Готові списки джерел за темами / Atmospheric cloud

Добірка наукової літератури з теми "Atmospheric cloud"

Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Atmospheric cloud"

1

Chou, Ming-Dah, Kyu-Tae Lee, Si-Chee Tsay, and Qiang Fu. "Parameterization for Cloud Longwave Scattering for Use in Atmospheric Models." Journal of Climate 12, no. 1 (January 1, 1999): 159–69. http://dx.doi.org/10.1175/1520-0442-12.1.159.

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Abstract A parameterization for the scattering of thermal infrared (longwave) radiation by clouds has been developed based on discrete-ordinate multiple-scattering calculations. The effect of backscattering is folded into the emission of an atmospheric layer and the absorption between levels by scaling the cloud optical thickness. The scaling is a function of the single-scattering albedo and asymmetry factor. For wide ranges of cloud particle size, optical thickness, height, and atmospheric conditions, flux errors induced by the parameterization are small. They are <4 W m−2 (2%) in the upward flux at the top of the atmosphere and <2 W m−2 (1%) in the downward flux at the surface. Compared to the case that scattering by clouds is neglected, the flux errors are more than a factor of 2 smaller. The maximum error in cooling rate is ≈8%, which occurs at the top of clouds, as well as at the base of high clouds where the difference between the cloud and surface temperatures is large. With the scaling approximation, radiative transfer equations for a cloudy atmosphere are identical with those for a clear atmosphere, and the difficulties in applying a multiple-scattering algorithm to a partly cloudy atmosphere (assuming homogeneous clouds) are avoided. The computational efficiency is practically the same as that for a clear atmosphere. The parameterization represents a significant reduction in one source of the errors involved in the calculation of longwave cooling in cloudy atmospheres.
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2

Komacek, Thaddeus D., Xianyu Tan, Peter Gao, and Elspeth K. H. Lee. "Patchy Nightside Clouds on Ultra-hot Jupiters: General Circulation Model Simulations with Radiatively Active Cloud Tracers." Astrophysical Journal 934, no. 1 (July 1, 2022): 79. http://dx.doi.org/10.3847/1538-4357/ac7723.

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Abstract The atmospheres of ultra-hot Jupiters have been characterized in detail through recent phase curve and low- and high-resolution emission and transmission spectroscopic observations. Previous numerical studies have analyzed the effect of the localized recombination of hydrogen on the atmospheric dynamics and heat transport of ultra-hot Jupiters, finding that hydrogen dissociation and recombination lead to a reduction in the day-to-night contrasts of ultra-hot Jupiters relative to previous expectations. In this work, we add to previous efforts by also considering the localized condensation of clouds in the atmospheres of ultra-hot Jupiters, their resulting transport by the atmospheric circulation, and the radiative feedback of clouds on the atmospheric dynamics. To do so, we include radiatively active cloud tracers into the existing MITgcm framework for simulating the atmospheric dynamics of ultra-hot Jupiters. We take cloud condensate properties appropriate for the high-temperature condensate corundum from CARMA cloud microphysics models. We conduct a suite of general circulation model (GCM) simulations with varying cloud microphysical and radiative properties, and we find that partial cloud coverage is a ubiquitous outcome of our simulations. This patchy cloud distribution is inherently set by atmospheric dynamics in addition to equilibrium cloud condensation, and causes a cloud greenhouse effect that warms the atmosphere below the cloud deck. Nightside clouds are further sequestered at depth due to a dynamically induced high-altitude thermal inversion. We post-process our GCMs with the Monte Carlo radiative transfer code gCMCRT and find that the patchy clouds on ultra-hot Jupiters do not significantly impact transmission spectra but can affect their phase-dependent emission spectra.
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3

Harrop, Bryce E., and Dennis L. Hartmann. "The Relationship between Atmospheric Convective Radiative Effect and Net Energy Transport in the Tropical Warm Pool." Journal of Climate 28, no. 21 (October 30, 2015): 8620–33. http://dx.doi.org/10.1175/jcli-d-15-0151.1.

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Abstract Reanalysis data and radiation budget data are used to calculate the role of the atmospheric cloud radiative effect in determining the magnitude of horizontal export of energy by the tropical atmosphere. Because tropical high clouds result in net radiative heating of the atmosphere, they increase the requirement for the atmosphere to export energy from convective regions. Increases in upper-tropospheric water vapor associated with convection contribute about a fifth of the atmospheric radiative heating anomaly associated with convection. Over the warmest tropical oceans, the radiative effect of convective clouds and associated water vapor is roughly two-thirds the value of the atmospheric energy transport. Cloud radiative heating and atmospheric heat transport increase at the same rate with increasing sea surface temperature, suggesting that the increased energy export is supplied by the radiative heating associated with convective clouds. The net cloud radiative effect at the top of the atmosphere is insensitive to changes in SST over the warm pool. Principal component analysis of satellite-retrieved cloud data reveals that the insensitivity of the net cloud radiative effect to SST is the result of changes in cloud amount offsetting changes in cloud optical thickness and cloud-top height. While increasing upward motion makes the cloud radiative effect more negative, that decrease is offset by reductions in outgoing longwave radiation owing to increases in water vapor.
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Errico, Ronald M., George Ohring, Fuzhong Weng, Peter Bauer, Brad Ferrier, Jean-François Mahfouf, and Joe Turk. "Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models: Introduction to the JAS Special Collection." Journal of the Atmospheric Sciences 64, no. 11 (November 1, 2007): 3737–41. http://dx.doi.org/10.1175/2007jas2622.1.

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Abstract To date, the assimilation of satellite measurements in numerical weather prediction (NWP) models has focused on the clear atmosphere. But satellite observations in the visible, infrared, and microwave provide a great deal of information on clouds and precipitation. This special collection describes how to use this information to initialize clouds and precipitation in models. Since clouds and precipitation often occur in sensitive regions for forecast impacts, such improvements are likely necessary for continuing to acquire significant gains in weather forecasting. This special collection of the Journal of the Atmospheric Sciences is devoted to articles based on papers presented at the International Workshop on Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models, in Lansdowne, Virginia, in May 2005. This introduction summarizes the findings of the workshop. The special collection includes review articles on satellite observations of clouds and precipitation (Stephens and Kummerow), parameterizations of clouds and precipitation in NWP models (Lopez), radiative transfer in cloudy/precipitating atmospheres (Weng), and assimilation of cloud and precipitation observations (Errico et al.), as well as research papers on these topics.
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5

Koren, I., L. Oreopoulos, G. Feingold, L. A. Remer, and O. Altaratz. "How small is a small cloud?" Atmospheric Chemistry and Physics 8, no. 14 (July 21, 2008): 3855–64. http://dx.doi.org/10.5194/acp-8-3855-2008.

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Abstract. The interplay between clouds and aerosols and their contribution to the radiation budget is one of the largest uncertainties of climate change. Most work to date has separated cloudy and cloud-free areas in order to evaluate the individual radiative forcing of aerosols, clouds, and aerosol effects on clouds. Here we examine the size distribution and the optical properties of small, sparse cumulus clouds and the associated optical properties of what is considered a cloud-free atmosphere within the cloud field. We show that any separation between clouds and cloud free atmosphere will incur errors in the calculated radiative forcing. The nature of small cumulus cloud size distributions suggests that at any resolution, a significant fraction of the clouds are missed, and their optical properties are relegated to the apparent cloud-free optical properties. At the same time, the cloudy portion incorporates significant contribution from non-cloudy pixels. We show that the largest contribution to the total cloud reflectance comes from the smallest clouds and that the spatial resolution changes the apparent energy flux of a broken cloudy scene. When changing the resolution from 30 m to 1 km (Landsat to MODIS) the average "cloud-free" reflectance at 1.65 μm increases from 0.0095 to 0.0115 (>20%), the cloud reflectance decreases from 0.13 to 0.066 (~50%), and the cloud coverage doubles, resulting in an important impact on climate forcing estimations. The apparent aerosol forcing is on the order of 0.5 to 1 Wm−2 per cloud field.
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6

Kato, Seiji, Fred G. Rose, David A. Rutan, and Thomas P. Charlock. "Cloud Effects on the Meridional Atmospheric Energy Budget Estimated from Clouds and the Earth’s Radiant Energy System (CERES) Data." Journal of Climate 21, no. 17 (September 1, 2008): 4223–41. http://dx.doi.org/10.1175/2008jcli1982.1.

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Abstract The zonal mean atmospheric cloud radiative effect, defined as the difference between the top-of-the-atmosphere (TOA) and surface cloud radiative effects, is estimated from 3 yr of Clouds and the Earth’s Radiant Energy System (CERES) data. The zonal mean shortwave effect is small, though it tends to be positive (warming). This indicates that clouds increase shortwave absorption in the atmosphere, especially in midlatitudes. The zonal mean atmospheric cloud radiative effect is, however, dominated by the longwave effect. The zonal mean longwave effect is positive in the tropics and decreases with latitude to negative values (cooling) in polar regions. The meridional gradient of the cloud effect between midlatitude and polar regions exists even when uncertainties in the cloud effect on the surface enthalpy flux and in the modeled irradiances are taken into account. This indicates that clouds increase the rate of generation of the mean zonal available potential energy. Because the atmospheric cooling effect in polar regions is predominately caused by low-level clouds, which tend to be stationary, it is postulated here that the meridional and vertical gradients of the cloud effect increase the rate of meridional energy transport by the dynamics of the atmosphere from the midlatitudes to the polar region, especially in fall and winter. Clouds then warm the surface in the polar regions except in the Arctic in summer. Clouds, therefore, contribute toward increasing the rate of meridional energy transport from the midlatitudes to the polar regions through the atmosphere.
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7

Mollière, P., T. Stolker, S. Lacour, G. P. P. L. Otten, J. Shangguan, B. Charnay, T. Molyarova, et al. "Retrieving scattering clouds and disequilibrium chemistry in the atmosphere of HR 8799e." Astronomy & Astrophysics 640 (August 2020): A131. http://dx.doi.org/10.1051/0004-6361/202038325.

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Context. Clouds are ubiquitous in exoplanet atmospheres and they represent a challenge for the model interpretation of their spectra. When generating a large number of model spectra, complex cloud models often prove too costly numerically, whereas more efficient models may be overly simplified. Aims. We aim to constrain the atmospheric properties of the directly imaged planet HR 8799e with a free retrieval approach. Methods. We used our radiative transfer code petitRADTRANS for generating the spectra, which we coupled to the PyMultiNest tool. We added the effect of multiple scattering which is important for treating clouds. Two cloud model parameterizations are tested: the first incorporates the mixing and settling of condensates, the second simply parameterizes the functional form of the opacity. Results. In mock retrievals, using an inadequate cloud model may result in atmospheres that are more isothermal and less cloudy than the input. Applying our framework on observations of HR 8799e made with the GPI, SPHERE, and GRAVITY, we find a cloudy atmosphere governed by disequilibrium chemistry, confirming previous analyses. We retrieve that C/O = 0.60−0.08+0.07. Other models have not yet produced a well constrained C/O value for this planet. The retrieved C/O values of both cloud models are consistent, while leading to different atmospheric structures: either cloudy or more isothermal and less cloudy. Fitting the observations with the self-consistent Exo-REM model leads to comparable results, without constraining C/O. Conclusions. With data from the most sensitive instruments, retrieval analyses of directly imaged planets are possible. The inferred C/O ratio of HR 8799e is independent of the cloud model and thus appears to be a robust. This C/O is consistent with stellar, which could indicate that the HR 8799e formed outside the CO2 or CO iceline. As it is the innermost planet of the system, this constraint could apply to all HR 8799 planets.
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8

Shupe, Matthew D., David D. Turner, Von P. Walden, Ralf Bennartz, Maria P. Cadeddu, Benjamin B. Castellani, Christopher J. Cox, et al. "High and Dry: New Observations of Tropospheric and Cloud Properties above the Greenland Ice Sheet." Bulletin of the American Meteorological Society 94, no. 2 (February 1, 2013): 169–86. http://dx.doi.org/10.1175/bams-d-11-00249.1.

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Cloud and atmospheric properties strongly influence the mass and energy budgets of the Greenland Ice Sheet (GIS). To address critical gaps in the understanding of these systems, a new suite of cloud- and atmosphere-observing instruments has been installed on the central GIS as part of the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project. During the first 20 months in operation, this complementary suite of active and passive ground-based sensors and radiosondes has provided new and unique perspectives on important cloud–atmosphere properties. High atop the GIS, the atmosphere is extremely dry and cold with strong near-surface static stability predominating throughout the year, particularly in winter. This low-level thermodynamic structure, coupled with frequent moisture inversions, conveys the importance of advection for local cloud and precipitation formation. Cloud liquid water is observed in all months of the year, even the particularly cold and dry winter, while annual cycle observations indicate that the largest atmospheric moisture amounts, cloud water contents, and snowfall occur in summer and under southwesterly flow. Many of the basic structural properties of clouds observed at Summit, Greenland, particularly for low-level stratiform clouds, are similar to their counterparts in other Arctic regions. The ICECAPS observations and accompanying analyses will be used to improve the understanding of key cloud–atmosphere processes and the manner in which they interact with the GIS. Furthermore, they will facilitate model evaluation and development in this data-sparse but environmentally unique region.
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9

Burley, Jarred L., Steven T. Fiorino, Brannon J. Elmore, and Jaclyn E. Schmidt. "A Remote Sensing and Atmospheric Correction Method for Assessing Multispectral Radiative Transfer through Realistic Atmospheres and Clouds." Journal of Atmospheric and Oceanic Technology 36, no. 2 (February 1, 2019): 203–16. http://dx.doi.org/10.1175/jtech-d-18-0078.1.

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Abstract The ability to quickly and accurately model actual atmospheric conditions is essential to remote sensing analyses. Clouds present a particularly complex challenge, as they cover up to 70% of Earth’s surface, and their highly variable and diverse nature necessitates physics-based modeling. The Laser Environmental Effects Definition and Reference (LEEDR) is a verified and validated atmospheric propagation and radiative transfer code that creates physically realizable vertical and horizontal profiles of meteorological data. Coupled with numerical weather prediction (NWP) model output, LEEDR enables analysis, nowcasts, and forecasts for radiative effects expected for real-world scenarios. A recent development is the inclusion of the U.S. Air Force’s World-Wide Merged Cloud Analysis (WWMCA) cloud data in a new tool set that enables radiance calculations through clouds from UV to radio frequency (RF) wavelengths. This effort details the creation of near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest. Calendar year 2015 data are analyzed to establish climatological limits for diffuse transmission in the 300–1300-nm band, and the impacts of various geometry, cloud microphysical, and atmospheric conditions are examined. The results show that 80% of diffuse band transmissions are estimated to fall between 0.248 and 0.889 under the assumptions of cloud homogeneity and maximum overlap and are sufficient for establishing diffuse transmission percentiles. The demonstrated capability provides an efficient way to extend optical wavelength cloud parameters across the spectrum for physics-based multiple-scattering effects modeling through cloudy and clear atmospheres, providing an improvement to atmospheric correction for remote sensing and cloud effects on system performance metrics.
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10

Voiculescu, Mirela. "Special Issue Atmospheric Composition and Cloud Cover Observations." Atmosphere 12, no. 1 (December 31, 2020): 56. http://dx.doi.org/10.3390/atmos12010056.

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A Special Issue of Atmosphere, “Atmospheric Composition and Cloud Cover Observations”, is focused on presenting some of the latest results of observations of clouds and atmospheric composition, mainly by referring to new equipment or experimental set-ups [...]
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Дисертації з теми "Atmospheric cloud"

1

Barahona, Donifan. "On the representation of aerosol-cloud interactions in atmospheric models." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/41169.

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Anthropogenic atmospheric aerosols (suspended particulate matter) can modify the radiative balance (and climate) of the Earth by altering the properties and global distribution of clouds. Current climate models however cannot adequately account for many important aspects of these aerosol-cloud interactions, ultimately leading to a large uncertainty in the estimation of the magnitude of the effect of aerosols on climate. This thesis focuses on the development of physically-based descriptions of aerosol-cloud processes in climate models that help to address some of such predictive uncertainty. It includes the formulation of a new analytical parameterization for the formation of ice clouds, and the inclusion of the effects of mixing and kinetic limitations in existing liquid cloud parameterizations. The parameterizations are analytical solutions to the cloud ice and water particle nucleation problem, developed within a framework that considers the mass and energy balances associated with the freezing and droplet activation of aerosol particles. The new frameworks explicitly account for the impact of cloud formation dynamics, the aerosol size and composition, and the dominant freezing mechanism (homogeneous vs. heterogeneous) on the ice crystal and droplet concentration and size distribution. Application of the new parameterizations is demonstrated in the NASA Global Modeling Initiative atmospheric and chemical and transport model to study the effect of aerosol emissions on the global distribution of ice crystal concentration, and, the effect of entrainment during cloud droplet activation on the global cloud radiative properties. The ice cloud formation framework is also used within a parcel ensemble model to understand the microphysical structure of cirrus clouds at very low temperature. The frameworks developed in this work provide an efficient, yet rigorous, representation of cloud formation processes from precursor aerosol. They are suitable for the study of the effect of anthropogenic aerosol emissions on cloud formation, and can contribute to the improvement of the predictive ability of atmospheric models and to the understanding of the impact of human activities on climate.
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2

Paunova, Irena T. "Explicit numerical study of aerosol-cloud interactions in boundary layer clouds." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100670.

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Aerosol-cloud interactions, the mechanisms by which aerosols impact clouds and precipitation and clouds impact aerosols as they are released upon droplet evaporation, are investigated by means of explicit high-resolution (3 km) numerical simulations with the Mesoscale Compressible Community (MC2) model. This model, which is non-hydrostatic and compressible, was extended by including separate continuity equations for dry and activated multi-modal aerosol, and for chemical species. The sources and sinks include: particle activation, solute transfer between drops, generation of extra soluble material in clouds via oxidation of dissolved SO2, and particle regeneration. The cloud processes are represented by an advanced double-moment bulk microphysical parameterization.
Three summertime cases have been evaluated: a marine stratus and a cold frontal system over the Bay of Fundy near Nova Scotia, formed on 1 Sep 1995 and extensively sampled as a part of the Radiation, Aerosol, and Cloud Experiment (RACE); and a continental stratocumulus, formed over the southern coast of Lake Erie on 11 July 2001. The marine stratus and the frontal system have been examined for the effects of aerosol on cloud properties and thoroughly evaluated against the available observations. The frontal system and the continental stratocumulus have been evaluated for the effects of cloud processing on the aerosol spectrum.
The marine stratus simulations suggest a significant impact of the aerosol on cloud properties. A simulation with mechanistic activation and a uni-modal aerosol showed the best agreement with observations in regards to cloud-base and cloud-top height, droplet concentration, and liquid water content. A simulation with a simple activation parameterization failed to simulate essential bulk cloud properties: droplet concentration was significantly underpredicted and the vertical structure of the cloud was inconsistent with the observations. A simulation with a mechanistic parameterization and a bi-modal aerosol, including a coarse mode observed in particle spectra below cloud, showed high sensitivity of droplet concentration to the inclusion of the coarse mode. There was a significant reduction in droplet number relative to the simulation without the coarse mode. A similar change occurred in the precipitating system preceding the stratus formation, resulting in an enhancement of precipitation in the weaker (upstream) part of the system while the precipitation in the more vigorous (downstream) part of the system remained almost unaffected.
Aerosol processing via collision-coalescence and aqueous chemistry in the non-drizzling stratocumulus case suggests that impact of the two mechanisms is of similar magnitude and can be as large as a 3-5 % increase in particle mean radius. A more detailed analysis reveals that the impact of chemical processing is oxidant-limited; beyond times when the oxidant (H 2O2) is depleted (∼ 40 minutes), the extent of processing is determined by supply of fresh oxidant from large-scale advection (fresh gaseous emissions are not considered). Aerosol processing via drop collision-coalescence alone suggests, as expected, sensitivity to the strength of the collection process in clouds. Larger particle growth, up to 5-10 %, is observed in the case of the frontal clouds, which exhibit stronger drop collection compared to that in the stratocumulus case. The processed aerosol exerted a measurable impact on droplet concentrations and precipitation production in the frontal clouds. For the case modeled here, contrary to expectations, the processed spectrum (via physical processing) produced higher droplet concentration than the unprocessed spectrum. The reasons explaining this phenomenon and the resulting impact on precipitation production are discussed.
The current work illustrates the complexity of the coupled system at the cloud system scales, revealed earlier at much smaller large eddy scales. If future parameterizations of the regional effect of aerosols on clouds are to be developed, careful consideration is required of the many of feedbacks in the boundary layer.
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3

Nugent, Paul Winston. "Wide-angle infrared cloud imaging for cloud cover statistics." Thesis, Montana State University, 2008. http://etd.lib.montana.edu/etd/2008/nugent/NugentP0508.pdf.

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4

Brösamlen, Gerd. "Radiative transfer in lognormal multifractal clouds and analysis of cloud liquid water data." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=68158.

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The study of radiative transfer in multifractal clouds is of great interest, an important application being to Global Climate Models. In this work we develop a formalism analogous to the multifractal singularity formalism for understanding photon scattering statistics in radiative transfer in multifractals, and test the results numerically on lognormal multifractals. Although the results are only exactly valid in the thick cloud limit, the approximation is found to be quite accurate down to optical thickness of $ tau approx1$-10, so the results may be widely applicable. Furthermore we show the possibility of "renormalizing" the multifractal by replacing it with a near equivalent homogeneous medium but with a "renormalized" optical thickness $ tau sp{1/(1+C sb1)}$ where C$ sb1$ is the codimension of the mean singularity of the cloud. We argue that this approximation is likely to continue to be valid for multiple scattering, and is also compatible with recent results for diffusion on multifractals. Finally we analyze cloud liquid water content data and estimate the universal multifractal indices. We find that the scaling is respected over the whole range 5m-330km and that the cloud can in fact be reasonably described by a lognormal multifractal.
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5

David, Robert O. "Cloud Dynamics and Microphysics during CAMPS| A Comparison between Airborne and Mountaintop Cloud Microphysics." Thesis, University of Nevada, Reno, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1591334.

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Orographically-enhanced clouds are essential for global hydrological cycles. To better understand the structure and microphysics of orographically-enhanced clouds, an airborne study, the Colorado Airborne Mixed-Phase Cloud Study (CAMPS), and a ground-based field campaign, the Storm Peak Lab (SPL) Cloud Property Validation Experiment (StormVEx) were conducted in the Park Range of the Colorado Rockies. The CAMPS study utilized the University of Wyoming King Air (UWKA) to provide airborne cloud microphysical and meteorological data on 29 flights totaling 98 flight hours over the Park Range from December 15, 2010 to February 28, 2011. The UWKA was equipped with instruments that measured cloud droplet and ice crystal size distributions, liquid water content, and 3-dimensional wind speed and direction. The Wyoming Cloud Radar and LiDAR were also deployed during the campaign. These measurements are used to characterize cloud structure upwind and above the Park Range. StormVEx measured temperature and cloud droplet and ice crystal size distributions at SPL. The observations from SPL are used to determine mountain top cloud microphysical properties at elevations lower than the UWKA was able to sample in-situ. To assess terrain flow effects on cloud microphysics and structure, vertical profiles of temperature, humidity and wind were obtained from balloon borne soundings and verified with high resolution modeling. Comparisons showed that cloud microphysics aloft and at the surface were consistent with respect to snow growth processes and previous studies on terrain flow effects. Small ice crystal concentrations were routinely higher at the surface and a relationship between small ice crystal concentrations, large cloud droplet concentrations and temperature was observed, suggesting liquid-dependent ice nucleation near cloud base.

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6

Miller, Daniel J. "Satellite Simulator Studies of the Impact of Cloud Inhomogeneity on Passive Cloud Remote Sensing Retrievals." Thesis, University of Maryland, Baltimore County, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10642202.

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Satellite cloud remote sensing provides us the opportunity to study the spatial and temporal distributions of marine boundary layer clouds, as well as their connections with environments on a global scale. However, cloud remote sensing is not without difficulties; retrievals require numerous simplifying assumptions, placing limits on our understanding of cloud processes. Passive remote sensing retrievals often assume that clouds are homogeneous slabs, when in reality, these clouds often have complex inhomogeneous vertical and horizontal structures. Enhancing our understanding of how cloud inhomogeneity influences passive cloud remote sensing requires comparison between cloud retrievals and the underlying cloud properties. In observational data-sets this can become problematic, as it is difficult to compare satellite and airborne measurements because they have both different observed spatial scales and sensitivities to cloud properties. To avoid these complications, this work is based on a satellite retrieval simulator – a Large-Eddy Simulation (LES) cloud model coupled to radiative transfer and retrieval algorithms. The LES-satellite simulator can be used to study the source of retrieval biases. It provides the underlying realistic cloud structure as a reference, informing conclusions about its impact on various cloud retrieval methods. In the first step we focus on cloud vertical profile, finding that the selection of appropriate vertical profile assumptions for the retrieval of cloud liquid water path. Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias liquid water path retrievals away from adiabatic and toward homogeneous profile assumptions. The mean bias induced by drizzle-influenced profiles was shown to be on the order of 5–10 grams per meter squared. In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is also developed to explain variability in LWP retrievals by introducing modifications to the adiabatic effective radius profile. The second step focuses on horizontal inhomogeneity and exploring a comparison of both the bispectral and polarimetric cloud retrieval techniques. Using the satellite retrieval simulator we are able to verify that at high spatial resolution (50 meters) the bispectral and polarimetric retrievals are indeed highly correlated with one another. The small differences at high spatial resolution can be attributed to different sensitivity limitations of the two retrievals. In contrast, a systematic difference between the two effective radius retrievals emerges at coarser resolution. This bias largely stems from differences related to sensitivity of the two retrievals to unresolved inhomogeneities in effective variance and optical thickness. The influence of coarse angular resolution is found to increase uncertainty in the polarimetric effective radius retrieval, but generally maintains a constant mean value. The third study focuses on 3-D radiative effects influencing both total and polarized reflectances and retrievals. Comparisons between the 1-D and 3-D reflectances are made in order to study horizontal photon transfer and radiative smoothing. We find noticeable differences between the total and polarized reflectance 3-D effects, with radiative smoothing and roughening occurring at different scales as well as viewing geometry dependence. Despite these apparently strong 3-D effects on polarized reflectances, the polarimetric retrieval is robust to the influence of 3-D effects – with only sub-micron biases in the retrieval of effective radius.

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7

Duane, William John. "Correcting middle infrared cloud reflectances for atmospheric effects." Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324809.

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8

Grandey, Benjamin Stephen. "Investigating aerosol-cloud interactions." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:8b48c02b-3d43-4b04-ae55-d9885960103d.

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Microphysical and dynamical interactions between aerosols and clouds are associated with some of the largest uncertainties in projections of future climate. Many possible aerosol effects on clouds have been suggested, but large uncertainties remain. In order to improve model projections of future climate, it is essential that we improve our quantitative understanding of anthropogenic aerosol effects. Several studies investigating interactions between satellite-observed aerosol and cloud properties have been published in recent years. However, the observed relationships are not necessarily due to aerosol effects on clouds. They may be due to cloud and precipitation effects on aerosol, meteorological covariation, observational data errors or methodological errors. An analysis of methodological errors arising through climatological spatial gradients is performed. For region sizes larger than 4°×4°, commonly used in the literature, spurious spatial variations in retrieved cloud and aerosol properties are found to introduce widespread significant errors to calculations of aerosol-cloud relationships. Small scale analysis prior to error-weighted aggregation to larger region sizes is recommended. Appropriate ways of quantifying relationships between aerosol optical depth (τ) and cloud properties are considered, and results are presented for three satellite datasets. There is much disagreement in observed relationships between τ and liquid cloud droplet number concentration and between τ and liquid cloud droplet effective radius, particularly over land. However, all three satellite datasets are in agreement about strong positive relationships between τ and cloud top height and between τ and cloud fraction (f_c). Using reanalysis τ data, which are less affected by retrieval artifacts, it is suggested that a large part of the observed f_c-τ signal may be due to cloud contamination of τ. General circulation model simulations further demonstrate that positive f_c-τ relationships may primarily arise due to covariation with relative humidity, and that negative f_c-τ relationships may arise due to scavenging of aerosol by precipitation. A new method of investigating the contribution of meteorological covariation to the observed relationships is introduced. Extratropical cyclone storm-centric composites of retrieved aerosol and cloud properties are investigated. A storm-centric description of the synoptics is found to be capable of explaining spurious f_c-τ relationships, although the spurious relationships explained are considerably smaller than observed relationships.
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9

Vaillancourt, Paul. "Numerical experiments on entrainment, mixing and their effect on cloud dropsize distributions in a cumulus cloud." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=61085.

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Entrainment, extreme inhomogeneous mixing, in the presence of wind shear, and their effect on cloud droplet spectra are investigated. A dynamical model in conjunction with a microphysical model designed to predict evolution of cloud droplet spectra, is employed to perform a two-dimensional simulation of a small nonprecipitating cumulus cloud in the presence of wind shear.
Results show that vortex circulations and penetrative downdrafts are responsible for entrainment of clear air into the cloud structure. Entrainment and mixing are more severe on the downshear side of the cloud leading to a more fragmented structure and often to total dissipation of cloudy air rather than partial dilution as is the case on the upshear side. Mixing followed by uplifting leads to fresh activation of cloud droplets and results in multimodal spectra. In areas where mixing has occurred, the spectra exhibit smaller average radius and larger standard deviation.
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10

Zhong, Weiguo. "Characteristics of the Pinatubo aerosol cloud." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/290573.

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Optical depths at visible and infrared wavelengths obtained in Tucson, Arizona before and after the Pinatubo eruption in June 1991 have been used to investigate the characteristics of the stratospheric aerosols due to the Pinatubo eruption. The intrusion of the Pinatubo aerosols over Tucson first occurred on July 26, 1991 when the spectral optical depth values rose to two to four times their normal values. In general, there was a pattern of increase between June 1991 and April 1992, and a gradual decrease after April 1992. The stratospheric Pinatubo aerosol in April 1992 was characterized by a typical columnar total number density on the order of 8.78 x 106 in the size range of 0.2-0.7 μm. The total number density decreased to the order of 9.28 x 105 by April 1994. Simulations of the size distribution using a simple polydisperse coagulation and fallout model showed that both of the processes played a very important role in the evolution and transport of the particles in the interval from April 1992 to March 1993. A strong seasonal variation was observed in the aerosol optical depth data. The values are higher in the winter and spring and lower in the summer and fall. This variation is explained by more effective transport of particles from the tropics poleward in the winter and spring than in the summer and fall. We also observed that there was a reduction in stratospheric ozone associated with the Pinatubo aerosols, possibly because of the extra sites available for heterogeneous chemical reactions. The reduction was more noticeable in the spring and summer than in other seasons. The magnitude of the ozone reduction was in a good agreement with other studies.
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Книги з теми "Atmospheric cloud"

1

Bai︠a︡nov, I. M. Cloud formation. New York: Nova Science Publishers, 2011.

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2

Berger, Franz Herbert. Die Bestimmung des Einflusses von hohen Wolken auf das Strahlungsfeld und auf das Klima durch Analyse von NOAA AVHRR-Daten: (DK551.501.776 ...). Berlin: D. Reimer, 1992.

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3

Sandro, Fuzzi, ed. The Kleiner Feldberg Cloud Experiment 1990: Eurotrac Subproject Ground-based Cloud Experiment (GCE). Dordrecht: Kluwer Academic Publishers, 1995.

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4

Allen, Zak Joseph, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Division., eds. A cloud model simulation of space shuttle exhaust clouds in different atmospheric conditions. [Washington, DC]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1989.

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5

A, Khananʹi͡a︡n A., ed. Fizika verkhneĭ atmosfery. Moskva: Moskovskoe otd-nie Gidrometeoizdata, 1990.

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6

H, Helsdon John, Farley Richard D, and George C. Marshall Space Flight Center., eds. A cloud, precipitation and electrification modeling effort for COHMEX. Rapid City, S.D: Institute of Atmospheric Sciences, South Dakota School of Mines and Technology, 1991.

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7

J, Heintzenberg, and Charlson Robert J, eds. Clouds in the perturbed climate system: Their relationship to energy balance, atmospheric dynamics, and precipitation. Cambridge, MA: MIT Press, 2009.

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8

Chen, C. A cloud model simulation of space shuttle exhaust clouds in different atmospheric conditions. [Washington, DC]: National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1989.

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9

Zak, J. Allen. Operational implications of a cloud model simulation of space shuttle exhaust clouds in different atmospheric conditions. Huntsville, Ala: Marshall Space Flight Center, 1989.

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10

N, Nevzorov A., ed. Voprosy fiziki oblakov i atmosfernoĭ turbulentnosti. Moskva: Moskovskoe otd-nie Gidrometeoizdata, 1992.

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Частини книг з теми "Atmospheric cloud"

1

Boucher, Olivier. "Aerosol–Cloud Interactions." In Atmospheric Aerosols, 193–226. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9649-1_9.

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2

Hagen, Martin, Hartmut Höller, and Kersten Schmidt. "Cloud and Precipitation Radar." In Atmospheric Physics, 347–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30183-4_21.

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3

Krishnamurti, T. N., Lydia Stefanova, and Vasubandhu Misra. "Tropical Cloud Ensembles." In Springer Atmospheric Sciences, 233–59. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7409-8_11.

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4

Bugliaro, Luca, Hermann Mannstein, and Stephan Kox. "Ice Cloud Properties From Space." In Atmospheric Physics, 417–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30183-4_25.

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5

Wagner, T., T. Senne, F. Erle, C. Otten, J. Stutz, K. Pfeilsticker, and U. Platt. "Determination of Cloud Properties and Cloud Type from DOAS-Measurements." In Atmospheric Ozone Dynamics, 327–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60797-4_27.

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6

Unterstrasser, Simon, Ingo Sölch, and Klaus Gierens. "Cloud Resolving Modeling of Contrail Evolution." In Atmospheric Physics, 543–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30183-4_33.

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7

Arking, Albert, Jeffrey D. Childs, and John Merritt. "Remote Sensing of Cloud Cover Parameters." In Atmospheric Radiation, 473–88. Boston, MA: American Meteorological Society, 1987. http://dx.doi.org/10.1007/978-1-935704-18-8_70.

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8

Wu, Man-Li C. "Remote Sensing of Cloud Physical Parameters." In Atmospheric Radiation, 504–7. Boston, MA: American Meteorological Society, 1987. http://dx.doi.org/10.1007/978-1-935704-18-8_73.

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9

Stathopoulos, S., K. Kourtidis, and A. K. Georgoulias. "Aerosol–Cloud Relations for Cloud Systems of Different Heights." In Perspectives on Atmospheric Sciences, 769–74. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-35095-0_110.

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10

Ching, J. K. S., S. T. Shipley, E. V. Browell, and D. A. Brewer. "Cumulus Cloud Venting of Mixed Layer Ozone." In Atmospheric Ozone, 745–49. Dordrecht: Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-009-5313-0_146.

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Тези доповідей конференцій з теми "Atmospheric cloud"

1

Hofstadter, Mark, and Andrew Heidinger. "Infrared Low-Cloud Detection." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1997. http://dx.doi.org/10.1364/orsa.1997.otub.5.

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Traditional infrared cloud retrieval algorithms, such as the Chahine method or the CO2 Slicing technique (Chahine 1974, Smith 1968), rely on recognizing the temperature difference between the ground and the cloud tops. For a low-cloud, however, the temperature difference is small, making it indistinguishable from the surface. As part of our work for the Atmospheric Infrared Sounder (AIRS), to be flown on the EOS-PM platform, we are developing an improved technique for the detection of low-clouds. It is based upon observations of the depth of narrow water vapor lines in an atmospheric window region. Compared to traditional methods, there is an extra factor (the water vapor amount) making the signal from a cloudy column different than that from a clear column, which increases our sensitivity to low-clouds.
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2

Alvarez, J. M., and M. A. Vaughn. "Numerical Calculation of Cloud Optical Extinction from Lidar." In Inaugural Forum for the Research Center for Optical Physics. Washington, D.C.: Optica Publishing Group, 1993. http://dx.doi.org/10.1364/rcop.1993.tpl90.

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A simple numerical algorithm to calculate optical extinction from cloud lidar data is presented. A two-component atmosphere consisting of "clear air" and cloud particulates is assumed. "Clear air" consists of either molecules only or a mix of molecules and the atmospheric aerosol. If the lidar data can be used to determine the cloud optical thickness then the method provides an estimate of an assumed cloud-atmospheric constant. The optical thickness is used as a constraint on the numerical solution and provides the additional information necessary to calculate the cloud-atmospheric constant. Conversely, the method may also be applied to obtain cloud extinction and optical thickness from lidar cloud soundings provided the cloud-atmospheric constant is known.
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3

Chubarova, Natalia, Julia Khlestova, Marina Shatunova, Vladimir Platonov, Gdaly Rivin, Ulrich Görsdorf, and Ralf Becker. "Cloud characteristics and cloud radiative effects according to COSMO mesoscale model and measurements." In XXIV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, edited by Oleg A. Romanovskii and Gennadii G. Matvienko. SPIE, 2018. http://dx.doi.org/10.1117/12.2504340.

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4

Manninen, Hanna E., Hannes Tammet, Antti Mäkelä, Jussi Haapalainen, Sander Mirme, Tuomo Nieminen, Alessandro Franchin, Tuukka Petäjä, Markku Kulmala, and Urmas Hõrrak. "Atmospheric electricity and aerosol-cloud interactions in earth’s atmosphere." In NUCLEATION AND ATMOSPHERIC AEROSOLS: 19th International Conference. AIP, 2013. http://dx.doi.org/10.1063/1.4803390.

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5

Moncet, J. L., and S. A. Clough. "Retrieval of Effective Cloud Radiative Properties from Ground Based Spectral Measurements." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1997. http://dx.doi.org/10.1364/orsa.1997.othc.4.

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A fast and numerically accurate model for monochromatic radiative transfer in scattering atmospheres has been developed to extend the capabilities of the existing LBLRTM line-by-line model [Clough et al., 1992] to the treatment of clouds and aerosols. The algorithm is based on the adding-doubling method and is specifically designed to perform radiance calculations in both the thermal and solar regimes using any specified number of computational streams. The efficient implementation of the adding-doubling scheme makes it possible to use the multiple-scattering algorithm in retrieval applications, an essential requirement for the intended use of the algorithm in atmospheric validation studies. The algorithm is applied to daytime observations of water clouds from the ground-based high spectral resolution Atmospheric Emitted Radiance Interferometer (AERI) [Smith et al., 1995]. Cloud particle size and density, and cloud fraction are retrieved from the spectral measurements in the 520-1500 cm-1 and 1800-3020 cm-1 bands. An initial assessment is made of the spectral information content of the AERI measurements for water cloud properties, and of the quality of the spectral fits obtainable with those three free parameters in the two bands.
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6

Sassen, Kenneth. "Cirrus Cloud Remote Sensing Program at FARS." In Optical Remote Sensing of the Atmosphere. Washington, D.C.: Optica Publishing Group, 1995. http://dx.doi.org/10.1364/orsa.1995.wb1.

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High level cirrus clouds are believed to be important modulators of the radiation balance of the earth/atmosphere system, yet their effects on our potentially warming climate are poorly understood. Although satellites are well positioned to monitor global cloud cover, improvements in current multichannel radiance cloud algorithms to identify and categorize high level clouds are needed. In support of Project FIRE and a broader program of basic cloud research, passive and active remote sensing instrumentation at the University of Utah Facility for Atmospheric Remote Sensing (FARS) has been applied to the study of cirrus clouds since December 1986. At FARS we maintain a data collection schedule in support of NOAA satellite measurements to provide cloud-truth information, routinely using 0.1 Hz polarization (0.694 µm) lidar and coaligned narrow-beam infrared (9.5-11.5 µm) radiometer, various wideband radiometers, and all-sky photography. Derived data products are cloud top and base heights (and local sounding temperatures), cloud phase and composition information, and estimated visible cloud optical thickness and infrared emissivity. As of this time about 1600-hr of this sort of data have been collected at FARS, and more recent observation periods have also involved high-resolution, two-color (1.06 and 0.532 µm) polarization lidar and W-band (3.2 mm) polarimetric Doppler radar.
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7

Igel, Adele L., Susan C. van den Heever, Catherine M. Naud, Stephen M. Saleeby, and Derek J. Posselt. "Impacts of cloud condensation nuclei on deep stratus clouds." In NUCLEATION AND ATMOSPHERIC AEROSOLS: 19th International Conference. AIP, 2013. http://dx.doi.org/10.1063/1.4803374.

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8

Shamanaev, Vitalii S., and Ivan E. Penner. "Lidar studies of the upper cloud boudary altitude." In XXIV International Symposium, Atmospheric and Ocean Optics, Atmospheric Physics, edited by Oleg A. Romanovskii and Gennadii G. Matvienko. SPIE, 2018. http://dx.doi.org/10.1117/12.2503351.

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9

Galileiskii, Viktor P., Alexey I. Elizarov, Dmitrii V. Kokarev, Alexandr M. Morozov, and N. N. Skorohod. "Image processing of cloud fields based on satellite data." In XXI International Symposium Atmospheric and Ocean Optics. Atmospheric Physics, edited by Oleg A. Romanovskii. SPIE, 2015. http://dx.doi.org/10.1117/12.2205238.

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10

Pastushkov, A. V., and V. T. Kalayda. "Search and tracking method of cloud fields on image." In XXI International Symposium Atmospheric and Ocean Optics. Atmospheric Physics, edited by Oleg A. Romanovskii. SPIE, 2015. http://dx.doi.org/10.1117/12.2205433.

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Звіти організацій з теми "Atmospheric cloud"

1

Seinfeld, John H. Aerosol-Cloud-Radiation Interactions in Atmospheric Forecast Models. Fort Belvoir, VA: Defense Technical Information Center, September 2006. http://dx.doi.org/10.21236/ada611945.

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2

Seinfeld, John H. Aerosol-Cloud-Radiation Interactions in Atmospheric Forecast Models. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada532930.

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3

Seinfeld, John H. Aerosol-Cloud-Radiation Interactions in Atmospheric Forecast Models. Fort Belvoir, VA: Defense Technical Information Center, September 2007. http://dx.doi.org/10.21236/ada541254.

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4

Seinfeld, John H. Aerosol-Cloud-Radiation Interactions in Atmospheric Forecast Models. Fort Belvoir, VA: Defense Technical Information Center, September 2009. http://dx.doi.org/10.21236/ada602941.

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5

Lewellen, David C., and W. S. Lewellen. Cloud Structure and Entrainment in Marine Atmospheric Boundary Layers. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada629768.

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6

Li, Z., and A. Trishchenko. Quantifying Uncertainties in Determining SW Cloud Radiative Forcing and Cloud Absorption due to Variability in Atmospheric Conditions. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2001. http://dx.doi.org/10.4095/219772.

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7

Wehr, Tobias, ed. EarthCARE Mission Requirements Document. European Space Agency, November 2006. http://dx.doi.org/10.5270/esa.earthcare-mrd.2006.

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ESA's EarthCARE (Cloud, Aerosol and Radiation Explorer) mission - scheduled to be launched in 2024 - is the largest and most complex Earth Explorer to date and will advance our understanding of the role that clouds and aerosols play in reflecting incident solar radiation back into space and trapping infrared radiation emitted from Earth's surface. The mission is being implemented in cooperation with JAXA (Japan Aerospace Exploration Agency). It carries four scientific instruments. The Atmospheric Lidar (ATLID), operating at 355 nm wavelength and equipped with a high-spectral resolution and depolarisation receiver, measures profiles of aerosols and thin clouds. The Cloud Profiling Radar (CPR, contribution of JAXA), operates at 94 GHz to measure clouds and precipitation, as well as vertical motion through its Doppler functionality. The Multi-Spectral Imager provides across-track information of clouds and aerosols. The Broad-Band Radiometer (BBR) measures the outgoing reflected solar and emitted thermal radiation in order to derive broad-band radiative fluxes at the top of atmosphere. The Mission Requirement Document defines the scientific mission objectives and observational requirements of EarthCARE. The document has been written by the ESA-JAXA Joint Mission Advisory Group for EarthCARE.
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8

Jensen, M., and K. Jensen. Continuous Profiles of Cloud Microphysical Properties for the Fixed Atmospheric Radiation Measurement Sites. Office of Scientific and Technical Information (OSTI), June 2006. http://dx.doi.org/10.2172/1021013.

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9

Barker, Howard, and Jason Cole. 3D Atmospheric Radiative Transfer for Cloud System-Resolving Models: Forward Modelling and Observations. Office of Scientific and Technical Information (OSTI), May 2012. http://dx.doi.org/10.2172/1040616.

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10

Ferrare, Richard A. Final Technical Report. Cloud and Radiation Testbed (CART) Raman Lidar measurement of atmospheric aerosols for the Atmospheric Radiation Measurement (ARM) Program. Office of Scientific and Technical Information (OSTI), August 2002. http://dx.doi.org/10.2172/799175.

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