GPS Strain Measurement Spectrum and Potential Benefit of Collocation with Modern Broadband Seismographic Network
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measurements↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The Design of H(sub infinity) Controllers for an Experimental Non-collocated Flexible Structure
This paper describes recent results in applying robust control techniques to achieve vibration suppression of an active precision truss structure.
robust control↗
3D Aerosol-Cloud Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus Cloud Fields
3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.
Wen, Guoyong↗
An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers
This study focuses on a comparison of peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. The legacy mechanical wind instruments on CCAFS/KSC and VAFB weather towers are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. The wind tower networks on KSC/CCAFS and VAFB have 41 and 27 towers, respectively. Launch Weather Officers, forecasters, and Range Safety analysts at both locations need to understand the performance of the new wind sensors for a myriad of reasons that include weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The Legacy sensors measure wind speed and direction mechanically. The ultrasonic RSA sensors have no moving parts. Ultrasonic sensors were originally developed to measure very light winds (Lewis and Dover 2004). The technology has evolved and now ultrasonic sensors provide reliable wind data over a broad range of wind speeds. However, because ultrasonic sensors respond more quickly than mechanical sensors to rapid fluctuations in speed, characteristic of gusty wind conditions, comparisons of data from the two sensor types have shown differences in the statistics of peak wind speeds (Lewis and Dover 2004). The 45th Weather Squadron (45 WS) and the 30 WS requested the Applied Meteorology Unit (AMU) to compare data from RSA and Legacy sensors to determine if there are significant differences in peak wind speed information from the two systems.
Short, David A.↗
Constraining Aerosol Optical Models Using Ground-Based, Collocated Particle Size and Mass Measurements in Variable Air Mass Regimes During the 7-SEAS/Dongsha Experiment
During the spring of 2010, NASA Goddard's COMMIT ground-based mobile laboratory was stationed on Dongsha Island off the southwest coast of Taiwan, in preparation for the upcoming 2012 7-SEAS field campaign. The measurement period offered a unique opportunity for conducting detailed investigations of the optical properties of aerosols associated with different air mass regimes including background maritime and those contaminated by anthropogenic air pollution and mineral dust. What appears to be the first time for this region, a shortwave optical closure experiment for both scattering and absorption was attempted over a 12-day period during which aerosols exhibited the most change. Constraints to the optical model included combined SMPS and APS number concentration data for a continuum of fine and coarse-mode particle sizes up to PM2.5. We also take advantage of an IMPROVE chemical sampler to help constrain aerosol composition and mass partitioning of key elemental species including sea-salt, particulate organic matter, soil, non sea-salt sulphate, nitrate, and elemental carbon. Our results demonstrate that the observed aerosol scattering and absorption for these diverse air masses are reasonably captured by the model, where peak aerosol events and transitions between key aerosols types are evident. Signatures of heavy polluted aerosol composed mostly of ammonium and non sea-salt sulphate mixed with some dust with transitions to background sea-salt conditions are apparent in the absorption data, which is particularly reassuring owing to the large variability in the imaginary component of the refractive indices. Extinctive features at significantly smaller time scales than the one-day sample period of IMPROVE are more difficult to reproduce, as this requires further knowledge concerning the source apportionment of major chemical components in the model. Consistency between the measured and modeled optical parameters serves as an important link for advancing remote sensing and climate research studies in dynamic aerosol-rich environments like Dongsha.
Bell, Shaun W.↗
Comparison of Raindrop Size Distribution Measurements by Collocated Disdrometers
An impact-type Joss-Waldvogel disdrometer (JWD), a two-dimensional video disdrometer (2DVD), and a laser optical OTT Particle Size and Velocity (PARSIVEL) disdrometer (PD) were used to measure the raindrop size distribution (DSD) over a 6-month period in Huntsville, Alabama. Comparisons indicate event rain totals for all three disdrometers that were in reasonable agreement with a reference rain gauge. In a relative sense, hourly composite DSDs revealed that the JWD was more sensitive to small drops (,1 mm), while the PD appeared to severely underestimate small drops less than 0.76mm in diameter. The JWD and 2DVD measured comparable number concentrations of midsize drops (1-3mm) and large drops (3-5 mm), while the PD tended to measure relatively higher drop concentrations at sizes larger than 2.44mm in diameter. This concentration disparity tended to occur when hourly rain rates and drop counts exceeded 2.5mm/h and 400/min, respectively. Based on interactions with the PD manufacturer, the partially inhomogeneous laser beam is considered the cause of the PD drop count overestimation. PD drop fall speeds followed the expected terminal fall speed relationship quite well, while the 2DVD occasionally measured slower drops for diameters larger than 2.4mm, coinciding with events where wind speeds were greater than 4m/s. The underestimation of small drops by the PD had a pronounced effect on the intercept and shape of parameters of gamma-fitted DSDs, while the overestimation of midsize and larger drops resulted in higher mean values for PD integral rain parameters
disdrometers↗
Aerosol Optical Depths over Oceans: a View from MISR Retrievals and Collocated MAN and AERONET in Situ Observations
In this study, aerosol optical depths over oceans are analyzed from satellite and surface perspectives. Multiangle Imaging SpectroRadiometer (MISR) aerosol retrievals are investigated and validated primarily against Maritime Aerosol Network (MAN) observations. Furthermore, AErosol RObotic NETwork (AERONET) data from 19 island and coastal sites is incorporated in this study. The 270 MISRMAN comparison points scattered across all oceans were identified. MISR on average overestimates aerosol optical depths (AODs) by 0.04 as compared to MAN; the correlation coefficient and root-mean-square error are 0.95 and 0.06, respectively. A new screening procedure based on retrieval region characterization is proposed, which is capable of substantially reducing MISR retrieval biases. Over 1000 additional MISRAERONET comparison points are added to the analysis to confirm the validity of the method. The bias reduction is effective within all AOD ranges. Setting a clear flag fraction threshold to 0.6 reduces the bias to below 0.02, which is close to a typical ground-based measurement uncertainty. Twelve years of MISR data are analyzed with the new screening procedure. The average over ocean AOD is reduced by 0.03, from 0.15 to 0.12. The largest AOD decrease is observed in high latitudes of both hemispheres, regions with climatologically high cloud cover. It is postulated that the screening procedure eliminates spurious retrieval errors associated with cloud contamination and cloud adjacency effects. The proposed filtering method can be used for validating aerosol and chemical transport models.
AERONET↗
Collocated Argo-Hyperspectral Infrared Satellite Measurements: An Idea
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Santha Akella↗
SAGE III/ISS Validation of Ozone and Water Vapor V5.2 Data Using Collocated Balloon-Borne Measurements
The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument installed on the International Space Station (ISS) has completed nearly four years of data collection and production of science data products. The SAGE III/ISS is a solar and lunar occultation instrument that scans the light from the Sun and Moon through the limb of the Earth’s atmosphere to produce vertical profiles of aerosol, ozone, water vapor, and other trace gases. It continues the legacy of previous SAGE instruments dating back to the 1970s to provide data continuity of stratospheric constituents critical for assessing trends in the ozone layer. This presentation shows the validation results of comparing SAGE III/ISS ozone and water vapor vertical profiles from the newly released v5.2 science product with those of balloon launched ozonesonde and frost point hygrometer measurements and satellite data from the Microwave Limb Sounder.
S Kizer↗
Novel Parameterization of Ice Cloud Effective Diameter from Collocated CALIOP-IIR and CloudSat Retrievals
Satellite-based measurements of global ice cloud microphysical properties are sampled to develop a novel set of physical parameterizations, relating to cloud layer temperature and effective diameter D(e), that can be implemented for two separate applications: in numerical weather prediction models and lidar-based cloud radiative forcing studies. Ice cloud optical properties (i.e., spectral scattering and absorption) are estimated based on the effective size and habit mixture of the cloud particles. Historically, the ice cloud D(e) has been parameterized from aircraft in situ measurements. However, aircraft-based parameterizations are opportunistic in that they only represent specific types of clouds (e.g., convective anvil, tropopause-topped cirrus) in the regions in which they were sampled and, in some cases, are limited in fully resolving the entire vertical cloud layer. Breaking away from the aircraft-based parameterization paradigm, this study is the first of its kind to attempt a parameterization of D(e) as a function of temperature, ice water content (IWC), and lidar-derived extinction from satellite-based global oceanic measurements of ice clouds. Data from both active and passive remote sensing sensors from two of NASA’s A-Train satellites, CloudSat and CALIPSO, are collected to guide development of globally robust parameterizations of all ice cloud types and one exclusively for cirrus clouds.
Ice Cloud↗
Implicit Temporal Methods for Entropy Stable Spectral Collocation
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Implicit Runge-Kutta↗
AMSR-2 Daily Snow Depth Data Product Using a Neural Network Algorithm Trained by Collocated ICESat-2 Measurements
By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu 1 et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu 2 et al. (2022,2024) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, a neural network (NN) algorithm, employing several channels from AMSR-2 and the humidity vertical profiles GMAO GEOS-IT, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained NN snow-depth was applied to 2014-2020 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. This paper used AMSR-2 data, a passive microwave instrument to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.
Neural Network↗
Spectral and Spatial Dependencies in the Validation of Satellite-Based Aerosol Optical Depth from the Geostationary Ocean Color Imager Using the Aerosol Robotic Network
The regional and global scale of aerosols in the atmosphere can be quantified using the aerosol optical depth (AOD) retrieved from satellite observations. To obtain reliable satellite AODs, conducting consistent validations and refining retrieval algorithms are crucial. AODs and Ångström exponents (AEs) measured with the aerosol robotic network (AERONET) are considered as the ground truth for satellite validations. AERONET AEs are used to collocate the wavelength of the AERONET AODs to those of the satellite AODs when there is a discordancy in their wavelengths. However, numerous validation studies have proposed different strategies by applying the AERONET AODs and AEs, and spatiotemporal collocation criteria. This study examined the impact of the wavelength and spatial collocation radius variations by comparing AODs at 550 nm derived from the geostationary ocean color imager (GOCI) with those obtained from the AERONET for the year 2016. The estimated AERONET AODs at 550 nm varied from 5.18% to 11.73% depending on the selection of AOD and AE, and the spatial collocation radii from 0 to 40 km, respectively. The longer the collocation radius and the higher the AODs, the greater the variability observed in the validation results. Overall, the selection of the spatial collocation radius had a stronger impact on the variability in the validation results obtained compared to the selection of the wavelength. The variability was also found in seasonal analysis. Therefore, it is recommended to carefully select the data wavelength and spatial collocation radius, consider seasonal effects, and provide this information when validating satellite AODs using AERONET.
GOCI↗
Methods for local gravity field approximation
The most widely known modern method for estimating gravity field values from observed data is least-squares collocation. Its advantages are that it can make estimates at arbitrary locations based on irregularly spaced observations, and that it makes use of statistical information about errors in the input data while providing corresponding information about the quality of the output estimates. Disadvantages of collocation include the necessity of inverting square matrices of dimension equal to the number of data values and the need to assume covariance models for the gravity field and the data errors. Fourier methods are an important alternative to collocation; having the advantage of greater computational efficiency, but requiring data estimates to be on a regular grid and not using or providing statistical accuracy information. The GEOFAST algorithm is an implementation of collocation that achieves high computational efficiency by transforming the estimation equations into the frequency domain where an accurate approximation may be made to reduce the workload. The forward and inverse Fast Fourier Transforms (FFTs) are utilized. The accuracy and computational efficiency of the GEOFAST algorithm is demonstrated using two sets of synthetic gravity data: marine gravity for an ocean trench region including wavelengths longer than 200 km; and local land gravity containing wavelengths as short as 5 km. These results are discussed along with issues such as the advantages of first removing reference field models before carrying out the estimation algorithm.
Sailor, R. V.↗
The zeroes of controlled structures - Sensor/actuator attributes and structural modelling
The effects of sensor/actuator design and modeling decisions on the zero frequencies of single input single output structural systems are explored. A zero definition based on the high gain closed loop character of the poles of a system is used to study parametrically zeroes as a function of sensor and actuator location. An infinite order model is adopted so that the effects of finite order modeling are removed. Examples focus on point or localized actuators and sensors and simple uniform structures. The sensitivity of the zero frequencies to changes in the sensor and actuator location for both collocated and non-collocated cases are presented. Non-minimum phase behavior is visible in only certain non-collocated situations. In addition to the sensor/actuator attributes, the zeroes are shown to be a function of the truncation and discretization used to model the structural response for collocated and dual systems. Methods for improving the zero predictions in the control bandwidth are suggested.
Fleming, Farla M.↗
Application of Gaussian Mixture Regression for the Correction of Low Cost PM2.5 Monitoring Data in Accra, Ghana
Low-cost sensors (LCSs) for air quality monitoring have enormous potential to improve air quality data coverage in resource-limited parts of the world such as sub-Saharan Africa. LCSs, however, are affected by environment and source conditions. To establish high-quality data, LCSs must be collocated and calibrated with reference grade PM2.5 monitors. From March 2020, a low-cost PurpleAir PM2.5 monitor was collocated with a Met One Beta Attenuation Monitor 1020 in Accra, Ghana. While previous studies have shown that multiple linear regression (MLR) and random forest regression (RF) can improve accuracy and correlation between PurpleAir and reference data, MLR and RF yielded suboptimal improvement in the Accra collocation (R2 = 0.81 and R2 = 0.81, respectively). We present the first application of Gaussian mixture regression (GMR) to air quality data calibration and demonstrate improvement over traditional methods by increasing the collocated PM2.5 correlation and accuracy to R2 = 0.88 and MAE = 2.2 μg/cu. m. Gaussian mixture models (GMMs) are a probability density estimator and clustering method from which nonlinear regressions that tolerate missing inputs can be derived. We find that even when given missing inputs, GMR provides better correlation than MLR and RF performed with complete data. GMR also allows us to estimate calibration certainty. When evaluated, 95% confidence intervals agreed with reference PM2.5 data 96% of the time, suggesting that the model accurately assesses its own confidence. Additionally, clustering within the GMM is consistent with climate characteristics, providing confidence that the calibration approach can learn underlying relationships in data.
Sensors↗