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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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TRMM Microwave Imager (TMI) Gridded Oceanic Rainfall Product (TRMM Product 3A11) V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:52:56.000ZThe Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. TRMM was successfully launched on November 27, at 4:27 PM (EST) from the Tanegashima Space Center in Japan. The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer, which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I) instrument flown aboard the Defense Meteorological Satellite Program (DMSP) platforms. Microwave radiation is emitted by the Earth's surface and by water droplets within clouds. However, when layers of large ice particles are present in upper cloud regions - a condition highly correlated with heavy rainfall - microwave radiation tends to scatter at frequencies above 19 GHz. The TMI detects radiation at five frequencies chosen to discriminate among these processes, thus revealing the likelihood of rainfall. The key to accurate retrieval of rainfall rates by this method is the deduction of cloud precipitation consistent with the radiation measurement at each frequency. The TMI frequencies are 10.65, 19.35, 37 and 85.5 GHz (dual polarization), and 21 GHz (vertical polarization only). The TMI Gridded Oceanic Rainfall Product, also known as TMI Emission, consists of 5 degree by 5 degree monthly oceanic rainfall maps using TMI Level 1 data as input. Statistics of the monthly rainfall, including number of samples, standard deviation, goodness-of-fit (of the brightness temperature histogram to the lognormal rainfall distribution function) and rainfall probability are also included in the output for each grid box. Spatial coverage is between 40 degrees North and 40 degrees South owing to the 35 degree inclination of the TRMM satellite. TMI brightness temperature histograms at 1 degree intervals are generated based on the 19, 21 and 19-21 GHz combination channels obtained from the Level 1B (calibrated brightness temperature) TMI product. Monthly rainfall indices over the ocean are derived by statistically matching monthly histograms of brightness temperatures with model calculated rainfall Probability Distribution Functions (PDF) using the 19-21 GHz combination data. Retrieved monthly rainfall data must pass a quality test based on the quality of the PDF fit. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the TMI measurements. A file contains 12 arrays of rainfall data and supporting information each of dimension 72 x 16, with a file size of about 40 KB (uncompressed). The HDF-EOS "grid" structure is used to accommodate the actual geophysical data arrays. There is 1 file of TMI 3A11 data produced per month.
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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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GPM GROUND VALIDATION NASA S-BAND DUAL POLARIMETRIC (NPOL) DOPPLER RADAR IFLOODS V2
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:47:15.000ZThe GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloods V2 data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign. The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign. The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS V2 data is available in Universal [Radar] Format (UF).
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Superconducting Electric Boost Pump for Nuclear Thermal Propulsion Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:34:52.000ZA submersible, superconducting electric boost pump sized to meet the needs of future Nuclear Thermal Propulsion systems in the 25,000 lbf thrust range is proposed. The proposed solution combines active electronic speed control technology with state-of-the-art cavitation suppression techniques to meet the near-zero Net Positive Suction Head requirements with up to 50% vapor content and enables a higher level of safety, reliability and operability for the Nuclear Thermal Propulsion (NTP) system than turbine driven pumps. The proposed pump configuration enables placement in, or close-coupled to the tank where it can be shielded from the reactor to prevent neutron flux heating. Evaluation of NTP power cycles will enable feasibility determination for driving the boost pump, and possibly the main pump, electrically and provides a comparison of approaches for the derivation of requirements needed in the development of an ultra-long life, highly reliable integrated pump system for NTP. The requirements, system trades and benefits analysis, conceptual design, risk reduction and Phase II planning will be documented to enable further development and TRL transition from TRL 3 at the completion of Phase I to TRL 5 at the completion of Phase II.
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GPM GROUND VALIDATION NASA S-BAND DUAL POLARIMETRIC (NPOL) DOPPLER RADAR IFLOODS V2
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:47:13.000ZThe GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloods V2 data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign. The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign. The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS V2 data is available in Universal [Radar] Format (UF).
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Mobile Passive Optical Imager for Remote Gas Detection Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:38:03.000ZTunable filters based on electro-optic effect have shown great potential in detecting gas concentration through obtaining its absorption spectrum. In filter-based technologies, the x-y 2D imaging is usually taken at once, while the wavelength dimension is performed by tunable filters that are mounted in front of a monochrome IR camera. Several types of tunable filters are currently available, including mechanically tuned Fabry-Perot etalon (FP filter), liquid-crystal Lyot-Ohman filters and acousto-optic filters. However, these EO tuning technologies have some shortages, such as slow tuning speed, bulky design, limited working band and small aperture. Boston Applied Technologies, Inc. (BATi) proposes a unique remote sensing system which is based on a tunable filter with under millisecond tuning time for high speed detection of gas concentration. The core part, tunable filter, of the proposed system is made of patented OptoCeramic® material. The system features high speed, wide spectral range from visible to MWIR, low cost, light weight, big aperture, and robust.
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Designer's Situation Awareness Toolbox (DeSAT) Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:22:49.000ZThis SBIR will develop a design decision support tool that will assist designers in providing a powerful, supportive work environment for aviation crews that support the maintenance of a high level of situation awareness in the flight environment. DeSAT will be developed as a design decision support system providing the capability to (1) analyze the situation awareness requirements associated with operational requirements (which could include ground based or flight based crew members), (2) compare situation awareness information requirements to system design features to identify potential situation awareness problems and deficiencies early in the design process, and (3) evaluate the degree to which design concepts support SA via the Situation Awareness Global Assessment Technique (SAGAT). DeSAT will be developed for analysis of SA for both individual crew stations and for distributed teams operating across flight and time. DeSAT will allow designers to modify design concepts early in the design process to ensure that they provide the needed situation awareness to system users.
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GPM GROUND VALIDATION NASA S-BAND DUAL POLARIMETRIC (NPOL) DOPPLER RADAR IFLOODS V2
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:47:14.000ZThe GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloods V2 data set was collected from April 30, 2013 to June 16, 2013 near Traer, Iowa as a part of the Global Precipitation Measurement Mission (GPM) Iowa Flood Studies (IFloodS) campaign. The NASA NPOL radar, developed by a research team from Wallops Flight Facility, is a fully transportable and self-contained S-band (10 cm), scanning dual-polarimetric, Doppler research radar that collected and operated nearly continuously during the IFloodS field campaign. The GPM Ground Validation NASA S-Band Dual Polarimetric (NPOL) Doppler Radar IFloodS V2 data is available in Universal [Radar] Format (UF).
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TRMM Microwave Imager (TMI) Gridded Oceanic Rainfall Product (TRMM Product 3A11) V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:52:56.000ZThe Tropical Rainfall Measuring Mission (TRMM) is a joint U.S.-Japan satellite mission to monitor tropical and subtropical precipitation and to estimate its associated latent heating. TRMM was successfully launched on November 27, at 4:27 PM (EST) from the Tanegashima Space Center in Japan. The TRMM Microwave Imager (TMI) is a nine-channel passive microwave radiometer, which builds on the heritage of the Special Sensor Microwave/Imager (SSM/I) instrument flown aboard the Defense Meteorological Satellite Program (DMSP) platforms. Microwave radiation is emitted by the Earth's surface and by water droplets within clouds. However, when layers of large ice particles are present in upper cloud regions - a condition highly correlated with heavy rainfall - microwave radiation tends to scatter at frequencies above 19 GHz. The TMI detects radiation at five frequencies chosen to discriminate among these processes, thus revealing the likelihood of rainfall. The key to accurate retrieval of rainfall rates by this method is the deduction of cloud precipitation consistent with the radiation measurement at each frequency. The TMI frequencies are 10.65, 19.35, 37 and 85.5 GHz (dual polarization), and 21 GHz (vertical polarization only). The TMI Gridded Oceanic Rainfall Product, also known as TMI Emission, consists of 5 degree by 5 degree monthly oceanic rainfall maps using TMI Level 1 data as input. Statistics of the monthly rainfall, including number of samples, standard deviation, goodness-of-fit (of the brightness temperature histogram to the lognormal rainfall distribution function) and rainfall probability are also included in the output for each grid box. Spatial coverage is between 40 degrees North and 40 degrees South owing to the 35 degree inclination of the TRMM satellite. TMI brightness temperature histograms at 1 degree intervals are generated based on the 19, 21 and 19-21 GHz combination channels obtained from the Level 1B (calibrated brightness temperature) TMI product. Monthly rainfall indices over the ocean are derived by statistically matching monthly histograms of brightness temperatures with model calculated rainfall Probability Distribution Functions (PDF) using the 19-21 GHz combination data. Retrieved monthly rainfall data must pass a quality test based on the quality of the PDF fit. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the TMI measurements. A file contains 12 arrays of rainfall data and supporting information each of dimension 72 x 16, with a file size of about 40 KB (uncompressed). The HDF-EOS "grid" structure is used to accommodate the actual geophysical data arrays. There is 1 file of TMI 3A11 data produced per month.