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All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

An Evaluation of the Liquid Cloud Droplet Effective Radius Derived from MODIS, Airborne Remote Sensing, and in Situ Measurements from CAMP2Ex

The cloud drop effective radius (Re) of the drop size distribution derived from passive satellite sensors is a key variable used in climate research. Validation of these satellite products has often taken place under stratiform cloud conditions that favor the assumption of cloud horizontal homogeneity used by the retrieval techniques. However, many studies have noted concerns with respect to significant biases in retrieved Re arising from cloud heterogeneity, for example, in cumulus cloud fields. Here, we examine data collected during the 2019 “Cloud, Aerosol and Monsoon Processes Philippines Experiment” (CAMP2Ex), which, in part, targeted the objective of providing the first detailed evaluation of Re retrieved across multiple platforms and techniques in a cumulus and congestus cloud region. Our evaluation consists of cross-comparisons of Re between the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra satellite, the Research Scanning Polarimeter (RSP) onboard the NASA P-3 aircraft, and in situ measurements from both the NASA P-3 and Learjet aircraft that are all taken in close spatiotemporal proximity to the same cloud fields. A particular advantage of our approach lies in the capability of the RSP to retrieve Re using a bi-spectral MODIS approach and a polarimetric approach, which allows for the evaluation of bi-spectral and polarimetric Re retrievals from an airborne perspective using the same samples. Averaged over all P-3 flight segments examined here for warm clouds, the RSP polarimetric method, the in situ method, and the bias-adjusted MODIS method of Fu et al. (2019) show a comparable median (mean ± standard deviation) for the Re samples of 9.6 (10.2 ± 4.0) µm, 11.0 (13.6 ± 11.3) µm, and 10.4 (10.8 ± 3.8) µm, respectively. These values are far lower than the values of 15.1 (16.2 ± 5.5) µm and 17.2 (17.7 ± 5.7) µm from the bi-spectral retrievals of RSP and MODIS, respectively. Similar results are observed when Re is segregated by cloud-top height and in detailed case studies. The clouds sampled during CAMP2Ex consist of mostly small (mean transect length ∼ 1.4 km) and low clouds (mean cloud-top height ∼ 1 km), which had more numerous small clouds than the trade wind cumuli sampled in past field campaigns such as Rain in Shallow Cumulus over the Ocean (RICO) and the Indian Ocean Experiment (INDOEX). The overestimates of Re from the RSP bi-spectral technique compared with the polarimetric technique increased as cloud size and cloud optical depth decreased. Drizzle, cloud-top bumpiness, and solar zenith angle, however, are not closely correlated with the overestimate of bi-spectral Re. For shallow clouds that dominated the liquid cloud cover for the CAMP2Ex region and period, we show that 3-D radiative transfer and cloud heterogeneity, particularly for the optically thin and small clouds, appear to be the leading cause of the large positive biases in bi-spectral retrievals. Because this bias varies with the underlying structure of the cloud field, caution continues to be warranted in studies that use bi-spectral Re retrievals in cumulus cloud fields.

Cloud microphysics↗
NASA NTRS2014

Wireless Capacitive Pressure Sensor Operating up to 400 Celcius from 0 to 100 psi Utilizing Power Scavenging

In this paper, a wireless capacitive pressure sensor developed for the health monitoring of aircraft engines has been demonstrated. The sensing system is composed of a Clapp-type oscillator that operates at 131 MHz. The Clapp oscillator is fabricated on a alumina substrate and consists of a Cree SiC (silicon carbide) MESFET (Metal Semiconductor Field Effect Transistors), this film inductor, Compex chip capacitors and Sporian Microsystem capacitive pressure sensor. The resonant tank circuit within the oscillator is made up of the pressure sensor and a spiral thin film inductor, which is used to magnetically couple the wireless pressure sensor signal to a coil antenna placed over 1 meter away. 75% of the power used to bias the sensing system is generated from thermoelectric power modules. The wireless pressure sensor is operational at room temperature through 400 C from 0 to 100 psi and exhibits a frequency shift of over 600 kHz.

Scardelletti, Maximilian C.↗
NASA NTRS1994

Particle sensor array

A particle sensor array which in a preferred embodiment comprises a static random access memory having a plurality of ion-sensitive memory cells, each such cell comprising at least one pull-down field effect transistor having a sensitive drain surface area (such as by bloating) and at least one pull-up field effect transistor having a source connected to an offset voltage. The sensitive drain surface area and the offset voltage are selected for memory cell upset by incident ions such as alpha-particles. The static random access memory of the present invention provides a means for selectively biasing the memory cells into the same state in which each of the sensitive drain surface areas is reverse biased and then selectively reducing the reversed bias on these sensitive drain surface areas for increasing the upset sensitivity of the cells to ions. The resulting selectively sensitive memory cells can be used in a number of applications. By way of example, the present invention can be used for measuring the linear energy transfer of ion particles, as well as a device for assessing the resistance of CMOS latches to Cosmic Ray induced single event upsets. The sensor of the present invention can also be used to determine the uniformity of an ion beam.

Buehler, Martin G.↗
NASA NTRS2016

Unexpected Nonlinear Effects in Superconducting Transition-Edge Sensors

When a normal metal transitions into the superconducting state the DC resistance drops from a finite value to zero over some finite transition width in temperature, current, and magnetic field. Superconducting transition-edge sensors (TESs) operate within this transition region and uses resistive changes to measure deposited thermal energy. This resistive transition is not perfectly smooth and a wide range of TES designs and materials show sub-structure in the resistive transition (as seen in smooth nonmonotonic behavior, jump discontinuities, and hysteresis in the devices current-voltage relation and derivatives of the resistance with respect to temperature, bias current, and magnetic field). TES technology has advanced to the point where for many applications this structure is the limiting factor in performance and optimization consists of finding operating points away from these structures. For example, operating at or near this structure can lead to nonlinearity in the detectors response and gain scale, limit the spectral range of the detector by limiting the usable resistive range, and degrade energy resolution. The origin of much of this substructure is unknown. This presentation investigates a number of possible sources in turn. First we model the TES as a superconducting weak-link and solve for the characteristic differential equations current and voltage time dependence. We find:(1) measured DC biased current-voltage relationship is the time-average of a much higher frequency limit cycle solution.(2) We calculate the fundamental frequency and estimate the power radiated from the TES treating the bias leads as an antennae.(3) The solution for a set of circuit parameters becomes multivalued leading to current transitions between levels.(4)The circuit parameters can change the measure resistance and mask the true critical current. As a consequence the TES resistance surface is not just a function of temperature, current, and magnetic field but is also a function of the circuit elements (such as shunt resistor, SQUID inductance, and capacitor values). In other words, same device measured in different electrical circuits will have a different resistive surface in temperature, current, and magnetic field. Next we consider that at the transition temperature of a superconductor both the magnetic penetration depth and coherence length are divergent. As a consequence these important characteristic length scales are changing with operating point. We present measurements on devices showing commensurate behavior between these characteristic lengths and the length scale of added normal metal structures. Reordering of proximity vortices leads to discontinuities and irreversibility of the current-voltage curves. Last we consider a weak-link TES including both thermal activated resistance effects and the effect of the magnetic penetration depth being a function of temperature and magnetic field. We derive its impact on the resistive transition surface and the important device parameters a and b.

Superconducting Detectors↗
NASA NTRS2021

Chapter 13: Errors and Uncertainties Associated with Quasi-Global Satellite Precipitation Products

Measuring precipitation on a global scale is only possible from satellite platforms. Satellite precipitation estimates are based on geosynchronous infrared sensors on geostationary satellites, characterized by high sampling frequency, and polar-orbiting microwave sensors on low-Earth-orbiting satellites with less-frequent sampling. Assessing satellite product performance is fundamental to infer the reliability of such estimates and effectively use them in water resources management, extreme event characterization, disease control, or weather forecasting. Nevertheless, errors and uncertainties associated with satellite precipitation products are often masked due to temporal and spatial sampling, as well as bias-corrections against a reference dataset. Moreover, the verification of satellite precipitation products is easier over land areas, where rain gauges and ground radars are available as benchmark, but extremely limited over the oceans. Substantial work still remains to better quantify relative and absolute errors and uncertainties within satellite-based precipitation products over land and oceans.

Viviana Maggioni↗
NASA NTRSDate not supplied

Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder Intercalibration Data Analysis Strategy

One of the prime science objectives of NASA’s Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) mission is to acquire unprecedentedly accurate Système Internationale (SI)-traceable Earth-view measurements that can be used as reference for intercalibrating the Clouds and the Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments onboard NOAA-20 satellite. The hyperspectral nature of CPF measurements will significantly reduce spectrally induced biases when intercalibrating multiband or broadband satellite instruments with CPF. This advancement eliminates the requirement for spectral band adjustment factors, representing a substantial improvement in sensor intercalibration studies. The CPF intercalibration team is aiming to achieve a maximum intercalibration methodology uncertainty of 0.3 % (k=1). Our studies have revealed that the most significant contribution to the targeted uncertainty budget originates from the combined effects of spatial and temporal matching errors. Spatial matching error arises from discrepancies in CPF and target instrument pixel resolution and geolocation uncertainty, while temporal matching error is caused by changes in scene radiances over time, occurring between when the target and reference instruments observe the same scenes. To estimate the maximum expected uncertainty contribution from these sources, spatial and temporal matching noise analyses were conducted using algorithmically filtered Landsat 9 Operational Land Imager (OLI) and Geostationary Operational Environmental Satellite (GOES)-16 ABI CONUS scan data as proxies for CPF and target instruments. In the upcoming conference presentation, we will elaborate on the methodology employed in these experiments, provide details of the data filtering algorithms, and present results of the spatial and temporal matching uncertainty analyses.

Intercalibration↗
DOE OSTI2026

Detectors and beam monitors based on wide bandgap semiconductors at cryogenic temperatures

Wide-bandgap semiconductors, such as single-crystal diamond and sapphire, can be used to measure the flux of passing particles through a particle-induced conductivity effect. We recently demonstrated a diamond-based, electrodeless electron beam halo monitor. This monitor utilized a thin diamond blade placed within an open, high-quality microwave resonator. The blade partially intercepted the beam and changes in the RF properties of the resonator were used to infer beam parameters. To enhance the sensitivity of our semiconductor sensors, we propose two new techniques: (1) biasing the semiconductor sensor to support avalanche multiplication of free carriers, and (2) operating at cryogenic temperatures to reduce intrinsic semiconductor losses and increase the mobility of induced carriers. These techniques are applicable not only to particle beam diagnostics but also to the detection of various types of ionizing radiation.

Accelerator Physics↗
NASA NTRS2020

Investigation Of Prandtl-Ishlinskii Hysteresis Compensation for Deep Space Optical Communications Pointing Control

This paper studies the simulated performance of the Deep Space Optical Communication (DSOC) laser downlink pointing control system that has a pointing requirement at the sub-microradian scale. To achieve the required pointing precision, the DSOC Flight Laser Transceiver (FLT) point-ahead mirror (PAM) employs piezoelectric actuators, which are widely used in precision applications due to their high motion resolution, rapid response, and high output forces. However, a piezoelectric actuator's performance is often limited by nonlinearities in their response, most significantly hysteresis. To study the effect of hysteresis on our simulated pointing performance, an invertible hysteresis model is developed using the Classical Prantdl-Ishlinskii (CPI) method. The simulation includes models of DSOC hardware and electronic system components based on key parameters (bias, frequency response, noise), with the hysteresis modeled in the PAM piezo actuator dynamics. A Proportional-Integral controller provides feedback with measurements from two potential sources: strain gauge sensors or a photon-counting camera. To compensate for hysteresis behavior, a feedforward inverse CPI hysteresis model is implemented in the control system. Two CPI models are built using different sampling methods (uniform sampling and cosine spacing) and controller performance is compared. For the maximum command range of ±400 μrad at 1 mHz, results show that the feedforward combined with feedback control reduces output tracking error by 50% or 58% (to 0.20 or 0.38 μrad) compared to feedback control alone (from 0.40 or 0.90 μrad), corresponding to the uniform-sampled and cosine-sampled CPI models, respectively.

Marinello, Lindsey A.↗
NASA NTRS2006

TRMM On-Orbit Performance Reassessed After Control Change

The Tropical Rainfall Measuring Mission (TRMM) spacecraft, a joint mission between the U.S. and Japan, launched onboard an H-I1 rocket on November 27, 1997, and transitioned in August, 2001, from an average operating altitude of 350 kilometers to 402.5 kilometers. Due to problems using the Earth Sensor Assembly (ESA) at the higher altitude, TRMM switched to a backup attitude control mode. Prior to the orbit boost TRMM controlled pitch and roll to the local vertical using ESA measurements while using gyro data to propagate yaw attitude between yaw updates from the Sun sensors. After the orbit boost, a Kalman filter used 3-axis gyro data with Sun sensor and magnetometers to estimate onboard attitude. While originally intended to meet a degraded attitude accuracy of 0.7 degrees, the new control mode met the original 0.2 degree attitude accuracy requirement after improving onboard ephemeris prediction and adjusting the magnetometer calibration onboard. Independent roll attitude checks using a science instrument, the Precipitation Radar (PR) which was built in Japan, provided a novel insight into the pointing performance. The PR data helped identify the pointing errors after the orbit boost, track the performance improvements, and show subtle effects from ephemeris errors and gyro bias errors. It also helped identify average bias trends throughout the mission. Roll errors tracked by the PR from sample orbits pre-boost and post-boost are shown in Figure 1. Prior to the orbit boost, the largest attitude errors were due to occasional interference in the ESA. These errors were sometime larger than 0.2 degrees in pitch and roll, but usually less, as estimated from a comprehensive review of the attitude excursions using gyro data. Sudden jumps in the onboard roll show up as spikes in the reported attitude since the control responds within tens of seconds to null the pointing error. The PR estimated roll tracks well with an estimate of the roll history propagated using gyro data. After the orbit boost, the attitude errors shown by the PR roll have a smooth sine-wave type signal because of the way that attitude errors propagate with the use of gyro data. Yaw errors couple at orbit period to roll with 1/4 orbit lag. By tracking the amplitude, phase, and bias of the sinusoidal PR roll error signal, it was shown that the average pitch rotation axis tends to be offset from orbit normal in a direction perpendicular to the Sun direction, as shown in Figure 2 for a 200 day period following the orbit boost. This is a result of the higher accuracy and stability of the Sun sensor measurements relative to the magnetometer measurements used in the Kalman filter. In November, 2001 a magnetometer calibration adjustment was uploaded which improved the pointing performance, keeping the roll and yaw amplitudes within about 0.1 degrees.

Bilanow, Stephen↗
NASA NTRS2003

Sensitivity Studies for Space-based Measurements of Atmospheric Total Column Carbon Dioxide Using Reflected Sunlight

A series of sensitivity studies is carried out to explore the feasibility of space-based global carbon dioxide (CO2) measurements for global and regional carbon cycle studies. The detection method uses absorption of reflected sunlight in the CO2 vibration-rotation band at 1.58 micron. The sensitivities of the detected radiances are calculated using the line-by-line model (LBLRTM), implemented with the DISORT (Discrete Ordinates Radiative Transfer) model to include atmospheric scattering in this band. The results indicate that (a) the small (approx.1%) changes in CO2 near the Earth's surface are detectable in this CO2 band provided adequate sensor signal-to-noise ratio and spectral resolution are achievable; (b) the effects of other interfering constituents, such as water vapor, aerosols and cirrus clouds, on the radiance are significant but the overall effects of the modification of light path length on total back-to-space radiance sensitivity to CO2 change are minor for general cases, which means that generally the total column CO2 can be derived in high precision from the ratio of the on-line center to off-line radiances; (c) together with CO2 gas absorption aerosol/cirrus cloud layer has differential scattering which may result in the modification of on-line to off-line radiance ratio which could lead a large bias in the total column CO2 retrieval. Approaches to correct such bias need further investigation. (d) CO2 retrieval requires good knowledge of the atmospheric temperature profile, e.g. approximately 1K RMS error in layer temperature, which is achievable from new atmospheric sounders in the near future; (e) the atmospheric path length, over which the CO2 absorption occurs, should be known in order to correctly interpret horizontal gradients of CO2 from the total column CO2 measurement; thus an additional sensor for surface pressure measurement needs to be attached for a complete measurement package.

Mao, Jianping↗
NASA NTRS2012

Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data

This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.

Gorinevsky, Dimitry↗
NASA NTRSDate not supplied

X-Ray Missions Based on LTD Technologies

Microcalorimeter arrays used as imaging spectrometers will enable ground-breaking science in X-ray astrophysics. Their development has been one of the driving applications of the low temperature detector community since the early 1980s. While their application in space remains in relative infancy, we are on the verge of an era in which microcalorimeter spectrometers are likely to dominate instrumentation for high-energy astrophysics missions. NASA sounding rocket experiments such as the X-ray Quantum Calorimeter (XQC) and Micro-X have now paved the way for orbital observatories. JAXA’s Astro-H gave us a glimpse of this fantastic new capability before its unfortunate demise. The launch of XRISM later this year should finally demonstrate the sort of large suite of observations that X-ray microcalorimeter arrays will make major contributions to. In the mid-2030s, we will see the launch of ESA’s flagship Athena mission, that will further advance the imaging and spectroscopic capabilities for the high-energy X-ray community enormously. Numerous other potential new mission concepts using X-ray microcalorimeters have been studied in detail such as NASA’s Lynx and the Light Element Mapper (LEM), JAXA’s Super-DIOS, and China’s Hot Universe Baryon Surveyor (HUBS). In the first half of this presentation, I will review the development and desired requirements of the X-ray microcalorimeter missions and concepts, and describe the current progress and status missions being implemented and proposed. In the second half of this presentation, I will focus on The Line Emission Mapper (LEM) which is a probe-class mission concept under study by NASA that is designed to provide unprecedented insight into the physics of galaxy formation, including stellar and black-hole feedback and flows of baryonic matter into and out of galaxies. LEM incorporates a light-weight X-ray optic with 10” angular resolution and a large-format microcalorimeter array with a 15” pixel pitch over a 29’ field of view (FOV). The main microcalorimeter array and readout design takes advantage of mature technology that has been developed for Athena X-IFU. The central 7’ region of the array consists of ~ 800 transition-edge sensors (TESs), optimized for a bandpass of 0.3-2 keV and with an energy resolution of 1.2 eV at 1 keV. The rest of the FOV is covered by 4-pixel TES hydras with 2.5 eV energy resolution at 1 keV. Hydras are position-sensitive (‘thermally multiplexed’) detectors that enable extremely large numbers of effective pixels in an array, without a commensurate increase in the number of wires, bias circuit, and readout components. In total the array will have ~ 4k TESs with ~ 14k imaging elements on a 290 micron-pitch. The array will be read out with state-of-the-art time-division multiplexing (TDM), implement with 59 pixels (and 1 dark pixel) in each of the 69 TDM columns. Here we present a detailed overview of the baseline microcalorimeter detector design and present first results from both single pixel TESs and 4-pixel hydras. Our prototype LEM pixels utilize 15um x 50um Mo/Au TESs with a transition temperature of around 58 mK. These pixels incorporate high-fill-factor Au absorbers of thickness 0.54um. We have demonstrated an energy resolution of 0.90+/-0.02 eV and 1.90 +/-0.02 eV at 1.5 keV for single pixel and 4-pixel hydras, respectively, meeting the performance requirements of LEM. We show how the position discrimination in the hydra pixels can be achieved, down to energies of a few 100 eV, using the measured pulse rise-times. Finally, we will show that the properties of the LEM pixels are well optimized for the proposed TDM read out architecture.

Simon Richard Bandler↗
NASA NTRS2014

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3◦: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

long-term variability↗
NASA NTRS1972

Some effects of bias errors in redundant flight control systems.

The controllability and steady-state response of parallel-redundant flight control systems are examined. It is found that state components which appear in the parallel signal paths, e.g., individual actuator commands, are not controllable, although the sum of the command signals is well-behaved. If the response modes associated with these components are not stable, bias errors can cause the components to diverge, leading to the possibility of 'nuisance trips' in failure detection/isolation logic and eventual control system lockup (at saturation). Combining the inputs to the control computers assures that sensor bias will not cause divergence, while cross-strapping control strings bounds divergent response to all bias error inputs. Results of numerical solutions confirm the problem and its solutions.

Stengel, R. F.↗
NASA NTRS1972

An adaptive technique for a redundant-sensor navigation system.

An on-line adaptive technique is developed to provide a self-contained redundant-sensor navigation system with a capability to utilize its full potentiality in reliability and performance. This adaptive system is structured as a multistage stochastic process of detection, identification, and compensation. It is shown that the detection system can be effectively constructed on the basis of a design value, specified by mission requirements, of the unknown parameter in the actual system, and of a degradation mode in the form of a constant bias jump. A suboptimal detection system on the basis of Wald's sequential analysis is developed using the concept of information value and information feedback. The developed system is easily implemented, and demonstrates a performance remarkably close to that of the optimal nonlinear detection system. An invariant transformation is derived to eliminate the effect of nuisance parameters such that the ambiguous identification system can be reduced to a set of disjoint simple hypotheses tests. By application of a technique of decoupled bias estimation in the compensation system the adaptive system can be operated without any complicated reorganization.

Chien, T.-T.↗
NASA NTRS1972

Some effects of bias errors in redundant flight control systems

The controllability and steady-state response of parallel-redundant flight control systems are examined. It is found that state components which appear in the parallel signal paths, or individual actuator commands, are not controllable, although the sum of the command signals is well-behaved. If the response modes associated with these components are not stable, bias errors can cause the components to diverge, leading to the possibility of nuisance trips in failure detection/isolation logic and eventual control system lockup (at saturation). Combining the inputs to the control computers assures that sensor bias will not cause divergence, while cross-strapping control strings bounds divergent response to all bias error inputs. Results of numerical solutions confirm the problem and its solutions.

Stengel, R. F.↗
NASA NTRS1973

Some effects of bias errors in redundant flight control systems.

The controllability and steady-state response of parallel-redundant flight control systems are examined. It is found that state components which appear in the parallel signal paths, e.g., individual actuator-commands, are not controllable, although the sum of the command signals is well behaved. If the response modes associated with these components are not stable, bias errors can cause the components to diverge, leading to the possibility of nuisance trips in failure detection/isolation logic and eventual control system lockup (at saturation). Combining the inputs to the control computers assures that sensor bias will not cause divergence, while cross-strapping control strings bounds divergent response to all bias error inputs.

Stengel, R. F.↗
NASA NTRS2014

How Well Do Satellite AOD Observations Represent the Spatial and Temporal Variability of PM2.5 Concentration for the United States?

Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.

MODIS (radiometry)↗