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At least 127 records · Page 7

Vertical Scales of Turbulence at the Mount Wilson Observatory

The vertical scales of turbulence at the Mount Wilson Observatory are inferred from data from the University of California at Berkeley Infrared Spatial Interferometer (ISI), by modeling path length fluctuations observed in the interferometric paths to celestial objects and those in instrumental ground-based paths. The correlations between the stellar and ground-based path length fluctuations and the temporal statistics of those fluctuations are modeled on various timescales to constrain the vertical scales. A Kolmogorov-Taylor turbulence model with a finite outer scale was used to simulate ISI data. The simulation also included the white instrumental noise of the interferometer, aperture-filtering effects, and the data analysis algorithms. The simulations suggest that the path delay fluctuations observed in the 1992-1993 ISI data are largely consistent with being generated by refractivity fluctuations at two characteristic vertical scales: one extending to a height of 45 m above the ground, with a wind speed of about 1 m/ s, and another at a much higher altitude, with a wind speed of about 10 m/ s. The height of the lower layer is of the order of the dimensions of trees and other structures near the interferometer, which suggests that these objects, including elements of the interferometer, may play a role in generating the lower layer of turbulence. The modeling indicates that the high- attitude component contributes primarily to short-period (less than 10 s) fluctuations, while the lower component dominates the long-period (up to a few minutes) fluctuations. The lower component turbulent height, along with outer scales of the order of 10 m, suggest that the baseline dependence of long-term interferometric, atmospheric fluctuations should weaken for baselines greater than a few tens of meters. Simulations further show that there is the potential for improving the seeing or astrometric accuracy by about 30%-50% on average, if the path length fluctuations in the lower component are directly calibrated. Statistical and systematic effects induce an error of about 15 m in the estimate of the lower component turbulent altitude.

Treuhaft, Robert N.↗

Leonardo-BRDF: A New Generation Satellite Constellation

Instantaneous net radiation flux at the top of the atmosphere is one of the primary drivers of climate and global change. Since the dawn of the satellite era, great efforts and expense have gone into measuring this flux from single satellites and even (for a several-year period) from a constellation of three satellites called ERBE. However, the reflected solar flux is an angular and spectral integral over the so-called "BRDF" or Bidirectional Reflectance Distribution Function, which is the angular distribution of reflected solar radiation for each solar zenith angle and each wavelength. Previous radiation flux satellites could not measure instantaneous BRDF, so scientists have had to fall back on models or composites. Because their range of observed solar zenith angles was very limited due to sunsynchronous orbits, the resultant flux maps are too inaccurate to see the dynamics of radiation flux or to reliably correlate it with specific phenomena (hurricanes, biomass fires, urban pollution, dust outbreaks, etc.). Accuracy only becomes acceptable after monthly averaging, but this washes out almost all cause-and-effect information, further exacerbated by the lack of spectral resolution. Leonardo-BRDF is a satellite system designed to measure the instantaneous spectral BRDF using a formation of highly coordinated satellites, all pointing at the same Earth targets at the same time. It will allow scientists for the first time to assess the radiative forcing of climate due to specific phenomena, which is bound to be important in the ongoing debate about global warming and what is causing it. The formation is composed of two satellite types having, as instrument payloads, single highly-integrated miniature imaging spectrometers or radiometers. Two nearby "keystone" satellites anchor the formation and fly in static orbits. They employ wide field of view imaging spectrometers that are extremely light and compact. The keystone satellites are identical and can operate in alongtrack or cross-track mode, or anything in between, at ground command. This provides inherent system redundancy and cross-calibration capability. Several "wing-man" satellites in non-static orbits fly in formation up to 1000 km out from the keystone satellites to provide additional along- and cross-track angular sampling. They view the target(s) observed by the keystone satellites from different zenith and azimuth angles and are maneuverable within a limited range of zenith angle using thrusters, and within a large range of azimuth angle using clever orbit design. The wing-man satellites carry single miniature imaging radiometers with just a few wavelength bands in order to be lighter and more agile.

Esper, Jaime↗

Structure and Dynamics of the Polar Regions of Mars from MGS Topography and Gravity

The Mars Global Surveyor (MGS) spacecraft has been engaged in systematic mapping of Mars since insertion into Mars orbit in September, 1997. The objectives of the MGS mission are to globally map Mars as well as to quantify seasonal changes on the planet. MGS geophysical/geodetic observations of topography from the Mars Orbiter Laser Altimeter (MOLA) and gravity from the Radio Science investigation are providing significant new insights on both static and time-varying aspects of the polar regions of Mars. These observations have implications for polar processes on diurnal seasonal and climatic timescales. Thus far, MOLA has collected over 300 million precise measurements of Martian topography and cloud heights. The instrument has also provided measurements of the width of the backscattered optical pulse and of the 1064 nm reflectivity of the Martian surface and atmosphere. The along-track resolution of MOLA ground shots is approx. 300 m and the across-track spacing in the polar regions is a maximum of about four kilometers. The vertical accuracy of the topography is determined by the precision recovery of spacecraft orbits from the Radio Science investigation, which includes MOLA altimetry in the form of crossovers. This accuracy is currently approx. one meter. The gravity field is derived from X-band Doppler tracking with typical accuracy of 0.03 to 0.05 mm/s averaged over ten seconds. Current Mars gravity fields are to approximately degree and order 80 but are interpretable to the approximate degree and order 60 (spatial resolution < 180 km), which represents an estimate of the approximate coefficient limit of a field that can be produced without a power law constraint on the gravitational field inversion, which is commonly imposed for solution stability. Additional information is contained in the original extended abstract.

Zuber, Maria T.↗

CLARREO Cornerstone of the Earth Observing System: Measuring Decadal Change Through Accurate Emitted Infrared and Reflected Solar Spectra and Radio Occultation

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is one of four Tier 1 missions recommended by the recent NRC Decadal Survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to provide accurate, broadly acknowledged climate records that are used to enable validated long-term climate projections that become the foundation for informed decisions on mitigation and adaptation policies that address the effects of climate change on society. The CLARREO mission accomplishes this critical objective through rigorous SI traceable decadal change observations that are sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. These same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. For the first time CLARREO will make highly accurate, global, SI-traceable decadal change observations sensitive to the most critical, but least understood, climate forcings, responses, and feedbacks. The CLARREO breakthrough is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. The required accuracy levels are determined so that climate trend signals can be detected against a background of naturally occurring variability. Climate system natural variability therefore determines what level of accuracy is overkill, and what level is critical to obtain. In this sense, the CLARREO mission requirements are considered optimal from a science value perspective. The accuracy for decadal change traceability to SI standards includes uncertainties associated with instrument calibration, satellite orbit sampling, and analysis methods. Unlike most space missions, the CLARREO requirements are driven not by the instantaneous accuracy of the measurements, but by accuracy in the large time/space scale averages that are key to understanding decadal changes.

Sandford, Stephen P.↗

Aquarius Instrument and Salinity Retrieval

Aquarius has been designed to map the surface salinity field of the global ocean from space a parameter important for understanding ocean circulation and its relationship to climate and the global water cycle. Salinity is measured remotely from space by measuring the thermal emission from the ocean surface. This is done at the low frequency end of the microwave spectrum (e.g. 1.4 GHz) where the emission is sufficiently sensitive to changes in salinity to be detected with sophisticated radiometers. The goal is to monitor the seasonal and interannual variation of the large scale features of the surface salinity field in the open ocean by providing maps on a monthly basis with a spatial resolution of 150 km and an accuracy of 0.2 psu. These are challenging requirements that have led to some unique features of the instrument. These include: a) The addition of a co-located scatterometer to help provide a correction for roughness; b) The addition of a polarimetric channel (third Stokes parameter) to the radiometer to help correct for Faraday rotation; c) Asun-synchronous orbit with a 6 pm ascending equatorial crossing to minimize Faraday rotation and with the antennas looking away from the sun toward the nighttime side to minimize contamination by radiation from the sun; and d) An antenna designed to limit side lobes in the direction of rays from the sun. In addition, achieving the accuracy goal of 0.2 psu requires averaging over one month and to do this requires a highly stable radiometer. Aquarius has three separate radiometers that image in pushbroom fashion with the three antenna beams looking across track. The antenna is a 2.5-m diameter, offset parabolic reflector with three feed horns and the three beams are arranged to image with the boresight aligned to look across track, roughly perpendicular to the spacecraft heading and pointing away from the Sun. The three beams point at angles of theta = 25.8 deg., 33.8 deg. and 40.3 deg. with respect to the spacecraft nadir which correspond to local incidence angles at the surface of 28.7 deg., 37.8 deg. and 45.6 deg., respectively. The resolution of the three radiometer beams (axes of the 3dB ellipse) is: 76 x 94 km for the inner beam, 84 x 120 km for the middle beam to 96 x 156 km for the outer beam. Together they cover a swath of about 390 km. Aquarius will map the global ice-free ocean every 7-days from which monthly average composites will be derived. This will provide a snapshot of the mean field, as well as resolving the seasonal to interannual variations over the three-year baseline of the mission.

Le Vine, D. M.↗

Assessment of the SMAP Passive Soil Moisture Product

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

passive↗

Cross-Sensor Validation of the Optical Transient Detector (OTD)

Lightning data from the U.S. National Lightning Detection Network (NLDN) is used to perform preliminary validation of the satellite-based Optical Transient Detector (OTD). Sensor precision, accuracy, detection efficiency and biases of the deployed instrument are considered. We estimate the sensor to have, on average, better than 30 km spatial and 100 ms temporal accuracy. The detection efficiency for cloud-to-ground lightning is about 45-70%, slightly higher for intracloud lightning. There are only marginal day/night biases in the dataset, although 55 day averaging is required to remove sampling-based diurnal lightning cycle biases. The sensor detects statistically significant differences in the optical characteristics of intracloud, negative cloud-to-ground and positive cloud-to-ground lightning, although it cannot a priori determine flash types.

Boccippio, D. J.↗

Mapping the Daily Progression of Large Wildland Fires Using MODIS Active Fire Data

High temporal resolution information on burned area is a prerequisite for incorporating bottom-up estimates of wildland fire emissions in regional air transport models and for improving models of fire behavior. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product (MO(Y)D14) as input to a kriging interpolation to derive continuous maps of the evolution of nine large wildland fires. For each fire, local input parameters for the kriging model were defined using variogram analysis. The accuracy of the kriging model was assessed using high resolution daily fire perimeter data available from the U.S. Forest Service. We also assessed the temporal reporting accuracy of the MODIS burned area products (MCD45A1 and MCD64A1). Averaged over the nine fires, the kriging method correctly mapped 73% of the pixels within the accuracy of a single day, compared to 33% for MCD45A1 and 53% for MCD64A1.

Aqua↗

Evaluation of the procedure for separating barley from other spring small grains

The success of the Transition Year procedure to separate and label barley and the other small grains was assessed. It was decided that developers of the procedure would carry out the exercise in order to prevent compounding procedural problems with implementation problems. The evaluation proceeded by labeling the sping small grains first. The accuracy of this labeling was, on the average, somewhat better than that in the Transition Year operations. Other departures from the original procedure included a regionalization of the labeling process, the use of trend analysis, and the removal of time constraints from the actual processing. Segment selection, ground truth derivation, and data available for each segment in the analysis are discussed. Labeling accuracy is examined for North Dakota, South Dakota, Minnesota, and Montana as well as for the entire four-state area. Errors are characterized.

Magness, E. R.↗

Investigation of TM Band-to-band Registration Using the JSC Registration Processor

The JSC registration processor performs scene-to-scene (or band-to-band) correlation based on edge images. The edge images are derived from a percentage of the edge pixels calculated from the raw scene data, excluding clouds and other extraneous data in the scene. Correlations are performed on patches (blocks) of the edge images, and the correlation peak location in each patch is estimated iteratively to fractional pixel location accuracy. Peak offset locations from all patches over the scene are then considered together, and a variety of tests are made to weed out outliers and other inconsistencies before a distortion model is assumed. Thus, the correlation peak offset locations in each patch indicate quantitatively how well the two TM bands register to each other over that patch of scene data. The average of these offsets indicate the overall accuracies of the band-to-band registration. The registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. Band 4 images from both acquisitions were correlated and an rms error of a fraction of a pixel was routinely obtained.

Yao, S. S.↗

Grid Refinement Techniques for the 𝜸-Re𝜽𝒕 Transition Model in FUN3D

There has been an increased focus on the overall accuracy and grid convergence of Reynolds-averaged Navier-Stokes (RANS)-based transition models from the recent AIAA and NATO-AVT workshops. Even though satisfactory grid convergence could be achieved for simple two-dimensional flow configurations, it required mesh counts that are substantially larger than those used in typical applications. In this paper, we focus our efforts on understanding how the grid resolution and topology influences the accuracy and convergence of results by studying the Schubauer and Skramstad flat-plate configuration and the NLF-0416 airfoil at an angle of attack equal to five degrees using FUN3D, a second-order finite-volume code. By focusing on these cases, we can analyze both natural and separation-induced transition scenarios. Multiple grid refinement strategies are investigated. First, we determine the relative effectiveness of zonal streamwise refinement in the transition region within structured grids as an alternative to the costly option of globally uniform refinement of a baseline grid. We also complement this zonal technique by globally varying the wall-normal resolution keeping the streamwise resolution fixed. The zonal streamwise refinement can accurately model natural transition in a flat-plate boundary layer and separation-induced transition, but struggles to accurately model natural transition in airfoil flows. A series of unstructured prismatic grids that have similar node counts and viscous wall spacings as the structured hexahedral grids are also tested, and they do not achieve grid convergence until an extremely fine resolution. Last, we employ adjoint-based unstructured grid adaptation in FUN3D to natural and separation-induced transition on the NLF-0416 airfoil. The adjoint-based refinement process converges to the same solution as the baseline family of structured grids, but leads to smaller errors on coarser grids.

Grid Adaptation↗

Grid Refinement Techniques for the 𝜸-Re 𝜽 𝒕 Transition Model in FUN3D

There has been an increased focus on the overall accuracy and grid convergence of Reynolds-averaged Navier-Stokes (RANS)-based transition models from the recent AIAA and NATO-AVT workshops. Even though satisfactory grid convergence could be achieved for simple two-dimensional flow configurations, it required mesh counts that are substantially larger than those used in typical applications. In this paper, we focus our efforts on understanding how the grid resolution and topology influences the accuracy and convergence of results by studying the Schubauer and Skramstad flat-plate configuration and the NLF-0416 airfoil at an angle of attack equal to five degrees using FUN3D, a second-order finite-volume code. By focusing on these cases, we can analyze both natural and separation-induced transition scenarios. Multiple grid refinement strategies are investigated. First, we determine the relative effectiveness of zonal streamwise refinement in the transition region within structured grids as an alternative to the costly option of globally uniform refinement of a baseline grid. We also complement this zonal technique by globally varying the wall-normal resolution keeping the streamwise resolution fixed. The zonal streamwise refinement can accurately model natural transition in a flat-plate boundary layer and separation-induced transition, but struggles to accurately model natural transition in airfoil flows. A series of unstructured prismatic grids that have similar node counts and viscous wall spacings as the structured hexahedral grids are also tested, and they do not achieve grid convergence until an extremely fine resolution. Last, we employ adjoint-based unstructured grid adaptation in FUN3D to natural and separation-induced transition on the NLF-0416 airfoil. The adjoint-based refinement process converges to the same solution as the baseline family of structured grids, but leads to smaller errors on coarser grids.

Grid Adaptation↗

Dynamics of aircraft antiskid braking systems

A computer study was performed to assess the accuracy of three brake pressure-torque mathematical models. The investigation utilized one main gear wheel, brake, and tire assembly of a McDonnell Douglas DC-9 series 10 airplane. The investigation indicates that the performance of aircraft antiskid braking systems is strongly influenced by tire characteristics, dynamic response of the antiskid control valve, and pressure-torque response of the brake. The computer study employed an average torque error criterion to assess the accuracy of the models. The results indicate that a variable nonlinear spring with hysteresis memory function models the pressure-torque response of the brake more accurately than currently used models.

Tanner, J. A.↗

New Capabilities and Improvements to the High-Order Glenn Flux Reconstruction Code

The Glenn Flux Reconstruction (GFR) code is a computational fluid dynamics (CFD) code under development at NASA Glenn Research Center. GFR is based on the high-order flux reconstruction (FR) method and provides a large-eddy simulation (LES) capability that is both accurate and efficient for complex aeropropulsion flows. Three significant new capabilities have been added to the code that improve its performance and functionality. First, a variety of explicit Runge-Kutta methods, including some with adaptive time stepping, were added to GFR with two methods offering a 33% improvement in time-to-solution. Second, GFR can now utilize fully unstructured, mixed-element meshes to more easily facilitate the grid generation process for complex geometries. Finally, a rotating reference frame capability has been added to GFR for solving rotating turbomachinery problems. A selection of results demonstrating these new capabilities are presented in this work. The Taylor-Green vortex problem is used to verify the new unstructured capability by showing similar accuracy and resolution for all element types. LES of the Turbulent Heat Flux Phase III (THX3) experiment with comparison to another high-order LES code and a popular Reynolds-averaged Navier-Stokes (RANS) code demonstrates the accuracy of the code for complex aeropropulsion flows. Finally, LES of a spacecraft cabin ventilation fan shows the ability of GFR to efficiently establish a fan performance map and identify operating points for further analysis at high orders of accuracy.

High-Order Methods↗

New Capabilities and Improvements to the High-Order Glenn Flux Reconstruction Code

The Glenn Flux Reconstruction (GFR) code is a computational fluid dynamics (CFD) code under development at NASA Glenn Research Center. GFR is based on the high-order flux reconstruction (FR) method and provides a large-eddy simulation (LES) capability that is both accurate and efficient for complex aeropropulsion flows. Three significant new capabilities have been added to the code that improve its performance and functionality. First, a variety of explicit Runge-Kutta methods, including some with adaptive time stepping, were added to GFR with two methods offering a 33% improvement in time-to-solution. Second, GFR can now utilize fully unstructured, mixed-element meshes to more easily facilitate the grid generation process for complex geometries. Finally, a rotating reference frame capability has been added to GFR for solving rotating turbomachinery problems. A selection of results demonstrating these new capabilities are presented in this work. The Taylor-Green vortex problem is used to verify the new unstructured capability by showing similar accuracy and resolution for all element types. LES of the Turbulent Heat Flux Phase III (THX3) experiment with comparison to another high-order LES code and a popular Reynolds-averaged Navier-Stokes (RANS) code demonstrates the accuracy of the code for complex aeropropulsion flows. Finally, LES of a spacecraft cabin ventilation fan shows the ability of GFR to efficiently establish a fan performance map and identify operating points for further analysis at high orders of accuracy.

Direct Numerical Simulations↗

Tolerating failures of continuous-valued sensors

One aspect of fault tolerance in process control programs is the ability to tolerate sensor failure. A methodology for transforming a process control program that cannot tolerate sensor failures onto one that can is presented. Issues addressed include modifying specifications in order to accommodate uncertainty in sensor values and averaging sensor values in a fault tolerant manner. In addition, a hierarchy of sensor failure models is identified, and both the attainable accuracy and the run-time complexity of sensor averaging with respect to this hierarchy is discussed.

Marzullo, Keith↗

The difference between laboratory and in-situ pixel-averaged emissivity: The effects on temperature-emissivity separation

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a Japanese future imaging sensor which has five channels in thermal infrared (TIR) region. To extract spectral emissivity information from ASTER and/or TIMS data, various temperature-emissivity (T-E) separation methods have been developed to date. Most of them require assumptions on surface emissivity, in which emissivity measured in a laboratory is often used instead of in-situ pixel-averaged emissivity. But if these two emissivities are different, accuracies of separated emissivity and surface temperature are reduced. In this study, the difference between laboratory and in-situ pixel-averaged emissivity and its effect on T-E separation are discussed. TIMS data of an area containing both rocks and vegetation were also processed to retrieve emissivity spectra using two T-E separation methods.

Matsunaga, Tsuneo↗

Spatial land-use inventory, modeling, and projection/Denver metropolitan area, with inputs from existing maps, airphotos, and LANDSAT imagery

A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.

Tom, C.↗