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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluating WRF-Solar EPS cloud mask forecast using the NSRDB

Improving the accuracy of day-ahead solar forecasts using numerical weather prediction models requires improving the forecasting of cloud occurrence and properties. Validating cloud forecasts is challenging because this requires evaluating different types of clouds over a wide variety of regions. This study analyzes the cloud occurrence (or cloud mask) over the contiguous United States (CONUS), predicted by the Weather Research and Forecasting-Solar Ensemble Prediction System (WRF-Solar EPS), to identify the strengths and limitations of the model in reproducing cloud fields. To enable the in-depth analysis of cloud mask forecasts covering CONUS, we use satellite observations from the National Solar Radiation Database (NSRDB). Two evaluation methods are implemented to consider all clouds and partially removed clouds from the 2-km NSRDB in evaluating the 9-km WRF-Solar EPS cloud mask. Cloud detection metrics as well as the frequency of cloud occurrence are used to quantify the monthly performance of WRF-Solar EPS. Mismatched cloud frequency (MCF) is used to assess the model's capability to predict different types of clouds, which are classified using three levels of cloud optical depth (COD) and cloud top height (CTH). The day-ahead forecasts covering the full year of 2018 demonstrate that WRF-Solar EPS produces MCFs ranging from 27%-46%, 13%-34%, and 8%-19% for thin, mid-thickness, and thick clouds, respectively. For three CTH levels, the model shows MCFs ranging from 19%-46%, 16%-33%, and 8%-27% for low-level, middle-level, and high-level clouds, respectively. This comprehensive characterization of model performance helps identify model weakness and will eventually lead to improvements in cloud and solar radiation forecasting.

14 SOLAR ENERGY↗
NASA NTRS1992

Subvisual-thin cirrus lidar dataset for satellite verification and climatological research

A polarization (0.694 microns wavelength) lidar dataset for subvisual and thin (bluish-colored) cirrus clouds is drawn from project FIRE (First ISCCP Regional Experiment) extended time observations. The clouds are characterized by their day-night visual appearance; base, top, and optical midcloud heights and temperatures; measured physical and estimated optical cloud thicknesses; integrated linear depolarization ratios; and derived k/2 eta ratios. A subset of the data supporting 30 NOAA polar-orbiting satellite overpasses is given in tabular form to provide investigators with the means to test cloud retrieval algorithms and establish the limits of cirrus detectability from satellite measurements under various conditions. Climatologically, subvisual-thin cirrus appear to be higher, colder, and more strongly depolarizing than previously reported multilatitude cirrus, although similar k/2 eta that decrease with height and temperature are found.

Sassen, Kenneth↗
NASA NTRS2021

Modeling the Radiative Effect on Microphysics in Cirrus Clouds against Satellite Observations

The radiative effect on microphysics 23 (REM) plays an important role in the dew/frost formation near the surface. How REM impacts cirrus clouds is investigated in this paper, using bin microphysical model simulations and coincident data of the CloudSat and Global Precipitation Measurement (GPM) satellites. REM affects ice crystal spectrum with two types: radiative cooling and warming. Radiative cooling, as predicted by the bin model simulations, favors the formation of horizontally oriented ice crystals (HOICs), but radiative warming does not. Hence, a test of REM can be transformed to a test of HOICs, because HOICs can be measured by the microwave polarization observations of the GPM Microwave Imager (GMI) at 166 GHz. To analyze the GMI data for their HOIC distribution, clouds are sorted into four groups with different optical depth and altitude, based on the radiative cooling/warming ratio (or eta) computed with satellite-retrieved ice water content. Their HOIC distributions (e.g., the mid-level thick clouds have more HOICs than the high-level ones) agree well with those predicted by the bin model simulations. The general agreement between the GMI observations and bin model simulations suggests that REM is common in cirrus clouds and impacts cirrus clouds significantly.

microphysics↗
NASA NTRS1995

Extinction coefficient (1 micrometer) properties of high-altitude clouds from solar occultation measurements (1985-1990): Evidence of volcanic aerosol effect

The properties of the 1-micrometer volume extinction coefficient of two geographically different high-altitude cloud systems have been examined for the posteruption period (1985-1990) of the April 1982 El Chichon volcanic event with emphasis on the effect of volcanic aerosols on clouds. These two high-altitude cloud systems are the tropical clouds in the tropopause region observed by the Stratospheric Aerosol and Gas Experiment (SAGE) 2 and the polar stratospheric clouds (PSCs) sighted by the Stratospheric Aerosol Measurement (SAM) 2. The results indicate that volcanic aerosols alter the frequency distributions of these high-altitude clouds in such a manner that the occurrence of clouds having high extinction coefficients (6 x 10(exp -3) - 2 x 10(exp -2)/km) is suppressed, while that of clouds having low extinction coefficients (2 x 10(exp -3) - 6 x 10(exp -2)/km) is enhanced. This influence of the volcanic aerosols appears to be opposite to the increase in the extinction coefficient of optically thick clouds observed by the Earth Radiation Budget Experiment (ERBE) during the initial posteruption period of the June 1991 Pinatubo eruption. A plausible explanation of this difference, based on the Mie theory, is presented. As a consequence of the Mie theory, the effective radius of most, if not all, of the high-altitude clouds, measured by the SAGE series of satellite instruments must be less than about 0.8 micrometers. This mean cloud particle size implied by the satellite extinction-coefficient data at a single wavelength (1 micrometer) is further substantiated by the particle size analysis based on cloud extinction coefficient at two wavelengths (0.525 and 1.02 micrometers) obtained by the SAGE 2 observations. Most of the radiation measured by ERBE is reflected by cloud systems comprised of particles having effective radii much greater than 1 micrometer. A reduction in the effective radius of these clouds due to volcanic aerosols is expected to increase their extinction-coefficient values, opposite the effect observed by SAGE 2 and SAM 2. This work further illustrates the capability of the solar occultation satellite sensor to provide particulate extinction-coefficient measurements important to the study of the aerosol-cloud interactions. It is important to examine the variations of the extinction coefficient of these two high-altitude cloud systems for the posteruption years of the Pinatubo volcanic event for further evidence of the impact of volcanic aerosols on high-altitude clouds.

Wang, Pi-Huan↗
NASA NTRS1998

Infrared Low-Cloud Detection

Traditional down-looking infrared techniques for the detection and study of clouds have difficulties when clouds are within approximately 200 mbar of the surface. This is because of the lack of thermal contrast between the surface and a low cloud. We present a technique that, using a prior knowledge of the total water column, allows a down-looking high spectral resolution infrared spectrometer to recognize when a significant fraction of its field-of-view contains optically thick clouds (low-altitute or not).

clouds total water column down-looking high-spectr↗
NASA NTRS1980

Spatially resolved methane band photometry of Jupiter. III - Cloud vertical structures for several axisymmetric bands and the Great Red Spot

The paper presents cloud structure models for Jupiter's Great Red Spot, Equatorial and North Tropical Zones, North and South Temperate Zones, and North and South Polar Regions. The models are based on images of Jupiter in three methane bands and nearby continuum; radiative transfer calculations include multiple scattering and absorption from three aerosol layers. The model results include the transition in the upper-cloud altitude to 3 km lower altitude from the tropical zones to temperate zones and polar regions, a N/S asymmetry in cloud thickness in the tropical and temperature zones, and the presence of aerosols up to about 0.3 bar in the Great Red Spot and Equatorial Zone. It is concluded that polarization data are sensitive to aerosols in and above the upper cloud layer but insensitive to deeper cloud structure.

West, R. A.↗
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↗
DOE OSTI2020

Cloud Atlas: Unraveling the Vertical Cloud Structure with the Time-series Spectrophotometry of an Unusually Red Brown Dwarf

Rotational modulations of emission spectra in brown dwarf and exoplanet atmospheres show that clouds are often distributed non-uniformly in these ultracool atmospheres. The spatial heterogeneity in cloud distribution demonstrates the impact of atmospheric dynamics on cloud formation and evolution. In this study, we update the Hubble Space Telescope (HST) time-series data analysis of the previously reported rotational modulations of WISEP J004701+680352—an unusually red late-L brown dwarf with a spectrum similar to that of the directly imaged planet HR 8799e. We construct a self-consistent spatially heterogeneous cloud model to explain the HST and the Spitzer time-series observations, as well as the time-averaged spectra of WISE 0047. Additionally, in the heterogeneous cloud model, a cloud thickness variation of around one pressure scale height explains the wavelength dependence in the HST near-IR spectral variability. By including disequilibrium CO/CH 4 chemistry, our models also reproduce the redder $J-{K}_{{\rm{s}}}$ color of WISE 0047 compared to that of field brown dwarfs. We discuss the impact of vertical cloud structure on atmospheric profile and estimate the minimum eddy diffusivity coefficient for other objects with redder colors. Our data analysis and forward modeling results demonstrate that time-series spectrophotometry with a broad wavelength coverage is a powerful tool for constraining heterogeneous atmospheric structure.

79 ASTRONOMY AND ASTROPHYSICS↗
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↗
DOE OSTI2020

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

The U.S. 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 dataset, 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.

54 ENVIRONMENTAL SCIENCES↗
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.↗