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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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DOE OSTI2025

Search for a Cloud Phase Feedback in the Arctic Climate System

This project was motivated by a hypothesis involving the transition in lower troposphere temperatures across the freezing point of water. Specifically, at temperatures just below to about ten degrees below freezing, Arctic clouds should be in a mixed-phase, with strong influences from secondary ice production (e.g., the Hallett-Mossop process). At temperatures just above freezing, clouds should become entirely deglaciated. We hypothesized that, with multiple years of ARM data, a statistically significant change could be detected in cloud radiative properties and surface radiative fluxes that could be directly attributed to this phase change. Furthermore, in a gradually warming climate, these phase change-related responses in surface radiation would represent a cloud phase feedback as part of Arctic amplification. We designed this research project to coincide with a new ARM Arctic cloud radar product developed by Ed Luke and collaborators at BNL (Luke et al., 2021: PNAS, doi:10.1073/pnas.2021387118) that explicitly contains SIP cloud properties retrieved from radar data. This research project has successfully concluded after analysis of a much larger North Slope of Alaska (NSA) data sample than originally anticipated, and the results are quite different than originally hypothesized.

58 GEOSCIENCES↗

NASA NTRS2015

Urbanization Causes Increased Cloud Base Height and Decreased Fog in Coastal Southern California

Subtropical marine stratus clouds regulate coastal and global climate, but future trends in these clouds are uncertain. In coastal Southern California (CSCA), interannual variations in summer stratus cloud occurrence are spatially coherent across 24 airfields and dictated by positive relationships with stability above the marine boundary layer (MBL) and MBL height. Trends, however, have been spatially variable since records began in the mid-1900s due to differences in nighttime warming. Among CSCA airfields, differences in nighttime warming, but not daytime warming, are strongly and positively related to fraction of nearby urban cover, consistent with an urban heat island effect. Nighttime warming raises the near-surface dew point depression, which lifts the altitude of condensation and cloud base height, thereby reducing fog frequency. Continued urban warming, rising cloud base heights, and associated effects on energy and water balance would profoundly impact ecological and human systems in highly populated and ecologically diverse CSCA.

coasts↗

DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data inputs to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

cloud properties↗

NASA NTRS1992

Evidence for liquid-phase cirrus cloud formation from volcanic aerosols - Climatic implications

Supercooled droplets in cirrus uncinus cell heads between -40 and -50 C are identified from the First International Satellite Cloud Climatology Project Regional Experiment polarization lidar measurements. Although short-lived, complexes of these small liquid cells seem to have contributed importantly to the formation of the cirrus. Freezing-point depression effects in solution droplets, apparently resulting from relatively large cloud condensation nuclei of volcanic origin, can be used to explain this rare phenomenon. An unrecognized volcano-cirrus cloud climate feedback mechanism is implied by these findings.

Sassen, Kenneth↗

DOE OSTI2021

Physics-Guided Machine Learning for Prediction of Cloud Properties in Satellite-Derived Solar Data: Preprint

With over 20 years of high-resolution surface irradiance data covering most of the western hemisphere, the National Solar Radiation Database (NSRDB) is a vital public data asset. The NSRDB uses a two-step Physical Solar Model (PSM) that explicitly considers the effects of clouds and other atmospheric variables on radiative transfer. High-quality physical and optical cloud properties derived from satellite imagery are perhaps the most important data input to the PSM, representing the greatest source of radiation attenuation and scattering. However, traditional methods for cloud property retrieval have their own limitations and are unable to accurately predict cloud properties outside of nominal conditions. We introduce a physics-guided neural network that can accurately predict cloud properties when traditional methods fail or are inaccurate. Using this framework, we show reductions in relative Root Mean Square Error (RMSE) for Global Horizontal Irradiance (GHI) up to 13 percentage points for timesteps that previously had missing or low-quality cloud property data. We expect that this methodology will be effective in improving the quality of cloud property and solar irradiance data in the NSRDB.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2019

kazr2cfrpr (a1)

The Ka-band ARM Zenith Radar (KAZR) remotely probes the extent and composition of clouds at millimeter wavelengths. The KAZR is a zenith-pointing Doppler radar that operates at a frequency of approximately 35 GHz. The main purpose of this radar is to determine the first three Doppler moments (reflectivity, vertical velocity, and spectral width) at a range resolution of approximately 30 meters from near-ground to nearly 20 kilometers in altitude. The KAZR replaces the millimeter-wavelength cloud radar (MMCR) and uses a new digital receiver that provides higher spatial and temporal resolution than the MMCR. In addition, spectral artifacts in the data are significantly reduced in the KAZR, allowing researchers to study cloud dynamics much more closely than with the MMCR. KAZR data from the 2018–2019 Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina are now available as b1-level products. Building on the original CACTI operational data, the b1-level products feature improved data quality resulting from extensive analyses and corrections. The data are cross-calibrated to a common point, datastreams are corrected for operational issues that occurred during the campaign, and several data quality masks and basic derived products are incorporated. For more information, read the CACTI radar b1-level processing report.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

kazr2cfrge (a1)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

kazr2cfrmd (a1)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A Time-Gated, Time-Correlated Single-Photon-Counting Lidar to Observe Atmospheric Clouds at Submeter Resolution

Most lidars used for cloud observations have the range resolution of about 10 m, so they are incapable of resolving submeter-scale processes that are crucial to cloud evolution. This article describes a prototype of a ground-based, vertically pointing, time-gated, time-correlated single-photon-counting lidar (referred to as the T2 lidar) developed to explore atmospheric clouds at range resolution two orders of magnitude finer than traditional atmospheric lidars. The T2 lidar emits green-light pulses (532 nm) at a repetition rate of 20.6 kHz and a pulse width of ∼650 ps, which enables the observation of aerosol and cloud layers at heights from a few hundred meters to 7.28 km above the ground level at range resolution down to 10 cm. In addition, a digital delay pulse generator controls the detector to only receive photons for a short period after each laser pulse. This time-gated technique blocks photons arriving from regions outside the target zone, thus significantly reducing the noise level and allowing observation even inside clouds. Initial observations show that the T2 lidar can detect sharp cloud boundaries and fine structures near the cloud base. Such refined measurements of cloud structure could lead to an improved understanding of microphysical processes such as droplet activation, entrainment and mixing, and precipitation.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1984

Overshooting cloud top, variation of tropopause and severe storm formation

The development of severe multicell thunderstorms leading to the touchdown of six tornados near Pampa, TX, on May 19-20, 1982, is characterized in detail on the basis of weather maps, rawinsonde data, and radar summaries, and the results are compared with GOES rapid-scan IR images. The multicell storm cloud is shown to have formed beginning at 1945 GMT at the point of highest horizontal moisture convergence and lowest tropopause height and to have penetrated the tropopause at 2130 GMT, reaching a maximum altitude and a cloud-top black-body temperature 9 C lower than the tropopause temperature at 2245 GMT and collapsing about 20 min, when the firt tornado touched down. The value of the real-time vertical profiles provided by satellite images in predicting which severe storms will produce tornados or other violent phenomena is stressed.

Hung, R. J.↗

NASA NTRS1994

High altitude molecular clouds

A population of molecular clouds with a significantly greater scale height than that of giant molecular clouds (GMCs) has been identified by examining maps of the latitude distribution of the (12)CO(1 - 0) emission in the first quadrant of the Galaxy. These clouds are found by identifying emission more than 2.6 times the scale-height away from the Galactic midplane (centroid of CO emission) at the tangent points. Since the distance to the tangent points is known, we know the heights and the sizes of these clouds. They are smaller and fainter than the GMCs and do not seem to be gravitationally bound. These clouds have properties similar to the high-latitude clouds in the solar neighborhood. Although they lie outside the molecular cloud layer, the high-altitude clouds are well within the H I layer in the Galaxy and coincide with distinct peaks in the H I distribution. These clouds represent a Galaxy-wide population of small molecular clouds having a larger scale height. They may be clouds in transition between molecular and atomic phases.

Malhotra, Sangeeta↗

NASA NTRS2003

The "RED Versa NIR" Plane to Retrieve Broken-Cloud Optical Depth from Ground-Based Measurements"

A new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (MR) spectral regions is introduced. Because zenith radiance does not have a one-to-one relationship with optical depth, it is absolutely impossible to use a monochromatic retrieval. On the other side, algebraic combinations of spectral radiances such as NDCI while largely removing nouniquiness and the radiative effects of cloud inhomogeneity, can result in poor retrievals due to its insensitivity to cloud fraction. Instead, both RED and NIR radiances as points on the 'RED vs. NIR' plane are proposed to be used for retrieval. The proposed retrieval method is applied to Cimel measurements at the Atmospheric Radiation Measurements (ARM) site in Oklahoma. Cimel, a multi-channel sunphotometer, is a part of AERONET - a ground-based network for monitoring aerosol optical properties. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and Multi-Filter Rotating Shadowband Radiometers (MFRSR) located next to Cimel at the ARM site. In addition, the performance of the retrieval method is assessed using a fractal model of cloud inhomogeneity and broken cloudiness. The preliminary results look very promising both theoretically and from measurements.

Marshak, A.↗

NASA NTRS1992

Magnetic cloud passage at Earth and associated substorm activity

An approach to the study of the solar wind-magnetosphere interaction by signal type, that is, by examining the effect in the magnetosphere of well defined interplanetary structures, is presented. Focus is on the response of the magnetosphere to interplanetary magnetic clouds. Among their properties are: the slow and smooth variation of the magnetic field vector, with fluctuation level well below common interplanetary values; the similarly well behaved bulk flow; the wide range of field and flow parameters; and the longevity of passage (1 to 2 days). If the magnetic cloud is oriented such that a long period of uninterruptedly northward pointing field is followed by a long interval of continuously southward pointing field, then the transition of the magnetosphere from a quiescent state (the 'ground state') to a very active state can be studied, the latter being sustained by continued forcing from the magnetic cloud. A synopsis of the main findings of a recent study in such an interaction is given, concentrating on the substorm activity attending the second part of cloud passage.

Farrugia, C. J.↗

NASA NTRS1997

Molecular Hydrogen in Diffuse Interstellar Clouds of Arbitrary Three-Dimensional Geometry

We have constructed three-dimensional models for the equilibrium abundance of molecular hydrogen in diffuse interstellar clouds of arbitrary geometry that are illuminated by ultraviolet radiation. The position-dependent photodissociation rate of H2 in such clouds was computed with a 26 ray approximation to model the attenuation of the incident ultraviolet radiation field by dust and by H2 line absorption. We have applied our modeling technique to the isolated diffuse cloud G236+39, assuming that the cloud has a constant density and that the thickness of the cloud along the line of sight is at every point proportional to the 100 micron continuum intensity measured by IRAS. We find that our model can successfully account for observed variations in the ratio of 100 micron continuum intensity to H I column density, with larger values of that ratio occurring along lines of sight in which the molecular hydrogen fraction is expected to be the largest. Using a standard chi square analysis to assess the goodness of fit of our models, we find (at the 60 a level) that a three-dimensional model is more successful in matching the observational data than a one-dimensional model in which the geometrical extent of the cloud along the line of sight is assumed to be much smaller than its extent in the plane of the sky. If D is the distance to G236 + 39, and given standard assumptions about the rate of grain-catalyzed H2 formation, we find that the cloud has an extent along the line of sight that is 0.9 +/- 0.1 times its mean extent projected onto the plane of the sky and a gas density of 53 +/- 8 (100 pc/D) H nuclei/cc and is illuminated by a radiation field of 1.1 +/- 0.2 (100 pc/D) times the mean interstellar radiation field. The derived 100 micron emissivity per nucleon is 1.13 +/- 0.06 x 10(exp -20) MJy/sr sq cm.

Spaans, Marco↗

NASA NTRS1983

Kinetics and mechanism of the oxidation of S(IV) by ozone in aqueous solution with particular reference to SO2 conversion in nonurban tropospheric clouds

Results are presented from a laboratory study of the kinetics of the S(IV)-O3 reaction in aqueous solution, including measurements of the effects of UV radiation, dissolved transition metals, and an antioxidant (hydroquinone) on the rate. On the basis of the results, relative rates of S(IV) conversion by O3 in tropospheric cloud water are compared with those predicted for H2O2 and for O2. The reaction mechanism is discussed, with an outline given of the elements of a possible reaction scheme. Application of the rate constants obtained to SO2 conversion in cloud water predicts conversion rates by ozone to be competitive with those by H2O2 at pH above about 4.5 and to dominate at pH above about 5.5. It is pointed out that since these pH's are typical for nonurban tropospheric cloud water, ozone is a potentially important contributor to the overall oxidative conversion of SO2 to sulfate in the nonurban troposphere.

Maahs, H. G.↗

NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2005

A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗