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All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Comparison of the Atomic Oxygen Erosion Depth and Cone Height of Various Materials at Hyperthermal Energy

Atomic oxygen readily reacts with most spacecraft polymer materials exposed to the low Earth orbital (LEO) environment. If the atomic oxygen arrival comes from a fixed angle of impact, the resulting erosion will foster the development of a change in surface morphology as material thickness decreases. Hydrocarbon and halopolymer materials, as well as graphite, are easily oxidized and textured by directed atomic oxygen in LEO at energies of approx.4.5 eV. What has been curious is that the ratio of cone height to erosion depth is quite different for different materials. The formation of cones under fixed direction atomic oxygen attack may contribute to a reduction in material tensile strength in excess of that which would occur if the cone height to erosion depth ratio was very low because of greater opportunities for crack initiation. In an effort to understand how material composition affects the ratio of cone height to erosion depth, an experimental investigation was conducted on 18 different materials exposed to a hyperthermal energy directed atomic oxygen source (approx.70 eV). The materials were first salt-sprayed to provide microscopic local areas that would be protected from atomic oxygen. This allowed erosion depth measurements to be made by scanning microscopy inspection. The polymers were then exposed to atomic oxygen produced by an end Hall ion source that was operated on pure oxygen. Samples were exposed to an atomic oxygen effective fluence of 1.0x10(exp 20) atoms/sq cm based on Kapton H polyimide erosion. The average erosion depth and average cone height were determined using field emission scanning electron microscopy (FESEM). The experimental ratio of average cone height to erosion depth is compared to polymer composition and other properties.

Waters, Deborah L.↗
NASA NTRS2006

Snow Depth and Ice Thickness Measurements From the Beaufort and Chukchi Seas Collected During the AMSR-Ice03 Campaign

In March 2003, a field validation campaign was conducted on the sea ice near Barrow, AK. The goal of this campaign was to produce an extensive dataset of sea ice thickness and snow properties (depth and stratigraphy) against which remote sensing products collected by aircraft and satellite could be compared. Chief among these were products from the Polarimetric Scanning Radiometer (PSR) flown aboard a NASA P-3B aircraft and the Aqua Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). The data were collected in four field areas: three on the coastal sea ice near Barrow, AK, and the fourth out on the open ice pack 175 km northeast of Barrow. The snow depth ranged from 9.4-20.8 cm in coastal areas (n = 9881 for three areas) with the thinnest snow on ice that had formed late in the winter. Out in the main pack ice, the snow was 20.6 cm deep (n = 1906). The ice in all four areas ranged from 138-219 cm thick (n = 1952), with the lower value again where the ice had formed late in the winter. Snow layer and grain characteristics observed in 118 snow pits indicated that 44% of observed snow layers were depth hoar; 46% were wind slab. Snow and ice measurements were keyed to photomosaics produced from low-altitude vertical aerial photographs. Using these, and a distinctive three-way relationship between ice roughness, snow surface characteristics, and snow depth, strip maps of snow depth, each about 2 km wide, were produced bracketing the traverse lines. These maps contain an unprecedented level of snow depth detail against which to compare remote sensing products. The maps are used in other papers in this special issue to examine the retrieval of snow properties from the PSR and AMSR-E sensors.

Sturm, M.↗
NASA NTRS2008

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Yang, Yuekui↗
NASA NTRS2009

Estimation of Sea Ice Thickness Distributions through the Combination of Snow Depth and Satellite Laser Altimetry Data

Combinations of sea ice freeboard and snow depth measurements from satellite data have the potential to provide a means to derive global sea ice thickness values. However, large differences in spatial coverage and resolution between the measurements lead to uncertainties when combining the data. High resolution airborne laser altimeter retrievals of snow-ice freeboard and passive microwave retrievals of snow depth taken in March 2006 provide insight into the spatial variability of these quantities as well as optimal methods for combining high resolution satellite altimeter measurements with low resolution snow depth data. The aircraft measurements show a relationship between freeboard and snow depth for thin ice allowing the development of a method for estimating sea ice thickness from satellite laser altimetry data at their full spatial resolution. This method is used to estimate snow and ice thicknesses for the Arctic basin through the combination of freeboard data from ICESat, snow depth data over first-year ice from AMSR-E, and snow depth over multiyear ice from climatological data. Due to the non-linear dependence of heat flux on ice thickness, the impact on heat flux calculations when maintaining the full resolution of the ICESat data for ice thickness estimates is explored for typical winter conditions. Calculations of the basin-wide mean heat flux and ice growth rate using snow and ice thickness values at the 70 m spatial resolution of ICESat are found to be approximately one-third higher than those calculated from 25 km mean ice thickness values.

Kurtz, Nathan T.↗
NASA NTRS2011

Freeboard, Snow Depth and Sea-Ice Roughness in East Antarctica from In Situ and Multiple Satellite Data

In October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50 500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. The results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.

Markus, Thorsten↗
NASA NTRS2012

The Use of Satellite-Measured Aerosol Optical Depth to Constrain Biomass Burning Emissions Source Strength in a Global Model GOCART

Small particles in the atmosphere, called "atmospheric aerosol" have a direct effect on Earth climate through scattering and absorbing sunlight, and also an indirect effect by changing the properties of clouds, as they interact with solar radiation as well. Aerosol typically stays in the atmosphere for several days, and can be transported long distances, affecting air quality, visibility, and human health not only near the source, but also far downwind. Smoke from vegetation fires is one of the main sources of atmospheric aerosol; other sources include anthropogenic pollution, dust, and sea salt. Chemistry transport models (CTMs) are among the major tools for studying the atmospheric and climate effects of aerosol. Due to the considerable variation of aerosol concentrations and properties on many temporal and spatial scales, and the complexity of the processes involved, the uncertainties in aerosol effects on climate are large, as is featured in the latest report of Intergovernmental Panel on Climate Change (IPCC) in 2007. Reducing this uncertainty in the models is very important both for predicting future climate scenarios and for regional air quality forecasting and mitigation. During vegetation fires, also called biomass burning (BB) events, complex mixture of gases and particles is emitted. The amount of BB emissions is usually estimated taking into account the intensity and size of the fire and the properties of burning vegetation. These estimates are input into CTMs to simulate BB aerosol. Unfortunately, due to large variability of fire and vegetation properties, the quantity of BB emissions is very difficult to estimate and BB emission inventories provide numbers that can differ by up to the order of magnitude in some regions. Larger uncertainties in data input make uncertainties in model output larger as well. A powerful way to narrow the range of possible model estimates is to compare model output to observations. We use satellite observations of aerosol properties, specifically aerosol optical depth, which is directly proportional to the amount of aerosol in the atmosphere, and compare it to the model output. Assuming the model represents aerosol transport and particle properties correctly, the amount of BB emissions determines the simulated aerosol optical depth. In this study, we explore the regional performance of 13 commonly used emission estimates. These are each input to global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We then evaluate how well each emission estimate reproduces the smoke aerosol optical depth measured by the MODIS instrument. We compared GOCART-simulate aerosol optical depth with that measured from the satellite for 124 fire cases around the world during 2006 and 2007. We summarize the regional performance of each emission inventory and discuss reasons for their differences by considering the assumptions made during their development. We also show that because stronger wind disperses smoke plumes more readily, in cases with stronger wind, a larger increase in emission amount is needed to increase aerosol optical depth. In quiet, low-wind-speed environments, BB emissions produce a more significant increase in aerosol optical depth, other things being equal. Using the region-specific, quantitative relationships derived in our paper, together with the wind speed obtained from another source for a given fire case, we can constrain the amount of emission required in the model to reproduce the observations. The results of this paper are useful to the developers of BB emission inventories, as they show the strengths and weaknesses of individual emission inventories in different regions of the globe, and also for modelers who use these inventories and wish to improve their model results.

Petrenko, Mariya↗
NASA NTRS2012

Global Estimates of PBL Depth from Space-Borne LIDAR

The planetary boundary layer (PBL) is responsible for communicating the exchange of energy, moisture, momentum, pollutants, and aerosols between the surface and the free atmosphere and is therefore crucial to many studies of the atmosphere. Unfortunately, there have historically been few observations of this important layer due to the complexity involved in its measurement. However, with the advent of more advanced satellites, global measurements of the PBL are now becoming possible. The PBL is often characterized by a high concentration of aerosols within the layer and low level clouds capping it and these are observable from space. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite was launched in 2006 with the intention of observing aerosols and clouds and was the first space-based LIDAR optimized for this purpose. CALIPSO observations are therefore well suited to observing the depth of the PBL. Since it was launched, CALIPSO has been making nearly continuous measurements enabling a global picture of PBL depth. We plan to present a global PBL depth product and how it evolves throughout the year. The product is able to identify deeper PBL depths in the summer hemisphere over land and deeper depths along the northern hemisphere oceanic storm tracks in winter associated with cold air traveling over warm water. Large seasonal cycles are also evident in the subtropical desert locations among other features. In addition, comparisons will be made between several estimates of PBL depth based on turbulent intensity, meteorology profiles, and aerosol profiles from the GEOS5 model.

McGrath-Spangler, Erica lynn↗
NASA NTRS2011

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Feng, Qian↗
NASA NTRS2019

Estimating Alpine Snow Depth by Combining Multi-Frequency Passive Radiance Observations with Ensemble Snowpack Modeling

This paper presents a physically-based snow depth retrieval algorithm adapted for deep mountainous snowpack and airborne multifrequency (10.7, 18.7, 37.0 and 89.0 GHz) passive microwave (PM) radiance observations from a single flight. The algorithm employs a single forecast-analysis cycle of a traditional sequential assimilation scheme. It uses an ensemble of multi-layer snowpack model runs to resolve snow microstructure and melt-refreeze crusts, andmicrowave radiative transfer models to relate snow properties to microwave measurements.Snow depth was retrieved at a 120 m spatial resolution over three 1 km2 Intensive Study Area (ISA) within the Rabbit Ears Meso-Cell Study Area (MSA) from the NASA Cold Land Processes Experiment (CLPX) in Colorado (United States) for one date in February 2003. When evaluated against in situ observations, root mean square error (RMSE) of the snow depth from the assimilation was 13.3 cm for areas with low (<5 %) forest cover, which was a reduction of 48 % in the RMSE compared with the modeled snow depth when the PM observations were not assimilated; indicating a ~5% relative error of the posterior snow depth with respect to the average snow depth (200 cm) measured at these pixels. For pixels with forest cover ranging from 5-15% and 15-30%, results were improved (R2 increased from 0.65 to 0.71 and from 0 to 0.38, respectively) by introducing a forest radiative transfer model during the assimilation.

Airborne Multifrequency↗
NASA NTRS2020

ICESat-2 Meltwater Depth Estimates: Application to Surface Melt on Amery Ice Shelf, East Antarctica

Surface melting occurs during summer on the Antarctic and Greenland ice sheets, but the volume of meltwater stored has been difficult to quantify due to a lack of accurate depth estimates. NASA’s ICESat-2 laser altimeter brings a new capability: photons penetrate water and are reflected from both the water and the underlying ice; the difference provides a depth estimate. ICESat-2 sampled Amery Ice Shelf on 2 January 2019 and showed double returns from surface depressions, indicating meltwater. For four melt features, we compared depth estimates from eight algorithms: six based on ICESat-2 and two from coincident Landsat-8 and Sentinel-2 imagery. All algorithms successfully identified surface water at the same locations. Algorithms based on ICESat-2 produced the most accurate depths; the image-based algorithms underestimated depths (by 30-70%). This implies that ICESat-2 depths can be used to tune image-based algorithms, moving us closer to quantifying stored meltwater volumes across Antarctica and Greenland.

ICESat-2↗
NASA NTRS2021

Inter-comparison of snow depth over Arctic sea ice from reanalysis reconstructions and satellite retrieval

In this study, we compare eight recently developed snow depth products over Arctic sea ice, which use satellite observations, modeling, or a combination of satellite and modeling approaches. These products are further compared against various ground-truth observations, including those from ice mass balance observations and airborne measurements. Large mean snow depth discrepancies are observed over the Atlantic and Canadian Arctic sectors. The differences between climatology and the snow products early in winter could be in part a result of the delaying in Arctic ice formation that reduces early snow accumulation, leading to shallower snowpacks at the start of the freeze-up season. These differences persist through spring despite overall more winter snow accumulation in the reanalysis-based products than in the climatologies. Among the products evaluated, the University of Washington (UW) snow depth product produces the deepest spring (March–April) snowpacks, while the snow product from the Danish Meteorological Institute (DMI) provides the shallowest spring snow depths. Most snow products show significant correlation with snow depths retrieved from Operational IceBridge (OIB) while correlations are quite low against buoy measurements, with no correlation and very low variability from University of Bremen and DMI products. Inconsistencies in reconstructed snow depth among the products, as well as differences between these products and in situ and airborne observations, can be partially attributed to differences in effective footprint and spatial–temporal coverage, as well as insufficient observations for validation/bias adjustments. Our results highlight the need for more targeted Arctic surveys over different spatial and temporal scales to allow for a more systematic comparison and fusion of airborne, in situ and remote sensing observations.

Lu Zhou↗
NASA NTRSDate not supplied

AMSR-2 Daily Snow Depth Data Product Using a Neural Network Algorithm Trained by Collocated ICESat-2 Measurements

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu 1 et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu 2 et al. (2022,2024) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, a neural network (NN) algorithm, employing several channels from AMSR-2 and the humidity vertical profiles GMAO GEOS-IT, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained NN snow-depth was applied to 2014-2020 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. This paper used AMSR-2 data, a passive microwave instrument to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗
DOE OSTI2019

Deep Direct-Use Feasibility Study Temperature-Depth Estimates for West Virginia University, Morgantown, WV

This dataset contains data spreadsheets and figures that summarize the results of a stochastic analysis of temperatures at depth below the West Virginia University campus in Morgantown, WV. These results are extracted from a study by Smith (2019), whose results are included in a GDR submission that provides rasters and shapefiles for the Appalachian Basin states of New York, Pennsylvania, and West Virginia (GDR submission #1182). Uncertainties considered included geologic properties, thermal properties, and uncertainty from geostatistical interpolation of the surface heat flow. A Monte Carlo analysis of these uncertain properties was used to predict temperatures at depth using a 1-D heat conduction model. For the pixel corresponding to West Virginia University, a .csv file containing the 10,000 temperature-depth profiles estimated from a Monte Carlo analysis is provided. Temperatures are provided for depths from 1-5 km in 0.5 km increments. These data are summarized in a figure containing violin plots that illustrates the probability of obtaining certain temperatures at depth for Morgantown.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Pyrolysis temperature and soil depth interactions determine PyC turnover and induced soil organic carbon priming

Pyrogenic organic carbon (PyC) is a complex, heterogeneous class of thermally altered organic substrates, but its dynamics and how its behavior changes with soil depth remain poorly understood. We conducted a laboratory incubation study to investigate the interactive effects of pyrolysis temperature and soil depth on the turnover of PyC compared to its precursor wood and native SOC (NSOC). We incubated dual-labeled (13C and 15N) jack pine pyrogenic organic matter produced at 300 °C (PyC300), 450 °C (PyC450), and their precursor pine wood in a fine-loamy, mixed-conifer forest soil for 745 days. A mixture of surface (0–10 cm) and subsurface (50–70 cm) forest soils, with and without labeled biomass were incubated in the dark at 55% soil water field capacity and 25 °C. Total 13C from PyC and wood mineralized as 13C-CO2 (as % of C added to soil) declined with an increase in pyrolysis temperature as follows: 54 ± 7.7% for wood, 3.1 ± 0.2% for PyC300, and 0.94 ± 0.08% for PyC450. Furthermore, after 2 years, soil depth interacted with pyrolysis temperature to affect C turnover, with total wood C losses significantly declining from 70.6% in surface soils to 37.5% in subsurface soil, while total losses of PyC300 and PyC450 were unaffected by differences between surface and subsurface soils. Wood induced negative priming (i.e., decreased mineralization rates) in surface soil at days 3 and 60, while PyC300 induced positive priming (i.e., increased mineralization rates) in subsurface soil at day 60. After 2 years, unlabeled NSOC losses increased from 9.2 ± 0.8% of NSOC in unamended treatments to 16.5 ± = 2.6% of NSOC with PyC450 additions. Our results suggest that PyC pyrolyzed at a given temperature can mineralize at similar rates between soil depths, and high amounts of PyC450 in subsurface soils can stimulate NSOC losses. These findings indicate that soil depth imposes critical controls on PyC dynamics belowground.

13C-labeling↗
DOE OSTI2019

High-Cycle Fatigue Behavior of Vacuum-Carburized 20Cr2Ni4 Steel with Different Case Depths

High-cycle fatigue behavior of vacuum-carburized 20Cr2Ni4 steel with three different case depths was studied by using rotating bending fatigue test. The results show that fatigue strength exhibits an increase–decrease pattern with increasing effective case dept, which is regarded to be mainly due to the unavoidable change in other parameters such as residual stress and grain size in case layer besides case depth. The present data and data in the available literature suggest that a dimensionless parameter of relative case depth is more appropriate to reflect the influence of case depth on fatigue strength. Further fracture surface analysis revealed that the fatigue failure was dominated by surface crack initiation mainly due to the extremely high cleanness of the tested steel with inclusion control. It is thus concluded that both relative case depth and other parameters should be comprehensively considered in obtaining optimized fatigue performance of vacuum-carburized steel.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Mechanical specific energy versus depth of cut in rock cutting and drilling

The relationship between Mechanical Specific Energy (MSE) and the Rate of Penetration (ROP), or equivalently the depth of cut per revolution, provides an important measure for strategizing a drilling operation. This study explores how MSE evolves with depth of cut, and presents a concerted effort that encompasses analytical, computational and experimental approaches. A simple model for the relationship between MSE and cutting depth is first derived with consideration of the wear progression of a circular cutter. This is an extension of Detournay and Defourny's phenomenological cutting model. Wear is modeled as a flat contact area at the bottom of a cutter referred to as a wear flat, and that wear flat in the past is often considered to be fixed during cutting. But during a drilling operation by a full bit that consists of multiple circular cutters, the wear flat length may increase because of various wear mechanisms involved. The wear progression of cutters generally results in reduced efficiency with either increased MSE or decreased ROP. Also, an accurate estimate of removed rock volume is found important for the evaluation of MSE. The derived model is compared with experiment results from a single circular cutter, for cutting soft rock under ambient pressure with actual depth measured through a micrometer, and for cutting high strength rock under high pressure with actual cutting area measured by a confocal microscope. Lastly, the model is employed to interpret the evolution of MSE with depth of cut for a full drilling bit under confining pressure. The general form of equation of the developed model is found to describe well the experiment data and can be applied to interpret the drilling data for a full bit.

42 ENGINEERING↗
DOE OSTI2019

Mechanisms Behind the Extratropical Stratiform Low-Cloud Optical Depth Response to Temperature in ARM Site Observations

Ground-based observations from three middle- and high-latitude sites managed by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program are used to determine the sensitivity of the low-cloud optical depth to temperature and to test whether observations support mechanisms previously proposed to affect the optical depth feedback. Analysis of cloud optical depth retrievals support previous satellite findings that the optical depth decreases or stays constant with increases in temperature when the cloud is warm but increases when the cloud is cold. The cloud liquid water path sensitivity to warming largely explains the optical depth sensitivity at all sites.Mechanisms examined in this study involve the temperature dependence of (a) the moist-adiabatic lapse rate, (b) cloud phase partitioning, (c) drying efficiency of cloud top mixing, (d) cloud top inversion strength,and (e) boundary layer decoupling. Mechanism (a) is present across all clouds and explains 30% to 50%of the increase in liquid water path with warming at temperatures below 0°C. However, the cloud's adiabaticity, the ratio between the liquid water path and its theoretical maximum, is at least as important and determines how the liquid water path sensitivity to temperature varies with temperature. At temperatures below 0°C, the adiabaticity increases with warming, and the data support mechanism (b).At warmer temperatures, the adiabaticity decreases with warming, overwhelming mechanism (a) and resulting in the liquid water path decreasing with warming. This adiabaticity decrease arises primarily because of mechanism (d), and to a lesser degree because of mechanism (e). No evidence is found supporting mechanism (c)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Capacitive radio frequency discharges with a single ring-shaped narrow trench of various depths to enhance the plasma density and lateral uniformity

Spatial structures of the electron density and temperature in ring-shaped hollow cathode capacitive rf plasma with a single narrow trench of 2 mm width have been investigated at various trench depths of D = 5, 8, 10, 12, and 15 mm. It is found that the plasma density is increased in the presence of the trench and that the radial profile of the plasma density has a peak around the narrow hollow trench near the cathode. The density becomes uniform further away from the cathode at all trench depths, whereas the electron temperature distribution remains almost uniform. The measured radial profiles of the plasma density are in good agreement with a theoretical diffusion model for all the trench depths, which explains the local density increase by a local enhancement of the electron heating. Under the conditions investigated, the trench of 10 mm depth is found to result in the highest plasma density at various axial and radial positions. The results show that the radial uniformity of the plasma density at various axial positions can be improved by using structured electrodes of distinct depths rather than planar electrodes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗