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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

Large-scale reflection and absorption of solar radiation by clouds as influencing earth radiation budgets - New aircraft measurements.

Discussion of the first results of extensive recent aircraft measurements, in the short wavelengths, of the reflection and absorption properties of clouds and their impact on radiation budget studies. From the data obtained, the albedo of typical cloud types was determined integrally and spectrally. Some preliminary results are also offered for short-wave absorption and the apparent transmission of clouds. The effect of the atmospheric pathlength between sensor and target, exhibited through molecular scattering and aerosol scattering and absorption, is included in the data analysis. Results are also presented on vertical (short-wave) radiative flux profiles, within specific wavelength intervals, from near sea level to altitudes of about 40,000 ft over relatively short time intervals.

Drummond, A. J.↗
NASA NTRS1990

On the interannual variation of the earth radiation balance

The interannual variability of the top of the atmosphere net radiation budget as measured from the Nimbus-7 earth radiation budget instruments was calculated for an eight-year period 1979-1986. The largest fluctuations are shown to occur in three tropical areas: the Atlantic off the west coast of Africa, the eastern Pacific near South America, and the western Pacific northeast of Indonesia. The variability in the Atlantic was 20 percent greater than in the eastern Pacific and 35 percent greater than in the Indonesian area. The maximum anomalies in these two Pacific regions occurred during the El Nino year 1982-1983, while the maximum Atlantic anomalies, south of the Gulf of Guinea, were during 1984. An independent data set of derived cloud type and amount from the Temperature Humidity Infrared Radiometer and the Total Ozone Mapping Spectrometer instruments shows interannual changes in multilevel convective cloud systems have a minimal effect of the net balance. However, changes in middle and low clouds drastically affect the balance, and are the most likely cause of the maximum radiation balance variability in the Gulf of Guinea region. This observed interannual variation of the top of the atmosphere net balance denotes the most variable 'cloud radiative forcing' situation observed to date.

Randel, David L.↗
NASA NTRS2016

Observation-Based Cloud Radiative Kernels from A-Train

We develop a method to empirically derive broadband and spectral cloud radiative kernels by cloud type from pixel-scale collocated A-Train observations and reanalysis, which does not require additional cloudy radiative transfer calculations nor cloud properties. This method is able to estimate the cloud feedback by maintaining the consistency between CRKs and cloud responses.

Yue, Qing↗
DOE OSTI2020

Cloud regimes over the Amazon Basin: perspectives from the GoAmazon2014/5 campaign

Abstract. Radiosonde observations collected during the GoAmazon2014/5 campaign are analyzed to identify the primary thermodynamic regimes accompanying different modes of convection over the Amazon. This analysis identifies five thermodynamic regimes that are consistent with traditional Amazon calendar definitions of seasonal shifts, which include one wet, one transitional, and three dry season regimes based on a k-means cluster analysis. A multisensor ground-based approach is used to project associated bulk cloud and precipitation properties onto these regimes. This is done to assess the propensity for each regime to be associated with different characteristic cloud frequency, cloud types, and precipitation properties. Additional emphasis is given to those regimes that promote deep convective precipitation and organized convective systems. Overall, we find reduced cloud cover and precipitation rates to be associated with the three dry regimes and those with the highest convective inhibition. While approximately 15 % of the dataset is designated as organized convection, these events are predominantly contained within the transitional regime.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Radar sensitivity and antenna scan pattern study for a satellite-based Radar Wind Sounder (RAWS)

Modeling global atmospheric circulations and forecasting the weather would improve greatly if worldwide information on winds aloft were available. Recognition of this led to the inclusion of the LAser Wind Sounder (LAWS) system to measure Doppler shifts from aerosols in the planned for Earth Observation System (EOS). However, gaps will exist in LAWS coverage where heavy clouds are present. The RAdar Wind Sensor (RAWS) is an instrument that could fill these gaps by measuring Doppler shifts from clouds and rain. Previous studies conducted at the University of Kansas show RAWS as a feasible instrument. This thesis pertains to the signal-to-noise ratio (SNR) sensitivity, transmit waveform, and limitations to the antenna scan pattern of the RAWS system. A dop-size distribution model is selected and applied to the radar range equation for the sensitivity analysis. Six frequencies are used in computing the SNR for several cloud types to determine the optimal transmit frequency. the results show the use of two frequencies, one higher (94 GHz) to obtain sensitivity for thinner cloud, and a lower frequency (24 GHz) to obtain sensitivity for thinner cloud, and a lower frequency (24 GHz) for better penetration in rain, provide ample SNR. The waveform design supports covariance estimation processing. This estimator eliminates the Doppler ambiguities compounded by the selection of such high transmit frequencies, while providing an estimate of the mean frequency. the unambiguous range and velocity computation shows them to be within acceptable limits. The design goal for the RAWS system is to limit the wind-speed error to less than 1 ms(exp -1). Due to linear dependence between vectors for a three-vector scan pattern, a reasonable wind-speed error is unattainable. Only the two-vector scan pattern falls within the wind-error limits for azimuth angles between 16 deg to 70 deg. However, this scan only allows two components of the wind to be determined. As a result, a technique is then shown, based on the Z-R-V relationships, that permit the vertical component (i.e., rain) to be computed. Thus the horizontal wind components may be obtained form the covariance estimator and the vertical component from the reflectivity factor. Finally, a new candidate system is introduced which summarizes the parameters taken from previous RAWS studies, or those modified in this thesis.

Stuart, Michael A.↗
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↗
NASA NTRS2017

Global Statistics of Microphysical Properties of Cloud-Top Ice Crystals

Ice crystals in clouds are highly complex. Their sizes, macroscale shape (i.e., habit), mesoscale shape (i.e., aspect ratio of components) and microscale shape (i.e., surface roughness) determine optical properties and affect physical properties such as fall speeds, growth rates and aggregation efficiency. Our current understanding on the formation and evolution of ice crystals under various conditions can be considered poor. Commonly, ice crystal size and shape are related to ambient temperature and humidity, but global observational statistics on the variation of ice crystal size and particularly shape have not been available. Here we show results of a project aiming to infer ice crystal size, shape and scattering properties from a combination of MODIS measurements and POLDER-PARASOL multi-angle polarimetry. The shape retrieval procedure infers the mean aspect ratios of components of ice crystals and the mean microscale surface roughness levels, which are quantifiable parameters that mostly affect the scattering properties, in contrast to a habit. We present global statistics on the variation of ice effective radius, component aspect ratio, microscale surface roughness and scattering asymmetry parameter as a function of cloud top temperature, latitude, location, cloud type, season, etc. Generally, with increasing height, sizes decrease, roughness increases, asymmetry parameters decrease and aspect ratios increase towards unity. Some systematic differences are observed for clouds warmer and colder than the homogeneous freezing level. Uncertainties in the retrievals will be discussed. These statistics can be used as observational targets for modeling efforts and to better constrain other satellite remote sensing applications and their uncertainties.

Van Diedenhoven, Bastiaan↗
NASA NTRS1982

Microwave noise temperature and attenuation of clouds - Statistics of these effects at various sites in the United States, Alaska, and Hawaii

The microwave attenuation and noise temperature effects of clouds can result in serious degradation of telecommunications link performance, especially for low-noise systems presently used in deep-space communications. Although cloud effects are generally less than rain effects, the frequent presence of clouds will cause some amount of link degradation a large portion of the time. This paper presents a general review of cloud types and their water particle densities, attenuation and noise temperature calculations, and basic link signal-to-noise ratio calculations. Tabular results of calculations for 12 different cloud models are presented for frequencies in the range 10-50 GHz. Curves of average-year attenuation and noise temperature statistics at frequencies ranging from 10 to 90 GHz, calculated from actual surface and radiosonde observations, are given for 15 climatologically distinct regions in the contiguous United States, Alaska, and Hawaii. Nonuniform sky cover is considered in these calculations.

Slobin, S. D.↗
NASA NTRS1986

Investigation of clouds spatial distribution using ground-based lidar

Certain investigations of spatial distribution of clouds by employing ground based lidar are presented. The great changeability is one of the main properties of the clouds in the boundary layer. As a result, their optical properties change rapidly which complicates the modeling of cloud evolution. Suitable equipped lidars are widely used for diagnostics of the clouds via a number of scattering and absorption processes. In particular, lidar can provide information on the distribution of meteorological parameters and of the other important cloud characteristics both in vertical and horizontal directions. Herein the time and spatial distribution of the aerosol backscattering coefficient of S sub t and S sub c type clouds are investigated by means of a correlation analysis of the lidar obtained data provided from several arbitrary directions and heights.

Kolev, I. N.↗
NASA NTRS1993

Homogeneous ice nucleation and supercooled liquid water in orographic wave clouds

This study investigates ice nucleation mechanisms in cold lenticular wave clouds, a cloud type characterized by quasi-steady-state air motions and microphysical properties. It is concluded that homogeneous ice nucleation is responsible for the ice production in these clouds at temperatures below about -33 C. The lack of ice nucleation observed above -33 C indicates a dearth of ice-forming nuclei, and hence heterogeneous ice nucleation, in these clouds. Aircraft measurements in the temperature range -31 to -41 C show the following complement of simultaneous and abrupt changes in cloud properties that indicate a transition from the liquid phase to ice: disappearance of liquid water; decrease in relative humidity from near water saturation to ice saturation; increase in mean particle size; change in particle concentration; and change in temperature due to the release of latent heat. A numerical model of cloud particle growth and homogeneous ice nucleation is used to aid in interpretation of our in situ measurements. The abrupt changes in observed cloud properties compare favorably, both qualitatively and quantitatively, with results from the homogeneous ice nucleation model. It is shown that the homogeneous ice nucleation rates from the measurements are consistent with the temperature-dependent rates employed by the model (within a factor of 100, corresponding to about 1 C in temperature) in the temperature range -35 deg to -38 C. Given the theoretical basis of the modeled rates, it may be reasonable to apply them throughout the -30 to -50 C temperature range considered by the theory.

Heymsfield, Andrew J.↗
NASA NTRS2010

Characterization of Cloud Water-Content Distribution

The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.

Lee, Seungwon↗
DOE OSTI2024

Areal-Averaged Surface Albedo (ArealAveAlb) Value-Added Product

The surface albedo plays an important role in the Earth's radiation balance. This report provides information on how to estimate areal-averaged surface albedo from ground-based measurements of solar radiation at five wavelengths (415,500,615,675, and 870 nm). The report first explains why this estimation is important and challenging. Then the report defines both the required and complimentary inputs for the corresponding Areal-Averaged Surface Albedo (ArealAveAlb) Value-Added Product (VAP) and highlights the major outputs of this VAP. The following section explains how estimation of the areal-averaged surface albedo at four wavelengths (500,615,675, and 870 nm) can be performed for different surface types, including those partly covered by snow. The final section provides three examples that illustrate the VAP’s performance and emphasizes the benefits of complementary inputs, such as distinct cloud types and precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Microwave noise temperature and attenuation of clouds at frequencies below 50 GHz

The microwave attenuation and noise temperature effects of clouds can result in serious degradation of telecommunications link performance, especially for low-noise systems presently used in deep-space communications. Although cloud effects are generally less than rain effects, the frequent presence of clouds will cause some amount of link degradation a large portion of the time. Cloud types, water particle densities, radiative transfer, attenuation and noise temperature calculations are reviewed and examples of basic link signal to noise ratio calculations are given. Calculations for twelve different cloud models are presented for frequencies of from 1 to 50 GHz and elevation angles of 30 degrees and 90 degrees. These case results may be used as a handbook to predict noise temperature and attenuation values for known or forecast cloud conditions.

Slobin, S. D.↗
NASA NTRS1992

Arctic cloudiness - Comparison of ISCCP-C2 and Nimbus-7 satellite-derived cloud products with a surface-based cloud climatology

One surface-based and two satellite arctic cloud climatologies are compared in terms of the annual cycle and spatial patterns of total monthly cloud amounts. Additionally, amounts and spatial patterns of low, middle, and high cloud type are compared. The surface-based dataset is for the years 1951-81, while the satellite-based data are for 1979-85 and 1983-86. The satellite cloud amounts are generally 5-35 percent less than the surface observations over the entire Arctic. However, regional differences may be as high as 45 percent. During July the surface-based cloud amounts for the central Arctic are about 40 percent greater than the satellite-based, but only 10 percent greater in the Norwegian Sea area. Surprisingly, (ISCCP) cloud climatology and surface observations agree better during winter than during summer. Possible reasons for these differences are discussed.

Schweiger, Axel J.↗
NASA NTRSDate not supplied

NASA GLOBE CLOUD GAZE: Creating Data Quality Flags for Citizen Science Cloud Observations Matched to NASA Satellite Data

The GLOBE Program, NASA’s largest and longest lasting citizen science program about the Earth, has been collecting cloud observations matched to multiple satellite data daily. The program’s cloud protocol is historically the most popular protocol as your eyes are the only instruments you need to collect observations of the sky. This dataset includes over 3,300,000 cloud observations with variables like total cloud cover, cloud type and opacity that are collocated to the nearest overpass times of geostationary satellites (GOES-15, GOES-16, GOES-17, Meteosat-8, Meteosat-11, or Himawari-8), or to Clouds and the Earth’s Radiant Energy System (CERES) instruments onboard Aqua and Terra, or the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. In order to increase the usability of this dataset, the Community science project Leveraging Online and User Data through GLOBE And Zooniverse Engagement (CLOUD GAZE) has been developed to generate data quality flags of these ground-up and top-down perspectives of sky and clouds. Recently funded through NASA’s Citizen Science for Earth Systems Program, CLOUD GAZE has partnered with the Zooniverse online platform to obtain reference data and image tagging of sky photographs collected through The GLOBE Program’s clouds protocol. This paper will present the GLOBE Clouds dataset matched to NASA satellite data, integration of CLOUD GAZE to develop data quality flags, and research applications of the dataset (includes ground-up and top-down perspective comparisons, ground observations of dust storms and smoke plumes, and cloud observations in polar regions). The paper will also present on techniques and recommendations for classroom use and for community engagement, particularly for those looking to online resources.

Marilé Colón Robles↗
NASA NTRS2013

Vertical Structure of Ice Cloud Layers From CloudSat and CALIPSO Measurements and Comparison to NICAM Simulations

The shape of the vertical profile of ice cloud layers is examined using 4 months of CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) global measurements taken on January, April, July, and October 2007. Ice clouds are selected using temperature profiles when the cloud base is located above the 253K temperature level. The obtained ice water content (IWC), effective radius, or extinction coefficient profiles are normalized by their layer mean values and are expressed in the normalized vertical coordinate, which is defined as 0 and 1 at the cloud base and top heights, respectively. Both CloudSat and CALIPSO observations show that the maximum in the IWC and extinction profiles shifts toward the cloud bottom, as the cloud depth increases. In addition, clouds with a base reaching the surface in a high-latitude region show that the maximum peak of the IWC and extinction profiles occurs near the surface, which is presumably due to snow precipitation. CloudSat measurements show that the seasonal difference in normalized cloud vertical profiles is not significant, whereas the normalized cloud vertical profile significantly varies depending on the cloud type and the presence of precipitation. It is further examined if the 7 day Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulation results from 25 December 2006 to 1 January 2007 generate similar cloud profile shapes. NICAM IWC profiles also show maximum peaks near the cloud bottom for thick cloud layers and maximum peaks at the cloud bottom for low-level clouds near the surface. It is inferred that oversized snow particles in the NICAM cloud scheme produce a more vertically inhomogeneous IWC profile than observations due to quick sedimentation.

Ham, Seung-Hee↗
DOE OSTI2025

The NASA ACTIVATE Mission

The NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) conducted 162 joint flights with two aircraft over the northwest Atlantic to study aerosol–cloud interactions (ACIs), which represent the largest uncertainty in estimating total anthropogenic radiative forcing. The combination of a high-flying King Air and low-flying HU-25 Falcon, equipped with remote sensing and in situ instruments, characterized trace gases, aerosol particles, clouds, and meteorological variables with data collected nearly simultaneously below, within, and above marine boundary layer (MBL) clouds. Flights spanning warm and cold seasons across 3 years (2020–22) provided a broad range of conditions associated with aerosol particles, cloud properties (including particle size and phase), and meteorology, ideally suited for robust ACI calculations and assessing how well models simulate a wide range of MBL clouds from stratiform to cumulus. ACTIVATE data suggest that drivers of cloud droplet number concentration N d , including aerosol particles and MBL dynamics, vary between winter and summer months with a stronger potential to convert aerosol particles into cloud droplets in winter. Models of varying complexity not only highlight some skills in simulating winter and summer cloud types but also identify challenges that still need to be addressed such as treatment of turbulence, wet scavenging, and mesoscale organization. Remote sensing advances range from new retrieval methods for N d , cloud phase classification, vertically resolved aerosol and cloud condensation nuclei number concentration, and ocean surface wind speed. This work describes these scientific and technological advances along with efforts in outreach and open data science.

aerosol indirect effect↗
DOE OSTI2026

Occurrence of seeding multi-layer clouds in the Arctic from ground-based observations

Studies of Arctic clouds often focus on low-level single-layer clouds (SLCs). Here, we use combined observations of soundings and cloud radar during the MOSAiC, ACSE, and AO2018 research cruises as well as from long-term observations at Ny-Ålesund, Svalbard and Utqiagvik, Alaska to investigate the occurrence of SLCs and multi-layer clouds (MLCs) in the Arctic and to assess the rate of ice-crystal seeding in cold MLCs. MOSAiC observations show cloudy conditions in between 70 % and 90 % of sounding-radar cases. SLCs show occurrence rates of 30 % to 40 % with the highest value of 45 % during October. Cold MLCs are most abundant from November to June (40 % to 55 % of cases). Seeding occurs in about half to two thirds of the identified cold MLCs during MOSAiC for which the sub-saturated layer extends between 100 and 1000 m. The seeding rate increases by as much as 20 percentage points as the assumed size of the falling ice crystals is increased from 100 to 400 µm. The observations reveal a stable rate of cloud-free conditions of around 20 % over the covered latitude range. Cloud occurrence during MOSAiC and at Ny-Ålesund in July, when the geographical distance between observations was minimal, shows reasonable agreement. Comparisons of MOSAiC and other research cruises to the central Arctic also indicate consistent occurrence rates of different cloud types despite the likely effect of year-to-year variability. The comparison of data from ship campaigns and land sites suggests that the latter are not necessarily a good indicator of cloud occurrence in the high Arctic.

Achtert, Peggy [Leipzig Univ. (Germany); Meteorolo↗