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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

The CIRS Investigation on Cassini after Six Years at Saturn

The CIRS investigation designed to provide: 1) infrared spectroscopy of thermal emission from atmospheres, rings, and surfaces in 10 +/- 1450 cm(exp -1) (1000 +/- 7 micron) region; 2) global mapping in atmospheres of three dimensional and temporal variation of gas composition, temperatures, dynamics, and aerosols and clouds; and 3) mapping of rings and icy satellite surfaces for composition and thermal properties. Topics include: optical and mechanical layouts, instrument description, preparation for launch, Saturn's rings in the light spectrum, Saturn brightness temperature spectrum, and views of Saturn's surface, rings, and Saturn's moons and their atmospheres.

Jennings, Donald↗
NASA NTRS2020

Snow Property Inversion from Remote Sensing (SPIReS): A Generalized Multispectral Unmixing Approach with Examples from MODIS and Landsat 8 OLI

Spectral mixture analysis has a history in mappingsnow, especially where mixed pixels prevail. Using multiplespectral bands rather than band ratios or band indices, retrievalsof snow properties that affect its albedo lead to more accu-rate estimates than widely used age-based models of albedoevolution. Nevertheless, there is substantial room for improve-ment. We present the Snow Property Inversion from RemoteSensing (SPIReS) approach, offering the following improve-ments: 1) Solutions for grain size and concentrations of lightabsorbing particles are computed simultaneously; 2) Only snowand snow-free endmembers are employed; 3) Cloud-maskingand smoothing are integrated; 4) Similar spectra are groupedtogether and interpolants are used to reduce computation time.The source codes are available in an open repository. Com-putation is fast enough that users can process imagery ondemand. Validation of retrievals from Landsat 8 operational landimager (OLI) and moderate-resolution imaging spectroradiome-ter (MODIS) against WorldView-2/3 and the Airborne SnowObservatory shows accurate detection of snow and estimatesof fractional snow cover. Validation of albedo shows low errorsusing terrain-correctedin situmeasurements. We conclude bydiscussing the applicability of this approach to any airborne orspaceborne multispectral sensor and options to further improve retrievals.

Edward H Blair↗
NASA NTRS1984

Thunderstorm cloud top dynamics as inferred from satellite observations and models

Satellite observations of convective towers penetrating the tropopause are summarized. Three classes of thunderstorm cloud tops including storm tops that have a monotonic temperature-height pattern with the highest point being the coldest point (class 1), tops that have a colocated cold and high point with the warm point on the downward slope to the rear of the highest point (class 2), and tops in which the cold point is offset upwind from the high point, with a cold-warm couplet straddling the convective cloud top (class 3), are described. A one-dimensional cloud parcel model applied in the overshooting region is used to explore the causes of the storm top's unique temperature/height structures.

Adler, R. F.↗
NASA NTRS1994

Clouds, hazes, and the stratospheric methane abundance in Neptune

Analysis of high-spatial-resolution (approximately 0.8 arcsec) methane band and continuum imagery of Neptune's relatively homogeneous Equatorial Region yields significant constraints on (1) the stratospheric gaseous methane mixing ratio (f(sub CH4, S)), (2) the column abundances and optical properties of stratospheric and tropospheric hydrocarbon hazes, and (3) the wavelength-dependent single-scattering albedo of the 3-bar opaque cloud. From the center-to-limb behavior of the 7270-A and 8900-A CH4 bands, the stratospheric methane mixing ratios is limited to f(sub CH4, S) less than 1.7 x 10(exp -3), with a nominal value of f(sub CH4, S) = 3.5 x 10(exp -4), one to two orders of magnitude less than pre-Voyager estimates, but in agreement with a number of recent ultraviolet and thermal infrared measurements, and largely in agreement with the tropopause mixing ratio implied by Voyager temperature measurements. Upper limits to the stratospheric haze mass column abundance and 6190-A and 8900-A haze opacities are 0.61 micrograms/sq cm and 0.075 and 0.042, respectively, with nominal values of 0.20 micrograms/sq cm and 0.025 and 0.014 for the 0.2 micrometers radius particles preferred by the recent Voyager PPS analysis of Pryor et al. (1992). The tropospheric CH4 haze opacities are comparable to that found in the stratosphere, i.e., upper limits of 0.104 and 0.065 at 6190 A and 8900 A, respectively, with nominal values of 0.085 and 0.058. This indicates a column abundance less than 11.0 micrograms/sq cm, corresponding to the methane gas content within a well-mixed 3% methane tropospheric layer only 0.1 cm thick near the 1.5-bar CH4 condensation level. Conservative scattering is ruled out for the opaque cloud near 3 bars marking the bottom of the visible atmosphere. Specifically, we find cloud single-scattering albedos of 0.915 +/- 0.006 at 6340 A, 0.775 +/- 0.012 at 7490 A, and 0.803 +/- 0.010 at 8260 A. Global models utilizing a complete global spectrum confirm the red-absorbing character of the 3-bar cloud. The global-mean model has approximately 7.7 times greater stratospheric aerosol content than the Equatorial Region. An analysis of stratospheric haze precipitation rates indicates a steady-state haze production rate of 0.185-1.5 x 10(exp -14) g/sq cm/s, in agreement with recent theoretical photochemical estimates. Finally, reanalysis of the Voyager PPS 7500-A phase angle data utilizing the f(sub CH4, S) value derived here confirms the Pryor et al. result of a tropospheric CH4 haze opacity of a few tenths in the 22-30 degs S latitude region, several times that of the Equatorial Region or of the globe. The factor-of-10 reduction in f(sub CH4, S) below that assumed by Pryor et al. implies decreased gas absorption and consequently a decrease in the forward-scattering component of tropospheric aerosols.

Baines, Kevin H.↗
NASA NTRS2007

On the Magnitude of the Electric Field Near Thunderstorm-Associated Clouds

Electric field measurements made in and near clouds during two airborne field mill programs are presented. Aircraft equipped with multiple electric field mills and cloud physics sensors were flown near active convection and into thunderstorm anvil and debris clouds. The magnitude of the electric field was measured as a function of position with respect to the cloud edge in order to provide an observational basis for modifications to the lightning launch commit criteria (LLCC) used by the U.S. space program. These LLCC are used to reduce the risk that an ascending launch vehicle will trigger a lightning strike that could cause the loss of the mission or vehicle. The results suggest that even with fields of tens of kV/m inside electrically active convective clouds, the fields external to these clouds decay to less than 3 kV/m within fifteen kilometers of cloud edge. Fields exceeding 3 kV/m were not found external to anvil and debris clouds.

Merceret, Francis J.↗
NASA NTRS1981

Stereographic observations from geosynchronous satellites - An important new tool for the atmospheric sciences

Observations of cloud geometry using scan-synchronized stereo geostationary satellites having images with horizontal spatial resolution of approximately 0.5 km, and temporal resolution of up to 3 min are presented. The stereo does not require a cloud with known emissivity to be in equilibrium with an atmosphere with a known vertical temperature profile. It is shown that absolute accuracies of about 0.5 km are possible. Qualitative and quantitative representations of atmospheric dynamics were shown by remapping, display, and stereo image analysis on an interactive computer/imaging system. Applications of stereo observations include: (1) cloud top height contours of severe thunderstorms and hurricanes, (2) cloud top and base height estimates for cloud-wind height assignment, (3) cloud growth measurements for severe thunderstorm over-shooting towers, (4) atmospheric temperature from stereo heights and infrared cloud top temperatures, and (5) cloud emissivity estimation. Recommendations are given for future improvements in stereo observations, including a third GOES satellite, operational scan synchronization of all GOES satellites and better resolution sensors.

Hasler, A. F.↗
NASA NTRS1995

Ammonia Observations of NGC 6334 I(N)

Coincident with the far-infrared source NGC 6334 I(N) and water maser source E is a massive dense cloud which has the most intense ammonia (1, 1) emission of any known interstellar cloud. We have mapped the (3, 3) emission and find the cloud is extended 0.8 pc in the direction parallel to the Galactic plane, and 0.5 pc perpendicular to it. It has a velocity gradient of 1 km/s.pc perpendicular to the Galactic plane. The gas kinetic temperature is about 30 K and the density is greater than 10(exp 6)/cc. The mass of the cloud is about 3000 solar mass, 3 times greater than previously estimated. The para-ammonia column density is 6 - 8 x 10(exp 15)/sq cm. An ammonia abundance of 0.5 - 1.5 x 10(exp -8) is inferred, where the larger number assumes an early time ortho/para ratio. This suggests either a cloud age of less than approximately 10(exp 6) yr, or substantial depletion of ammonia.

Kuiper, T. B. H.↗
NASA NTRS1991

CO J = 3-2 observations of translucent and high-latitude molecular clouds

Measurements were carried out on the CO J = 3-2 emission line at 345 GHz from a number of translucent and high-latitude molecular clouds, as well as on the J = 2-1 and J = 1-0 lines of both the (C-12)O and (C-13)O. It is shown that the physical conditions in the high-latitude clouds are very similar to those in the translucent clouds. The densities derived from measured (C-12)O 1-0/3-2 ratios were often found to be higher than those based on the C2 excitation, while densities derived from measured 3-2/(C-13)O 1-0 ratios were similar to those based on C2.

Van Dishoeck, Ewine F.↗
NASA NTRS1990

Aircraft measurements of electrified clouds at Kennedy Space Center, part 3

Flights made by the Special Purpose Test Vehicle for Atmospheric Research (SPTVAR) airplane during a second deployment to Florida during the summer of 1989 are discussed. The findings based on the data gathered are presented. The progress made during the second year of the project is discussed. The summer 1989 study was carried out with the support and guidance of Col. John Madura, Commander of Detachment 11, 2nd Weather Squadron, USAF, at Patrick Air Force Base (PAFB) and Cape Canaveral Air Force Station. The project goals were to develop and demonstrate techniques for measuring the electric field aloft and locating regions of charge during flight within and near clouds; to characterize the electric conditions that are presently identified as a threat to space launch vehicles; and to study the correlation between the electric field aloft and that at Kennedy Space Center's ground-based electric field mill array for a variety of electrified clouds.

Jones, J. J.↗
NASA NTRS2019

Cloud Scattering Impact on Thermal Radiative Transfer and Global Longwave Radiation

The potential importance of longwave (LW) cloud scattering has been recognized but the actual estimate of this effect on thermal radiation varies greatly among different studies. General circulation models (GCMs) generally neglect or simplify the multiple scattering in the LW. In this study, we use a rigorous radiative transfer algorithm to explicitly consider LW multiple-scattering and apply the GCM to quantify the impact of cloud LW scattering on thermal radiation fluxes. Our study shows that the cloud scattering effect on downward thermal radiation at the surface is concentrated in the infrared atmospheric window spectrum (800–1250 cm9exp −1)). The scattering effect on the outgoing longwave radiation (OLR) is also present in the window region over low clouds but it is mainly in the far-infrared spectrum (300–600 cm(exp −1)) over high clouds. For clouds with small to moderate optical depth (τ < 10), the scattering effect on thermal fluxes shows large variation with the cloud τ and has a maximum at an optical depth of ∼3. For opaque clouds, the scattering effect approaches an asymptote and is smaller and less important. The 2-stream radiative transfer scheme could have an error over 10% with an RMS error around 3.5%–4.0% in the calculated LW flux. This algorithm error of the 2-stream approximation could readily exceed the no-scattering error in the LW, and thus it is worthless to include the time-consuming computation of multiple scattering in a 2-stream radiative transfer scheme. However, the calculation error rapidly decreases as stream number increases and the RMS error in LW flux using the 4-stream scheme is under 0.3%, an accuracy sufficient for most climate studies. We implement the 4-stream discrete-ordinate algorithm in the GISS GCM and run the GCM for 20 years with and without the LW scattering effect, respectively. When cloud LW scattering is included, we find that the global annual mean OLR is reduced by 2.7 W/m(exp 2), and the downward surface flux and the net atmospheric absorption are increased by 1.6 W/m2 and 1.8 W/m(exp 2), respectively. Using one year of ISCCP clouds and running the standalone radiative transfer offline, the global annual mean non-scattering errors in OLR, surface LW downward flux and net atmospheric absorption are 3.6 W/m(exp 2), −1.1 W/m(exp 2), and −2.5 W/m(exp 2), respectively. The global scattering impact of 2.7 W/m(exp 2) on the OLR is small when compared to the typical global OLR value of 240 W/m2, but it is significant when compared to cloud LW radiative forcing (30 W/m2) and net cloud forcing (−14 W/m(exp 2)). Overall, the effect of neglecting scattering on the thermal fluxes is comparable to the reported clear sky radiative effect of doubling CO2.

longwave cloud scattering↗
NASA NTRS2012

The Namibia Early Flood Warning System, A CEOS Pilot Project

Over the past year few years, an international collaboration has developed a pilot project under the auspices of Committee on Earth Observation Satellite (CEOS) Disasters team. The overall team consists of civilian satellite agencies. For this pilot effort, the development team consists of NASA, Canadian Space Agency, Univ. of Maryland, Univ. of Colorado, Univ. of Oklahoma, Ukraine Space Research Institute and Joint Research Center(JRC) for European Commission. This development team collaborates with regional , national and international agencies to deliver end-to-end disaster coverage. In particular, the team in collaborating on this effort with the Namibia Department of Hydrology to begin in Namibia . However, the ultimate goal is to expand the functionality to provide early warning over the South Africa region. The initial collaboration was initiated by United Nations Office of Outer Space Affairs and CEOS Working Group for Information Systems and Services (WGISS). The initial driver was to demonstrate international interoperability using various space agency sensors and models along with regional in-situ ground sensors. In 2010, the team created a preliminary semi-manual system to demonstrate moving and combining key data streams and delivering the data to the Namibia Department of Hydrology during their flood season which typically is January through April. In this pilot, a variety of moderate resolution and high resolution satellite flood imagery was rapidly delivered and used in conjunction with flood predictive models in Namibia. This was collected in conjunction with ground measurements and was used to examine how to create a customized flood early warning system. During the first year, the team made use of SensorWeb technology to gather various sensor data which was used to monitor flood waves traveling down basins originating in Angola, but eventually flooding villages in Namibia. The team made use of standardized interfaces such as those articulated under the Open Cloud Consortium (OGC) Sensor Web Enablement (SWE) set of web services was good [1][2]. However, it was discovered that in order to make a system like this functional, there were many performance issues. Data sets were large and located in a variety of location behind firewalls and had to be accessed across open networks, so security was an issue. Furthermore, the network access acted as bottleneck to transfer map products to where they are needed. Finally, during disasters, many users and computer processes act in parallel and thus it was very easy to overload the single string of computers stitched together in a virtual system that was initially developed. To address some of these performance issues, the team partnered with the Open Cloud Consortium (OCC) who supplied a Computation Cloud located at the University of Illinois at Chicago and some manpower to administer this Cloud. The Flood SensorWeb [3] system was interfaced to the Cloud to provide a high performance user interface and product development engine. Figure 1 shows the functional diagram of the Flood SensorWeb. Figure 2 shows some of the functionality of the Computation Cloud that was integrated. A significant portion of the original system was ported to the Cloud and during the past year, technical issues were resolved which included web access to the Cloud, security over the open Internet, beginning experiments on how to handle surge capacity by using the virtual machines in the cloud in parallel, using tiling techniques to render large data sets as layers on map, interfaces to allow user to customize the data processing/product chain and other performance enhancing techniques. The conclusion reached from the effort and this presentation is that defining the interoperability standards in a small fraction of the work. For example, once open web service standards were defined, many users could not make use of the standards due to security restrictions. Furthermore, once an interoperable sysm is functional, then a surge of users can render a system unusable, especially in the disaster domain.

Mandl, Daniel↗
NASA NTRS2012

Heading Toward Launch with the Integrated Multi-Satellite Retrievals for GPM (IMERG)

The Day-l algorithm for computing combined precipitation estimates in GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). We plan for the period of record to encompass both the TRMM and GPM eras, and the coverage to extend to fully global as experience is gained in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following cloud motion; and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures. In this talk we summarize the major building blocks and important design issues driven by user needs and practical data issues. One concept being pioneered by the IMERG team is that the code system should produce estimates for the same time period but at different latencies to support the requirements of different groups of users. Another user requirement is that all these runs must be reprocessed as new IMERG versions are introduced. IMERG's status at meeting time will be summarized, and the processing scenario in the transition from TRMM to GPM will be laid out. Initially, IMERG will be run with TRMM-based calibration, and then a conversion to a GPM-based calibration will be employed after the GPM sensor products are validated. A complete reprocessing will be computed, which will complete the transition from TMPA.

Huffman, George J.↗
NASA NTRS1999

Studying the Fine Structure and Temporal Variations of the Zodiacal Cloud and Asteroidal Dust Bands Using the 3-Year Near-IR COBE-DIRBE Data

The report presents the results of the data analyses of the DIRBE-COBE data set to study the structure of the zodiacal cloud in the near-infrared wavebands at 1.2, 2.2, and 3.4 microns. The cloud has been divided into two components which have been analyzed and studied separately. The annual variation of the flux in the smooth or low frequency component has been measured in all three bands and the presence of any asymmetries due to the Earth's resonant ring have been studied. The high frequency component which primarily consisted of the asteroidal dust bands. Extensive and careful co-addition was done to extract the central bands in all three wavebands. The ten-degree bands are present in the 1.2 and 2.2 microns but not in the 3.4 micron waveband.

Jayaraman, Sumita↗
NASA NTRS2017

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions 'How does the Earth system respond to forcing?' and 'What are the origins and consequences of systematic model biases?' and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity. A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming? CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. 1. How well do clouds and other relevant variables simulated by models agree with observations? 2. What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models? 3. Which models have the most credible representations of processes relevant to the simulation of clouds? 4. How do clouds and their changes interact with other elements of the climate system?

carbon dioxide↗
NASA NTRSDate not supplied

Snow Depth from AMSR-2 Using Multispectral Satellite Data in an Artificial Neural Network

By using diffusion theory and Monte Carlo lidar radiative transfer simulations, Hu et al. (2022b) has derived snow depth from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. Lu et al. (2022) calculated the snow depth by applying the methods to the satellite ICESat-2 lidar measurements over the Arctic sea ice, as well as land surfaces of Northern Hemisphere. In this paper, an artificial neural network (ANN) algorithm, employing several channels from Advanced Microwave Scanning Radiometer 2 (AMSR-2) and the humidity vertical profiles from Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System for Instrument Teams (GEOS-IT) product, is trained to determine snow depth identified by time and geolocation matched 2019 ICESat-2 snow-depth data during winter months over the Arctic sea ice. The trained ANN snow-depth was applied to 2018 AMSR-2 clear pixel data, although the algorithms perform reasonably well in thinner clouds. The validation data (different from the training set) of ANN snow depth from AMSR-2 showed a good agreement with time matched and co-located snow-depth values from ICESat-2. The bias was near zero, with mean absolute error (MAE) 0.05 cm and a root-mean-square-error (RMSE) 0.08 cm. Prior applying the trained ANN snow depth to AMSR-2 data, a cloud screening algorithm was developed with a similar approach. A separate ANN cloud mask was trained to determine an AMSR-2 pixel is clear or cloudy with time and geolocation matched 2015 CALIOP Vertical Feature Mask (VFM) over Arctic sea ice. The ANN cloud mask from AMSR-2 under-estimated cloud fraction by 3-6% compared to CALIOP . The additional research is needed to conclusively evaluate the ANN cloud mask accuracy. Finally, this paper will lay the foundation for a sustained long-term snowfall and snow-storm monitoring system. The future Cloud Aerosol LIdar for Global scale Observations of the ocean-Land Atmosphere system (CALIGOLA) mission will provide a means to calculate snow depth from the lidar backscattering pathlength distribution, benefiting from the UV, visible and infrared pulses. With the calculated snow depth as the truth one could develop a machine learning algorithm, as it was done in this paper, using a passive microwave instrument available at that time to generate a wide range of snow depth data, covering extensive spatial areas in the cross-orbit direction.

Neural Network↗
NASA NTRS1993

Simultaneous observations of solar MeV particles in a magnetic cloud and in the earth's northern tail lobe - Implications for the global field line topology of magnetic clouds and for the entry of solar particles into the magnetosphere during cloud passage

Simultaneous ISEE 3 and IMP 8 spacecraft observations of magnetic fields and flow anisotropies of solar energetic protons and electrons during the passage of an interplanetary magnetic cloud show various particle signature differences at the two spacecraft. These differences are interpretable in terms of the magnetic line topology of the cloud, the connectivity of the cloud field lines to the solar surface, and the interconnection between the magnetic fields of the magnetic clouds and of the earth. These observations are consistent with a magnetic cloud model in which these mesoscale configurations are curved magnetic flux ropes attached at both ends to the sun's surface, extending out to 1 AU.

Farrugia, C. J.↗