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All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Saturation point structure of marine stratocumulus clouds

An investigation of the microstructure of a Pacific stratocumulus capped boundary layer is presented. A complex structure of three branches, identified using conserved variable diagrams, is found to correspond well to a conceptual model for the unstable, radiatively cooled cloud topped boundary layer. A simple conditional sampling method was used to identify saturation point pairs for ascending and descending branches of the internal boundary layer circulation. Results indicate a primary circulation scale of 5 km and provide a reasonable cloud top entrainment rate of 1 cm/s.

Boers, Reinout↗
NASA NTRS1990

Stratocumulus cloud height variations determined from surface and satellite observations

Determination of cloud-top heights from satellite-inferred cloud-top temperatures is a relatively straightforward procedure for a well-behaved troposphere. The assumption of a monotonically decreasing temperature with increasing altitude is commonly used to assign a height to a given cloud-top temperature. In the hybrid bispectral threshold method, or HBTM, Minnis et al. (1987) assume that the lapse rate for the troposphere is -6.5/Kkm and that the surface temperature which calibrated this lapse rate is the 24 hour mean of the observed or modeled clear-sky, equivalent blackbody temperature. The International Satellite Cloud Climatology Project (ISCCP) algorithm (Rossow et al., 1988) attempts a more realistic assignment of height by utilizing interpolations of analyzed temperature fields from the National Meteorological Center (NMC) to determine the temperature at a given level over the region of interest. Neither these nor other techniques have been tested to any useful extent. The First ISCCP Regional Experiment (FIRE) Intensive Field Observations (IFO) provide an excellent opportunity to assess satellite-derived cloud height results because of the availability of both direct and indirect cloud-top altitude data of known accuracy. The variations of cloud-top altitude during the Marine Stratocumulus IFO (MSIFO, June 29 to July 19, 1987) derived from surface, aircraft, and satellite data are examined.

Minnis, Patrick↗
NASA NTRS1992

Stratocumulus cloud properties derived from simultaneous satellite and island-based instrumentation during FIRE

Cloud parameters derived from visible and infrared window data from the Geostationary Operational Environmental Satellite (GOES) are compared to corresponding properties determined from instrumentation on San Nicolas Island off the coast of California during the First ISCCP Regional Experiment marine stratocumulus intensive field observations period in July 1987. Examination of the satellite imagery revealed that the apparent bias can be explained by the persistence of the clouds over the northwest part of the island during periods of clearing around the island. Diurnal variations in the cloud cover were very significant; minimum cloudiness occurred during the late afternoon and maximum cloudiness early in the morning. Relationships were established between the satellite-derived cloud optical depth and two surface-observed quantities: cloud liquid water path and cloud thickness. Simultaneous observations of liquid water path and satellite-derived cloud optical depth were used to infer effective cloud-droplet radius, resulting in good agreement with correlative data. The diurnal variations in cloud amount are accompanied by changes in cloud thickness, cloud-top height, cloud liquid water path, and effective droplet size. These observations provide the most complete picture, to date, of the diurnal cycle of marine stratocumulus clouds, confirming previous satellite-based inferences of the diurnal behavior of marine stratocumulus at larger scales.

Minnis, Patrick↗
DOE OSTI2024

Stratus and Stratocumulus Cloud Microphysics and Drizzle Relationships With CCN Modality

High resolution extended-range cloud condensation nuclei (CCN) spectral comparisons with cloud microphysics and drizzle of the Physics of Stratocumulus Tops (POST) field experiment confirmed results in the Marine Stratus/Stratocumulus Experiment (MASE). Both of these stratus cloud projects demonstrated that bimodal CCN spectra typically caused by cloud processing were associated with clouds that exhibited higher concentrations of smaller droplets with narrower distributions and less drizzle than clouds associated with unimodal CCN spectra. Resulting brighter clouds and increased cloudiness could enhance both indirect aerosol effects (IAE). These stratus findings are opposite of analogous measurements in two cumulus cloud projects, which showed bimodal CCN associated with fewer larger droplets more broadly distributed and with more drizzle than clouds associated with unimodal CCN. Resulting reduced cumulus brightness and cloudiness could reduce both IAE. Physics of Stratocumulus Tops (POST) flights in air masses with higher CCN concentrations, N CCN , showed more extremes of the stratus characteristics. However, POST flights with lower N CCN showed opposite droplet characteristics similar to the cumulus clouds, yet still showed less drizzle in clouds associated with bimodal CCN, but not as much less as the flights with higher N CCN . Since all MASE clouds were in polluted air masses, while the two cumulus projects were in clean air masses we deduce from these four projects that both the dynamic stratus/cumulus differences (vertical wind) and N CCN are responsible for the microphysics and drizzle differences among these projects. This is because the clean POST characteristics are a hybrid between MASE/POST high N CCN and the two cumulus projects.

bimodality↗
NASA NTRS2016

Neural Network (NN) Retrievals of Stratocumulus Cloud Properties Using Multiangle Polarimetric Observations During ORACLES

The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the SouthEast Atlantic during the Austral Spring for three consecutive years from 20162018. The study area encompasses one of the Earths three semipermanent subtropical Stratocumulus (Sc) cloud decks,and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), butstill challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe anew algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER2and P3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrievalscheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a morerealistic representation of the signals. Before introducing the input variables to the network, the signals are projected on a principle component plane that retains the maximal signal information but minimizes the noise contribution. We will discuss parameter choices for the network and present preliminary results of cloudretrievals from ORACLES, compared with standard RSP low-levelcloud retrieval method that has been validated against in situ observations.

Cloud-aerosol↗
NASA NTRS1983

On the joint bimodality of temperature and moisture near stratocumulus cloud tops

The observed distributions of the thermodynamic variables near stratocumulus top are highly bimodal. Two simple models of sub-grid fractional cloudiness motivated by this observed bimodality are examined. In both models, certain low order moments of two independent, moist-conservative thermodynamic variables are assumed to be known. The first model is based on the assumption of two discrete populations of parcels: a warm-day population and a cool-moist population. If only the first and second moments are assumed to be known, the number of unknowns exceeds the number of independent equations. If the third moments are assumed to be known as well, the number of independent equations exceeds the number of unknowns. The second model is based on the assumption of a continuous joint bimodal distribution of parcels, obtained as the weighted sum of two binormal distributions. For this model, the third moments are used to obtain 9 independent nonlinear algebraic equations in 11 unknowns. Two additional equations are needed to determine the covariance within the two subpopulations. In case these two internal covariance vanish, the system of equations can be solved analytically.

Randall, D. A.↗
NASA NTRS1984

On the bimodality of temperature and moisture near stratocumulus cloud tops

The observed distributions of the thermodynamic variables near stratocumulus top are highly bimodal (Mahrt and Paumier, 1982). This suggests a model based on the assumption of a joint bimodal distribution of parcels, obtained as the weighted sum of two binormal distributions. The properties of joint normal distribution, G, show that there will almost always have two distinct populations.

Randall, D. A.↗
DOE OSTI2020

Assessment of Precipitating Marine Stratocumulus Clouds in the E3SMv1 Atmosphere Model: A Case Study from the ARM MAGIC Field Campaign

This paper presents a process-oriented evaluation of precipitating stratocumulus and its transition to cumulus in version 1 of the Energy Exascale Earth System Model (E3SMv1) using comprehensive case-study observations from a field campaign of the Atmospheric Radiation Measurement program (ARM). The E3SMv1 single-column model (SCM) of the marine boundary layer and its low clouds and precipitation are compared to observations including subcloud drizzle retrievals from a combination of Doppler radar and lidar backscatter measurements. Additionally, the SCM is also compared to a large-eddy simulation (LES) of the same case. The combination of advanced remote sensing observations and LES is a powerful framework to evaluate the physical parameterizations of large-scale models. Given the observed large-scale environment, the E3SMv1 SCM realistically represents the evolution of clouds and boundary layer structure during the stratocumulus-to-cumulus transition. The model well simulates the liquid water path and its diurnal cycle in the stratocumulus period as well as the two-layer vertical thermodynamic structure and lower cloud fraction in the transition period. E3SMv1’s success in simulating the cloud in the stratocumulus period permitted examination of its precipitation processes. Here problems were identified with E3SMv1 producing an unrealistically small subcloud precipitation fraction, an unrealistic double peak in the vertical profiles of precipitation mass, and drizzle that evaporates too close to the surface. Further model diagnostics determined that these unrealistic characteristics resulted from an overly long microphysics time step and an unrealistic parameterization of the precipitation fraction. These results imply that careful consideration of these issues is needed in order to better simulate precipitation processes in marine stratocumulus.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improving Stratocumulus Cloud Amounts in a 200‐m Resolution Multi‐Scale Modeling Framework Through Tuning of Its Interior Physics

Abstract High‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over‐entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present‐day climate, limiting their scientific utility. We report new results showing that this over‐entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small‐scale momentum fluctuations associated with the formulation of the momentum solver of the embedded large eddy simulation. By considering the sedimentation process adjacent to default one‐moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that can produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub‐cloud eddy spectrum are observed. We report these sensitivities in multi‐week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5° exterior resolution. The result is a new HR having desired improvements in the baseline present‐day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Marine stratocumulus cloud parameters from GOES during the 1987 FIRE intensive field observation period

GOES was used to perform the Marine Stratocumulus Intensive Field Observations (IFO) from June 29 to July 19, 1987. Preliminary results of an analysis of GOES data covering most of the IFO period are discussed. The large-scale cloud-field characteristics are derived, and then related to a longer period of measurements and to surface observations. Some preliminary point measurements taken from the surface are compared to regional-scale cloud parameters derived from satellite radiances.

Young, David F.↗
NASA NTRS1995

Windowed and Wavelet Analysis of Marine Stratocumulus Cloud Inhomogeneity

To improve radiative transfer calculations for inhomogeneous clouds, a consistent means of modeling inhomogeneity is needed. One current method of modeling cloud inhomogeneity is through the use of fractal parameters. This method is based on the supposition that cloud inhomogeneity over a large range of scales is related. An analysis technique named wavelet analysis provides a means of studying the multiscale nature of cloud inhomogeneity. In this paper, the authors discuss the analysis and modeling of cloud inhomogeneity through the use of wavelet analysis. Wavelet analysis as well as other windowed analysis techniques are used to study liquid water path (LWP) measurements obtained during the marine stratocumulus phase of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment. Statistics obtained using analysis windows, which are translated to span the LWP dataset, are used to study the local (small scale) properties of the cloud field as well as their time dependence. The LWP data are transformed onto an orthogonal wavelet basis that represents the data as a number of times series. Each of these time series lies within a frequency band and has a mean frequency that is half the frequency of the previous band. Wavelet analysis combined with translated analysis windows reveals that the local standard deviation of each frequency band is correlated with the local standard deviation of the other frequency bands. The ratio between the standard deviation of adjacent frequency bands is 0.9 and remains constant with respect to time. This ratio defined as the variance coupling parameter is applicable to all of the frequency bands studied and appears to be related to the slope of the data's power spectrum. Similar analyses are performed on two cloud inhomogeneity models, which use fractal-based concepts to introduce inhomogeneity into a uniform cloud field. The bounded cascade model does this by iteratively redistributing LWP at each scale using the value of the local mean. This model is reformulated into a wavelet multiresolution framework, thereby presenting a number of variants of the bounded cascade model. One variant introduced in this paper is the 'variance coupled model,' which redistributes LWP using the local standard deviation and the variance coupling parameter. While the bounded cascade model provides an elegant two- parameter model for generating cloud inhomogeneity, the multiresolution framework provides more flexibility at the expense of model complexity. Comparisons are made with the results from the LWP data analysis to demonstrate both the strengths and weaknesses of these models.

Gollmer, Steven M.↗
DOE OSTI2022

Evolution of Droplet Size Distributions During the Transition of an Ultraclean Stratocumulus Cloud System to Open Cell Structure: An LES Investigation Using Lagrangian Microphysics

Here, a state-of-the-art Lagrangian microphysics scheme is used in a large-eddy simulation to investigate the stratocumulus transition from closed to open cell structure. Processes controlling precipitation development, which is a key to the transition, are analyzed by leveraging unique benefits of Lagrangian microphysics, particularly the ability to track computational drops in the flow. Sufficient time is needed for coalescence growth of cloud drops to drizzle within the updraft-downdraft cycle of large eddies. This favors broad drop size distributions (DSDs) and drizzle growth in downdrafts, where drops are typically much older than in updrafts. During the closed cell stage, mean cloud drop radius is too small, and the DSDs are too narrow, so that the timescale for coalescence is much longer than the large eddy turnover time and drizzle growth is limited. The closed-to-open cell transition occurs when these timescales become comparable and the precipitation flux increases sharply.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

Entrainment, Drizzle, and Stratocumulus Cloud Albedo

Globally averaged cloud changes from GCMs on average show a doubling of the Twomey effect, which is the change in cloud albedo with respect to changes in droplet concentrations for fixed cloud water and droplet dispersion. In contrast, ship-track measurements show a much more modest amplification of the Twomey effect, suggesting that the GCMs are exaggerating the indirect aerosol effect. We have run large-eddy simulations with bin microphysics of marine stratocumulus from multiple field campaigns, and find that the large-eddy simulations are in much better agreement with the ship-track measurements. The inversion strength over N. Pacific stratocumulus (as measured during DYCOMS-II) is generally much stronger than over N. Atlantic stratocumulus (as measured during ASTEX), and we have found that the response of cloud water to increasing droplet concentration changes sign as the inversion strengthens. For the different environmental conditions, we will show the overall response of cloud albedo to droplet concentrations, and decompose the response into its contributing factors of changes in cloud water, droplet dispersion, and horizontal inhomogeneity.

Ackerman, A. S.↗
NASA NTRS1990

An eight-month climatology of marine stratocumulus cloud fraction, albedo, and integrated liquid water

As part of the FIRE/Extended Time Observations (ETO) program, extended time observations were made at San Nicolas Island (SNI) from March to October, 1987. Hourly averages of air temperature, relative humidity, wind speed and direction, solar irradiance, and downward longwave irradiance were recorded. The radiation sensors were standard Eppley pyranometers (shortwave) and pyrgeometers (longwave). The SNI data were processed in several ways to deduce properties of the stratocumulus covered marine boundary layer (MBL). For example, from the temperature and humidity the lifting condensation level, which is an estimate of the height of the cloud bottom, can be computed. A combination of longwave irradiance statistics can be used to estimate fractional cloud cover. An analysis technique used to estimate the integrated cloud liquid water content (W) and the cloud albedo from the measured solar irradiance is also described. In this approach, the cloud transmittance is computed by dividing the irradiance measured at some time by a clear sky value obtained at the same hour on a cloudless day. From the transmittance and the zenith angle, values of cloud albedo and W are computed using the radiative transfer parameterizations of Stephens (1978). These analysis algorithms were evaluated with 17 days of simultaneous and colocated mm-wave (20.6 and 31.65 GHz) radiometer measurements of W and lidar ceilometer measurements of cloud fraction and cloudbase height made during the FIRE IFO. The algorithms are then applied to the entire data set to produce a climatology of these cloud properties for the eight month period.

Fairall, C. W.↗
NASA NTRS1990

Extended time observations of California marine stratocumulus clouds from GOES for July 1983-1987

One of the goals of the First ISCCP Regional Experiment (FIRE) is to relate the relatively small scale (spatial and temporal) Intensive Field Observations (IFO) to larger time and space domains embodied in the Extended Time Observations (ETO) phase of the experiment. The data analyzed as part of the ETO are to be used to determine some climatological features of the limited area which encompasses the Marine Stratocumulus IFO which took place between 29 June and 19 July 1987 off the coast of southern California.

Minnis, Patrick↗
NASA NTRS1990

Radiative diffusivity factors in cirrus and stratocumulus clouds: Application to two-stream models

A diffusion-like description of radiative transfer in clouds and the free atmosphere is often used. The two stream model is probably the best known example of such a description. The main idea behind the approach is that only the first few moments of radiance are needed to describe the radiative field correctly. Integration smooths details of the angular distribution of specific intensity and it is assumed that the closure parameters of the theory (diffusivity factors) are only weakly dependent on the distribution. The diffusivity factors are investigated using the results obtained from both Stratocumulus and Cirrus phases of FIRE experiment. A new theoretical framework is described in which two (upwards and downwards) diffusivity factors are used and a detailed multistream model is used to provide further insight about both the diffusivity factors and their dependence on scattering properties of clouds.

Stephens, Graeme L.↗
DOE OSTI2021

Underestimated marine stratocumulus cloud feedback associated with overly active deep convection in models

Cloud feedback remains the largest source of uncertainty in equilibrium climate sensitivity (ECS). Many studies have attempted to narrow uncertainties in cloud feedback and ECS by proposing observable metrics with high skill at predicting future climate, referred to as emergent constraints. These constraints are often associated with clouds, convection, and circulation, and are interrelated. However, physical explanations for these connections remain unclear. Here, we propose a new mechanism relating convection and clouds across multiple climate models. Some models show overly active deep convection on daily timescales in the subtropical low cloud regions, which contributes to weaker subsidence inversion and smaller amounts of low-level clouds. Such models predict smaller shortwave (SW) cloud feedback. Using precipitation frequency in these regions as an emergent constraint, encapsulating this mechanism, models with lower SW cloud feedback (<0.50 W m -2 °C - 1) are found to exhibit erroneously frequent convection. Our results suggest that further improvements in understanding and better modeling of cloud and convective systems are necessary for accurate climate predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance Statement A typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds.

54 ENVIRONMENTAL SCIENCES↗