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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

A 10,000-gpm liquid hydrogen transfer system for the Saturn/Apollo program.

Brief description of the design and operation of the liquid hydrogen transfer system used to service the Saturn V launch vehicle. The cryogenic loading of the huge booster begins eight hours before the scheduled liftoff. The first three hours of fueling are spent in cold hydrogen gas conditioning of the fuel tank. The cold hydrogen gas is provided by vaporizing liquid hydrogen from the storage tank and routing the resultant gas through the fill system. Boil-off losses after loading are continuously replaced through control valves which are driven by a computer system. The liquid hydrogen transfer system is made up of a number of subsystems including the 850,000 gal storage tank whose boil-off losses amount to only 200 gal/day, the pressurization system, the burn pond for controlled disposal of hydrogen waste gas, the storage tank fill manifold, and the hazardous gas monitoring system. Some of the subsystems and components are redundant to provide a high degree of reliability.

Wybranowski, E., Jr.↗
NASA NTRS2001

Improving Global Modeling and Data Analysis Using Remotely-Sensed Rainfall Data: Lessons From TRMM and Plans for GPM

I will discuss the need for accurate rainfall observations to improve our ability to model the earth's climate and improve short-range weather forecasts. I will give an overview of the recent progress in using of rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and diagnose state-dependent systematic errors in physical parameterizations. I will outline the current and future research strategies in preparation for the Global Precipitation Mission.

Hou, Arthur Y.↗
NASA NTRS2004

GMS-based"Future Time" Rainfall Data Assimilation for Mesoscale Weather Prediction over Korean Peninsula and Future Prospects with GPM Satellite Measurements

This study examines the use of satellite-derived nowcasted (short-term forecasted) rainfall over 3-hour time periods to gain an equivalent time increment in initializing a nonhydrostatic mesoscale model used for predicting convective rainfall events over the Korean peninsula. Infrared (IR) window measurements from the Japanese Geostationary Meteorological Satellite (GMS) are used to specify latent heating for a spinup period of the model - but in future time -- thus initializing in advance of actual time in the framework of a prediction scenario. The main scientific objective of the study is to investigate the strengths and weaknesses of this approach insofar as data assimilation, in which the nowcasted assimilation data are derived independently of the prognostic model itself. Although there have been various recent improvements in formulating the dynamics, thermodynamics, and microphysics of mesoscale models, as well as computer advances which allow the use of high resolution cloud-resolving grids and explicit latent heating over regional domains, spinup remains at the forefront of unresolved mesoscale modeling problems. In general, non-realistic spinup limits the skill in predicting the spatial-temporal distribution of convection and precipitation, primarily in the early hours of a. forecast, stemming from standard prognostic variables not representing the initial diabatic heating field produced by the ambient convection and cloud fields. The long-term goal of this research is to improve short-range (12-hour) quantitative precipitation forecasting (QPF) over the Korean peninsula through the use of innovative data assimilation methods based on geosynchronous satellite measurements. As a step in th~s direction, a non-standard data assimilation experiment in conjunction with GMS-retrieved nowcasted rainfall information introduced to the mesoscale model is conducted. The 3-hourly precipitation forecast information is assimilated through nudging the associated diabatic heating during the early stages of a forecast period. This procedure is expected to enhance details in the moisture field during model integration, and thus improve spinup performance, assuming the errors in the future time latent heating data ate less than intrinsic model background errors.

Smith, Eric A.↗
NASA NTRS2005

Anticipated Improvements to Net Surface Freshwater Fluxes from GPM

Evaporation and precipitation over the oceans play very important roles in the global water cycle, upper-ocean heat budget, ocean dynamics, and coupled ocean-atmosphere dynamics. In the conventional representation of the terrestrial water cycle, the assumed role of the oceans is to act as near-infinite reservoirs of water with the main drivers of the water cycle being land- atmosphere interactions in which excess precipitation (P) over evaporation (E) is returned to the oceans as surface runoff and baseflow. Whereas this perspective is valid for short space and time scales -- fundamental principles, available observed estimates, and results from models indicate that the oceans play a far more important role in the large-scale water cycle at seasonal and longer timescales. Approximately 70-80% of the total global evaporation and precipitation occurs over oceans. Moreover, latent heat release into the atmosphere over the oceans is the major heat source driving global atmospheric circulations, with the moisture transported by circulations from oceans to continents being the major source of water precipitating over land. Notably, the major impediment in understanding and modeling the oceans role in the global water cycle is the lack of reliable net surface freshwater flux estimates (E - P fluxes) at the salient spatial and temporal resolutions, i.e., consistent coupled weekly to monthly E - P gridded datasets.

Smith, Eric A.↗
NASA NTRS2009

Global Precipitation Measurement: GPM Microwave Imager (GMI) Algorithm Development Approach

This slide presentation reviews the approach to the development of the Global Precipitation Measurement algorithm. This presentation includes information about the responsibilities for the development of the algorithm, and the calibration. Also included is information about the orbit, and the sun angle. The test of the algorithm code will be done with synthetic data generated from the Precipitation Processing System (PPS).

Stocker, Erich Franz↗
NASA NTRS2010

Global Precipitation Measurement (GPM) Validation Network

The method averages the minimum TRMM PR and Ground Radar (GR) sample volumes needed to match-up spatially/temporally coincident PR and GR data types. PR and GR averages are calculated at the geometric intersection of the PR rays with the individual Ground Radar(GR)sweeps. Along-ray PR data are averaged only in the vertical, GR data are averaged only in the horizontal. Small difference in PR & GR reflectivity high in the atmosphere, relatively larger differences. Version 6 TRMM PR underestimates rainfall in the case of convective rain in the lower part of the atmosphere by 30 to 40 percent.

Schwaller, Mathew↗
NASA NTRS2011

Global Precipitation Measurement (GPM) Mission Development Status

Mission Objective: (1) Improve scientific understanding of the global water cycle and fresh water availability (2) Improve the accuracy of precipitation forecasts (3) Provide frequent and complete sampling of the Earth s precipitation Mission Description (Class B, Category I): (1) Constellation of spacecraft provide global precipitation measurement coverage (2) NASA/JAXA Core spacecraft: Provides a microwave radiometer (GMI) and dual-frequency precipitation radar (DPR) to cross-calibrate entire constellation (3) 65 deg inclination, 400 km altitude (4) Launch July 2013 on HII-A (5) 3 year mission (5 year propellant) (6) Partner constellation spacecraft.

Azarbarzin, Ardeshir Art↗
NASA NTRS2016

GPM Rainfall-Based Streamflow Analyses for East Africa

SERVIR is a joint project of NASA and US Agency for International Development (USAID). Mission is to use satellite data and geospatial technology to help developing countries manage resources, land use, and climate risks. Means to serve, in Spanish.

remote sensing↗