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At least 613 records · Page 34

Study of InGaAs based MODFET structures using variable angle spectroscopic ellipsometry

Variable angle spectroscopic ellipsometry was used to estimate the thicknesses of all layers within the optical penetration depth of InGaAs based MODFET structures. Strained and unstrained InGaAs channels were made by MBE on InP substrates and by MOCVD on GaAs substrates. In most cases, ellipsometrically determined thicknesses were within 10 percent of the growth calibration results. The MBE made InGaAs strained layers showed large strain effects, indicating a probable shift in the critical points of their dielectric function toward the InP lattice matched concentration.

Alterovitz, S. A.↗

Tropical Rainfall Measuring Mission (TRMM) project. VI - Spacecraft, scientific instruments, and launching rocket. Part 3 - The electrically Scanning Microwave Radiometer and the Special Sensor Microwave/Imager

The two microwave radiometers for TRMM are designed to measure thermal microwave radiation upwelling from the earth. The Electrically Scanning Microwave Radiometer (ESMR) scans from 50 deg to the left through nadir to 50 deg to the right in 78 steps with no moving mechanical parts in a band centered at 19.35 GHz. The TRMM concept uses the radar to develop a climatology of rain-layer thickness which can be used for the interpretation of the radiometer data over a swath wider than the radar. The ESMR data are useful for estimating rain intensity only over an ocean background. The Special Sensor Microwave/Imager (SSM/I), which scans conically with three dual polarized channels at 19, 37, and 85 GHz and a single polarized channel at 22 GHz, provides a wider range of rainfall intensities. The SSM/I spins about an axis parallel to the local spacecraft vector and 128 uniformly spaced samples of the 85 GHz data are taken on each scan over a 112-deg scan region simultaneously with 64 samples of the other frequencies.

Wilheit, Thomas T.↗

Metallized Gelled Propellant Heat Transfer Tests Analyzed

A series of rocket engine heat transfer experiments using metallized gelled liquid propellants was conducted at the NASA Lewis Research Center. These experiments used a small 20- to 40-lbf thrust engine composed of a modular injector, an igniter, a chamber, and a nozzle. The fuels used were traditional liquid RP-1 and gelled RP-1 with 0-, 5-, and 55-wt % loadings of aluminum particles. Gaseous oxygen was used as the oxidizer. Heat transfer measurements were made with a rocket engine calorimeter chamber and nozzle with a total of 31 cooling channels. Each channel used water flow to carry heat away from the chamber and the attached thermocouples; flow meters allowed heat flux estimates at each of the 31 stations.

Palaszewski, Bryan A.↗

Detection Thresholds of Falling Snow from Satellite-Borne Active and Passive Sensors

Precipitation, including rain and snow, is a critical part of the Earth's energy and hydrology cycles. In order to collect information on the complete global precipitation cycle and to understand the energy budget in terms of precipitation, uniform global estimates of both liquid and frozen precipitation must be collected. Active observations of falling snow are somewhat easier to estimate since the radar will detect the precipitation particles and one only needs to know surface temperature to determine if it is liquid rain or snow. The challenges of estimating falling snow from passive spaceborne observations still exist though progress is being made. While these challenges are still being addressed, knowledge of their impact on expected retrieval results is an important key for understanding falling snow retrieval estimations. Important information to assess falling snow retrievals includes knowing thresholds of detection for active and passive sensors, various sensor channel configurations, snow event system characteristics, snowflake particle assumptions, and surface types. For example, can a lake effect snow system with low (~2.5 km) cloud tops having an ice water content (Iwe) at the surface of 0.25 g m-3 and dendrite snowflakes be detected? If this information is known, we can focus retrieval efforts on detectable storms and concentrate advances on achievable results. Here, the focus is to determine thresholds of detection for falling snow for various snow conditions over land and lake surfaces. The analysis relies on simulated Weather Research Forecasting (WRF) simulations of falling snow cases since simulations provide all the information to determine the measurements from space and the ground truth. Results are presented for active radar at Ku, Ka, and W-band and for passive radiometer channels from 10 to 183 GHz (Skofronick-Jackson, et al. submitted to IEEE TGRS, April 2012). The notable results show: (1) the W-Band radar has detection thresholds more than an order of magnitude lower than the future GPM sensors, (2) the cloud structure macrophysics influences the thresholds of detection for passive channels, (3) the snowflake microphysics plays a large role in the detection threshold for active and passive instruments, (4) with reasonable assumptions, the passive 166 GHz channel has detection threshold values comparable to the GPM DPR Ku and Ka band radars with ~0.05 g m-3 detected at the surface, or an ~0.5-1 mm hr-l melted snow rate (equivalent to 0.5-2 cm hr-l solid fluffy snowflake rate).

Jackson, Gail↗

Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

Quets, Jan↗

Development of a Consistent GEOsat Cloud Property Dataset for the CERES Climate Data Record

Cloud properties are critical for understanding the Earth’s radiation budget and cloud feedbacks. At NASA Langley Research Center, the Satellite ClOud and Radiative Property retrieval System (SatCORPS) provides real-time and historical analyses of clouds derived from Geostationary satellite (GEOsat) data for weather and climate applications. For the Clouds and the Earth’s Radiant Energy System (CERES) program, the global constellation of GEOsats has been analyzed since 2000 to help characterize and account for the diurnal cycle of clouds and their radiative impacts in the CERES climate data record. Obtaining consistent cloud properties over the GEOsat data record during the CERES era is a major objective but a significant challenge considering the diversity of imaging capabilities deployed during that time. The GEOsat data analysis approach for the current CERES Edition-4 (Ed4) data products was focused on accuracy and consistency with MODIS by employing as much spectral information as possible from each satellite. However, the inconsistent use of spectral information across GEOsats led to marked discontinuities in the spatial and temporal record of cloud properties that had to be accounted for post facto in downstream CERES processing. This paper reports progress in developing a new GEOsat analysis system for the next CERES edition (Ed5) that has potential to improve cross-platform consistency and continuity. In this approach, the spectral channel complement is limited to just 3-channels during daytime, ~0.65 µm (VIS), ~3.9 µm (NIR), and ~10.8 µm (IR), common to nearly all of the satellites in the record. At night, a 2-channel approach is taken with the NIR and IR, and ~6.7 µm bands that includes a machine learning approach for optically thick cloud properties. A tradeoff is the potential for reduced accuracy particularly using data from the more advanced satellites that have more spectral channels (e.g. SEVIRI, AHI and ABI) that are known to help improve thin cirrus detection, cloud-aerosol discrimination and estimates in other difficult conditions that challenge cloud remote sensing. The new continuity approach is applied to one month of global GEOSat data for each year of the CERES record since 2000 and compared with the Ed4 GEO and MODIS cloud property time series in order to evaluate the level of improved consistency in the GEOsat record and to assess the accuracy impacts. Cloud fraction will also be assessed with CALIPSO data. Outstanding issues and challenges will be discussed. The results are expected to guide future work needed to develop a more robust GEOsat cloud data record for CERES.

CERES CDR↗

ELMO: ELectron Microburst Observatory Mission to Study Microbursts

We describe the ELectron Microburst Observatory mission, ELMO which is proposed as a CubeSat constellation mission to fully characterize microburst event spatial extent systematically for the first time both in latitude and longitude. ELMO comprises 4 CubeSats two per orbit plane in two orbit planes. ELMO will fly in a high inclination LEO at about 500 km in altitude. The CubeSats will systematically separate both in latitude and longitude over the mission lifetime and will carry MERIT, Miniaturized Electron and Proton Telescope as the the payload. MERIT has been built,tested and delivered to fly on NASA's HERMES, Lunar Gateway mission. MERIT is a solid state detector particle telescope with two identical sensor heads pointed zenith- and nadir-wards enabling measurement of both downgpoing and upwelling electrons thereby accurately estimating electron precipitation into the atmosphere. MERIT will measure electron and protons over a wide energy range in multiple differential channels with a very time resolution of less than 4 ELMO will quantify for the first time the contribution of microbursts to radiation belt electron loss using systematic coordinated multipoint measurements. Energetic electron precipitation affects atmospheric chemistry and therefore climate change. ELMO measures microbursts with unprecedented time and energy resolution. ELMO provides critical knowledge of electron loss processes required for quantitative prediction of global electron fluxes.

Shri Kanekal↗

Properties of Linear Contrails Detected in 2012 Northern Hemisphere MODIS Imagery

Observation of linear contrail cirrus coverage and retrieval of their optical properties are valuable data for validating atmospheric climate models that represent contrail formation explicitly. These data can reduce our uncertainty of the regional effects of contrail-generated cirrus on global radiative forcing, and thus improve our estimation of the impact of commercial aviation on climate change. We use an automated contrail detection algorithm (CDA) to determine the coverage of linear persistent contrails over the Northern Hemisphere during 2012. The contrail detection algorithm is a modified form of the Mannstein et al. (1999) method, and uses several channels from thermal infrared MODIS data to reduce the occurrence of false positive detections. A set of contrail masks of varying sensitivity is produced to define the potential range of uncertainty in contrail coverage estimated by the CDA. Global aircraft emissions waypoint data provided by FAA allow comparison of detected contrails with commercial aircraft flight tracks. A pixel-level product based on the advected flight tracks defined by the waypoint data and U-V wind component profiles from the NASA GMAO GEOS-4 reanalysis has been developed to assign a confidence of contrail detection for the contrail mask. To account for possible contrail cirrus missed by the CDA, a post-processing method based on the assumption that pixels adjacent to detected linear contrails will have radiative signatures similar to those of the detected contrails is applied to the Northern Hemisphere data. Results from several months of MODIS observations during 2012 will be presented, representing a near-global climatology of contrail coverage. Linear contrail coverage will be compared with coverage estimates determined previously from 2006 MODIS data.

Duda, David P.↗

Accuracy of telemetry signal power loss in a filter as an estimate for telemetry degradation

When telemetry data is transmitted through a communication link, some degradation in telemetry performance occurs as a result of the imperfect frequency response of the channel. The term telemetry degradation as used here is the increase in received signal power required to offset this filtering. The usual approach to assessing this degradation is to assume that it is equal to the signal power loss in the filtering, which is easily calculated. However, this approach neglects the effects of the nonlinear phase response of the filter, the effect of any reduction of the receiving system noise due to the filter, and intersymbol interference. Here, an exact calculation of the telemetry degradation, which includes all of the above effects, is compared with the signal power loss calculation for RF filtering of NRZ data on a carrier. The signal power loss calculation is found to be a reasonable approximation when the filter follows the point at which the receiving system noise is introduced, especially if the signal power loss is less than 0.5 dB. The signal power loss approximation is less valid when the receiving system noise is not filtered.

Koerner, M. A.↗

Microwave Radiometer

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by UND on the Barge for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗

Description of SAFIRE for ISES

The SAFIRE (Spectroscopy of the Atmosphere using Far Infrared Emission) is a limb emission experiment using a far-IR Fourier transform spectrometer (FTS) and a mid-IR broadband multispectral radiometer covering the range 80 to 1600/cm. The purpose of this experiment is to obtain vertical distributions of temperature and key constituents of O(y), HO(y), NO(y), ClO(y), and BrO(y) families in the stratosphere, mesosphere, and thermosphere. The spectral channels and gases within each channel are summarized. The instrument includes a 48 element (6 x 8) Ge:GA detector array operating at 4 K in the far-IR and a 105 element (7 x 15) HgCdTe array operating at 80 K in the mid-IR. The SAFIRE uses four different scan modes for vertical coverage and resolution to address various scientific requirements. The SAFIRE data reduction will start with the retrieval of temperature profile as a function of pressure using two CO2 channel data. Constituent distributions then are obtained from other channel data using the retrieved temperature profile. The SAFIRE measurements are limited to the region above the tropopause because of radiance saturation by H2O and clouds. The computational capability necessary to process at the instrument data rate is estimated to be 19 MFLOPS for FTS data and 0.02 MFLOPS for radiometer data. It seems, therefore, that the real-time applications of SAFIRE data using an onboard processing device is not feasible. Although a temperature anomaly may be detected from the two CO2 radiometer channels using an onboard processor for the stratosphere, it is not possible to distinguish between CO2 outflux and temperature anomaly. Temperature anomaly does not, therefore, offer tropospheric information useful for real-time application.

Park, Jae H.↗

Code Benchmark of the HTTF Pressurized Conduction Cooldown Test Using SAM

The High Temperature Test Facility (HTTF) at Oregon State University is an integral system test facility to simulate postulated reactor transients of prismatic high-temperature gas-cooled reactors(HTGRs). A series of test campaigns was launched, providing abundant test data that could be used to benchmark reactor system analysis codes like the System Analysis Module (SAM). In this study, a SAM model of the facility is developed based on the two-dimensional (2D) ring model approach. All components including the ceramic matrix, graphite heaters, helium coolant channels, core barrel, upcomer, pressure vessel, and reactor cavity cooling system are modeled as concentric cylindrical rings. The model is used to simulate one of the benchmark problems-Pressurized Conduction Cooldown (PCC)-within the scope of the Organisation for Economic Co-operation and Development Nuclear Energy Agency International HTTF Benchmark. The simulations consist of two parts. In the first part, operating and boundary conditions as well as thermophysical properties of materials are specified for the benchmark problem. In this work, results from the first part will be used in code-to-code comparison. In the second part, the SAM model is used to simulate Test PG-27, which is the first PCC test carried out in the HTTF, with only two of the ten heater banks activated. The results in the second part are used for code-to-data comparison. Because the helium coolant flow rate is not measured in this facility, it is estimated using the input power and inlet/outlet coolant temperatures. Additionally, radial heat flow in the ceramic blocks is complicated by hundreds of cylindrical coolant channels and heater rods embedded in them. As such, it is necessary to deduce an effective thermal conductivity for the ceramic to analyze the core thermal behavior. SAM predictions of the helium coolant and ceramic temperatures are compared with test data measured in three equivalent sectors. Overall, the SAM results agree reasonably well with test data within the variation of data among the three sectors, which demonstrates SAM's capability in capturing transient effects in HTGR using the simplified 2D ring model.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Estimating the Electric Fields Driving Lightning Dart Leader Development With BIMAP‐3D Observations

Abstract In this paper, a numerical dart leader model has been implemented to understand the leader's development and the corresponding electric field changes observed by the 3D broadband mapping and polarization (BIMAP‐3D) system. The model assumes the extending leader channel is equipotential and has a linear charge distribution induced by an ambient electric field. The charge distribution induced by the ambient field can be used to model the electric field change at the ground. We then find the ambient electric field which best fits the field change measurements at the two BIMAP stations. The estimated ambient electric field decreases in the direction of dart leader propagation. Our observations and modeling results are consistent with our earlier hypothesis that dart leader speed is proportional to the electric field at the leader tip. The model also supports our earlier analysis that leader speed variations near branch junctions were due to previous charge deposits near the junctions. The modeled tip electric field is generally lower than the breakdown field unless the pre‐dart‐leader channel has a significant temperature of 3,000 K. This is consistent with the fact that dart leaders typically do not form new branches into the virgin air. Furthermore, the tip field is generally close to the negative streamer stability field at ambient temperatures, explaining the nature of the narrow and well‐defined channel structure. In addition to the charge distribution and the ambient and tip electric field, the development of the channel potential and current distribution are also presented.

3D lightning mapping↗

DISTEMA: distance map-based estimation of single protein model accuracy with attentive 2D convolutional neural network

Abstract Background Estimation of the accuracy (quality) of protein structural models is important for both prediction and use of protein structural models. Deep learning methods have been used to integrate protein structure features to predict the quality of protein models. Inter-residue distances are key information for predicting protein’s tertiary structures and therefore have good potentials to predict the quality of protein structural models. However, few methods have been developed to fully take advantage of predicted inter-residue distance maps to estimate the accuracy of a single protein structural model. Result We developed an attentive 2D convolutional neural network (CNN) with channel-wise attention to take only a raw difference map between the inter-residue distance map calculated from a single protein model and the distance map predicted from the protein sequence as input to predict the quality of the model. The network comprises multiple convolutional layers, batch normalization layers, dense layers, and Squeeze-and-Excitation blocks with attention to automatically extract features relevant to protein model quality from the raw input without using any expert-curated features. We evaluated DISTEMA’s capability of selecting the best models for CASP13 targets in terms of ranking loss of GDT-TS score. The ranking loss of DISTEMA is 0.079, lower than several state-of-the-art single-model quality assessment methods. Conclusion This work demonstrates that using raw inter-residue distance information with deep learning can predict the quality of protein structural models reasonably well. DISTEMA is freely at https://github.com/jianlin-cheng/DISTEMA

59 BASIC BIOLOGICAL SCIENCES↗

NANT Site - Microwave Radiometer Thermodynamic Retrievals TROPoe / Derived Data

This dataset contains daily files with thermodynamic profiles retrieved with the optimal estimation physical retrieval TROPoe (Turner and Löhnert 2014; Turner and Blumberg 2019; Turner and Löhnert 2021). The profiles are retrieved every 10 minutes from instantaneous brightness temperature measurements at 35 channels observed with a microwave radiometer MP3000A operated by NOAA Physical Sciences Laboratory on Nantucket Island for WFIP3. Additional input data in TROPoe are cloud base height from a collocated ceilometer operated by NOAA GML and temperature, water vapor mixing ratio, and pressure from a sensor attached to the MWR housing. In addition to these temporally resolved input data, TROPoe requires an a priori dataset (prior) that provides mean climatological estimates of thermodynamic profiles and specifies how temperature and humidity covary with height as an input (for details see, e.g., Djalalova et al. 2022). The prior is a key component of the retrieval and provides a constraint on the ill-posed inversion problem. A monthly prior was computed from operational radiosonde launches at Upton, NY.

17 WIND ENERGY↗

Disaster warning system: Satellite feasibility and comparison with terrestrial systems. Volume 1: Executive summary

The Disaster Warning System (DWS) is a conceptual system which will provide the National Weather Service (NWS) with communication services in the 1980s to help minimize losses caused by natural disasters. The object of this study is a comparative analysis between a terrestrial DWS and a satellite DWS. Baseline systems satisfying the NOAA requirements were synthesized in sufficient detail so that a comparison could be made in terms of performance and cost. The cost of both baseline systems is dominated by the disaster warning and spotter reporting functions. An effort was undertaken to reduce system cost through lower-capacity alternative systems generated by modifying the baseline systems. By reducing the number of required channels and modifying the spotter reporting techniques, alternative satellite systems were synthesized. A terrestrial alternative with the coverage reduced to an estimated 95 percent of the population was considered.

Spoor, J. H.↗

Flight data processing with the F-8 adaptive algorithm

An explicit adaptive control algorithm based on maximum likelihood estimation of parameters has been designed for NASA's DFBW F-8 aircraft. To avoid iterative calculations, the algorithm uses parallel channels of Kalman filters operating at fixed locations in parameter space. This algorithm has been implemented in NASA/DFRC's Remotely Augmented Vehicle (RAV) facility. Real-time sensor outputs (rate gyro, accelerometer and surface position) are telemetered to a ground computer which sends new gain values to an on-board system. Ground test data and flight records were used to establish design values of noise statistics and to verify the ground-based adaptive software. The software and its performance evaluation based on flight data are described

Hartmann, G.↗