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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2000

AROTEL Temperature Retrievals Within PSC's Using Raman Scattering

NASA Goddard Space Flight Center's Airborne Raman Ozone Temperature Lidar (AROTEL) made temperature retrievals within Polar Stratospheric Clouds (PSCs) on several flights during the SAGE III Ozone Loss and Validation Experiment (SOLVE) campaign. The location of the PSCs was confirmed using simultaneously acquired data from the NASA Langley Aerosol lidar. Retrievals were made on flight dates 991207, 991210 and 000127 from just above the aircraft to 25 kilometers geometric altitude. Raman temperature retrievals are, to first order, insensitive to Mie interference because the Raman signals are red shifted by 2331 cm(exp -1) from the initial laser wavelength. Backscattering from clouds and aerosols is consequently not observed by the detector; however, extinction does impact the measurement and limits retrievals to optically thin clouds. Comparisons between retrievals employing Rayleigh and Raman scattering show the Raman temperatures to be significantly warmer than those employing Rayleigh scattering. Uncertainties are a function of altitude: at 25 km they were approximately 3 K. Temperature profiles could not be retrieved for optically thick clouds.

Burris, John↗
NASA NTRS1999

Diffuse Reflection of Laser Light From Clouds

Laser light reflected from an aqueous suspension of particles or "cloud" with known thickness and particle size distribution defines the "cloud radiative Green's function", G. G is sensitive to cloud thickness, allowing retrieval of that important quantity. We describe a laboratory simulation of G, useful in design of an offbeam Lidar instrument for remote sensing of cloud thickness. Clouds of polystyrene microspheres suspended in water are analogous to real clouds of water droplets suspended in air. The size distribution extends from 0.5 microns to 25 microns, roughly lognormal, similar to real clouds. Density of suspended spheres is adjusted so photon mean-free-path is about 10 cm, 1000 times smaller than in real clouds. The light source is a Nd:YAG laser at 530 nm. Detectors are flux and photon-counting PMTs, with a glass probe for precise positioning. A Labview 5 VI controls position and data acquisition, via an NI Motion Control board connected to a stepper motor driving an Edmund linear slider,and a 16-channel 16-bit NI-DAQ board. The stepper motor is accurate to 10 microns. Step size is selectable. Far from the beam, the rate of exponential increase in the beam direction scales as expected from diffusion theory, linearly with cloud thickness, and inversely as the square root of the reduced optical thickness, independent of particle size. Nearer the beam the signal increases faster than exponential and depends on particle size. Results verify 3D Monte Carlo simulations that demonstrate detectability of remotely sensed offbeam returns, without filters at night, with narrow bandpass filter in day.

Cahalan, R. F.↗
NASA NTRSDate not supplied

Machine Learning Application for Improving Cloud Detection and Phase Determination Over Sunglint Regions for Geostationary Satellites

Cloud detection and phase determination over sunglint regions has been a challenge, especially for geostationary (GEO) satellites. Sunglint is observed when the sunlight specular reflection is at the same viewing angle of the satellite sensor. This intense reflection in the visible channels (VIS) is often comparable to that from optically thick clouds. It also contaminates the shortwave infrared channels (SWIR). Consequently, VIS and SWIR channels become less useful - or not useful- when they are saturated, hampering the detection of cloudy and clear-sky pixels. Sunglint contamination happens frequently and exists nearly in every daytime GEO full disk satellite images. However, sunglint intensity and region are difficult to model due to variable viewing geometry and ocean surface conditions. Moreover, existing physical models do not meet the accuracy required for operational GEO satellite cloud detection. We developed a machine learning algorithm to improve cloud detection in sunglint conditions for the NASA Langley’s Satellite ClOud and radiation Property retrieval System (SatCORPS). This poster presents our recent progress in the algorithm development, validation and applications. The algorithm is validated using collocated SatCORPS GOES-East and GOES-West cloud products. We demonstrate that the machine learning cloud detection in sunglint regions is superior to the traditional approach by improving temporal consistency between sunglint and non-sunglint conditions.

Machine Learning, Cloud detection, Sunglint, SatCO↗
NASA NTRS1979

Asymmetries of the emission lines of QSOs, Seyfert galaxies, and novae

Calculations of the anisotropy of line emission from photoionized clouds, and the resulting asymmetry in the line profiles are discussed. The permitted emission-line profiles of Seyfert galaxies and QSO's often contain more light in the red than in the violet wing, and this asymmetry can arise from self-absorption of the line radiation in an expanding system of optically thick clouds. It is shown that the Balmer line optical depths are large enough to give strongly asymmetric line profiles for pure expansion, but the observed lack of strong asymmetry in the Balmer lines of most Seyfert galaxies suggests that the broad-line widths may result from random motions, or that clouds radiate isotropically. It is concluded that the frequently observed absorption of the violet wing of Lyman-alpha must occur in a surrounding region undergoing systematic outflow, or that the weakness of the Balmer line asymmetries is explained by the Balmer line emission resulting from collisional excitation from n=2.

Ferland, G. J.↗
NASA NTRS1986

The response of cloud tops to radiative forcing

A longwave radiative transfer model was developed to study the effects on clouds of radiative loss of thermal energy from boundary layer cloud tops. Spectral properties of the drop size distributions are considered with Mie theory and LOWTRAN 6 gas transmission, which is combined with pathlength distributions from a Monte Carlo simulation, are used to obtain a 20/cm spectral resolution. Results are provided from a simulation of radiative cooling, at various wavelengths, of a 500 m thick cloud with a top at 2 km altitude. The very high values generated for the rates of cooling, of change of the liquid water content and of droplet growth rates indicate that cloud tops respond dynamically to strong thermal forcing.

Alves, A. R.↗
NASA NTRS2022

Cloud Mask Intercomparison eXercise (CMIX): An evaluation of cloud masking algorithms for Landsat 8 and Sentinel-2

Cloud cover is a major limiting factor in exploiting time-series data acquired by optical spaceborne remote sensing sensors. Multiple methods have been developed to address the problem of cloud detection in satellite imagery and a number of cloud masking algorithms have been developed for optical sensors but very few studies have carried out quantitative intercomparison of state-of-the-art methods in this domain. This paper summarizes results of the first Cloud Masking Intercomparison eXercise (CMIX) conducted within the Committee Earth Observation Satellites (CEOS) Working Group on Calibration & Validation (WGCV). CEOS is the forum for space agency coordination and cooperation on Earth observations, with activities organized under working groups. CMIX, as one such activity, is an international collaborative effort aimed at intercomparing cloud detection algorithms for moderate-spatial resolution (10–30 m) spaceborne optical sensors. The focus of CMIX is on open and free imagery acquired by the Landsat 8 (NASA/USGS) and Sentinel-2 (ESA) missions. Ten algorithms developed by nine teams from fourteen different organizations representing universities, research centers and industry, as well as space agencies (CNES, ESA, DLR, and NASA), are evaluated within the CMIX. Those algorithms vary in their approach and concepts utilized which were based on various spectral properties, spatial and temporal features, as well as machine learning methods. Algorithm outputs are evaluated against existing reference cloud mask datasets. Those datasets vary in sampling methods, geographical distribution, sample unit (points, polygons, full image labels), and generation approaches (experts, machine learning, sky images). Overall, the performance of algorithms varied depending on the reference dataset, which can be attributed to differences in how the reference datasets were produced. The algorithms were in good agreement for thick cloud detection, which were opaque and had lower uncertainties in their identification, in contrast to thin/semi-transparent clouds detection. Not only did CMIX allow identification of strengths and weaknesses of existing algorithms and potential areas of improvements, but also the problems associated with the existing reference datasets. The paper concludes with recommendations on generating new reference datasets, metrics, and an analysis framework to be further exploited and additional input datasets to be considered by future CMIX activities.

Sergii Skakun↗
NASA NTRS1975

The C/+/-CO transition in interstellar clouds

Ionized carbon recombines as the ultraviolet radiation field is attenuated inside interstellar clouds. It is proposed that C(+) is transformed into CO, the CO being formed by ion-molecule reactions of C(+) with OH and H2O. The characteristic column density of hydrogen required for the transition is approximately 3 sextillion per sq cm. The C(+)-CO transition has important implications for observations of CO and the thermal properties of sufficiently thick clouds.

Glassgold, A. E.↗
NASA NTRS2020

AWARE: The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment

The US Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) performed comprehensive meteorological and aerosol measurements, and ground-based atmospheric remote sensing at two Antarctic stations using the most advanced instrumentation available. A suite of cloud research radars, lidars, spectral and broadband radiometers, aerosol chemical and microphysical sampling equipment, and meteorological instrumentation was deployed at McMurdo Station on Ross Island from December 2015 through December 2016. A smaller suite of radiometers and meteorological equipment including radiosondes, optimized for surface energy budget measurement, was deployed on the West Antarctic Ice Sheet between 4 December 2015 and 17 January 2016. AWARE provided Antarctic atmospheric data comparable to several well-instrumented high Arctic sites that have operated for many years and that reveal numerous contrasts with the Arctic in aerosol and cloud microphysical properties. These include persistent differences in liquid cloud occurrence, cloud height and cloud thickness. Antarctic aerosol properties are also quite different from the Arctic in both seasonal cycle and composition, due to the continent’s isolation from lower latitudes by Southern Ocean storm tracks. Antarctic aerosol number and mass concentrations are not only non-negligible but perhaps play a more important role than previously recognized because of the higher sensitivities of clouds at the very low concentrations caused by the large-scale dynamical isolation. Antarctic aerosol chemical composition, particularly organic components, has implications for local cloud microphysics. The AWARE data set, fully available online in the ARM Program data archive, offers numerous case studies for unique and rigorous evaluation of mixed-phase cloud parameterization in climate models.

Atmospheric Radiation Measurement (ARM)↗
NASA NTRS1989

Marine stratocumulus structure

Thirty-three Landsat TM scenes of California stratocumulus cloud fields were acquired as part of the FIRE Marine Stratocumulus Intensive Field Observations in July 1987. They exhibit a wide variety of stratocumulus structures. Analysis has so far focused upon the July 7 scene, in which aircraft from NASA, NCAR, and the British Meteorological Office repeatedly gathered data across a stratocumulus-fair weather cumulus transition. The aircraft soundings validate the cloud base temperature threshold determined by spatial coherence analysis of the TM thermal band. Brightness variations in the stratocumulus region exhibit a -5/3 power-law decrease of the wavenumber spectra for scales larger than the cloud thickness, about 200 m, changing to a -3 power at smaller scales. Observations by an upward-looking three-channel microwave radiometer on San Nicolas Island also show the -5/3 power-law in total integrated liquid water, suggesting that the largest-scale TM brightness variations are primarily due to variations in the liquid water. The Kolmogorov 5/3 power suggests that for some purposes liquid water in turbulent stratocumulus clouds may be treated as a passive scalar, simply reflecting variations in vertical velocity. This may be tested using the velocities measured by the aircraft.

Cahalan, Robert F.↗
NASA NTRS1997

Report on the Radar/PIREP Cloud Top Discrepancy Study

This report documents the results of the Applied Meteorology Unit's (AMU) investigation of inconsistencies between pilot reported cloud top heights and weather radar indicated echo top heights (assumed to be cloud tops) as identified by the 45 Weather Squadron (45WS). The objective for this study is to document and understand the differences in echo top characteristics as displayed on both the WSR-88D and WSR-74C radars and cloud top heights reported by the contract weather aircraft in support of space launch operations at Cape Canaveral Air Station (CCAS), Florida. These inconsistencies are of operational concern since various Launch Commit Criteria (LCC) and Flight Rules (FR) in part describe safe and unsafe conditions as a function of cloud thickness. Some background radar information was presented. Scan strategies for the WSR-74C and WSR-88D were reviewed along with a description of normal radar beam propagation influenced by the Effective Earth Radius Model. Atmospheric conditions prior to and leading up to both launch operations were detailed. Through the analysis of rawinsonde and radar data, atmospheric refraction or bending of the radar beam was identified as the cause of the discrepancies between reported cloud top heights by the contract weather aircraft and those as identified by both radars. The atmospheric refraction caused the radar beam to be further bent toward the Earth than normal. This radar beam bending causes the radar target to be displayed erroneously, with higher cloud top heights and a very blocky or skewed appearance.

Wheeler, Mark M.↗
NASA NTRS1992

Lidar multiple scattering: Dependence on atmospheric parameters

Backscatter lidars are very useful tools in gaining information about the atmosphere. Inversion of backscatter signals can be used to retrieve the spatial distribution of clouds and aerosols, e.g., vertical extensions of clouds and aerosol layers, detection of 'subvisible' cirrus, etc., very accurately compared to passive radiometers. To retrieve extinction coefficient profiles, in general, the so-called lidar equation is solved. This equation describes a laser pulse which propagates through an atmosphere with transmission exp(- integral of sigma(z')dz'), which is scattered singly under 180 degrees towards a receiver, and which is attenuated on its way back again by exp(- integral of sigma(z')dz'). For inversion, further information on optical properties of the scatterers are required (extinction to backscatter ratio). However, it is evident that, at least for optically thick clouds and/or large receiver's field-of-views, this approach may be erroneous because of multiply scattered photons. Several studies were performed to simulate multiple scattering in case of collimated beams or pulses including Monte Carlo, transport, and diffusion theory. Unfortunately, most of the approaches require an enormous amount of computer time. Thus, it is meaningful to elaborate approximate methods, and one such method is discussed. Our method is based on Bissonnett (1988). We have improved the numerical simulation of limited field-of-view detectors, and compared the results to Monte Carlo calculations and an exact model of Altmann (1989).

Wiegner, Matthias↗
NASA NTRS1983

Inference of cloud temperature and thickness by microwave radiometry from space

The Scanning Multichannel Microwave Radiometer (SMMR) on the Seasat and Nimbus-7 satellites measured microwave radiation at 6.6, 10.69, 18.0, 21.0 and 37.0 GHz with both horizontal and vertical polarizations. Numerical simulations have been performed to explore the potential of using the 18.0, 21.0 and 37.0 GHz SMMR channels with simultaneous infrared measurements of cloud top height for retrieving cloud temperature differential and thickness over the ocean. The results suggest it is possible to infer cloud vertical thickness to approximately 0.4 km rms accuracy and cloud temperature differential to approximately 3 C rms. These accuracies are approximately half the a priori variances.

Pandey, P. C.↗
NASA NTRSDate not supplied

Development of a Consistent GEOsat Cloud Property Dataset for the CERES Climate Data Record

Cloud properties are critical for understanding the Earth’s radiation budget and cloud feedbacks. At NASA Langley Research Center, the Satellite ClOud and Radiative Property retrieval System (SatCORPS) provides real-time and historical analyses of clouds derived from Geostationary satellite (GEOsat) data for weather and climate applications. For the Clouds and the Earth’s Radiant Energy System (CERES) program, the global constellation of GEOsats has been analyzed since 2000 to help characterize and account for the diurnal cycle of clouds and their radiative impacts in the CERES climate data record. Obtaining consistent cloud properties over the GEOsat data record during the CERES era is a major objective but a significant challenge considering the diversity of imaging capabilities deployed during that time. The GEOsat data analysis approach for the current CERES Edition-4 (Ed4) data products was focused on accuracy and consistency with MODIS by employing as much spectral information as possible from each satellite. However, the inconsistent use of spectral information across GEOsats led to marked discontinuities in the spatial and temporal record of cloud properties that had to be accounted for post facto in downstream CERES processing. This paper reports progress in developing a new GEOsat analysis system for the next CERES edition (Ed5) that has potential to improve cross-platform consistency and continuity. In this approach, the spectral channel complement is limited to just 3-channels during daytime, ~0.65 µm (VIS), ~3.9 µm (NIR), and ~10.8 µm (IR), common to nearly all of the satellites in the record. At night, a 2-channel approach is taken with the NIR and IR, and ~6.7 µm bands that includes a machine learning approach for optically thick cloud properties. A tradeoff is the potential for reduced accuracy particularly using data from the more advanced satellites that have more spectral channels (e.g. SEVIRI, AHI and ABI) that are known to help improve thin cirrus detection, cloud-aerosol discrimination and estimates in other difficult conditions that challenge cloud remote sensing. The new continuity approach is applied to one month of global GEOSat data for each year of the CERES record since 2000 and compared with the Ed4 GEO and MODIS cloud property time series in order to evaluate the level of improved consistency in the GEOsat record and to assess the accuracy impacts. Cloud fraction will also be assessed with CALIPSO data. Outstanding issues and challenges will be discussed. The results are expected to guide future work needed to develop a more robust GEOsat cloud data record for CERES.

CERES CDR↗
NASA NTRS1992

Does UV instrumentation effectively measure ozone abundance?

Measurements of O3 on Mars provide significant information about the chemistry and composition of the atmosphere, including long-term changes. The most extensive and accurate data were inferred from the Mariner 9 UV spectrometer experiment. Mars O3 shows strong seasonal and latitudinal variation, with column abundances ranging from 0.2 microns at equatorial latitudes to 60 microns over the northern winter polar latitudes (1 micron-atm is a column abundance of 2.689 x 10(exp 15) molecules cm(exp-2)). The Mariner 9 UV spectrometer scanned from 2100 to 3500 Angstroms in one of its two spectral channels every 3 seconds with a spectral resolution of 15 Angstroms and an effective field-of-view of approximately 300 km(exp 2). Measurements were made for almost half a Martian year, with winter and spring in the Northern Hemisphere and summer and fall in the Southern Hemisphere. The detectability limit of the spectrometer was approximately 3 microns of ozone. The UV spectrometer on Mariner 9 was incapable of penetrating the dust during dust storms; the single-scattering albedo and phase function of airborne dust and cloud ice are not known to the degree required to extract the small UV signal reflected up from near the surface. The reflectance spectroscopy technique would also have difficulty detecting the total column abundance of O3 in cases where large dust abundances exist together with the polar hood, especially at high latitudes where large solar zenith angles magnify those optical depths; yet these cases would contain the maximum O3, based on theoretical results. It is quite possible that the maximum O3 column abundance observed by Mariner 9 of 60 microns is common. In fact, larger quantities may exist in some of the colder areas with optically thick clouds and dust. As the Viking period often had more atmospheric dust loading than did that of Mariner 9, the reflectance spectroscopy technique may even have been incapable of detecting the entire O3 column abundance during much of the Mars year that Viking observed, particularly at high latitudes.

Lindner, Bernhard Lee↗
NASA NTRS1977

The atmosphere of Jupiter from earth-based and spacecraft observations in the thermal infrared

The temperature and cloud structure, relative abundances of H2 and He, and the global climatology of Jupiter's atmosphere have been deduced from Pioneer 10 and 11 infrared radiometer data, along with earth-based observations of the spectrum at 8-14 and 12-24 microns. The H2 and He abundances are near those expected from 'solar' composition. The effective planetary temperature is 125 + or - 3 K. Temperatures at 1.0 bar are near 165 K and drop to 100-110 K at 0.1 bar; an overlying thermal inversion reaches 133-145 K near 0.03 bar. Temperature profiles for various regions of the planet may be quite similar, with differences due to the presence or absence of a thick cloud near 0.7 bar, close to the temperature where NH3 saturation is expected. Remaining problems in the remote sounding of Jupiter's atmosphere are accurate calibration of the global energy balance, sounding in the presence of significant heterogeneity, and temperature recovery of the thermally inverted stratosphere.

Orton, G. S.↗
NASA NTRS2013

A Simple Model of Global Aerosol Indirect Effects

Most estimates of the global mean indirect effect of anthropogenic aerosol on the Earth's energy balance are from simulations by global models of the aerosol lifecycle coupled with global models of clouds and the hydrologic cycle. Extremely simple models have been developed for integrated assessment models, but lack the flexibility to distinguish between primary and secondary sources of aerosol. Here a simple but more physically based model expresses the aerosol indirect effect (AIE) using analytic representations of cloud and aerosol distributions and processes. Although the simple model is able to produce estimates of AIEs that are comparable to those from some global aerosol models using the same global mean aerosol properties, the estimates by the simple model are sensitive to preindustrial cloud condensation nuclei concentration, preindustrial accumulation mode radius, width of the accumulation mode, size of primary particles, cloud thickness, primary and secondary anthropogenic emissions, the fraction of the secondary anthropogenic emissions that accumulates on the coarse mode, the fraction of the secondary mass that forms new particles, and the sensitivity of liquid water path to droplet number concentration. Estimates of present-day AIEs as low as 5 W/sq m and as high as 0.3 W/sq m are obtained for plausible sets of parameter values. Estimates are surprisingly linear in emissions. The estimates depend on parameter values in ways that are consistent with results from detailed global aerosol-climate simulation models, which adds to understanding of the dependence on AIE uncertainty on uncertainty in parameter values.

Clouds↗