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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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NLDAS Mosaic Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:56:09.000ZThis monthly climatology 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. 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 Mosaic LSM data can be found from the GCMD DIFs for GES_DISC_NLDAS_MOS0125_H_V002 and GES_DISC_NLDAS_MOS0125_M_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_MOS0125_H_V002 and http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_MOS0125_M_V002. Details about the NLDAS-2 configuration of the Mosaic LSM can be found in Xia et al. (2012). The NLDAS-2 Mosaic model monthly climatology data set contains 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. There are six vertical levels for the Soil Moisture (PDS 086) in the Mosaic GRIB files. For more information, 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_MC.002.ctl.
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Software for Application of HHT Technologies to Time Series Analysis Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:27:16.000ZThe proposed innovation is a robust and user-friendly software environment where NASA researchers can customize the latest HHT technologies for the LISA (and LIGO) application. The proposed technology will include the latest discoveries and inventions not available in the state-of-the-art. Its taxonomy includes gravitational sensors and sources, expert systems, portable data analysis tools, software development environments, and software tools for distributed analysis and simulation. The disturbance caused by the passage of a gravitational wave is expected to be very small and will be measured with laser interferometry. The Hilbert-HuangTransform (HHT)and related analysis technologies developed since the original concept has been used successfully in other applications to extract non-linear and transient signal comonents of very small magnitude with respect to the measured signal. The proposed research and development team has participated in the latest cycle of technology development related to the HHT at the theoretical, implementation, and application levels. Not only will the creation of the proposed software contribute to the data analysis of the gravitational wave signals in the laser interferometry measurements (for both LIGO and LISA data), but also in other applications within and outside NASA's mission.
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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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SBUV2/NOAA-18 Ozone (O3) Profile and Total Column Ozone Monthly L3 Global 5.0deg Lat Zones V1
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:44:52.000ZThe Solar Backscattered Ultra Violet (SBUV) from NOAA-18 Level-3 monthly zonal mean (MZM) product (SBUV2N18L3zm) 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 78 months of data from July 2005 through December 2011. 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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TRMM Precipitation Radar (PR) Level 2 Rainfall Rate and Profile Product (TRMM Product 2A25) V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:52:32.000ZThe TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines the layer depth of the precipitation. The objectives of 2A25 is to correct for the rain attenuation in measured radar reflectivity and to estimate the instantaneous three-dimensional distribution of rain from the TRMM Precipitation Radar (PR) data. The estimates of attenuation-corrected radar reflectivity factor and rainfall rate are given at each resolution cell of the PR. The estimated near-surface rainfall rate and average rainfall rate between the two pre-defined altitudes (2 and 4 km) are also calculated for each beam position. 2A25 basically uses a hybrid of the Hitschfeld-Bordan method and the surface reference method to estimate the vertical true radar reflectivity (Z) profile. (The hybrid method is described in Iguchi and Meneghini (1994)). The vertical rain profile is then calculated from the estimated true Z profile by using an appropriate Z-R relationship. The attenuation correction is, in principle, based on the surface reference method. This method assumes that the decrease in the apparent surface cross section (delta sigma-zero) is caused by the propagation loss in rain. The coefficient a in the k-Z relationship, k=a Z**b, is adjusted in such a way that the path-integrated attenuation (PIA) estimated from the measured Zm-profile will match the delta sigma-zero. The attenuation correction of Z is carried out by the Hitschfeld-Bordan method with the modified a. Since a is adjusted, this type of surface reference method is called the a-adjustment method. The a-adjustment method assumes that the discrepancy between the PIA estimate from delta sigma-zero and that from the measured Zm-profile can be attributed to the inappropriate choice of a values, which may vary depending on the raindrop size distribution and other conditions. It assumes that the radar is properly calibrated and that the measured Zm has no error. In order to avoid inaccuracies in the attenuation correction when rain is weak, a hybrid of the surface reference method and the Hitschfeld-Bordan method is used (Iguchi and Meneghini, 1994). The PIA is first estimated from the precipitation echo alone. The weight given by the hybrid method to the PIA estimate from the surface reference increases as the attenuation estimate increases. When rain is very weak and the attenuation estimate is small, the PIA estimate from the surface reference is effectively neglected. With the introduction of the hybrid method, the divergence associated with the Hitschfeld-Bordan method is also prevented. One major difference from the method described in the above reference is that, in order to deal with the beam-filling problem, a non-uniformity parameter is introduced and is used to correct the bias in the surface reference arising from the horizontal non-uniformity of rain field within the beam. Since radar echoes from near the surface are contaminated by the mainlobe clutter, the rain estimate at the lowest point in the clutter-free region is given as the near-surface rainfall rate for each angle bin. Spatial coverage is between 38 degrees North and 38 degrees South, owing to the 35 degree inclination of the TRMM satellite. This orbit provides extensive coverage in the tropics and allows each location to be covered at a different local time each day, enabling the analysis of the diurnal cycle of precipitation. There are, in general, 9150 scans along the orbit, with each scan consisting of 49 rays. The scan width is about 220 km. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the PR measurements. A fi...
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TRMM Microwave Imager (TMI) Level 3 Monthly 0.5 degree x 0.5 degree Profiling V7 (3A12) at GES DISC V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:53:10.000ZThis document provides basic information on 3A12, TMI Monthly 0.5 deg. x 0.5 deg. Profiling. Algorithm 3A12 produces global 0.5 deg. x 0.5 deg. monthly gridded means using 2A12 data. Vertical hydrometeor profiles and surface rainfall means are computed. Various pixel counts are also reported. The granule size is one month.This document provides basic information on 3A12, TMI Monthly 0.5 deg. x 0.5 deg. Profiling. Algorithm 3A12 produces global 0.5 deg. x 0.5 deg. monthly gridded means using 2A12 data. Vertical hydrometeor profiles and surface rainfall means are computed. Various pixel counts are also reported. The granule size is one month. The average operating altitude for TRMM was changed from 350 to 403 km during the period of August 7-24, 2001. This orbit boost maneuver extended the mission life significantly. All post-boost data products had been released by the TRMM Science Project, as of early December 2001. All TRMM data products (post- and pre-boost) are available via the TRMM data search-and-order system at http://mirador.gsfc.nasa.gov/cgi-bin/mirador/presentNavigation.pl?tree=project&project=TRMM . The time period before August 7, 2001 is referred to as pre-boost, and the time period after August 24, 2001 is referred to as post-boost. [Summary provided by the GES-DISC DAAC]
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CogGauge Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:22:36.000ZCog-Gauge is a portable hand-held game that can be used by astronauts and crew members during space exploration missions to assess their cognitive workload decrements that possibly result from fatigue, stress, or neurocognitive deficits. Cog-Gauge combines behavioral workload assessment using a dual-task approach with predictive workload models to counter the effects of game learning. The game will be built using an iterative usability driven approach where emphasis will be placed on building an engaging relevant game that builds from contextual task analysis and user profiling. The specific technical challenges foreseen are integrating two approaches of cognitive workload modeling, and using learning curves to model game learning, then using algorithms to determine a user's workload as soon as they complete a timed interaction with the game. Specific questions to address pertain to feasibility of proposed solution and hardware/software requirements.
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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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Nanotube Electrodes for Dust Mitigation Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:11:57.000ZDust mitigation is critical to the survivability of vehicle and infrastructure components and systems and to the safety of astronauts during EVAs and planetary surface operations. By coupling Eikos Invisicon<SUP>REG</SUP> nanocomposite conductors with existing dust mitigation Dust Shield technology developed at NASA-KSC, the Phase I program demonstrated an enabling approach to producing electrodynamic dust mitigation devices on a wide variety of surfaces not possible with traditional metal based electrode materials. Eikos reproduced proven NASA spiral electrodes using Invisicon<SUP>REG</SUP> patterned onto transparent plastics, Tyvek<SUP>REG</SUP> fabric, and silicone rubber sheets; employing inkjet and spray deposition methods, two CNT ink formulations, and four dielectric binders to create working devices. These Invisicon<SUP>REG</SUP>-based devices are far more flexible then traditional devices and exhibit superior durability to abrasion, elongation, and thermal cycling. A dust mitigation system utilizing this technology has broad value to many NASA mission directorates and terrestrial commercial applications. The Phase II project will build on these successes and integrate the electrode into larger surfaces, and more complex components. Further, extensive dust mitigation, and both environmental and mechanical testing, will be conducted to position this electrode technology for insertion into windows, fabrics, and elastomeric components in space and terrestrial applications.