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The ground based phase control concept was studied as an alternative approach to the reference SPS phase control system. The details of the ground based phase control system study are documented. The coherent multiple tone technique used for the ground based phase measurement waveform design and phase control system is summarized.
Ground based optical observation of raylike artificial auroras produced by rocket-borne accelerator generated electron beams, using image orthicon TV system
Ground-based observations of the evening zodiacal light are used to derive a table of zodiacal light brightnesses at spatial resolutions as small as 0.5 deg in differential ecliptic longitude and 1.0 deg in ecliptic latitude. Significant differences are found in the brightness distribution above and below the ecliptic plane. Attention is given to a feature found in the brightness at all ecliptic latitudes, between differential ecliptic longitudes 39 deg and 42 deg.
Ground-based photoelectric photometry in b, y, and the 6190 and 7250 A methane-bands, as well as spectrum scans of the methane 6190 A band and CCD images at 6190 and 8900 A, were obtained for Neptune during Voyager 2's approach of that planet on August 24, 1989. Photometric variations are presently correlated with the disk transit of bright planetary features, and the changes in feature distribution and brightness noted in the results are evaluated for implications bearing on long-term variability. It is suggested that the long-term secular variation is related to a slow change in a size of location of both the bright companion and the Great Dark Spot.
Ground-based spectral characteristics of fir wave damage and an analysis of calibrated FLI data acquired along the same fir wave utilized for the in situ measurements are presented. Derivative curve data were produced from both in situ and FLI reflectance measurements for the red edge spectral region for birch and for various portions of a fir wave. The results suggested that with proper atmospheric correction of airborne imaging spectrometer data sets, the derivative curve approach will provide an accurate means of assessing red edge parameters, and that such data will permit identification of specific types of forest damage on the basis of spectral fine features.
Ground-based studies of soot processes in laminar flames proceeded in two phases, considering laminar premixed flames and laminar diffusion flames, in turn. The test arrangement for laminar premixed flames involved round flat flame burners directed vertically upward at atmospheric pressure. The test arrangement for laminar jet diffusion flames involved a round fuel port directed vertically upward with various hydrocarbon fuels burning at atmospheric pressure in air. In both cases, coflow was used to prevent flame oscillations and measurements were limited to the flame axes. The measurements were sufficient to resolve soot nucleation, growth and oxidation rates, as well as the properties of the environment needed to evaluate mechanisms of these processes. The experimental methods used were also designed to maintain capabilities for experimental methods used in corresponding space-based experiments. This section of the report will be limited to consideration of flame structure for both premixed and diffusion flames.
Current ground-based cosmological surveys, such as the Dark Energy Survey (DES), are predicted to discover thousands of galaxy-scale strong lenses, while future surveys, such as the Vera Rubin Observatory Legacy Survey of Space and Time (LSST) will increase that number by 1-2 orders of magnitude. The large number of strong lenses discoverable in future surveys will make strong lensing a highly competitive and complementary cosmic probe. To leverage the increased statistical power of the lenses that will be discovered through upcoming surveys, automated lens analysis techniques are necessary. We present two Simulation-Based Inference (SBI) approaches for lens parameter estimation of galaxy-galaxy lenses. We demonstrate the successful application of Neural Posterior Estimation (NPE) to automate the inference of a 12-parameter lens mass model for DES-like ground-based imaging data. We compare our NPE constraints to a Bayesian Neural Network (BNN) and find that it outperforms the BNN, producing posterior distributions that are for the most part both more accurate and more precise; in particular, several source-light model parameters are systematically biased in the BNN implementation.
Ground-based optical telescopes are seriously affected by atmospheric turbulence induced aberrations. Understanding properties of these aberrations is important both for instrument design and image restoration method development. Because the point-spread function can reflect performance of the whole optic system, it is appropriate to use the point-spread function to describe atmospheric turbulence induced aberrations. Assuming point-spread functions induced by the atmospheric turbulence with the same profile belong to the same manifold space, we propose a nonparametric point-spread function—PSF–NET. The PSF–NET has a cycle convolutional neural network structure and is a statistical representation of the manifold space of PSFs induced by the atmospheric turbulence with the same profile. Testing the PSF–NET with simulated and real observation data, we find that a well trained PSF–NET can restore any short exposure images blurred by atmospheric turbulence with the same profile. Besides, we further use the impulse response of the PSF–NET, which can be viewed as the statistical mean PSF, to analyze interpretation properties of the PSF–NET. We find that variations of statistical mean PSFs are caused by variations of the atmospheric turbulence profile: as the difference of the atmospheric turbulence profile increases, the difference between statistical mean PSFs also increases. The PSF–NET proposed in this paper provides a new way to analyze atmospheric turbulence induced aberrations, which would benefit the development of new observation methods for ground-based optical telescopes.
The ground-based network that has been in existence for several decades is described. Attention is given to two basic questions, namely the way in which monthly satellite analyses compare with those from the ground-based network and the way in which the trends from the satellite and ground-based data compare. Synoptic analyses of total ozone for December 1970 are compared with a subjective analysis of the ground-based network and an objective backscatter ultraviolet (BUV) analysis. It is found that the BUV analysis is the more consistent of the two. Considering monthly analyses for September 1970, satellite and ground-based data are found to agree quite well. In considering the question of trend determination by the ground-based versus the satellite systems, attention is given to the sources of error in the satellite system. The principal sources of error in BUV analysis are thought to be calibration drift with time and the fact that, over the lifetime of the satellite spacecraft, power limitations result in a decrease in the number of data points per month, possibly with significant gaps in the coverage.
Ground-based instruments cannot directly measure solar irradiance variability at the 0.1% level at which it occurs because of the earth's atmosphere. However, many forms of ground-based solar observations correlate well with solar irradiance variations, and this fact has been used to construct facular-sunspot models which can explain about 90% of the variance of total solar irradiance as observed by spacecraft radiometers. It is not yet clear whether remaining discrepancies are observational or require additional sources in the model. This paper is a selective review of the current status of the use of ground-based data to understand spacecraft observations of solar irradiance and to apply this understanding to periods before space-based measurements were available. New results from the extension of the histogram analysis of NASA/NSO spectromagnetograph observations (Jones et al., 2000, ApJ529, 1070) to the period from Nov. 1992 to Sep. 2000 are reported which confirm that strong mixed polarity magnetic regions (quiet network) are not significantly correlated with total solar irradiance and which show an unexplained linear trend in the residuals of a multiple regression.
Current and future ground-based cosmological surveys, such as the Dark Energy Survey (DES), and the Vera Rubin Observatory Legacy Survey of Space and Time (LSST), are predicted to discover thousands to tens of thousands of strong gravitational lenses. The large number of strong lenses discoverable in future surveys will make strong lensing a highly competitive and complementary cosmic probe. However, conventional lens modeling techniques are unable to scale up to the sheer number of lenses that will be discovered through upcoming surveys. Therefore, the use of automated lens analysis techniques is necessary. We demonstrate that machine learning methods can be used to automate the inference of informative model posteriors of strong lensing systems in ground-based surveys with credible uncertainty estimation. We present two Simulation-Based Inference (SBI) approaches for lens parameter estimation of galaxy-galaxy lenses. We demonstrate applications of Neural Posteriors Estima tors (NPEs) and Bayesian Neural Network (BNNs) to automate the inference of a 12-parameter lensing system for DES-like ground-based imaging data. We apply a suite of diagnostics (e.g., posterior coverage and SBC) to validate the performance of our methods. We find that NPEs outperform the BNN, producing posterior distributions that are for the most part both more accurate and more precise; in particular, several source-light model parameters are systematically biased in the BNN implementation.
The ASTROCULTURE(trademark) plant growth unit flown as part on the STS-63 mission in February 1995, represented the first time plants were flown in microgravity in a enclosed controlled environment plant growth facility. In addition to control of the major environmental parameters, nutrients were provided to the plants with the ZEOPONICS system developed by NASA Johnson Space Center scientists. Two plant species were included in this space experiment, dwarf wheat (Triticum aestivum) and a unique mustard called "Wisconsin Fast Plants" (Brassica rapa). Extensive post-flight analyses have been performed on the plant material and it has been concluded that plant growth and development was normal during the period the plants were in the microgravity environment of space. However, adequate plant growth and development control data were not available for direct comparisons of plant responses to the microgravity environment with those of plants grown at 1 g. Such data would allow for a more complete interpretation of the extent that microgravity affects plant growth and development.
We report the diurnal and semi-diurnal cycle of precipitation simulated from CMIP6 models during 1996-2005 are evaluated globally between 60°S and 60°N, as well as at ten selected locations representing three categories of diurnal cycle of precipitation: (1) afternoon precipitation over land, (2) early morning precipitation over ocean, and (3) nocturnal precipitation over land. Three satellite-based and two ground-based rainfall products are used to evaluate the climate models. Globally, the ensemble mean of CMIP6 models shows a diurnal phase of 3 to 4 hours earlier over land and 1 to 2 hours earlier over ocean, when compared with the latest satellite products. These biases are in line with what were found in previous versions of climate models but reduced compared to the CMIP5 ensemble mean. Analysis at the selected locations complimented with in-situ measurements further reinforces these results. Several CMIP6 models have shown a significant improvement in the diurnal cycle of precipitation compared to their CMIP5 counterparts, notably on delaying afternoon precipitation over land. This can be attributed to the use of more sophisticated convective parameterizations. Most models are still unable to capture the nocturnal peak associated with elevated convection and propagating mesoscale convective systems, with a few exceptions that allow convection to be initiated above the boundary layer to capture nocturnal elevated convection. We also quantify an encouraging consistency between the satellite- and ground-based precipitation measurements despite differing spatiotemporal resolutions and sampling periods, which provides confidence in using them to evaluate the diurnal and semi-diurnal cycle of precipitation in climate models.
The effects of atomic oxygen on boron nitride (BN) and silicon nitride (Si3N4) were evaluated in a low Earth orbit (LEO) flight experiment and in a ground based simulation facility. In both the inflight and ground based experiments, these materials were coated on thin (approx. 250A) silver films, and the electrical resistance of the silver was measured in situ to detect any penetration of atomic oxygen through the BN and Si3N4 materials. In the presence of atomic oxygen, silver oxidizes to form silver oxide, which has a much higher electrical resistance than pure silver. Permeation of atomic oxygen through BN, as indicated by an increase in the electrical resistance of the silver underneath, was observed in both the inflight and ground based experiments. In contrast, no permeation of atomic oxygen through Si3N4 was observed in either the inflight or ground based experiments. The ground based results show good qualitative correlation with the LEO flight results, indicating that ground based facilities such as the one at Los Alamos National Lab can reproduce space flight data from LEO.
The spatiotemporal sampling differences between ground-based and satellite lidar data can contribute to significant errors for direct measurement comparisons. Improvement in sample correspondence is examined by the use of radiosonde wind velocity to vary the time average in ground-based lidar data to spatially match coincident satellite lidar measurements. Results are shown for the 26 February 2004 GLAS/ICESat overflight of a ground-based lidar stationed at NASA GSFC. Statistical analysis indicates that improvement in signal correlation is expected under certain conditions, even when a ground-based observation is mismatched in directional orientation to the satellite track.
The Skylab Ground-Based Astronomy Program (SGAP) was conducted to enhance the data base of solar physics obtained during the Apollo Telescope Mount (ATM) mission flown in conjunction with the Skylab orbital station. Leading solar physicists from various observatories obtained data from the ground at the same time that orbital data were being acquired by ATM. The acquisition of corollary solar data from the ground simultaneously with the ATM orbital observations helped to provide a broader basis for understanding solar physics by increasing spectral coverage and by the use of additional sophisticated instruments of various types. This report briefly describes the individual tasks and the associated instrumentation selected for this ground-based program and contains as appendices, the final reports from the Principal Investigators.
Ground-based high-power CW lasers can be used to beam power to photovoltaic receivers in space that furnish electricity to space vehicles; this energy can also be used to power electric-propulsion orbital transfer vehicles. An account is presently given of the anticipated requirements for the pulsed FEL lasers, large adaptive optics, photovoltaic receivers, and high specific impulse electrical propulsion. Preliminary system analysis results are presented.
Ground-based Global Positioning System (GPS) measurements of ionospheric Total Electron Content (TEC) show variations consistent with atmospheric internal gravity waves caused by ocean tsunamis following recent seismic events, including the Tohoku tsunami of March 11, 2011. We observe fluctuations correlated in time, space, and wave properties with this tsunami in TEC estimates processed using JPL's Global Ionospheric Mapping Software. These TEC estimates were band-pass filtered to remove ionospheric TEC variations with periods outside the typical range of internal gravity waves caused by tsunamis. Observable variations in TEC appear correlated with the Tohoku tsunami near the epicenter, at Hawaii, and near the west coast of North America. Disturbance magnitudes are 1-10% of the background TEC value. Observations near the epicenter are compared to estimates of expected tsunami-driven TEC variations produced by Embry Riddle Aeronautical University's Spectral Full Wave Model, an atmosphere-ionosphere coupling model, and found to be in good agreement. The potential exists to apply these detection techniques to real-time GPS TEC data, providing estimates of tsunami speed and amplitude that may be useful for future early warning systems.