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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Cloud Thickness from Offbeam Returns - Thor Lidar

Physical thickness of a cloud layer, and sometimes multiple cloud layers, can be estimated from the time delay of off-beam returns from a pulsed laser source illuminating one side of the cloud layer. In particular, the time delay of light returning from the outer diffuse halo of light surrounding the beam entry point, relative to the time delay at beam center, determines the cloud physical thickness. The delay combined with the pulse stretch gives the optical thickness. The halo method works best for thick cloud layers, typically optical thickness exceeding 2, and thus compliments conventional lidar which cannot penetrate thick clouds. Cloud layer top and base have been measured independently over the ARM/SGP site using conventional laser ranging (lidar) and the top minus base thickness are compared with a cloud top halo estimate obtained from the NASA/Goddard THOR System (THOR = THickness from Offbeam Returns). THOR flies on the NASA P3, and measures the halo timings from several km above cloud top, at the same time providing conventional lidar cloud top height. The ARM/SGP micropulse lidar provides cloud base height for validation.

Cahalan, R.↗
DOE OSTI2023

Let’s Unleash the Network Judgment: A Self-Supervised Approach for Cloud Image Analysis

Accurate cloud type identification and coverage analysis are crucial in understanding the Earth’s radiative budget. Traditional computer vision methods rely on low-level visual features of clouds for estimating cloud coverage or sky conditions. Several handcrafted approaches have been proposed; however, scope for improvement still exists. Newer deep neural networks (DNNs) have demonstrated superior performance for cloud segmentation and categorization. These methods, however, need expert engineering intervention in the preprocessing steps—in the traditional methods—or human assistance in assigning cloud or clear sky labels to a pixel for training DNNs. Such human mediation imposes considerable time and labor costs. We present the application of a new self-supervised learning approach to autonomously extract relevant features from sky images captured by ground-based cameras, for the classification and segmentation of clouds. We evaluate a joint embedding architecture that uses self-knowledge distillation plus regularization. We use two datasets to demonstrate the network’s ability to classify and segment sky images—one with ~85,000 images collected from our ground-based camera and another with 400 labeled images from the WSISEG database. We find that this approach can discriminate full-sky images based on cloud coverage, diurnal variation, and cloud base height. Additionally, it semantically segments the cloud areas without labels. The approach shows competitive performance in all tested tasks, suggesting a new alternative for cloud characterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Estimating Scaled Cloud Height in Pulse Jet Mixed Vessels

To suspend and mix radioactive slurries without pumps or impellers, the performance of pulsed jet mixed vessels has been investigated. The slurry in the pulse tubes is expelled impinging upon the vessel floor and lifting solids to a “cloud height” in a cyclic process. Experiments measuring cloud height for a variety of waste simulants have been conducted for vessel configurations that varied vessel diameter, fill height and pulse tube number, volume, and nozzle diameter. The elevation to which suspended particles rise is termed the cloud height and derives from a balance between the fluid forces of the jet and the gravitational forces acting on the particle ensemble. Here we use scaling to estimate the cloud height based on conservation of mass and momentum and jet similarity. We find that the cloud height varies with the nozzle exit velocity to the 2/3 power in agreement with observations.

cloud height, effective cleaning radius, effective↗
DOE OSTI2021

A Bimodal Diagnostic Cloud Fraction Parameterization. Part II: Evaluation and Resolution Sensitivity

A wide range of approaches exists to account for subgrid cloud variability in regional simulations of the atmosphere. This paper addresses the following questions: 1) Is there still benefit in representing subgrid variability of cloud in convection-permitting simulations? 2) What is the sensitivity to the cloud fraction parameterization complexity? 3) Are current cloud fraction parameterizations scale-aware across convection-permitting resolutions? These questions are addressed for regional simulations of a 6-week observation campaign in the U.S. southern Great Plains. Particular attention is given to a new diagnostic cloud fraction scheme with a bimodal subgrid saturation-departure PDF, described in Part I. The model evaluation is performed using ground-based remote sensing synergies, satellite-based retrievals, and surface observations. It is shown that not using a cloud fraction parameterization results in underestimated cloud frequency and water content, even for stratocumulus. The use of a cloud fraction parameterization does not guarantee improved cloud property simulations, however. Diagnostic and prognostic cloud schemes with a symmetric subgrid saturation-departure PDF underestimate cloud fraction and cloud optical thickness, and hence overestimate surface shortwave radiation. These schemes require empirical bias-correction techniques to improve the cloud cover. The new cloud fraction parameterization, introduced in Part I, improves cloud cover, liquid water content, cloud-base height, optical thickness, and surface radiation compared to schemes reliant on a symmetric PDF. Furthermore, cloud parameterizations using turbulence-based, rather than prescribed constant subgrid variances, are shown to be more scale-aware across convection-permitting resolutions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Stratus: An interactive steady state mixed layer model for personal computers

A steady-state, horizontally homogeneous, cloud-topped marine boundary layer model based primarily on the work of Lilly (1968) and Schubert et al., (1979) is presented. The conservative thermodynamic variables are equivalent potential temperature, theta(sub e), and total water mixing ratio, q + l. Some of the differences between this and Lilly's (1968) model are: radiation is allowed to penetrate into the boundary layer; cloud top values of longwave radiation, equivalent potential temperature, and water vapor mixing ratio are linear functions of height derived from climatological data at California coastal stations; and the closure assumption assumes a weighted average of Lilly's (1968) maximum and minimum entrainment theories. This model was programmed in FORTRAN and will run interactively on an IBM-compatible personal computer. The program allows the user to specify the geographical location, the wind speed, the sea-surface temperature, the large scale horizontal divergence, and the initial guess for cloud top height. Output includes the steady state values of cloud top and cloud base height, mixed layer equivalent potential temperature and total water mixing ratio, and the associated convective and radiative fluxes.

Guinn, Thomas A.↗
NASA NTRS2004

Real-Time Cloud, Radiation, and Aircraft Icing Parameters from GOES over the USA

A preliminary new, physically based method for realtime estimation of the probability of icing conditions has been demonstrated using merged GOES-10 and 12 data over the continental United States and southern Canada. The algorithm produces pixel-level cloud and radiation properties as well as an estimate of icing probability with an associated intensity rating Because icing depends on so many different variables, such as aircraft size or air speed, it is not possible to achieve 100% success with this or any other type of approach. This initial algorithm, however, shows great promise for diagnosing aircraft icing and putting it at the correct altitude within 0.5 km most of the time. Much additional research must be completed before it can serve as a reliable input for the operational CIP. The delineation of the icing layer vertical boundaries will need to be improved using either the RUC or balloon soundings or ceilometer data to adjust the cloud base height, a change that would require adjustment of the cloud-top altitude also.

Minnis, Patrick↗
NASA NTRS1994

Study of atmospheric parameters measurements using MM-wave radar in synergy with LITE-2

The Lidar In-Space Technology Experiment, (LITE), has been developed, designed, and built by NASA Langley Research Center, to be flown on the space shuttle 'Discovery' on September 9, 1994. Lidar, which stands for light detecting and ranging, is a radar system that uses short pulses of laser light instead of radio waves in the case of the common radar. This space-based lidar offers atmospheric measurements of stratospheric and tropospheric aerosols, the planetary boundary layer, cloud top heights, and atmospheric temperature and density in the 10-40 km altitude range. A study is being done on the use, advantages, and limitations of a millimeterwave radar to be utilized in synergy with the Lidar system, for the LITE-2 experiment to be flown on a future space shuttle mission. The lower atmospheric attenuation, compared to infrared and optical frequencies, permits the millimeter-wave signals to penetrate through the clouds and measure multi-layered clouds, cloud thickness, and cloud-base height. These measurements would provide a useful input to radiation computations used in the operational numerical weather prediction models, and for forecasting. High power levels, optimum modulation, data processing, and high antenna gain are used to increase the operating range, while space environment, radar tradeoffs, and power availability are considered. Preliminary, numerical calculations are made, using the specifications of an experimental system constructed at Georgia Tech. The noncoherent 94 GHz millimeter-wave radar system has a pulsed output with peak value of 1 kW. The backscatter cross section of the particles to be measured, that are present in the volume covered by the beam footprint, is also studied.

Andrawis, Madeleine Y.↗
NASA NTRS1990

Comparison and calibration of NCAR electra instruments: July 5 and 7, 1987

Measurements of temperature, water vapor, cloud liquid water, and lidar cloud height taken by the National Center for Aeronautical Research (NCAR) Electra are analyzed for two days of the First ISCCP Regional Experiment (FIRE) stratocumulus field program. Examination of instrument time series, correlations between sensors, soundings through the layer, and lidar measurements of cloud base height are used to correct sensor offset problems, check for probe wetting, and choose the most accurate measurements of temperature, humidity, and cloud liquid water.

Austin, Philip H.↗
NASA NTRS2019

Fusion of Surface Ceilometer Data and Satellite Cloud Retrievals in 2D Mesh Interpolating Model with Clustering

For accurate cloud ceiling information, a data fusion approach is proposed that utilizes satellite data to extend surface station information to much wider areas. Cloud base height (CBH) retrieved from satellite observations provides for much larger spatial coverage and higher resolution. The direct comparison of GOES-16 CBH with surface station ceiling yields a local bias that has to be corrected for in the initial GOES-16 cloud base information. This sparsely sampled bias correction presents an irregular 2D mesh of control points, which is then interpolated by constructing a continuous smooth field using polyharmonic splines. The influence of remote stations is restricted by grouping the control points into clusters depending on an effective distance. This cluster-based approach allows for constructing separate spline surfaces corresponding to physically different clouds. The obtained continuous bias correction function is then applied to the entire GOES-16 pixel level CBH except for areas far away from surface stations in data sparse regions such as offshore. The described method is currently being tested using daytime-only observations over the central and eastern United States. Overall, this approach has potential to provide more accurate, high spatial resolution cloud ceiling information for the aviation community.

Khlopenkov, Konstantin↗
DOE OSTI2023

Relationships among diurnal variations of polar night cloud, precipitation, surface temperatures, and the fair-weather return current of the global electric circuit (GEC)

Over the past five years (June 2017-current), the vertical electric field (E z ) as well as numerous cloud, precipitation and radiation properties have been monitored at the Department of Energy-Atmospheric Radiation Measurement (DOE ARM) North Slope of Alaska (NSA) field site. Comparisons between the composite diurnal averaged fair-weather E z , and composite ceilometer derived cloud base height during the polar night, reveal a significant correlation between the parameters (r = 0.62), supporting previous studies that there is high correlation between local electric field and cloud properties. With the use of extensive instrumentation at the site, such as the Micro Pulse Lidar (MPL), Ka-band Zenith Radar (KAZR), ceilometer, SKYRAD, Precipitation Imaging Package (PIP), among others, this study provides a more comprehensive examination of the diurnal cycle of cloud and precipitation properties along with the localized fair-weather return current of the larger Global Electric Circuit (GEC) system. Comparisons between the composite diurnal averaged fair-weather E z , and cloud thickness, maximum column backscatter, and precipitation particle counts all show similar diurnal variability during the polar night, indicating that during the largest magnitude fair weather E z time periods, clouds bases tend to be higher, clouds are thicker, have a larger column backscatter, and display more precipitating particles. Furthermore, a slight diurnal variability in the polar night surface temperature was found to be highly correlated (r = 0.87) to the longwave downwelling irradiance measured by SKYRAD, indicating that the variations in the physical properties of local clouds could modulate the diurnal polar night surface temperature variability on the order of 0.5 °C/day. In conclusion, these findings emphasize the importance and global nature of the GEC system, with the global aggregate of thunderstorms and electrified clouds potentially influencing polar night cloud properties as well as diurnal wintertime polar surface temperature variation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

KAZR Hydrometeor and Insect Masks

The Ka-band ARM zenith pointing radar (aka, KAZR) is so sensitive that it detects cloud particles and individual insects. While detecting insects with Ka-band radar is beneficial and desirable to advance radar entomology, this sensitivity can be detrimental to radar meteorology because insects could be interpreted as clouds or precipitation. For example, misclassifying insects as clouds has been a problem for the ARM Active Remote Sensing of Clouds (ARSCL) Value Added Product since its inception (Clothiaux et al. 2000). Based on cloud particle and insect radar scattering properties, an algorithm was developed that identifies clouds, raindrops, ice particles, and insects in KAZR co- and cross-polarimeteric Doppler velocity spectra. The algorithm produces affirmative masks in the KAZR native time and height resolution indicating time-height locations of hydrometeors and insects. The hydrometeor mask contains binary information (e.g., yes/no hydrometeor presence), and the insect mask includes a proxy for insect activity that increases when more insects are detected in the Doppler velocity spectra. The algorithm was developed using KAZR medium sensitivity mode (MD) observations and was applied to two summer seasons of KAZR observations at the Southern Great Plains (SGP) Central Facility: May-October 2018 and 2019. In the future, this data set will be expanded to include other KAZR operating modes and observations from other ARM field sites. Details of the algorithm and data set can be found in: Williams, C.R., K.L. Johnson, S.E. Giangrande, J. C. Hardin, R. Oktem, and D. M. Romps, 2021: Identifying Insects, Clouds, and Precipitation using Vertically Pointing Polarimetric Radar Doppler Velocity Spectra. Atmospheric Measurement Techniques, submitted 6-Feb-2021. https://amt.copernicus.org/preprints/amt-2021-27/#discussion.For more information on the ARSCL VAP, see Clothiaux, E. E., T. P. Ackerman, G. G. Mace, K. P. Moran, R. T. Marchand, M. A. Miller, and B. E. Martner, 2000; J. Appl. Meteor., 39, 645-665.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

A numerical modeling study of a Montana thunderstorm. I - Model results versus observations involving nonelectrical aspects. II - Model results versus observations involving electrical aspects

Model results and the observed cloud behavior are examined in terms of nonelectrical and electrical aspects of a thunderstorm. The characteristics of the two-dimensional, time-dependent atmospheric electricity model used to simulate the cloud observations of July 19, 1981 in Miles City, Montana are described. The interactions of the dynamics and microphysics of the cloud with the charge separation mechanisms are analyzed. It is observed that the model accurately represents many of the observed characteristics of the cloud; however, the cloud base height, maximum liquid water content, and the time from first formation of precipitation until it reaches the ground are not accurately modeled. It is found that the model adequately represents the electrical field structure of the cloud and the electrical field strengths.

Helsdon, John H., Jr.↗
NASA NTRS1990

Overview of the 27-28 October FIRE Cirrus IFO case: Meteorology and cloud fields

A detailed description of the meteorology of the 27 and 28 October FIRE Cirrus IFO case is presented. The progression of synoptic scale events over the region is reviewed including the evolution of surface and upper air features, i.e., the surface cyclone that formed to the west over Montana on the 27th and moved through Wisconsin late on the 28th and the associated short wave ridge aloft. A summary of the corresponding cloud conditions observed over the area of aircraft operations is given including characterization of the cloud forms and cloud heights based on information derived from debriefings of the aircrews, surface observations, airborne (ER-2) and surface lidars observations and satellite imagery (GOES). The correspondence between the resolved meteorological features (subsynoptic rawinsonde network) and the development of cloud layers is illustrated. In particular, the discussion emphasizes the relationship between vertical thermodynamic structure and the character and vertical structure of the cloud fields. The role of the larger scale in maintaining the observed vertical structure is quantified both with respect to its control via forced ascent and advective processes. Based on results of these analyses, conclusions are drawn with respect to the design of future field missions.

Starr, David OC.↗
DOE OSTI2020

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Correlations among the Optical Properties of Cirrus-Cloud Particles: Microphysical Interpretation

Cirrus measurements obtained with a ground-based polarization Raman lidar at 67.9 deg N in January 1997 reveal a strong positive correlation between the particle optical properties, specifically depolarization ratio delta(sub par) and extinction- to-backscatter (lidar) ratio S, for delta(sub par) less than approximately 40%, and an anti-correlation for delta(sub par) greater than approximately 40%. Over the length of the measurements the particle properties vary systematically. Initially, delta (sub par) approximately equals 60% and S approximately equals 10sr are observed. Then, with decreasing delta(sub par), S first increases to approximately 27sr (delta(sub par) approximately equals 40%) before decreasing to values around 10sr again (delta(sub par) approximately equals 20%). The analysis of lidar humidity and radiosonde temperature data shows that the measured optical properties stem from scattering by dry solid ice particles, while scattering by supercooled droplets, or by wetted or subliming ice particles can be excluded. For the microphysical interpretation of the lidar measurements, ray-tracing computations of particle scattering properties have been used. The comparison with the theoretical data suggests that the observed cirrus data can be interpreted in terms of size, shape, and, under the assumption that the lidar measurements of consecutive cloud segments can be mapped on the temporal development of a single cloud parcel moving along its trajectory, growth of the cirrus particles: Near the cloud top in the early stage of cirrus development, light scattering by nearly isometric particles that have the optical characteristics of hexagonal columns (short, column-like particles) is dominant. Over time the ice particles grow, and as the cloud base height extends to lower altitudes characterized by warmer temperatures they become morphologically diverse. For large S and depolarization values of approximately 40%, the scattering contributions of column- and plate-like particles are roughly the same. In the lower ranges of the cirrus clouds, light scattering is predominantly by plate-like ice particles. This interpretation assumes random orientation of the cirrus particles. Simulations with a simple model suggest, however, that the positive correlation between S and delta(sub par) which is observed for depolarization ratios less than 40% mainly at low cloud altitudes, can be alternatively explained by horizontal alignment of a fraction of the cirrus particle population.

Reichardt, J.↗