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At least 937 records · Page 52

The Plane-parallel Albedo Bias of Liquid Clouds from MODIS Observations

In our most advanced modeling tools for climate change prediction, namely General Circulation Models (GCMs), the schemes used to calculate the budget of solar and thermal radiation commonly assume that clouds are horizontally homogeneous at scales as large as a few hundred kilometers. However, this assumption, used for convenience, computational speed, and lack of knowledge on cloud small scale variability, leads to erroneous estimates of the radiation budget. This paper provides a global picture of the solar radiation errors at scales of approximately 100 km due to warm (liquid phase) clouds only. To achieve this, we use cloud retrievals from the instrument MODIS on the Terra and Aqua satellites, along with atmospheric and surface information, as input into a GCM-style radiative transfer algorithm. Since the MODIS product contains information on cloud variability below 100 km we can run the radiation algorithm both for the variable and the (assumed) homogeneous clouds. The difference between these calculations for reflected or transmitted solar radiation constitutes the bias that GCMs would commit if they were able to perfectly predict the properties of warm clouds, but then assumed they were homogeneous for radiation calculations. We find that the global average of this bias is approx.2-3 times larger in terms of energy than the additional amount of thermal energy that would be trapped if we were to double carbon dioxide from current concentrations. We should therefore make a greater effort to predict horizontal cloud variability in GCMs and account for its effects in radiation calculations.

Oreopoulos, Lazaros↗

CCD imager with photodetector bias introduced via the CCD register

An infrared charge-coupled-device (IR-CCD) imager uses an array of Schottky-barrier diodes (SBD's) as photosensing elements and uses a charge-coupled-device (CCD) for arranging charge samples supplied in parallel from the array of SBD's into a succession of serially supplied output signal samples. Its sensitivity to infrared (IR) is improved by placing bias charges on the Schottky barrier diodes. Bias charges are transported to the Schottky barrier diodes by a CCD also used for charge sample read-out.

Kosonocky, Walter F.↗

Radiation Dry Bias of the Vaisala RS92 Humidity Sensor

The comparison of simultaneous humidity measurements by the Vaisala RS92 radiosonde and by the Cryogenic Frostpoint Hygrometer (CFH) launched at Alajuela, Cosla Rica, during July 2005 reveals a large solar radiation dry bias of the Vaisala RS92 humidity sensor and a minor temperature-dependent calibration error. For soundings launched at solar zenith angles between 10" and 30 , the average dry bias is on the order of 9% at the surface and increases to 50% at 15 km. A simple pressure- and temperature-dependent correction based on the comparison with the CFH can reduce this error to less than 7% at all altitudes up to 15.2 km, which is 700 m below the tropical tropopause. The correction does not depend on relative humidity, but is able to reproduce the relative humidity distribution observed by the CFH.

Vomel, H.↗

Electro-Optical Modulator Bias Control Using Bipolar Pulses

An improved method has been devised for controlling the DC bias applied to an electro-optical crystal that is part of a Mach-Zehnder modulator that generates low-duty-cycle optical pulses for a pulse-position modulation (PPM) optical data-communication system. In such a system, it is desirable to minimize the transmission of light during the intervals between pulses, and for this purpose, it is necessary to maximize the extinction ratio of the modulator (the ratio between the power transmitted during an "on" period and the power transmitted during an "off" period). The present method is related to prior dither error feedback methods, but unlike in those methods, there is no need for an auxiliary modulation subsystem to generate a dithering signal. Instead, as described below, dither is effected through alternation of the polarity of the modulation signal. The upper part of Figure 1 schematically depicts a Mach-Zehnder modulator. The signal applied to the electro-optical crystal consists of a radio-frequency modulating pulse signal, VRF, superimposed on a DC bias Vbias. Maximum extinction occurs during the off (VRF = 0) period if Vbias is set at a value that makes the two optical paths differ by an odd integer multiple of a half wavelength so that the beams traveling along the two paths interfere destructively at the output beam splitter. Assuming that the modulating pulse signal VRF has a rectangular waveform, maximum transmission occurs during the "on" period if the amplitude of VRF is set to a value, V , that shifts the length of the affected optical path by a half wavelength so that now the two beams interfere constructively at the output beam splitter. The modulating pulse signal is AC-coupled from an amplifier to the electro-optical crystal. Sometimes, two successive pulses occur so close in time that the operating point of the amplifier drifts, one result being that there is not enough time for the signal level to return to ground between pulses. Also, the difference between the optical-path lengths can drift with changes in temperature and other spurious effects. The effects of both types of drift are suppressed in the present method, in which one takes advantage of the fact that when Vbias is set at the value for maximum extinction, equal-magnitude positive and negative pulses applied to the electro-optical crystal produce equal output light pulses.

Farr, William↗

Visual Bias Predicts Gait Adaptability in Novel Sensory Discordant Conditions

We designed a gait training study that presented combinations of visual flow and support-surface manipulations to investigate the response of healthy adults to novel discordant sensorimotor conditions. We aimed to determine whether a relationship existed between subjects visual dependence and their postural stability and cognitive performance in a new discordant environment presented at the conclusion of training (Transfer Test). Our training system comprised a treadmill placed on a motion base facing a virtual visual scene that provided a variety of sensory challenges. Ten healthy adults completed 3 training sessions during which they walked on a treadmill at 1.1 m/s while receiving discordant support-surface and visual manipulations. At the first visit, in an analysis of normalized torso translation measured in a scene-movement-only condition, 3 of 10 subjects were classified as visually dependent. During the Transfer Test, all participants received a 2-minute novel exposure. In a combined measure of stride frequency and reaction time, the non-visually dependent subjects showed improved adaptation on the Transfer Test compared to their visually dependent counterparts. This finding suggests that individual differences in the ability to adapt to new sensorimotor conditions may be explained by individuals innate sensory biases. An accurate preflight assessment of crewmembers biases for visual dependence could be used to predict their propensities to adapt to novel sensory conditions. It may also facilitate the development of customized training regimens that could expedite adaptation to alternate gravitational environments.

Brady, Rachel A.↗

Molecular Technique to Reduce PCR Bias for Deeper Understanding of Microbial Diversity

Current planetary protection policies require that spacecraft targeted to sensitive solar system bodies be assembled and readied for launch in controlled cleanroom environments. A better understanding of the distribution and frequency at which high-risk contaminant microbes are encountered on spacecraft surfaces would significantly aid in assessing the threat of forward contamination. However, despite a growing understanding of the diverse microbial populations present in cleanrooms, less abundant microbial populations are probably not adequately taken into account due to technological limitations. This novel approach encompasses a wide spectrum of microbial species and will represent the true picture of spacecraft cleanroom-associated microbial diversity. All of the current microbial diversity assessment techniques are based on an initial PCR amplification step. However, a number of factors are known to bias PCR amplification and jeopardize the true representation of bacterial diversity. PCR amplification of a minor template appears to be suppressed by the amplification of a more abundant template. It is widely acknowledged among environmental molecular microbiologists that genetic biosignatures identified from an environment only represent the most dominant populations. The technological bottleneck overlooks the presence of the less abundant minority population and may underestimate their role in the ecosystem maintenance. DNA intercalating agents such as propidium monoazide (PMA) covalently bind with DNA molecules upon photolysis using visible light, and make it unavailable for DNA polymerase enzyme during polymerase chain reaction (PCR). Environmental DNA samples will be treated with suboptimum PMA concentration, enough to intercalate with 90 99% of the total DNA. The probability of PMA binding with DNA from abundant bacterial species will be much higher than binding with DNA from less abundant species. This will increase the relative DNA concentration of previously "shadowed" less abundant species available for PCR amplification. These PCR products obtained with and without PMA treatment will then be subjected to downstream diversity analyses such as sequencing and DNA microarray. It is expected that PMA-coupled PCR will amplify the "minority population" and help in understanding microbial diversity spectrum of an environmental sample at a much deeper level. This new protocol aims to overcome the major potential biases faced when analyzing microbial 16S rRNA gene diversity. This study will lead to a technological advancement and a commercial product that will aid microbial ecologists in understanding microbial diversity from various environmental niches. Implementation of this technique may lead to discoveries of novel microbes and their functions in sustenance of the ecosystem.

Vaishampayan, Parag A.↗

On Identifiability of Bias-Type Actuator-Sensor Faults in Multiple-Model-Based Fault Detection and Identification

This paper explores a class of multiple-model-based fault detection and identification (FDI) methods for bias-type faults in actuators and sensors. These methods employ banks of Kalman-Bucy filters to detect the faults, determine the fault pattern, and estimate the fault values, wherein each Kalman-Bucy filter is tuned to a different failure pattern. Necessary and sufficient conditions are presented for identifiability of actuator faults, sensor faults, and simultaneous actuator and sensor faults. It is shown that FDI of simultaneous actuator and sensor faults is not possible using these methods when all sensors have biases.

Joshi, Suresh M.↗

Estimation and Bias Correction of Aerosol Abundance using Data-driven Machine Learning and Remote Sensing

Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies.

Malakar, Nabin K.↗

The Fixed-bias Langmuir Probe on the Communication-navigation Outage Forecast System Satellite: Calibration and Validation

A fixed-bias spherical Langmuir probe is included as part of the Vector Electric Field Instrument (VEFI) suite on the Communication Navigation Outage Forecast System (CNOFS) satellite.CNOFS gathers data in the equatorial ionosphere between 400 and 860 km, where the primary constituent ions are H+ and O+. The ion current collected by the probe surface per unit plasmadensity is found to be a strong function of ion composition. The calibration of the collected current to an absolute density is discussed, and the performance of the spherical probe is compared to other in situ instruments on board the CNOFS satellite. The application of the calibration is discussed with respect to future xed-bias probes; in particular, it is demonstrated that some density fluctuations will be suppressed in the collected current if the plasma composition rapidly changes along with density. This is illustrated in the observation of plasma density enhancements on CNOFS.

VEFI↗

Bias Correction for Assimilation of Retrieved AIRS Profiles of Temperature and Humidity

Atmospheric Infrared Sounder (AIRS) is a hyperspectral radiometer aboard NASA's Aqua satellite designed to measure atmospheric profiles of temperature and humidity. AIRS retrievals are assimilated into the Weather Research and Forecasting (WRF) model over the North Pacific for some cases involving "atmospheric rivers". These events bring a large flux of water vapor to the west coast of North America and often lead to extreme precipitation in the coastal mountain ranges. An advantage of assimilating retrievals rather than radiances is that information in partly cloudy fields of view can be used. Two different Level 2 AIRS retrieval products are compared: the Version 6 AIRS Science Team standard retrievals and a neural net retrieval from MIT. Before assimilation, a bias correction is applied to adjust each layer of retrieved temperature and humidity so the layer mean values agree with a short-term model climatology. WRF runs assimilating each of the products are compared against each other and against a control run with no assimilation. This paper will describe the bias correction technique and results from forecasts evaluated by validation against a Total Precipitable Water (TPW) product from CIRA and against Global Forecast System (GFS) analyses.

Blankenship, Clay↗

SLS Trade Study 0058: Day of Launch (DOL) Wind Biasing

SLS heritage hardware and legacy designs have shown load exceedances at several locations during Design Analysis Cycles (DAC): MPCV Z bending moments; ICPS Electro-Mechanical Actuator (EMA) loads; Core Stage loads just downstream of Booster forward interface. SLS Buffet Loads Mitigation Task Team (BLMTT) tasked to study issue. Identified low frequency buffet load responses are a function of the vehicle's total angle of attack (AlphaTotal). SLS DOL Wind Biasing Trade team to analyze DOL wind biasing methods to limit maximum AlphaTotal in the M0.8 - 2.0 altitude region for EM-1 and EM-2 missions through investigating: Trajectory design process; Wind wavelength filtering options; Launch availability; DOL process to achieve shorter processing/uplink timeline. Trade Team consisted of personnel supporting SLS, MPCV, GSDO programs.

Decker, Ryan K.↗

The Fixed-Bias Langmuir Probe on the Communication-Navigation Outage Forecast System Satellite: Calibration and Validation

A fixed-bias spherical Langmuir probe is included as part of the Vector Electric Field Instrument (VEFI) suite on the Communication Navigation Outage Forecast System (CNOFS) satellite.CNOFS gathers data in the equatorial ionosphere between 400 and 860 km, where the primary constituent ions are H+ and O+. The ion current collected by the probe surface per unit plasma density is found to be a strong function of ion composition. The calibration of the collected current to an absolute density is discussed, and the performance of the spherical probe is compared to other in situ instruments on board the CNOFS satellite. The application of the calibration is discussed with respect to future fixed-bias probes; in particular, it is demonstrated that some density fluctuations will be suppressed in the collected current if the plasma composition rapidly changes along with density. This is illustrated in the observation of plasma density enhancements on CNOFS.

Vector Electric Field Instrument↗

Cassini Thruster Calibration Algorithm Using Reaction Wheel Biasing Data

Thrust force estimates for the reaction control thrusters on-board Cassini spacecraft are presented in this paper. Cassini consists of two thruster branches (A and B) each with eight thrusters. The four Z-thrusters control the X and Y-axes, while the four Y-thrusters control the Z-axis. It is important to track the thrust force estimates in order to detect any thruster degradation and for supporting various activities in spacecraft operations (Titan flyby, spacecraft maneuvers). The Euler equation, which describes the rotational motion of the spacecraft during a reaction wheel bias event, is used to develop the algorithm. The thrust estimates are obtained from the pseudo inverse solution using flight telemetry during the bias. Results show that the A-branch Z3A and Z4A thrusters exhibited degraded thrust in November 2008. Due to the degraded thrust performance of Z3A and Z4A, A-branch usage was discontinued and prime branch was swapped to B-branch in March 2009. The thrust estimates from the B-branch do not show any degradation to date. The algorithm is used to trend the B-branch thrust force estimates as the mission continues.

attitude control↗

Use of a Closed-Loop Tracking Algorithm for Orientation Bias Determination of an S-Band Ground Station

The Space Communications and Navigation (SCaN) Testbed project completed installation and checkout testing of a new S-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio in 2015. As with all ground stations, a key alignment process must be conducted to obtain offset angles in azimuth (AZ) and elevation (EL). In telescopes with AZ-EL gimbals, this is normally done with a two-star alignment process, where telescope-based pointing vectors are derived from catalogued locations with the AZ-EL bias angles derived from the pointing vector difference. For an antenna, the process is complicated without an optical asset. For the present study, the solution was to utilize the gimbal control algorithms closed-loop tracking capability to acquire the peak received power signal automatically from two distinct NASA Tracking and Data Relay Satellite (TDRS) spacecraft, without a human making the pointing adjustments. Briefly, the TDRS satellite acts as a simulated optical source and the alignment process proceeds exactly the same way as a one-star alignment. The data reduction process, which will be discussed in the paper, results in two bias angles which are retained for future pointing determination. Finally, the paper compares the test results and provides lessons learned from the activity.

ground station↗

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Xu, Kuan-Man↗

Use of a Closed-Loop Tracking Algorithm for Orientation Bias Determination of an S-Band Ground Station

The Space Communications and Navigation (SCaN) Testbed project completed installation and checkout testing of a new S-Band ground station at the NASA Glenn Research Center in Cleveland, Ohio in 2015. As with all ground stations, a key alignment process must be conducted to obtain offset angles in azimuth (AZ) and elevation (EL). In telescopes with AZ-EL gimbals, this is normally done with a two-star alignment process, where telescope-based pointing vectors are derived from catalogued locations with the AZ-EL bias angles derived from the pointing vector difference. For an antenna, the process is complicated without an optical asset. For the present study, the solution was to utilize the gimbal control algorithms closed-loop tracking capability to acquire the peak received power signal automatically from two distinct NASA Tracking and Data Relay Satellite (TDRS) spacecraft, without a human making the pointing adjustments. Briefly, the TDRS satellite acts as a simulated optical source and the alignment process proceeds exactly the same way as a one-star alignment. The data reduction process, which will be discussed in the paper, results in two bias angles which are retained for future pointing determination. Finally, the paper compares the test results and provides lessons learned from the activity.

reflector antenna↗

SPICE Modeling of Body Bias Effect in 4H-SiC Integrated Circuit Resistors

The DC electrical behavior of n-type 4H-SiC resistors used for realizing 500C durable integrated circuits (ICs) is studied as a function of substrate bias and temperature. Improved fidelity electrical simulation is described using SPICE NMOS model to simulate resistor substrate body bias effect that is absent from the SPICE semiconductor resistor model.

Neudeck, Philip G.↗