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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Evidence linking coronal mass ejections with interplanetary magnetic clouds

Using proxy data for the occurrence of those mass ejections from the solar corona which are directed earthward, we investigate the association between the post-1970 interplanetary magnetic clouds of Klein and Burlaga and coronal mass ejections. The evidence linking magnetic clouds following shocks with coronal mass ejections is striking; six of nine clouds observed at Earth were preceded an appropriate time earlier by meter-wave type II radio bursts indicative of coronal shock waves and coronal mass ejections occurring near central meridian. During the selected periods when no clouds were detected near Earth, the only type II bursts reported were associated with solar activity near the limbs. Where the proxy solar data to be sought are not so clearly suggested, that is, for clouds preceding interaction regions and clouds within cold magnetic enhancements, the evidence linking the clouds and coronal mass ejections is not as clear; proxy data usually suggest many candidate mass-ejection events for each cloud. Overall, the data are consistent with and support the hypothesis suggested by Klein and Burlaga that magnetic clouds observed with spacecraft at 1 AU are manifestations of solar coronal mass ejection transients.

Wilson, R. M.↗
NASA NTRS1984

Are interplanetary magnetic clouds manifestations of coronal transients at 1 AU?

Using proxy data for the occurrence of those mass ejections from the solar corona which are directed earthward, the association between the post-1970 interplanetary magnetic clouds of Klein and Burlaga (1982) and coronal mass ejections is investigated. The evidence linking magnetic clouds following shocks with coronal mass ejections is striking; six of nine clouds observed at earth were preceded an appropriate time earlier by meter-wave type II radio bursts indicative of coronal shock waves and coronal mass ejections occurring near central meridian. During the selected control periods when no clouds were detected near earth, the only type II bursts reported were associated with solar activity near the limbs. Where the proxy solar data to be sought are not so clearly suggested, that is, for clouds preceding interaction regions and clouds within cold magnetic enhancements, the evidence linking the clouds and coronal mass ejections is not as clear; proxy data usually suggest many candidate mass-ejection events for each cloud.

Wilson, R. M.↗
NASA NTRS1983

Influence of clouds on the earth's radiation budget determined from GOES data

Estimates of the cloud radiative effects on the earth's regional and zonal radiation budgets derived from GOES data during November 1978 are presented. The diurnal cloud cover variability is shown to affect both the radiation-budget measurements and the estimation of the overall effect of clouds on the net flux. For this data set, the cloud cover causes a decrease in the net flux from the clear-sky value. Thus, the cloud albedo effect outweights the greenhouse effect of the clouds. It is found that the value of the change in the radiation balance is closely related to the amount of incident solar radiation and to the zonal distributions of low, middle, and high cloud cover.

Harrison, E. F.↗
NASA NTRS1985

Cloud shadow effects on remote sensing

On relatively clear days, the shadow cast by an isolated, optically dense cloud produces an effect which is similar in extent and magnitude to the adjacency effects associated with high-contrast ground albedo boundaries. A Monte Carlo radiative transfer model has been used to examine the intensity and its components, comparing the cloud shadow case with that for a Lambertian albedo boundary. Although the behavior of the total intensity is nearly the same for both cases, the behaviors of the intensity components differ significantly.

Pearce, W. A.↗
NASA NTRS2019

Turbulent Transport in the Gray Zone: A Large Eddy Model Intercomparison Study of the CONSTRAIN Cold Air Outbreak Case

To quantify the turbulent transport at gray zone length scales between 1 and 10 km the Lagrangian evolution of the CONSTRAIN cold air outbreak (CAO) case was simulated with seven large eddy models. The case is characterized by rather large latent and sensible heat fluxes, and a rapid deepening rate of the boundary layer. In some models the entrainment velocity exceeds 4 cm/s. A significant fraction of this growth is attributed to a strong longwave radiative cooling of the inversion layer. The evolution and the timing of the breakup of the stratocumulus cloud deck differ significantly among the models. Sensitivity experiments demonstrate that a decrease in the prescribed cloud droplet number concentration, and the inclusion of ice microphysics, both act to speed up the thinning of the stratocumulus by enhancing the production of precipitation. In all models the formation of mesoscale fluctuations is clearly evident in the cloud fields but also in the horizontal wind velocity. Resolved vertical fluxes remain important for scales up to 10 km. The simulation results show that the resolved vertical velocity variance gradually diminishes with a coarsening of the horizontal mesh, but the total vertical fluxes of heat, moisture, and momentum are only weakly affected. This is a promising result as it demonstrates the potential use of a mesh size dependent turbulent length scale for convective boundary layers at gray zone model resolutions.

gray zone↗
NASA NTRS1991

RADAR performance experiments

Theoretical studies and experimental results obtained at Coulommiers airport showed the capability of Proust radar to detect wind shears, in clear air condition as well as in presence of clouds or rain. Several examples are presented: in a blocking highs situation an atmospheric wave system at the Brunt-Vaisala frequency can be clearly distinguished; in a situation of clouds without rain the limit between clear air and clouds can be easily seen; and a windshear associated with a gust front in rainy conditions is shown. A comparison of 30 cm clear air radar Proust and 5 cm weather Doppler radar Ronsard will allow to select the best candidate for wind shear detection, taking into account the low sensibility to ground clutter of Ronsard radar.

Leroux, C.↗
NASA NTRSDate not supplied

Understanding Relationships Between Satellite, Model, and Ground-Based Surface Temperature Characterizations From Overcast to Clear Conditions in Support of Satellite Remote Sensing of Clouds and Radiation

Accurate and consistent global estimates of cloud coverage and their properties are fundamental to long-term Earth radiation budget (ERB) monitoring efforts like the Clouds and the Earth’s Radiant Energy System (CERES) project. Cloud detection algorithms often apply thresholding approaches to identify where clouds occur by comparing satellite-measured radiances with those that are expected under cloud-free conditions. In addition, once a cloud is detected, the derivation of cloud optical and microphysical properties also requires knowledge of the background radiances below the cloud. In the infrared, knowledge of the surface emissivity and the expected skin temperature under both cloudy and cloud-free conditions is needed. These traits are generally well known over the oceans. Over land, however, comparisons between satellite-derived land surface temperature (LST) with that characterized in numerical weather analyses reveal large differences in many parts of the world, often exceeding 5 K, which can lead to significant satellite cloud detection and cloud property retrieval errors. Furthermore, clouds have a dramatic influence on the LST, and therefore characterization of that model parameter also depends on the capability of the model to accurately resolve clouds. Thus, the LST characterized in models is, at times, a poor approximation for what would otherwise be observed, thereby impeding accurate satellite cloud retrievals. As a result, we seek to develop a more robust method for estimating the LST required for satellite cloud characterizations. This effort is accomplished through a combination of surface emission/air temperature relationship studies in all-sky conditions using ground measurement stations, along with deep neural network (DNN) estimates of expected LST under overcast and cloud-free conditions. We demonstrate that substituting DNN-predicted LST for that generated by numerical models can mitigate model-inherent diurnal dependencies and reduce overall bias and uncertainty relative to satellite/ground observations by 0.5–4 K and 0.5–2 K, respectively. It is expected that this work will lead to improved satellite cloud retrievals that enhance ERB monitoring efforts.

B Scarino↗
NASA NTRS1992

Remote Sensing Data from CLARET: A Prototype Cart Data Set

A data set containing radiation, meteorological, and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of this experiment, ARM scientists requested archival of subsets or the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. The cases range from 2 to 9.5 h in length. A pyranometer, pyrgeometer, pyrheliometer, and an infrared radiometer constituted the ensemble of instruments that provided surface radiation data. A lidar, radar, and ceilometer observed the cloud geometrical structure, and visual reports and all-sky camera observations were assimilated to provide cloud cover data. Radiosondes, wind profiler, RASS (profiling virtual temperature), microwave radiometers (observing column integrated liquid water and water vapor), and standard surface measurements provided meteorological data. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory. In addition to documenting the data set, this report describes CLARET and gives a bibliography of publications associated with the project. Some preliminary results of CLARET' research are also summarized. Simultaneous CO 2 lidar and radar backscatter measurements were shown to provide estimates of the effective radius of ice particles. Simultaneous radar and infrared radiometer data appear useful for estimating column-integrated numbers and average sizes of ice cloud particles. Ice water content obtained with this method compared favorably with values from another empirical technique using radar data alone. Depolarization of the CO 2 lidar signal from ice clouds was surprisingly small, suggesting that calculation of backscatter from nonspherical particles for this lidar is a tractable problem. Examples are also cited of CO 2 lidar measurements of the effective radius of water cloud drop size distributions and of inference of the size of pristine ice crystals that assume a particular orientation in the air. These parameters are all important to radiative transfer through clouds.

Clouds (Meteorology)↗
NASA NTRS2004

2D Analysis of In-flight Light Particles

One of the primary uses of the in-flight icing research performed aboard NASA Glenn s DHC-6 Twin Otter is for Icing Research Tunnel (IRT) and icing prediction code (Lewice) validation. Using the in-flight data to establish the IRT and Lewice as accurate simulators of actual icing conditions is crucial for supporting the research done in the Icing Branch. During test flights during the 2003 and 2004 flight season, a Natural Ice Shape Database was collected. For flights where conditions were appropriate, the aircraft is flown in an icing cloud with all ice protection systems deactivated. The duration of this period is usually determined by the pilot s ability to safely control the aircraft. When safe flight is no longer possible, the aircraft is maneuvered into clear air above the cloud layer. At this point several photographs are taken of the ice shape that was accreted on the wing test section during this icing encounter using a stereo photograph system (Figure 1). The stereo photograph system utilizes two cameras located at different locations on the fuselage that are both pointed at the same location on the wing. When both cameras take photographs of the same location at the same time, the negatives can be combined digitally to generate a two dimensional plot describing the cross-section of the ice shape. After these photographs are taken, the wing de-icing boots are activated and the ice shape is removed.

Shearer, Jonathan↗
NASA NTRSDate not supplied

Surface Radiation Budget (SRB) Release 2 Shortwave 3 hourly Data in Native Format (SRB_REL2_SW_3HRLY)

The SRB data include the average upward and downward fluxes, photosynthetically active radiative flux, aerosol and cloud optical depth, cloud fraction, and solar zenith angle measured at three hourly intervals for each day for the entire globe between 07/01/1983 and 10/31/1995. These SW surface radiative parameters were derived with the Shortwave algorithm of the NASA World Climate Research Programme/Global Energy and Water-Cycle Experiment (WCRP/GEWEX) Surface Radiation Budget (SRB) Project. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1998-07-26] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=Ranges from 1 degree (tropics and subtropics) to 120 degrees (the poles).; Temporal_Resolution=3 hourly; Temporal_Resolution_Range=3 hourly].

ALL SKY SW SURFACE DOWNWARD DIFFUSE FLUX↗
NASA NTRS2004

Cloud Detection Using Measured and Modeled State Parameters

In this study, hourly RUC analyses were used to examine the differences between RH and temperature values from RUC reanalysis data and from radiosonde atmospheric profiles obtained at the ARM SCF. The results show that the temperature observations from the SONDE and RUC are highly correlated. The RHs are also well-correlated, but the SONDE values generally exceed those from RUC. Inside cloud layers, the RH from RUC is 2-14% lower than the RH from SONDE for all RUC layers. Although the layer mean RH within clouds is much greater than the layer mean RH outside cloud or in the clear-sky, RH thresholds chosen as a function of temperature can more accurately diagnose cloud occurrence for either dataset. For overcast clouds, it was found that the 50% probability RH threshold for diagnosing a cloud, within a given upper tropospheric layer is roughly 90% for the Vaisala RS80-15LH radisonde and 80% for RUC data. While for the partial cloud (cloud amount is less than 90%), the RH thresholds of SONDE are close to RUC for a given probability in upper tropospheric layers. The probabilities of detecting clouds at a given RH and temperature should be useful for a variety of application such as the development of new cloud parameterizations or for estimating the vertical profile of cloudiness underneath a given cloud observed from the satellite to construct a 3-D cloud data set for computing atmospheric radiative heating profiles or determining potential aircraft icing conditions.

Yi, Y.↗
NASA NTRSDate not supplied

Imbalanced Multi-layer Cloud Classification with Advanced Baseline Imager (ABI) and CloudSat/CALIPSO Data

Clouds at different altitudes play different roles in Earth’s climate. Comprehensive understanding of overlapping clouds is important for climate and weather prediction. The East Pacific region is where El Ni˜no and La Ni˜na originate and where multi-layer clouds frequently occur. The overlap of clouds at different altitudes in this region increases the classification complexity for cloud-based climatological studies. Unlike prior work in cloud layer classification that assumes single layer or two-layer of clouds, in this work, we consider multi-layer cloud classification with 8 cloud-level classes (clear-sky, high, middle, low, high+middle, high+low, middle+low, high+middle+low). We develop and analyze machine learning models on features extracted from satellite images from the East Pacific regions collected by GOES Advanced Baseline Imager (ABI). These are used to classify CloudSat/CALIPSO observed multi-layer clouds. Due to the imbalanced nature of the data, we investigate the adoption of conventional resampling methods, as well as deep learning methods with data augmentation. In our experiments, we utilize the random forest classifier and Multilayer perceptron classifier with data augmentation methods to reduce the class imbalance during training. With these approaches, we achieve a classification accuracy of 83.6% without exploiting any ancillary information.

machine learning↗
DOE OSTI2022

Influence of Aerosol Embedded in Shallow Cumulus Cloud Fields on the Surface Solar Irradiance

Ubiquitous shallow cumulus clouds are associated with complex variability in surface solar irradiance (SSI). Aerosol embedded in the cloud field typically has a much smaller overall radiative effect, but can significantly perturb the shape of the SSI probability density function (PDF). These perturbations have important implications for several applications that utilize SSI, but are poorly quantified and are the subject of this study. Multiple cases of shallow cumulus cloud fields with embedded aerosol are simulated at the Southern Great Plains Atmospheric Observatory using large eddy simulation (LES). The LES-derived cloud and aerosol fields are then ingested into Monte Carlo three-dimensional (3D) radiative transfer to simulate SSI. We find a variety of perturbations to the SSI PDF that depend on aerosol presence and optical properties. The processes leading to these perturbations include extinction of the direct beam that often increases from the clear-sky region toward cloud edge due to aerosol hygroscopic growth, and scattering of radiation by aerosol into cloud shadows. The ability to predict the SSI PDF in the presence of aerosol is assessed by adding three representative aerosol optical properties into an existing machine learning framework. We show that machine learning accurately predicts the SSI PDF across a wide range of conditions with negligible computational expense. Importance metrics reveal the relatively high influence of aerosol optical properties in making the predictions. These new findings highlight the important role that aerosol plays in SSI variability for highly 3D cloud-aerosol environments and provides a computationally efficient route forward for its simulation.

3D radiative transfer↗
NASA NTRS2006

Aviation Applications for Satellite-Based Observations of Cloud Properties, Convection Initiation, In-flight Icing, Turbulence and Volcanic Ash

Advanced Satellite Aviation Weather Products (ASAP) was jointly initiated by the NASA Applied Sciences Program and the NASA Aviation Safety and Security Program in 2002. The initiative provides a valuable bridge for transitioning new and existing satellite information and products into Federal Aviation Administration (FAA) Aviation Weather Research Program (AWRP) efforts to increase the safety and efficiency of the airspace system. The ASAP project addresses hazards such as convective weather, turbulence (clear-air and cloud-induced), icing and volcanic ash and is particularly applicable in extending the monitoring of weather over data-sparse areas such as the oceans and other observationally remote locations. ASAP research is conducted by scientists from NASA, the FAA AWRP's Product Development Teams (PDT), NOAA and the academic research community. In this paper we provide a summary of activities since the inception of ASAP that emphasize the use of current-generation satellite technologies toward observing and mitigating specified aviation hazards. A brief overview of future ASAP goals is also provided in light of the next generation of satellite sensors (e.g., hyperspectral; high spatial resolution) to become operational in the 2006-2013 timeframe.

Mecikalski, John R.↗
NASA NTRS1985

Numberical simulation of the effects of radially injected barium plasma in the ionosphere

The morphology of the ion cloud in the radial shaped charge barium injection was studied. The shape of the ion cloud that remains after the explosive products and neutral barium clears away was examined. The ion cloud which has the configuration of a rimless wagon wheel is shown. The major features are the 2.5 km radius black hole in the center of the cloud, the surrounding ring of barium ion and the spokes of barium ionization radiating away from the center. The cloud shows no evolution after it emerges from the neutral debris and it is concluded that it is formed within 5 seconds of the event. A numerical model is used to calculate the motion of ions and electrons subject to the electrostatic and lorenz forces.

Swift, D. W.↗
NASA NTRS2003

Computation of Domain-Averaged Shortwave Irradiance by a One-Dimensional Algorithm Incorporating Correlations between Optical Thickness and Direct Incident Radiation

A one-dimensional radiative transfer algorithm that accounts for correlations between the optical thickness and the incident direct solar radiation is developed to compute the domain-averaged shortwave irradiance profile. It divides the direct irradiance into four components and treats the direct irradiance in two separate, clear and cloudy columns to account for the fact that clouds attenuate the direct irradiance more than clear-sky. The horizontal inhomogeneity of clouds in the cloudy column is treated by the gamma weighted two-stream approximation, which assumes that the optical thickness of clouds follows a gamma distribution. The algorithm inputs the cloud fraction, cumulative cloud fraction as a function of height, and a parameter expressing the shape of the probability density function of the cloud optical thickness distribution in addition to inputs required for a two-stream radiative transfer model. These cloud property inputs can be obtained using ground- and satellite-based instruments. Therefore, the algorithm can treat realistic cloud overlap features and horizontal inhomogeneity of clouds in a framework of one- dimensional radiative transfer. Heating rates computed by the algorithm using cloud fields generated by cloud resolving models agree with those computed with a Monte Carlo model. If optical properties in computational layers that divide a vertically extensive cloud are correlated, the irradiance profile computed by the algorithm further improves.

Kato, S.↗
NASA NTRS2019

Assimilating microwave cloudy observations into NASA GEOS model using a novel Bayesian Monte Carlo technique

Despite the importance of clouds and their influence on atmospheric water and energy balance, Numerical Weather Prediction (NWP) centers systematically exclude cloud information from the assimilation process and only assimilate clear-sky radiances (Janiskov´a et al. 2012). In order to ensure that only clear sky radiances are assimilated, strict cloud detection thresholds are applied before radiances are fed into data assimilation (DA) systems. This process not only excludes a large portion of satellite radiances, but causes loss of information in the regions that are of high interest to meteorologists and are most challenging for weather forecasts (Errico et al. 2007; Haddad et al. 2015). Although, in recent years there has been great advances in the operational weather forecasting, the prediction of tropical cyclones (TC), especially the intensity of TCs, remains challenging. According to Aksoy et al. (2013), in addition to the model deficiencies, another important factor that contributes to this challenge includes lack of observations in the peripheral environment (rain- bands) of TCs mainly because of the selective assimilation of existing observations. Satellite observations provide more than 90 % of the input data for the initialization of NWP models but more than 75 % of satellite observations are discarded due to the cloud contamination as well as land, snow, and ice emissivity issues (Bauer et al. 2010).

Rainband↗
NASA NTRS1992

Southern Hemisphere Lidar Measurements of the Aerosol Clouds from Mt. Pinatubo and Mt. Hudson

On 19 Jul., 1991, during tests to determine the ability of the newly-modified CSIRO Ns:YAG lidar to measure signals from the stratosphere before the arrival of dust from the eruption of Mt. Pinatubo, a strongly scattering layer was detected at an altitude of 2 km. That evening, the spectacular sunset and twilight were typical of volcanically disturbed conditions. Lidar measurements at 532 nm were made between 1400 and 1500 EST (0400-0500 UT) on 19 Jul. through broken cloud. Approximately 3800 laser firings were averaged in 256 shot blocks. These and subsequent data have been analyzed to produce profiles of aerosol volume backscatter function and scattering ratio. Clouds again prevented a clear view of the twilights on the next two nights, although there was some evidence for an enhanced glow. The evidence suggested that the aerosol layer had disappeared. An explanation for this disappearance and the earlier than expected arrival of the layer over Melbourne was required. Nimbus 7 TOMS data for 23 Jun. showed that the SO2 from the eruption had extended at least 11000 km to the west and that the southern boundary of the cloud had reached 15 degrees S just 8 days after the climactic eruption. It can be assumed that this cloud also contained dust and sulphuric acid aerosol. It was proposed that a section had then been broken away from the main cloud and carried south by a large scale eddy between the low latitude easterlies and the strong mid-latitude westerlies which finally carried the aerosol cloud over southern Australia. Accompanying 30 mb wind data showed a counter clockwise circulation, responsible for the transport, located in the South Atlantic Ocean.

Young, Stuart A.↗