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At least 559 records · Page 31

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NASA NTRS1994

Physical Retrievals of Over-Ocean Rain Rate from Multichannel Microwave Imagery: Theoretical Characteristics of Normalized Polarization and Scattering Indices - Part 1

Microwave rain rate retrieval algorithms have most often been formulated in terms of the raw brightness temperatures observed by one or more channels of a satellite radiometer. Taken individually, single-channel brightness temperatures generally represent a near-arbitrary combination of positive contributions due to liquid water emission and negative contributions due to scattering by ice and/or visibility of the radiometrically cold ocean surface. Unfortunately, for a given rain rate, emission by liquid water below the freezing level and scattering by ice particles above the freezing level are rather loosely coupled in both a physical and statistical sense. Furthermore, microwave brightness temperatures may vary significantly (approx. 30-70 K) in response to geophysical parameters other than liquid water and precipitation. Because of these complications, physical algorithms which attempt to directly invert observed brightness temperatures have typically relied on the iterative adjustment of detailed micro-physical profiles or cloud models, guided by explicit forward microwave radiative transfer calculations. In support of an effort to develop a significantly simpler and more efficient inversion-type rain rate algorithm, the physical information content of two linear transformations of single-frequency, dual-polarization brightness temperatures is studied: the normalized polarization difference P of Petty and Katsaros (1990, 1992), which is intended as a measure of footprint-averaged rain cloud transmittance for a given frequency; and a scattering index S (similar to the polarization corrected temperature of Spencer et al.,1989) which is sensitive almost exclusively to ice. A reverse Monte Carlo radiative transfer model is used to elucidate the qualitative response of these physically distinct single-frequency indices to idealized 3-dimensional rain clouds and to demonstrate their advantages over raw brightness temperatures both as stand-alone indices of precipitation activity and as primary variables in physical, multichannel rain rate retrieval schemes. As a byproduct of the present analysis, it is shown that conventional plane-parallel analyses of the well-known foot-print-filling problem for emission-based algorithms may in some cases give seriously misleading results.

Petty, G. W.↗

NASA NTRS1985

Advance particle and Doppler measurement methods

Particle environments, i.e., rain, ice, and snow particles are discussed. Two types of particles addressed are: (1) the natural environment in which airplanes fly and conduct test flights; and (2) simulation environments that are encountered in ground-test facilities such as wind tunnels, ranges, etc. There are characteristics of the natural environment that one wishes to measure. The liquid water content (LWC) is the one that seems to be of most importance; size distribution may be of importance in some applications. Like snow, the shape of the particle may be an important parameter to measure. As one goes on to environment in simulated tests, additional parameters may be required such as velocity distribution, the velocity lag of the particle relative to the aerodynamic flow, and the trajectory of the particle as it goes through the aerodynamic flow and impacts on the test object.

Busch, C.↗

NASA NTRS2006

Dehydrating and Sterilizing Wastes Using Supercritical CO2

A relatively low-temperature process for dehydrating and sterilizing biohazardous wastes in an enclosed life-support system exploits (1) the superior mass-transport properties of supercritical fluids in general and (2) the demonstrated sterilizing property of supercritical CO2 in particular. The wastes to be treated are placed in a chamber. Liquid CO2, drawn from storage at a pressure of 850 psi (approx.=5.9 MPa) and temperature of 0 C, is compressed to pressure of 2 kpsi (approx.=14 MPa) and made to flow into the chamber. The compression raises the temperature to 10 C. The chamber and its contents are then further heated to 40 C, putting the CO2 into a supercritical state, in which it kills microorganisms in the chamber. Carrying dissolved water, the CO2 leaves the chamber through a back-pressure regulator, through which it is expanded back to the storage pressure. The expanded CO2 is refrigerated to extract the dissolved water as ice, and is then returned to the storage tank at 0 C

Brown, Ian J.↗

NASA NTRS1999

Charge Transfer Process During Collision of Riming Graupel Pellet with Small Ice Crystals within a Thundercloud

A charge transfer process during the collision of a riming graupel pellet and an ice-crystal at low temperature is proposed. During riming, the surface structure of graupel deviates from perfect crystalline structure. A concept of quasi-solid layer (QSL) formation on the surface is introduced. This QSL contains defects formed during riming. In absence of impurities, positively charged X-defect abundance is considered in the outer layer. These defects are assumed to be the charge carriers during the charge transfer process. Some part of the QSL is stripped off by the colliding ice crystals, which thereby gain some positive charge, leaving the graupel pellet negatively charged. With the proposed model, fC to pC of charge transfer is observed per collision. A transition temperature between -10 C to -15 C is also noted beyond which the QSL concept does not hold. This transition temperature is dependent on the bulk liquid water content of the cloud.

Datta, Saswati↗

NASA NTRS2012

NASA Glenn Icing Research Tunnel: Upgrade and Cloud Calibration

In 2011, NASA Glenn s Icing Research Tunnel underwent a major modification to it s refrigeration plant and heat exchanger. This paper presents the results of the subsequent full cloud calibration. Details of the calibration procedure and results are presented herein. The steps include developing a nozzle transfer map, establishing a uniform cloud, conducting a drop sizing calibration and finally a liquid water content calibration. The goal of the calibration is to develop a uniform cloud, and to build a transfer map from the inputs of air speed, spray bar atomizing air pressure and water pressure to the output of median volumetric droplet diameter and liquid water content.

VanZante, Judith Foss↗

NASA NTRS2012

NASA Glenn Icing Research Tunnel: 2012 Cloud Calibration Procedure and Results

VanZante, Judith Foss↗

NASA NTRS1990

Development of a phase Doppler based probe for icing cloud droplet characterization

The development and evaluation of a compact optical fiber probe (OFP) for airborne and wind tunnel icing cloud characterizations is described. This probe was based upon the proven phase Doppler technique for measuring the size and velocity of spherical drops. Direct comparisons of the size distributions from the standard PDPA with the OFP were used to confirm the reliability of the probe. After some improvements in the fiber coupling efficiency, the number density and liquid water content data agreed to within 15 percent.

Rudoff, R. C.↗

NASA NTRS1980

An empirical model for the complex dielectric permittivity of soils as a function of water content

Recent measurements on the dielectric properties of soils have shown that the variation of dielectric constant with moisture content depends on soil types. The observed dielectric constant increases only slowly with moisture content up to a transition point. Beyond the transition it increases rapidly with moisture content. The moisture value at transition region was found to be higher for high clay content soils than for sandy soils. Many mixing formulas reported in the literature were compared with, and were found incompatible with, the measured dielectric variations of soil-water mixtures. A simple empirical model was proposed to describe the dielectric behavior of the soil-water mixtures. This model employs the mixing of either the dielectric constants or the refraction indices of ice, water, rock, and air, and treats the transition moisture value as an adjustable parameter. The calculated mixture dielectric constants from the model were found to be in reasonable agreement with the measured results over the entire moisture range of 0-0.5 cu cm/cu cm. The transition moistures derived from the model range from 0.16 to 0.33 and are strongly correlated with the wilting points of the soils estimated from their textures. This relationship between transition moisture and wilting point provides a means of estimating soil dielectric properties on the basis of texture information.

Wang, J. R.↗

NASA NTRS1998

Remote Sensing of Clouds and Water Vapor with Submillimeter-Wave Radiometers

This paper focuses mostly on satellite microwave observations from UARS MLS (Upper Atmosphere Research Satellite Microwave Limb Sounder) at 186.5 and 203.2 GHz.

cloud emission↗

NASA NTRS2016

Global Linkages Originating from Decadal Oceanic Variability in the Subpolar North Atlantic

The anomalous decadal warming of the subpolar North Atlantic Ocean (SPNA), and the northward spreading of this warm water, has been linked to rapid Arctic sea ice loss and more frequent cold European winters. Recently, variations in this heat transport have also been reported to covary with global warming slowdown/acceleration periods via a Pacific climate response. We here examine the role of SPNA temperature variability in this Atlantic-Pacific climate connectivity. We find that the evolution of ocean heat content anomalies from the subtropics to the subpolar region, likely due to ocean circulation changes, coincides with a basin-wide Atlantic warming/cooling. This induces an Atlantic-Pacific sea surface temperature seesaw, which in turn, strengthens/weakens the Walker circulation and amplifies the Pacific decadal variability that triggers pronounced global-scale atmospheric circulation anomalies. We conclude that the decadal oceanic variability in the SPNA is an essential component of the tropical interactions between the Atlantic and Pacific Oceans.

Atlantic variability↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

CFD↗

DOE OSTI2026

Overview of design developments for Condensable Vapor Devices for ITER

The Condensable Vapor Devices (CVDs), which are part of the ITER Roughing Pump System (RPS), are designed to separate tritiated water content to protect downstream pumps and transfer the water to Tokamak Exhaust Processing (TEP) systems for further separation. CVDs operate on the principle that a cooling fluid, such as liquid nitrogen, cools the exhaust gas stream (process gas) from the Tokamak, allowing the water present in the process gas to condense and freeze, thereby trapping it in the CVDs. The CVDs once saturated with the ice are then regenerated to release the trapped water molecules, which are sent to the TEP. The present article will describe the technical requirements, challenges, and design progress made so far in the development of the CVDs.

Choukekar, Ketan [ORNL] (ORCID:0009000288016383)↗

NASA NTRS1991

Short-period comets

The spacecraft flybys of Comet Halley in 1986 confirmed Whipple's icy conglomerate hypothesis for cometary nuclei and showed that comets are far richer in volatiles than any other class of solar system bodies. Water is the most abundant volatile, comprising roughly 80 percent of the gas flowing out from the nucleus. Carbon monoxide is next with a content of 15 percent relative to water, though with approximately half of that coming from an extended source in the cometary coma, i.e., hydrocarbon dust grains. The detection of large numbers of hydrocarbon CHON grains was one of the more significant discoveries of the Halley flybys, as was the ground-based observation that CN occurs in jets, again indicating an extended source. Evidence was also found for more complex hydrocarbons. Estimates of the total dust-to-gas ratio for Halley range as high as 2:1, indicating that a substantial fraction of the volatile material may be tied up in solid hydrocarbons rather than ices. The role of clathrates in trapping more volatile ices is not yet understood. If Halley can be taken to be representative of all short-period comets, then the short-period comets may provide a significant source of volatiles in near-earth space. This resource is more difficult to reach dynamically than the near-earth asteriods, but the high volatile content may justify the additional effort necessary. In addition, there is considerable evidence that at least some fraction of the near-earth asteriods are extinct cometary nuclei which have evolved into asteroid orbits, and which may contain significant volatiles buried beneath an insulating lag-deposit crust of nonvolatiles. Knowledge of comets will be greatly enhanced in the near future by the Comet Rendezvous Flyby mission now under development by NASA, and by the proposed Rosetta mission.

Weissman, Paul R.↗

DOE OSTI2025

Improved Representations of Longwave Surface Emissivity to Reduce Surface and Atmospheric Heating Biases in Earth System Models

Abstract Many Earth system models (ESMs) approximate surface emissivity as a broadband constant. This approximation reduces the computational burden, yet omits the spectral structure of emissivity and atmospheric absorption. Neglecting spectral variation in surface emission introduces biases in longwave (LW) atmospheric fluxes and heating. Biases are strongest over surfaces with strongly varying emissivity and minimal atmospheric opacity. We examine these biases over water, ice, and snow surfaces. We partition spectral emissivity into the 16 spectral bands utilized by a single‐column atmospheric radiative transfer model (RRTMG_LW) commonly used in ESMs. We quantify flux and heating biases introduced by broadband assumptions relative to the spectrally resolved case for standard atmospheric profiles over each surface type. Current assumptions tend to overestimate upwelling surface fluxes; for example, the greybody assumption overestimates flux by 1.6 W/m 2 (0.52%) at the bottom of a mid‐latitude winter atmosphere over ice, and by 2.33 (1.0%) at the top of atmosphere. The blackbody assumption tends to artificially cool Earth's surface, stabilizing the lower troposphere. Interestingly, the optimal broadband emissivity can deviate from the Planck‐weighted mean by up to 3% depending on surface type and atmospheric profile. We investigate bias sensitivity to surface temperature, cloud water path, and atmospheric water vapor. Bias is most sensitive to water vapor content, and least sensitive to cloud water path. Lastly, we show that a modified greybody method with updated broadband values can reduce total surface flux bias up to 1.69 , comparable to a five‐band approach and at a fraction of the computational cost.

Manzo, L. [Department of Earth System Science Univ↗

NASA NTRS1993

An Arctic source for the Great Salinity Anomaly - A simulation of the Arctic ice-ocean system for 1955-1975

The paper employs a fully prognostic Arctic ice-ocean model to study the interannual variability of sea ice during the period 1955-1975 and to explain the large variability of the ice extent in the Greenland and Iceland seas during the late 1960s. The model is used to test the contention of Aagaard and Carmack (1989) that the Great Salinity Anomaly (GSA) was a consequence of the anomalously large ice export in 1968. The high-latitude ice-ocean circulation changes due to wind field changes are explored. The ice export event of 1968 was the largest in the simulation, being about twice as large as the average and corresponding to 1600 cu km of excess fresh water. The simulations suggest that, besides the above average ice export to the Greenland Sea, there was also fresh water export to support the larger than average ice cover. The model results show the origin of the GSA to be in the Arctic, and support the view that the Arctic may play an active role in climate change.

Hakkinen, Sirpa↗

NASA NTRS2022

In Situ Measurements of Surface Texture with Virtual Environments Support Science-Driven Human Surface Operations on the Moon and Beyond

Visualization tools enabling real-time scientific analysis are important for supporting future astronaut operations on the lunar surface. Such tools can be built into virtual environments to support scientific investigations, as well as situational awareness, real-time decision making, and efficient communication between astronauts and ground and support systems. Understanding how these tools can be optimized for science is essential for upcoming Artemis missions. In this contribution, we discuss how measurements of surface texture at multiple length scales can greatly enhance in situ science on/of the Moon, and eventually Mars, asteroids, and beyond. Roughness measurements at various wavelengths directly support objectives defined in the Artemis Science Plan, including (O1) “understanding planetary processes,” (O2) “understanding volatile cycles,” and (O3) “interpreting the impact history of the Earth-Moon system” . Key scientific analyses enabled by texture measurements at different length scales include: ● Sub-centimeter scales: Texture measurements can help constrain lava flow crystallinity, lava rheology, emplacement flow dynamics, and cooling histories (O1). Measurements of lacunarity (voids in fractal fill space) can shed light on eruptive volatile content, residence time of migrating volatiles, and near-surface volume available for micro-cold trapping of volatiles (O1, O2). ● Centimeter–meter scales: Texture measurements can be used for the differentiation of individual lava flows, the reconstruction of local stratigraphies and emplacement sequences, characterization of post-emplacement surface modification processes (O1, O3). Derived roughness (polarization) metrics can be used in the detection of water ice and characterization of ice properties (e.g., purity, grade, depth, abundance). ● Hectometer–Kilometer scales: Texture measurements can be used to differentiate major geologic surface units and surface structures (O1), constrain the presence of abundant ground ices (O2), and analyze surface modification and estimate surface age (O3). Real-time measurements of surface texture across these multiple length scales will enable efficient sample identification and scientific investigations by future astronauts. To support these investigations and the objective classification of surface texture, virtual environments employed by astronauts should be able to instantaneously convert raw data into processed data (e.g., digital terrain and elevation models) and derived metrics (e.g., RMS, std, Hurst, CPR) and perform statistical analyses (e.g., PCA, outliers, correlation matrices). Such tools are being developed and tested by the Resource Exploration and Science of our Cosmic Environment (RESOURCE) team, a node of NASA’s Solar System Exploration Research Virtual Institute (SSERVI), and are an excellent example of the powerful synergies of human and robotic ground assets critical in the return of humans to the Moon.

Ariel N. Deutsch↗

NASA NTRS2012

Iterative Atmospheric Correction Scheme and the Polarization Color of Alpine Snow

Characterization of the Earth's surface is crucial to remote sensing, both to map geomorphological features and because subtracting this signal is essential during retrievals of the atmospheric constituents located between the surface and the sensor. Current operational algorithms model the surface total reflectance through a weighted linear combination of a few geometry-dependent kernels, each devised to describe a particular scattering mechanism. The information content of these measurements is overwhelmed by that of instruments with polarization capabilities: proposed models in this case are based on the Fresnel reflectance of an isotropic distribution of facets. Because of its remarkable lack of spectral contrast, the polarized reflectance of land surfaces in the shortwave infrared spectral region, where atmospheric scattering is minimal, can be used to model the surface also at shorter wavelengths, where aerosol retrievals are attempted based on well-established scattering theories. In radiative transfer simulations, straightforward separation of the surface and atmospheric contributions is not possible without approximations because of the coupling introduced by multiple reflections. Within a general inversion framework, the problem can be eliminated by linearizing the radiative transfer calculation, and making the Jacobian (i.e., the derivative expressing the sensitivity of the reflectance with respect to model parameters) available at output. We present a general methodology based on a Gauss-Newton iterative search, which automates this procedure and eliminates de facto the need of an ad hoc atmospheric correction. In this case study we analyze the color variations in the polarized reflectance measured by the NASA Goddard Institute of Space Studies Research Scanning Polarimeter during a survey of late-season snowfields in the High Sierra. This insofar unique dataset presents challenges linked to the rugged topography associated with the alpine environment and a likely high water content due to melting. The analysis benefits from ancillary information provided by the NASA Langley High Spectral Resolution Lidar deployed on the same aircraft. The results obtained from the iterative scheme are contrasted against the surface polarized reflectance obtained ignoring multiple reflections, via the simplistic subtraction of the atmospheric scattering contribution. Finally, the retrieved reflectance is modeled after the scattering properties of a dense collection of ice crystals at the surface. Confirming that the polarized reflectance of snow is spectrally flat would allow to extend the techniques already in use for polarimetric retrievals of aerosol properties over land to the large portion of snow-covered pixels plaguing orbital and suborbital observations.

Polarized BRDF↗