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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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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

The Pioneer Venus Spacecraft Program

The Pioneer Venus Program consists of two spacecraft: an Orbiter and a Multiprobe. Both spacecraft will arrive at Venus in early December, 1978. The Orbiter will collect data on the upper atmosphere and fields and particles and will remotely sense the clouds and surface from a 75 deg inclined orbit. The Multiprobe consists of a Bus, three Small Probes, and a Large Probe. All five objects will enter the Venus atmosphere and will transmit data on its characteristics directly back to earth while descending to the surface. The entire mission is expected to substantially increase our knowledge of the planet Venus, especially its atmosphere.

Dorfman, S. D.↗
NASA NTRS1991

Design, performance evaluation, and investigation of the theoretical capabilities of the NASA Millimeter-wave Imaging Radiometer (MIR)

The development of techniques for passive microwave retrieval of water vapor and precipitation parameters using millimeter- and sub-millimeter wavelength channels is reviewed. Channels of particular interest are in the tropospheric transmission windows at 90, 150, 220, and 340 GHz and centered around the water vapor lines at 183 and 325 GHz. Collectively, these channels have potential application in high-resolution mapping (e.g., from geosynchronous orbit), remote sensing of cloud and precipitation parameters, and retrieval of water vapor profiles. Both theoretical and experimental results to date are discussed.

Gasiewski, Albin J.↗
NASA NTRS1994

Surface-induced brightness temperature variations and their effects on detecting thin cirrus clouds using IR emission channels in the 8-12 microns region

A method for detecting cirrus clouds in terms of brightness temperature differences between narrowbands at 8, 11, and 12 microns has been proposed by Ackerman et al. In this method, the variation of emissivity with wavelength for different surface targets was not taken into consideration. Based on state-of-the-art laboratory measurements of reflectance spectra of terrestrial materials by Salisbury and D'Aria, it is found that the brightness temperature differences between the 8- and 11-microns bands for soils, rocks, and minerals, and dry vegetation can vary between approximately -8 and +8 K due solely to surface emissivity variations. The large brightness temperature differences are sufficient to cause false detection of cirrus clouds from remote sensing data acquired over certain surface targets using the 8-11-12-microns method directly. It is suggested that the 8-11-12-microns method should be improved to include the surface emissivity effects. In addition, it is recommended that in the future the variation of surface emissivity with wavelength should be taken into account in algorithms for retrieving surface temperatures and low-level atmospheric temperature and water vapor profiles.

Gao, Bo-Cai↗
NASA NTRS1999

The Infrared Spectral Imaging Radiometer and Laser Altimeter on STS-85 (an Aircraft Style Experiment Flown in Space)

Improvements in the remote sensing of clouds from space in the future will come from instruments with higher spatial and spectral resolution on more platforms and supported by active sounding. The space shuttle hitchhiker system allows new measurements to be prototyped in space with costs, operating flexibility and data volumes similar to aircraft experiments. The Infrared Spectral Imaging Radiometer and Shuttle Laser Altimeter hitchhiker experiment was flown in 1997. The experiment tested the use of uncooled thermal infrared imaging, laser cloud altitude measurements and high spatial resolution, tri-spectral sensing of cloud particle size and phase. A 1/4 km resolution, fifty orbit data set was obtained from STS-85. The presentation will focus on the use of the shuttle as an experiment platform and cover possible transition to the space station in the future.

Spinhirne, James D.↗
NASA NTRS2000

The Ceres S'COOL Project: Two Years After First Launch

The idea for the Students' Cloud Observations OnLine (S'COOL) project as an outreach and education element of NASA's Clouds and the Earth's Radiant Energy System (CERES) research program was conceived in late 1996 during a conversation with a middle school science teacher. S'COOL was implemented in a series of increasingly developed test phases during 1997, as the launch of the first CERES instrument approached. Even before launch, the reception of the project in schools far exceeded expectations. After several delays the first instrument, on the Tropical Rainfall Measuring Mission (TRMM) spacecraft, was launched on Thanksgiving Day, 1997. Since the first launch, development and expansion of the project has continued with expectations for launch of Terra carrying two CERES instruments into a polar orbit in mid-1998. That launch is now expected in fall 1999, and will finally provide overflight of all participating schools. In two years, the project has grown from three initial test participants to over 300 schools now participating in 23 countries on five continents. Students from first grade through university level are involved (most participants are ages 10-15). S'COOL is also being used by a few education professors to teach about Internet use in the classroom. The project continues to grow through word of mouth, presentations at teacher workshops, and now increasingly through teachers who find it during web searches. Participants in the S'COOL project are part of the CERES validation team. They provide ground truth measurements at the time the CERES instrument flies over their location, to be compared with the retrieval of cloud properties by remote sensing from CERES. Quantities reported include cloud type, height, fraction and opacity; information on contrails; surface temperature, pressure and relative humidity; and ground cover (snow/ice, wet, dry; leaves on trees or not). in addition, a comment field on the report form serves as a catch-all for all kinds of interesting observations, including similes written by some classes to describe more exactly the clouds they see. Several not totally unexpected complications with the CERES instrument and processing software mean that the CERES team has not yet reached the point of computing the cloud properties, a high level product at the end of the processing stream. However, progress is being made and we anticipate that we will soon be populating the S'COOL database with a large number of satellite retrievals for comparison with the students' observations. Some satellite retrievals from the initial test phases are already available in the database, The CERES instruments are planned to operate at least through 2006, and the S'COOL Project is planned to continue at least that long, providing motivational learning to as many students as possible. This paper reports on the first several years of the S'CCOL project. It further reports on some of the noteworthy observations and comparisons made possible by this project. Schools are often located in interesting places, in terms of the clouds found there and the satellite's ability to observe these clouds. The paper also reports on the learning opportunities delivered by this project, and on new questions about the planet and its climate which arise in the students' minds as a result of their active participation.

Chambers, Lin H.↗
NASA NTRS2000

Early Results from the MODIS Atmosphere Cloud Algorithms

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System platform launched in December 1999. With 36 spectral bands from the visible through the infrared, and spatial resolution from 250m to 1km, the instrument provides an unprecedented opportunity for global cloud studies. A comprehensive set of remote sensing algorithms for cloud masking and retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud top physical parameters (temperature, pressure, emissivity), cloud phase, cloud optical parameters (optical depth, effective particle radius, water path), visible cirrus reflectance, a contrail flag, and other derived parameters. All products are archived into two categories: pixel-level retrievals at a 1 km or 5 km spatial resolution at nadir (referred to as Level-2 products) and 1 degree global gridded statistics (Level-3 products). An overview of the MODIS atmosphere algorithms and products, their status, validation activities, and early level-2 and -3 results will be presented.

Platnick, S.↗
NASA NTRS2003

Promise and Capability of NASA's Earth Observing System to Monitor Human-Induced Climate Variations

The Earth Observing System (EOS) is a space-based observing system comprised of a series of satellite sensors by which scientists can monitor the Earth, a Data and Information System (EOSDIS) enabling researchers worldwide to access the satellite data, and an interdisciplinary science research program to interpret the satellite data. The Moderate Resolution Imaging Spectroradiometer (MODIS), developed as part of the Earth Observing System (EOS) and launched on Terra in December 1999 and Aqua in May 2002, is designed to meet the scientific needs for satellite remote sensing of clouds, aerosols, water vapor, and land and ocean surface properties. This sensor and multi-platform observing system is especially well suited to observing detailed interdisciplinary components of the Earth s surface and atmosphere in and around urban environments, including aerosol optical properties, cloud optical and microphysical properties of both liquid water and ice clouds, land surface reflectance, fire occurrence, and many other properties that influence the urban environment and are influenced by them. In this presentation I will summarize the current capabilities of MODIS and other EOS sensors currently in orbit to study human-induced climate variations.

King, M. D.↗
NASA NTRS2003

Infrared remote sensing in the presence of clouds with AIRS-AMSU-HSB

The Atmospheric Infrared Sounder (AIRS) and its two companion instruments (AMSU) and (HSB) are designed to provide atmospheric temperature and humidity profiles with radiosonde accuracty. The performance of AIRS since launch on Aqua has been exceptional indicating that it will meet or exceed its objectives.

AIRS EOS spectrometers infrared temperature sounde↗
NASA NTRS2004

Support vector machines

Support Vector Machines (SVMs) are a type of supervised learning algorith,, other examples of which are Artificial Neural Networks (ANNs), Decision Trees, and Naive Bayesian Classifiers. Supervised learning algorithms are used to classify objects labled by a 'supervisor' - typically a human 'expert.'.

multiangle↗
NASA NTRS2009

Case Studies of Aerosol Remote Sensing in the Vicinity of Clouds

Studying the spatial variability of aerosol properties in the vicinity of clouds is essential to our ability to determine aerosol direct and indirect effects on climate. In this paper, we describe aerosol observations collected near cloud edges by an airborne Sun photometer over dark ocean waters. Focusing on case studies of aerosol measurements near eight cloud edges within a dissipating stratiform cloud deck, we compare the airborne Sun photometer observations to retrievals of aerosol properties using the standard Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol algorithm applied to 500-m-resolution MODIS spectral reflectances. We find a persistent, spectrally neutral increase in the Sun photometer-derived aerosol optical depth (AOD) of up to 10% (0.015) in the 2-km distances closest to the edges of several distinct clouds. At midvisible wavelengths, the MODIS AOD retrievals show similar increases toward cloud edges, although a larger increase in AOD is found in the MODIS along-scan direction. At shortwave infrared (SWIR) wavelengths (1240-2130 nm), the MODIS-derived AOD increases near cloud edges are of the order of 0.03 and as such three times as large as the Sun photometer-derived values. Hence, in contrast to recently discussed bluing of aerosols near cloud edges, i.e., a preferential apparent increase in the visible reflectances of clear-sky pixels due to 3-D radiative transfer effects in the vicinity of clouds, we find a reddening of aerosols in the MODIS 500-m-resolution aerosol retrievals near clouds. This reddening in our study can be traced to larger absolute increases in SWIR reflectances when compared to visible reflectances near clouds, which in turn seem to stem from larger electronic cross talk in the MODIS SWIR bands (5-7). We note that the lack of bluing in our MODIS observations is likely due to the small geometric and optical thicknesses of the clouds considered.

Redemann, Jens↗
NASA NTRS2012

Rainbow Fourier Transform

We present a novel technique for remote sensing of cloud droplet size distributions. Polarized reflectances in the scattering angle range between 135deg and 165deg exhibit a sharply defined rainbow structure, the shape of which is determined mostly by single scattering properties of cloud particles, and therefore, can be modeled using the Mie theory. Fitting the observed rainbow with such a model (computed for a parameterized family of particle size distributions) has been used for cloud droplet size retrievals. We discovered that the relationship between the rainbow structures and the corresponding particle size distributions is deeper than it had been commonly understood. In fact, the Mie theory-derived polarized reflectance as a function of reduced scattering angle (in the rainbow angular range) and the (monodisperse) particle radius appears to be a proxy to a kernel of an integral transform (similar to the sine Fourier transform on the positive semi-axis). This approach, called the rainbow Fourier transform (RFT), allows us to accurately retrieve the shape of the droplet size distribution by the application of the corresponding inverse transform to the observed polarized rainbow. While the basis functions of the proxy-transform are not exactly orthogonal in the finite angular range, this procedure needs to be complemented by a simple regression technique, which removes the retrieval artifacts. This non-parametric approach does not require any a priori knowledge of the droplet size distribution functional shape and is computationally fast (no look-up tables, no fitting, computations are the same as for the forward modeling).

Alexandrov, Mikhail D.↗
NASA NTRS2012

Impacts of Spatial Fidelity Violations in the Forward Signal Model on DOAS-based Greenhouse Gas Retrievals: a Preliminary Analysis for OCO-2 (and Other Missions)

Success in three aspects of OCO‐2 mission is threatened by unaccounted spa,al variability effects, all involving atmospheric scattering: 1. Low/moderately opaque clouds can escape the prescreening by mimicking a brighter surface. 2. Prescreening does not account for long‐range radia,ve impact (adjacency effect) of nearby clouds. Need for extended cloud masking? 3. Oblique looks in target mode are highly exposed to surface adjacency and aerosol variability effects.We'll be covering all three bases!

aerosols↗
NASA NTRS2014

How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

Aerosol↗