Search NASASearch

SEARCH · Search NASA

Results for “Stratus clouds”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Stratocumulus simulation with a general circulation model

Stratus and stratocumulus cloud sheets which are among the most common cloud types over the world are discussed. They are characteristic of the undisturbed subtropical marine boundary layer over the eastern oceans, where cool water and large scale sinking motion suppress penetrative cumulus convection. They also occur over the Arctic Ocean, particularly in summer, and behind cold outbreaks over the western oceans in winter. Observational studies were conducted and further observations are planned.

Randall, D. A.

Feature Selection for Classification of Polar Regions Using a Fuzzy Expert System

Labeling, feature selection, and the choice of classifier are critical elements for classification of scenes and for image understanding. This study examines several methods for feature selection in polar regions, including the list, of a fuzzy logic-based expert system for further refinement of a set of selected features. Six Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) arctic scenes are classified into nine classes: water, snow / ice, ice cloud, land, thin stratus, stratus over water, cumulus over water, textured snow over water, and snow-covered mountains. Sixty-seven spectral and textural features are computed and analyzed by the feature selection algorithms. The divergence, histogram analysis, and discriminant analysis approaches are intercompared for their effectiveness in feature selection. The fuzzy expert system method is used not only to determine the effectiveness of each approach in classifying polar scenes, but also to further reduce the features into a more optimal set. For each selection method,features are ranked from best to worst, and the best half of the features are selected. Then, rules using these selected features are defined. The results of running the fuzzy expert system with these rules show that the divergence method produces the best set features, not only does it produce the highest classification accuracy, but also it has the lowest computation requirements. A reduction of the set of features produced by the divergence method using the fuzzy expert system results in an overall classification accuracy of over 95 %. However, this increase of accuracy has a high computation cost.

Penaloza, Mauel A.

Aerosol and Cloud Microphysical Characteristics of Rifts and Gradients in Maritime Stratocumulus Clouds

A cloud rift is characterized as a large-scale, persistent area of broken, low reflectivity stratocumulus clouds usually surrounded by a solid deck of stratocumulus. A rift observed off the coast of Monterey Bay, California on 16 July 1999 was studied to compare the aerosol and cloud microphysical properties in the rift with those of the surrounding solid stratus deck. Variables measured from an instrumented aircraft included temperature, water vapor, and cloud liquid water. These measurements characterized the thermodynamic properties of the solid deck and rift areas. Microphysical measurements made included aerosol, cloud drop and drizzle drop concentrations and cloud condensation nuclei (CCN) concentrations. The microphysical characteristics in a solid stratus deck differ substantially from those of a broken, cellular rift where cloud droplet concentrations are a factor of 2 lower than those in the solid cloud. Further, CCN concentrations were found to be about 3 times greater in the solid cloud area compared with those in the rift and aerosol concentrations showed a similar difference as well. Although drizzle was observed near cloud top in parts of the solid stratus cloud, the largest drizzle rates were associated with the broken clouds within the rift area. In addition to marked differences in particle concentrations, evidence of a mesoscale circulation near the solid cloud rift boundary is presented. This mesoscale circulation provides a mechanism for maintaining a rift, but further study is required to understand the initiation of a rift and the conditions that may cause it to fill.

Sharon, Tarah M.

The relationship of marine stratus to synoptic conditions

The marine stratus which persistently covered most of the eastern Pacific Ocean, had large clear areas during the FIRE Intensive Field Operations (IFO) in 1987. Clear zones formed inside the large oceanic cloud mass on almost every day during the IFO. The location and size of the clear zones varied from day to day implying that they were related to dynamic weather conditions and not to oceanic conditions. Forecasting of cloud cover for aircraft operations during the IFO was directed towards predicting when and where the clear and broken zones would form inside the large marine stratus cloud mass. The clear zones often formed to the northwest of the operations area and moved towards it. However, on some days the clear zones appeared to form during the day in the operations area as part of the diurnal cloud burn off. The movement of the clear zones from day to day were hard to follow because of the large diurnal changes in cloud cover. Clear and broken cloud zones formed during the day only to distort in shape and fill during the following night. The field forecasters exhibited some skill in predicting when the clear and broken cloud patterns would form in the operations area. They based their predictions on the analysis and simulations of the models run by NOAA's Numeric Meteorological Center. How the atmospheric conditions analyzed by one NOAA/NMC model related to the cloud cover is discussed.

Wylie, Donald P.

Antarctica Cloud Cover for October 2003 from GLAS Satellite Lidar Profiling

Seeing clouds in polar regions has been a problem for the imagers used on satellites. Both clouds and snow and ice are white, which makes clouds over snow hard to see. And for thermal infrared imaging both the surface and the clouds cold. The Geoscience Laser Altimeter System (GLAS) launched in 2003 gives an entirely new way to see clouds from space. Pulses of laser light scatter from clouds giving a signal that is separated in time from the signal from the surface. The scattering from clouds is thus a sensitive and direct measure of the presence and height of clouds. The GLAS instrument orbits over Antarctica 16 times a day. All of the cloud observations for October 2003 were summarized and compared to the results from the MODIS imager for the same month. There are two basic cloud types that are observed, low stratus with tops below 3 km and high cirrus form clouds with cloud top altitude and thickness tending at 12 km and 1.3 km respectively. The average cloud cover varies from over 93 % for ocean and coastal regions to an average of 40% over the East Antarctic plateau and 60-90% over West Antarctica. When the GLAS monthly average cloud fractions are compared to the MODIS cloud fraction data product, differences in the amount of cloud cover are as much as 40% over the continent. The results will be used to improve the way clouds are detected from the imager observations. These measurements give a much improved understanding of distribution of clouds over Antarctica and may show how they are changing as a result of global warming.

Spinhirne, J. D.

Studies of Radiation and Microphysics in Cirrus and Marine Stratocumulus Clouds

Two tasks were completed during this period. In the first, we examined the polarization of millimeter-wavelength radar beams scattered by ice crystals. Because of their non-spherical shape and size, ice crystals depolarize the incident polarized radar beam. In principle, this depolarization can be used to identify ice from liquid water, as well as provide some information on size. However, the amount of de-polarization is small, producing only a weak signal at the receiver. Our task was to determine the magnitude of such a signal and decide if our radar would be capable of measuring it under typical cirrus conditions. The theoretical study was carried out by Henrietta Lemke, a visiting graduate student from Germany. She had prior experience using a discrete dipole code to compute scattering depolarization. Dr. Kultegin Aydin of the Penn State Electrical Engineering Department, who is also expert in this area, consulted with us on this project at no cost to the project. Our conclusion was that the depolarization signal is too weak to be usefully measured by our system. Therefore we proceeded no further in this study. The second task involved the study of the effect of stratus microphysics on surface cloud forcing. Manajit Sengupta, a graduate student, and the project PI jointly carried out this task. The study used data culled from over a year of continuous radar and radiometer observations at the Atmospheric Radiation Measurement (ARM) site in Oklahoma. The study compared solar radiation calculations made using constant microphysics with calculations made using a retrieved mean particle size. The results showed that on average the constant microphysics produced the correct forcing when compared with the observed forcing. We conclude, therefore, that there is little impetus on radiation grounds alone to include explicit microphysics in climate models. The question of pollutant particle emission impacts on microphysics remains to be resolved. A manuscript is in preparation and will be submitted this year.

Source record

Lidar and radiometer results from the ER-2 for the FIRE field experiments

The airborne lidar and radiometers which were flown during the FIRE cirrus and marine stratus field experiments had multiple objectives. Cloud parameters of direct interest, such as cirrus infrared emittance or convective scales for marine stratus, may be derived from the observations and analyzed along with the available cloud physics and meteorological observations. Additionally however a stated goal of the FIRE studies was to validate satellite cloud retrievals. To this end a number of derived products are to be available from the basic lidar and radiometer observations. The characteristics of the derived products are described, and in addition analysis results for cloud radiometric and structure parameters are presented. This extended abstract will be used to describe the available data products and the associated presentation will emphasize case study analysis results.

Spinhirne, James D.

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

Platnick, Steven

A technique for determining cloud free vs cloud contaminated pixels in satellite imagery

Since the first earth orbiting satellite sent pictures of the earth back to them, atmospheric scientists have been focused on the possibilities of using that information as both a forecasting tool and as a meteorological research tool. With the latest generation of Geostationary Operational Environmental Satellites (GOES) now entering service, that view of the earth yields views at a frequency and resolution never before available. These satellites have imagers with a five band multi-spectral capability with high spatial resolution. In addition, the sounder has eighteen thermal infrared (IR) channels plus one low-resolution visible band. With a resolution as small as one kilometer, GOES provides scientists with a powerful eye on the atmosphere. Menzel and Purdom (1994) detail both the imager and sounder capability as well as other systems on the GOES satellites. Immediately apparent in the visible channel are the patterns of clouds swirling over both oceans and continents. These clouds range in size from huge planetary systems covering thousands of kilometers to puffy fair weather cumulus clouds on the order of half a kilometer in size. With the IR sensors temperature patterns are observed. High clouds appear very cold, while low stratus field show temperatures near that of the surface. The surface, in turn, generally appears warmer than the clouds. It would seem then a simple manner to determine cloud and surface temperature from the imagery, but such is not the case. While most of the atmospheric constituents are well mixed and homogeneous, water vapor is not. The water molecule, because of its unique structure and vibration modes, affects the transmittance of the atmosphere most notably in the infrared regions. There are regions of the IR spectrum where water vapor acts as a strong absorber, and at others it is nearly transparent. The transparent wavelengths are called windows, and one such window occurs at 11.2 microns. Adjacent to this window at 12.7 microns which is strongly absorbed by water vapor. These two wavelengths form what is known as a split window, the utility of which was used. Using the linearized form of the radiative transfer equation, they were able to use the split window to determine the amount of water vapor present in the atmosphere. Jedlovec developed the physical split-window (PSW) technique which determines the integrated water content (IWC). The PSW method using Visible Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) found on the older versions of the GOES satellites was used. Recently, Jedlovec and colleagues have been attempting to apply the PSW method using full disk IR imagery obtained by the new generation of GOES satellites. IWC is essential for improved analysis and prediction of convective storms which have been observed to develop in regions of both strong and rapidly evolving moisture gradients. It has also been used in the prediction of clouds and precipitation.

Wohlman, Richard A.

Cloud micro- and macrophysical properties from ground-based remote sensing during the MOSAiC drift experiment

In the framework of the Multidisciplinary drifting Observatory for the Study of Arctic Climate Polarstern expedition, the Leibniz Institute for Tropospheric Research, Leipzig, Germany, operated the shipborne OCEANET-Atmosphere facility for cloud and aerosol observations throughout the whole year. OCEANET-Atmosphere comprises, amongst others, a multiwavelength Raman lidar, a microwave radiometer, and an optical disdrometer. A cloud radar was operated aboard Polarstern by the US Atmospheric Radiation Measurement program. These measurements were processed by applying the so-called Cloudnet methodology to derive cloud properties. To gain a comprehensive view of the clouds, lidar and cloud radar capabilities for low- and high-altitude observations were combined. Cloudnet offers a variety of products with a spatiotemporal resolution of 30 s and 30 m, such as the target classification, and liquid and ice microphysical properties. Additionally, a lidar-based low-level stratus retrieval was applied for cloud detection below the lowest range gate of the cloud radar. Based on the presented dataset, e.g., studies on cloud formation processes and their radiative impact, and model evaluation studies can be conducted.

54 ENVIRONMENTAL SCIENCES

Re-Evaluation of Low Cloud Amount Relationships With Lower-Tropospheric Stability and Estimated Inversion Strength

Lower-tropospheric stability (LTS) and estimated inversion strength (EIS) have a widely accepted relationship with low cloud amount and are key observational foundations for understanding and modeling low-level stratiform clouds. Using the updated surface-based and satellite cloud data, we find that low cloud amount is not as strongly correlated with LTS, and not as sensitive to LTS, as established in the past. EIS does not provide a stronger correlation with low cloud amount than LTS over all eight regions (including the midlatitudes). Further analyzing the relationships between LTS and EIS with different types of low clouds, we find that there is a strong correlation of LTS and EIS with stratocumulus only. This explains the weaker correlation of low cloud fraction (including cumulus, stratocumulus, and stratus) to both LTS and EIS. These results also suggest the need to re-evaluate these relationships in Earth system models. Plain Language Summary: Low-level clouds play an important role in the global radiation budget. Low cloud amount has two established linear relationships with lower-tropospheric stability (LTS) and estimated inversion strength (ETS). These two relationships are re-evaluated here using three separate observational cloud and two reanalysis datasets for three distinct but overlapping time periods. The analysis shows that the strength of the LTS and ETS relationships with low cloud amount varies, depending on the cloud data used. They have a strong relationship with stratocumulus cloud amount only.

Lauren Cutler

Predicting Ground Delay Program at an Airport Based on Meteorological Conditions

In this paper, we present two supervised-learning models, logistic regression and decision tree, to predict occurrence of ground delay program at an airport based on meteorological conditions and scheduled traffic demand. Such predictive capabilities can help the Federal Aviation Administration traffic managers and airline dispatchers to prepare mitigation strategies to reduce the impact of adverse weather. The models are applied to predict ground delay program occurrence at two major U.S. airports: Newark Liberty Intl. and San Francisco Intl. airports. The logistic regression model estimates the probability that a ground delay program will occur during a given hour. Decision tree, on the other hand, classifies an hour as a ground delay program or not based on the input variables. Results indicate that both models perform significantly better than a purely random prediction of ground delay program occurrence at the two airports. The logistic regression model performs better than the decision tree model. The degree to which various input variables impact the probability of ground delay program vary between the two airports. While the enroute convective weather is a dominant factor causing ground delay programs at New York airports, poor visibility and low cloud ceiling caused by marine stratus are major drivers of ground delay programs at San Francisco Intl. airport.

traffic flow management

Effect of marine stratocumulus in TOMS ozone

The algorithm used to correct total O3 from the total ozone mapping spectrometer (TOMS) for cloud effects is based on the measured reflectivity, a climatological cloud top height, and an assumed tropospheric O3 column amount below clouds. In regions of persistent subtropical marine stratocumulus it is assumed that this introduces a positive error into total O3 because these clouds are lower than the assumed mean cloud height used in the algorithm. This appears to be confirmed by high correlation between Nimbus 7 TOMS total O3 and reflectivity data for typical regimes of persistent stratus, as identified by the international satellite cloud climatology project (ISCCP) observations. The TOMS total O3 overestimate has been computed using Nimbus 7/solar backscattered ultraviolet total O3 derived using temperature humidity infrared radiometer (THIR) data for years 1979-1984. A functional relationship between the THIR/non-THIR total O3 difference and reflectivity is used with TOMS reflectivity to modify Nimbus 7 TOMS O3 data for selected regions and periods. The correction diminishes or eliminates a number of apparent O3 maxima, with reductions of up to 20 Dobson units (DU) in total O3 on daily maps and approximately 5 DU on monthly mean O3 maps. Significant correlation between corrected TOMS O3 and reflectivity data remains because low-altitude O3 is retrieved more efficiently over a high-albedo surface. It is also possible that dynamical influences leading to stratocumulus formation bring O3-enriched air into the area. These results imply that although good arguments can be made for the use of TOMS total O3 as a proxy for tropospheric O3 in the tropics, caution must be exercised in the use of daily and even monthly O3 maps in the vicinity of clouds. Further research into the TOMS algorithm in cloudy regions is required to derive reliable estimates of tropospheric O3.

Thompson, A. M.

Venus - Further evidence of vortex circulation

A space-time composite of polar stereographic ultraviolet images of Venus from Mariner 10 shows a remarkable circumpolar vortex. The vortex is characterized by a cloud which appears similar to dense terrestrial stratus having an albedo that is 50 percent higher. Spiral streaks converge into it from low latitudes, akin to the spiral bands of a hurricane. The bright visible polar cloud is not axisymmetric but has roughly an elliptical shape. The high brightness of the polar cloud suggests that it has a different origin from the rest of the Venus cloud cover.

Suomi, V. E.

Features of mid- and high-latitude low-level clouds and their relation to strong aerosol effects in the Energy Exascale Earth System Model version 2 (E3SMv2)

The E3SMv2 model, like various other global models that include representations of aerosol–cloud interactions, uses an empirically chosen lower bound on the simulated in-cloud cloud droplet number concentration (CDNC) to help constrain the effective radiative forcing of anthropogenic aerosols, ERFaer. This study identifies where ultra-low CDNCs (i.e., concentrations lower than 10 cm−3) occur in the stratiform and shallow convective clouds simulated by E3SMv2 and which of the occurrences have the strongest impact on ERF aer . Process-level analyses are presented to reveal characteristics of the cloud droplet formation and removal processes associated with impactful ultra-low CDNCs. Simulations performed with present-day emissions show that ultra-low CDNCs are most frequently found over the mid- and high-latitude oceans in both hemispheres, while the occurrences are also frequent in polluted continental regions despite the high aerosol concentrations. Ultra-low CDNCs with the largest impacts on the simulated regional and global mean ERF aer are found in the lower troposphere in the Northern Hemisphere middle and high latitudes. These cases are typically associated with large cloud fractions, strong water vapor condensation, weak turbulence, and lack of cloud droplet nucleation from aerosol activation. Under such atmospheric conditions, boosting aerosol activation and enhancing turbulent mixing of cloud droplet number can increase the simulated CDNCs, although the magnitude of the global mean ERF aer increases undesirably. The reason for this model behavior is discussed. Overall, our study suggests that mid- and high-latitude low-level stratus occurring under weak turbulence is a cloud regime worth further investigating for the purpose of identifying and addressing the root causes of ultra-low CDNCs and strong ERF aer in E3SM.

Aerosol-Cloud Interaction

Towards a Marine Stratus Climatology on Drizzle Occurrence from CALIPSO

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

CALIPSO

Microwave radiometry for monitoring the diverse cloudiness regimes on Earth: A review

Recent work concerning the use of microwave radiometers in space to provide views of the water content of clouds is reported. Recently, theoretical algorithms were refined and the sampling by microwave radiometers for polar orbiting satellite became more commensurate in resolution and coverage with the scale of the meteorological phenomena. Parameters available from the Special Sensor Microwave/Imager (SSM/I) include total integrated water vapor (kg/sq m), integrated cloud liquid water (kg/sq m), rain rate (mm/hr), and an index for the presence and concentration of large ice particles; this so called scattering index can also be converted to a rain rate, although conversion is still rather uncertain. The hydrologic aspects of climatically important cloud systems on the Earth such as subtropical stratus decks, tropical convection, and midlatitude and polar cyclone can thus be monitored with the SSM/I parameters. The diagnostic as well as prognostic potential of these satellite derived water content properties of cloud systems are also discussed.

Katsaros, Kristina B.

CGILS: Results from the First Phase of an International Project to Understand the Physical Mechanisms of Low Cloud Feedbacks in Single Column Models

1] CGILS-the CFMIP-GASS Intercomparison of Large Eddy Models (LESs) and single column models (SCMs)-investigates the mechanisms of cloud feedback in SCMs and LESs under idealized climate change perturbation. This paper describes the CGILS results from 15 SCMs and 8 LES models. Three cloud regimes over the subtropical oceans are studied: shallow cumulus, cumulus under stratocumulus, and well-mixed coastal stratus/stratocumulus. In the stratocumulus and coastal stratus regimes, SCMs without activated shallow convection generally simulated negative cloud feedbacks, while models with active shallow convection generally simulated positive cloud feedbacks. In the shallow cumulus alone regime, this relationship is less clear, likely due to the changes in cloud depth, lateral mixing, and precipitation or a combination of them. The majority of LES models simulated negative cloud feedback in the well-mixed coastal stratus/stratocumulus regime, and positive feedback in the shallow cumulus and stratocumulus regime. A general framework is provided to interpret SCM results: in a warmer climate, the moistening rate of the cloudy layer associated with the surface-based turbulence parameterization is enhanced; together with weaker large-scale subsidence, it causes negative cloud feedback. In contrast, in the warmer climate, the drying rate associated with the shallow convection scheme is enhanced. This causes positive cloud feedback. These mechanisms are summarized as the "NESTS" negative cloud feedback and the "SCOPE" positive cloud feedback (Negative feedback from Surface Turbulence under weaker Subsidence-Shallow Convection PositivE feedback) with the net cloud feedback depending on how the two opposing effects counteract each other. The LES results are consistent with these interpretations

Single Column Models