour estimates to be calibrated with climatological coefficients that vary by month and location, while in the Final post-real-time run the multi-satellite half-hour estimates are adjusted so that they sum to a monthly satellite-gauge combination. In all cases the output contains multiple fields that provide information on the input data, selected intermediate fields, and estimation quality. Release document: http://pmm.nasa.gov/sites/default/files/document_files/IMERG_FinalRun_Day1_release_notes.pdf Other key documents: Technical document and acronyms: http://pmm.nasa.gov/sites/default/files/document_files/IMERG_doc.pdf Algorithm Theoretical Basis Document (ATBD): http://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V4.4.pdf In brief, the input precipitation estimates computed from the various satellite passive microwave sensors are intercalibrated to the GPM Combined Instrument product (because it is presumed to be the best snapshot GPM estimate), then “morphed” and combined with microwave precipitation-calibrated geo-IR fields, and adjusted with monthly surface precipitation gauge analysis data (where available) to provide half-hourly and monthly precipitation estimates on a 0.1° lat./long. grid over the domain 60°N-S. Precipitation phase is diagnosed using analyses of surface temperature, humidity, and pressure. The current period of record is mid-March 2014 to the present (delayed by about 2 months).The Integrated Multi-Satellite Retrievals for GPM (IMERG) algorithm is designed to leverage the international constellation of precipitation-relevant satellites to create a long record of uniformly time/space gridded precipitation estimates for the globe. The algorithm is focused on creating the best estimate at each time step, meaning that it is not a Climate Data Record, although the ideal is as homogenous a record as possible.
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GPM, DPR, GMI Level 3 Combined Precipitation V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:03:54.000ZThere are uncertainties in the interpretation of data from any one of the instruments (KuPR, KaPR, and GMI). By using data from multiple instruments, further constraints on the solution of precipitation structure improve the final product.The purpose of 3CMB is to give a daily and monthly accumulation of the 2BCMB precipitation product. The 3CMB product is a daily and monthly accumulation of the 2BCMB orbital combined product at two grid sizes, 5 x 5 degrees (G1) and 0.25 x 0.25 degrees (G2). Grid G1 contains the following physical measurements of general interest, among others. Grid G2 contains the same groups, but it is on the ltH x lnH grid and does not have the surface type (st) dimension or the histograms (see dimension definitions below). Below, conditional products represent means based upon precipitating areas only; unconditional products represent means for raining and non-raining areas combined. Probabilities represent the number of raining observations divided by the total number of raining and non-raining observations. precipTotRate (Group in G1)- Conditional mean rate for all precipitation phases (ice, liquid, mixed-phase). * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqRate (Group in G1) - Conditional mean rate for liquid precipitation. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotWaterContent (Group in G1) - Conditional mean water content for all precipitation phases. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqWaterContent (Group in G1) - Conditional mean liquid water content. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotDm (Group in G1) - Conditional mass-weighted mean particle diameter. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotRateDiurnal (Group in G1) - Conditional mean total surface precipitation rate indexed by local time. * count (4-byte integer, array size: ltL x lnL x ns x st x tim): Count. * mean (4-byte float, array size: ltL x lnL x ns x st x tim): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x st x tim): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. surfPrecipTotRateDiurnalAllObs (4-byte integer, array size: ltL x lnL x ns x st x tim): Number of total observa...
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Polymer Matrix Composite Materials for Lightning Strike Mitigation Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:23:31.000ZIn this phase I SBIR program, a team led by Advanced Ceramics Research Inc. (ACR) propose a novel, low-cost manufacturing process for multi-functional polymer composite components with improved lightning strike mitigation and EMI shielding capabilities. The proposed program will develop and demonstrate a process for manufacturing complex-geometry composite parts with tailored lightning strike mitigation capability based on design requirements. This process is a natural extension of the ACR water-soluble tooling process for fabricating complex-geometry polymer composite parts as well as filament wound composite tanks. For the proposed phase I program, the ACR-led team will use a novel process to create a highly conductive surface capable of providing the necessary lightning strike protection and EMI shielding. The ACR team will evaluate the new approach with two different space qualified matrix polymers with graphite fibers and compare the surface conductivity with baseline composite systems.
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BUV/Nimbus-04 Ozone (O3) Profile and Total Column Ozone Monthly L3 Global 5.0deg Lat Zones V1
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:06:00.000ZThe Solar Backscattered Ultra Violet (SBUV) from Nimbus-4 Level-3 monthly zonal mean (MZM) product (BUVN04L3zm) 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 72 months of data from May 1970 through April 1976. 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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NLDAS Mosaic Land Surface Model L4 Monthly 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:56:10.000ZThis data set contains a series of land surface parameters simulated from the Mosaic land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing and range from Jan 1979 to the present. The temporal resolution is monthly. The file format is WMO GRIB-1. The NLDAS-2 monthly Mosaic model data were generated from the NLDAS-2 hourly Mosaic model data, as monthly accumulation for rainfall, snowfall, subsurface runoff, surface runoff, total evapotranspiration, and snow melt, and monthly average for other variables. Monthly period of each month is from 00Z at start of the month to 23:59Z at end of the month, except the first month (Jan. 1979) that starts from 00Z 02 Jan 1979. Brief description about the NLDAS-2 monthly Mosaic model can be found from the GCMD DIF for NLDAS-2 hourly Mosaic data GES_DISC_NLDAS_MOS0125_H_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_MOS0125_H_V002. Details about the NLDAS-2 configuration of the Mosaic LSM can be found in Xia et al. (2012). The NLDAS-2 monthly Mosaic model data contain thirty-seven fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_MOS.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For information about the vertical layers of the Soil Moisture Content (PDS 086) and Soil Temperature (PDS 085), please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf or the GrADS ctl file at ftp://hydro1.sci.gsfc.nasa.gov/data/gds/NLDAS/NLDAS_MOS0125_M.002.ctl.
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NLDAS VIC Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:29:26.000ZAbstract: This data set contains a series of land surface parameters simulated from the VIC land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing. The temporal resolution is monthly, ranging from January to December. The file format is WMO GRIB-1. The NLDAS-2 monthly climatology data are the monthly data averaged over the thirty years (1980-2009) of the NLDAS-2 monthly data. Brief description about the NLDAS-2 hourly and monthly VIC LSM data can be found from the GCMD DIFs for GES_DISC_NLDAS_VIC0125_H_V002 and GES_DISC_NLDAS_VIC0125_M_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_VIC0125_H_V002 and http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_VIC0125_M_V002. Details about the NLDAS-2 configuration of the VIC LSM can be found in Xia et al. (2012). The version of the VIC model for the NLDAS-2 VIC data available from the NASA GES DISC is VIC-4.0.3; this version of the VIC model is the same as used in Sheffield et al. (2003). The NLDAS-2 VIC monthly climatology data contain forty-three fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_VIC.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For information about the vertical layers of the Soil Moisture Content (PDS 086), Soil Temperature (PDS 085), and Liquid Soil Moisture Content (PDS 151), please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf or the GrADS ctl file at ftp://hydro1.sci.gsfc.nasa.gov/data/gds/NLDAS/NLDAS_VIC0125_MC.002.ctl.
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Deep Ultraviolet Macroporous Silicon Filters Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:30:51.000ZThis SBIR Phase I proposal describes a novel method to make deep and far UV optical filters from macroporous silicon. This type of filter consists of an array of parallel, independent leaky waveguides made in the form of a free-standing, two-dimensionally ordered silicon structure with pore walls coated by a dielectric multilayer. The proposed filters offer unmatched levels of rejection within a very wide rejection band combined with a high level of transmission within the pass band that can be centered throughout the deep and far UV range. In addition, unlike common interference-based filters, the spectral position of the pass and rejection bands will not depend on the angle of incidence. The proposed filters will be light weight and may be manufactured cost-effectively in large quantities. In Phase I, it is proposed to demonstrate the feasibility of the method by fabricating pore structures with different pore wall coatings and measuring the transmission and other optical properties. In Phase II, optimized filters will be fabricated and their properties compared with design predictions. Phase III will involve product design, fabricating filter structures to meet customers' physical as well as optical needs, and marketing and sales investments.