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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Simulated convective systems using a cloud resolving model: Impact of large-scale temperature and moisture forcing using observations and GEOS-3 reanalysis

The GCE (Goddard Cumulus Ensemble) model, which has been developed and improved at NASA Goddard Space Flight Center over the past two decades, is considered as one of the finer and state-of-the-art CRMs (Cloud Resolving Models) in the research community. As the chosen CRM for a NASA Interdisciplinary Science (IDS) Project, GCE has recently been successfully upgraded into an MPI (Message Passing Interface) version with which great improvement has been achieved in computational efficiency, scalability, and portability. By basically using the large-scale temperature and moisture advective forcing, as well as the temperature, water vapor and wind fields obtained from TRMM (Tropical Rainfall Measuring Mission) field experiments such as SCSMEX (South China Sea Monsoon Experiment) and KWAJEX (Kwajalein Experiment), our recent 2-D and 3-D GCE simulations were able to capture detailed convective systems typical of the targeted (simulated) regions. The GEOS-3 [Goddard EOS (Earth Observing System) Version-3] reanalysis data have also been proposed and successfully implemented for usage in the proposed/performed GCE long-term simulations (i.e., aiming at producing massive simulated cloud data -- Cloud Library) in compensating the scarcity of real field experimental data in both time and space (location). Preliminary 2-D or 3-D pilot results using GEOS-3 data have generally showed good qualitative agreement (yet some quantitative difference) with the respective numerical results using the SCSMEX observations. The first objective of this paper is to ensure the GEOS-3 data quality by comparing the model results obtained from several pairs of simulations using the real observations and GEOS-3 reanalysis data. The different large-scale advective forcing obtained from these two kinds of resources (i.e., sounding observations and GEOS-3 reanalysis) has been considered as a major critical factor in producing various model results. The second objective of this paper is therefore to investigate and present such an impact of large-scale forcing on various modeled quantities (such as hydrometeors, rainfall, and etc.). A third objective is to validate the overall GCE 3-D model performance by comparing the numerical results with sounding observations, as well as available satellite retrievals.

Shie, C.-L.↗
NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document: Cloud Analyses and Determination of Improved Top of Atmosphere Fluxes (Subsystem 4) - Volume 3

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 3 details the advanced CERES methods for performing scene identification and inverting each CERES scanner radiance to a top-of-the-atmosphere (TOA) flux. CERES determines cloud fraction, height, phase, effective particle size, layering, and thickness from high-resolution, multispectral imager data. CERES derives cloud properties for each pixel of the Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and the Earth Observing System (EOS) moderate-resolution imaging spectroradiometer. Cloud properties for each imager pixel are convolved with the CERES footprint point spread function to produce average cloud properties for each CERES scanner radiance. The mean cloud properties are used to determine an angular distribution model (ADM) to convert each CERES radiance to a TOA flux. The TOA fluxes are used in simple parameterization to derive surface radiative fluxes. This state-of-the-art cloud-radiation product will be used to substantially improve our understanding of the complex relationship between clouds and the radiation budget of the Earth-atmosphere system.

Source record↗
NASA NTRS2016

Update on the NASA Glenn Propulsion Systems Lab Ice Crystal Cloud Characterization (2015)

NASA Glenn's Propulsion Systems Lab (PSL), an altitude engine test facility, was outfitted with a spray system to generate ice crystals. The first ice crystal characterization test occurred in 2012. At PSL, turbine engines and driven rigs can experience ice crystal icing at flight altitudes, temperatures and Mach numbers. To support these tests, four ice crystal characterizations have been conducted in two different facility configurations. In addition, super-cooled liquid and mixed phase clouds have also been generated. This paper will discuss the recent learning from the previous two calibrations. It will describe some of the 12-parameter calibration space, and how those parameters interact with each other, the instrumentation used to characterize the cloud and present a sample of the cloud characterization results.

Ice Clouds↗
NASA NTRS1999

Vertical Profiles of Latent Heat Release and Their Retrieval for TOGA COARE Convective Systems Using a Cloud Resolving Model, SSM/I, and Ship-borne Radar Data

Latent heating profiles associated with three (TOGA COARE) Tropical Ocean and Global Atmosphere Coupled Ocean Atmosphere Response Experiment active convective episodes (December 10-17 1992; December 19-27 1992; and February 9-13 1993) are examined using the Goddard Cumulus Ensemble (GCE) Model and retrieved by using the Goddard Convective and Stratiform Heating (CSH) algorithm . The following sources of rainfall information are input into the CSH algorithm: Special Sensor Microwave Imager (SSM/1), Radar and the GCE model. Diagnostically determined latent heating profiles calculated using 6 hourly soundings are used for validation. The GCE model simulated rainfall and latent heating profiles are in excellent agreement with those estimated by soundings. In addition, the typical convective and stratiform heating structures (or shapes) are well captured by the GCE model. Radar measured rainfall is smaller than that both estimated by the GCE model and SSM/I in all three different COARE IFA periods. SSM/I derived rainfall is more than the GCE model simulated for the December 19-27 and February 9-13 periods, but is in excellent agreement with the GCE model for the December 10-17 period. The GCE model estimated stratiform amount is about 50% for December 19-27, 42% for December 11-17 and 56% for the February 9-13 case. These results are consistent with large-scale analyses. The accurate estimates of stratiform amount is needed for good latent heating retrieval. A higher (lower) percentage of stratiform rain can imply a maximum heating rate at a higher (lower) altitude. The GCE model always simulates more stratiform rain (10 to 20%) than the radar for all three convective episodes. SSM/I derived stratiform amount is about 37% for December 19-27, 48% for December 11-17 and 41% for the February 9-13 case. Temporal variability of CSH algorithm retrieved latent heating profiles using either GCE model simulated or radar estimated rainfall and stratiform amount is in good agreement with that diagnostically determined for all three periods. However, less rainfall and a smaller stratiform percentage estimated by radar resulted in a weaker (underestimated) latent heating profile and a lower maximum latent heating level compared to those determined diagnostically. Rainfall information from SSM/I can not retrieve individual convective events due to poor temporal sampling. Nevertheless, this study suggests that a good 4r, rainfall retrieval from SSM/I for a convective event always leads to a good latent heating retrieval. Sensitivity testing has been performed and the results indicate that the SSM/I derived time averaged stratiform amount may be underestimated for December 19-27. Time averaged heating profiles derived from SSM/I, however, are not in bad agreement with those derived by soundings for the December 10-17 convective period. The heating retrievals may be more accurate for longer time scales provided there is no bias in the sampling.

Tao, Wei-Kuo↗
NASA NTRS2008

Lidar System for Airborne Measurement of Clouds and Aerosols

A lidar system for measuring optical properties of clouds and aerosols at three wavelengths is depicted. The laser transmitter is based on a Nd:YVO4 laser crystal pumped by light coupled to the crystal via optical fibers from laser diodes that are located away from the crystal to aid in dissipating the heat generated in the diodes and their drive circuits. The output of the Nd:YVO4 crystal has a wavelength of 1064 nm, and is made to pass through frequency-doubling and frequency-tripling crystals. As a result, the net laser output is a collinear superposition of beams at wavelengths of 1064, 532, and 355 nm. The laser operates at a pulse-repetition rate of 5 kHz, emitting per-pulse energies of 50 microJ at 1064 nm, 25 microJ at 532 nm and 50 microJ at 355 nm. An important feature of this system is an integrating sphere located between the laser output and the laser beam expander lenses. The integrating sphere collects light scattered from the lenses. Three energy-monitor detectors are located at ports inside the integrating sphere. Each of these detectors is equipped with filters such that the laser output energy is measured independently for each wavelength. The laser output energy is measured on each pulse to enable the most accurate calibration possible. The 1064-nm and 532-nm photodetectors are, more specifically, single photon-counting modules (SPCMs). When used at 1064 nm, these detectors have approximately 3% quantum efficiency and low thermal noise (fewer than 200 counts per second). When used at 532 nm, the SPCMs have quantum efficiency of about 60%. The photodetector for the 355-nm channel is a photon-counting photomultiplier tube having a quantum efficiency of about 20%. The use of photon-counting detectors is made feasible by the low laser pulse energy. The main advantage of photon-counting is ease of inversion of data without need for complicated calibration schemes like those necessary for analog detectors. The disadvantage of photon-counting detectors is that they inherently have narrow dynamic ranges. However, by using photon-counting detectors along with a high-repetition rate laser, it is possible to obtain wide dynamic range through accumulation of counts over many pulses.

McGill, Matthew↗
NASA NTRS2016

Update on the NASA Glenn Propulsion Systems Lab Ice Crystal Cloud Characterization (2015, 2016)

NASA Glenn's Propulsion Systems Lab, an altitude engine test facility, was outfitted with a spray system to generate ice crystals in 2011. Turbine engines and driven rigs can experience ice crystal icing at flight altitudes, temperatures and Mach numbers. To support these tests, four ice crystal characterizations have been conducted in two different facility configurations. In addition, super-cooled liquid and mixed phase clouds have also been generated. This paper represents a work in progress. It will describe some of the 11-parameter calibration space, and how those parameters interact with each other, the instrumentation used to characterize the cloud and present a sample of the cloud characterization results.

Engine Icing↗
NASA NTRS2009

Anvil Clouds of Tropical Mesoscale Convective Systems in Monsoon Regions

The anvil clouds of tropical mesoscale convective systems (MCSs) in West Africa, the Maritime Continent and the Bay of Bengal have been examined with TRMM and CloudSat satellite data and ARM ground-based radar observations. The anvils spreading out from the precipitating cores of MCSs are subdivided into thick, medium and thin portions. The thick portions of anvils show distinct differences from one climatological regime to another. In their upper portions, the thick anvils of West Africa MCSs have a broad, flat histogram of reflectivity, and a maximum of reflectivity in their lower portions. The reflectivity histogram of the Bay of Bengal thick anvils has a sharply peaked distribution of reflectivity at all altitudes with modal values that increase monotonically downward. The reflectivity histogram of the Maritime Continent thick anvils is intermediate between that of the West Africa and Bay of Bengal anvils, consistent with the fact this region comprises a mix of land and ocean influences. It is suggested that the difference between the statistics of the continental and oceanic anvils is related to some combination of two factors: (1) the West African anvils tend to be closely tied to the convective regions of MCSs while the oceanic anvils are more likely to be extending outward from large stratiform precipitation areas of MCSs, and (2) the West African MCSs result from greater buoyancy, so that the convective cells are more likely to produce graupel particles and detrain them into anvils

Cetrone, J.↗
NASA NTRS1988

A support architecture for reliable distributed computing systems

The Clouds project is well underway to its goal of building a unified distributed operating system supporting the object model. The operating system design uses the object concept of structuring software at all levels of the system. The basic operating system was developed and work is under progress to build a usable system.

Dasgupta, Partha↗
NASA NTRS2003

Impact of Aerosols and Atmospheric Thermodynamics on Cloud Properties within the Climate System

A combination of cloud-top and columnar droplet sizes derived from the multi Tropical Rainfall Measurement Mission (TRMM) sensors reveals the sensitivity of the aerosols effect on cloud-precipitation process due to environmental vertical thermodynamic structure. First, the magnitude of aerosol indirect effect could be larger with the analysis of columnar droplet sizes than that derived from the cloud-top droplet sizes, since column-droplet size can account for the broader droplet spectra in the cloud layers. Second, a combination of cloud- top and columnar droplet sizes reveals that the warm rain process is prevented regardless of the aerosols concentration under a high static stability such as when a strong temperature inversion exists, while a high aerosol concentration suppresses the warm rain formulation under a low static stability.

Matsui, Toshihisa↗
NASA NTRS1990

Aircraft observations and cloud-microwave radiative model simulations of a deep convective system

A 3D cloud model is used to simulate the storm structure of the June 29, 1986 storm system observed during the Cooperative Huntsville Meteorological Experiment (Dodge et al., 1986), and the results are linked to a microwave radiative transfer model for simulating aircraft observations. The results of cloud and radiative model simulations are then compared with radar data and aircraft microwave observations, respectively. It is shown that the degree of agreement between model simulations and the aircraft microwave observations depends on the model-derived microphysics of cloud and precipitation. It is found that the calculated values of the brightness temperature (Tb) at 92 GHz are close to the observed temperatures, while the calculated Tb values at 18 and 37 GHz are lower than the observed Tb.

Yeh, H.-Y. M.↗
NASA NTRS1994

System Design for a Spaceborne Cloud Rada

This paper presents some crucial design parameters and a strawman system design for a nadir-looking, 94-GHz spaceborne cloud profiling radar. This sensor is expected to provide cloud measurements at vertical resolution of 500 m and with a minimum detectable cloud reflectivity of slightly better than -30 dBZ. The radar design is intended to be accommodated by a spacecraft with limited resources. It uses a 2-m antenna and an extended interaction amplifier (EIA) that are readily available in either ground-based and airborne applications. For space application, improvements in the EIA lifetime and space qualification will be required. For various reasons, the spaceborne cloud radar system development is expected to be greatly benefited by the implementation of an aircraft cloud radar instrument.

Cloud Measurement Spaceborne Cloud↗