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Selected information from the current Hubble Space Telescope (HST) science programs for the Guaranteed Time Observers (GTO's) and General Observers (GO's) is presented. Included are program abstracts, detailed listings of specific targets, and exposure information.
To take unit commitment (UC) decisions under uncertain load, most existing stochastic optimization (SO) frameworks adopt a generic representation of uncertainty. While load levels that materialize on a particular day are influenced by various covariates (such as the day of the week or temperature), SO frameworks typically disregard such side observations, wasting actionable information that could significantly enhance decision quality. Here, this article proposes a contextual SO (CSO) framework for UC under uncertain load, which can effectively exploit covariate observations in conjunction with a class of machine learning (ML) algorithms to improve the out-of-sample performance of UC decisions. It shows how three ML algorithms, adaptive boosting, gradient boosted trees, and extreme gradient boosting, can be used to this end, constituting the first application of these algorithms in any CSO framework. Using real-world data harvested from the New York ISO grid, we measure the out-of-sample performance of the framework in terms of total operation cost, shed load values, locational marginal prices, and total payments by the loads, against several benchmark methods proposed in the literature. The article has an online companion (Yurdakul et al.), wherein we present additional results and lay out further mathematical formulations used in this work.
In the spring of 1986 the EOSAT Company and NASA Headquarters organized a workshop to consider: (1) the potential value of space-acquired multiband thermal remote sensing in terrestrial research and commercial applications, and (2) the scientific and technological requirements for conducting such observations from the LANDSAT platform. The workshop defined the instrument characteristics of three types of sensors that would be needed to expand the use of thermal information for Earth observation and new commercial opportunities. The panels from two disciplines, geology and evapotranspiration/botany, along with the instrument panel, presented their recommendations to the workshop. The findings of these meetings are presented.
We have investigated the response of particles, in the energy range approximately 1-5000 MeV, to interplanetary shocks and coronal ejecta. Shocks can accelerate particles or cause decreases in particle densities. Ejecta cause decreases. Thus particle observations can provide information about solar wind disturbances. Of particular interest is that the boundaries of ejecta can often be more readily identified from approximately l GeV particle decrease observations than from most other phenomena associated with ejecta. We will discuss the properties of less energetic shocks and ejecta and compare them with those of the more energetic events which are normally discussed in the context of Forbush decreases, large proton events, etc. We use data from both Helios spacecraft and IMP 8 which allows some spatial variations to be studied.
We used speed discrimination tasks to measure the ability of observers to combine speed information from multiple stimuli distributed across space. We compared speed discrimination thresholds in a classical discrimination paradigm to those in an uncertainty/search paradigm. Thresholds were measured using a temporal two-interval forced-choice design. In the discrimination paradigm, the n gratings in each interval all moved at the same speed and observers were asked to choose the interval with the faster gratings. Discrimination thresholds for this paradigm decreased as the number of gratings increased. This decrease was not due to increasing the effective stimulus area as a control experiment that increased the area of a single grating did not show a similar improvement in thresholds. Adding independent speed noise to each of the n gratings caused thresholds to decrease at a rate similar to the original no-noise case, consistent with observers combining an independent sample of speed from each grating in both the added- and no-noise cases. In the search paradigm, observers were asked to choose the interval in which one of the n gratings moved faster. Thresholds in this case increased with the number of gratings, behavior traditionally attributed to an input bottleneck. However, results from the discrimination paradigm showed that the increase was not due to observers' inability to process these gratings. We have also shown that the opposite trends of the data in the two paradigms can be predicted by a decision theory model that combines independent samples of speed information across space. This demonstrates that models typically used in classical detection and discrimination paradigms are also applicable to search paradigms. As our model does not distinguish between samples in space and time, it predicts that discrimination performance should be the same regardless of whether the gratings are presented in two spatial intervals or two temporal intervals. Our last experiment largely confirmed this prediction.
We used speed discrimination tasks to measure the ability of observers to combine speed information from multiple stimuli distributed across space. We compared speed discrimination thresholds in a classical discrimination paradigm to those in an uncertainty/search paradigm. Thresholds were measured using a temporal two-interval forced-choice design. In the discrimination paradigm, the n gratings in each interval all moved at the same speed and observers were asked to choose the interval with the faster gratings. Discrimination thresholds for this paradigm decreased as the number of gratings increased. This decrease was not due to increasing the effective stimulus area as a control experiment that increased the area of a single grating did not show a similar improvement in thresholds. Adding independent speed noise to each of the n gratings caused thresholds to decrease at a rate similar to the original no-noise case, consistent with observers combining an independent sample of speed from each grating in both the added- and no-noise cases. In the search paradigm, observers were asked to choose the interval in which one of the n gratings moved faster. Thresholds in this case increased with the number of gratings, behavior traditionally attributed to an input bottleneck. However, results from the discrimination paradigm showed that the increase was not due to observers' inability to process these gratings. We have also shown that the opposite trends of the data in the two paradigms can be predicted by a decision theory model that combines independent samples of speed information across space. This demonstrates that models typically used in classical detection and discrimination paradigms are also applicable to search paradigms. As our model does not distinguish between samples in space and time, it predicts that discrimination performance should be the same regardless of whether the gratings are presented in two spatial intervals or two temporal intervals. Our last experiment largely confirmed this prediction.
Multi-spacecraft solar wind observations reveal that many interplanetary shocks deviate significantly from exact planarity on scale length of the magnetospheric cross section. A number of different IP shock observations with four spacecraft will be presented to demonstrate quantitatively the angular deviations between shock normals obtained from 4-spacecraft methods, using only the time and position information of shock observations but assuming a exactly planar geometry, and those obtained from a non-linear least squares fitting of the "Rankine-Hugoniot" conservation equations at each spacecraft. Moreover, the curvature of the shock fronts is strongly related to its driver, typically magnetic clouds. It will be demonstrated that small and slower moving magnetic clouds drive shocks with significantly more irregular surface geometries.
The decomposition of solar oscillations into their constituent normal modes requires a knowledge of both the spatial and temporal variation of the perturbation to the Sun's surface. The task is especially difficult when only limited spatial information is available. Observations of the limb darkening function, for example, are probably sensitive to too large a number of modes to permit most of the modes to be identified in a power spectrum of measurements at only a few points on the limb, unless the results are combined with other data. A procedure was considered by which the contributions from quite small groups of modes to spatially well resolved data obtained at any instant can be extracted from the remaining modes. Combining these results with frequency information then permits the modes to be identified, at least if their frequencies are low enough to ensure that modes of high degree do not contribute substantially to the signal.
X-ray emissions from Jupiter have been observed for over 20 years. Jovian x-ray emissions are associated with high-latitude aurora and with solar fluorescence and/or an energetic particle source at low-latitudes as identified by past Einstein and ROSAT observations. Enhanced auroral x-rays were also observed to be associated with the impact of Comet Shoemaker-Levy 9. The high-latitude x-ray emissions are best explained by energetic sulfur and oxygen ion precipitation from the Jovian magnetosphere, a suggestion that has been confirmed by recent Chandra ACIS observations. Exciting new information about Jovian x-ray emissions has been made possible with Chandra's High Resolution Camera. We report here for the first time the detection of a forty minute oscillation associated with the Jovian x-ray aurora. With the help of ultraviolet auroral observations from Hubble Space Telescope, we pinpoint the auroral mapping of the x-rays and provide new information on the x-ray source mechanism.
The decomposition of solar oscillations into their constituent normal modes requires a knowledge of both the spatial and temporal variation of the perturbation to the sun's surface. The task can be especially difficult when only limited spatial information is available. Observations of the limb-darkening function, for example, are probably sensitive to too large a number of modes to permit most of the modes to be identified in a power spectrum of measurements at only a few points on the limb, unless the results are combined with other data. In this paper a procedure is considered by which the contributions from quite small groups of modes to spatially well resolved data obtained at any instant can be extracted from the remaining modes. Combining these results with frequency information then permits the modes to be identified, at least if their frequencies are low enough to ensure that modes of high degree do not contribute substantially to the signal.
Information about the physical parameters of neutron stars is obtained from pulsar observations. The energy balance of the Crab nebula and the Vela X remnant allows derivation of limits for the masses of the Crab and Vela pulsars. Glitch observations provide further clues on the masses of these two pulsars. The degree of confidence in the derived numbers is pointed out. The possibility of observing neutron stars in binary systems as pulsating X-ray sources is discussed. The importance of observing redshifted gamma ray lines from the surface of neutron stars, and thus directly measuring either individual or statistical properties of these objects is pointed out.
Information about the physical parameters of neutron stars is obtained from pulsar observations. The energy balance of the Crab Nebula and the Vela X remnant allows one to derive limits for the masses of the Crab and Vela pulsars. Glitch observations provide further clues on the masses of these two pulsars. The degree of confidence with which one should believe the derived numbers is pointed out. The possibility of observing neutron stars in binary systems as pulsating X-ray sources is discussed. Finally, the importance of observing redshifted gamma ray lines from the surface of neutron stars, and thus directly measuring either individual or statistical properties of these objects, is pointed out.
Assimilation of precipitation in a global modeling system poses a special challenge in that the observation operators for precipitation processes are highly nonlinear. In the variational approach, substantial development work and model simplifications are required to include precipitation-related physical processes in the tangent linear model and its adjoint. An ensemble based data assimilation algorithm "Maximum Likelihood Ensemble Smoother (MLES)" has been developed to explore the ensemble representation of the precipitation observation operator with nonlinear convection and large-scale moist physics. An ensemble assimilation system based on the NASA GEOS-5 GCM has been constructed to assimilate satellite precipitation data within the MLES framework. The configuration of the smoother takes the time dimension into account for the relationship between state variables and observable rainfall. The full nonlinear forward model ensembles are used to represent components involving the observation operator and its transpose. Several assimilation experiments using satellite precipitation observations have been carried out to investigate the effectiveness of the ensemble representation of the nonlinear observation operator and the data impact of assimilating rain retrievals from the TMI and SSM/I sensors. Preliminary results show that this ensemble assimilation approach is capable of extracting information from nonlinear observations to improve the analysis and forecast if ensemble size is adequate, and a suitable localization scheme is applied. In addition to a dynamically consistent precipitation analysis, the assimilation system produces a statistical estimate of the analysis uncertainty.
In November 2020, Hurricanes Eta and Iota hit Central America within weeks of each other, causing severe flooding, landslides, and widespread damage. NASA DEVELOP partnered with Comité Regional de Recursos Hidráulicos (CRRH), Centro de Coordinación para la Prevención de los Desastres en América Central y República Dominicana (CEPREDENAC), and Sistema de la Integración Centroamericana (SICA) to better understand how flooding throughout Central America has impacted and will continue to affect communities, focusing on sites in Guatemala, Honduras, El Salvador, Belize, Nicaragua, western Panama, and eastern Costa Rica from January 2015 to October 2021. The team utilized surface reflectance data from Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS), and Terra Moderate Resolution Imaging Spectroradiometer (MODIS). This project also utilized backscatter data from Sentinel-1 C-band Synthetic Aperture Radar (C-SAR) and elevation data from the Shuttle Radar Topography Mission (SRTM). Incorporating these Earth observations in NASA SERVIR’s Hydrologic Remote Sensing Analysis for Floods (HYDRAFloods) tool run on Google Earth Engine (GEE), the team produced historical surface water maps, a case study analysis of the two hurricanes, and a code tutorial. These results indicated that surface water increased in priority sites from 2015 to 2021, optical and SAR imagery detected similar flood patterns and extent after the hurricanes, and rainfall was concentrated on the east coast of the region. These products allow partners to make informed decisions around flooding preparation and disaster mitigation.
This study highlights hyperspectral infrared observations from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) collected as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) deployment on the icebreaker RV Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. The ARM M-AERI directly measures the infrared radiance emission spectrum between 520 cm –1 and 3000 cm –1 (19.2–3.3 μm) at 0.5 cm –1 spectral resolution. These ship-based observations provide a valuable set of radiance data for the modeling of snow/ice infrared emission as well as validation data for the assessment of satellite soundings. Remote sensing using hyperspectral infrared observations provides valuable information on sea surface properties (skin temperature and infrared emissivity), near-surface air temperature, and temperature lapse rate in the lowest kilometer. Comparison of the M-AERI observations with those from the DOE ARM meteorological tower and downlooking infrared thermometer are generally in good agreement with some notable differences. Operational satellite soundings from the NOAA-20 satellite were also assessed using ARM radiosondes launched from the RV Polarstern and measurements of the infrared snow surface emission from the M-AERI showing reasonable agreement.
Earth- and space-based observations provide synergistic information for space mission encounters by providing data over longer timescales. at different wavelengths and using techniques that are impossible with an in situ flyby. We report here such observations in support of the EPOXI spacecraft flyby of comet 103P (Hartley 2. The nucleus is small and dark, and exhibited a very rapidly changing rotation period. Prior to the onset of activity, the period was approximately 16.4 hr. Starting in 2010 August the period changed from 16.6 hr to near 19 hr in December. With respect to dust composition, most volatiles and carbon and nitrogen isotope ratios, the comet is similar to other Jupiter-family comets. What is unusual is the dominance of CO2-driven activity near perihelion, which likely persists out to aphelion. Near perihelion the comet nucleus was surrounded by a large halo of water-ice grains that contributed significantly to the total water production.
Geodetic information is presented for NASA tracking stations and observation stations in the NASA geodetic satellites program. A geodetic data sheet is provided for each station, giving the position of the station and describing briefly how it was established. Geodetic positions and geocentric coordinates of these stations are tabulated on local or major geodetic datums, and on selected world geodetic systems when available information permits.
Localized, correlated biases exist in OCO-2 (Orbiting Carbon Observatory-2) data. These biases do not improve with averaging. These have been noted by O'Dell (various OCO-2 telecons), Worden (2017), Kulawik (2018). We propose to utilize information from adjacent observations to reduce this bias. This works on the assumption that grouping the observations allows the system to find a better, global minimum. Pooling adjacent observations could allow more accurate characterization of interferents (e.g. retrieving additional albedo parameters), reducing entanglement with CO2.