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NASA NTRS2007

Benefits Derived From Laser Ranging Measurements for Orbit Determination of the GPS Satellite Orbit

While navigation systems for the determination of the orbit of the Global Position System (GPS) have proven to be very effective, the current research is examining methods to lower the error in the GPS satellite ephemerides below their current level. Two GPS satellites that are currently in orbit carry retro-reflectors onboard. One notion to reduce the error in the satellite ephemerides is to utilize the retro-reflectors via laser ranging measurements taken from multiple Earth ground stations. Analysis has been performed to determine the level of reduction in the semi-major axis covariance of the GPS satellites, when laser ranging measurements are supplemented to the radiometric station keeping, which the satellites undergo. Six ground tracking systems are studied to estimate the performance of the satellite. The first system is the baseline current system approach which provides pseudo-range and integrated Doppler measurements from six ground stations. The remaining five ground tracking systems utilize all measurements from the current system and laser ranging measurements from the additional ground stations utilized within those systems. Station locations for the additional ground sites were taken from a listing of laser ranging ground stations from the International Laser Ranging Service. Results show reductions in state covariance estimates when utilizing laser ranging measurements to solve for the satellite s position component of the state vector. Results also show dependency on the number of ground stations providing laser ranging measurements, orientation of the satellite to the ground stations, and the initial covariance of the satellite's state vector.

Welch, Bryan W.↗
NASA NTRS2008

Comparison of Satellite-Derived and In-Situ Observations of Ice and Snow Surface Temperatures over Greenland

The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Hall, Dorothy K.↗
NASA NTRS2009

Micro-Satellite Impact Tests to Investigate Multi-Layer Insulation Fragments

This paper summarizes two satellite impact experiments completed in 2008. The objective of the experiments is to investigate the physical properties of satellite fragments, including those originated from Multi-Layer Insulation (MLI) and solar panels. The ultimate goal is to use the results to improve the NASA Standard Breakup Model. The targets were two cubic micro-satellites, 20 cm by 20 cm by 20 cm in size, and approximately 1,500 g in mass. The main structure of each micro-satellite was composed of five layers; the top and bottom layers and three internal layers parallel to the top and bottom layers, plus four side panels. The top layer was equipped with solar cells that was mounted to an aluminum honeycomb sandwich panel with CFRP face sheets. The four side panels and the bottom layer are all covered with MLI. The two satellite impact experiments were conducted using the two-stage light gas gun at the Kyushu Institute of Technology in Kitakyusyu, Japan. For the first experiment (labeled Shot F), the satellite was oriented in such a way that the solar panel was facing the incoming projectile, a 39.3 g aluminum alloy solid sphere. For the second experiment (labeled Shot R), the satellite was oriented so that the solar panel was on the opposite side of the impact surface. The projectile used in the second shot was a 39.2 g aluminum alloy solid sphere. The impact speeds of Shot F and Shot R were 1.74 km/s and 1.78 km/s, respectively. The ratio of the impact kinetic energy to satellite mass for the two experiments was about 40 J/g. Both target satellites were completely fragmented, although there were noticeable differences in the characteristics of the fragments. Approximately 1,800 fragments were collected from Shot F but only 1,000 fragments were collected from Shot R. This difference primarily comes from the number of needle-like CFRP and MLI fragments. The difference in CFRP pieces depends on how the CFRP panels were fragmented. Regarding the MLI pieces, a significant difference in size and number can be observed. The largest MLI pieces in Shot F are almost of the same size as the side panels, whereas those in Shot R are larger by about a factor of two. The collected fragments and MLI pieces will be measured and analyzed using the same method as described in the NASA Standard Breakup Model. This paper will present: (1) the area-to-mass ratio, size, and mass distributions of the fragments, and (2) the differences in fragment properties between Shot F and Shot R.

Liou, J.C.↗
NASA NTRS2009

Icy Satellites of Saturn: Impact Cratering and Age Determination

Saturn is the first giant planet to be visited by an orbiting spacecraft that can transmit large amounts of data to Earth. Crater counts on satellites from Phoebe inward to the regular satellites and ring moons are providing unprecedented insights into the origin and time histories of the impacting populations. Many Voyager-era scientists concluded that the satellites had been struck by at least two populations of impactors. In this view, the Population I impactors, which were generally judged to be comets orbiting the Sun, formed most of the larger and older craters, while Population II impactors, interpreted as Saturn-orbiting ejecta from impacts on satellites, produced most of the smaller and younger craters. Voyager data also implied that all of the ring moons, and probably some of the midsized classical moons, had been catastrophically disrupted and reaccreted since they formed. We examine models of the primary impactor populations in the Saturn system. At the present time, ecliptic comets, which likely originate in the Kuiper belt/scattered disk, are predicted to dominate impacts on the regular satellites and ring moons, but the models require extrapolations in size (from the observed Kuiper belt objects to the much smaller bodies that produce the craters) or in distance (from the known active Jupiter family comets to 9.5 AU). Phoebe, Iapetus, and perhaps even moons closer to Saturn have been struck by irregular satellites as well. We describe the Nice model, which provides a plausible mechanism by which the entire Solar System might have experienced an era of heavy bombardment long after the planets formed. We then discuss the three cratering chronologies, including one based upon the Nice model, that have been used to infer surface ages from crater densities on the saturnian satellites. After reviewing scaling relations between the properties of impactors and the craters they produce, we provide model estimates of the present-day rate at which comets impact, and catastrophically disrupt, the saturnian moons. Finally, we present crater counts on the satellites from two different groups. Many of the heavily cratered terrains appear to be nearly saturated, so it is difficult to infer the provenance of the impactors from crater counts alone. More large craters have been found on Iapetus than on any other satellite. Enceladus displays an enormous range of surface ages, ranging from the old mid-latitude plains to the extremely young South Polar Terrain. Cassini images provide some evidence for the reality of Population II. Most of the observed craters may have formed in one or more cataclysms, but more work is needed to determine the roles of heliocentric and planetocentric bodies in creating the craters.

Dones, L.↗
NASA NTRS2009

Satellite Contributions to Global Change Studies

By providing a global view with a level playing field (no region missed because of unfavorable surface conditions or political boundaries), satellites have made major contributions to improved monitoring and understanding of our constantly changing planet. The global view has allowed surprising realizations like the relative sparsity of lightning strikes over oceans and the large-scale undulations on the massive Antarctic ice sheet. It has allowed the tracking of all sorts of phenomena, including aerosols, both natural and anthropogenic, as they move with the atmospheric circulation and impact weather and human health. But probably nothing that the global view allows is more important in the long term than its provision. of unbiased data sets to address the issue of global change, considered by many to be among the most important issues facing humankind today. With satellites we can monitor atmospheric temperatures at all latitudes and longitudes, and obtain a global average that lessens the likelihood of becoming endlessly mired in the confusions brought about by the certainty of regional differences. With satellites we can monitor greenhouse gases such as CO2 not just above individual research stations but around the globe. With satellites we can monitor the polar sea ice covers, as we have done since the late 1970s, determining and quantifying the significant reduction in Arctic sea ice and the slight growth in Antarctic sea ice over that period, With satellites we can map the full extent and changes in the Antarctic stratospheric ozone depletions that were first identified from using a single ground station; and through satellite data we have witnessed from afar land surface changes brought about by humans both intentionally, as with wide-scale deforestation, and unintentionally, as with the decay of the Aral Sea. The satellite data are far from sufficient for all that we need in order to understand the global system and forecast its changes, as we also need sophisticated climate models, in situ process studies, and data sets that extend back well before the introduction of satellite technology. Nonetheless, the repetitive, global view provided by satellites is contributing in a major way to our improved recognition of how the Earth im changing, a recognition that is none too soon in view of the magnitude of the impacts that humans can now have.

Parkinson, Claire L.↗
NASA NTRS2011

Combining Satellite and in Situ Data with Models to Support Climate Data Records in Ocean Biology

The satellite ocean color data record spans multiple decades and, like most long-term satellite observations of the Earth, comes from many sensors. Unfortunately, global and regional chlorophyll estimates from the overlapping missions show substantial biases, limiting their use in combination to construct consistent data records. SeaWiFS and MODIS-Aqua differed by 13% globally in overlapping time segments, 2003-2007. For perspective, the maximum change in annual means over the entire Sea WiFS mission era was about 3%, and this included an El NinoLa Nina transition. These discrepancies lead to different estimates of trends depending upon whether one uses SeaWiFS alone for the 1998-2007 (no significant change), or whether MODIS is substituted for the 2003-2007 period (18% decline, P less than 0.05). Understanding the effects of climate change on the global oceans is difficult if different satellite data sets cannot be brought into conformity. The differences arise from two causes: 1) different sensors see chlorophyll differently, and 2) different sensors see different chlorophyll. In the first case, differences in sensor band locations, bandwidths, sensitivity, and time of observation lead to different estimates of chlorophyll even from the same location and day. In the second, differences in orbit and sensitivities to aerosols lead to sampling differences. A new approach to ocean color using in situ data from the public archives forces different satellite data to agree to within interannual variability. The global difference between Sea WiFS and MODIS is 0.6% for 2003-2007 using this approach. It also produces a trend using the combination of SeaWiFS and MODIS that agrees with SeaWiFS alone for 1998-2007. This is a major step to reducing errors produced by the first cause, sensor-related discrepancies. For differences that arise from sampling, data assimilation is applied. The underlying geographically complete fields derived from a free-running model is unaffected by solar zenith angle requirements and obscuration from clouds and aerosols. Combined with in situ dataenhanced satellite data, the model is forced into consistency using data assimilation. This approach eliminates sampling discrepancies from satellites. Combining the reduced differences of satellite data sets using in situ data, and the removal of sampling biases using data assimilation, we generate consistent data records of ocean color. These data records can support investigations of long-term effects of climate change on ocean biology over multiple satellites, and can improve the consistency of future satellite data sets.

Gregg, Watson↗
NASA NTRS2012

The Antarctic Ice Sheet, Sea Ice, and the Ozone Hole: Satellite Observations of how they are Changing

Antarctica is the Earth's coldest and highest continent and has major impacts on the climate and life of the south polar vicinity. It is covered almost entirely by the Earth's largest ice sheet by far, with a volume of ice so great that if all the Antarctic ice were to go into the ocean (as ice or liquid water), this would produce a global sea level rise of about 60 meters (197 feet). The continent is surrounded by sea ice that in the wintertime is even more expansive than the continent itself and in the summertime reduces to only about a sixth of its wintertime extent. Like the continent, the expansive sea ice cover has major impacts, reflecting the sun's radiation back to space, blocking exchanges between the ocean and the atmosphere, and providing a platform for some animal species while impeding other species. Far above the continent, the Antarctic ozone hole is a major atmospheric phenomenon recognized as human-caused and potentially quite serious to many different life forms. Satellites are providing us with remarkable information about the ice sheet, the sea ice, and the ozone hole. Satellite visible and radar imagery are providing views of the large scale structure of the ice sheet never seen before; satellite laser altimetry has produced detailed maps of the topography of the ice sheet; and an innovative gravity-measuring two-part satellite has allowed mapping of regions of mass loss and mass gain on the ice sheet. The surrounding sea ice cover has a satellite record that goes back to the 1970s, allowing trend studies that show a decreasing sea ice presence in the region of the Bellingshausen and Amundsen seas, to the west of the prominent Antarctic Peninsula, but increasing sea ice presence around much of the rest of the continent. Overall, sea ice extent around Antarctica has increased at an average rate of about 17,000 square kilometers per year since the late 1970s, as determined from satellite microwave data that can be collected under both light and dark conditions and irrespective of whether clouds are in the way between the surface and the satellite. In contrast, the highest quality satellite measurements of the ozone hole use ultraviolet light, which requires daylight conditions. Still, satellite ultraviolet measurements of the ozone hole have also been made since the late 1970s, and these show a marked increase in the area and depth of the ozone hole in the 1980s and early 1990s, followed by a welcome leveling off of both measures since the mid-1990s.

Parkinson, Claire L.↗
NASA NTRS2019

Impact of Satellite Sea Surface Salinity Observations on ENSO Predictions from the GMAO Seasonal Forecast System

El Nino/Southern Oscillation (ENSO) has far reaching global climatic impacts and so extending useful ENSO forecasts would be of great benefit for society. However, one key variable that has yet to be fully exploited within coupled forecast systems is accurate estimation of near-surface ocean density. Satellite sea surface salinity (SSS), combined with temperature, help to identify ocean density changes and associated mixing near the ocean surface. We assess the impact of satellite SSS observations for improving near-surface dynamics within ocean analyses and how these impact dynamical ENSO forecasts using the NASA GMAO (Global Modeling and Assimilation Office) Sub-seasonal to Seasonal (S2S_v2.1) coupled forecast system (Molod et al. 2018 - i.e. NASA's contribution to the NMME (North American Multi-Model Ensemble) project). For all initialization experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF (Local Ensemble Transform Kalman Filter) scheme similar to Penny et al., 2013. A separate reanalysis additionally assimilates Aquarius V5 (September 2011 to June 2015) and SMAP (Soil Moisture Active Passive satellite) V4.1 (March 2015 to present) along-track data.We highlight the impact of satellite SSS on ocean reanalyses by comparing validation statistics of experiments that assimilate SSS versus our current prediction system that withholds SSS. We find that near-surface validation versus observed statistics for salinity are slightly degraded when assimilating SSS. This is an expected result due to known biases between SSS (measured by satellite at approximately 1-centimeter depth) and in situ measurements (typically measured by Argo floats at 3-meters depth). On the other hand, a very encouraging result is that both temperature, absolute dynamic topography, and mixed layer statistics are improved with SSS assimilation. Previous work has shown that correcting near-surface density structure via gridded SSS assimilation can improve coupled forecasts. Here we present results of coupled forecasts that are initialized from GMAO S2S spring reanalyses that assimilate/withhold along-track (L2) SSS. In particular, we contrast forecasts of the big 2015 El Nino, the 2017 La Nina and the 2018 weak El Nino. For each of these ENSO scenarios, assimilation of satellite SSS improves the forecast validation. Improved SSS and density upgrade the mixed layer depth leading to more accurate coupled air/sea interaction. From March to June 2015, the availability of two overlapping satellite SSS instruments, Aquarius and SMAP, allows a unique opportunity to compare and contrast forecasts initialized with the benefit of these two satellite SSS observation types. We assess the impact of gridded satellite sea surface salinity observations on dynamical ENSO forecasts for the big 2015 El Nino.

Hackert, E.↗
NASA NTRS2021

Evaluation of 18 Satellite- and Model-Based Soil Moisture Products Using in Situ Measurements From 826 Sensors

Information about the spatiotemporal variability of soil moisture is critical for many purposes, including monitoring of hydrologic extremes, irrigation scheduling, and prediction of agricultural yields. We evaluated the temporal dynamics of 18 state-of-the-art (quasi-)global near-surface soil moisture products, including six based on satellite retrievals, six based on models without satellite data assimilation (referred to hereafter as “open-loop” models), and six based on models that assimilate satellite soil moisture or brightness temperature data. Seven of the products are introduced for the first time in this study: one multi-sensor merged satellite product called MeMo (Merged soil Moisture) and six estimates from the HBV (Hydrologiska Byråns Vattenbalansavdelning) model with three precipitation inputs (ERA5, IMERG, and MSWEP) with and without assimilation of SMAPL3E satellite retrievals, respectively. As reference, we used in situ soil moisture measurements between 2015 and 2019 at 5 cm depth from 826 sensors, located primarily in the USA and Europe. The 3-hourly Pearson correlation (R) was chosen as the primary performance metric. We found that application of the Soil Wetness Index (SWI) smoothing filter resulted in improved performance for all satellite products. The best-to-worst performance ranking of the four single-sensor satellite products was SMAPL3E SWI , SMOS SWI , AMSR2 SWI , and ASCAT SWI , with the L-band-based SMAPL3E SWI (median R of 0.72) outperforming the others at 50 % of the sites. Among the two multi-sensor satellite products (MeMo and ESA-CCI SWI ), MeMo performed better on average (median R of 0.72 versus 0.67), probably due to the inclusion of SMAPL3E SWI . The best-to-worst performance ranking of the six open-loop models was HBV-MSWEP, HBV-ERA5, ERA5-Land, HBV-IMERG, VIC-PGF, and GLDAS-Noah. This ranking largely reflects the quality of the precipitation forcing. HBV-MSWEP (median R of 0.78) performed best not just among the open-loop models but among all products. The calibration of HBV improved the median R by +0.12 on average compared to random parameters, highlighting the importance of model calibration. The best-to-worst performance ranking of the six models with satellite data assimilation was HBV-MSWEP+SMAPL3E, HBV-ERA5+SMAPL3E, GLEAM, SMAPL4, HBV-IMERG+SMAPL3E, and ERA5. The assimilation of SMAPL3E retrievals into HBV-IMERG improved the median R by +0.06, suggesting that data assimilation yields significant benefits at the global scale.

Hylke E. Beck↗
NASA NTRS2019

Small-Satellite Mission Failure Rates

The purpose of this report is to determine the failure rate of small-satellite missions launched between the years 2000 and 2016. This analysis considers the rates of both partial and total mission failure, as well as the failures attributable to failure of the launch vehicle. This study observed that between the years of 2000 to 2016, 41.3% of all small satellites launched failed or partially failed. Of these small satellite missions, 24.2% were total mission failures, another 11% were partial mission failures, and 6.1% were launch vehicle failures. The small satellite failure data reveals an increase in the failure rate as the yearly launch rate has increased. The period 2000 to 2008 averaged 15 launches per year, during which 28.6% of the small satellite missions failed or partially failed. The period from 2009 to 2016 averaged 48 launches per year, during which 42.6% of the small satellite missions failed or partially failed. The launch vehicle failure rate for both periods was the same at around 6.1%. The implication is that for modern small satellite missions, almost one out of every two small satellite missions will result in either a total or a partial mission failure. Counting the partial mission successes as “successful missions” reduces the failure rate, but only to 38.2% for the period 2009 to 2016.

Small Satellite↗
DOE OSTI2025

Link Scheduling in Satellite Networks via Machine Learning Over Riemannian Manifolds

Low Earth Orbit (LEO) satellites play a crucial role in enhancing global connectivity, serving a complementary solution to existing terrestrial systems. In wireless networks, scheduling is a vital process that allocates time-frequency resources to users for interference management. However, LEO satellite networks face significant challenges in scheduling their links towards ground users due to the satellites’ mobility and overlapping coverage. This paper addresses the dynamic link scheduling problem in LEO satellite networks by considering spatio-temporal correlations introduced by the satellites’ movements. The first step in the proposed solution involves modeling the network over Riemannian manifolds, thanks to their representation as symmetric positive definite matrices. We introduce two machine learning (ML)-based link scheduling techniques that model the dynamic evolution of satellite positions and link conditions over time and space. To accurately predict satellite link states, we present a recurrent neural network (RNN) over Riemannian manifolds, which captures spatio-temporal characteristics over time. Furthermore, we introduce a separate model, the convolutional neural network (CNN) over Riemannian manifolds, which captures geometric relationships between satellites and users by extracting spatial features from the network topology across all links. Simulation results demonstrate that both RNN and CNN over Riemannian manifolds deliver comparable performance to the fractional programming-based link scheduling (FPLinQ) benchmark. Remarkably, unlike other ML-based models that require extensive training data, both models only need 30 training samples to achieve over 99% of the sum rate while maintaining similar computational complexity relative to the benchmark.

42 ENGINEERING↗
NASA NTRS2018

Large Satellite Bus Reliability

NASA is proposing to build a small space station in Cis-lunar orbit called Deep Space Gateway (DSG). At the heart of the DSG is the Power and Propulsion Element (PPE) which is conceptually similar to previously designed and operated satellite buses. A satellite bus is composed of the satellite spacecraft infrastructure minus the payload, and generally includes power, propulsion, avionics, and guidance, navigation and control. In November of 2017, five companies were awarded contracts by NASA to research PPE designs. In order to better understand the reliability of large satellite buses which may be the starting point of the PPE, NASA used Weibull analysis to evaluate spacecraft with similar masses and design life to the PPE. In addition, a subset of the large satellites which had satellite buses manufactured by any one of the five companies was also evaluated. This paper provides the results of the reliability analysis and compares the reliability of the general population of large satellites to the reliability associated with large satellite buses manufactured by the five companies currently studying PPE options.

Bus↗
NASA NTRS2021

Satellite Remote Sensing to Assess Cyanobacterial Bloom Frequency Across the United States at Multiple Spatial Scales

Cyanobacterial blooms can have negative effects on human health and local ecosystems. Field monitoring of cyanobacterial blooms can be costly, but satellite remote sensing has shown utility for more efficient spatial and temporal monitoring across the United States. Here, satellite imagery was used to assess the annual frequency of surface cyanobacterial blooms, defined for each satellite pixel as the percentage of images for that pixel throughout the year exhibiting detectable cyanobacteria. Cyanobacterial frequency was assessed across 2,196 large lakes in 46 states across the continental United States (CONUS) using imagery from the European Space Agency’s Ocean and Land Colour Imager for the years 2017 through 2019. In 2019, across all satellite pixels considered, annual bloom frequency had a median value of 4% and a maximum value of 100%, the latter indicating that for those satellite pixels, a cyanobacterial bloom was detected by the satellite sensor for every satellite image considered. In addition to annual pixel-scale cyanobacterial frequency, results were summarized at the lake- and state-scales by averaging annual pixel-scale results across each lake and state. For 2019, average annual lake-scale frequencies also had a maximum value of 100%, and Oregon and Ohio had the highest average annual state-scale frequencies at 65% and 52%. Pixel-scale frequency results can assist in identifying portions of a lake that are more prone to cyanobacterial blooms, while lake- and state-scale frequency results can assist in the prioritization of sampling resources and mitigation efforts. Satellite imagery is limited by the presence of snow and ice, as imagery collected in these conditions are quality flagged and discarded. Thus, annual bloom frequencies within nine climate regions were investigated to determine whether missing data biased results in climate regions more prone to snow and ice, given that their annual summaries would be weighted toward the summer months when cyanobacterial blooms tend to occur. Results were unbiased by the time period selected in most climate regions, but a large bias was observed for the Northwest Rockies and Plains climate region. Moderate biases were observed for the Ohio Valley and the Southeast climate regions. Finally, a clustering analysis was used to identify areas of high and low cyanobacterial frequency across CONUS based on average annual lake-scale cyanobacterial frequencies for 2019. Several clusters were identified that transcended state, watershed, and eco-regional boundaries. Combined with additional data, results from the clustering analysis may offer insight regarding large-scale drivers of cyanobacterial blooms.

remote sensing↗
NASA NTRSDate not supplied

GeoNEX-SUBSETS: Geostationary Satellite Observations Over International Observing Network Sites

Satellite remote sensing is crucial for monitoring the Earth’s surface and for simulating global carbon and water cycles. Subsets of satellite data from sensors such as MODIS over established observing networks have been valuable for researchers for comparing the ground observed phenomena with satellite observations. Here, we introduce new subsets of the GeoNEX geostationary satellite datasets over locations of several ground observation networks. The NASA Earth Exchange group has been generating geostationary satellite products with our international partners and universities to cover the entire globe. In comparison to polar-orbiting satellite sensors such as MODIS, the new generation geostationary satellites observe target areas at a higher frequency (5-10 minutes), which also significantly increased the data volume. To reduce the burden of downloading and extracting geostationary time series data and provide easy access to the community, we provide subsets of GeoNEX products through our data portal [www.data.nas.nasa.gov]. The ready-to-use subset follows the same format as the MODIS fixed sites subset tools for users who are familiar with MODIS subset data and software. The selected networks include Fluxnet, AERONET, and Phenocam over the conterminous US. We demonstrate the usage of the GeoNEX fixed-site subset data and showcase thir advantages with three example studies. The first example is simulating the diurnal cycle of plant ecophysiology at Fluxnet sites. The high frequency of the GeoNEX time series allows us to run ecological models at sub-hour time steps and directly compare the simulated carbon and water fluxes with half-hourly Fluxnet data. The second example uses the geostationary data to track phenological changes. It highlights the high-frequent observations of geostationary satellites in helping mask cloud covers and capture the quick responses of vegetation to environmental changes. As such, these examples demonstrate the value of ready-to-use GeoNEX subsets data in terrestrial ecophysiology research.

GeoNEX↗
DOE OSTI2023

SDSS-IV MaNGA: The Effect of Stellar Mass and Halo Mass on the Assembly Histories of Satellite Galaxies

We combine an unprecedented MaNGA sample of over 3000 passive galaxies in the stellar mass range 10 9 –10 12 M ⊙ with the Sloan Digital Sky Survey group catalog by Tinker to quantify how central and satellite formation, quantified by radial profiles in stellar age, [Fe/H], and [Mg/Fe], depends on the stellar mass of the galaxy (M * ) and the mass of the host halo (M h ). After controlling for M * and M h , the stacked spectra of centrals and satellites beyond the effective radius (r e ) show small, yet significant differences in multiple spectral features at the 1% level. According to spectral fitting with the code alf , a primary driver of these differences appears to be [Mg/Fe] variations, suggesting that stellar populations in the outskirts of satellites formed more rapidly than the outer populations of centrals. To probe the physical mechanisms that may be responsible for this signal, we examined how satellite stellar populations depend on M h . We find that satellites in high-M h halos show older stellar ages, lower [Fe/H], and higher [Mg/Fe] compared to satellites in low-M h halos, especially for M * = 10 9.5 –10 10.5 M ⊙ . These signals lend support to environmentally driven processes that quench satellite galaxies, although variations in the merger histories of central and satellite galaxies also emerge as a viable explanation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

The role of time-frequency in satellite position determination systems.

Tests were conducted by NASA on radio navigation satellite systems that employ the use of time-frequency determination. The satellites used for this purpose were the ATS 1 and 3, and the Nimbus 3 and 4. Several systems were tested in order to examine the feasibility of three satellite navigation concepts: (1) multiple satellite range measurements, (2) satellite range rate, or range and range rate measurements and (3) satellite angle measurements. Test results indicate that locations of ships and aircraft can be determined to within 3-5 km, one sigma, by these satellite methods, and that location accuracy is both a function of the RF employed and of the extent of knowledge of the satellite orbit.

Ehrlich, E.↗
NASA NTRS1972

Measured physical and optical properties of the passive geodetic satellite /Pageos/ and Echo 1.

Two satellites used for geodesy, Pageos and Echo 1, have been observed in a continuing program since 1966 to determine the stability of their physical and optical properties. Measurements are made in the UBVRI spectral system. The amount of solar radiation reflected from a satellite's surface is measured photoelectrically and is calibrated against known stellar magnitudes by standard astronomical techniques. The calibrated satellite magnitudes are analyzed with respect to the sun-satellite-observer phase angle to infer the shape and size of the satellite and the reflective properties of the satellite's surface material. The physical and optical properties are used to determine proper position of the solar image on the satellite's surface, resulting in more precise geometric geodesy. Quantitative results from five observing periods indicate that, although local structural anomalies appear to exist, both satellites essentially maintained their nominal average 30.48-meter (50-ft) radius of curvature and specular reflecting characteristics.

Mcdougal, D. S.↗
NASA NTRS1973

Submicrosecond time transfer between the United States, United Kingdom, and Australia via satellite

During 1972 time transfer experiments were run between the U.S. Naval Observatory and the Royal Greenwich Observatory and, in 1973, between the U.S. Naval Observatory and the Division of National Mapping in Canberra, Australia. In both cases the time transfer agent was the TIMATION 2 satellite, 1969-82B. The satellite ephemerides were computed from data provided by the Defense Mapping Agency TRANET. This net tracked the satellite's Doppler transmissions. The phase of the satellite clock was determined from knowledge of the position of the satellite and of the observer and the computed distance between the two. By monitoring the clock on successive passes the rate of the satellite clock was determined at Washington. By again monitoring the satellite clock at the distant station the satellite clock could be compared to the local clock and this local clock compared to the U.S. Naval Observatory clocks. In 1972 the RMS of observations at Greenwich deviated by approximately 1/4 microsecond from a straight line when compared to the Naval Observatory. In 1973 the observation errors at Canberra were approximately half as great.

Easton, R. L.↗