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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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NASA NTRS1984

Voyager photometry of Rhea, Dione, Tethys, Enceladus and Mimas

Voyager imaging observations provide new photometric data on Saturn's satellites at large phase angles (up to 133 deg in the case of Mimas) not observable from earth. Significant new results include the determination of phase integrals ranging from 0.7 in the case of Rhea to 0.9 for Enceladus. For Enceladus an average geometric albedo 1.04 and a Bond albedo of 0.9 are found. The data indicate an orbital lightcurve with an amplitude of 0.2 mag, the trailing side being the brighter. For Mimas, the lightcurve amplitude is probably less than 0.1 mag. The value of the geometric albedo of Mimas reported here, is definitely higher than the currently accepted value of about 0.5. For Dione, the Voyager data show a well-defined orbital lightcurve of amplitude about 0.6 mag, with the leading hemisphere brighter than the trailing one.

Buratti, B.↗
NASA NTRS2005

Expected Constraints on Rhea's Interior from Cassini

We model the interior of Rhea based on observational constraints and the results from geodynamical models available in the literature. Ten main types of models are defined, depending on the presence or absence of a high-pressure ice layer (ice II), and the extent of separation of the rock component from the volatiles. We present degree-two gravity components computed for each of these models in order to assess which properties of the interior are likely to be inferred from Cassini radio science measurements scheduled on November 26, 2005.

Castillo, J. C.↗
NASA NTRS2020

Kenya Food Security & Agriculture II: Utilizing NASA Earth Observations to Enhance Drought Warning Systems and Develop Capacity to Use the RHEAS Model in Kenya

Twenty-three counties in Kenya experience frequent drought, which damages agricultural productivity and threatens the health and well being of millions. NASA DEVELOP partnered with NASA SERVIR, the Regional Centre for Mapping of Resources for Development (RCMRD) and Kenya’s National Drought Management Authority (NDMA) to enhance drought-detection capacity using NASA Earth observations. Currently, the NDMA publishes monthly Early Warning Bulletins with drought conditions for each arid or semi-arid county in Kenya. These bulletins utilize the Vegetation Condition Index (VCI) from the Moderate Resolution ImagingSpectroradiometer (MODIS) as well as a variety of biophysical, social and economic drought indicators, but do not allow for advanced forecasting. To improve drought-monitoring capabilities, the team created a Combined Drought Indicator (CDI) using the Regional Hydrologic Extremes Assessment System (RHEAS) model and data from Aqua and Terra MODIS and the National Centers for Environmental Prediction. The CDI combined precipitation anomalies, soil moisture anomalies, evaporative stress, and VCI according to weights determined by principal component analysis. To evaluate the performance of the CDI across Kenya, the team compiled a dataset of drought events from historical reports and the NDMA’s records. Results suggested that the CDI detected drought earlier thanVCI alone. However, more validation is needed to ensure that the CDI accurately and consistently detects drought earlier than current warning systems. In order to better understand the behavior of individual indices and the potential for earlier drought detection, the team also conducted a time-lag analysis. The team found that VCI responds to drought, on average, one month later than most other indices included in the CDI, suggesting that incorporating additional indices could improve early drought warning systems in Kenya.

Food Security & Agriculture↗
NASA NTRS2020

Kenya Food Security & Agriculture II: Utilizing NASA Earth Observations to Enhance Drought Warning Systems and Develop Capacity to Use the RHEAS Model in Kenya

Twenty-three counties in Kenya experience frequent drought, which damages agricultural productivity and threatens the health and well being of millions. NASA DEVELOP partnered with NASA SERVIR, the Regional Centre for Mapping of Resources for Development (RCMRD) and Kenya’s National Drought Management Authority (NDMA) to enhance drought-detection capacity using NASA Earth observations. Currently, the NDMA publishes monthly Early Warning Bulletins with drought conditions for each arid or semi-arid county in Kenya. These bulletins utilize the Vegetation Condition Index (VCI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as a variety of biophysical, social and economic drought indicators, but do not allow for advanced forecasting. To improve drought-monitoring capabilities, the team created a Combined Drought Indicator (CDI) using the Regional Hydrologic Extremes Assessment System (RHEAS) model and data from Aqua and Terra MODIS and the National Centers for Environmental Prediction.The CDI combined precipitation anomalies, soil moisture anomalies, evaporative stress, and VCI according to weights determined by principal component analysis. To evaluate the performance of the CDI across Kenya, the team compiled a dataset of drought events from historical reports and the NDMA’s records. Results suggested that the CDI detected drought earlier than VCI alone. However, more validation is needed to ensure that the CDI accurately and consistently detects drought earlier than current warning systems. In order to better understand the behavior of individual indices and the potential for earlier drought detection, the team also conducted a time-lag analysis. The team found that VCI responds to drought, on average, one month later than most other indices included in the CDI, suggesting that incorporating additional indices could improve early drought warning systems in Kenya.

Food Security & Agriculture↗
NASA NTRS2006

Interiors of Enceladus and Rhea

Measurement method and data set: Gravity field parameters determined by means of range rate measurements over multiple arcs across flyby. Optical imaging not required when reliable a priori estimates of spacecraft state vector are available. Interior of Enceladus: Density of 1605 +/-14 kg/cu m, higher than pre-Cassini estimates, requires a substantial amount of rock to warmer interior to enhance likelihood of differentiation of water from rock-metal. Assume no porosity. Assuming Io s mean density for the rock-metal component, one finds its fractional mass to be 0.52+/-0.06. There is evidence that Enceladus may be differentiated: a) Areas devoid of craters must be geologically young. b) Systems of ridges, fractures, and groove indicate that the surface has been tectonically altered. c) Viscous relaxation of craters has occurred, and d) The plumes near the South pole indicate venting of subsurface volatiles.

gravity fields↗
NASA NTRS2006

Cassini RADAR Observations of Enceladus, Tethys, Dione, Rhea, Iapetus, Hyperion, and Phoebe

The Cassini mission includes 34 investigations of Saturn's icy satellites by the 2.2-cm-wavelength (13.8-GHz) RADAR instrument, operating both as a scatterometric radar and a passive radiometer. These measurements are sensitive to near-surface electrical properties and structure at scales about six times smaller than the only groundbased radar wavelength available to study the satellites (13 cm) and 22 times longer than the millimeter wavelengths at the limit of Cassini's Composite Infrared Spectrometer (CIRS). Here we present Cassini's first radar results for seven of the satellites.

Saturn↗
NASA NTRS2023

Evaluation of a Regional Crop Model Implementation for Sub-National Yield Assessments in Kenya

CONTEXT: Cropping system models can be used to both assess regional food security and to monitor and predict agricultural drought. Agriculture in Kenya is extremely important to both the economy and food security of the country. OBJECTIVE: This study evaluated a regional implementation of a widely used crop model, the Decision Support System for Agrotechnology Transfer (DSSAT), within a coupled modeling framework, the Regional Hydrologic Extremes Assessment System (RHEAS), over Kenya. The goal of this study was to assess the ability of RHEAS to simulate the annual variability of maize yields at the county level and evaluate the uncertainty inherent in the model and inputs. METHODS: The RHEAS system implements a stochastic ensemble approach to account for field scale variabilities in crop management practices and underlying soil and weather conditions. Satellite-derived datasets were used to evaluate the land surface component of the system and seasonally disaggregated yield for 5 years was used to assess the performance of the cropping system model. RESULTS AND CONCLUSIONS: The median correlation between RHEAS and satellite-derived soil moisture and evapotranspiration estimates were 0.78, and 0.51, respectively, indicating that the model is able to capture the key drivers of the hydrological budget. Overall, RHEAS simulated yearly yield variations with a median correlation of 0.7 with reported yields, with the best performance in the short rains season. However, across both seasons, the RHEAS model was positively biased on the order of ~1.6 MT/ha. The overall median unbiased RMSE was 0.66 MT/ha. The RHEAS system shows skill at simulating extreme departures in anomalies, and a majority of the time (62.5%) the reported yields fall within the interquartile range of the simulations. SIGNIFICANCE: One of the most important areas of improvement for the next generation of agricultural data and models is to better understand and communicate the inherent uncertainties. This is especially critical in data-limited regions. Here we present a modeling system and its implementation that begins to address these concerns. We demonstrate the ability to simulate broad trends in yields at the county level for sub-annual yields with skills that commensurate previous national/annual level studies.

Crop model↗
NASA NTRS2018

Comparisons of Two Spatial Implementations of a Crop Model Using Remotely Sensed Observations over Southeastern United States

Global food security is one of the most pressing issues of the current century, particularly for developing nations. Agricultural simulation models can be a key component in testing new technologies, seeds and cultivars etc. However, inaccurate input information, model related errors and the mode of implementation can also add to model uncertainties. In this study, the crop model is implemented in two separate fashions: a)gridded (GriDSSAT model) and b) using random spatial ensembles (RHEAS model). This is done in the Southeastern US to evaluate and understand the modelperformance over a region data availabilities. Once the model performance is assessed, multiple satellite based earth observation parameters such as soil moisture, vegetation index etc. can be assimilated into crop models to reduce input and model related uncertainties particularly in data limited regions. In this study, the National Agricultural Statistical Services (NASS) reported yield data at county levels are used for comparison andvalidation purposes. The GriDSSAT model estimation of corn yields in comparison with the reported NASS yields showed an overall RMSD of nearly 3720 (kg/ha) whereas RMSD for the RHEAS model implementation was 3550 (kg/ha). Overall the GriDSSAT model had negative bias of nearly 2400 kg/ha (except for 2013) while RHEAS had a slight positive bias of 400 kg/ha (approx.).

SERVIR↗
NASA NTRS1975

Commensurabilities of satellites' apsidal precession periods

The orientation of the major axis of Saturn's satellite Rhea librates about alignment with Titan's major axis. This behavior is a result of Titan's gravitational influence on Rhea. Similar effects may be important in the Uranian satellite system if they are enhanced by commensurabilities of apsidal precession periods. Extensive observations will be required if this possibility is to be confirmed. The effects of possible stable alignments have not been included in past analyses of the motions of Uranus' satellites, so the results of those studies should be accepted only tentatively.

Greenberg, R.↗
NASA NTRS1981

Saturn gravity results obtained from Pioneer 11 tracking data and earth-based Saturn satellite data

Improved gravity coefficients for Saturn, its satellites and rings are calculated on the basis of a combination of Pioneer 11 spacecraft Doppler tracking data and earth-based determinations of Saturn natural satellite apse and node rates. Solutions are first obtained separately from the coherent Doppler tracking data obtained for the interval from August 20 to September 4, surrounding the time of closest approach, with the effects of solar plasma on radio signal propagation taken into account, and from secular rates for Mimas, Enceladus, Tethys, Dione, Rhea and Titan determined from astrometric data by Kozai (1957, 1976) and Garcia (1972). Combination of the data by the use of the Pioneer solution and corresponding unadjusted covariance matrix as a priori information for a secular rate analysis results in values for the total ring mass of essentially zero at a standard error level of 1.7 x 10 to the -6th Saturn masses, a ratio of solar mass to that of the Saturn system of 3498.09 + or - 0.22, masses of Rhea, Titan and Iapetus of 4.0 + or - 0.9, 238.8 + or - 3, and 3.4 + or - 1.3 x 10 to the -6th Saturn masses, respectively, and second and fourth zonal harmonics of 16,479 + or - 18 and -937 + or - 38, respectively. The harmonic coefficients are noted to be important as boundary conditions in the modeling of the Saturn interior.

Null, G. W.↗