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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 NTRSDate not supplied

Towards a Marine Stratus Climatology on Drizzle Occurrence from CALIPSO

Marine stratus are a predominant feature of our planet with the annual mean coverage exceeding 20%. They strongly reflect sunlight, yet exert only a modest effect on outgoing infrared radiation, providing a significant net cooling to the Earth’s radiative balance. Their formation is coupled to boundary layer circulations that are driven, in part, by cloud top radiative cooling and evaporative cooling from precipitation in downdrafts. Understanding how these cloud systems evolve as the climate changes is a key question that requires additional information on their lifecycle and microphysical properties to accurately represent their behavior in global circulation models. From a large-scale perspective, insight into the microphysical properties of marine stratus at cloud top can be realized through estimates of the effective radius (Re) of the droplet size distributions derived from MODIS observations. Estimates on the occurrence of rain/drizzle are available from CloudSat. Together these observations indicate that precipitation frequently occurs in clouds with higher cloud top Re. This relationship is consistent with the well documented shift in cloud top droplet size distributions towards fewer, yet larger droplets prior the onset of precipitation. Here we report on a new and complementary set observations from the CALIPSO mission. The approach derives an extinction-to-backscatter ratio (Sc, also known as the cloud lidar ratio) using an established relationship that depends on observations of the lidar attenuated backscatter and volume depolarization ratio within the cloud. Because Sc is strongly and inversely related to Re, a change in the derived Sc from higher to lower values corresponds to a change in the droplet size distribution as seen by MODIS. This change in the lidar signals at cloud top clearly identifies clouds that are capable of precipitation. The presentation provides a brief overview of the approach for deriving Sc and compares CALIOP-derived Sc with observations from other techniques. CALIOP classifications of drizzling clouds, based on the retrieved values Sc, are compared to independent, collocated assessments of drizzle occurrence reported in the standard CloudSat data products. Regional and seasonal comparisons highlight the strengths and weaknesses of the two sensors. A machine learning approach that combines information from both CALIOP and CloudSat showcases possible improvements in the global identification of scenes likely to contain rain-bearing clouds.

CALIPSO↗
NASA NTRS2010

Utilizing the MODIS 1.38 micrometer Channel for Cirrus Cloud Optical Thickness Retrievals: Algorithm and Retrieval Uncertainties

The cloud products from the Moderate Resolution Imaging Spectroradiometers (MODIS) on Terra and Aqua have been widely used within the atmospheric research community. The retrieval algorithms, however, oftentimes have difficulty detecting and retrieving thin cirrus, due to sensitivities to surface reflectance. Conversely, the 1.38 micron channel, located within a strong water vapor absorption band, is quite useful for detecting thin cirrus clouds since the signal from the surface can be blocked or substantially attenuated by the absorption of atmospheric water vapor below cirrus. This channel, however, suffers from nonnegligible attenuation due to the water vapor located above and within the cloud layer. Here we provide details of a new technique pairing the 1.38 micron and 1.24 micron channels to estimate the above/in-cloud water vapor attenuation and to subsequently retrieve thin cirrus optical thickness (tau) from attenuation-corrected 1.38 p.m reflectance measurements. In selected oceanic cases, this approach is found to increase cirrus retrievals by up to 38% over MOD06. For these cases, baseline 1.38 micron retrieval uncertainties are estimated to be between 15 and 20% for moderately thick cirrus (tau > 1), with the largest error source being the unknown cloud effective particle radius, which is not retrieved with the described technique. Uncertainties increase to around 90% for the thinnest clouds (tau < 0.5) where instrument and surface uncertainties dominate.

Meyer, Kerry↗
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↗
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)↗
NASA NTRS2019

Tropopause Laminar Cirrus and Its Role in the Lower Stratosphere Total Water Budget

Laminar cirrus are thin, extensive, isolated layers of ice clouds frequently observed in the tropical tropopause layer. Widespread laminar cirrus significantly affects tropical tropopause layer total water and thermal budget. In this study, we extract laminar cirrus from the Cloud‐Aerosol Lidar with Orthogonal Polarization Level 1 attenuated total backscatter images for January 2009, in order to characterize statistical properties of laminar cirrus cloud length, base, thickness, optical depth, and layer partial ice water path. These characteristics are used to develop an algorithm identifying laminar cirrus automatically from the Cloud‐Aerosol Lidar with Orthogonal Polarization Level 2 layer product for 2008–2017. The nearly 10‐year records reveal that tropopause laminar cirrus occurrence (30–40% of total cirrus) is strongly anticorrelated with the tropopause temperatures in that colder tropopause in frequent (super)saturation during boreal winter favors in situ formation of clouds. Interannually, anomalously warmer troposphere temperature (ΔT), easterly shear of the quasi‐biennial oscillation, and stronger upwelling branch of the Brewer‐Dobson circulation enhance laminar cirrus formation via cooling of the tropopause. The tropopause laminar cirrus carries ~0.05 mg/m(exp 3) (~0.5 ppmv) of ice water content during boreal winter and <0.01 mg/m(exp 3) during summer, which is anticorrelated with the seasonal variations of water vapor (H2O) observed by the Microwave Lime Sounder, indicating a temperature‐regulated partition between vapor and ice. Interannually, in cirrus‐rich region 1 ppmv decrease in H2O corresponds to 0.2–0.3 ppmv increase in ice water content. Frequently situated in (super)saturated air, tropopause laminar cirrus are likely to survive multiple lifecycles of the sublimation‐deposition processes, and may contribute up to 10% to the total water budget in the lower stratosphere. Satellites constantly observe thin, isolated, extensive layer of cirrus around the tropopause. The so‐called “laminar” cirrus occurrence and their ice amount are strongly regulated by temperature, such that colder temperatures favor more frequent (super)saturation, which results in more frequent laminar cirrus with more ice amount and therefore less water vapor. In this study we analyze laminar cirrus and water vapor from the Cloud‐Aerosol Lidar with Orthogonal Polarization and Microwave Lime Sounder observations, and hypothesize that laminar cirrus could act as an important transient water storage and contribute to the total water budget in the lower stratosphere.

Tao Wang↗
NASA NTRS2017

CATS Version 2 Aerosol Feature Detection and Applications for Data Assimilation

Using GEOS-5, we are developing a 1D ENS approach for assimilating CATS near real time observations of total attenuated backscatter at 1064 nm: a) After performing a 1-ENS assimilation of a cloud-free profile, the GEOS-5 analysis closely followed observed total attenuated backscatter. b) Vertical localization length scales were varied for the well-mixed PBL and the free troposphere After assimilating a cloud free segment of a CATS granule, the fine detail of a dust event was obtained in the GEOS-5 analysis for both total attenuated backscatter and extinction. Future Work: a) Explore horizontal localization and test within a cloudy aerosol layer. b) Address noisy analysis increments in the free troposphere where both CATS and GEOS-5 aerosol loadings are low. c) Develop a technique to screen CATS ground return from profiles. d) "Dynamic" lidar ratio that will evolve in conjunction with simulated aerosol mixtures.

Cloud Aerosol Transport↗
NASA NTRS2002

Cloud Algorithm Design and Performance for the 2002 Geoscience Laser Altimeter System Mission

A satellite borne lidar instrument, the Geoscience Laser Altimeter System (GLAS), is to be launched in late 2002 and will provide continuous profiling of atmospheric clouds and aerosol on a global basis. Data processing algorithms have been developed to provide operational data products in near real time. Basic data products for cloud observations are the height of the top and bottom of single to multiple cloud layers and the lidar calibrated observed backscatter cross section up to the level of signal attenuation. In addition the optical depth and vertical profile of visible extinction cross section of many transmissive cloud layers and most haze layers are to be derived. The optical thickness is derivable in some cases from the attenuation of the molecular scattering below cloud base. In other cases an assumption of the scattering phase function is required. In both cases a estimated correction for multiple scattering is required. The data processing algorithms have been tested in part from aircraft measurements used to simulated satellite data. The GLAS lidar observations will be made from an orbit that will allow inter comparison with all other existing satellite cloud measurements.

Spinhirne, J. D.↗
NASA NTRS1974

Model calculations for diffuse molecular clouds

A local steady-state isobaric model of the interstellar clouds is developed and applied to the OAO-3 observations. The model allows for cooling by C II fine-structure transitions and for inhomogeneities resulting from attenuations in the external radiations which heat the cloud constituents. Factors affecting the thermal properties of the clouds are emphasized; these include H and H2 balance, interstellar grain heating, electron density, and calcium equilibrium. The thermodynamic consequences of the attenuation of the ultraviolet interstellar radiation field are studied. The effect of varying the most important parameters and their allowed ranges is considered. Results indicate that the model is capable of reproducing the H2 fractional abundances and kinetic temperatures observed by OAO-3.

Glassgold, A. E.↗
NASA NTRS2007

Future of Land Remote Sensing: What is Needed

A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do. A viewgraph presentation describing the future of land remote sensing and the new technologies needed for clear views of the Earth is shown. The contents include: 1) Viewing the Earth; 2) Multi-Imagery; 3) May Missions and Sensors; 4) What is Needed; 5) Things to Think About; 6) Global Land Remote Sensing in Landsat 7 Era; 7) Seasonality; 8) Cloud Contamination; 9) NRC Decadal Study; 10) Atmospheric Attenuation; 11) Geo-Registration; 12) Orthorectification Required; 13) Band Registration with OLI; and 14) Things to Do.

Goward, Samuel N.↗
DOE OSTI2021

Effects of a nuclear disturbed environment on a quantum free space optical link

This manuscript investigates the potential effect of a nuclear-disturbed atmospheric environment on the signal attenuation of a ground/satellite transmitter/receiver system for both classical optical and quantum communications applications. Attenuation of a signal transmitted through the rising nuclear cloud and the subsequently transported debris is modeled climatologically for surface-level detonations of 10 kt, 100 kt, and 1 Mt. Attenuation statistics were collected as a function of time after detonation. These loss terms were compared to normal loss sources such as clouds, smoke from fires, and clear sky operation. Finally, the loss was related to the degradation of transmitted entanglement derived from Bayesian mean estimation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗
NASA NTRS1973

Atmospheric attenuation relative to earth-viewing orbital sensors

Earth viewing space missions offer exciting new possibilities in several earth resources disciplines - geography, hydrology, agriculture, geology, and oceanography, to name a few. A most useful tool in planning experiments and applying space technology to earth observation is a statistical description of atmospheric parameters. Four dimensional atmospheric models and a world wide cloud model are used to produce atmospheric attenuation models to predict degradation effects for all classes of sensors for application to earth sensing experiments from spaceborne platforms. To insure maximum utility and application of these products, the development of an interaction model of microwave energy and atmospheric variables provides a complete description of the effects of atmospheric moisture upon microwaves.

Brown, S. C.↗
NASA NTRS1975

An infrared heterodyne radiometer for high-resolution measurements of solar radiation and atmospheric transmission

A tunable, Dicke-switched, infrared heterodyne radiometer (IHR) has been designed, fabricated, tested, and used to observe solar radiation and determine the atmospheric transmissivity in the 9-11-micron spectral band. The IHR provides a spectral resolution of 0.0067 reciprocal cm, a minimum detectable power level of 2.9 times ten to the minus twenty-third power W/Hz, and a temperature resolution of less than 1 K for a source temperature of 1000 K, an IF predetection bandwidth of 100 MHz, and an integration time of 30 s. Detailed design equations and measured IHR performance are presented. The IHR was used to make solar and atmospheric transmission measurements, and a vertical-path atmospheric attenuation of 2.3 dB has been established under favorable weather conditions. The attenuation of solar radiation due to cloud cover and haze has also been investigated.

Peyton, B. J.↗
NASA NTRS1981

Optical search for lightning on Venus

Electrical signals attributed to lightning events on Venus have been observed by instruments aboard Veneras 11 and 12 and aboard the Pioneer Venus Orbiter. This paper reports the results of a search for optical pulses from the dark side of Venus made with the star sensor aboard the Pioneer Venus Orbiter. A comparison of both the frequency and amplitude distributions of received pulses with those of control experiments in which the star sensor observed deep space showed no statistically significant differences. Based on observations made during orbits 300 through 345, an upper limit of 30 flashes/sq km/yr has been derived for the average lightning frequency on the dark side of Venus. This value assumes that the amplitude distribution of lightning and the attenuation of the optical pulse by clouds on Venus are not substantially different from that occurring on earth.

Borucki, W. J.↗
NASA NTRS1989

The effects of particle loading on turbulence structure and modelling

The objective of the present research was to extend the Direct Numerical Simulation (DNS) approach to particle-laden turbulent flows using a simple model of particle/flow interaction. The program addressed the simplest type of flow, homogeneous, isotropic turbulence, and examined interactions between the particles and gas phase turbulence. The specific range of problems examined include those in which the particle is much smaller than the smallest length scales of the turbulence yet heavy enough to slip relative to the flow. The particle mass loading is large enough to have a significant impact on the turbulence, while the volume loading was small enough such that particle-particle interactions could be neglected. Therefore, these simulations are relevant to practical problems involving small, dense particles conveyed by turbulent gas flows at moderate loadings. A sample of the results illustrating modifications of the particle concentration field caused by the turbulence structure is presented and attenuation of turbulence by the particle cloud is also illustrated.

Squires, Kyle D.↗
NASA NTRS1995

Modeling Ka-band low elevation angle propagation statistics

The statistical variability of the secondary atmospheric propagation effects on satellite communications cannot be ignored at frequencies of 20 GHz or higher, particularly if the propagation margin allocation is such that link availability falls below 99 percent. The secondary effects considered in this paper are gaseous absorption, cloud absorption, and tropospheric scintillation; rain attenuation is the primary effect. Techniques and example results are presented for estimation of the overall combined impact of the atmosphere on satellite communications reliability. Statistical methods are employed throughout and the most widely accepted models for the individual effects are used wherever possible. The degree of correlation between the effects is addressed and some bounds on the expected variability in the combined effects statistics are derived from the expected variability in correlation. Example estimates are presented of combined effects statistics in the Washington D.C. area of 20 GHz and 5 deg elevation angle. The statistics of water vapor are shown to be sufficient for estimation of the statistics of gaseous absorption at 20 GHz. A computer model based on monthly surface weather is described and tested. Significant improvement in prediction of absorption extremes is demonstrated with the use of path weather data instead of surface data.

Russell, Thomas A.↗