A laser satellite ranging system. I - Equipment description.
Laser tracking and ranging system with high resolution and accuracy used on three passive satellites with retroreflectors
Johnson, T. S.↗
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Results for “PASSIVE SATELLITE”
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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Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice
An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.
Maslanik, J. A.↗
Effective radio cross-section analysis from experimental measurements, Echo I Final report, 21 Jun. 1965 - 28 Apr. 1967
Statistical reduction of satellite effective radio cross section of reflected radio signal power measurements made on Echo I passive satellite
ECHO II SATELLITE↗
Design of the passive thermal control system of the SERT II satellite
Mercury bombardment ion thrustor life test in space environment onboard space electric rocket test /SERT/ satellite, describing passive satellite thermal control system design
Smolak, G. R.↗
Communications satellites - The experimental years
Only eight years after the launc of Sputnik-1 by the Soviet Union, the first commercial satellite, 'Early Bird', entered service. In just twelve years commercial satellite service extended around the earth and became profitable. The reasons for the successful development of the communications satellite services in a comparatively short time are considered. These reasons are related to the presence of three ingredients, taking into account technology to create the system, communications requirements to form a market, and a management structure to implement the system. The formation of the concept of using earth orbiting satellites for telecommunications is discussed. It is pointed out that the years from 1958 to 1964 were the true 'experimental years' for satellite communications. The rapid development of technology during this crucial period is described, giving attention to passive satellites, active systems, and development satellites.
Edelson, B. I.↗
A Regional CO2 Observing System Simulation Experiment for the ASCENDS Satellite Mission
Top-down estimates of the spatiotemporal variations in emissions and uptake of CO2 will benefit from the increasing measurement density brought by recent and future additions to the suite of in situ and remote CO2 measurement platforms. In particular, the planned NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) satellite mission will provide greater coverage in cloudy regions, at high latitudes, and at night than passive satellite systems, as well as high precision and accuracy. In a novel approach to quantifying the ability of satellite column measurements to constrain CO2 fluxes, we use a portable library of footprints (surface influence functions) generated by the WRF-STILT Lagrangian transport model in a regional Bayesian synthesis inversion. The regional Lagrangian framework is well suited to make use of ASCENDS observations to constrain fluxes at high resolution, in this case at 1 degree latitude x 1 degree longitude and weekly for North America. We consider random measurement errors only, modeled as a function of mission and instrument design specifications along with realistic atmospheric and surface conditions. We find that the ASCENDS observations could potentially reduce flux uncertainties substantially at biome and finer scales. At the 1 degree x 1 degree, weekly scale, the largest uncertainty reductions, on the order of 50 percent, occur where and when there is good coverage by observations with low measurement errors and the a priori uncertainties are large. Uncertainty reductions are smaller for a 1.57 micron candidate wavelength than for a 2.05 micron wavelength, and are smaller for the higher of the two measurement error levels that we consider (1.0 ppm vs. 0.5 ppm clear-sky error at Railroad Valley, Nevada). Uncertainty reductions at the annual, biome scale range from 40 percent to 75 percent across our four instrument design cases, and from 65 percent to 85 percent for the continent as a whole. Our uncertainty reductions at various scales are substantially smaller than those from a global ASCENDS inversion on a coarser grid, demonstrating how quantitative results can depend on inversion methodology. The a posteriori flux uncertainties we obtain, ranging from 0.01 to 0.06 Pg C yr-1 across the biomes, would meet requirements for improved understanding of long-term carbon sinks suggested by a previous study.
remote sensing↗
Microwave Brightness Temperatures of Tilted Convective Systems
Aircraft and ground-based radar data from the Tropical Ocean and Global Atmosphere Coupled-Ocean Atmosphere Response Experiment (TOGA COARE) show that convective systems are not always vertical. Instead, many are tilted from vertical. Satellite passive microwave radiometers observe the atmosphere at a viewing angle. For example, the Special Sensor Microwave/Imager (SSM/I) on Defense Meteorological Satellite Program (DMSP) satellites and the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) on the TRMM satellite have an incident angle of about 50deg. Thus, the brightness temperature measured from one direction of tilt may be different than that viewed from the opposite direction due to the different optical depth. This paper presents the investigation of passive microwave brightness temperatures of tilted convective systems. To account for the effect of tilt, a 3-D backward Monte Carlo radiative transfer model has been applied to a simple tilted cloud model and a dynamically evolving cloud model to derive the brightness temperature. The radiative transfer results indicate that brightness temperature varies when the viewing angle changes because of the different optical depth. The tilt increases the displacements between high 19 GHz brightness temperature (Tb(sub 19)) due to liquid emission from lower level of cloud and the low 85 GHz brightness temperature (Tb(sub 85)) due to ice scattering from upper level of cloud. As the resolution degrades, the difference of brightness temperature due to the change of viewing angle decreases dramatically. The dislocation between Tb(sub 19) and Tb(sub 85), however, remains prominent.
Hong, Ye↗
A Model Assessment of Satellite Observed Trends in Polar Sea Ice Extents
For more than three decades now, satellite passive microwave observations have been used to monitor polar sea ice. Here we utilize sea ice extent trends determined from primarily satellite data for both the Northern and Southern Hemispheres for the period 1972(73)-2004 and compare them with results from simulations by eleven climate models. In the Northern Hemisphere, observations show a statistically significant decrease of sea ice extent and an acceleration of sea ice retreat during the past three decades. However, from the modeled natural variability of sea ice extents in control simulations, we conclude that the acceleration is not statistically significant and should not be extrapolated into the future. Observations and model simulations show that the time scale of climate variability in sea ice extent in the Southern Hemisphere is much larger than in the Northern Hemisphere and that the Southern Hemisphere sea ice extent trends are not statistically significant.
Vinnikov, Konstantin Y.↗
Passive Microwave Algorithms for Sea Ice Concentration: A Comparison of Two Techniques
The most comprehensive large-scale characterization of the global sea ice cover so far has been provided by satellite passive microwave data. Accurate retrieval of ice concentrations from these data is important because of the sensitivity of surface flux(e.g. heat, salt, and water) calculations to small change in the amount of open water (leads and polynyas) within the polar ice packs. Two algorithms that have been used for deriving ice concentrations from multichannel data are compared. One is the NASA Team algorithm and the other is the Bootstrap algorithm, both of which were developed at NASA's Goddard Space Flight Center. The two algorithms use different channel combinations, reference brightness temperatures, weather filters, and techniques. Analyses are made to evaluate the sensitivity of algorithm results to variations of emissivity and temperature with space and time. To assess the difference in the performance of the two algorithms, analyses were performed with data from both hemispheres and for all seasons. The results show only small differences in the central Arctic in but larger disagreements in the seasonal regions and in summer. In some ares in the Antarctic, the Bootstrap technique show ice concentrations higher than those of the Team algorithm by as much as 25%; whereas, in other areas, it shows ice concentrations lower by as much as 30%. The The differences in the results are caused by temperature effects, emissivity effects, and tie point differences. The Team and the Bootstrap results were compared with available Landsat, advanced very high resolution radiometer (AVHRR) and synthetic aperture radar (SAR) data. AVHRR, Landsat, and SAR data sets all yield higher concentrations than the passive microwave algorithms. Inconsistencies among results suggest the need for further validation studies.
Comiso, Josefino C.↗
TPSAS-NF1676L-20735-DND
Higher than normal accuracy is required to rigorously observe decadal climate change. But what level is needed? How can this be quantified? This presentation will summarize a new more rigorous and quantitative approach to determining the required accuracy for climate change observations (Wielicki et al., 2013, BAMS). Most current global satellite observations cannot meet this accuracy level. A proposed new satellite mission to resolve this challenge is CLARREO (Climate Absolute Radiance and Refractivity Observatory). CLARREO is designed to achieve advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra (Wielicki et al., Oct. 2013 BAMS). The CLARREO spectrometers are designed to serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and to greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar passive satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, SPOT, etc). Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A study has been carried out to quantify the economic benefits of such an advance as part of a rigorous and complete climate observing system. The study concludes that the economic value is ~ $12 Trillion U.S. dollars in Net Present Value for a nominal discount rate of 3% (Cooke et al. 2013, J. Env. Sys. Dec.). A brief summary of these two studies and their implications for the future of climate science will be presented.
Bruce Wielicki↗
Sensitivity of Passive Microwave Snow Depth Retrievals to Weather Effects and Snow Evolution
Snow fall and snow accumulation are key climate parameters due to the snow's high albedo, its thermal insulation, and its importance to the global water cycle. Satellite passive microwave radiometers currently provide the only means for the retrieval of snow depth and/or snow water equivalent (SWE) over land as well as over sea ice from space. All algorithms make use of the frequency-dependent amount of scattering of snow over a high-emissivity surface. Specifically, the difference between 37- and 19-GHz brightness temperatures is used to determine the depth of the snow or the SWE. With the availability of the Advanced Microwave Scanning Radiometer (AMSR-E) on the National Aeronautics and Space Administration's Earth Observing System Aqua satellite (launched in May 2002), a wider range of frequencies can be utilized. In this study we investigate, using model simulations, how snow depth retrievals are affected by the evolution of the physical properties of the snow (mainly grain size growth and densification), how they are affected by variations in atmospheric conditions and, finally, how the additional channels may help to reduce errors in passive microwave snow retrievals. The sensitivity of snow depth retrievals to atmospheric water vapor is confirmed through the comparison with precipitable water retrievals from the National Oceanic and Atmospheric Administration's Advanced Microwave Sounding Unit (AMSU-B). The results suggest that a combination of the 10-, 19-, 37-, and 89-GHz channels may significantly improve retrieval accuracy. Additionally, the development of a multisensor algorithm utilizing AMSR-E and AMSU-B data may help to obtain weather-corrected snow retrievals.
Markus, Thorsten↗
TSS Satellite Overview
The responsibilities of NASA and PSN/CNR in the tethered satellite system cooperative program are listed and PSN/CNR-AIT system support and technologies studies are summarized. Results are given for investigations of active vs. passive satellite trade offs; analysis of alternative maneuvers; satellite attitude and position determination analysis failure modes analysis; moveable boom dynamic analysis; double tethered satellite system; and thermo/dynamic analysis for 100 km to 120 km altitude range. Objectives for the space plasma science mission and its applications are outlined and the TSS satellite configuration is highlighted. Programmatic aspects are included.
Manarini, G.↗
Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone
A recent, interdisciplinary survey of more than 40 international remote sensing experts reviewed the strengths and limitations of current space-based observational capabilities of the Arctic Boreal Zone (ABZ) and made recommendations for improving upon these current capabilities (Duncan et al., 2019). General recommendations focused on the complementarity of sub-orbital and satellite observations, the need for measurement continuity, and the importance of stakeholder engagement. The development of a comprehensive and robust sub-orbital portion of an ABZ observing network can act to fill some temporal gaps in satellite coverage, provide detail unobtainable from space, and is necessary for validation and interpretation of satellite data. A priority across all types of observations is the continuation, enhancement, and/or creation of long-term, multi-satellite, climate-quality, and self-consistent data records of ABZ components, such as surface temperature, energy fluxes, or sea ice extent and volume, for improved determination of trends. Long-term passive satellite observations currently represent the only feasible option for monitoring change of the ABZ at broad spatial scales required to address pressing science challenges. Active sensors are particularly attractive for the ABZ as they do not depend on reflected sunlight and so join passive microwave sensors in having a significant advantage over passive visible and infrared sensors in the low-light conditions that are typical of the ABZ for several months of the year. Application of consistent retrieval algorithms to multiple data sets, as well as careful characterization of satellite instruments and their temporal evolution, helps to ensure data quality and consistency. Among the needs ranked as “Most Important” are those associated with gaining a process-based understanding of the ABZ carbon cycle and hydrologic cycle (which includes sea level rise) as they have the potential to affect a large portion of Earth’s population.
Remote sensing↗
Precipitation Characteristics of ISCCP Cloud Regimes for Improving Model Hydrological Budgets
The key in unraveling relationships between precipitation and atmospheric circulations is their common linkage to clouds. Clouds can be described in a variety of ways and several approaches can be adopted to examine their connections to precipitation. We claim that when cloud regimes (aka weather states) from the International Satellite Cloud Climatology Project (ISCCP) are used to conditionally sample/sort and average precipitation data, useful insight and GCM-appropriate diagnostics on the origins and distribution of precipitation can be obtained. The ISCCP cloud regimes are mesoscale (2.5 ) cloud mixtures determined by cluster analysis on joint histograms of cloud optical thickness and cloud top pressure inferred from geostationary and polar orbiter satellite passive retrievals. The ISCCP cloud regime data are combined with GPCP IDD merged surface precipitation data and/or higher temporal and spatial resolution TRMM Multi-Satellite Precipitation Analysis (TMPA) data. The analysis is performed separately for three geographical zones, tropics, and northern/southern midlatitudes (for GPCP; only the tropics can be examined with TMPA data). Our presentation aspires to provide answers to the following questions: (l) What is the mean and variability of surface precipitation produced by each cloud regime at the time of regime occurrence? (2) What is the relative contribution of each cloud regime to the total precipitation within its geographical zone? (3) What is the geographical distribution of precipitation corresponding to particular cloud regime? (4) To what extent are the cloud regimes distinct in terms of their precipitation characteristics and is the regime ordering in terms of convective strength consistent with the observed precipitation intensity?
Lee, D.↗
Laser range measurement for a satellite navigation scheme and mid-range path selection and obstacle avoidance
The functions of a laser rangefinder on board an autonomous Martian roving vehicle are discussed. The functions are: (1) navigation by means of a passive satellite and (2) mid-range path selection and obstacle avoidance. The feasibility of using a laser to make the necessary range measurements is explored and a preliminary design is presented. The two uses of the rangefinder dictate widely different operating parameters making it impossible to use the same system for both functions.
Zuraski, G. D.↗
TPSAS-NF1676L-34528-DND
Since 2006, the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite, has provided a unique vertical perspective of Earth's atmosphere. These measurements have furthered our understanding of the role aerosols and clouds play in the climate system and have been leveraged for atmospheric modeling and air quality studies. In this seminar, the basics of LIDAR remote sensing will first be presented, including its operating principles, setup and geometry, the LIDAR equation, and different LIDAR types and techniques. Next, an overview of the LIDAR systems at NASA Langley Research Center will be provided, with an emphasis on the CALIPSO satellite mission, including available data products and examples of browse images. Lastly, several CALIPSO-based science applications and research projects will be discussed, including cloud contamination in passive satellite aerosol retrievals, aerosol detection limits, trends in aerosol vertical distribution, and air quality (PM2.5 concentrations).
Travis Toth↗
Large Scale Characteristics and Variability of the Global Sea Ice Cover
More than two decades of satellite passive microwave data are used to study and evaluate the large scale characteristics and the changing state of the sea ice cover in both the Northern and Southern Hemispheres. Satellite data provide day/night almost continuous observation of global sea ice cover thereby enabling quantitative variability studies at various time scales. Despite coarse sensor resolution, spatial detail is provided through the use of sea ice concentrations which are derived using an algorithm that determines the fraction of ice and open water within each satellite footprint. Large seasonal fluctuations in the extent are apparent with those of the Southern Hemisphere having larger amplitudes but less symmetrical seasonal distribution than those of the Northern Hemisphere. The large scale interannual variability of the ice cover has been evaluated globally as well as regionally and in the Northern Hemisphere, the yearly anomaly maps show a predominance of positive values in the 1980s and negative values in the 1990s. Regression analysis show that the ice extent and ice area are on a decline at the rate of -2.0 +/- 0.5% and -3.1 +/- 0.3% per decade, respectively, in the Northern Hemisphere but there are regions like the Bering Sea with positive trends. What is intriguing, however, is that the perennial sea ice cover has been declining at a much faster rate than for the entire hemisphere, i.e., 6.7 +/- 2.4% and 8.3 +/- 2.4 % per decade for ice extent and ice area, respectively. The perennial ice cover consists mainly of thick multiyear ice floes, and its persistent decline would mean a reduction in the average thickness of sea ice and a change in the overall characteristics of the Arctic sea ice cover. Furthermore, the yearly anomaly patterns are coherent with those of surface temperatures derived from 19 years of thermal infrared AVHRR data. The latter also shows that in consolidated ice regions, the average temperature during summer minima has been increasing at about 0.9 +/- 0.6 K per decade.
Comiso, Josefino C.↗
Using AI/ML to Address Satellite Cloud Remote Sensing Challenges
Various AI/ML tools, employed within the Clouds and the Earth's Radiant Energy System (CERES) Satellite Cloud and Radiation Property retrieval System (SatCORPS) project, are being used to mitigate satellite radiance artifacts and thereby yield more accurate cloud and radiation data products. Neural network and K-nearest neighbor approaches have been developed that enable us to better address common passive satellite remote sensing challenges, such as corrupted imagery, day/night cloud property discontinuities, solar terminator artifacts, inadequate knowledge of the land surface emission temperature (i.e., skin temperature), and poor assumptions about vertical cloud structure, that have otherwise proven difficult to solve using more conventional methods. Fixing these problems promotes a more consistent Earth radiation budget record. These efforts demonstrate effective use of AI/ML architecture to exploit complex, multivariate predictor relationships and produce usable output at satellite spatial and temporal resolutions that would otherwise be ignored or have large biases.
Benjamin Scarino↗