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Map of Med-QUEST Office Locations
data.hawaii.gov | Last Updated 2018-07-26T13:01:17.000ZLocations
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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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Trails
data.cityofgp.com | Last Updated 2019-10-31T15:14:19.000ZMajor access points and markers, trails, trails - gravel, trails - natural surface and trails . Historical linework shows only if trail is present or not, recent dev'ts show actual location of trail from asbuilt drawing offsets.
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Residential Snow Plowing Schedule
data.cityofgp.com | Last Updated 2016-11-14T20:56:27.000ZCity of Grande Prairie Snow and Ice Control Policy 606 - Schedule 5 Residential by Day
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NLDAS Noah Land Surface Model L4 Monthly 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:56:05.000ZThis data set contains a series of land surface parameters simulated from the Noah 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 Noah model data were generated from the NLDAS-2 hourly Noah 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. Also for the first month (Jan 1979), because the variables listed as instantaneous in the README file (http://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf) do not have valid data exactly on 00Z 02 Jan 1979, and this one hour is not included in the average for this month only. Brief description about the NLDAS-2 monthly Noah model can be found from the GCMD DIF for GES_DISC_NLDAS_NOAH0125_H_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_NOAH0125_H_V002. Details about the NLDAS-2 configuration of the Noah LSM can be found in Xia et al. (2012). The NLDAS-2 Noah monthly data contain fifty-two 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_NOAH.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_NOAH0125_M.002.ctl.
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Utilizing MIL-STD-1553B Digital Data Bus Devices Across an IEEE-1394A Serial Bus Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:41:52.000ZUtilizing MIL-STD-1553B Digital Data Bus Devices Across an IEEE-1394A Serial Bus Project
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Advanced Modular, Multi-Channel, High Speed Fiber Optic Sensing System for Acoustic Emissions Monitoring Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:14:18.000ZIntelligent Fiber Optic Systems Corporation (IFOS) proposes to prove the feasibility of innovations based on ultra-light-weight, ultra-high-speed, multi-channel, optical fiber sensor system for acoustics emissions (AE) monitoring for detection of impact damage and cracks in structural components in Aerospace structures. The project goals are to design an ultra-high-speed/high resolution with a small foot print fiber Bragg grating (FBG) sensor interrogator, construct a system model, test platform including embedded FBG sensors and develop signal processing algorithms to identify and measure AE signals in the presence of a quasi-static background strain field. The system model will demonstrate proof-of-principle and the test results will provide proof-of-functionality of the proposed sensor system for monitoring AE including using the advanced fiber optic sensor signal processing algorithms. AE will be simulated in an Aluminum by performing pencil break or impact hammer tests. The model test results will be compared to the measurements made concurrently by a standard single channel piezoelectric AE transducer. IFOS and its collaborators in this project will develop a Phase II strategy plan that includes development and integration strategy, potential demonstration opportunities, program schedule, and estimated costs. The key proposed innovation is a modular, light-weight, ultra-high-speed, multi-channel, optical fiber sensor system for AE monitoring.
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Aircraft Anomaly Prognostics Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:14:40.000ZRidgetop Group will leverage its proven Electromechanical Actuator (EMA) prognostics methodology to develop an advanced model-based actuator prognostic reasoner (MAPR). Ridgetop's concept is a self-contained, embedded prognostic reasoner with a passive connection to common avionic data busses. By monitoring actuator health in real time and providing early warning of incipient fault conditions, the proposed MAPR would enable condition based maintenance (CBM) of critical avionic flight control systems and support safer, more reliable next generation air transportation. The novel approach will effectively decouple the passive prognostic reasoner from the target flight control system, or actuator, and will support multiple avionic data bus interfaces, such as MIL-STD-1553, easing adoption, validation, integration, and support. Potentially, a single MAPR could monitor multiple flight control systems, reducing overall sensor costs. Furthermore, an embedded MAPR implementation with field upgradeable firmware would support evolving interface standards and prognostic health measurement capabilities. Finally, the proposed MAPR architecture is ideally suited for hardware-in-the-loop (HIL) testing, which dramatically accelerates technology readiness and commercial introduction.
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A Simulation Testbed for Dynamic Air Corridors within the Next Generation Air Transportation System Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:24:12.000ZThe key innovation in this effort is the development of a simulation testbed for identifying dynamic air corridors that can increase aircraft throughput in and around the terminal airspace. In this proposal, an air corridor is a three-dimensional region of space that is intended to safely isolate a stream of aircraft from other aircraft outside the corridor. Air corridors/routes effectively exist today in two forms: static and dynamic. Static air corridors exist in the form of published standard arrival routes (STAR) and standard instrument departures (SID). Dynamic air corridors are effectively created when air traffic control (ATC) issues vector and speed instructions to aircraft. The proposed testbed would identify dynamic air corridors that provide ATC with more options that are optimized to provide greater throughput than is currently available with today's static air corridors. The testbed would continuously identify dynamic air corridors in order to adapt to changing hazards, changing queues of arriving and departing aircraft, and changing runway configurations. We further propose integrating the simulation testbed with NASA's Airspace Concept Evaluation Software (ACES) in order to assess the impact of dynamic air corridors on the entire U.S. national airspace.
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Life Science Research Sample Transfer Technology for On Orbit Analysis Project
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:09:52.000ZWith retirement of the space shuttle program, microgravity researchers can no longer count on bringing experiment samples back to earth for post-flight analysis. Locker-sized processing facilities, which were typically transported up to and down from the International Space Station during the shuttle era, quite simply consume too much volume, mass, and power to be accommodated as part of both the upmass and downmass on current space transportation vehicles. As a result, more analysis must be accomplished on ISS, which makes on-orbit analytical tools critical to the continued success of microgravity research. The Analytical Cassette transfer Tool (ACT) is a low-cost, disposable device that efficiently transfers experiment samples in a safe and contained manner from unique experiment specific spaceflight hardware to on-orbit analytical tools that enable real-time analysis in microgravity. ACT interfaces with several flight qualified processing payloads to extract experiment samples via a needle-less septum and then allows transfer of those samples into a number of different on-orbit analytical devices, including such instrumentation as the Light Microscopy Module, the Microfluidic Flow Cytometer, a Spectrophotometer, and/or a Mass Spectrometer. Applications in life and environmental sciences include sampling liquid cultures/suspensions or sampling spacecraft water for quality evaluation. ACT functions within or outside of on-orbit gloveboxes to safely transfer any liquid material from one container fitted with the ACT mating receptacle to another container fitted with a receptacle. Its safe, simple, effective, and with its economical advantage, ACT is destined to become the new standard fluid transfer device for the ISS and future space research venues. For the Phase II project, Techshot will develop a flight version of the ACT and subject it to the major spaceflight integration tests.