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At least 163 records · Page 9

Analysis of the low gravity tolerance of Bridgman-Stockbarger crystal growth. I - Steady and impulse accelerations

The effects of steady and impulse-type residual accelerations on dopant distributions during directional solidification in 2D and 3D 'generic' models of the Bridgman-Stockbarger technique are investigated using numerical methods. The calculations are based on the thermophysical properties of molten germanium doped with a low concentration of gallium. A Chebyshev collocation pseudospectral method is used for the solution of the governing momentum-, mass-, species-, and heat-transfer equations. Only convection caused by temperature gradients is considered. It is found that lateral nonuniformity in composition is very sensitive to the orientation of the steady component of the residual gravity vector and to the particular operating conditions under consideration. It is also found that laterally or radially averaged composition profiles are alone insufficient to describe the extent of residual convection in a spacecraft environment. The effects of impulse-type disturbances can be severe and can extend for times on the order of 1000 sec after the termination of the impulse.

Alexander, J. Iwan D.↗

Derivation of Sky-View Factors from LIDAR Data

The use of Lidar (Light Detection and Ranging), an active light-emitting instrument, is becoming increasingly common for a range of potential applications. Its ability to provide fine resolution spatial and vertical resolution elevation data makes it ideal for a wide range of studies. This paper demonstrates the capability of Lidar data to measure sky view factors (SVF). The Lidar data is used to generate a spatial map of SVFs which are then compared against photographically-derived SVF at selected point locations. At each location three near-surface elevations measurements were taken and compared with collocated Lidar-derived estimated. It was found that there was generally good agreement between the two methodologies, although with decreasing SVF the Lidar-derived technique tended to overestimate the SVF: this can be attributed in part to the spatial resolution of the Lidar sampling. Nevertheless, airborne Lidar systems can map sky view factors over a large area easily, improving the utility of such data in atmospheric and meteorological models.

spatial map↗

Evaluation of three lidar scanning strategies for turbulence measurements

Abstract. Several errors occur when a traditional Doppler beam swinging (DBS) or velocity–azimuth display (VAD) strategy is used to measure turbulence with a lidar. To mitigate some of these errors, a scanning strategy was recently developed which employs six beam positions to independently estimate the u, v, and w velocity variances and covariances. In order to assess the ability of these different scanning techniques to measure turbulence, a Halo scanning lidar, WindCube v2 pulsed lidar, and ZephIR continuous wave lidar were deployed at field sites in Oklahoma and Colorado with collocated sonic anemometers.Results indicate that the six-beam strategy mitigates some of the errors caused by VAD and DBS scans, but the strategy is strongly affected by errors in the variance measured at the different beam positions. The ZephIR and WindCube lidars overestimated horizontal variance values by over 60 % under unstable conditions as a result of variance contamination, where additional variance components contaminate the true value of the variance. A correction method was developed for the WindCube lidar that uses variance calculated from the vertical beam position to reduce variance contamination in the u and v variance components. The correction method reduced WindCube variance estimates by over 20 % at both the Oklahoma and Colorado sites under unstable conditions, when variance contamination is largest. This correction method can be easily applied to other lidars that contain a vertical beam position and is a promising method for accurately estimating turbulence with commercially available lidars.

Newman, Jennifer F.↗

Evaluation of CALIOP 532-nm Aerosol Optical Depth Over Opaque Water Clouds

With its height-resolved measurements and near global coverage, the CALIOP lidar onboard the CALIPSO satellite offers a new capability for aerosol retrievals in cloudy skies. Validation of these retrievals is difficult, however, as independent, collocated and co-temporal data sets are generally not available. In this paper, we evaluate CALIOP aerosol products above opaque water clouds by applying multiple retrieval techniques to CALIOP Level 1 profile data and comparing the results. This approach allows us to both characterize the accuracy of the CALIOP above-cloud aerosol optical depth (AOD) and develop an error budget that quantifies the relative contributions of different error sources. We focus on two spatial domains: the African dust transport pathway over the tropical North Atlantic and the African smoke transport pathway over the southeastern Atlantic. Six years of CALIOP observations (2007-2012) from the northern hemisphere summer and early fall are analyzed. The analysis is limited to cases where aerosol layers are located above opaque water clouds so that a constrained retrieval technique can be used to directly retrieve 532 nm aerosol optical depth and lidar ratio. For the moderately dense Sahara dust layers detected in the CALIOP data used in this study, the mean/median values of the lidar ratios derived from a constrained opaque water cloud (OWC) technique are 45.1/44.4 +/- 8.8 sr, which are somewhat larger than the value of 40 +/- 20 sr used in the CALIOP Level 2 (L2) data products. Comparisons of CALIOP L2 AOD with the OWC-retrieved AOD reveal that for nighttime conditions the L2 AOD in the dust region is underestimated on average by approx. 26% (0.183 vs. 0.247). Examination of the error sources indicates that errors in the L2 dust AOD are primarily due to using a lidar ratio that is somewhat too small. The mean/median lidar ratio retrieved for smoke is 70.8/70.4 +/- 16.2 sr, which is consistent with the modeled value of 70 +/- 28 sr used in the CALIOP L2 retrieval. Smoke AOD is found to be underestimated, on average, by approx. 39% (0.191 vs. 0.311). The primary cause of AOD differences in the smoke transport region is the tendency of the CALIOP layer detection scheme to prematurely assign layer base altitudes and thus underestimate the geometric thickness of smoke layers.

Liu, Z.↗

Evaluating Grid Strength under Uncertain Renewable Generation

The increasing displacement of synchronous generators with renewable resources such as wind and solar via power electronic interfaces causes a reduction in short-circuit strength and weak grid issues. The variation and uncertainty of renewable energy increase challenges for identifying weak grid conditions. This paper proposes an efficient method to analyze the impact of uncertain renewable energy on grid strength. The proposed method uses the probabilistic collocation method (PCM) to approximate the results of grid strength assessment under uncertain renewable generation, in order to reduce computational burden without compromising result accuracy when compared with traditional Monte Carlo simulation (MCS). To improve the accuracy of the approximation results, the proposed method integrates the K-means clustering technique with PCM to select the approximation samples of input variables. The efficacy of the proposed method is demonstrated by comparison with MCS on the modified IEEE 9-bus system and modified IEEE 39-bus system with multiple renewable generators.

grid strength↗

Numerical approach based on fractional-order Lagrange polynomials for solving a class of fractional differential equations

In this study, we propose a new set of fractional functions based on the Lagrange polynomials to solve a class of fractional differential equations. Fractional differential equations are the best tools for modelling natural phenomenon that are elaborated by fractional calculus. Therefore, we need an accurate and efficient technique for solving them. The main purpose of this article is to generalize new functions based on Lagrange polynomials to the fractional calculus. At first, we present a new representation of Lagrange polynomials and in continue, we propose a new set of fractional-order functions which are called fractional-order Lagrange polynomials (FLPs). Besides, a general formulation for operational matrices of fractional integration and derivative of FLPs on arbitrary nodal points are extracted. These matrices are obtained using Laplace transform. The initial value problems is reduced to the system of algebraic equations using the operational matrix of fractional integration and collocation method. Also, we find the upper bound of error vector for the fractional integration operational matrix and we indicate convergence of approximations of FLPs. Illustrative examples are included to demonstrate the validity and applicability of the proposed technique.

97 MATHEMATICS AND COMPUTING↗

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗

Chemical Imaging of Ambient Aerosol Particles: Observational Constraints on Mixing State Parameterization

A new parameterization for quantifying the mixing state of aerosol populations has been applied for the first time to samples of ambient particles analyzed using spectro-microscopy techniques. Scanning transmission x-ray microscopy/near edge x-ray absorption fine structure (STXM/NEXAFS) and computer controlled scanning electron microscopy/energy dispersive x-ray spectroscopy (CCSEM/EDX) were used to probe the composition of the organic and inorganic fraction of individual particles collected on June 27th and 28th during the 2010 Carbonaceous Aerosols and Radiative Effects (CARES) study in the Central Valley, California. The first field site, T0, was located in downtown Sacramento, while T1 was located near the Sierra Nevada Mountains. Mass estimates of the aerosol particle components were used to calculate mixing state metrics, such as the particle-specific diversity, bulk population diversity, and mixing state index, for each sample. Both microscopy imaging techniques showed more changes over these two days in the mixing state at the T0 site than at the T1 site. The STXM data showed evidence of changes in the mixing state associated with a build-up of organic matter confirmed by collocated measurements and the largest impact on the mixing state was due to an increase in soot dominant particles during this build-up. The CCSEM/EDX analysis showed the presence of two types of particle populations; the first was dominated by aged sea salt particles and had a higher mixing state index (indicating a more homogeneous population), the second was dominated by carbonaceous particles and had a lower mixing state index.

Environmental Molecular Sciences Laboratory↗

Community Radiative Transfer Model: Implementing A New Cloud Scattering Database and Developing the Forward Radar Module

The Mie theory is used by many fast RT models to estimate the optical properties of single particles. The Mie theory assumes spherical shapes for ice or snow particles with mixture of air and ice. However, hydrometeors scattering radiation at microwave frequencies have different shapes, sizes, and orientations. Therefore, using Mie theory to determine their optical properties leads to large uncertainties in all-sky radiative transfer calculations. The discrete dipole approximation (DDA) which approximates the optical properties of large objects in terms of discrete dipoles has shown promises in calculating the scattering properties of particles with different shapes in the microwave frequencies. The goal of the research was to enhance the CRTM scattering calculations for frozen hydrometeors in the microwave frequencies using the DDA technique. Given that such optical properties cannot be practically calculated on the fly, pre-computed look-up tables need to be implemented into the fast RT models to calculate the scattering properties of these particles using the DDA technique and the inputs provided by the users. Therefore, we implemented such pre-computed DDA databases into CRTM. In addition to using stand-alone CRTM calculations using collocated ATMS and reanalysis profiles, the data assimilation experiments conducted using the NOAA FV3GFS forecast system will be used to evaluate the scattering improvements. Additionally, we used the backscattering information from the DDA database to implement a radar simulator into CRTM. The radar operators takes advantage of CRTM different modules to calculate clouds absorption and scattering properties. In addition to the forward model both adjoint and tangent linear of the radar simulator are implemented and evaluated as well. The radar simulator is currently being tested within the JEDI/GEOS data assimilation framework to facilitate the assimilation of radar measurements such as CloudSat CPR and GPM DPR into the NASA GEOS model.

Isaac Moradi↗

Mapping Aerosol Lidar Ratios Over Ocean using MODIS AOD Constrained Retrievals and GOCART Model Simulations

After 17 years, the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission ceased science operations in August 2023. For the final CALIPSO data products release (Version 5), the CALIPSO project seeks to improve the accuracy of its aerosol extinction by advancing knowledge of aerosol lidar ratios (i.e., extinction-to-backscatter ratios; LRs) for various aerosol types. The current algorithm assigns one LR value globally for each of the seven tropospheric aerosol types. The CALIPSO team aims to improve the retrieval algorithm through the development of regional and seasonal LR climatologies for the same aerosol types. In this study, aerosol LRs are inferred through Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscatter profiles constrained by collocated aerosol optical depth (AOD) from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data over oceans during daytime. This analysis is subsampled for those profiles that are cloud-free and contain only one CALIOP-classified aerosol type. The CALIOP profiles are then collocated with aerosol volume fractions obtained through Goddard Chemistry Aerosol Radiation and Transport (GOCART) model simulations. This presentation will reveal findings that the 12-year (June 2006-August 2018) mean spatial distributions of inferred aerosol LRs for CALIOP-classified marine and dusty marine aerosols correspond inversely with patterns of GOCART sea salt volume fraction (SSVF). For example, smaller SSVFs (< 65%) and larger LRs (> 55 sr), are found near land masses (Fig. 1). This indicates the influence of advected anthropogenic aerosols (e.g., pollution and biomass burning smoke). In the remote oceans (i.e., regions likely less impacted by non-sea salt aerosols), the SSVFs are larger (> 95%) and the LRs are smaller (< 25 sr) (Fig. 1). A polynomial fit of the MODIS AOD constrained LRs to the corresponding GOCART SSVFs (intersect values of ~58 sr for SSVF of 0% and ~21 sr for SSVF of 100%) is further used to produce model-assisted climatological LR maps on seasonal scales. Additionally, we will show results of a LR validation analysis for which we compare the revised CALIPSO AODs obtained by applying the seasonal/regional constrained LRs against CALIPSO Version 4.51 Ocean Derived Column Optical Depth (ODCOD). While the majority of the presentation will focus on LRs for CALIOP-classified marine and dusty marine aerosols, an overview of LR results will show preliminary results for other aerosol types over ocean, such as dust and elevated smoke. The technique demon-strated in this study highlights the benefits not only to the final planned CALIPSO data release in 2025, but similar methods can be applied to future spaceborne elastic backscatter lidars with collocated passive sensors (e.g., such as those associated with NASA’s proposed Atmosphere Observing System).

Travis D Toth↗

Evaluating Light Rain Drop Size Estimates from Multiwavelength Micropulse Lidar Network Profiling

This paper investigates multiwavelength retrievals of median equivolumetric drop diameter D(sub 0) suitable for drizzle and light rain, through collocated 355-/527-nm Micropulse Lidar Network (MPLNET) observations collected during precipitation occurring 9 May 2012 at the Goddard Space Flight Center (GSFC) project site. By applying a previously developed retrieval technique for infrared bands, the method exploits the differential backscatter by liquid water at 355 and 527 nm for water drops larger than approximately 50 micrometers. In the absence of molecular and aerosol scattering and neglecting any transmission losses, the ratio of the backscattering profiles at the two wavelengths (355 and 527 nm), measured from light rain below the cloud melting layer, can be described as a color ratio, which is directly related to D(sub 0). The uncertainty associated with this method is related to the unknown shape of the drop size spectrum and to the measurement error. Molecular and aerosol scattering contributions and relative transmission losses due to the various atmospheric constituents should be evaluated to derive D(sub 0) from the observed color ratio profiles. This process is responsible for increasing the uncertainty in the retrieval. Multiple scattering, especially for UV lidar, is another source of error, but it exhibits lower overall uncertainty with respect to other identified error sources. It is found that the total error upper limit on D(sub 0) approaches 50%. The impact of this retrieval for long-term MPLNET monitoring and its global data archive is discussed.

light-rain drop size estimates↗

A Chebyshev matrix method for spatial modes of the Orr-Sommerfeld equation

The Chebyshev matrix collocation method is applied to obtain the spatial modes of the Orr-Sommerfeld equation for Poiseuille flow and the Blausius boundary layer. The problem is linearized by the companion matrix technique for semi-infinite domain using a mapping transformation. The method can be easily adapted to problems with different boundary conditions requiring different transformations.

Danabasoglu, G.↗

A Chebyshev matrix method for the spatial modes of the Orr-Sommerfeld equation

The Chebyshev matrix collocation method is applied to obtain the spatial modes of the Orr-Sommerfeld equation for Poiseuille flow and the Blasius boundary layer. The problems is linearized by the companion matrix technique for semiinfinite domain using a mapping transformation. The method can be easily adapted to problems with different boundary conditions requiring different transformations.

Danabasoglu, Gokhan↗

Spiral Chip Implantable Radiator and Printed Loop External Receptor for RF Telemetry in Bio-Sensor Systems

The paper describes the operation of a patented wireless RF telemetry system, consisting of a bio-MEMS implantable sensor and an external hand held unit, operating over the frequency range of few hundreds of MHz. A MEMS capacitive pressure sensor integrated with a miniature inductor/antenna together constitute the implantable sensor. Signal processing circuits collocated with a printed loop antenna together form the hand held unit, capable of inductively powering and also receiving the telemetry signals from the sensor. The paper in addition, demonstrates a technique to enhance the quality factor and inductance of the inductor in the presence of a lower ground plane and also presents the radiation characteristics of the loop antenna.

Simons, Rainee N.↗

Comparison of Daytime Low-Level Cloud Properties Derived From GOES and ARM SGP Measurements

Large-scale satellite data are critical for both verifying and improving general circulation model parameterizations of clouds and radiation for climate prediction. For reliable application of satellite data sets in cloud processes and climate models, it is important to have a reasonable estimate of the errors in the derived cloud properties. The daytime single-layered low-level cloud properties retrieved by the Geostationary Operational Environmental Satellite system (GOES) are compared with ground-based observations and retrievals over the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility from June 1998 to December 2006. The GOES retrievals are made via the Visible-Infrared Solar-infrared Split-window Technique. They are spatially averaged within a 0.15° × 0.15° box centered on the ARM SGP site, and the ARM surface observations are temporally averaged ±15 min around the GOES scans to produce collocated pairs. Comparisons are made for monthly means, diurnal means, and one-to-one GOES and ARM collocated pairs. GOES T eff is highly correlated with ARM T top cloud temperature, having an R 2 value of 0.75, though GOES exhibits a cold bias. GOES-retrieved τ and liquid water path have very good agreement with ARM retrievals with R 2 s of 0.45 and 0.47, while r e (GOES), on average, is about 2 μm greater than ARM r e . An examination of solar and viewing geometry has shown that GOES-retrieved mean r e and τ values are impacted by solar zenith angle and especially scattering angle, which is not unexpected and needs to be accounted for by users.

54 ENVIRONMENTAL SCIENCES↗

Spectral Characteristics of Daily to Seasonal Ground Motion at the Piñon Flats Observatory from Coherence of Seismic Data

We investigate coherences of seismic data recorded during three years (2015–2017) at the Piñon Flats Observatory (PY) array and a collocated 148 m deep borehole station B084, along with oceanic data from a buoy southwest of the PY array. Seismic and barometric recordings at PY stations are analyzed with a multitaper spectral technique. The coherence of signals from seismic sources is >0.6 at 0.05–8 Hz between closely spaced (<65m) surface stations and decreases to ~0.2 in frequency bands in which the wavelengths are smaller than interstation distances. There are several local coherence increases at 1–8 Hz between nearby (<65 m) surface stations, whereas large coherence values between a surface and 148 m deep borehole stations are only present at the secondary microseism (~0.14 Hz). These points to significant modification of seismic recordings in the top crust, and those continual near-surface failures might produce shallow rapidly attenuating signals at surface stations. Incoherent local atmospheric effects induce incoherent seismic signals in low- and high-frequency ranges through different coupling mechanisms. Between 0.003 and 0.05 Hz, atmospheric loadings generate ground tilts that contaminate the two horizontal seismic recordings and decrease their coherence, whereas the vertical component is less affected. At 1–8 Hz, coupling of atmospheric pressure with surface structures transmits incoherent signals into the ground, degrading the seismic coherence in all three components. The two horizontal coherences show seasonal variations with extended coherent frequency bands in winter and spring, likely to be produced by seasonal variations in microseisms and local ground tilts. The coherences also contain high anomalies between 2 and 4 Hz resulting from anthropogenic activities. The results provide useful information on instrument characteristics and variations in the shallow crustal response to earthquakes, seasonal and ambient sources of seismic energy, along with atmospheric pressure–temperature changes and anthropogenic activities.

Geochemistry & Geophysics↗

A survey of decentralized control techniques for large space structures

Preliminary results on the design of decentralized controllers for the COFS I Mast are reported. A nine mode finite element model is used along with second order model of the actuators. It is shown that without actuator dynamics, the system is stable with collocated rate feedback and has acceptable performace. However, when actuator dynamics are included, the system is unstable.

Lindner, D. K.↗

Cutting Silica Aerogel for Particle Extraction

The detailed laboratory analyses of extraterrestrial particles have revolutionized our knowledge of planetary bodies in the last three decades. This knowledge of chemical composition, morphology, mineralogy, and isotopics of particles cannot be provided by remote sensing. In order to acquire these detail information in the laboratories, the samples need be intact, unmelted. Such intact capture of hypervelocity particles has been developed in 1996. Subsequently silica aerogel was introduced as the preferred medium for intact capturing of hypervelocity particles and later showed it to be particularly suitable for the space environment. STARDUST, the 4th NASA Discovery mission to capture samples from 81P/Wild 2 and contemporary interstellar dust, is the culmination of these new technologies. In early laboratory experiments of launching hypervelocity projectiles into aerogel, there was the need to cut aerogel to isolate or extract captured particles/tracks. This is especially challenging for space captures, since there will be many particles/tracks of wide ranging scales closely located, even collocated. It is critical to isolate and extract one particle without compromising its neighbors since the full significance of a particle is not known until it is extracted and analyzed. To date, three basic techniques have been explored: mechanical cutting, lasers cutting and ion beam milling. We report the current findings.

Tsou, P.↗