Sample records for identify cloud types

  1. ISCCP Cloud Properties Associated with Standard Cloud Types Identified in Individual Surface Observations

    NASA Technical Reports Server (NTRS)

    Hahn, Carole J.; Rossow, William B.; Warren, Stephen G.

    1999-01-01

    Individual surface weather observations from land stations and ships are compared with individual cloud retrievals of the International Satellite Cloud Climatology Project (ISCCP), Stage C1, for an 8-year period (1983-1991) to relate cloud optical thicknesses and cloud-top pressures obtained from satellite data to the standard cloud types reported in visual observations from the surface. Each surface report is matched to the corresponding ISCCP-C1 report for the time of observation for the 280x280-km grid-box containing that observation. Classes of the surface reports are identified in which a particular cloud type was reported present, either alone or in combination with other clouds. For each class, cloud amounts from both surface and C1 data, base heights from surface data, and the frequency-distributions of cloud-top pressure (p(sub c) and optical thickness (tau) from C1 data are averaged over 15-degree latitude zones, for land and ocean separately, for 3-month seasons. The frequency distribution of p(sub c) and tau is plotted for each of the surface-defined cloud types occurring both alone and with other clouds. The average cloud-top pressures within a grid-box do not always correspond well with values expected for a reported cloud type, particularly for the higher clouds Ci, Ac, and Cb. In many cases this is because the satellites also detect clouds within the grid-box that are outside the field of view of the surface observer. The highest average cloud tops are found for the most extensive cloud type, Ns, averaging 7 km globally and reaching 9 km in the ITCZ. Ns also has the greatest average retrieved optical thickness, tau approximately equal 20. Cumulonimbus clouds may actually attain far greater heights and depths, but do not fill the grid-box. The tau-p(sub c) distributions show features that distinguish the high, middle, and low clouds reported by the surface observers. However, the distribution patterns for the individual low cloud types (Cu, Sc, St

  2. Cloud Type Classification (cldtype) Value-Added Product

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Flynn, Donna; Shi, Yan; Lim, K-S

    The Cloud Type (cldtype) value-added product (VAP) provides an automated cloud type classification based on macrophysical quantities derived from vertically pointing lidar and radar. Up to 10 layers of clouds are classified into seven cloud types based on predetermined and site-specific thresholds of cloud top, base and thickness. Examples of thresholds for selected U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility sites are provided in Tables 1 and 2. Inputs for the cldtype VAP include lidar and radar cloud boundaries obtained from the Active Remotely Sensed Cloud Location (ARSCL) and Surface Meteorological Systems (MET) data. Rainmore » rates from MET are used to determine when radar signal attenuation precludes accurate cloud detection. Temporal resolution and vertical resolution for cldtype are 1 minute and 30 m respectively and match the resolution of ARSCL. The cldtype classification is an initial step for further categorization of clouds. It was developed for use by the Shallow Cumulus VAP to identify potential periods of interest to the LASSO model and is intended to find clouds of interest for a variety of users.« less

  3. CloudNeo: a cloud pipeline for identifying patient-specific tumor neoantigens.

    PubMed

    Bais, Preeti; Namburi, Sandeep; Gatti, Daniel M; Zhang, Xinyu; Chuang, Jeffrey H

    2017-10-01

    We present CloudNeo, a cloud-based computational workflow for identifying patient-specific tumor neoantigens from next generation sequencing data. Tumor-specific mutant peptides can be detected by the immune system through their interactions with the human leukocyte antigen complex, and neoantigen presence has recently been shown to correlate with anti T-cell immunity and efficacy of checkpoint inhibitor therapy. However computing capabilities to identify neoantigens from genomic sequencing data are a limiting factor for understanding their role. This challenge has grown as cancer datasets become increasingly abundant, making them cumbersome to store and analyze on local servers. Our cloud-based pipeline provides scalable computation capabilities for neoantigen identification while eliminating the need to invest in local infrastructure for data transfer, storage or compute. The pipeline is a Common Workflow Language (CWL) implementation of human leukocyte antigen (HLA) typing using Polysolver or HLAminer combined with custom scripts for mutant peptide identification and NetMHCpan for neoantigen prediction. We have demonstrated the efficacy of these pipelines on Amazon cloud instances through the Seven Bridges Genomics implementation of the NCI Cancer Genomics Cloud, which provides graphical interfaces for running and editing, infrastructure for workflow sharing and version tracking, and access to TCGA data. The CWL implementation is at: https://github.com/TheJacksonLaboratory/CloudNeo. For users who have obtained licenses for all internal software, integrated versions in CWL and on the Seven Bridges Cancer Genomics Cloud platform (https://cgc.sbgenomics.com/, recommended version) can be obtained by contacting the authors. jeff.chuang@jax.org. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  4. Cloud Radiative Effect in dependence on Cloud Type

    NASA Astrophysics Data System (ADS)

    Aebi, Christine; Gröbner, Julian; Kämpfer, Niklaus; Vuilleumier, Laurent

    2015-04-01

    Radiative transfer of energy in the atmosphere and the influence of clouds on the radiation budget remain the greatest sources of uncertainty in the simulation of climate change. Small changes in cloudiness and radiation can have large impacts on the Earth's climate. In order to assess the opposing effects of clouds on the radiation budget and the corresponding changes, frequent and more precise radiation and cloud observations are necessary. The role of clouds on the surface radiation budget is studied in order to quantify the longwave, shortwave and the total cloud radiative forcing in dependence on the atmospheric composition and cloud type. The study is performed for three different sites in Switzerland at three different altitude levels: Payerne (490 m asl), Davos (1'560 m asl) and Jungfraujoch (3'580 m asl). On the basis of data of visible all-sky camera systems at the three aforementioned stations in Switzerland, up to six different cloud types are distinguished (Cirrus-Cirrostratus, Cirrocumulus-Altocumulus, Stratus-Altostratus, Cumulus, Stratocumulus and Cumulonimbus-Nimbostratus). These cloud types are classified with a modified algorithm of Heinle et al. (2010). This cloud type classifying algorithm is based on a set of statistical features describing the color (spectral features) and the texture of an image (textural features) (Wacker et al. (2015)). The calculation of the fractional cloud cover information is based on spectral information of the all-sky camera data. The radiation data are taken from measurements with pyranometers and pyrgeometers at the different stations. A climatology of a whole year of the shortwave, longwave and total cloud radiative effect and its sensitivity to integrated water vapor, cloud cover and cloud type will be calculated for the three above-mentioned stations in Switzerland. For the calculation of the shortwave and longwave cloud radiative effect the corresponding cloud-free reference models developed at PMOD/WRC will be

  5. Application of the CERES Flux-by-Cloud Type Simulator to GCM Output

    NASA Technical Reports Server (NTRS)

    Eitzen, Zachary; Su, Wenying; Xu, Kuan-Man; Loeb, Norman G.; Sun, Moguo; Doelling, David R.; Bodas-Salcedo, Alejandro

    2016-01-01

    The CERES Flux By CloudType data product produces CERES top-of-atmosphere (TOA) fluxes by region and cloud type. Here, the cloud types are defined by cloud optical depth (t) and cloud top pressure (pc), with bins similar to those used by ISCCP (International Satellite Cloud Climatology Project). This data product has the potential to be a powerful tool for the evaluation of the clouds produced by climate models by helping to identify which physical parameterizations have problems (e.g., boundary-layer parameterizations, convective clouds, processes that affect surface albedo). Also, when the flux-by-cloud type and frequency of cloud types are simultaneously used to evaluate a model, the results can determine whether an unrealistically large or small occurrence of a given cloud type has an important radiative impact for a given region. A simulator of the flux-by-cloud type product has been applied to three-hourly data from the year 2008 from the UK Met Office HadGEM2-A model using the Langley Fu-Lour radiative transfer model to obtain TOA SW and LW fluxes.

  6. MODIS Views Variations in Cloud Types

    NASA Technical Reports Server (NTRS)

    2002-01-01

    This MODIS image, centered over the Great Lakes region in North America, shows a variety of cloud types. The clouds at the top of the image, colored pink, are cold, high-level snow and ice clouds, while the neon green clouds are lower-level water clouds. Because different cloud types reflect and emit radiant energy differently, scientists can use MODIS' unique data set to measure the sizes of cloud particles and distinguish between water, snow, and ice clouds. This scene was acquired on Feb. 24, 2000, and is a red, green, blue composite of bands 1, 6, and 31 (0.66, 1.6, and 11.0 microns, respectively). Image by Liam Gumley, Space Science and Engineering Center, University of Wisconsin-Madison

  7. Cloud cover typing from environmental satellite imagery. Discriminating cloud structure with Fast Fourier Transforms (FFT)

    NASA Technical Reports Server (NTRS)

    Logan, T. L.; Huning, J. R.; Glackin, D. L.

    1983-01-01

    The use of two dimensional Fast Fourier Transforms (FFTs) subjected to pattern recognition technology for the identification and classification of low altitude stratus cloud structure from Geostationary Operational Environmental Satellite (GOES) imagery was examined. The development of a scene independent pattern recognition methodology, unconstrained by conventional cloud morphological classifications was emphasized. A technique for extracting cloud shape, direction, and size attributes from GOES visual imagery was developed. These attributes were combined with two statistical attributes (cloud mean brightness, cloud standard deviation), and interrogated using unsupervised clustering amd maximum likelihood classification techniques. Results indicate that: (1) the key cloud discrimination attributes are mean brightness, direction, shape, and minimum size; (2) cloud structure can be differentiated at given pixel scales; (3) cloud type may be identifiable at coarser scales; (4) there are positive indications of scene independence which would permit development of a cloud signature bank; (5) edge enhancement of GOES imagery does not appreciably improve cloud classification over the use of raw data; and (6) the GOES imagery must be apodized before generation of FFTs.

  8. Observational evidence for the aerosol impact on ice cloud properties regulated by cloud/aerosol types

    NASA Astrophysics Data System (ADS)

    Zhao, B.; Gu, Y.; Liou, K. N.; Jiang, J. H.; Li, Q.; Liu, X.; Huang, L.; Wang, Y.; Su, H.

    2016-12-01

    The interactions between aerosols and ice clouds (consisting only of ice) represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. The observational evidence for the aerosol impact on ice cloud properties has been quite limited and showed conflicting results, partly because previous observational studies did not consider the distinct features of different ice cloud and aerosol types. Using 9-year satellite observations, we find that, for ice clouds generated from deep convection, cloud thickness, cloud optical thickness (COT), and ice cloud fraction increase and decrease with small-to-moderate and high aerosol loadings, respectively. For in-situ formed ice clouds, however, the preceding cloud properties increase monotonically and more sharply with aerosol loadings. The case is more complicated for ice crystal effective radius (Rei). For both convection-generated and in-situ ice clouds, the responses of Rei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters, but the sensitivities of Rei to aerosols under the same water vapor amount differ remarkably between the two ice cloud types. As a result, overall Rei slightly increases with aerosol loading for convection-generated ice clouds, but decreases for in-situ ice clouds. When aerosols are decomposed into different types, an increase in the loading of smoke aerosols generally leads to a decrease in COT of convection-generated ice clouds, while the reverse is true for dust and anthropogenic pollution. In contrast, an increase in the loading of any aerosol type can significantly enhance COT of in-situ ice clouds. The modulation of the aerosol impacts by cloud/aerosol types is demonstrated and reproduced by simulations using the Weather Research and Forecasting (WRF) model. Adequate and accurate representations of the impact of different cloud/aerosol types in climate models are crucial for reducing the

  9. Observational evidence for the aerosol impact on ice cloud properties regulated by cloud/aerosol types

    NASA Astrophysics Data System (ADS)

    Zhao, B.; Gu, Y.; Liou, K. N.; Jiang, J. H.; Li, Q.; Liu, X.; Huang, L.; Wang, Y.; Su, H.

    2017-12-01

    The interactions between aerosols and ice clouds (consisting only of ice) represent one of the largest uncertainties in global radiative forcing from pre-industrial time to the present. The observational evidence for the aerosol impact on ice cloud properties has been quite limited and showed conflicting results, partly because previous observational studies did not consider the distinct features of different ice cloud and aerosol types. Using 9-year satellite observations, we find that, for ice clouds generated from deep convection, cloud thickness, cloud optical thickness (COT), and ice cloud fraction increase and decrease with small-to-moderate and high aerosol loadings, respectively. For in-situ formed ice clouds, however, the preceding cloud properties increase monotonically and more sharply with aerosol loadings. The case is more complicated for ice crystal effective radius (Rei). For both convection-generated and in-situ ice clouds, the responses of Rei to aerosol loadings are modulated by water vapor amount in conjunction with several other meteorological parameters, but the sensitivities of Rei to aerosols under the same water vapor amount differ remarkably between the two ice cloud types. As a result, overall Rei slightly increases with aerosol loading for convection-generated ice clouds, but decreases for in-situ ice clouds. When aerosols are decomposed into different types, an increase in the loading of smoke aerosols generally leads to a decrease in COT of convection-generated ice clouds, while the reverse is true for dust and anthropogenic pollution. In contrast, an increase in the loading of any aerosol type can significantly enhance COT of in-situ ice clouds. The modulation of the aerosol impacts by cloud/aerosol types is demonstrated and reproduced by simulations using the Weather Research and Forecasting (WRF) model. Adequate and accurate representations of the impact of different cloud/aerosol types in climate models are crucial for reducing the

  10. Photogrammetry and photo interpretation applied to analyses of cloud cover, cloud type, and cloud motion

    NASA Technical Reports Server (NTRS)

    Larsen, P. A.

    1972-01-01

    A determination was made of the areal extent of terrain obscured by clouds and cloud shadows on a portion of an Apollo 9 photograph at the instant of exposure. This photogrammetrically determined area was then compared to the cloud coverage reported by surface weather observers at approximately the same time and location, as a check on result quality. Stereograms prepared from Apollo 9 vertical photographs, illustrating various percentages of cloud coverage, are presented to help provide a quantitative appreciation of the degradation of terrain photography by clouds and their attendant shadows. A scheme, developed for the U.S. Navy, utilizing pattern recognition techniques for determining cloud motion from sequences of satellite photographs, is summarized. Clouds, turbulence, haze, and solar altitude, four elements of our natural environment which affect aerial photographic missions, are each discussed in terms of their effects on imagery obtained by aerial photography. Data of a type useful to aerial photographic mission planners, expressing photographic ground coverage in terms of flying height above terrain and camera focal length, for a standard aerial photograph format, are provided. Two oblique orbital photographs taken during the Apollo 9 flight are shown, and photo-interpretations, discussing the cloud types imaged and certain visible geographical features, are provided.

  11. Cloud radiative effect, cloud fraction and cloud type at two stations in Switzerland using hemispherical sky cameras

    NASA Astrophysics Data System (ADS)

    Aebi, Christine; Gröbner, Julian; Kämpfer, Niklaus; Vuilleumier, Laurent

    2017-11-01

    The current study analyses the cloud radiative effect during the daytime depending on cloud fraction and cloud type at two stations in Switzerland over a time period of 3 to 5 years. Information on fractional cloud coverage and cloud type is retrieved from images taken by visible all-sky cameras. Cloud-base height (CBH) data are retrieved from a ceilometer and integrated water vapour (IWV) data from GPS measurements. The longwave cloud radiative effect (LCE) for low-level clouds and a cloud coverage of 8 oktas has a median value between 59 and 72 Wm-2. For mid- and high-level clouds the LCE is significantly lower. It is shown that the fractional cloud coverage, the CBH and IWV all have an influence on the magnitude of the LCE. These observed dependences have also been modelled with the radiative transfer model MODTRAN5. The relative values of the shortwave cloud radiative effect (SCErel) for low-level clouds and a cloud coverage of 8 oktas are between -90 and -62 %. Also here the higher the cloud is, the less negative the SCErel values are. In cases in which the measured direct radiation value is below the threshold of 120 Wm-2 (occulted sun) the SCErel decreases substantially, while cases in which the measured direct radiation value is larger than 120 Wm-2 (visible sun) lead to a SCErel of around 0 %. In 14 and 10 % of the cases in Davos and Payerne respectively a cloud enhancement has been observed with a maximum in the cloud class cirrocumulus-altocumulus at both stations. The calculated median total cloud radiative effect (TCE) values are negative for almost all cloud classes and cloud coverages.

  12. Quantifying Diurnal Cloud Radiative Effects by Cloud Type in the Tropical Western Pacific

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Burleyson, Casey D.; Long, Charles N.; Comstock, Jennifer M.

    2015-06-01

    Cloud radiative effects are examined using long-term datasets collected at the three Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facilities in the tropical western Pacific. We quantify the surface radiation budget, cloud populations, and cloud radiative effects by partitioning the data by cloud type, time of day, and as a function of large scale modes of variability such as El Niño Southern Oscillation (ENSO) phase and wet/dry seasons at Darwin. The novel facet of our analysis is that we break aggregate cloud radiative effects down by cloud type across the diurnal cycle. The Nauru cloud populations andmore » subsequently the surface radiation budget are strongly impacted by ENSO variability whereas the cloud populations over Manus only shift slightly in response to changes in ENSO phase. The Darwin site exhibits large seasonal monsoon related variations. We show that while deeper convective clouds have a strong conditional influence on the radiation reaching the surface, their limited frequency reduces their aggregate radiative impact. The largest source of shortwave cloud radiative effects at all three sites comes from low clouds. We use the observations to demonstrate that potential model biases in the amplitude of the diurnal cycle and mean cloud frequency would lead to larger errors in the surface energy budget compared to biases in the timing of the diurnal cycle of cloud frequency. Our results provide solid benchmarks to evaluate model simulations of cloud radiative effects in the tropics.« less

  13. Studies in the use of cloud type statistics in mission simulation

    NASA Technical Reports Server (NTRS)

    Fowler, M. G.; Willand, J. H.; Chang, D. T.; Cogan, J. L.

    1974-01-01

    A study to further improve NASA's global cloud statistics for mission simulation is reported. Regional homogeneity in cloud types was examined; most of the original region boundaries defined for cloud cover amount in previous studies were supported by the statistics on cloud types and the number of cloud layers. Conditionality in cloud statistics was also examined with special emphasis on temporal and spatial dependencies, and cloud type interdependence. Temporal conditionality was found up to 12 hours, and spatial conditionality up to 200 miles; the diurnal cycle in convective cloudiness was clearly evident. As expected, the joint occurrence of different cloud types reflected the dynamic processes which form the clouds. Other phases of the study improved the cloud type statistics for several region and proposed a mission simulation scheme combining the 4-dimensional atmospheric model, sponsored by MSFC, with the global cloud model.

  14. Exploiting Cloud Radar Doppler Spectra of Mixed-Phase Clouds during ACCEPT Field Experiment to Identify Microphysical Processes

    NASA Astrophysics Data System (ADS)

    Kalesse, H.; Myagkov, A.; Seifert, P.; Buehl, J.

    2015-12-01

    Cloud radar Doppler spectra offer much information about cloud processes. By analyzing millimeter radar Doppler spectra from cloud-top to -base in mixed-phase clouds in which super-cooled liquid-layers are present we try to tell the microphysical evolution story of particles that are present by disentangling the contributions of the solid and liquid particles to the total radar returns. Instead of considering vertical profiles, dynamical effects are taken into account by following the particle population evolution along slanted paths which are caused by horizontal advection of the cloud. The goal is to identify regions in which different microphysical processes such as new particle formation (nucleation), water vapor deposition, aggregation, riming, or sublimation occurr. Cloud radar measurements are supplemented by Doppler lidar and Raman lidar observations as well as observations with MWR, wind profiler, and radio sondes. The presence of super-cooled liquid layers is identified by positive liquid water paths in MWR measurements, the vertical location of liquid layers (in non-raining systems and below lidar extinction) is derived from regions of high-backscatter and low depolarization in Raman lidar observations. In collocated cloud radar measurements, we try to identify cloud phase in the cloud radar Doppler spectrum via location of the Doppler peak(s), the existence of multi-modalities or the spectral skewness. Additionally, within the super-cooled liquid layers, the radar-identified liquid droplets are used as air motion tracer to correct the radar Doppler spectrum for vertical air motion w. These radar-derived estimates of w are validated by independent estimates of w from collocated Doppler lidar measurements. A 35 GHz vertically pointing cloud Doppler radar (METEK MIRA-35) in linear depolarization (LDR) mode is used. Data is from the deployment of the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of

  15. Cloud types and the tropical Earth radiation budget, revised

    NASA Technical Reports Server (NTRS)

    Dhuria, Harbans L.; Kyle, H. Lee

    1989-01-01

    Nimbus-7 cloud and Earth radiation budget data are compared in a study of the effects of clouds on the tropical radiation budget. The data consist of daily averages over fixed 500 sq km target areas, and the months of July 1979 and January 1980 were chosen to show the effect of seasonal changes. Six climate regions, consisting of 14 to 24 target areas each, were picked for intensive analysis because they exemplified the range in the tropical cloud/net radiation interactions. The normal analysis was to consider net radiation as the independent variable and examine how cloud cover, cloud type, albedo and emitted radiation varied with the net radiation. Two recurring themes keep repeating on a local, regional, and zonal basis: the net radiation is strongly influenced by the average cloud type and amount present, but most net radiation values could be produced by several combinations of cloud types and amount. The regions of highest net radiation (greater than 125 W/sq m) tend to have medium to heavy cloud cover. In these cases, thin medium altitude clouds predominate. Their cloud tops are normally too warm to be classified as cirrus by the Nimbus cloud algorithm. A common feature in the tropical oceans are large regions where the total regional cloud cover varies from 20 to 90 percent, but with little regional difference in the net radiation. The monsoon and rain areas are high net radiation regions.

  16. Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, Zhien

    2010-06-29

    The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processesmore » is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model

  17. Reassessing the effect of cloud type on Earth's energy balance

    NASA Astrophysics Data System (ADS)

    Hang, A.; L'Ecuyer, T.

    2017-12-01

    Cloud feedbacks depend critically on the characteristics of the clouds that change, their location and their environment. As a result, accurately predicting the impact of clouds on future climate requires a better understanding of individual cloud types and their spatial and temporal variability. This work revisits the problem of documenting the effects of distinct cloud regimes on Earth's radiation budget distinguishing cloud types according to their signatures in spaceborne active observations. Using CloudSat's multi-sensor radiative fluxes product that leverages high-resolution vertical cloud information from CloudSat, CALIPSO, and MODIS observations to provide the most accurate estimates of vertically-resolved radiative fluxes available to date, we estimate the global annual mean net cloud radiative effect at the top of the atmosphere to be -17.1 W m-2 (-44.2 W m-2 in the shortwave and 27.1 W m-2 in the longwave), slightly weaker than previous estimates from passive sensor observations. Multi-layered cloud systems, that are often misclassified using passive techniques but are ubiquitous in both hemispheres, contribute about -6.2 W m-2 of the net cooling effect, particularly at ITCZ and higher latitudes. Another unique aspect of this work is the ability of CloudSat and CALIPSO to detect cloud boundary information providing an improved capability to accurately discern the impact of cloud-type variations on surface radiation balance, a critical factor in modulating the disposition of excess energy in the climate system. The global annual net cloud radiative effect at the surface is estimated to be -24.8 W m-2 (-51.1 W m-2 in the shortwave and 26.3 W m-2 in the longwave), dominated by shortwave heating in multi-layered and stratocumulus clouds. Corresponding estimates of the effects of clouds on atmospheric heating suggest that clouds redistribute heat from poles to equator enhancing the general circulation.

  18. Type-Dependent Responses of Ice Cloud Properties to Aerosols From Satellite Retrievals

    NASA Astrophysics Data System (ADS)

    Zhao, Bin; Gu, Yu; Liou, Kuo-Nan; Wang, Yuan; Liu, Xiaohong; Huang, Lei; Jiang, Jonathan H.; Su, Hui

    2018-04-01

    Aerosol-cloud interactions represent one of the largest uncertainties in external forcings on our climate system. Compared with liquid clouds, the observational evidence for the aerosol impact on ice clouds is much more limited and shows conflicting results, partly because the distinct features of different ice cloud and aerosol types were seldom considered. Using 9-year satellite retrievals, we find that, for convection-generated (anvil) ice clouds, cloud optical thickness, cloud thickness, and cloud fraction increase with small-to-moderate aerosol loadings (<0.3 aerosol optical depth) and decrease with further aerosol increase. For in situ formed ice clouds, however, these cloud properties increase monotonically and more sharply with aerosol loadings. An increase in loading of smoke aerosols generally reduces cloud optical thickness of convection-generated ice clouds, while the reverse is true for dust and anthropogenic pollution aerosols. These relationships between different cloud/aerosol types provide valuable constraints on the modeling assessment of aerosol-ice cloud radiative forcing.

  19. Changes in the type of precipitation and associated cloud types in Eastern Romania (1961-2008)

    NASA Astrophysics Data System (ADS)

    Manea, Ancuta; Birsan, Marius-Victor; Tudorache, George; Cărbunaru, Felicia

    2016-03-01

    Recent climate change is characterized (among other things) by changes in the frequency of some meteorological phenomena. This paper deals with the long-term changes in various precipitation types, and the connection between their variability and cloud type frequencies, at 11 meteorological stations from Eastern Romania over 1961-2008. These stations were selected with respect to data record completeness for all considered variables (weather phenomena and cloud type). The meteorological variables involved in the present study are: monthly number of days with rain, snowfall, snow showers, rain and snow (sleet), sleet showers and monthly frequency of the Cumulonimbus, Nimbostratus and Stratus clouds. Our results show that all stations present statistically significant decreasing trends in the number of days with rain in the warm period of the year. Changes in the frequency of days for each precipitation type show statistically significant decreasing trends for non-convective (stratiform) precipitation - rain, drizzle, sleet and snowfall -, while the frequencies of rain shower and snow shower (convective precipitation) are increasing. Cloud types show decreasing trends for Nimbostratus and Stratus, and increasing trends for Cumulonimbus.

  20. Identifying clouds over the Pierre Auger Observatory using infrared satellite data

    NASA Astrophysics Data System (ADS)

    Abreu, P.; Aglietta, M.; Ahlers, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allekotte, I.; Allen, J.; Allison, P.; Almela, A.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Alves Batista, R.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Aramo, C.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Badescu, A. M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Baughman, B.; Bäuml, J.; Baus, C.; Beatty, J. J.; Becker, K. H.; Bellétoile, A.; Bellido, J. A.; BenZvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brancus, I.; Brogueira, P.; Brown, W. C.; Buchholz, P.; Bueno, A.; Buroker, L.; Burton, R. E.; Buscemi, M.; Caballero-Mora, K. S.; Caccianiga, B.; Caccianiga, L.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Cheng, S. H.; Chiavassa, A.; Chinellato, J. A.; Chirinos, J.; Chudoba, J.; Cilmo, M.; Clay, R. W.; Cocciolo, G.; Colalillo, R.; Collica, L.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coutu, S.; Covault, C. E.; Criss, A.; Cronin, J.; Curutiu, A.; Dallier, R.; Daniel, B.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; De Domenico, M.; de Jong, S. J.; De La Vega, G.; de Mello, W. J. M.; de Mello Neto, J. R. T.; De Mitri, I.; de Souza, V.; de Vries, K. D.; del Peral, L.; Deligny, O.; Dembinski, H.; Dhital, N.; Di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Diogo, F.; Dobrigkeit, C.; Docters, W.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Espadanal, J.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Fang, K.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Fick, B.; Figueira, J. M.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fox, B. D.; Fracchiolla, C. E.; Fraenkel, E. D.; Fratu, O.; Fröhlich, U.; Fuchs, B.; Gaior, R.; Gamarra, R. F.; Gambetta, S.; García, B.; Garcia Roca, S. T.; Garcia-Gamez, D.; Garcia-Pinto, D.; Garilli, G.; Gascon Bravo, A.; Gemmeke, H.; Ghia, P. L.; Giller, M.; Gitto, J.; Glaser, C.; Glass, H.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gómez Vitale, P. F.; Gonçalves, P.; Gonzalez, J. G.; Gookin, B.; Gorgi, A.; Gorham, P.; Gouffon, P.; Grebe, S.; Griffith, N.; Grillo, A. F.; Grubb, T. D.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hansen, P.; Harari, D.; Harrison, T. A.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hill, G. C.; Hojvat, C.; Hollon, N.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horvath, P.; Hrabovský, M.; Huber, D.; Huege, T.; Insolia, A.; Jansen, S.; Jarne, C.; Jiraskova, S.; Josebachuili, M.; Kadija, K.; Kampert, K. H.; Karhan, P.; Kasper, P.; Katkov, I.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Krause, R.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; LaHurd, D.; Latronico, L.; Lauer, R.; Lauscher, M.; Lautridou, P.; Le Coz, S.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lu, L.; Lucero, A.; Ludwig, M.; Lyberis, H.; Maccarone, M. C.; Macolino, C.; Malacari, M.; Maldera, S.; Maller, J.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, J.; Marin, V.; Mariş, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martinez, H.; Martínez Bravo, O.; Martraire, D.; Masías Meza, J. J.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurel, D.; Maurizio, D.; Mayotte, E.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Messina, S.; Meyhandan, R.; Mićanović, S.; Micheletti, M. I.; Middendorf, L.; Minaya, I. A.; Miramonti, L.; Mitrica, B.; Molina-Bueno, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, J. C.; Mostafá, M.; Moura, C. A.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Neuser, J.; Nhung, P. T.; Niechciol, M.; Niemietz, L.; Nierstenhoefer, N.; Niggemann, T.; Nitz, D.; Nosek, D.; Nožka, L.; Oehlschläger, J.; Olinto, A.; Oliveira, M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parra, A.; Pastor, S.; Paul, T.; Pech, M.; Peķala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrolini, A.; Petrov, Y.; Pfendner, C.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Plum, M.; Ponce, V. H.; Pontz, M.; Porcelli, A.; Privitera, P.; Prouza, M.; Quel, E. J.; Querchfeld, S.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Riggi, S.; Risse, M.; Ristori, P.; Rivera, H.; Rizi, V.; Roberts, J.; Rodrigues de Carvalho, W.; Rodriguez Cabo, I.; Rodriguez Fernandez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-d'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Saffi, S. J.; Saftoiu, A.; Salamida, F.; Salazar, H.; Salesa Greus, F.; Salina, G.; Sánchez, F.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, B.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schröder, F. G.; Schulz, J.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Sima, O.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Srivastava, Y. N.; Stanič, S.; Stapleton, J.; Stasielak, J.; Stephan, M.; Straub, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tapia, A.; Tartare, M.; Taşcău, O.; Tcaciuc, R.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tkaczyk, W.; Todero Peixoto, C. J.; Toma, G.; Tomankova, L.; Tomé, B.; Tonachini, A.; Torralba Elipe, G.; Torres Machado, D.; Travnicek, P.; Tridapalli, D. B.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van Aar, G.; van den Berg, A. M.; van Velzen, S.; van Vliet, A.; Varela, E.; Vargas Cárdenas, B.; Varner, G.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Vicha, J.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Walz, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Werner, F.; Westerhoff, S.; Whelan, B. J.; Widom, A.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Wundheiler, B.; Yamamoto, T.; Yapici, T.; Younk, P.; Yuan, G.; Yushkov, A.; Zamorano Garcia, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Zhou, J.; Zhu, Y.; Zimbres Silva, M.; Ziolkowski, M.

    2013-12-01

    We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ˜2.4 km by ˜5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

  1. Identifying clouds over the Pierre Auger Observatory using infrared satellite data

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Abreu, Pedro; et al.,

    2013-12-01

    We describe a new method of identifying night-time clouds over the Pierre Auger Observatory using infrared data from the Imager instruments on the GOES-12 and GOES-13 satellites. We compare cloud identifications resulting from our method to those obtained by the Central Laser Facility of the Auger Observatory. Using our new method we can now develop cloud probability maps for the 3000 km^2 of the Pierre Auger Observatory twice per hour with a spatial resolution of ~2.4 km by ~5.5 km. Our method could also be applied to monitor cloud cover for other ground-based observatories and for space-based observatories.

  2. AIRS Subpixel Cloud Characterization Using MODIS Cloud Products.

    NASA Astrophysics Data System (ADS)

    Li, Jun; Menzel, W. Paul; Sun, Fengying; Schmit, Timothy J.; Gurka, James

    2004-08-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable improved global monitoring of the distribution of clouds. MODIS is able to provide, at high spatial resolution (1 5 km), a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud optical thickness (COT). AIRS is able to provide CTP, ECA, CPS, and COT at coarser spatial resolution (13.5 km at nadir) but with much better accuracy using its high-spectral-resolution measurements. The combined MODIS AIRS system offers the opportunity for improved cloud products over those possible from either system alone. The key steps for synergistic use of imager and sounder radiance measurements are 1) collocation in space and time and 2) imager cloud amount, type, and phase determination within the sounder pixel. The MODIS and AIRS measurements from the EOS Aqua satellite provide the opportunity to study the synergistic use of advanced imager and sounder measurements. As the first step, the MODIS classification procedure is applied to identify various surface and cloud types within an AIRS footprint. Cloud-layer information (lower, midlevel, or high clouds) and phase information (water, ice, or mixed-phase clouds) within the AIRS footprint are sorted and characterized using MODIS 1-km-spatial-resolution data. The combined MODIS and AIRS data for various scenes are analyzed to study the utility of the synergistic use of high-spatial-resolution imager products and high-spectral-resolution sounder radiance measurements. There is relevance to the optimal use of data from the Advanced Baseline Imager (ABI) and Hyperspectral Environmental Suite (HES) systems, which are to fly on the Geostationary Operational Environmental Satellite (GOES)-R.


  3. Using cloud models of heartbeats as the entity identifier to secure mobile devices.

    PubMed

    Fu, Donglai; Liu, Yanhua

    2017-01-01

    Mobile devices are extensively used to store more private and often sensitive information. Therefore, it is important to protect them against unauthorised access. Authentication ensures that authorised users can use mobile devices. However, traditional authentication methods, such as numerical or graphic passwords, are vulnerable to passive attacks. For example, an adversary can steal the password by snooping from a shorter distance. To avoid these problems, this study presents a biometric approach that uses cloud models of heartbeats as the entity identifier to secure mobile devices. Here, it is identified that these concepts including cloud model or cloud have nothing to do with cloud computing. The cloud model appearing in the study is the cognitive model. In the proposed method, heartbeats are collected by two ECG electrodes that are connected to one mobile device. The backward normal cloud generator is used to generate ECG standard cloud models characterising the heartbeat template. When a user tries to have access to their mobile device, cloud models regenerated by fresh heartbeats will be compared with ECG standard cloud models to determine if the current user can use this mobile device. This authentication method was evaluated from three aspects including accuracy, authentication time and energy consumption. The proposed method gives 86.04% of true acceptance rate with 2.73% of false acceptance rate. One authentication can be done in 6s, and this processing consumes about 2000 mW of power.

  4. Relating Solar Resource Variability to Cloud Type

    NASA Astrophysics Data System (ADS)

    Hinkelman, L. M.; Sengupta, M.

    2012-12-01

    Power production from renewable energy (RE) resources is rapidly increasing. Generation of renewable energy is quite variable since the solar and wind resources that form the inputs are, themselves, inherently variable. There is thus a need to understand the impact of renewable generation on the transmission grid. Such studies require estimates of high temporal and spatial resolution power output under various scenarios, which can be created from corresponding solar resource data. Satellite-based solar resource estimates are the best source of long-term solar irradiance data for the typically large areas covered by transmission studies. As satellite-based resource datasets are generally available at lower temporal and spatial resolution than required, there is, in turn, a need to downscale these resource data. Downscaling in both space and time requires information about solar irradiance variability, which is primarily a function of cloud types and properties. In this study, we analyze the relationship between solar resource variability and satellite-based cloud properties. One-minute resolution surface irradiance data were obtained from a number of stations operated by the National Oceanic and Atmospheric Administration (NOAA) under the Surface Radiation (SURFRAD) and Integrated Surface Irradiance Study (ISIS) networks as well as from NREL's Solar Radiation Research Laboratory (SRRL) in Golden, Colorado. Individual sites were selected so that a range of meteorological conditions would be represented. Cloud information at a nominal 4 km resolution and half hour intervals was derived from NOAA's Geostationary Operation Environmental Satellite (GOES) series of satellites. Cloud class information from the GOES data set was then used to select and composite irradiance data from the measurement sites. The irradiance variability for each cloud classification was characterized using general statistics of the fluxes themselves and their variability in time, as represented

  5. Online single particle analysis of ice particle residuals from mountain-top mixed-phase clouds using laboratory derived particle type assignment

    NASA Astrophysics Data System (ADS)

    Schmidt, Susan; Schneider, Johannes; Klimach, Thomas; Mertes, Stephan; Schenk, Ludwig Paul; Kupiszewski, Piotr; Curtius, Joachim; Borrmann, Stephan

    2017-01-01

    In situ single particle analysis of ice particle residuals (IPRs) and out-of-cloud aerosol particles was conducted by means of laser ablation mass spectrometry during the intensive INUIT-JFJ/CLACE campaign at the high alpine research station Jungfraujoch (3580 m a.s.l.) in January-February 2013. During the 4-week campaign more than 70 000 out-of-cloud aerosol particles and 595 IPRs were analyzed covering a particle size diameter range from 100 nm to 3 µm. The IPRs were sampled during 273 h while the station was covered by mixed-phase clouds at ambient temperatures between -27 and -6 °C. The identification of particle types is based on laboratory studies of different types of biological, mineral and anthropogenic aerosol particles. The outcome of these laboratory studies was characteristic marker peaks for each investigated particle type. These marker peaks were applied to the field data. In the sampled IPRs we identified a larger number fraction of primary aerosol particles, like soil dust (13 ± 5 %) and minerals (11 ± 5 %), in comparison to out-of-cloud aerosol particles (2.4 ± 0.4 and 0.4 ± 0.1 %, respectively). Additionally, anthropogenic aerosol particles, such as particles from industrial emissions and lead-containing particles, were found to be more abundant in the IPRs than in the out-of-cloud aerosol. In the out-of-cloud aerosol we identified a large fraction of aged particles (31 ± 5 %), including organic material and secondary inorganics, whereas this particle type was much less abundant (2.7 ± 1.3 %) in the IPRs. In a selected subset of the data where a direct comparison between out-of-cloud aerosol particles and IPRs in air masses with similar origin was possible, a pronounced enhancement of biological particles was found in the IPRs.

  6. A Climatology of Polar Stratospheric Cloud Types by MIPAS-Envisat

    NASA Astrophysics Data System (ADS)

    Spang, Reinhold; Hoffmann, Lars; Griessbach, Sabine; Orr, Andrew; Höpfner, Michael; Müller, Rolf

    2015-04-01

    For Chemistry Climate Models (CCM) it is still a challenging task to properly represent the evolution of the polar vortices over the entire winter season. The models usually do not include comprehensive microphysical modules to evolve the formation of different types of polar stratospheric clouds (PSC) over the winter. Consequently, predictions on the development and recovery of the future ozone hole have relatively large uncertainties. A climatological record of hemispheric measurement of PSC types could help to better validate and improve the PSC schemes in CCMs. The Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument onboard the ESA Envisat satellite operated from July 2002 to April 2012. The infra-red limb emission measurements compile a unique dataset of day and night measurements of polar stratospheric clouds up to the poles. From the spectral measurements in the 4.15-14.6 microns range it is possible to select a number of atmospheric window regions and spectral signatures to classify PSC cloud types like nitric acid hydrates, sulfuric ternary solution droplets, and ice particles. The cloud detection sensitivity is similar to space borne lidars, but MIPAS adds complementary information due to its different measurement technique (limb instead of nadir) and wavelength region. Here we will describe a new classification method for PSCs based on the combination of multiple brightness temperature differences (BTD) and colour ratios. Probability density functions (PDF) of the MIPAS measurements in conjunction with a database of radiative transfer model calculations of realistic PSC particle size distributions enable the definition of regions attributed to specific or mixed types clouds. Applying a naive bias classifier for independent criteria to all defined classes in four 2D PDF distributions, it is possible to assign the most likely PSC type to any measured cloud spectrum. Statistical Monte Carlo test have been applied to quantify

  7. Effects of 3-D clouds on atmospheric transmission of solar radiation: Cloud type dependencies inferred from A-train satellite data

    NASA Astrophysics Data System (ADS)

    Ham, Seung-Hee; Kato, Seiji; Barker, Howard W.; Rose, Fred G.; Sun-Mack, Sunny

    2014-01-01

    Three-dimensional (3-D) effects on broadband shortwave top of atmosphere (TOA) nadir radiance, atmospheric absorption, and surface irradiance are examined using 3-D cloud fields obtained from one hour's worth of A-train satellite observations and one-dimensional (1-D) independent column approximation (ICA) and full 3-D radiative transfer simulations. The 3-D minus ICA differences in TOA nadir radiance multiplied by π, atmospheric absorption, and surface downwelling irradiance, denoted as πΔI, ΔA, and ΔT, respectively, are analyzed by cloud type. At the 1 km pixel scale, πΔI, ΔA, and ΔT exhibit poor spatial correlation. Once averaged with a moving window, however, better linear relationships among πΔI, ΔA, and ΔT emerge, especially for moving windows larger than 5 km and large θ0. While cloud properties and solar geometry are shown to influence the relationships amongst πΔI, ΔA, and ΔT, once they are separated by cloud type, their linear relationships become much stronger. This suggests that ICA biases in surface irradiance and atmospheric absorption can be approximated based on ICA biases in nadir radiance as a function of cloud type.

  8. The identification of cloud types in LANDSAT MSS images. [Great Britain

    NASA Technical Reports Server (NTRS)

    Barrett, E. C. (Principal Investigator); Grant, C. K.

    1976-01-01

    The author has identified the following significant results. Five general families of clouds were identified: cumulonimbiform, cumuliform, stratiform, stratocumuliform, and cirriform. Four members of this five-fold primary division of clouds were further divided into a number of subgroups. The MSS observed and recorded earth radiation in four different wavebands. Two of these bands (4 and 5) image in the visible portion of the electromagnetic spectrum, while the others (6 and 7) image the short wave portion, or just into the infrared. The main differences between the appearances of clouds in the four wavebands are related to the background brightness of land and sea surfaces.

  9. Compact Neutral Hydrogen Clouds: Searching for Undiscovered Dwarf Galaxies and Gas Associated with an Algol-type Variable Star

    NASA Astrophysics Data System (ADS)

    Grcevich, Jana; Berger, Sabrina; Putman, Mary E.; Eli Goldston Peek, Joshua

    2016-01-01

    Several interesting compact neutral hydrogen clouds were found in the GALFA-HI (Galactic Arecibo L-Band Feed Array HI) survey which may represent undiscovered dwarf galaxy candidates. The continuation of this search is motivated by successful discoveries of Local Volume dwarfs in the GALFA-HI DR1. We identify additional potential dwarf galaxies from the GALFA-HI DR1 Compact Cloud Catalog which are indentified as having unexpected velocities given their other characteristics via the bayesian analysis software BayesDB. We also present preliminary results of a by-eye search for dwarf galaxies in the GALFA-HI DR2, which provides additional sky coverage. Interestingly, one particularly compact cloud discovered during our dwarf galaxy search is spatially coincident with an Algol-type variable star. Although the association is tentative, Algol-type variables are thought to have undergone significant gas loss and it is possible this gas may be observable in HI.

  10. CMSAF products Cloud Fraction Coverage and Cloud Type used for solar global irradiance estimation

    NASA Astrophysics Data System (ADS)

    Badescu, Viorel; Dumitrescu, Alexandru

    2016-08-01

    Two products provided by the climate monitoring satellite application facility (CMSAF) are the instantaneous Cloud Fractional Coverage (iCFC) and the instantaneous Cloud Type (iCTY) products. Previous studies based on the iCFC product show that the simple solar radiation models belonging to the cloudiness index class n CFC = 0.1-1.0 have rRMSE values ranging between 68 and 71 %. The products iCFC and iCTY are used here to develop simple models providing hourly estimates for solar global irradiance. Measurements performed at five weather stations of Romania (South-Eastern Europe) are used. Two three-class characterizations of the state-of-the-sky, based on the iCTY product, are defined. In case of the first new sky state classification, which is roughly related with cloud altitude, the solar radiation models proposed here perform worst for the iCTY class 4-15, with rRMSE values ranging between 46 and 57 %. The spreading error of the simple models is lower than that of the MAGIC model for the iCTY classes 1-4 and 15-19, but larger for iCTY classes 4-15. In case of the second new sky state classification, which takes into account in a weighted manner the chance for the sun to be covered by different types of clouds, the solar radiation models proposed here perform worst for the cloudiness index class n CTY = 0.7-0.1, with rRMSE values ranging between 51 and 66 %. Therefore, the two new sky state classifications based on the iCTY product are useful in increasing the accuracy of solar radiation models.

  11. Statistical Analyses of Satellite Cloud Object Data From CERES. Part 4; Boundary-layer Cloud Objects During 1998 El Nino

    NASA Technical Reports Server (NTRS)

    Xu, Kuan-Man; Wong, Takmeng; Wielicki, Bruce A.; Parker, Lindsay

    2006-01-01

    Three boundary-layer cloud object types, stratus, stratocumulus and cumulus, that occurred over the Pacific Ocean during January-August 1998, are identified from the CERES (Clouds and the Earth s Radiant Energy System) single scanner footprint (SSF) data from the TRMM (Tropical Rainfall Measuring Mission) satellite. This study emphasizes the differences and similarities in the characteristics of each cloud-object type between the tropical and subtropical regions and among different size categories and among small geographic areas. Both the frequencies of occurrence and statistical distributions of cloud physical properties are analyzed. In terms of frequencies of occurrence, stratocumulus clouds dominate the entire boundary layer cloud population in all regions and among all size categories. Stratus clouds are more prevalent in the subtropics and near the coastal regions, while cumulus clouds are relatively prevalent over open ocean and the equatorial regions, particularly, within the small size categories. The largest size category of stratus cloud objects occurs more frequently in the subtropics than in the tropics and has much larger average size than its cumulus and stratocumulus counterparts. Each of the three cloud object types exhibits small differences in statistical distributions of cloud optical depth, liquid water path, TOA albedo and perhaps cloud-top height, but large differences in those of cloud-top temperature and OLR between the tropics and subtropics. Differences in the sea surface temperature (SST) distributions between the tropics and subtropics influence some of the cloud macrophysical properties, but cloud microphysical properties and albedo for each cloud object type are likely determined by (local) boundary-layer dynamics and structures. Systematic variations of cloud optical depth, TOA albedo, cloud-top height, OLR and SST with cloud object sizes are pronounced for the stratocumulus and stratus types, which are related to systematic

  12. LUMINOSITY FUNCTIONS OF SPITZER-IDENTIFIED PROTOSTARS IN NINE NEARBY MOLECULAR CLOUDS

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kryukova, E.; Megeath, S. T.; Allen, T. S.

    2012-08-15

    We identify protostars in Spitzer surveys of nine star-forming (SF) molecular clouds within 1 kpc: Serpens, Perseus, Ophiuchus, Chamaeleon, Lupus, Taurus, Orion, Cep OB3, and Mon R2, which combined host over 700 protostar candidates. These clouds encompass a variety of SF environments, including both low-mass and high-mass SF regions, as well as dense clusters and regions of sparsely distributed star formation. Our diverse cloud sample allows us to compare protostar luminosity functions in these varied environments. We combine near- and mid-infrared photometry from the Two Micron All Sky Survey and Spitzer to create 1-24 {mu}m spectral energy distributions (SEDs). Usingmore » protostars from the c2d survey with well-determined bolometric luminosities, we derive a relationship between bolometric luminosity, mid-IR luminosity (integrated from 1-24 {mu}m), and SED slope. Estimations of the bolometric luminosities for protostar candidates are combined to create luminosity functions for each cloud. Contamination due to edge-on disks, reddened Class II sources, and galaxies is estimated and removed from the luminosity functions. We find that luminosity functions for high-mass SF clouds (Orion, Mon R2, and Cep OB3) peak near 1 L{sub Sun} and show a tail extending toward luminosities above 100 L{sub Sun }. The luminosity functions of the low-mass SF clouds (Serpens, Perseus, Ophiuchus, Taurus, Lupus, and Chamaeleon) do not exhibit a common peak, however the combined luminosity function of these regions peaks below 1 L{sub Sun }. Finally, we examine the luminosity functions as a function of the local surface density of young stellar objects. In the Orion molecular clouds, we find a significant difference between the luminosity functions of protostars in regions of high and low stellar density, the former of which is biased toward more luminous sources. This may be the result of primordial mass segregation, although this interpretation is not unique. We compare our

  13. Bianchi type-VIh string cloud cosmological models with bulk viscosity

    NASA Astrophysics Data System (ADS)

    Tripathy, Sunil K.; Behera, Dipanjali

    2010-11-01

    String cloud cosmological models are studied using spatially homogeneous and anisotropic Bianchi type VIh metric in the frame work of general relativity. The field equations are solved for massive string cloud in presence of bulk viscosity. A general linear equation of state of the cosmic string tension density with the proper energy density of the universe is considered. The physical and kinematical properties of the models have been discussed in detail and the limits of the anisotropic parameter responsible for different phases of the universe are explored.

  14. Analysis of the VIIRS cloud mask, comparison with the NAVOCEANO cloud mask, and how they complement each other

    NASA Astrophysics Data System (ADS)

    Cayula, Jean-François P.; May, Douglas A.; McKenzie, Bruce D.

    2014-05-01

    The Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask (VCM) Intermediate Product (IP) has been developed for use with Suomi National Polar-orbiting Partnership (NPP) VIIRS Environmental Data Record (EDR) products. In particular, the VIIRS Sea Surface Temperature (SST) EDR relies on VCM to identify cloud contaminated observations. Unfortunately, VCM does not appear to perform as well as cloud detection algorithms for SST. This may be due to similar but different goals of the two algorithms. VCM is concerned with detecting clouds while SST is interested in identifying clear observations. The result is that in undetermined cases VCM defaults to "clear," while the SST cloud detection defaults to "cloud." This problem is further compounded because classic SST cloud detection often flags as "cloud" all types of corrupted data, thus making a comparison with VCM difficult. The Naval Oceanographic Office (NAVOCEANO), which operationally produces a VIIRS SST product, relies on cloud detection from the NAVOCEANO Cloud Mask (NCM), adapted from cloud detection schemes designed for SST processing. To analyze VCM, the NAVOCEANO SST process was modified to attach the VCM flags to all SST retrievals. Global statistics are computed for both day and night data. The cases where NCM and/or VCM tag data as cloud-contaminated or clear can then be investigated. By analyzing the VCM individual test flags in conjunction with the status of NCM, areas where VCM can complement NCM are identified.

  15. Satellite Data Analysis of Impact of Anthropogenic Air Pollution on Ice Clouds

    NASA Astrophysics Data System (ADS)

    Gu, Y.; Liou, K. N.; Zhao, B.; Jiang, J. H.; Su, H.

    2017-12-01

    Despite numerous studies about the impact of aerosols on ice clouds, the role of anthropogenic aerosols in ice processes, especially over pollution regions, remains unclear and controversial, and has not been considered in a regional model. The objective of this study is to improve our understanding of the ice process associated with anthropogenic aerosols, and provide a comprehensive assessment of the contribution of anthropogenic aerosols to ice nucleation, ice cloud properties, and the consequent regional radiative forcing. As the first attempt, we evaluate the effects of different aerosol types (mineral dust, air pollution, polluted dust, and smoke) on ice cloud micro- and macro-physical properties using satellite data. We identify cases with collocated CloudSat, CALIPSO, and Aqua observations of vertically resolved aerosol and cloud properties, and process these observations into the same spatial resolution. The CALIPSO's aerosol classification algorithm determines aerosol layers as one of six defined aerosol types by taking into account the lidar depolarization ratio, integrated attenuated backscattering, surface type, and layer elevation. We categorize the cases identified above according to aerosol types, collect relevant aerosol and ice cloud variables, and determine the correlation between column/layer AOD and ice cloud properties for each aerosol type. Specifically, we investigate the correlation between aerosol loading (indicated by the column AOD and layer AOD) and ice cloud microphysical properties (ice water content, ice crystal number concentration, and ice crystal effective radius) and macro-physical properties (ice water path, ice cloud fraction, cloud top temperature, and cloud thickness). By comparing the responses of ice cloud properties to aerosol loadings for different aerosol types, we infer the role of different aerosol types in ice nucleation and the evolution of ice clouds. Our preliminary study shows that changes in the ice crystal

  16. Using Long-Term Satellite Observations to Identify Sensitive Regimes and Active Regions of Aerosol Indirect Effects for Liquid Clouds Over Global Oceans

    NASA Astrophysics Data System (ADS)

    Zhao, Xuepeng; Liu, Yangang; Yu, Fangquan; Heidinger, Andrew K.

    2018-01-01

    Long-term (1981-2011) satellite climate data records of clouds and aerosols are used to investigate the aerosol-cloud interaction of marine water cloud from a climatology perspective. Our focus is on identifying the regimes and regions where the aerosol indirect effects (AIEs) are evident in long-term averages over the global oceans through analyzing the correlation features between aerosol loading and the key cloud variables including cloud droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP), cloud top height (CTH), and cloud top temperature (CTT). An aerosol optical thickness (AOT) range of 0.13 < AOT < 0.3 is identified as the sensitive regime of the conventional first AIE where CDER is more susceptible to AOT than the other cloud variables. The first AIE that manifests as the change of long-term averaged CDER appears only in limited oceanic regions. The signature of aerosol invigoration of water clouds as revealed by the increase of cloud cover fraction (CCF) and CTH with increasing AOT at the middle/high latitudes of both hemispheres is identified for a pristine atmosphere (AOT < 0.08). Aerosol invigoration signature is also revealed by the concurrent increase of CDER, COD, and CWP with increasing AOT for a polluted marine atmosphere (AOT > 0.3) in the tropical convergence zones. The regions where the second AIE is likely to manifest in the CCF change are limited to several oceanic areas with high CCF of the warm water clouds near the western coasts of continents. The second AIE signature as represented by the reduction of the precipitation efficiency with increasing AOT is more likely to be observed in the AOT regime of 0.08 < AOT < 0.4. The corresponding AIE active regions manifested themselves as the decline of the precipitation efficiency are mainly limited to the oceanic areas downwind of continental aerosols. The sensitive regime of the conventional AIE identified in this observational study is likely associated with the

  17. The origin of Halley-type comets: probing the inner Oort cloud

    NASA Astrophysics Data System (ADS)

    Levison, H.; Dones, L.; Duncan, M.

    2000-10-01

    We have integrated the orbits of 27,700 test particles initially entering the planetary system from the Oort cloud in order to study the origin of Halley-type comets (HTCs). We included the gravitational influence of the Sun, giant planets, passing stars, and galactic tides. We find that an isotropically distributed Oort cloud does not reproduce the observed orbital element distribution of the HTCs. In order to match the observations, the initial inclination distribution of the progenitors of the HTCs must be similar to the observed HTC inclination distribution. We can match the observations with an Oort cloud that consists of an isotropic outer cloud and a disk-like massive inner cloud. These idealized two-component models have inner disks with median inclinations that range from 10 to 50o. This analysis represents the first link between observations and the structure of the inner Oort cloud. HFL and LD gratefully acknowledges grants provided by the NASA Origins of Solar Systems and Planetary Geology and Geophysics Programs. MJD is grateful for the continuing financial support of the Natural Science and Engineering Research Council of Canada and for financial support for work done inthe U.S.from NASA Planetary Geology and Geophysics Programs.

  18. Impact of a Pioneer/Rindler-type acceleration on the Oort Cloud

    NASA Astrophysics Data System (ADS)

    Iorio, Lorenzo

    2012-01-01

    According to a recent modified model of gravity at large distances, a radial constant and uniform extra-acceleration ? of Rindler type acts upon a test particle p in the static field of a central mass M if certain conditions are satisfied. Among other things, it was proposed as a potentially viable explanation of a part of the Pioneer anomaly. We study the impact that an anomalous Rindler-type term as large as ? m s-2 may have on the the orbital dynamics of a typical object of the Oort Cloud whose self-energy is quite smaller than its putative Rindler energy. By taking a typical comet moving along a highly eccentric and inclined orbit throughout the expected entire extension of the Oort Cloud (? pc), it turns out that the addition of an outward Rindler-like acceleration, that is, for ?, does not allow bound orbits. Instead, if ?, the resulting numerically integrated trajectory is limited in space, but it radically differs from the standard Keplerian ellipse. In particular, the heliocentric distance of the comet gets markedly reduced and experiences high-frequency oscillations, its speed is increased, and the overall pattern of the trajectory is quite isotropic. As a consequence, the standard picture of the Oort Cloud is radically altered since its modified orbits are much less sensitive to the disturbing actions of the Galactic tide and nearby passing stars whose effects, in the standard scenario, are responsible for the phenomenology on which our confidence in the existence of the cloud itself is based. The present analysis may be supplemented in future by further statistical Monte Carlo type investigations by randomly varying the initial conditions of the comets.

  19. Using Long‐Term Satellite Observations to Identify Sensitive Regimes and Active Regions of Aerosol Indirect Effects for Liquid Clouds Over Global Oceans

    PubMed Central

    Liu, Yangang; Yu, Fangquan; Heidinger, Andrew K.

    2018-01-01

    Abstract Long‐term (1981–2011) satellite climate data records of clouds and aerosols are used to investigate the aerosol‐cloud interaction of marine water cloud from a climatology perspective. Our focus is on identifying the regimes and regions where the aerosol indirect effects (AIEs) are evident in long‐term averages over the global oceans through analyzing the correlation features between aerosol loading and the key cloud variables including cloud droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP), cloud top height (CTH), and cloud top temperature (CTT). An aerosol optical thickness (AOT) range of 0.13 < AOT < 0.3 is identified as the sensitive regime of the conventional first AIE where CDER is more susceptible to AOT than the other cloud variables. The first AIE that manifests as the change of long‐term averaged CDER appears only in limited oceanic regions. The signature of aerosol invigoration of water clouds as revealed by the increase of cloud cover fraction (CCF) and CTH with increasing AOT at the middle/high latitudes of both hemispheres is identified for a pristine atmosphere (AOT < 0.08). Aerosol invigoration signature is also revealed by the concurrent increase of CDER, COD, and CWP with increasing AOT for a polluted marine atmosphere (AOT > 0.3) in the tropical convergence zones. The regions where the second AIE is likely to manifest in the CCF change are limited to several oceanic areas with high CCF of the warm water clouds near the western coasts of continents. The second AIE signature as represented by the reduction of the precipitation efficiency with increasing AOT is more likely to be observed in the AOT regime of 0.08 < AOT < 0.4. The corresponding AIE active regions manifested themselves as the decline of the precipitation efficiency are mainly limited to the oceanic areas downwind of continental aerosols. The sensitive regime of the conventional AIE identified in this observational study

  20. Using Long-Term Satellite Observations to Identify Sensitive Regimes and Active Regions of Aerosol Indirect Effects for Liquid Clouds Over Global Oceans.

    PubMed

    Zhao, Xuepeng; Liu, Yangang; Yu, Fangquan; Heidinger, Andrew K

    2018-01-16

    Long-term (1981-2011) satellite climate data records of clouds and aerosols are used to investigate the aerosol-cloud interaction of marine water cloud from a climatology perspective. Our focus is on identifying the regimes and regions where the aerosol indirect effects (AIEs) are evident in long-term averages over the global oceans through analyzing the correlation features between aerosol loading and the key cloud variables including cloud droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP), cloud top height (CTH), and cloud top temperature (CTT). An aerosol optical thickness (AOT) range of 0.13 < AOT < 0.3 is identified as the sensitive regime of the conventional first AIE where CDER is more susceptible to AOT than the other cloud variables. The first AIE that manifests as the change of long-term averaged CDER appears only in limited oceanic regions. The signature of aerosol invigoration of water clouds as revealed by the increase of cloud cover fraction (CCF) and CTH with increasing AOT at the middle/high latitudes of both hemispheres is identified for a pristine atmosphere (AOT < 0.08). Aerosol invigoration signature is also revealed by the concurrent increase of CDER, COD, and CWP with increasing AOT for a polluted marine atmosphere (AOT > 0.3) in the tropical convergence zones. The regions where the second AIE is likely to manifest in the CCF change are limited to several oceanic areas with high CCF of the warm water clouds near the western coasts of continents. The second AIE signature as represented by the reduction of the precipitation efficiency with increasing AOT is more likely to be observed in the AOT regime of 0.08 < AOT < 0.4. The corresponding AIE active regions manifested themselves as the decline of the precipitation efficiency are mainly limited to the oceanic areas downwind of continental aerosols. The sensitive regime of the conventional AIE identified in this observational study is likely associated

  1. Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global-Cloud Permitting Models Final Report

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Kollias, Pavlos

    This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation ratemore » retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.« less

  2. Using Long-term Satellite Observations to Identify Sensitive Regimes and Active Regions of Aerosol Indirect Effects for Liquid Clouds over Global Oceans

    DOE PAGES

    Zhao, Xuepeng; Liu, Yangang; Yu, Fangquan; ...

    2017-11-16

    Long-term (1981-2011) satellite climate data records (CDRs) of clouds and aerosols are used to investigate the aerosol-cloud interaction of marine water cloud from a climatology perspective. Our focus is on identifying the regimes and regions where the aerosol indirect effect (AIE) are evident in long-term averages over the global oceans through analyzing the correlation features between aerosol loading and the key cloud variables including cloud droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP), cloud top height (CTH), and cloud top temperature (CTT). An aerosol optical thickness (AOT) range of 0.13 < AOT < 0.3 is identifiedmore » as the sensitive regime of the conventional first AIE where CDER is more susceptible to AOT than the other cloud variables. The first AIE that manifests as the change of long-term averaged CDER appears only in limited oceanic regions. The signature of aerosol invigoration of water clouds as revealed by the increase of cloud cover fraction (CCF) and CTH with increasing AOT at the middle/high latitudes of both hemispheres is identified for a pristine atmosphere (AOT < 0.08). Aerosol invigoration signature is also revealed by the concurrent increase of CDER, COD, and CWP with increasing AOT for a polluted marine atmosphere (AOT > 0.3) in the tropical convergence zones. The regions where the second AIE is likely to manifest in the CCF change are limited to several oceanic areas with high CCF of the warm water clouds near the western coasts of continents. The second AIE signature as represented by the reduction of the precipitation efficiency with increasing AOT is more likely to be observed in the AOT regime of 0.08 < AOT < 0.4. The corresponding AIE active regions manifested themselves as the decline of the precipitation efficiency are mainly limited to the oceanic areas downwind of continental aerosols. Furthermore, the sensitive regime of the conventional AIE identified in this observational study is

  3. Using Long-term Satellite Observations to Identify Sensitive Regimes and Active Regions of Aerosol Indirect Effects for Liquid Clouds over Global Oceans

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zhao, Xuepeng; Liu, Yangang; Yu, Fangquan

    Long-term (1981-2011) satellite climate data records (CDRs) of clouds and aerosols are used to investigate the aerosol-cloud interaction of marine water cloud from a climatology perspective. Our focus is on identifying the regimes and regions where the aerosol indirect effect (AIE) are evident in long-term averages over the global oceans through analyzing the correlation features between aerosol loading and the key cloud variables including cloud droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP), cloud top height (CTH), and cloud top temperature (CTT). An aerosol optical thickness (AOT) range of 0.13 < AOT < 0.3 is identifiedmore » as the sensitive regime of the conventional first AIE where CDER is more susceptible to AOT than the other cloud variables. The first AIE that manifests as the change of long-term averaged CDER appears only in limited oceanic regions. The signature of aerosol invigoration of water clouds as revealed by the increase of cloud cover fraction (CCF) and CTH with increasing AOT at the middle/high latitudes of both hemispheres is identified for a pristine atmosphere (AOT < 0.08). Aerosol invigoration signature is also revealed by the concurrent increase of CDER, COD, and CWP with increasing AOT for a polluted marine atmosphere (AOT > 0.3) in the tropical convergence zones. The regions where the second AIE is likely to manifest in the CCF change are limited to several oceanic areas with high CCF of the warm water clouds near the western coasts of continents. The second AIE signature as represented by the reduction of the precipitation efficiency with increasing AOT is more likely to be observed in the AOT regime of 0.08 < AOT < 0.4. The corresponding AIE active regions manifested themselves as the decline of the precipitation efficiency are mainly limited to the oceanic areas downwind of continental aerosols. Furthermore, the sensitive regime of the conventional AIE identified in this observational study is

  4. Genes2WordCloud: a quick way to identify biological themes from gene lists and free text.

    PubMed

    Baroukh, Caroline; Jenkins, Sherry L; Dannenfelser, Ruth; Ma'ayan, Avi

    2011-10-13

    Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications.

  5. Feasibility and demonstration of a cloud-based RIID analysis system

    NASA Astrophysics Data System (ADS)

    Wright, Michael C.; Hertz, Kristin L.; Johnson, William C.; Sword, Eric D.; Younkin, James R.; Sadler, Lorraine E.

    2015-06-01

    A significant limitation in the operational utility of handheld and backpack radioisotope identifiers (RIIDs) is the inability of their onboard algorithms to accurately and reliably identify the isotopic sources of the measured gamma-ray energy spectrum. A possible solution is to move the spectral analysis computations to an external device, the cloud, where significantly greater capabilities are available. The implementation and demonstration of a prototype cloud-based RIID analysis system have shown this type of system to be feasible with currently available communication and computational technology. A system study has shown that the potential user community could derive significant benefits from an appropriately implemented cloud-based analysis system and has identified the design and operational characteristics required by the users and stakeholders for such a system. A general description of the hardware and software necessary to implement reliable cloud-based analysis, the value of the cloud expressed by the user community, and the aspects of the cloud implemented in the demonstrations are discussed.

  6. Cloud Computing Fundamentals

    NASA Astrophysics Data System (ADS)

    Furht, Borko

    In the introductory chapter we define the concept of cloud computing and cloud services, and we introduce layers and types of cloud computing. We discuss the differences between cloud computing and cloud services. New technologies that enabled cloud computing are presented next. We also discuss cloud computing features, standards, and security issues. We introduce the key cloud computing platforms, their vendors, and their offerings. We discuss cloud computing challenges and the future of cloud computing.

  7. Genes2WordCloud: a quick way to identify biological themes from gene lists and free text

    PubMed Central

    2011-01-01

    Background Word-clouds recently emerged on the web as a solution for quickly summarizing text by maximizing the display of most relevant terms about a specific topic in the minimum amount of space. As biologists are faced with the daunting amount of new research data commonly presented in textual formats, word-clouds can be used to summarize and represent biological and/or biomedical content for various applications. Results Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Methods Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W. Conclusions Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications. PMID:21995939

  8. SHOCKFIND - an algorithm to identify magnetohydrodynamic shock waves in turbulent clouds

    NASA Astrophysics Data System (ADS)

    Lehmann, Andrew; Federrath, Christoph; Wardle, Mark

    2016-11-01

    The formation of stars occurs in the dense molecular cloud phase of the interstellar medium. Observations and numerical simulations of molecular clouds have shown that supersonic magnetized turbulence plays a key role for the formation of stars. Simulations have also shown that a large fraction of the turbulent energy dissipates in shock waves. The three families of MHD shocks - fast, intermediate and slow - distinctly compress and heat up the molecular gas, and so provide an important probe of the physical conditions within a turbulent cloud. Here, we introduce the publicly available algorithm, SHOCKFIND, to extract and characterize the mixture of shock families in MHD turbulence. The algorithm is applied to a three-dimensional simulation of a magnetized turbulent molecular cloud, and we find that both fast and slow MHD shocks are present in the simulation. We give the first prediction of the mixture of turbulence-driven MHD shock families in this molecular cloud, and present their distinct distributions of sonic and Alfvénic Mach numbers. Using subgrid one-dimensional models of MHD shocks we estimate that ˜0.03 per cent of the volume of a typical molecular cloud in the Milky Way will be shock heated above 50 K, at any time during the lifetime of the cloud. We discuss the impact of this shock heating on the dynamical evolution of molecular clouds.

  9. Two evolved supernova remnants with newly identified Fe-rich cores in the Large Magellanic Cloud

    NASA Astrophysics Data System (ADS)

    Kavanagh, P. J.; Sasaki, M.; Bozzetto, L. M.; Points, S. D.; Crawford, E. J.; Dickel, J.; Filipović, M. D.; Haberl, F.; Maggi, P.; Whelan, E. T.

    2016-02-01

    Aims: We present a multi-wavelength analysis of the evolved supernova remnants MCSNR J0506-7025 and MCSNR J0527-7104 in the Large Magellanic Cloud. Methods: We used observational data from XMM-Newton, the Australian Telescope Compact Array, and the Magellanic Cloud Emission Line Survey to study their broad-band emission and used Spitzer and H I data to gain a picture of the environment into which the remnants are expanding. We performed a multi-wavelength morphological study and detailed radio and X-ray spectral analyses to determine their physical characteristics. Results: Both remnants were found to have bright X-ray cores, dominated by Fe L-shell emission, which is consistent with reverse shock-heated ejecta with determined Fe masses in agreement with Type Ia explosion yields. A soft X-ray shell, which is consistent with swept-up interstellar medium, was observed in MCSNR J0506-7025, suggestive of a remnant in the Sedov phase. Using the spectral fit results and the Sedov self-similar solution, we estimated the age of MCSNR J0506-7025 to be ~16-28 kyr, with an initial explosion energy of (0.07-0.84) × 1051 erg. A soft shell was absent in MCSNR J0527-7104, with only ejecta emission visible in an extremely elongated morphology that extends beyond the optical shell. We suggest that the blast wave has broken out into a low density cavity, allowing the shock heated ejecta to escape. We find that the radio spectral index of MCSNR J0506-7025 is consistent with the standard -0.5 for supernova remnants. Radio polarisation at 6 cm indicates a higher degree of polarisation along the western front and at the eastern knot with a mean fractional polarisation across the remnant of P ≅ (20 ± 6)%. Conclusions: The detection of Fe-rich ejecta in the remnants suggests that both resulted from Type Ia explosions. The newly identified Fe-rich cores in MCSNR J0506-7025 and MCSNR J0527-7104 make them members of the expanding class of evolved Fe-rich remnants in the Magellanic Clouds

  10. Diagnosing AIRS Sampling with CloudSat Cloud Classes

    NASA Technical Reports Server (NTRS)

    Fetzer, Eric; Yue, Qing; Guillaume, Alexandre; Kahn, Brian

    2011-01-01

    AIRS yield and sampling vary with cloud state. Careful utilization of collocated multiple satellite sensors is necessary. Profile differences between AIRS and ECMWF model analyses indicate that AIRS has high sampling and excellent accuracy for certain meteorological conditions. Cloud-dependent sampling biases may have large impact on AIRS L2 and L3 data in climate research. MBL clouds / lower tropospheric stability relationship is one example. AIRS and CloudSat reveal a reasonable climatology in the MBL cloud regime despite limited sampling in stratocumulus. Thermodynamic parameters such as EIS derived from AIRS data map these cloud conditions successfully. We are working on characterizing AIRS scenes with mixed cloud types.

  11. Mars Aerosol Studies with the MGS TES Emission Phase Function Observations: Opacities, Particle Sizes, and Ice Cloud Types

    NASA Astrophysics Data System (ADS)

    Wolff, M. J.; Clancy, R. T.; Pitman, K. M.; Christensen, P. R.; Whitney, B. A.

    2001-11-01

    A full Mars year (1999-2001) of emission phase function (EPF) observations from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) provide the most complete study of Mars dust and ice aerosol properties to date. TES visible (solar band average) and infrared spectral EPF sequences are analyzed self-consistently with detailed multiple scattering radiative transfer codes. As a consequence of the combined angular and wavelength coverage, we are able to define two distinct ice cloud types at 45\\arcdeg S-45\\arcdeg N latitudes on Mars. Type I ice clouds exhibit small particle sizes (1-2 \\micron\\ radii), as well as a broad, deep minimum in side-scattering that are potentially indicative of aligned ice grains. Type I ice aerosols are most prevalent in the southern hemisphere during Mars aphelion, but also appear more widely distributed in season and latitude as topographic and high altitude (>20 km) ice hazes. Type II ice clouds exhibit larger particle sizes (3-5 \\micron) and a much narrower side-scattering minimum, indicative of poorer grain alignment or a change in particle shape relative to the type I ice clouds. Type II ice clouds appear most prominently in the northern subtropical aphelion cloud belt, where relatively low altitudes water vapor saturation (10 km) coincide with strong advective transport. Retrieved dust particle radii of 1.5-1.8 \\micron\\ are consistent with Pathfinder and recent Viking/Mariner 9 reanalyses. Our analyses also find EPF-derived dust single scattering albedos (ssa) in agreement with those from Pathfinder. Spatial and seasonal changes in the dust ssa (0.92-0.95, solar band average) and phase functions suggest possible dust property variations, but may also be a consequence of variable high altitude ice hazes. The annual variations of both dust and ice clouds at 45S-45N latitudes are predominately orbital rather than seasonal in character and have shown remarkable repeatability during the portions of two Mars years observed

  12. Effects of cumulus entrainment and multiple cloud types on a January global climate model simulation

    NASA Technical Reports Server (NTRS)

    Yao, Mao-Sung; Del Genio, Anthony D.

    1989-01-01

    An improved version of the GISS Model II cumulus parameterization designed for long-term climate integrations is used to study the effects of entrainment and multiple cloud types on the January climate simulation. Instead of prescribing convective mass as a fixed fraction of the cloud base grid-box mass, it is calculated based on the closure assumption that the cumulus convection restores the atmosphere to a neutral moist convective state at cloud base. This change alone significantly improves the distribution of precipitation, convective mass exchanges, and frequencies in the January climate. The vertical structure of the tropical atmosphere exhibits quasi-equilibrium behavior when this closure is used, even though there is no explicit constraint applied above cloud base.

  13. Isolating signatures of major cloud-cloud collisions using position-velocity diagrams

    NASA Astrophysics Data System (ADS)

    Haworth, T. J.; Tasker, E. J.; Fukui, Y.; Torii, K.; Dale, J. E.; Shima, K.; Takahira, K.; Habe, A.; Hasegawa, K.

    2015-06-01

    Collisions between giant molecular clouds are a potential mechanism for triggering the formation of massive stars, or even super star clusters. The trouble is identifying this process observationally and distinguishing it from other mechanisms. We produce synthetic position-velocity diagrams from models of cloud-cloud collisions, non-interacting clouds along the line of sight, clouds with internal radiative feedback and a more complex cloud evolving in a galactic disc, to try and identify unique signatures of collision. We find that a broad bridge feature connecting two intensity peaks, spatially correlated but separated in velocity, is a signature of a high-velocity cloud-cloud collision. We show that the broad bridge feature is resilient to the effects of radiative feedback, at least to around 2.5 Myr after the formation of the first massive (ionizing) star. However for a head-on 10 km s-1 collision, we find that this will only be observable from 20 to 30 per cent of viewing angles. Such broad-bridge features have been identified towards M20, a very young region of massive star formation that was concluded to be a site of cloud-cloud collision by Torii et al., and also towards star formation in the outer Milky Way by Izumi et al.

  14. Towards a true aerosol-and-cloud retrieval scheme

    NASA Astrophysics Data System (ADS)

    Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don

    2014-05-01

    The Optimal Retrieval of Aerosol and Cloud (ORAC) - formally the Oxford-RAL Aerosol and Cloud retrieval - offers a framework that can provide consistent and well characterised properties of both aerosols and clouds from a range of imaging satellite instruments. Several practical issues stand in the way of achieving the potential of this combined scheme however; in particular the sometimes conflicting priorities and requirements of aerosol and cloud retrieval problems, and the question of the unambiguous identification of aerosol and cloud pixels. This presentation will present recent developments made to the ORAC scheme for both aerosol and cloud, and detail how these are being integrated into a single retrieval framework. The implementation of a probabilistic method for pixel identification will also be presented, for both cloud detection and aerosol/cloud type selection. The method is based on Bayesian methods applied the optimal estimation retrieval output of ORAC and is particularly aimed at providing additional information in the so-called "twilight zone", where pixels can't be unambiguously identified as either aerosol or cloud and traditional cloud or aerosol products do not provide results.

  15. Characteristics of mid-level clouds over West Africa

    NASA Astrophysics Data System (ADS)

    Bourgeois, Elsa; Bouniol, Dominique; Couvreux, Fleur; Guichard, Françoise; Marsham, John; Garcia-Carreras, Luis; Birch, Cathryn; Parker, Doug

    2017-04-01

    Clouds have a major impact on the distribution of water and energy fluxes within the atmosphere. They also represent one of the main sources of uncertainties in global climate models as a result of the difficulty to parametrize cloud processes. However, in West Africa, the cloud type, occurrence and radiative effects have not been extensively documented. This region is characterized by a strong seasonality with precipitation occurring in the Sahel from June to September (monsoon season). This period also coincides with the annual maximum of the cloud cover. Taking advantage of the one-year ARM Mobile Facility (AMF) deployment in 2006 in Niamey (Niger), Bouniol et al (2012) documented the distinct cloud types and showed the frequent occurrence of mid-level clouds (around 6 km height) and their substantial impact on the surface short-wave and long-wave radiative fluxes. Furthermore, in a process-oriented evaluation of climate models, Roehrig et al (2013) showed that these mid-level clouds are poorly represented in numerical models. The aim of this work is to document the macro- and microphysical properties of mid-level clouds and the environment in which such clouds occur across West Africa. To document those clouds, we extensively make use of observations from lidar and cloud radar either deployed at ground-based sites (Niamey and Bordj Badji Mokhtar (Sahara)) or on-board the A-Train constellation (CloudSat/CALIPSO). These datasets reveal the temporal and spatial occurrence of those clouds. They are found throughout the year with a predominance around the monsoon season and are preferentially observed in the Southern and Western part of West Africa which could be linked to the dynamics of the Saharan heat low. Those clouds are usually quite thin (most of them are less than 1000m deep). A clustering method applied to this data allows us to identify three different types of clouds : one with low bases, one with high bases and another with large thicknesses. The first

  16. Proposal for a Security Management in Cloud Computing for Health Care

    PubMed Central

    Dzombeta, Srdan; Brandis, Knud

    2014-01-01

    Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources. PMID:24701137

  17. Proposal for a security management in cloud computing for health care.

    PubMed

    Haufe, Knut; Dzombeta, Srdan; Brandis, Knud

    2014-01-01

    Cloud computing is actually one of the most popular themes of information systems research. Considering the nature of the processed information especially health care organizations need to assess and treat specific risks according to cloud computing in their information security management system. Therefore, in this paper we propose a framework that includes the most important security processes regarding cloud computing in the health care sector. Starting with a framework of general information security management processes derived from standards of the ISO 27000 family the most important information security processes for health care organizations using cloud computing will be identified considering the main risks regarding cloud computing and the type of information processed. The identified processes will help a health care organization using cloud computing to focus on the most important ISMS processes and establish and operate them at an appropriate level of maturity considering limited resources.

  18. VizieR Online Data Catalog: M33 molecular clouds and young stellar clusters (Corbelli+, 2017)

    NASA Astrophysics Data System (ADS)

    Corbelli, E.; Braine, J.; Bandiera, R.; Brouillet, N.; Combes, F.; Druard, C.; Gratier, P.; Mata, J.; Schuster, K.; Xilouris, M.; Palla, F.

    2017-04-01

    Table 5 : Physical parameters for the 566 molecular clouds identified through the IRAM 30m CO J=2-1 survey of the star forming disk of M33. For each cloud the cloud type and the following properties are listed: celestial coordinates, galactocentric radius, cloud deconvolved effective radius and its uncertainty, CO(2-1) line velocity dispersion from CPROPS and its uncertainty, line velocity dispersion from a Gaussian fit, CO luminous mass and its uncertainty, and virial mass from a Gaussian fit. In the last column the identification number of the young stellar cluster candidates associated with the molecular cloud are listed. Notes: We identify up to four young stellar cluster candidates (YSCCs) associated with each molecular cloud and we list them according to the identification number of Sharma et al. (2011, Cat. J/A+A/545/A96) given also in Table 6. Table 6 : Physical parameters for the 630 young stellar cluster candidates identified via their mid-infrared emission in the star forming disk of M33. For each YSCC we list the type of source, the identified number of the molecular clouds associated with it (if any) and the corresponding cloud classes. In addition, for each YSCC we give the celestial coordinates, the bolometric, total infrared, FUV and Halpha luminosities, the estimated mass and age, the visual extinction, the galactocentric radius, the source size, and its flux at 24μm. (2 data files).

  19. The effect of clouds on the earth's radiation budget

    NASA Technical Reports Server (NTRS)

    Ziskin, Daniel; Strobel, Darrell F.

    1991-01-01

    The radiative fluxes from the Earth Radiation Budget Experiment (ERBE) and the cloud properties from the International Satellite Cloud Climatology Project (ISCCP) over Indonesia for the months of June and July of 1985 and 1986 were analyzed to determine the cloud sensitivity coefficients. The method involved a linear least squares regression between co-incident flux and cloud coverage measurements. The calculated slope is identified as the cloud sensitivity. It was found that the correlations between the total cloud fraction and radiation parameters were modest. However, correlations between cloud fraction and IR flux were improved by separating clouds by height. Likewise, correlations between the visible flux and cloud fractions were improved by distinguishing clouds based on optical depth. Calculating correlations between the net fluxes and either height or optical depth segregated cloud fractions were somewhat improved. When clouds were classified in terms of their height and optical depth, correlations among all the radiation components were improved. Mean cloud sensitivities based on the regression of radiative fluxes against height and optical depth separated cloud types are presented. Results are compared to a one-dimensional radiation model with a simple cloud parameterization scheme.

  20. Aerosols, clouds, and precipitation in the North Atlantic trades observed during the Barbados aerosol cloud experiment - Part 1: Distributions and variability

    NASA Astrophysics Data System (ADS)

    Jung, Eunsil; Albrecht, Bruce A.; Feingold, Graham; Jonsson, Haflidi H.; Chuang, Patrick; Donaher, Shaunna L.

    2016-07-01

    deep. Clouds tend to precipitate when the cloud is thicker than 500-600 m. Distributions of cloud field characteristics (depth, radar reflectivity, Doppler velocity, precipitation) were well identified in the reflectivity-velocity diagram from the cloud radar observations. Two types of precipitation features were observed for shallow marine cumulus clouds that may impact boundary layer differently: first, a classic cloud-base precipitation where precipitation shafts were observed to emanate from the cloud base; second, cloud-top precipitation where precipitation shafts emanated mainly near the cloud tops, sometimes accompanied by precipitation near the cloud base. The second type of precipitation was more frequently observed during the experiment. Only 42-44 % of the clouds sampled were non-precipitating throughout the entire cloud layer and the rest of the clouds showed precipitation somewhere in the cloud, predominantly closer to the cloud top.

  1. Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud

    PubMed Central

    Florence, A. Paulin; Shanthi, V.; Simon, C. B. Sunil

    2016-01-01

    Cloud computing is a new technology which supports resource sharing on a “Pay as you go” basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption. PMID:27239551

  2. Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud.

    PubMed

    Florence, A Paulin; Shanthi, V; Simon, C B Sunil

    2016-01-01

    Cloud computing is a new technology which supports resource sharing on a "Pay as you go" basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption.

  3. Aerosol microphysical and radiative effects on continental cloud ensembles

    NASA Astrophysics Data System (ADS)

    Wang, Yuan; Vogel, Jonathan M.; Lin, Yun; Pan, Bowen; Hu, Jiaxi; Liu, Yangang; Dong, Xiquan; Jiang, Jonathan H.; Yung, Yuk L.; Zhang, Renyi

    2018-02-01

    Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.

  4. The Community Cloud Atlas - Building an Informed Cloud Watching Community

    NASA Astrophysics Data System (ADS)

    Guy, N.; Rowe, A.

    2014-12-01

    The sky is dynamic, from long lasting cloud systems to ethereal, fleeting formations. After years of observing the sky and growing our personal collections of cloud photos, we decided to take to social media to share pictures, as well as build and educate a community of cloud enthusiasts. We began a Facebook page, the Community Cloud Atlas, described as "...the place to show off your pictures of the sky, identify clouds, and to discuss how specific cloud types form and what they can tell you about current and future weather." Our main goal has been to encourage others to share their pictures, while we describe the scenes from a meteorological perspective and reach out to the general public to facilitate a deeper understanding of the sky. Nearly 16 months later, we have over 1400 "likes," spanning 45 countries with ages ranging from 13 to over 65. We have a consistent stream of submissions; so many that we decided to start a corresponding blog to better organize the photos, provide more detailed explanations, and reach a bigger audience. Feedback from users has been positive in support of not only sharing cloud pictures, but also to "learn the science as well as admiring" the clouds. As one community member stated, "This is not 'just' a place to share some lovely pictures." We have attempted to blend our social media presence with providing an educational resource, and we are encouraged by the response we have received. Our Atlas has been informally implemented into classrooms, ranging from a 6th grade science class to Meteorology courses at universities. NOVA's recent Cloud Lab also made use of our Atlas as a supply of categorized pictures. Our ongoing goal is to not only continue to increase understanding and appreciation of the sky among the public, but to provide an increasingly useful tool for educators. We continue to explore different social media options to interact with the public and provide easier content submission, as well as software options for

  5. Investigating Type I Polar Stratospheric Cloud Formation Mechanisms with POAM Satellite Observations

    NASA Technical Reports Server (NTRS)

    Strawa, Anthony W.; Drdla, K.; Fromm, M.; Hoppel, K.; Browell, E.; Hamill, P.; Dempsey, D.; Gore, Warren J. (Technical Monitor)

    2001-01-01

    Type Ia PSCs are believed to be composed of nitric acid hydrate particles. Recent results from the SOLVE/THESEO 2000 campaign showed evidence that this type of PSC was composed of a small number of very large particles capable of sedimentary denitrification of regions of the stratosphere. It is unknown whether homogeneous or heterogeneous nucleation is responsible for the formation of these PSCs. Arctic winters are tending to be colder in response to global tropospheric warming. The degree to which this influences ozone depletion will depend on the freezing mechanism of nitric acid hydrate particles. If nucleation is homogeneous it implies that the freezing process is an inherent property of the particle, while heterogeneous freezing means that the extent of PSCs will depend in part on the number of nuclei available. The Polar Ozone and Aerosol Measurement (POAM)II and III satellites have been making observations of stratospheric aerosols and Polar Stratospheric Clouds (PSCs) since 1994. Recently, we have developed a technique that can discriminate between Type Ia and Ib PSCs using these observations. A statistical approach is employed to demonstrate the robustness of this approach and results are compared with lidar measurements. The technique is used to analyze observations from POAM II and II during Northern Hemisphere winters where significant PSC formation occurred with the objective of exploring Type I PSC formation mechanisms. The different PSCs identified using this method exhibit different growth curve as expressed as extinction versus temperature.

  6. Effects of environment forcing on marine boundary layer cloud-drizzle processes: MBL Cloud-Drizzle Processes

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wu, Peng; Dong, Xiquan; Xi, Baike

    Determining the factors affecting drizzle formation in marine boundary layer (MBL) clouds remains a challenge for both observation and modeling communities. To investigate the roles of vertical wind shear and buoyancy (static instability) in drizzle formation, ground-based observations from the Atmospheric Radiation Measurement (ARM) Program at the Azores are analyzed for two types of conditions. The type I clouds should last for at least five hours and more than 90% time must be non-drizzling, and then followed by at least two hours of drizzling periods while the type II clouds are characterized by mesoscale convection cellular (MCC) structures with drizzlemore » occur every two to four hours. By analyzing the boundary layer wind profiles (direction and speed), it was found that either directional or speed shear is required to promote drizzle production in the type I clouds. Observations and a recent model study both suggest that vertical wind shear helps the production of turbulent kinetic energy (TKE), stimulates turbulence within cloud layer, and enhances drizzle formation near the cloud top. The type II clouds do not require strong wind shear to produce drizzle. The small values of lower-tropospheric stability (LTS) and negative Richardson number ( Ri) in the type II cases suggest that boundary layer instability plays an important role in TKE production and cloud-drizzle processes. As a result, by analyzing the relationships between LTS and wind shear for all cases and all time periods, a stronger connection was found between LTS and wind directional shear than that between LTS and wind speed shear.« less

  7. Effects of environment forcing on marine boundary layer cloud-drizzle processes: MBL Cloud-Drizzle Processes

    DOE PAGES

    Wu, Peng; Dong, Xiquan; Xi, Baike; ...

    2017-04-20

    Determining the factors affecting drizzle formation in marine boundary layer (MBL) clouds remains a challenge for both observation and modeling communities. To investigate the roles of vertical wind shear and buoyancy (static instability) in drizzle formation, ground-based observations from the Atmospheric Radiation Measurement (ARM) Program at the Azores are analyzed for two types of conditions. The type I clouds should last for at least five hours and more than 90% time must be non-drizzling, and then followed by at least two hours of drizzling periods while the type II clouds are characterized by mesoscale convection cellular (MCC) structures with drizzlemore » occur every two to four hours. By analyzing the boundary layer wind profiles (direction and speed), it was found that either directional or speed shear is required to promote drizzle production in the type I clouds. Observations and a recent model study both suggest that vertical wind shear helps the production of turbulent kinetic energy (TKE), stimulates turbulence within cloud layer, and enhances drizzle formation near the cloud top. The type II clouds do not require strong wind shear to produce drizzle. The small values of lower-tropospheric stability (LTS) and negative Richardson number ( Ri) in the type II cases suggest that boundary layer instability plays an important role in TKE production and cloud-drizzle processes. As a result, by analyzing the relationships between LTS and wind shear for all cases and all time periods, a stronger connection was found between LTS and wind directional shear than that between LTS and wind speed shear.« less

  8. Aerosol Microphysical and Radiative Effects on Continental Cloud Ensembles

    DOE PAGES

    Wang, Yuan; Vogel, Jonathan M.; Lin, Yun; ...

    2018-01-10

    Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. Here, an aerosol-aware Weather Research and Forecasting (WRF) model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the Southern Great Plains site of the US Atmospheric Radiation Measurement Program. Three cloud ensembles with different meteorological conditions are simulated, including a low-pressure deep convective cloud system, a series ofmore » lessprecipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by the available observations of cloud fraction, liquid water path, precipitation, and surface temperature. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not interfere the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with more prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. Furthermore, the simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the direction of precipitation changes by the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations than the cloud microphysics, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by

  9. Aerosol Microphysical and Radiative Effects on Continental Cloud Ensembles

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wang, Yuan; Vogel, Jonathan M.; Lin, Yun

    Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. Here, an aerosol-aware Weather Research and Forecasting (WRF) model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the Southern Great Plains site of the US Atmospheric Radiation Measurement Program. Three cloud ensembles with different meteorological conditions are simulated, including a low-pressure deep convective cloud system, a series ofmore » lessprecipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by the available observations of cloud fraction, liquid water path, precipitation, and surface temperature. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not interfere the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with more prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. Furthermore, the simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the direction of precipitation changes by the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity (typically less than 2%) to aerosol perturbations than the cloud microphysics, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by

  10. Identifying Key Features, Cutting Edge Cloud Resources, and Artificial Intelligence Tools to Achieve User-Friendly Water Science in the Cloud

    NASA Astrophysics Data System (ADS)

    Pierce, S. A.

    2017-12-01

    Decision making for groundwater systems is becoming increasingly important, as shifting water demands increasingly impact aquifers. As buffer systems, aquifers provide room for resilient responses and augment the actual timeframe for hydrological response. Yet the pace impacts, climate shifts, and degradation of water resources is accelerating. To meet these new drivers, groundwater science is transitioning toward the emerging field of Integrated Water Resources Management, or IWRM. IWRM incorporates a broad array of dimensions, methods, and tools to address problems that tend to be complex. Computational tools and accessible cyberinfrastructure (CI) are needed to cross the chasm between science and society. Fortunately cloud computing environments, such as the new Jetstream system, are evolving rapidly. While still targeting scientific user groups systems such as, Jetstream, offer configurable cyberinfrastructure to enable interactive computing and data analysis resources on demand. The web-based interfaces allow researchers to rapidly customize virtual machines, modify computing architecture and increase the usability and access for broader audiences to advanced compute environments. The result enables dexterous configurations and opening up opportunities for IWRM modelers to expand the reach of analyses, number of case studies, and quality of engagement with stakeholders and decision makers. The acute need to identify improved IWRM solutions paired with advanced computational resources refocuses the attention of IWRM researchers on applications, workflows, and intelligent systems that are capable of accelerating progress. IWRM must address key drivers of community concern, implement transdisciplinary methodologies, adapt and apply decision support tools in order to effectively support decisions about groundwater resource management. This presentation will provide an overview of advanced computing services in the cloud using integrated groundwater management case

  11. An AVHRR Cloud Classification Database Typed by Experts

    DTIC Science & Technology

    1993-10-01

    analysis. Naval Research Laboratory, Monterey, CA. 110 pp. Gallaudet , Timothy C. and James J. Simpson, 1991: Automated cloud screening of AVHRR imagery...1987) and Saunders and Kriebel (1988a,b) have used threshold techniques to classify clouds. Gallaudet and Simpson (1991) have used split-and-merge

  12. Biogeography, Cloud Base Heights and Cloud Immersion in Tropical Montane Cloud Forests

    NASA Astrophysics Data System (ADS)

    Welch, R. M.; Asefi, S.; Zeng, J.; Nair, U. S.; Lawton, R. O.; Ray, D. K.; Han, Q.; Manoharan, V. S.

    2007-05-01

    Tropical Montane Cloud Forests (TMCFs) are ecosystems characterized by frequent and prolonged immersion within orographic clouds. TMCFs often lie at the core of the biological hotspots, areas of high biodiversity, whose conservation is necessary to ensure the preservation of a significant amount of the plant and animal species in the world. TMCFs support islands of endemism dependent on cloud water interception that are extremely susceptible to environmental and climatic changes at regional or global scales. Due to the ecological and hydrological importance of TMCFs it is important to understand the biogeographical distribution of these ecosystems. The best current list of TMCFs is a global atlas compiled by the United Nations Environmental Program (UNEP). However, this list is incomplete, and it does not provide information on cloud immersion, which is the defining characteristic of TMCFs and sorely needed for ecological and hydrological studies. The present study utilizes MODIS satellite data both to determine orographic cloud base heights and then to quantify cloud immersion statistics over TMCFs. Results are validated from surface measurements over Northern Costa Rica for the month of March 2003. Cloud base heights are retrieved with approximately 80m accuracy, as determined at Monteverde, Costa Rica. Cloud immersion derived from MODIS data is also compared to an independent cloud immersion dataset created using a combination of GOES satellite data and RAMS model simulations. Comparison against known locations of cloud forests in Northern Costa Rica shows that the MODIS-derived cloud immersion maps successfully identify these cloud forest locations, including those not included in the UNEP data set. Results also will be shown for cloud immersion in Hawaii. The procedure appears to be ready for global mapping.

  13. Clouds in GEOS-5

    NASA Technical Reports Server (NTRS)

    Bacmeister, Julio; Rienecker, Michele; Suarez, Max; Norris, Peter

    2007-01-01

    The GEOS-5 atmospheric model is being developed as a weather-and-climate capable model. It must perform well in assimilation mode as well as in weather and climate simulations and forecasts and in coupled chemistry-climate simulations. In developing GEOS-5, attention has focused on the representation of moist processes. The moist physics package uses a single phase prognostic condensate and a prognostic cloud fraction. Two separate cloud types are distinguished by their source: "anvil" cloud originates in detraining convection, and large-scale cloud originates in a PDF-based condensation calculation. Ice and liquid phases for each cloud type are considered. Once created, condensate and fraction from the anvil and statistical cloud types experience the same loss processes: evaporation of condensate and fraction, auto-conversion of liquid or mixed phase condensate, sedimentation of frozen condensate, and accretion of condensate by falling precipitation. The convective parameterization scheme is the Relaxed Arakawa-Schubert, or RAS, scheme. Satellite data are used to evaluate the performance of the moist physics packages and help in their tuning. In addition, analysis of and comparisons to cloud-resolving models such as the Goddard Cumulus Ensemble model are used to help improve the PDFs used in the moist physics. The presentation will show some of our evaluations including precipitation diagnostics.

  14. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

    2005-01-01

    Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.

  15. Investigation of mesoscale cloud features viewed by LANDSAT

    NASA Technical Reports Server (NTRS)

    Sherr, P. E. (Principal Investigator); Feteris, P. J.; Lisa, A. S.; Bowley, C. J.; Fowler, M. G.; Barnes, J. C.

    1976-01-01

    The author has identified the following significant results. Some 50 LANDSAT images displaying mesoscale cloud features were analyzed. This analysis was based on the Rayleigh-Kuettner model describing the formation of that type of mesoscale cloud feature. This model lends itself to computation of the average wind speed in northerly flow from the dimensions of the cloud band configurations measured from a LANDSAT image. In nearly every case, necessary conditions of a curved wind profile and orientation of the cloud streets within 20 degrees of the direction of the mean wind in the convective layer were met. Verification of the results by direct observation was hampered, however, by the incompatibility of the resolution of conventional rawinsonde observations with the scale of the banded cloud patterns measured from LANDSAT data. Comparison seems to be somewhat better in northerly flows than in southerly flows, with the largest discrepancies in wind speed being within 8m/sec, or a factor of two.

  16. Cloud point phenomena for POE-type nonionic surfactants in a model room temperature ionic liquid.

    PubMed

    Inoue, Tohru; Misono, Takeshi

    2008-10-15

    The cloud point phenomenon has been investigated for the solutions of polyoxyethylene (POE)-type nonionic surfactants (C(12)E(5), C(12)E(6), C(12)E(7), C(10)E(6), and C(14)E(6)) in 1-butyl-3-methylimidazolium tetrafluoroborate (bmimBF(4)), a typical room temperature ionic liquid (RTIL). The cloud point, T(c), increases with the elongation of the POE chain, while decreases with the increase in the hydrocarbon chain length. This demonstrates that the solvophilicity/solvophobicity of the surfactants in RTIL comes from POE chain/hydrocarbon chain. When compared with an aqueous system, the chain length dependence of T(c) is larger for the RTIL system regarding both POE and hydrocarbon chains; in particular, hydrocarbon chain length affects T(c) much more strongly in the RTIL system than in equivalent aqueous systems. In a similar fashion to the much-studied aqueous systems, the micellar growth is also observed in this RTIL solvent as the temperature approaches T(c). The cloud point curves have been analyzed using a Flory-Huggins-type model based on phase separation in polymer solutions.

  17. Effect of cloud cover and surface type on earth's radiation budget derived from the first year of ERBE data

    NASA Technical Reports Server (NTRS)

    Gibson, G. G.; Denn, F. M.; Young, D. F.; Harrison, E. F.; Minnis, P.; Barkstrom, B. R.

    1990-01-01

    One year of ERBE data is analyzed for variations in outgoing LW and absorbed solar flux. Differences in land and ocean radiation budgets as well as differences between clear-sky and total scenes, including clouds, are studied. The variation of monthly average radiative parameters is examined for February 1985 through January 1986 for selected study regions and on zonal and global scales. ERBE results show significant seasonal variations in both outgoing LW and absorbed SW flux, and a pronounced difference between oceanic and continental surfaces. The main factors determining cloud radiative forcing in a given region are solar insolation, cloud amount, cloud type, and surface properties. The strongest effects of clouds are found in the midlatitude storm tracks over the oceans. Over much of the globe, LW warming is balanced by SW cooling. The annual-global average net cloud forcing shows that clouds have a net cooling effect on the earth for the year.

  18. Identification Code of Interstellar Cloud within IRAF

    NASA Astrophysics Data System (ADS)

    Lee, Youngung; Jung, Jae Hoon; Kim, Hyun-Goo

    1997-12-01

    We present a code which identifies individual clouds in crowded region using IMFORT interface within Image Reduction and Analysis Facility(IRAF). We define a cloud as an object composed of all pixels in longitude, latitude, and velocity that are simply connected and that lie above some threshold temperature. The code searches the whole pixels of the data cube in efficient way to isolate individual clouds. Along with identification of clouds it is designed to estimate their mean values of longitudes, latitudes, and velocities. In addition, a function of generating individual images(or cube data) of identified clouds is added up. We also present identified individual clouds using a 12CO survey data cube of Galactic Anticenter Region(Lee et al. 1997) as a test example. We used a threshold temperature of 5 sigma rms noise level of the data. With a higher threshold temperature, we isolated subclouds of a huge cloud identified originally. As the most important parameter to identify clouds is the threshold value, its effect to the size and velocity dispersion is discussed rigorously.

  19. Efficient Redundancy Techniques in Cloud and Desktop Grid Systems using MAP/G/c-type Queues

    NASA Astrophysics Data System (ADS)

    Chakravarthy, Srinivas R.; Rumyantsev, Alexander

    2018-03-01

    Cloud computing is continuing to prove its flexibility and versatility in helping industries and businesses as well as academia as a way of providing needed computing capacity. As an important alternative to cloud computing, desktop grids allow to utilize the idle computer resources of an enterprise/community by means of distributed computing system, providing a more secure and controllable environment with lower operational expenses. Further, both cloud computing and desktop grids are meant to optimize limited resources and at the same time to decrease the expected latency for users. The crucial parameter for optimization both in cloud computing and in desktop grids is the level of redundancy (replication) for service requests/workunits. In this paper we study the optimal replication policies by considering three variations of Fork-Join systems in the context of a multi-server queueing system with a versatile point process for the arrivals. For services we consider phase type distributions as well as shifted exponential and Weibull. We use both analytical and simulation approach in our analysis and report some interesting qualitative results.

  20. Searching for dark clouds in the outer galactic plane. I. A statistical approach for identifying extended red(dened) regions in 2MASS

    NASA Astrophysics Data System (ADS)

    Frieswijk, W. W. F.; Shipman, R. F.

    2010-06-01

    Context. Most of what is known about clustered star formation to date comes from well studied star forming regions located relatively nearby, such as Rho-Ophiuchus, Serpens and Perseus. However, the recent discovery of infrared dark clouds may give new insights in our understanding of this dominant mode of star formation in the Galaxy. Though the exact role of infrared dark clouds in the formation process is still somewhat unclear, they seem to provide useful laboratories to study the very early stages of clustered star formation. Infrared dark clouds have been identified predominantly toward the bright inner parts of the galactic plane. The low background emission makes it more difficult to identify similar objects in mid-infrared absorption in the outer parts. This is unfortunate, because the outer Galaxy represents the only nearby region where we can study effects of different (external) conditions on the star formation process. Aims: The aim of this paper is to identify extended red regions in the outer galactic plane based on reddening of stars in the near-infrared. We argue that these regions appear reddened mainly due to extinction caused by molecular clouds and young stellar objects. The work presented here is used as a basis for identifying star forming regions and in particular the very early stages. An accompanying paper describes the cross-identification of the identified regions with existing data, uncovering more on the nature of the reddening. Methods: We use the Mann-Whitney U-test, in combination with a friends-of-friends algorithm, to identify extended reddened regions in the 2MASS all-sky JHK survey. We process the data on a regular grid using two different resolutions, 60´´ and 90´´. The two resolutions have been chosen because the stellar surface density varies between the crowded spiral arm regions and the sparsely populated galactic anti-center region. Results: We identify 1320 extended red regions at the higher resolution and 1589 in the

  1. Stratocumulus Cloud Top Radiative Cooling and Cloud Base Updraft Speeds

    NASA Astrophysics Data System (ADS)

    Kazil, J.; Feingold, G.; Balsells, J.; Klinger, C.

    2017-12-01

    Cloud top radiative cooling is a primary driver of turbulence in the stratocumulus-topped marine boundary. A functional relationship between cloud top cooling and cloud base updraft speeds may therefore exist. A correlation of cloud top radiative cooling and cloud base updraft speeds has been recently identified empirically, providing a basis for satellite retrieval of cloud base updraft speeds. Such retrievals may enable analysis of aerosol-cloud interactions using satellite observations: Updraft speeds at cloud base co-determine supersaturation and therefore the activation of cloud condensation nuclei, which in turn co-determine cloud properties and precipitation formation. We use large eddy simulation and an off-line radiative transfer model to explore the relationship between cloud-top radiative cooling and cloud base updraft speeds in a marine stratocumulus cloud over the course of the diurnal cycle. We find that during daytime, at low cloud water path (CWP < 50 g m-2), cloud base updraft speeds and cloud top cooling are well-correlated, in agreement with the reported empirical relationship. During the night, in the absence of short-wave heating, CWP builds up (CWP > 50 g m-2) and long-wave emissions from cloud top saturate, while cloud base heating increases. In combination, cloud top cooling and cloud base updrafts become weakly anti-correlated. A functional relationship between cloud top cooling and cloud base updraft speed can hence be expected for stratocumulus clouds with a sufficiently low CWP and sub-saturated long-wave emissions, in particular during daytime. At higher CWPs, in particular at night, the relationship breaks down due to saturation of long-wave emissions from cloud top.

  2. Architectural Implications of Cloud Computing

    DTIC Science & Technology

    2011-10-24

    Public Cloud Infrastructure-as-a- Service (IaaS) Software -as-a- Service ( SaaS ) Cloud Computing Types Platform-as-a- Service (PaaS) Based on Type of...Twitter #SEIVirtualForum © 2011 Carnegie Mellon University Software -as-a- Service ( SaaS ) Model of software deployment in which a third-party...and System Solutions (RTSS) Program. Her current interests and projects are in service -oriented architecture (SOA), cloud computing, and context

  3. An Automated Cloud-edge Detection Algorithm Using Cloud Physics and Radar Data

    NASA Technical Reports Server (NTRS)

    Ward, Jennifer G.; Merceret, Francis J.; Grainger, Cedric A.

    2003-01-01

    An automated cloud edge detection algorithm was developed and extensively tested. The algorithm uses in-situ cloud physics data measured by a research aircraft coupled with ground-based weather radar measurements to determine whether the aircraft is in or out of cloud. Cloud edges are determined when the in/out state changes, subject to a hysteresis constraint. The hysteresis constraint prevents isolated transient cloud puffs or data dropouts from being identified as cloud boundaries. The algorithm was verified by detailed manual examination of the data set in comparison to the results from application of the automated algorithm.

  4. Clouds Aerosols Internal Affaires: Increasing Cloud Fraction and Enhancing the Convection

    NASA Technical Reports Server (NTRS)

    Koren, Ilan; Kaufman, Yoram; Remer, Lorraine; Rosenfeld, Danny; Rudich, Yinon

    2004-01-01

    Clouds developing in a polluted environment have more numerous, smaller cloud droplets that can increase the cloud lifetime and liquid water content. Such changes in the cloud droplet properties may suppress low precipitation allowing development of a stronger convection and higher freezing level. Delaying the washout of the cloud water (and aerosol), and the stronger convection will result in higher clouds with longer life time and larger anvils. We show these effects by using large statistics of the new, 1km resolution data from MODIS on the Terra satellite. We isolate the aerosol effects from meteorology by regression and showing that aerosol microphysical effects increases cloud fraction by average of 30 presents for all cloud types and increases convective cloud top pressure by average of 35mb. We analyze the aerosol cloud interaction separately for high pressure trade wind cloud systems and separately for deep convective cloud systems. The resultant aerosol radiative effect on climate for the high pressure cloud system is: -10 to -13 W/sq m at the top of the atmosphere (TOA) and -11 to -14 W/sq m at the surface. For deeper convective clouds the forcing is: -4 to -5 W/sq m at the TOA and -6 to -7 W/sq m at the surface.

  5. OORT-Cloud and Kuiper-Belt Comets

    NASA Technical Reports Server (NTRS)

    Whipple, Fred L.

    1998-01-01

    This paper follows the broadly accepted theory that Oort-Cloud Comets originated in the Solar Nebula in the general region where the major planets, Jupiter and Saturn, were formed while the Kuiper-Belt Comets originated farther out where the temperatures were lower. The Oort-Cloud Comets are identified orbitally by long periods and random inclinations and, including the Halley-type comets, comets with a Tisserand Criterion less than 2.0. Kuiper-Belt comets are identified by short periods, usually much less than 200 years, and small inclinations to the ecliptic. Here two criteria for comet activity are found to separate the two classes of comets. These quantities NG1 and NG2, were intended to measure theoretical nongravitaional effects on comet orbits. They are only, mildly successful in correlations with observed cases of measured non-gravitational forces. But, in fact, their variations with perihelion distance separate the two classes of comets. The results are consistent with the theory that the activity or intrinsic brightness of Oort-Cloud Comets fall off faster with increasing perihelion distance that does the intrinsic brightness of short-period Kuiper-Belt Comets.

  6. Tiny, Dusty, Galactic HI Clouds: The GALFA-HI Compact Cloud Catalog

    NASA Astrophysics Data System (ADS)

    Saul, Destry R.; Putman, M. E.; Peek, J. G.

    2013-01-01

    The recently published GALFA-HI Compact Cloud Catalog contains 2000 nearby neutral hydrogen clouds under 20' in angular size detected with a machine-vision algorithm in the Galactic Arecibo L-Band Feed Array HI survey (GALFA-HI). At a distance of 1kpc, the compact clouds would typically be 1 solar mass and 1pc in size. We observe that nearly all of the compact clouds that are classified as high velocity (> 90 km/s) are near previously-identified high velocity complexes. We separate the compact clouds into populations based on velocity, linewidth, and position. We have begun to search for evidence of dust in these clouds using IRIS and have detections in several populations.

  7. Satellite observations of the impact of weak volcanic activity on marine clouds

    NASA Astrophysics Data System (ADS)

    Gassó, Santiago

    2008-07-01

    Because emissions from weak volcanic eruptions tend to remain in the low troposphere, they may have a significant radiative impact through the indirect effect on clouds. However, this type of volcanic activity is underreported and its global impact has been assessed only by model simulations constrained with very limited observations. First observations of the impact of high-latitude active volcanoes on marine boundary layer clouds are reported here. These observations were made using a combination of standard derived products and visible images from the MODIS, AMSR-E and GOES detectors. Two distinctive effects are identified. When there is an existing boundary layer cloud deck, an increase in cloud brightness and a decrease in both cloud effective radius and liquid water content were observed immediately downwind of the volcanoes. The visible appearance of these "volcano tracks" resembles the effect of man-made ship tracks. When synoptic conditions favor low cloudiness, the volcano plume (or volcano cloud) increases significantly the cloud cover downwind. The volcano cloud can extend for hundreds of kilometers until mixing with background clouds. Unlike violent eruptions, the volcano clouds reported here (the Aleutian Islands in the North Pacific and the South Sandwich Islands in the South Atlantic) have retrieved microphysical properties similar to those observed in ship tracks. However, when comparing the volcano clouds from these two regions, liquid water content can decrease, increase or remain unchanged with respect to nearby unperturbed clouds. These differences suggest that composition at the source, type of eruption and meteorological conditions influence the evolution of the cloud.

  8. Classification of Arctic, Mid-Latitude and Tropical Clouds in the Mixed-Phase Temperature Regime

    NASA Astrophysics Data System (ADS)

    Costa, Anja; Afchine, Armin; Luebke, Anna; Meyer, Jessica; Dorsey, James R.; Gallagher, Martin W.; Ehrlich, André; Wendisch, Manfred; Krämer, Martina

    2016-04-01

    The degree of glaciation and the sizes and habits of ice particles formed in mixed-phase clouds remain not fully understood. However, these properties define the mixed clouds' radiative impact on the Earth's climate and thus a correct representation of this cloud type in global climate models is of importance for an improved certainty of climate predictions. This study focuses on the occurrence and characteristics of two types of clouds in the mixed-phase temperature regime (238-275K): coexistence clouds (Coex), in which both liquid drops and ice crystals exist, and fully glaciated clouds that develop in the Wegener-Bergeron-Findeisen regime (WBF clouds). We present an extensive dataset obtained by the Cloud and Aerosol Particle Spectrometer NIXE-CAPS, covering Arctic, mid-latitude and tropical regions. In total, we spent 45.2 hours within clouds in the mixed-phase temperature regime during five field campaigns (Arctic: VERDI, 2012 and RACEPAC, 2014 - Northern Canada; mid-latitude: COALESC, 2011 - UK and ML-Cirrus, 2014 - central Europe; tropics: ACRIDICON, 2014 - Brazil). We show that WBF and Coex clouds can be identified via cloud particle size distributions. The classified datasets are used to analyse temperature dependences of both cloud types as well as range and frequencies of cloud particle concentrations and sizes. One result is that Coex clouds containing supercooled liquid drops are found down to temperatures of -40 deg C only in tropical mixed clouds, while in the Arctic and mid-latitudes no liquid drops are observed below about -20 deg C. In addition, we show that the cloud particles' aspherical fractions - derived from polarization signatures of particles with diameters between 20 and 50 micrometers - differ significantly between WBF and Coex clouds. In Coex clouds, the aspherical fraction of cloud particles is generally very low, but increases with decreasing temperature. In WBF clouds, where all cloud particles are ice, about 20-40% of the cloud

  9. Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses

    NASA Technical Reports Server (NTRS)

    Molnar, Gyula I.; Susskind, Joel

    2005-01-01

    The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.

  10. Context-aware distributed cloud computing using CloudScheduler

    NASA Astrophysics Data System (ADS)

    Seuster, R.; Leavett-Brown, CR; Casteels, K.; Driemel, C.; Paterson, M.; Ring, D.; Sobie, RJ; Taylor, RP; Weldon, J.

    2017-10-01

    The distributed cloud using the CloudScheduler VM provisioning service is one of the longest running systems for HEP workloads. It has run millions of jobs for ATLAS and Belle II over the past few years using private and commercial clouds around the world. Our goal is to scale the distributed cloud to the 10,000-core level, with the ability to run any type of application (low I/O, high I/O and high memory) on any cloud. To achieve this goal, we have been implementing changes that utilize context-aware computing designs that are currently employed in the mobile communication industry. Context-awareness makes use of real-time and archived data to respond to user or system requirements. In our distributed cloud, we have many opportunistic clouds with no local HEP services, software or storage repositories. A context-aware design significantly improves the reliability and performance of our system by locating the nearest location of the required services. We describe how we are collecting and managing contextual information from our workload management systems, the clouds, the virtual machines and our services. This information is used not only to monitor the system but also to carry out automated corrective actions. We are incrementally adding new alerting and response services to our distributed cloud. This will enable us to scale the number of clouds and virtual machines. Further, a context-aware design will enable us to run analysis or high I/O application on opportunistic clouds. We envisage an open-source HTTP data federation (for example, the DynaFed system at CERN) as a service that would provide us access to existing storage elements used by the HEP experiments.

  11. First observations of tracking clouds using scanning ARM cloud radars

    DOE PAGES

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    2014-12-01

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud fieldmore » and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.« less

  12. First observations of tracking clouds using scanning ARM cloud radars

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Borque, Paloma; Giangrande, Scott; Kollias, Pavlos

    Tracking clouds using scanning cloud radars can help to document the temporal evolution of cloud properties well before large drop formation (‘‘first echo’’). These measurements complement cloud and precipitation tracking using geostationary satellites and weather radars. Here, two-dimensional (2-D) Along-Wind Range Height Indicator (AW-RHI) observations of a population of shallow cumuli (with and without precipitation) from the 35-GHz scanning ARM cloud radar (SACR) at the DOE Atmospheric Radiation Measurements (ARM) program Southern Great Plains (SGP) site are presented. Observations from the ARM SGP network of scanning precipitation radars are used to provide the larger scale context of the cloud fieldmore » and to highlight the advantages of the SACR to detect the numerous, small, non-precipitating cloud elements. A new Cloud Identification and Tracking Algorithm (CITA) is developed to track cloud elements. In CITA, a cloud element is identified as a region having a contiguous set of pixels exceeding a preset reflectivity and size threshold. The high temporal resolution of the SACR 2-D observations (30 sec) allows for an area superposition criteria algorithm to match cloud elements at consecutive times. Following CITA, the temporal evolution of cloud element properties (number, size, and maximum reflectivity) is presented. The vast majority of the designated elements during this cumulus event were short-lived non-precipitating clouds having an apparent life cycle shorter than 15 minutes. The advantages and disadvantages of cloud tracking using an SACR are discussed.« less

  13. Droplet Size Distributions as a function of rainy system type and Cloud Condensation Nuclei concentrations

    NASA Astrophysics Data System (ADS)

    Cecchini, Micael A.; Machado, Luiz A. T.; Artaxo, Paulo

    2014-06-01

    This work aims to study typical Droplet Size Distributions (DSDs) for different types of precipitation systems and Cloud Condensation Nuclei concentrations over the Vale do Paraíba region in southeastern Brazil. Numerous instruments were deployed during the CHUVA (Cloud processes of tHe main precipitation systems in Brazil: a contribUtion to cloud resolVing modeling and to the GPM) Project in Vale do Paraíba campaign, from November 22, 2011 through January 10, 2012. Measurements of CCN (Cloud Condensation Nuclei) and total particle concentrations, along with measurements of rain DSDs and standard atmospheric properties, including temperature, pressure and wind intensity and direction, were specifically made in this study. The measured DSDs were parameterized with a gamma function using the moment method. The three gamma parameters were disposed in a 3-dimensional space, and subclasses were classified using cluster analysis. Seven DSD categories were chosen to represent the different types of DSDs. The DSD classes were useful in characterizing precipitation events both individually and as a group of systems with similar properties. The rainfall regime classification system was employed to categorize rainy events as local convective rainfall, organized convection rainfall and stratiform rainfall. Furthermore, the frequencies of the seven DSD classes were associated to each type of rainy event. The rainfall categories were also employed to evaluate the impact of the CCN concentration on the DSDs. In the stratiform rain events, the polluted cases had a statistically significant increase in the total rain droplet concentrations (TDCs) compared to cleaner events. An average concentration increase from 668 cm- 3 to 2012 cm- 3 for CCN at 1% supersaturation was found to be associated with an increase of approximately 87 m- 3 in TDC for those events. For the local convection cases, polluted events presented a 10% higher mass weighted mean diameter (Dm) on average. For the

  14. Cloud computing security.

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Shin, Dongwan; Claycomb, William R.; Urias, Vincent E.

    Cloud computing is a paradigm rapidly being embraced by government and industry as a solution for cost-savings, scalability, and collaboration. While a multitude of applications and services are available commercially for cloud-based solutions, research in this area has yet to fully embrace the full spectrum of potential challenges facing cloud computing. This tutorial aims to provide researchers with a fundamental understanding of cloud computing, with the goals of identifying a broad range of potential research topics, and inspiring a new surge in research to address current issues. We will also discuss real implementations of research-oriented cloud computing systems for bothmore » academia and government, including configuration options, hardware issues, challenges, and solutions.« less

  15. Characterization of Cloud Water-Content Distribution

    NASA Technical Reports Server (NTRS)

    Lee, Seungwon

    2010-01-01

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

  16. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne

    2008-01-01

    Aerosols and especially their effect on clouds are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on clouds remains largely unknown and the processes involved not well understood. A recent report published by the National Academy of Science states "The greatest uncertainty about the aerosol climate forcing - indeed, the largest of all the uncertainties about global climate forcing - is probably the indirect effect of aerosols on clouds [NRC, 2001]." The aerosol effect on clouds is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the cloud droplet sizes for a constant liquid water path [Twomey, 1977] and the "semi-direct" effect on cloud coverage [e.g., Ackerman et al ., 2001]." Enhanced aerosol concentrations can also suppress warm rain processes by producing a narrow droplet spectrum that inhibits collision and coalescence processes [e.g., Squires and Twomey, 1961; Warner and Twomey, 1967; Warner, 1968; Rosenfeld, 19991. The aerosol effect on precipitation processes, also known as the second type of aerosol indirect effect [Albrecht, 1989], is even more complex, especially for mixed-phase convective clouds. Table 1 summarizes the key observational studies identifying the microphysical properties, cloud characteristics, thermodynamics and dynamics associated with cloud systems from high-aerosol continental environments. For example, atmospheric aerosol concentrations can influence cloud droplet size distributions, warm-rain process, cold-rain process, cloud-top height, the depth of the mixed phase region, and occurrence of lightning. In addition, high aerosol concentrations in urban environments could affect precipitation variability by providing an enhanced source of cloud condensation nuclei (CCN). Hypotheses have been developed to explain the effect of urban regions on convection and precipitation [van den Heever and Cotton, 2007 and Shepherd, 2005

  17. Cloud-Induced Uncertainty for Visual Navigation

    DTIC Science & Technology

    2014-12-26

    images at the pixel level. The result is a method that can overlay clouds with various structures on top of any desired image to produce realistic...cloud-shaped structures . The primary contribution of this research, however, is to investigate and quantify the errors in features due to clouds. The...of clouds types, this method does not emulate the true structure of clouds. An alternative popular modern method of creating synthetic clouds is known

  18. The peculiar, luminous early-type emission line stars of the Magellanic clouds: A preliminary taxonomy

    NASA Technical Reports Server (NTRS)

    Shore, S. N.; Sanduleak, N.

    1982-01-01

    A sample of some 20 early type emission supergiants in the Magellanic clouds was observed with both the SWP and LWR low resolution mode of IUE. All stars have strong H-emission, some showing P-Cygni structure as well with HeI, HeII, FeII and other ions also showing strong emission. It is found that the stars fall into three distinct groups on the basis of the HeII/HeI and HeI/HI strengths: (1) HeII strong, HeI, HI; (2) HeII absent, HeI, HI strong; (3) HeI absent, HI, FeII, FeII, strong in addition to low excitation ions. The two most extreme emission line stars found in the Clouds S 134/LMC and S 18/SMC are discussed. Results for the 2200A feature in these supergiants, and evidence for shells around the most luminous stars in the clouds are also described.

  19. Cloud and aerosol studies using combined CPL and MAS data

    NASA Astrophysics Data System (ADS)

    Vaughan, Mark A.; Rodier, Sharon; Hu, Yongxiang; McGill, Matthew J.; Holz, Robert E.

    2004-11-01

    Current uncertainties in the role of aerosols and clouds in the Earth's climate system limit our abilities to model the climate system and predict climate change. These limitations are due primarily to difficulties of adequately measuring aerosols and clouds on a global scale. The A-train satellites (Aqua, CALIPSO, CloudSat, PARASOL, and Aura) will provide an unprecedented opportunity to address these uncertainties. The various active and passive sensors of the A-train will use a variety of measurement techniques to provide comprehensive observations of the multi-dimensional properties of clouds and aerosols. However, to fully achieve the potential of this ensemble requires a robust data analysis framework to optimally and efficiently map these individual measurements into a comprehensive set of cloud and aerosol physical properties. In this work we introduce the Multi-Instrument Data Analysis and Synthesis (MIDAS) project, whose goal is to develop a suite of physically sound and computationally efficient algorithms that will combine active and passive remote sensing data in order to produce improved assessments of aerosol and cloud radiative and microphysical properties. These algorithms include (a) the development of an intelligent feature detection algorithm that combines inputs from both active and passive sensors, and (b) identifying recognizable multi-instrument signatures related to aerosol and cloud type derived from clusters of image pixels and the associated vertical profile information. Classification of these signatures will lead to the automated identification of aerosol and cloud types. Testing of these new algorithms is done using currently existing and readily available active and passive measurements from the Cloud Physics Lidar and the MODIS Airborne Simulator, which simulate, respectively, the CALIPSO and MODIS A-train instruments.

  20. Identifying the impact of G-quadruplexes on Affymetrix 3' arrays using cloud computing.

    PubMed

    Memon, Farhat N; Owen, Anne M; Sanchez-Graillet, Olivia; Upton, Graham J G; Harrison, Andrew P

    2010-01-15

    A tetramer quadruplex structure is formed by four parallel strands of DNA/ RNA containing runs of guanine. These quadruplexes are able to form because guanine can Hoogsteen hydrogen bond to other guanines, and a tetrad of guanines can form a stable arrangement. Recently we have discovered that probes on Affymetrix GeneChips that contain runs of guanine do not measure gene expression reliably. We associate this finding with the likelihood that quadruplexes are forming on the surface of GeneChips. In order to cope with the rapidly expanding size of GeneChip array datasets in the public domain, we are exploring the use of cloud computing to replicate our experiments on 3' arrays to look at the effect of the location of G-spots (runs of guanines). Cloud computing is a recently introduced high-performance solution that takes advantage of the computational infrastructure of large organisations such as Amazon and Google. We expect that cloud computing will become widely adopted because it enables bioinformaticians to avoid capital expenditure on expensive computing resources and to only pay a cloud computing provider for what is used. Moreover, as well as financial efficiency, cloud computing is an ecologically-friendly technology, it enables efficient data-sharing and we expect it to be faster for development purposes. Here we propose the advantageous use of cloud computing to perform a large data-mining analysis of public domain 3' arrays.

  1. ASCA observations of the Large Magellanic Cloud supernova remnant sample: Typing supernovae from their remnants

    NASA Technical Reports Server (NTRS)

    Hughes, John P.; Hayashi, Ichizo; Helfand, David; Hwang, Una; Itoh, Masayuki; Kirshner, Robert; Koyama, Katsuji; Markert, Thomas; Tsunemi, Hiroshi; Woo, Jonathan

    1995-01-01

    We present our first results from a study of the supernova remnants (SNRs) in the Large Magellanic Cloud (LMC) using data from ASCA. The three remnants we have analyzed to date, 0509-67.5, 0519-69.0, and N103B, are among the smallest, and presumably also the youngest, in the Cloud. The X-ray spectra of these SNRs show strong K alpha emission lines of silicon, sulfur, argon, and calcium with no evidence for corresponding lines of oxygen, neon, or magnesium. The dominant feature in the spectra is a broad blend of emission lines around 1 keV which we attribute to L-shell emission lines of iron. Model calculations (Nomoto, Thielemann, & Yokoi 1984) show that the major products of nucleosynthesis in Type Ia supernovae (SNs) are the elements from silicon to iron, as observed here. The calculated nucleosynthetic yields from Type Ib and II SNs are shown to be qualitatively inconsistent with the data. We conclude that the SNs which produced these remnants were of Type Ia. This finding also confirms earlier suggestions that the class of Balmer-dominated remnants arise from Type Ia SN explosions. Based on these early results from the LMC SNR sample, we find that roughly one-half of the SNRs produced in the LMC within the last approximately 1500 yr came from Type Ia SNs.

  2. RCW 36 in the Vela Molecular Ridge: Evidence for high-mass star-cluster formation triggered by cloud-cloud collision

    NASA Astrophysics Data System (ADS)

    Sano, Hidetoshi; Enokiya, Rei; Hayashi, Katsuhiro; Yamagishi, Mitsuyoshi; Saeki, Shun; Okawa, Kazuki; Tsuge, Kisetsu; Tsutsumi, Daichi; Kohno, Mikito; Hattori, Yusuke; Yoshiike, Satoshi; Fujita, Shinji; Nishimura, Atsushi; Ohama, Akio; Tachihara, Kengo; Torii, Kazufumi; Hasegawa, Yutaka; Kimura, Kimihiro; Ogawa, Hideo; Wong, Graeme F.; Braiding, Catherine; Rowell, Gavin; Burton, Michael G.; Fukui, Yasuo

    2018-02-01

    A collision between two molecular clouds is one possible candidate for high-mass star formation. The H II region RCW 36, located in the Vela molecular ridge, contains a young star cluster (˜ 1 Myr old) and two O-type stars. We present new CO observations of RCW 36 made with NANTEN2, Mopra, and ASTE using 12CO(J = 1-0, 2-1, 3-2) and 13CO(J = 2-1) emission lines. We have discovered two molecular clouds lying at the velocities VLSR ˜ 5.5 and 9 km s-1. Both clouds are likely to be physically associated with the star cluster, as verified by the good spatial correspondence among the two clouds, infrared filaments, and the star cluster. We also found a high intensity ratio of ˜ 0.6-1.2 for CO J = 3-2/1-0 toward both clouds, indicating that the gas temperature has been increased due to heating by the O-type stars. We propose that the O-type stars in RCW 36 were formed by a collision between the two clouds, with a relative velocity separation of 5 km s-1. The complementary spatial distributions and the velocity separation of the two clouds are in good agreement with observational signatures expected for O-type star formation triggered by a cloud-cloud collision. We also found a displacement between the complementary spatial distributions of the two clouds, which we estimate to be 0.3 pc assuming the collision angle to be 45° relative to the line-of-sight. We estimate the collision timescale to be ˜ 105 yr. It is probable that the cluster age found by Ellerbroek et al. (2013b, A&A, 558, A102) is dominated by the low-mass members which were not formed under the triggering by cloud-cloud collision, and that the O-type stars in the center of the cluster are explained by the collisional triggering independently from the low-mass star formation.

  3. RCW 36 in the Vela Molecular Ridge: Evidence for high-mass star-cluster formation triggered by cloud-cloud collision

    NASA Astrophysics Data System (ADS)

    Sano, Hidetoshi; Enokiya, Rei; Hayashi, Katsuhiro; Yamagishi, Mitsuyoshi; Saeki, Shun; Okawa, Kazuki; Tsuge, Kisetsu; Tsutsumi, Daichi; Kohno, Mikito; Hattori, Yusuke; Yoshiike, Satoshi; Fujita, Shinji; Nishimura, Atsushi; Ohama, Akio; Tachihara, Kengo; Torii, Kazufumi; Hasegawa, Yutaka; Kimura, Kimihiro; Ogawa, Hideo; Wong, Graeme F.; Braiding, Catherine; Rowell, Gavin; Burton, Michael G.; Fukui, Yasuo

    2018-05-01

    A collision between two molecular clouds is one possible candidate for high-mass star formation. The H II region RCW 36, located in the Vela molecular ridge, contains a young star cluster (˜ 1 Myr old) and two O-type stars. We present new CO observations of RCW 36 made with NANTEN2, Mopra, and ASTE using 12CO(J = 1-0, 2-1, 3-2) and 13CO(J = 2-1) emission lines. We have discovered two molecular clouds lying at the velocities VLSR ˜ 5.5 and 9 km s-1. Both clouds are likely to be physically associated with the star cluster, as verified by the good spatial correspondence among the two clouds, infrared filaments, and the star cluster. We also found a high intensity ratio of ˜ 0.6-1.2 for CO J = 3-2/1-0 toward both clouds, indicating that the gas temperature has been increased due to heating by the O-type stars. We propose that the O-type stars in RCW 36 were formed by a collision between the two clouds, with a relative velocity separation of 5 km s-1. The complementary spatial distributions and the velocity separation of the two clouds are in good agreement with observational signatures expected for O-type star formation triggered by a cloud-cloud collision. We also found a displacement between the complementary spatial distributions of the two clouds, which we estimate to be 0.3 pc assuming the collision angle to be 45° relative to the line-of-sight. We estimate the collision timescale to be ˜ 105 yr. It is probable that the cluster age found by Ellerbroek et al. (2013b, A&A, 558, A102) is dominated by the low-mass members which were not formed under the triggering by cloud-cloud collision, and that the O-type stars in the center of the cluster are explained by the collisional triggering independently from the low-mass star formation.

  4. Implementing a warm cloud microphysics parameterization for convective clouds in NCAR CESM

    NASA Astrophysics Data System (ADS)

    Shiu, C.; Chen, Y.; Chen, W.; Li, J. F.; Tsai, I.; Chen, J.; Hsu, H.

    2013-12-01

    Most of cumulus convection schemes use simple empirical approaches to convert cloud liquid mass to rain water or cloud ice to snow e.g. using a constant autoconversion rate and dividing cloud liquid mass into cloud water and ice as function of air temperature (e.g. Zhang and McFarlane scheme in NCAR CAM model). There are few studies trying to use cloud microphysical schemes to better simulate such precipitation processes in the convective schemes of global models (e.g. Lohmann [2008] and Song, Zhang, and Li [2012]). A two-moment warm cloud parameterization (i.e. Chen and Liu [2004]) is implemented into the deep convection scheme of CAM5.2 of CESM model for treatment of conversion of cloud liquid water to rain water. Short-term AMIP type global simulations are conducted to evaluate the possible impacts from the modification of this physical parameterization. Simulated results are further compared to observational results from AMWG diagnostic package and CloudSAT data sets. Several sensitivity tests regarding to changes in cloud top droplet concentration (here as a rough testing for aerosol indirect effects) and changes in detrained cloud size of convective cloud ice are also carried out to understand their possible impacts on the cloud and precipitation simulations.

  5. Cool Star Beginnings: YSOs in the Perseus Molecular Cloud

    NASA Astrophysics Data System (ADS)

    Young, Kaisa E.; Young, Chadwick H.

    2015-01-01

    Nearby molecular clouds, where there is considerable evidence of ongoing star formation, provide the best opportunity to observe stars in the earliest stages of their formation. The Perseus molecular cloud contains two young clusters, IC 348 and NGC 1333 and several small dense cores of the type that produce only a few stars. Perseus is often cited as an intermediate case between quiescent low-mass and turbulent high-mass clouds, making it perhaps an ideal environment for studying ``typical low-mass star formation. We present an infrared study of the Perseus molecular cloud with data from the Spitzer Space Telescope as part of the ``From Molecular Cores to Planet Forming Disks (c2d) Legacy project tep{eva03}. By comparing Spitzer's near- and mid-infrared maps, we identify and classify the young stellar objects (YSOs) in the cloud using updated extinction corrected photometry. Virtually all of the YSOs in Perseus are forming in the clusters and other smaller associations at the east and west ends of the cloud with very little evidence of star formation in the midsection even in areas of high extinction.

  6. DAΦNE operation with electron-cloud-clearing electrodes.

    PubMed

    Alesini, D; Drago, A; Gallo, A; Guiducci, S; Milardi, C; Stella, A; Zobov, M; De Santis, S; Demma, T; Raimondi, P

    2013-03-22

    The effects of an electron cloud (e-cloud) on beam dynamics are one of the major factors limiting performances of high intensity positron, proton, and ion storage rings. In the electron-positron collider DAΦNE, namely, a horizontal beam instability due to the electron-cloud effect has been identified as one of the main limitations on the maximum stored positron beam current and as a source of beam quality deterioration. During the last machine shutdown in order to mitigate such instability, special electrodes have been inserted in all dipole and wiggler magnets of the positron ring. It has been the first installation all over the world of this type since long metallic electrodes have been installed in all arcs of the collider positron ring and are currently used during the machine operation in collision. This has allowed a number of unprecedented measurements (e-cloud instabilities growth rate, transverse beam size variation, tune shifts along the bunch train) where the e-cloud contribution is clearly evidenced by turning the electrodes on and off. In this Letter we briefly describe a novel design of the electrodes, while the main focus is on experimental measurements. Here we report all results that clearly indicate the effectiveness of the electrodes for e-cloud suppression.

  7. CATS Cloud-Aerosol Products and Near Real Time Capabilities

    NASA Astrophysics Data System (ADS)

    Nowottnick, E. P.; Yorks, J. E.; McGill, M. J.; Palm, S. P.; Hlavka, D. L.; Selmer, P. A.; Rodier, S. D.; Vaughan, M. A.

    2016-12-01

    The Cloud-Aerosol Transport System (CATS) is a backscatter lidar that is designed to demonstrate technologies in space for future Earth Science missions. CATS is located on the International Space Station (ISS), where it has been operating semi-continuously since February 2015. CATS provides observations of cloud and aerosol vertical profiles similar to CALIPSO, but with more comprehensive coverage of the tropics and mid-latitudes due to the ISS orbit properties. Additionally, the ISS orbit permits the study of diurnal variability of clouds and aerosols. CATS data has applications for identifying of cloud phase and aerosol types. Analysis of recent Level 2 data yield several biases in cloud and aerosol layer detection and identification, as well as retrievals of optical properties that will be improved for the next version to be released in late 2016. With data latency of less than 6 hours, CATS data is also being used for forecasting of volcanic plume transport, experimental data assimilation into aerosol transport models (GEOS-5, NAAPS), and field campaign flight planning (KORUS-AQ, ORACLES).

  8. Evaluation of multi-layer cloud detection based on MODIS CO2-slicing algorithm with CALIPSO-CloudSat measurements.

    NASA Astrophysics Data System (ADS)

    Viudez-Mora, A.; Kato, S.; Smith, W. L., Jr.; Chang, F. L.

    2016-12-01

    Knowledge of the vertical cloud distribution is important for a variety of climate and weather applications. The cloud overlapping variations greatly influence the atmospheric heating/cooling rates, with implications for the surface-troposphere radiative balance, global circulation and precipitation. Additionally, an accurate knowledge of the multi-layer cloud distribution in real-time can be used in applications such safety condition for aviation through storms and adverse weather conditions. In this study, we evaluate a multi-layered cloud algorithm (Chang et al. 2005) based on MODIS measurements aboard Aqua satellite (MCF). This algorithm uses the CO2-slicing technique combined with cloud properties determined from VIS, IR and NIR channels to locate high thin clouds over low-level clouds, and retrieve the τ of each layer. We use CALIPSO (Winker et. al, 2010) and CloudSat (Stephens et. al, 2002) (CLCS) derived cloud vertical profiles included in the C3M data product (Kato et al. 2010) to evaluate MCF derived multi-layer cloud properties. We focus on 2 layer overlapping and 1-layer clouds identified by the active sensors and investigate how well these systems are identified by the MODIS multi-layer technique. The results show that for these multi-layered clouds identified by CLCS, the MCF correctly identifies about 83% of the cases as multi-layer. However, it is found that the upper CTH is underestimated by about 2.6±0.4 km, because the CO2-slicing technique is not as sensitive to the cloud physical top as the CLCS. The lower CTH agree better with differences found to be about 1.2±0.5 km. Another outstanding issue for the MCF approach is the large number of multi-layer false alarms that occur in single-layer conditions. References: Chang, F.-L., and Z. Li, 2005: A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J. Atmos. Sci., 62. Kato, S., et al. (2010), Relationships among cloud occurrence frequency

  9. Overlap Properties of Clouds Generated by a Cloud Resolving Model

    NASA Technical Reports Server (NTRS)

    Oreopoulos, L.; Khairoutdinov, M.

    2002-01-01

    In order for General Circulation Models (GCMs), one of our most important tools to predict future climate, to correctly describe the propagation of solar and thermal radiation through the cloudy atmosphere a realistic description of the vertical distribution of cloud amount is needed. Actually, one needs not only the cloud amounts at different levels of the atmosphere, but also how these cloud amounts are related, in other words, how they overlap. Currently GCMs make some idealized assumptions about cloud overlap, for example that contiguous cloud layers overlap maximally and non-contiguous cloud layers overlap in a random fashion. Since there are difficulties in obtaining the vertical profile of cloud amount from observations, the realism of the overlap assumptions made in GCMs has not been yet rigorously investigated. Recently however, cloud observations from a relatively new type of ground radar have been used to examine the vertical distribution of cloudiness. These observations suggest that the GCM overlap assumptions are dubious. Our study uses cloud fields from sophisticated models dedicated to simulate cloud formation, maintenance, and dissipation called Cloud Resolving Models . These models are generally considered capable of producing realistic three-dimensional representation of cloudiness. Using numerous cloud fields produced by such a CRM we show that the degree of overlap between cloud layers is a function of their separation distance, and is in general described by a combination of the maximum and random overlap assumption, with random overlap dominating as separation distances increase. We show that it is possible to parameterize this behavior in a way that can eventually be incorporated in GCMs. Our results seem to have a significant resemblance to the results from the radar observations despite the completely different nature of the datasets. This consistency is encouraging and will promote development of new radiative transfer codes that will

  10. MONET: multidimensional radiative cloud scene model

    NASA Astrophysics Data System (ADS)

    Chervet, Patrick

    1999-12-01

    All cloud fields exhibit variable structures (bulge) and heterogeneities in water distributions. With the development of multidimensional radiative models by the atmospheric community, it is now possible to describe horizontal heterogeneities of the cloud medium, to study these influences on radiative quantities. We have developed a complete radiative cloud scene generator, called MONET (French acronym for: MOdelisation des Nuages En Tridim.) to compute radiative cloud scene from visible to infrared wavelengths for various viewing and solar conditions, different spatial scales, and various locations on the Earth. MONET is composed of two parts: a cloud medium generator (CSSM -- Cloud Scene Simulation Model) developed by the Air Force Research Laboratory, and a multidimensional radiative code (SHDOM -- Spherical Harmonic Discrete Ordinate Method) developed at the University of Colorado by Evans. MONET computes images for several scenario defined by user inputs: date, location, viewing angles, wavelength, spatial resolution, meteorological conditions (atmospheric profiles, cloud types)... For the same cloud scene, we can output different viewing conditions, or/and various wavelengths. Shadowing effects on clouds or grounds are taken into account. This code is useful to study heterogeneity effects on satellite data for various cloud types and spatial resolutions, and to determine specifications of new imaging sensor.

  11. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.

    2004-01-01

    Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles (i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail). Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, in the sub-tropics (Florida) and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low 'clean' concentration and a high 'dirty' concentration.

  12. Development of a Cloud Computing-Based Pier Type Port Structure Stability Evaluation Platform Using Fiber Bragg Grating Sensors.

    PubMed

    Jo, Byung Wan; Jo, Jun Ho; Khan, Rana Muhammad Asad; Kim, Jung Hoon; Lee, Yun Sung

    2018-05-23

    Structure Health Monitoring is a topic of great interest in port structures due to the ageing of structures and the limitations of evaluating structures. This paper presents a cloud computing-based stability evaluation platform for a pier type port structure using Fiber Bragg Grating (FBG) sensors in a system consisting of a FBG strain sensor, FBG displacement gauge, FBG angle meter, gateway, and cloud computing-based web server. The sensors were installed on core components of the structure and measurements were taken to evaluate the structures. The measurement values were transmitted to the web server via the gateway to analyze and visualize them. All data were analyzed and visualized in the web server to evaluate the structure based on the safety evaluation index (SEI). The stability evaluation platform for pier type port structures involves the efficient monitoring of the structures which can be carried out easily anytime and anywhere by converging new technologies such as cloud computing and FBG sensors. In addition, the platform has been successfully implemented at “Maryang Harbor” situated in Maryang-Meyon of Korea to test its durability.

  13. The Influence of Cloud Field Uniformity on Observed Cloud Amount

    NASA Astrophysics Data System (ADS)

    Riley, E.; Kleiss, J.; Kassianov, E.; Long, C. N.; Riihimaki, L.; Berg, L. K.

    2017-12-01

    Two ground-based measurements of cloud amount include cloud fraction (CF) obtained from time series of zenith-pointing radar-lidar observations and fractional sky cover (FSC) acquired from a Total Sky Imager (TSI). In comparison with the radars and lidars, the TSI has a considerably larger field of view (FOV 100° vs. 0.2°) and therefore is expected to have a different sensitivity to inhomogeneity in a cloud field. Radiative transfer calculations based on cloud properties retrieved from narrow-FOV overhead cloud observations may differ from shortwave and longwave flux observations due to spatial variability in local cloud cover. This bias will impede radiative closure for sampling reasons rather than the accuracy of cloud microphysics retrievals or radiative transfer calculations. Furthermore, the comparison between observed and modeled cloud amount from large eddy simulations (LES) models may be affected by cloud field inhomogeneity. The main goal of our study is to estimate the anticipated impact of cloud field inhomogeneity on the level of agreement between CF and FSC. We focus on shallow cumulus clouds observed at the U.S. Department of Energy Atmospheric Radiation Measurement Facility's Southern Great Plains (SGP) site in Oklahoma, USA. Our analysis identifies cloud field inhomogeneity using a novel metric that quantifies the spatial and temporal uniformity of FSC over 100-degree FOV TSI images. We demonstrate that (1) large differences between CF and FSC are partly attributable to increases in inhomogeneity and (2) using the uniformity metric can provide a meaningful assessment of uncertainties in observed cloud amount to aide in comparing ground-based measurements to radiative transfer or LES model outputs at SGP.

  14. An Objective Classification of Saturn Cloud Features from Cassini ISS Images

    NASA Technical Reports Server (NTRS)

    Del Genio, Anthony D.; Barbara, John M.

    2016-01-01

    A k -means clustering algorithm is applied to Cassini Imaging Science Subsystem continuum and methane band images of Saturn's northern hemisphere to objectively classify regional albedo features and aid in their dynamical interpretation. The procedure is based on a technique applied previously to visible- infrared images of Earth. It provides a new perspective on giant planet cloud morphology and its relationship to the dynamics and a meteorological context for the analysis of other types of simultaneous Saturn observations. The method identifies 6 clusters that exhibit distinct morphology, vertical structure, and preferred latitudes of occurrence. These correspond to areas dominated by deep convective cells; low contrast areas, some including thinner and thicker clouds possibly associated with baroclinic instability; regions with possible isolated thin cirrus clouds; darker areas due to thinner low level clouds or clearer skies due to downwelling, or due to absorbing particles; and fields of relatively shallow cumulus clouds. The spatial associations among these cloud types suggest that dynamically, there are three distinct types of latitude bands on Saturn: deep convectively disturbed latitudes in cyclonic shear regions poleward of the eastward jets; convectively suppressed regions near and surrounding the westward jets; and baro-clinically unstable latitudes near eastward jet cores and in the anti-cyclonic regions equatorward of them. These are roughly analogous to some of the features of Earth's tropics, subtropics, and midlatitudes, respectively. This classification may be more useful for dynamics purposes than the traditional belt-zone partitioning. Temporal variations of feature contrast and cluster occurrence suggest that the upper tropospheric haze in the northern hemisphere may have thickened by 2014. The results suggest that routine use of clustering may be a worthwhile complement to many different types of planetary atmospheric data analysis.

  15. Clouds in the Martian Atmosphere

    NASA Astrophysics Data System (ADS)

    Määttänen, Anni; Montmessin, Franck

    2018-01-01

    Although resembling an extremely dry desert, planet Mars hosts clouds in its atmosphere. Every day somewhere on the planet a part of the tiny amount of water vapor held by the atmosphere can condense as ice crystals to form cirrus-type clouds. The existence of water ice clouds has been known for a long time, and they have been studied for decades, leading to the establishment of a well-known climatology and understanding of their formation and properties. Despite their thinness, they have a clear impact on the atmospheric temperatures, thus affecting the Martian climate. Another, more exotic type of clouds forms as well on Mars. The atmospheric temperatures can plunge to such frigid values that the major gaseous component of the atmosphere, CO2, condenses as ice crystals. These clouds form in the cold polar night where they also contribute to the formation of the CO2 ice polar cap, and also in the mesosphere at very high altitudes, near the edge of space, analogously to the noctilucent clouds on Earth. The mesospheric clouds are a fairly recent discovery and have put our understanding of the Martian atmosphere to a test. On Mars, cloud crystals form on ice nuclei, mostly provided by the omnipresent dust. Thus, the clouds link the three major climatic cycles: those of the two major volatiles, H2O and CO2; and that of dust, which is a major climatic agent itself.

  16. Exploring the factors influencing the cloud computing adoption: a systematic study on cloud migration.

    PubMed

    Rai, Rashmi; Sahoo, Gadadhar; Mehfuz, Shabana

    2015-01-01

    Today, most of the organizations trust on their age old legacy applications, to support their business-critical systems. However, there are several critical concerns, as maintainability and scalability issues, associated with the legacy system. In this background, cloud services offer a more agile and cost effective platform, to support business applications and IT infrastructure. As the adoption of cloud services has been increasing recently and so has been the academic research in cloud migration. However, there is a genuine need of secondary study to further strengthen this research. The primary objective of this paper is to scientifically and systematically identify, categorize and compare the existing research work in the area of legacy to cloud migration. The paper has also endeavored to consolidate the research on Security issues, which is prime factor hindering the adoption of cloud through classifying the studies on secure cloud migration. SLR (Systematic Literature Review) of thirty selected papers, published from 2009 to 2014 was conducted to properly understand the nuances of the security framework. To categorize the selected studies, authors have proposed a conceptual model for cloud migration which has resulted in a resource base of existing solutions for cloud migration. This study concludes that cloud migration research is in seminal stage but simultaneously it is also evolving and maturing, with increasing participation from academics and industry alike. The paper also identifies the need for a secure migration model, which can fortify organization's trust into cloud migration and facilitate necessary tool support to automate the migration process.

  17. Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

    NASA Technical Reports Server (NTRS)

    Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

    2012-01-01

    Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

  18. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.

    2004-01-01

    Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

  19. The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.

    2004-01-01

    Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.

  20. Apollo 7 Mission,Clouds

    NASA Image and Video Library

    1968-10-11

    Apollo 7,Cumulus,alto-cumulus,cirrus clouds. Very high oblique. Cloud Cover 50%. Original film magazine was labeled S. Camera Data: Hasselblad 500-C; Lens: Zeiss Planar,F/2.8,80mm; Film Type: Kodak SO-121,Aerial Ektachrome; Filter: Wratten 2A. Flight Date: October 11-12. 1968.

  1. The GOES-R/JPSS Approach for Identifying Hazardous Low Clouds: Overview and Operational Impacts

    NASA Astrophysics Data System (ADS)

    Calvert, Corey; Pavolonis, Michael; Lindstrom, Scott; Gravelle, Chad; Terborg, Amanda

    2017-04-01

    Low ceiling and visibility is a weather hazard that nearly every forecaster, in nearly every National Weather Service (NWS) Weather Forecast Office (WFO), must regularly address. In addition, national forecast centers such as the Aviation Weather Center (AWC), Alaska Aviation Weather Unit (AAWU) and the Ocean Prediction Center (OPC) are responsible for issuing low ceiling and visibility related products. As such, reliable methods for detecting and characterizing hazardous low clouds are needed. Traditionally, hazardous areas of Fog/Low Stratus (FLS) are identified using a simple stand-alone satellite product that is constructed by subtracting the 3.9 and 11 μm brightness temperatures. However, the 3.9-11 μm brightness temperature difference (BTD) has several major limitations. In an effort to address the limitations of the BTD product, the GOES-R Algorithm Working Group (AWG) developed an approach that fuses satellite, Numerical Weather Prediction (NWP) model, Sea Surface Temperature (SST) analyses, and other data sets (e.g. digital surface elevation maps, surface emissivity maps, and surface type maps) to determine the probability that hazardous low clouds are present using a naïve Bayesian classifier. In addition, recent research has focused on blending geostationary (e.g. GOES-R) and low earth orbit (e.g. JPSS) satellite data to further improve the products. The FLS algorithm has adopted an enterprise approach in that it can utilize satellite data from a variety of current and future operational sensors and NWP data from a variety of models. The FLS products are available in AWIPS/N-AWIPS/AWIPS-II and have been evaluated within NWS operations over the last four years as part of the Satellite Proving Ground. Forecaster feedback has been predominantly positive and references to these products within Area Forecast Discussions (AFD's) indicate that the products are influencing operational forecasts. At the request of the NWS, the FLS products are currently being

  2. A microphysics guide to cirrus clouds - Part 1: Cirrus types

    NASA Astrophysics Data System (ADS)

    Krämer, Martina; Rolf, Christian; Luebke, Anna; Afchine, Armin; Spelten, Nicole; Costa, Anja; Meyer, Jessica; Zöger, Martin; Smith, Jessica; Herman, Robert L.; Buchholz, Bernhard; Ebert, Volker; Baumgardner, Darrel; Borrmann, Stephan; Klingebiel, Marcus; Avallone, Linnea

    2016-03-01

    The microphysical and radiative properties of cirrus clouds continue to be beyond understanding and thus still represent one of the largest uncertainties in the prediction of the Earth's climate (IPCC, 2013). Our study aims to provide a guide to cirrus microphysics, which is compiled from an extensive set of model simulations, covering the broad range of atmospheric conditions for cirrus formation and evolution. The model results are portrayed in the same parameter space as field measurements, i.e., in the Ice Water Content-Temperature (IWC-T) parameter space. We validate this cirrus analysis approach by evaluating cirrus data sets from 17 aircraft campaigns, conducted in the last 15 years, spending about 94 h in cirrus over Europe, Australia, Brazil as well as South and North America. Altogether, the approach of this study is to track cirrus IWC development with temperature by means of model simulations, compare with observations and then assign, to a certain degree, cirrus microphysics to the observations. Indeed, the field observations show characteristics expected from the simulated Cirrus Guide. For example, high (low) IWCs are found together with high (low) ice crystal concentrations Nice. An important finding from our study is the classification of two types of cirrus with differing formation mechanisms and microphysical properties: the first cirrus type forms directly as ice (in situ origin cirrus) and splits in two subclasses, depending on the prevailing strength of the updraft: in slow updrafts these cirrus are rather thin with lower IWCs, while in fast updrafts thicker cirrus with higher IWCs can form. The second type consists predominantly of thick cirrus originating from mixed phase clouds (i.e., via freezing of liquid droplets - liquid origin cirrus), which are completely glaciated while lifting to the cirrus formation temperature region (< 235 K). In the European field campaigns, slow updraft in situ origin cirrus occur frequently in low- and high

  3. Synergistic use of MODIS cloud products and AIRS radiance measurements for retrieval of cloud parameters

    NASA Astrophysics Data System (ADS)

    Li, J.; Menzel, W.; Sun, F.; Schmit, T.

    2003-12-01

    The Moderate-Resolution Imaging Spectroradiometer (MODIS) and Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS) Aqua satellite will enable global monitoring of the distribution of clouds. MODIS is able to provide at high spatial resolution (1 ~ 5km) the cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), and cloud water path (CWP). AIRS is able to provide CTP, ECA, CPS, and CWP within the AIRS footprint with much better accuracy using its greatly enhanced hyperspectral remote sensing capability. The combined MODIS / AIRS system offers the opportunity for cloud products improved over those possible from either system alone. The algorithm developed was applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS cloud products, as well as with the Geostationary Operational Environmental Satellite (GOES) sounder cloud products, to demonstrate the advantage of synergistic use of high spatial resolution MODIS cloud products and high spectral resolution AIRS sounder radiance measurements for optimal cloud retrieval. Data from ground-based instrumentation at the Atmospheric Radiation Measurement (ARM) Program Cloud and Radiation Test Bed (CART) in Oklahoma were used for the validation; results show that AIRS improves the MODIS cloud products in certain cases such as low-level clouds.

  4. Cloud cover models derived from satellite radiation measurements

    NASA Technical Reports Server (NTRS)

    Bean, S. J.; Somerville, P. N.

    1979-01-01

    Using daily measurement of day and night infrared and incoming and absorbed solar radiation obtained from a TIROS satellite over a period of approximately 45 months, and integrated over 2.5 degree latitude-longitude grids, the proportion of cloud cover over each grid each day was derived for the entire period. For each of four three-month periods, estimates a and b of the two parameters of the best-fit beta distribution were obtained for each grid location. The (a,b) plane was divided into a number of regions. All the geographical locations whose (a,b) estimates were in the same region in the (a,b) plane were said to have the same cloud cover type for that season. For each season, the world was thus divided into separate cloud cover types. Using estimates of mean cloud cover for each season, the world was again divided into separate cloud cover types. The process was repeated for standard deviations. Thus for each season, three separate cloud cover models were obtained using the criteria of shape of frequency distribution, mean cloud cover, and variability of cloud cover. The cloud cover statistics were derived from once-a-day, near-local-noon satellite radiation measurements.

  5. Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

    PubMed

    Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

    2013-03-23

    Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

  6. ASTER cloud coverage reassessment using MODIS cloud mask products

    NASA Astrophysics Data System (ADS)

    Tonooka, Hideyuki; Omagari, Kunjuro; Yamamoto, Hirokazu; Tachikawa, Tetsushi; Fujita, Masaru; Paitaer, Zaoreguli

    2010-10-01

    In the Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) Project, two kinds of algorithms are used for cloud assessment in Level-1 processing. The first algorithm based on the LANDSAT-5 TM Automatic Cloud Cover Assessment (ACCA) algorithm is used for a part of daytime scenes observed with only VNIR bands and all nighttime scenes, and the second algorithm based on the LANDSAT-7 ETM+ ACCA algorithm is used for most of daytime scenes observed with all spectral bands. However, the first algorithm does not work well for lack of some spectral bands sensitive to cloud detection, and the two algorithms have been less accurate over snow/ice covered areas since April 2008 when the SWIR subsystem developed troubles. In addition, they perform less well for some combinations of surface type and sun elevation angle. We, therefore, have developed the ASTER cloud coverage reassessment system using MODIS cloud mask (MOD35) products, and have reassessed cloud coverage for all ASTER archived scenes (>1.7 million scenes). All of the new cloud coverage data are included in Image Management System (IMS) databases of the ASTER Ground Data System (GDS) and NASA's Land Process Data Active Archive Center (LP DAAC) and used for ASTER product search by users, and cloud mask images are distributed to users through Internet. Daily upcoming scenes (about 400 scenes per day) are reassessed and inserted into the IMS databases in 5 to 7 days after each scene observation date. Some validation studies for the new cloud coverage data and some mission-related analyses using those data are also demonstrated in the present paper.

  7. Evaluating stratiform cloud base charge remotely

    NASA Astrophysics Data System (ADS)

    Harrison, R. Giles; Nicoll, Keri A.; Aplin, Karen L.

    2017-06-01

    Stratiform clouds acquire charge at their upper and lower horizontal boundaries due to vertical current flow in the global electric circuit. Cloud charge is expected to influence microphysical processes, but understanding is restricted by the infrequent in situ measurements available. For stratiform cloud bases below 1 km in altitude, the cloud base charge modifies the surface electric field beneath, allowing a new method of remote determination. Combining continuous cloud height data during 2015-2016 from a laser ceilometer with electric field mill data, cloud base charge is derived using a horizontal charged disk model. The median daily cloud base charge density found was -0.86 nC m-2 from 43 days' data. This is consistent with a uniformly charged region 40 m thick at the cloud base, now confirming that negative cloud base charge is a common feature of terrestrial layer clouds. This technique can also be applied to planetary atmospheres and volcanic plumes.type="synopsis">type</span>="main">Plain Language SummaryThe idea that <span class="hlt">clouds</span> in the atmosphere can charge electrically has been appreciated since the time of Benjamin Franklin, but it is less widely recognized that it is not just thunderclouds which contain electric charge. For example, water droplets in simple layer <span class="hlt">clouds</span>, that are abundant and often responsible for an overcast day, carry electric charges. The droplet charging arises at the upper and lower edges of the layer <span class="hlt">cloud</span>. This occurs because the small droplets at the edges draw charge from the air outside the <span class="hlt">cloud</span>. Understanding how strongly layer <span class="hlt">clouds</span> charge is important in evaluating electrical effects on the development of such <span class="hlt">clouds</span>, for example, how thick the <span class="hlt">cloud</span> becomes and whether it generates rain. Previously, <span class="hlt">cloud</span> charge measurement has required direct measurements within the <span class="hlt">cloud</span> using weather balloons or aircraft. This work has monitored the lower <span class="hlt">cloud</span> charge continuously using instruments placed at the surface beneath</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120015500','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120015500"><span>The Role of Aerosols on Precipitation Processes: <span class="hlt">Cloud</span> Resolving Model Simulations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tao, Wei-Kuo; Li, X.; Matsui, T.</p> <p>2012-01-01</p> <p> <span class="hlt">identify</span> the impact of ice processes, radiation and large-scale influence on <span class="hlt">cloud</span>-aerosol interactive processes, especially regarding surface rainfall amounts and characteristics (i.e., heavy or convective versus light or stratiform <span class="hlt">types</span>). In addition, an inert tracer was included to follow the vertical redistribution of aerosols by <span class="hlt">cloud</span> processes. We will also give a brief review from observational evidence on the role of aerosol on precipitation processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070014887','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070014887"><span>Stable Low <span class="hlt">Cloud</span> Phase II: Nocturnal Event Study</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bauman, William H., III; Barrett, Joe, III</p> <p>2007-01-01</p> <p> and Wheeler 2005), nearly 30% of the low <span class="hlt">cloud</span> ceiling cases investigated were <span class="hlt">identified</span> as rapidly developing events. Forecasters at the Space Meteorology Group (SMG) issue 30 to 90 minute forecasts for low <span class="hlt">cloud</span> ceilings at TTS to support Space Shuttle landings. Mission verification statistics have shown ceilings to be the number one forecast challenge. More specifically, forecasters at SMG are concerned with any rapidly developing <span class="hlt">clouds</span>/ceilings below 8000 R in a stable, capped thermodynamic environment. Therefore, the AMU was tasked to examine archived events of rapid stable <span class="hlt">cloud</span> formation resulting in ceilings below 8000 ft, and document the atmospheric regimes favoring this <span class="hlt">type</span> of <span class="hlt">cloud</span> development. The AMU examined the cool season months of November to March during the years of 1994-2005 for nights that had low-level inversions and rapid, stable low <span class="hlt">cloud</span> formation that resulted in ceilings violating the Space Shuttle FR. The AMU wrote and modified existing code to <span class="hlt">identify</span> inversions from the evening and morning XMR radiosonde during the cool season and output pertinent sounding information. They parsed all days with <span class="hlt">cloud</span> ceilings below 8000 ft at TTS, forming a database of possible rapidly-developing low ceiling events. Nights with precipitation or noticeable fog burn-off situations were excluded from the database. Only the nighttime hours were examined for possible ceiling development events since the daytime events were examined in the first phase of this work. The report presents one sample case of rapidly-developing low <span class="hlt">cloud</span> ceilings. The case depicts the representative meteorological and thermodynamic characteristics of such events. The case also illustrates how quickly the <span class="hlt">cloud</span> decks can develop, sometimes forming in 30 minutes or less. The report also summarizes the composite meteorological conditions for 6 event nights with rapid low <span class="hlt">cloud</span> ceiling formation and 80 non-events nights consisting of advection or widespread low <span class="hlt">cloud</span> ceilings. The</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=TYPES+AND+OF+AND+RADAR&id=ED434823','ERIC'); return false;" href="https://eric.ed.gov/?q=TYPES+AND+OF+AND+RADAR&id=ED434823"><span>Weather Fundamentals: <span class="hlt">Clouds</span>. [Videotape].</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>1998</p> <p></p> <p>The videos in this educational series, for grades 4-7, help students understand the science behind weather phenomena through dramatic live-action footage, vivid animated graphics, detailed weather maps, and hands-on experiments. This episode (23 minutes) discusses how <span class="hlt">clouds</span> form, the different <span class="hlt">types</span> of <span class="hlt">clouds</span>, and the important role they play in…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PASJ..tmp...32T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PASJ..tmp...32T"><span>Formation of massive, dense cores by <span class="hlt">cloud-cloud</span> collisions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Takahira, Ken; Shima, Kazuhiro; Habe, Asao; Tasker, Elizabeth J.</p> <p>2018-03-01</p> <p>We performed sub-parsec (˜ 0.014 pc) scale simulations of <span class="hlt">cloud-cloud</span> collisions of two idealized turbulent molecular <span class="hlt">clouds</span> (MCs) with different masses in the range of (0.76-2.67) × 104 M_{⊙} and with collision speeds of 5-30 km s-1. Those parameters are larger than in Takahira, Tasker, and Habe (2014, ApJ, 792, 63), in which study the colliding system showed a partial gaseous arc morphology that supports the NANTEN observations of objects indicated to be colliding MCs using numerical simulations. Gas clumps with density greater than 10-20 g cm-3 were <span class="hlt">identified</span> as pre-stellar cores and tracked through the simulation to investigate the effects of the mass of colliding <span class="hlt">clouds</span> and the collision speeds on the resulting core population. Our results demonstrate that the smaller <span class="hlt">cloud</span> property is more important for the results of <span class="hlt">cloud-cloud</span> collisions. The mass function of formed cores can be approximated by a power-law relation with an index γ = -1.6 in slower <span class="hlt">cloud-cloud</span> collisions (v ˜ 5 km s-1), and is in good agreement with observation of MCs. A faster relative speed increases the number of cores formed in the early stage of collisions and shortens the gas accretion phase of cores in the shocked region, leading to the suppression of core growth. The bending point appears in the high-mass part of the core mass function and the bending point mass decreases with increase in collision speed for the same combination of colliding <span class="hlt">clouds</span>. The higher-mass part of the core mass function than the bending point mass can be approximated by a power law with γ = -2-3 that is similar to the power index of the massive part of the observed stellar initial mass function. We discuss implications of our results for the massive-star formation in our Galaxy.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PASJ...70S..58T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PASJ...70S..58T"><span>Formation of massive, dense cores by <span class="hlt">cloud-cloud</span> collisions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Takahira, Ken; Shima, Kazuhiro; Habe, Asao; Tasker, Elizabeth J.</p> <p>2018-05-01</p> <p>We performed sub-parsec (˜ 0.014 pc) scale simulations of <span class="hlt">cloud-cloud</span> collisions of two idealized turbulent molecular <span class="hlt">clouds</span> (MCs) with different masses in the range of (0.76-2.67) × 104 M_{⊙} and with collision speeds of 5-30 km s-1. Those parameters are larger than in Takahira, Tasker, and Habe (2014, ApJ, 792, 63), in which study the colliding system showed a partial gaseous arc morphology that supports the NANTEN observations of objects indicated to be colliding MCs using numerical simulations. Gas clumps with density greater than 10-20 g cm-3 were <span class="hlt">identified</span> as pre-stellar cores and tracked through the simulation to investigate the effects of the mass of colliding <span class="hlt">clouds</span> and the collision speeds on the resulting core population. Our results demonstrate that the smaller <span class="hlt">cloud</span> property is more important for the results of <span class="hlt">cloud-cloud</span> collisions. The mass function of formed cores can be approximated by a power-law relation with an index γ = -1.6 in slower <span class="hlt">cloud-cloud</span> collisions (v ˜ 5 km s-1), and is in good agreement with observation of MCs. A faster relative speed increases the number of cores formed in the early stage of collisions and shortens the gas accretion phase of cores in the shocked region, leading to the suppression of core growth. The bending point appears in the high-mass part of the core mass function and the bending point mass decreases with increase in collision speed for the same combination of colliding <span class="hlt">clouds</span>. The higher-mass part of the core mass function than the bending point mass can be approximated by a power law with γ = -2-3 that is similar to the power index of the massive part of the observed stellar initial mass function. We discuss implications of our results for the massive-star formation in our Galaxy.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070023463','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070023463"><span>3D Aerosol-<span class="hlt">Cloud</span> Radiative Interaction Observed in Collocated MODIS and ASTER Images of Cumulus <span class="hlt">Cloud</span> Fields</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wen, Guoyong; Marshak, Alexander; Cahalan, Robert F.; Remer, Lorraine A.; Kleidman, Richard G.</p> <p>2007-01-01</p> <p>3D aerosol-<span class="hlt">cloud</span> interaction is examined by analyzing two images containing cumulus <span class="hlt">clouds</span> in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on <span class="hlt">identifying</span> 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to <span class="hlt">identify</span> key parameters in 3D aerosol-<span class="hlt">cloud</span> interaction. We found that 3D <span class="hlt">cloud</span>-induced enhancement depends on optical properties of nearb y <span class="hlt">clouds</span> as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby <span class="hlt">clouds</span> as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to <span class="hlt">clouds</span> or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A31I3137R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A31I3137R"><span>Quantifying the Climate-Scale Accuracy of Satellite <span class="hlt">Cloud</span> Retrievals</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roberts, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Liang, L.; Di Girolamo, L.</p> <p>2014-12-01</p> <p>Instrument calibration and <span class="hlt">cloud</span> retrieval algorithms have been developed to minimize retrieval errors on small scales. However, measurement uncertainties and assumptions within retrieval algorithms at the pixel level may alias into decadal-scale trends of <span class="hlt">cloud</span> properties. We first, therefore, quantify how instrument calibration changes could alias into <span class="hlt">cloud</span> property trends. For a perfect observing system the climate trend accuracy is limited only by the natural variability of the climate variable. Alternatively, for an actual observing system, the climate trend accuracy is additionally limited by the measurement uncertainty. Drifts in calibration over time may therefore be disguised as a true climate trend. We impose absolute calibration changes to MODIS spectral reflectance used as input to the CERES <span class="hlt">Cloud</span> Property Retrieval System (CPRS) and run the modified MODIS reflectance through the CPRS to determine the sensitivity of <span class="hlt">cloud</span> properties to calibration changes. We then use these changes to determine the impact of instrument calibration changes on trend uncertainty in reflected solar <span class="hlt">cloud</span> properties. Secondly, we quantify how much <span class="hlt">cloud</span> retrieval algorithm assumptions alias into <span class="hlt">cloud</span> optical retrieval trends by starting with the largest of these biases: the plane-parallel assumption in <span class="hlt">cloud</span> optical thickness (τC) retrievals. First, we collect liquid water <span class="hlt">cloud</span> fields obtained from Multi-angle Imaging Spectroradiometer (MISR) measurements to construct realistic probability distribution functions (PDFs) of 3D <span class="hlt">cloud</span> anisotropy (a measure of the degree to which <span class="hlt">clouds</span> depart from plane-parallel) for different ISCCP <span class="hlt">cloud</span> <span class="hlt">types</span>. Next, we will conduct a theoretical study with dynamically simulated <span class="hlt">cloud</span> fields and a 3D radiative transfer model to determine the relationship between 3D <span class="hlt">cloud</span> anisotropy and 3D τC bias for each <span class="hlt">cloud</span> <span class="hlt">type</span>. Combining these results provides distributions of 3D τC bias by <span class="hlt">cloud</span> <span class="hlt">type</span>. Finally, we will estimate the change in</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20060024553','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20060024553"><span>Analysis of Rapidly Developing Low <span class="hlt">Cloud</span> Ceilings in a Stable Environment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wheeler, Mark M.; Case, Jonathan L.</p> <p>2005-01-01</p> <p> <span class="hlt">identify</span> inversions from the morning Cape Canaveral, FL rawinsonde (XMR) during the cool season and output pertinent sounding information. They parsed all days with <span class="hlt">cloud</span> ceilings below 8000 ft at TTS, forming a database of possible rapidly-developing low ceiling events. Days with precipitation or noticeable fog bum-off situations were excluded from the database. Only the daytime hours were examined for possible ceiling development events since low <span class="hlt">clouds</span> are easier to diagnose with visible satellite imagery. Follow-on work would expand the database to include nighttime cases, using a special enhancement of the infrared imagery for <span class="hlt">identifying</span> areas of low <span class="hlt">clouds</span>. The report presents two sample cases of rapidly-developing low <span class="hlt">cloud</span> ceilings. These cases depict the representative meteorological and thermodynamic characteristics of such events. The cases also illustrate how quickly the <span class="hlt">cloud</span> decks can develop, sometimes forming in 30 minutes or less. The report also summarizes the composite meteorological conditions for 20 event days with rapid low <span class="hlt">cloud</span> ceiling formation and 48 non-events days consisting of advection or widespread low <span class="hlt">cloud</span> ceilings. The meteorological conditions were quite similar for both the event and non-event days, since both <span class="hlt">types</span> of days experienced low <span class="hlt">cloud</span> ceilings. Both <span class="hlt">types</span> of days had a relatively moist environment beneath the inversion based below 8000 ft. In the 20 events <span class="hlt">identified</span>, de onset of low ceilings occurred between 1200-1800 UTC in every instance. The distinguishing factor between the event and non-event days appears to be the vertical wind profile in the XMR sounding. Eighty-five percent of the event days had a clockwise turning of the winds with height in the lower to middle troposphere whereas 83% of the non-events had a counter-clockwise turning of the winds with height or negligible vertical wind shear. A clockwise turning of the winds with height indicates a warm advection regime, which supports large-scale rising motn and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950041632&hterms=cloud+database&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcloud%2Bdatabase','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950041632&hterms=cloud+database&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcloud%2Bdatabase"><span>IRAS images of nearby dark <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wood, Douglas O. S.; Myers, Philip C.; Daugherty, Debra A.</p> <p>1994-01-01</p> <p>We have investigated approximately 100 nearby molecular <span class="hlt">clouds</span> using the extensive, all-sky database of IRAS. The <span class="hlt">clouds</span> in this study cover a wide range of physical properties including visual extinction, size, mass, degree of isolation, homogeneity and morphology. IRAS 100 and 60 micron co-added images were used to calculate the 100 micron optical depth of dust in the <span class="hlt">clouds</span>. These images of dust optical depth compare very well with (12)CO and (13)CO observations, and can be related to H2 column density. From the optical depth images we locate the edges of dark <span class="hlt">clouds</span> and the dense cores inside them. We have <span class="hlt">identified</span> a total of 43 `IRAS <span class="hlt">clouds</span>' (regions with A(sub v) greater than 2) which contain a total of 255 `IRAS cores' (regions with A(sub v) greater than 4) and we catalog their physical properties. We find that the <span class="hlt">clouds</span> are remarkably filamentary, and that the cores within the <span class="hlt">clouds</span> are often distributed along the filaments. The largest cores are usually connected to other large cores by filaments. We have developed selection criteria to search the IRAS Point Source Catalog for stars that are likely to be associated with the <span class="hlt">clouds</span> and we catalog the IRAS sources in each <span class="hlt">cloud</span> or core. Optically visible stars associated with the <span class="hlt">clouds</span> have been <span class="hlt">identified</span> from the Herbig and Bell catalog. From these data we characterize the physical properties of the <span class="hlt">clouds</span> including their star-formation efficiency.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009debs.book..110K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009debs.book..110K"><span>Do <span class="hlt">Clouds</span> Compute? A Framework for Estimating the Value of <span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klems, Markus; Nimis, Jens; Tai, Stefan</p> <p></p> <p>On-demand provisioning of scalable and reliable compute services, along with a cost model that charges consumers based on actual service usage, has been an objective in distributed computing research and industry for a while. <span class="hlt">Cloud</span> Computing promises to deliver on this objective: consumers are able to rent infrastructure in the <span class="hlt">Cloud</span> as needed, deploy applications and store data, and access them via Web protocols on a pay-per-use basis. The acceptance of <span class="hlt">Cloud</span> Computing, however, depends on the ability for <span class="hlt">Cloud</span> Computing providers and consumers to implement a model for business value co-creation. Therefore, a systematic approach to measure costs and benefits of <span class="hlt">Cloud</span> Computing is needed. In this paper, we discuss the need for valuation of <span class="hlt">Cloud</span> Computing, <span class="hlt">identify</span> key components, and structure these components in a framework. The framework assists decision makers in estimating <span class="hlt">Cloud</span> Computing costs and to compare these costs to conventional IT solutions. We demonstrate by means of representative use cases how our framework can be applied to real world scenarios.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=theory+AND+everything&pg=4&id=EJ1063988','ERIC'); return false;" href="https://eric.ed.gov/?q=theory+AND+everything&pg=4&id=EJ1063988"><span>Learning in the <span class="hlt">Clouds</span>?</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Butin, Dan W.</p> <p>2013-01-01</p> <p>Engaged learning--the <span class="hlt">type</span> that happens outside textbooks and beyond the four walls of the classroom--moves beyond right and wrong answers to grappling with the uncertainties and contradictions of a complex world. iPhones back up to the "<span class="hlt">cloud</span>." GoogleDocs is all about "<span class="hlt">cloud</span> computing." Facebook is as ubiquitous as the sky.…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JPhCS.513f2037P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JPhCS.513f2037P"><span>ATLAS <span class="hlt">Cloud</span> R&D</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Panitkin, Sergey; Barreiro Megino, Fernando; Caballero Bejar, Jose; Benjamin, Doug; Di Girolamo, Alessandro; Gable, Ian; Hendrix, Val; Hover, John; Kucharczyk, Katarzyna; Medrano Llamas, Ramon; Love, Peter; Ohman, Henrik; Paterson, Michael; Sobie, Randall; Taylor, Ryan; Walker, Rodney; Zaytsev, Alexander; Atlas Collaboration</p> <p>2014-06-01</p> <p>The computing model of the ATLAS experiment was designed around the concept of grid computing and, since the start of data taking, this model has proven very successful. However, new <span class="hlt">cloud</span> computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and <span class="hlt">cloud</span> computing as complementary technologies that will coexist at different levels of resource abstraction, and two years ago created an R&D working group to investigate the different integration scenarios. The ATLAS <span class="hlt">Cloud</span> Computing R&D has been able to demonstrate the feasibility of offloading work from grid to <span class="hlt">cloud</span> sites and, as of today, is able to integrate transparently various <span class="hlt">cloud</span> resources into the PanDA workload management system. The ATLAS <span class="hlt">Cloud</span> Computing R&D is operating various PanDA queues on private and public resources and has provided several hundred thousand CPU days to the experiment. As a result, the ATLAS <span class="hlt">Cloud</span> Computing R&D group has gained a significant insight into the <span class="hlt">cloud</span> computing landscape and has <span class="hlt">identified</span> points that still need to be addressed in order to fully utilize this technology. This contribution will explain the <span class="hlt">cloud</span> integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic <span class="hlt">cloud</span> providers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A24B..03B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A24B..03B"><span>Characteristics of tropical <span class="hlt">clouds</span> using A-train information and their relationships with sea surface temperature</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Behrangi, A.; Kubar, T. L.; Lambrigtsen, B.</p> <p>2011-12-01</p> <p>Different <span class="hlt">cloud</span> <span class="hlt">types</span> have substantially different characteristics in terms of radiative forcing and microphysical properties, both important components of Earth's climate system. Relationships between tropical <span class="hlt">cloud</span> <span class="hlt">type</span> characteristics and sea surface temperature (SST) using two-years of A-train data are investigated in this presentation. Stratocumulus <span class="hlt">clouds</span> are the dominant <span class="hlt">cloud</span> <span class="hlt">type</span> over SSTs less than 301K, and in fact their fraction is strongly inversely related to SST. This is physically logical as both static stability and large-scale subsidence scale well with decreasing SST. At SSTs greater than 301K, high <span class="hlt">clouds</span> are the most abundant <span class="hlt">cloud</span> <span class="hlt">type</span>. All <span class="hlt">cloud</span> <span class="hlt">types</span> (except nimbostratus and stratocumulus) become sharply more abundant for SSTs greater than a window between 299K and 300.5K, depending on <span class="hlt">cloud</span> <span class="hlt">type</span>. The fraction of high, deep convective, altostratus, and altocumulus <span class="hlt">clouds</span> peak at an SST close to 303K, while cumulus <span class="hlt">clouds</span> have a broad <span class="hlt">cloud</span> fraction peak centered near 301K. Deep convective and other high <span class="hlt">cloud</span> <span class="hlt">types</span> decrease sharply above SSTs of 303K. While overall early morning <span class="hlt">clouds</span> are 10% (4%) more frequent than afternoon <span class="hlt">clouds</span> as indicated by <span class="hlt">Cloud</span>Sat (lidar-radar), certain <span class="hlt">cloud</span> <span class="hlt">types</span> occur more frequently in the early afternoon, such as high <span class="hlt">clouds</span>. We also show that a large amount of warm precipitation mainly from stratocumulus <span class="hlt">clouds</span> is missed or significantly underestimated by the current suite of satellite-based global precipitation measuring sensors. However, the operational sensitivity of Cloudsat <span class="hlt">cloud</span> profiling radar permits to capture significant fraction of light drizzle and warm rain.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_5");'>5</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li class="active"><span>7</span></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_7 --> <div id="page_8" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="141"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.8690S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.8690S"><span>A European Federated <span class="hlt">Cloud</span>: Innovative distributed computing solutions by EGI</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sipos, Gergely; Turilli, Matteo; Newhouse, Steven; Kacsuk, Peter</p> <p>2013-04-01</p> <p> Environments - with the EGI Federated <span class="hlt">Cloud</span> as long as these services access <span class="hlt">cloud</span> resources through the user-facing interfaces selected by the EGI community. The Task Force will be closed in May 2013. It already • <span class="hlt">Identified</span> key enabling technologies by which a multinational, federated 'Infrastructure as a Service' (IaaS) <span class="hlt">type</span> <span class="hlt">cloud</span> can be built from the NGIs' resources; • Deployed a test bed to evaluate the integration of virtualised resources within EGI and to engage with early adopter use cases from different scientific domains; • Integrated <span class="hlt">cloud</span> resources into the EGI production infrastructure through <span class="hlt">cloud</span> specific bindings of the EGI information system, monitoring system, authentication system, etc.; • Collected and catalogued requirements concerning the federated <span class="hlt">cloud</span> services from the feedback of early adopter use cases; • Provided feedback and requirements to relevant technology providers on their implementations and worked with these providers to address those requirements; • <span class="hlt">Identified</span> issues that need to be addressed by other areas of EGI (such as portal solutions, resource allocation policies, marketing and user support) to reach a production system. The Task Force will publish a blueprint in April 2013. The blueprint will drive the establishment of a production level EGI Federated <span class="hlt">Cloud</span> service after May 2013.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016MNRAS.455.1782K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016MNRAS.455.1782K"><span>Giant molecular <span class="hlt">cloud</span> scaling relations: the role of the <span class="hlt">cloud</span> definition</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khoperskov, S. A.; Vasiliev, E. O.; Ladeyschikov, D. A.; Sobolev, A. M.; Khoperskov, A. V.</p> <p>2016-01-01</p> <p>We investigate the physical properties of molecular <span class="hlt">clouds</span> in disc galaxies with different morphologies: a galaxy without prominent structure, a spiral barred galaxy and a galaxy with flocculent structure. Our N-body/hydrodynamical simulations take into account non-equilibrium H2 and CO chemical kinetics, self-gravity, star formation and feedback processes. For the simulated galaxies, the scaling relations of giant molecular <span class="hlt">clouds</span>, or so-called Larson's relations, are studied for two <span class="hlt">types</span> of <span class="hlt">cloud</span> definition (or extraction method): the first is based on total column density position-position (PP) data sets and the second is indicated by the CO (1-0) line emission used in position-position-velocity (PPV) data. We find that the <span class="hlt">cloud</span> populations obtained using both <span class="hlt">cloud</span> extraction methods generally have similar physical parameters, except that for the CO data the mass spectrum of <span class="hlt">clouds</span> has a tail with low-mass objects M ˜ 103-104 M⊙. Owing toa varying column density threshold, the power-law indices in the scaling relations are significantly changed. In contrast, the relations are invariant to the CO brightness temperature threshold. Finally, we find that the mass spectra of <span class="hlt">clouds</span> for PPV data are almost insensitive to the galactic morphology, whereas the spectra for PP data demonstrate significant variation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ESSD....9..881S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ESSD....9..881S"><span><span class="hlt">Cloud</span> property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the <span class="hlt">Cloud</span>_cci project</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stengel, Martin; Stapelberg, Stefan; Sus, Oliver; Schlundt, Cornelia; Poulsen, Caroline; Thomas, Gareth; Christensen, Matthew; Carbajal Henken, Cintia; Preusker, Rene; Fischer, Jürgen; Devasthale, Abhay; Willén, Ulrika; Karlsson, Karl-Göran; McGarragh, Gregory R.; Proud, Simon; Povey, Adam C.; Grainger, Roy G.; Fokke Meirink, Jan; Feofilov, Artem; Bennartz, Ralf; Bojanowski, Jedrzej S.; Hollmann, Rainer</p> <p>2017-11-01</p> <p>New <span class="hlt">cloud</span> property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for <span class="hlt">cloud</span> detection and <span class="hlt">cloud</span> <span class="hlt">typing</span> followed by <span class="hlt">cloud</span> property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve <span class="hlt">cloud</span>-top pressure, <span class="hlt">cloud</span> particle effective radius and <span class="hlt">cloud</span> optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved <span class="hlt">cloud</span> properties are further processed to derive <span class="hlt">cloud</span>-top height, <span class="hlt">cloud</span>-top temperature, <span class="hlt">cloud</span> liquid water path, <span class="hlt">cloud</span> ice water path and spectral <span class="hlt">cloud</span> albedo. The <span class="hlt">Cloud</span>_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly <span class="hlt">cloud</span> properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the <span class="hlt">Cloud</span>_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1394932','SCIGOV-DOEDE'); return false;" href="https://www.osti.gov/servlets/purl/1394932"><span><span class="hlt">Cloud</span> Climatology for Land Stations Worldwide, 1971-2009 (NDP-026D)</span></a></p> <p><a target="_blank" href="http://www.osti.gov/dataexplorer">DOE Data Explorer</a></p> <p>Hahn, C. J. [University of Arizona; Warren, S. G. [University of Washington; Eastman, R. [University of Washington</p> <p>2012-08-01</p> <p>Surface synoptic weather reports for 39 years have been processed to provide a climatology of <span class="hlt">clouds</span> for each of over 5000 land-based weather stations with long periods of record both day and night. For each station, this digital archive includes: multi-year annual, seasonal and monthly averages for day and night separately; seasonal and monthly averages by year; averages for eight times per day; and analyses of the first harmonic for the annual and diurnal cycles. Averages are given for total <span class="hlt">cloud</span> cover, clear-sky frequency, and 9 <span class="hlt">cloud</span> <span class="hlt">types</span>: 5 in the low level (fog, St, Sc, Cu, Cb), 3 in the middle level (Ns, As, Ac) and one in the high level (all cirriform <span class="hlt">clouds</span> combined). <span class="hlt">Cloud</span> amounts and frequencies of occurrence are given for all <span class="hlt">types</span>. In addition, non-overlapped amounts are given for middle and high <span class="hlt">cloud</span> <span class="hlt">types</span>, and average base heights are given for low <span class="hlt">cloud</span> <span class="hlt">types</span>. Nighttime averages were obtained by using only those reports that met an "illuminance criterion" (i.e., made under adequate moonlight or twilight), thus making possible the determination of diurnal cycles and nighttime trends for <span class="hlt">cloud</span> <span class="hlt">types</span>.The authors have also produced an online, gridded atlas of the <span class="hlt">cloud</span> observations contained in NDP-026D. The Online <span class="hlt">Cloud</span> Atlas containing NDP-026D data is available via the University of Washington.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20170008294&hterms=budget&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dbudget','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20170008294&hterms=budget&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dbudget"><span>Responses of <span class="hlt">Cloud</span> <span class="hlt">Type</span> Distributions to the Large-Scale Dynamical Circulation: Water Budget-Related Dynamical Phase Space and Dynamical Regimes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wong, Sun; Del Genio, Anthony; Wang, Tao; Kahn, Brian; Fetzer, Eric J.; L'Ecuyer, Tristan S.</p> <p>2015-01-01</p> <p>Goals: Water budget-related dynamical phase space; Connect large-scale dynamical conditions to atmospheric water budget (including precipitation); Connect atmospheric water budget to <span class="hlt">cloud</span> <span class="hlt">type</span> distributions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018BoLMe.166..165K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018BoLMe.166..165K"><span>Quantifying and Modelling the Effect of <span class="hlt">Cloud</span> Shadows on the Surface Irradiance at Tropical and Midlatitude Forests</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kivalov, Sergey N.; Fitzjarrald, David R.</p> <p>2018-02-01</p> <p><span class="hlt">Cloud</span> shadows lead to alternating light and dark periods at the surface, with the most abrupt changes occurring in the presence of low-level forced cumulus <span class="hlt">clouds</span>. We examine multiyear irradiance time series observed at a research tower in a midlatitude mixed deciduous forest (Harvard Forest, Massachusetts, USA: 42.53{°}N, 72.17{°}W) and one made at a similar tower in a tropical rain forest (Tapajós National Forest, Pará, Brazil: 2.86{°}S, 54.96{°}W). We link the durations of these periods statistically to conventional meteorological reports of sky <span class="hlt">type</span> and <span class="hlt">cloud</span> height at the two forests and present a method to synthesize the surface irradiance time series from sky-<span class="hlt">type</span> information. Four classes of events describing distinct sequential irradiance changes at the transition from <span class="hlt">cloud</span> shadow and direct sunlight are <span class="hlt">identified</span>: sharp-to-sharp, slow-to-slow, sharp-to-slow, and slow-to-sharp. Lognormal and the Weibull statistical distributions distinguish among cloudy-sky <span class="hlt">types</span>. Observers' qualitative reports of `scattered' and `broken' <span class="hlt">clouds</span> are quantitatively distinguished by a threshold value of the ratio of mean clear to cloudy period durations. Generated synthetic time series based on these statistics adequately simulate the temporal "radiative forcing" linked to sky <span class="hlt">type</span>. Our results offer a quantitative way to connect the conventional meteorological sky <span class="hlt">type</span> to the time series of irradiance experienced at the surface.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1394925','SCIGOV-DOEDE'); return false;" href="https://www.osti.gov/servlets/purl/1394925"><span>Climatological Data for <span class="hlt">Clouds</span> Over the Globe from Surface Observations (1988) (NDP-026)</span></a></p> <p><a target="_blank" href="http://www.osti.gov/dataexplorer">DOE Data Explorer</a></p> <p>Hahn, Carole J. [Univ. of Colorado, Boulder, CO (United States). Cooperative Inst. for Research in Environmental Sciences (CIRES); Warren, Stephen G. [Department of Atmospheric Sciences, University of Washington, Seattle, Washington; London, Julius [Department of Astrophysical, Planetary, and Atmospheric Sciences, University of Colorado, Boulder, CO; Jenne, Ray L. [National Center for Atmospheric Research, Boulder, CO (United States); Chervin, Robert M. [National Center for Atmospheric Research, Boulder, CO (United States)</p> <p>1988-01-01</p> <p>With some data from as early as 1930, global long-term monthly and/or seasonal total <span class="hlt">cloud</span> cover, <span class="hlt">cloud</span> <span class="hlt">type</span> amounts and frequencies of occurrence, low <span class="hlt">cloud</span> base heights, harmonic analyses of annual and diurnal cycles, interannual variations and trends, and <span class="hlt">cloud</span> <span class="hlt">type</span> co-occurrences have been compiled and presented in two atlases (Warren et al. 1988, 1990). These data were derived from land and ship synoptic weather reports from the "SPOT" archive of the Fleet Numerical Oceanography Center (FNOC) and from Release 1 of the Comprehensive Ocean-Atmosphere Data Set (COADS) for the years 1930-1979. The data are in 12 files (one containing latitude, longitude, land-fraction, and number of land stations for grid boxes; four containing total <span class="hlt">cloud</span>, <span class="hlt">cloud</span> <span class="hlt">types</span>, harmonic analyses, and interannual variations and trends for land; four containing total <span class="hlt">cloud</span>, <span class="hlt">cloud</span> <span class="hlt">types</span>, harmonic analyses, and interannual variations and trends for oceans; one containing first <span class="hlt">cloud</span> analyses for the first year of the GARP Global Experiment (FGGE); one containing <span class="hlt">cloud-type</span> co-occurrences for land and oceans; and one containing a FORTRAN program to read and produce maps).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/22270901-giant-molecular-cloud-formation-disk-galaxies-characterizing-simulated-versus-observed-cloud-catalogs','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/22270901-giant-molecular-cloud-formation-disk-galaxies-characterizing-simulated-versus-observed-cloud-catalogs"><span>GIANT MOLECULAR <span class="hlt">CLOUD</span> FORMATION IN DISK GALAXIES: CHARACTERIZING SIMULATED VERSUS OBSERVED <span class="hlt">CLOUD</span> CATALOGS</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Benincasa, Samantha M.; Pudritz, Ralph E.; Wadsley, James</p> <p></p> <p>We present the results of a study of simulated giant molecular <span class="hlt">clouds</span> (GMCs) formed in a Milky Way-<span class="hlt">type</span> galactic disk with a flat rotation curve. This simulation, which does not include star formation or feedback, produces <span class="hlt">clouds</span> with masses ranging between 10{sup 4} M{sub ☉} and 10{sup 7} M{sub ☉}. We compare our simulated <span class="hlt">cloud</span> population to two observational surveys: the Boston University-Five College Radio Astronomy Observatory Galactic Ring Survey and the BIMA All-Disk Survey of M33. An analysis of the global <span class="hlt">cloud</span> properties as well as a comparison of Larson's scaling relations is carried out. We find that simulatedmore » <span class="hlt">cloud</span> properties agree well with the observed <span class="hlt">cloud</span> properties, with the closest agreement occurring between the <span class="hlt">clouds</span> at comparable resolution in M33. Our <span class="hlt">clouds</span> are highly filamentary—a property that derives both from their formation due to gravitational instability in the sheared galactic environment, as well as to <span class="hlt">cloud-cloud</span> gravitational encounters. We also find that the rate at which potentially star-forming gas accumulates within dense regions—wherein n{sub thresh} ≥ 10{sup 4} cm{sup –3}—is 3% per 10 Myr, in <span class="hlt">clouds</span> of roughly 10{sup 6} M{sub ☉}. This suggests that star formation rates in observed <span class="hlt">clouds</span> are related to the rates at which gas can be accumulated into dense subregions within GMCs via filamentary flows. The most internally well-resolved <span class="hlt">clouds</span> are chosen for listing in a catalog of simulated GMCs—the first of its kind. The cataloged <span class="hlt">clouds</span> are available as an extracted data set from the global simulation.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JPRS...66..588S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JPRS...66..588S"><span>A <span class="hlt">cloud</span> mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús</p> <p>2011-09-01</p> <p>This study presents a novel <span class="hlt">cloud</span> masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and <span class="hlt">cloud</span> free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and <span class="hlt">cloud</span> free MODIS composites as reference images. The selected scenes included a wide range of <span class="hlt">cloud</span> <span class="hlt">types</span> and surface features. The resulting <span class="hlt">cloud</span> masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated <span class="hlt">cloud</span> masks and with the automatic <span class="hlt">cloud</span> cover assessment algorithm (ACCA). In general the results showed an agreement in detected <span class="hlt">clouds</span> higher than 95% for <span class="hlt">clouds</span> larger than 50 ha. The approach produced consistent results <span class="hlt">identifying</span> and mapping <span class="hlt">clouds</span> of different <span class="hlt">type</span> and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=NASA&pg=6&id=EJ887850','ERIC'); return false;" href="https://eric.ed.gov/?q=NASA&pg=6&id=EJ887850"><span>Teaching through Trade Books: <span class="hlt">Cloud</span> Watchers</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Morgan, Emily; Ansberry, Karen; Phillips-Birdsong, Colleen</p> <p>2010-01-01</p> <p>Weather is a topic in science that is applicable to our lives on an everyday basis. The weather often determines what we wear, where we go, and what we do. This month's column focuses on <span class="hlt">clouds</span> and the part they play in determining our weather. In the K-3 lesson, students learn about different <span class="hlt">cloud</span> <span class="hlt">types</span> and sculpt each <span class="hlt">type</span> out of shaving cream.…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33E0225S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33E0225S"><span>A comparison of measured radiances from AIRS and HIRS across different <span class="hlt">cloud</span> <span class="hlt">types</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schreier, M. M.; Kahn, B. H.; Staten, P.</p> <p>2015-12-01</p> <p>The observation of Earth's atmosphere with passive remote sensing instruments is ongoing for decades and resulting in a long-term global dataset. Two prominent examples are operational satellite platforms from the National Oceanic and Atmospheric Administration (NOAA) or research platforms like NASA's Earth Observing System (EOS). The observed spectral ranges of these observations are often similar among the different platforms, but have large differences when it comes to resolution, accuracy and quality control. Our approach is to combine different kinds of instruments at the pixel-scale to improve the characterization of infrared radiances. We focus on data from the High-resolution Infrared Radiation Sounder (HIRS) and compare the observations to radiances from the Atmospheric Infrared Sounder (AIRS) on Aqua. The high spectral resolution of AIRS is used to characterize and possibly recalibrate the observed radiances from HIRS. Our approach is unique in that we use additional information from other passive instruments on the same platforms including the Advanced Very High Resolution Radiometer (AVHRR) and the MODerate resolution Imaging Spectroradiometer (MODIS). We will present comparisons of radiances from HIRS and AIRS within different <span class="hlt">types</span> of <span class="hlt">clouds</span> that are determined from the imagers. In this way, we can analyze and select the most homogeneous conditions for radiance comparisons and a possible re-calibration of HIRS. We hope to achieve a <span class="hlt">cloud-type</span>-dependent calibration and quality control for HIRS, which can be extrapolated into the past via inter-calibration of the different HIRS instruments beyond the time of AIRS.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JPRS..138..193S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JPRS..138..193S"><span>A <span class="hlt">cloud</span> shadow detection method combined with <span class="hlt">cloud</span> height iteration and spectral analysis for Landsat 8 OLI data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying</p> <p>2018-04-01</p> <p>Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high <span class="hlt">cloud</span> detection precisions, but for the detection of <span class="hlt">cloud</span> shadows, it still faces great challenges. Geometry-based <span class="hlt">cloud</span> shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) <span class="hlt">cloud</span> shadow detection method is one of the most representative geometry-based methods that has been used for <span class="hlt">cloud</span> shadow detection with Landsat 8 OLI. However, the Fmask method estimates <span class="hlt">cloud</span> height employing fixed temperature rates, which are highly uncertain, and errors of large area <span class="hlt">cloud</span> shadow detection can be caused by errors in estimations of <span class="hlt">cloud</span> height. This article improves the geometry-based <span class="hlt">cloud</span> shadow detection method for Landsat OLI from the following two aspects. (1) <span class="hlt">Cloud</span> height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, <span class="hlt">cloud</span> shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine <span class="hlt">cloud</span> shadow location. This effectively avoids the <span class="hlt">cloud</span> shadow leakage caused by the error in the height determination of a <span class="hlt">cloud</span>. (2) Object-based and pixel spectral analyses are combined to detect <span class="hlt">cloud</span> shadows, which can realize <span class="hlt">cloud</span> shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the <span class="hlt">cloud</span> shadow and typical ground objects, the best <span class="hlt">cloud</span> shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of <span class="hlt">cloud</span> shadows produced by thin <span class="hlt">clouds</span>. Several <span class="hlt">cloud</span> shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can <span class="hlt">identify</span> <span class="hlt">cloud</span> shadows in different regions with correct</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017amos.confE..66B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017amos.confE..66B"><span>Looking Down Through the <span class="hlt">Clouds</span> – Optical Attenuation through Real-Time <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Burley, J.; Lazarewicz, A.; Dean, D.; Heath, N.</p> <p></p> <p>Detecting and <span class="hlt">identifying</span> nuclear explosions in the atmosphere and on the surface of the Earth is critical for the Air Force Technical Applications Center (AFTAC) treaty monitoring mission. Optical signals, from surface or atmospheric nuclear explosions detected by satellite sensors, are attenuated by the atmosphere and <span class="hlt">clouds</span>. <span class="hlt">Clouds</span> present a particularly complex challenge as they cover up to seventy percent of the earth's surface. Moreover, their highly variable and diverse nature requires physics-based modeling. Determining the attenuation for each optical ray-path is uniquely dependent on the source geolocation, the specific optical transmission characteristics along that ray path, and sensor detection capabilities. This research details a collaborative AFTAC and AFIT effort to fuse worldwide weather data, from a variety of sources, to provide near-real-time profiles of atmospheric and <span class="hlt">cloud</span> conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest from source to satellite. AFIT has developed a means to model global <span class="hlt">clouds</span> using the U.S. Air Force’s World Wide Merged <span class="hlt">Cloud</span> Analysis (WWMCA) <span class="hlt">cloud</span> data in a new toolset that enables radiance calculations through <span class="hlt">clouds</span> from UV to RF wavelengths.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19720045149&hterms=physics+levels&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dphysics%2Blevels','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19720045149&hterms=physics+levels&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dphysics%2Blevels"><span>Zero-gravity <span class="hlt">cloud</span> physics.</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hollinden, A. B.; Eaton, L. R.; Vaughan, W. W.</p> <p>1972-01-01</p> <p>The first results of an ongoing preliminary-concept and detailed-feasibility study of a zero-gravity earth-orbital <span class="hlt">cloud</span> physics research facility are reviewed. Current planning and thinking are being shaped by two major conclusions of this study: (1) there is a strong requirement for and it is feasible to achieve important and significant research in a zero-gravity <span class="hlt">cloud</span> physics facility; and (2) some very important experiments can be accomplished with 'off-the-shelf' <span class="hlt">type</span> hardware by astronauts who have no <span class="hlt">cloud</span>-physics background; the most complicated experiments may require sophisticated observation and motion subsystems and the astronaut may need graduate level <span class="hlt">cloud</span> physics training; there is a large number of experiments whose complexity varies between these two extremes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A11I1987K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A11I1987K"><span>Parameterization of Cirrus <span class="hlt">Cloud</span> Vertical Profiles and Geometrical Thickness Using CALIPSO and <span class="hlt">Cloud</span>Sat Data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Khatri, P.; Iwabuchi, H.; Saito, M.</p> <p>2017-12-01</p> <p>High-level cirrus <span class="hlt">clouds</span>, which normally occur over more than 20% of the globe, are known to have profound impacts on energy budget and climate change. The scientific knowledge regarding the vertical structure of such high-level cirrus <span class="hlt">clouds</span> and their geometrical thickness are relatively poorer compared to low-level water <span class="hlt">clouds</span>. Knowledge regarding <span class="hlt">cloud</span> vertical structure is especially important in passive remote sensing of <span class="hlt">cloud</span> properties using infrared channels or channels strongly influenced by gaseous absorption when <span class="hlt">clouds</span> are geometrically thick and optically thin. Such information is also very useful for validating <span class="hlt">cloud</span> resolving numerical models. This study analyzes global scale data of ice <span class="hlt">clouds</span> <span class="hlt">identified</span> by <span class="hlt">Cloud</span> profiling Radar (CPR) onboard <span class="hlt">Cloud</span>Sat and <span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO to parameterize (i) vertical profiles of ice water content (IWC), <span class="hlt">cloud</span>-particle effective radius (CER), and ice-particle number concentration for varying ice water path (IWP) values and (ii) the relation of <span class="hlt">cloud</span> geometrical thickness (CGT) with IWP and CER for varying <span class="hlt">cloud</span> top temperature (CTT) values. It is found that the maxima in IWC and CER profile shifts towards <span class="hlt">cloud</span> base with the increase of IWP. Similarly, if the <span class="hlt">cloud</span> properties remain same, CGT shows an increasing trend with the decrease of CTT. The implementation of such <span class="hlt">cloud</span> vertical inhomogeneity parameterization in the forward model used in the Integrated <span class="hlt">Cloud</span> Analysis System ICAS (Iwabuchi et al., 2016) generally shows increase of brightness temperatures in infrared channels compared to vertically homogeneous <span class="hlt">cloud</span> assumption. The <span class="hlt">cloud</span> vertical inhomogeneity is found to bring noticeable changes in retrieved <span class="hlt">cloud</span> properties. Retrieved CER and <span class="hlt">cloud</span> top height become larger for optically thick <span class="hlt">cloud</span>. We will show results of comparison of <span class="hlt">cloud</span> properties retrieved from infrared measurements and active remote sensing.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://files.eric.ed.gov/fulltext/ED148615.pdf','ERIC'); return false;" href="http://files.eric.ed.gov/fulltext/ED148615.pdf"><span>Spotter's Guide for <span class="hlt">Identifying</span> and Reporting Severe Local Storms.</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>National Oceanic and Atmospheric Administration (DOC), Rockville, MD.</p> <p></p> <p>This guide is designed to assist personnel working in the National Weather Service's Severe Local Storm Spotter Networks in <span class="hlt">identifying</span> and reporting severe local storms. Provided are pictures of <span class="hlt">cloud</span> <span class="hlt">types</span> for severe storms including tornadoes, hail, thunder, lightning, heavy rains, and waterspouts. Instructions for key indications to watch for…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017A%26A...607A..57R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017A%26A...607A..57R"><span>Using polarimetry to retrieve the <span class="hlt">cloud</span> coverage of Earth-like exoplanets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rossi, L.; Stam, D. M.</p> <p>2017-11-01</p> <p>Context. <span class="hlt">Clouds</span> have already been detected in exoplanetary atmospheres. They play crucial roles in a planet's atmosphere and climate and can also create ambiguities in the determination of atmospheric parameters such as trace gas mixing ratios. Knowledge of <span class="hlt">cloud</span> properties is required when assessing the habitability of a planet. Aims: We aim to show that various <span class="hlt">types</span> of <span class="hlt">cloud</span> cover such as polar cusps, subsolar <span class="hlt">clouds</span>, and patchy <span class="hlt">clouds</span> on Earth-like exoplanets can be distinguished from each other using the polarization and flux of light that is reflected by the planet. Methods: We have computed the flux and polarization of reflected starlight for different <span class="hlt">types</span> of (liquid water) <span class="hlt">cloud</span> covers on Earth-like model planets using the adding-doubling method, that fully includes multiple scattering and polarization. Variations in <span class="hlt">cloud</span>-top altitudes and planet-wide <span class="hlt">cloud</span> cover percentages were taken into account. Results: We find that the different <span class="hlt">types</span> of <span class="hlt">cloud</span> cover (polar cusps, subsolar <span class="hlt">clouds</span>, and patchy <span class="hlt">clouds</span>) can be distinguished from each other and that the percentage of <span class="hlt">cloud</span> cover can be estimated within 10%. Conclusions: Using our proposed observational strategy, one should be able to determine basic orbital parameters of a planet such as orbital inclination and estimate <span class="hlt">cloud</span> coverage with reduced ambiguities from the planet's polarization signals along its orbit.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1993PhDT........42G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1993PhDT........42G"><span>The wavelet transform as an analysis tool for structure identification in molecular <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gill, Arnold Gerald</p> <p>1993-01-01</p> <p>Of the many methods used to attempt to understand the complex structure of giant molecular <span class="hlt">clouds</span>, perhaps the most commonly used are the autocorrelation functions (ACF), the structure function, and the power spectrum. However, these do not give unique interpretations of structure, as is shown by explicit examples compared to the Taurus Molecular Complex. Thus, another, independent method of analysis is indicated. Here, the wavelet transform is presented, a relatively new technique less than 10 years old. It can be thought of as a band-pass filter that <span class="hlt">identifies</span> structures of specific sizes. In addition, its mathematical properties allow it to be used to <span class="hlt">identify</span> fractal structures and accurately <span class="hlt">identify</span> the scaling exponent. This is shown by the wavelet transform <span class="hlt">identifying</span> the fractal dimension of a hierarchical rain <span class="hlt">cloud</span> model first proposed by Frisch et al. (1978). A wavelet analysis is then carried out for a range of astronomical CO data, including the <span class="hlt">clouds</span> Orion A and B and NGC 7538 (in (12)CO) and Orion A and B, Mon R2, and L1551 (in (13)CO). The data analyzed consists of the velocities of the fitted Gaussians to the individual spectra, the halfwidths and amplitude of these Gaussians, and the total area of the spectral line. For most of the <span class="hlt">clouds</span> investigated, each of these data <span class="hlt">types</span> showed a very high degree of scaling coherence over a wide range of scales, from down at the beam spacing up to the full size of the <span class="hlt">cloud</span>. The analysis carried out uses both the scaling and structure identification strengths of the wavelet transform The fragmentation parameters used by Scalo (1985) and the parameters of the geometric molecular <span class="hlt">cloud</span> description introduced by Henriksen (1986) are calculated for each <span class="hlt">cloud</span>. These results are all consistent with previous observations of these and other molecular <span class="hlt">clouds</span>, though they are obtained individually for each <span class="hlt">cloud</span> investigated. It is found that the uncertainties are of a magnitude that the differentiation of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19720023965','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19720023965"><span>Further developments in <span class="hlt">cloud</span> statistics for computer simulations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chang, D. T.; Willand, J. H.</p> <p>1972-01-01</p> <p>This study is a part of NASA's continued program to provide global statistics of <span class="hlt">cloud</span> parameters for computer simulation. The primary emphasis was on the development of the data bank of the global statistical distributions of <span class="hlt">cloud</span> <span class="hlt">types</span> and <span class="hlt">cloud</span> layers and their applications in the simulation of the vertical distributions of in-<span class="hlt">cloud</span> parameters such as liquid water content. These statistics were compiled from actual surface observations as recorded in Standard WBAN forms. Data for a total of 19 stations were obtained and reduced. These stations were selected to be representative of the 19 primary <span class="hlt">cloud</span> climatological regions defined in previous studies of <span class="hlt">cloud</span> statistics. Using the data compiled in this study, a limited study was conducted of the hemogeneity of <span class="hlt">cloud</span> regions, the latitudinal dependence of <span class="hlt">cloud-type</span> distributions, the dependence of these statistics on sample size, and other factors in the statistics which are of significance to the problem of simulation. The application of the statistics in <span class="hlt">cloud</span> simulation was investigated. In particular, the inclusion of the new statistics in an expanded multi-step Monte Carlo simulation scheme is suggested and briefly outlined.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007MAP....96..141D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007MAP....96..141D"><span><span class="hlt">Cloud</span> cover analysis associated to cut-off low-pressure systems over Europe using Meteosat Imagery</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Delgado, G.; Redaño, A.; Lorente, J.; Nieto, R.; Gimeno, L.; Ribera, P.; Barriopedro, D.; García-Herrera, R.; Serrano, A.</p> <p>2007-04-01</p> <p>This paper reports a <span class="hlt">cloud</span> cover analysis of cut-off low pressure systems (COL) using a pattern recognition method applied to IR and VIS bispectral histograms. 35 COL occurrences were studied over five years (1994-1998). Five <span class="hlt">cloud</span> <span class="hlt">types</span> were <span class="hlt">identified</span> in COLs, of which high <span class="hlt">clouds</span> (HCC) and deep convective <span class="hlt">clouds</span> (DCC) were found to be the most relevant to characterize COL systems, though not the most numerous. <span class="hlt">Cloud</span> cover in a COL is highly dependent on its stage of development, but a higher percentage of <span class="hlt">cloud</span> cover is always present in the frontal zone, attributable due to higher amounts of high and deep convective <span class="hlt">clouds</span>. These general characteristics are most marked during the first stage (when the amplitude of the geopotencial wave increases) and second stage (characterized by the development of a cold upper level low), closed cyclonic circulation minimizing differences between rearward and frontal zones during the third stage. The probability of heavy rains during this stage decreases considerably. The centres of mass of high and deep convective <span class="hlt">clouds</span> move towards the COL-axis centre during COL evolution.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_6");'>6</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li class="active"><span>8</span></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_8 --> <div id="page_9" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="161"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19900003687','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900003687"><span><span class="hlt">Cloud</span> cover determination in polar regions from satellite imagery</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barry, R. G.; Key, J.</p> <p>1989-01-01</p> <p>The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite <span class="hlt">Cloud</span> Climatology Project (ISCCP) algorithm for <span class="hlt">cloud</span> retrieval in polar regions, to <span class="hlt">identify</span> limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic <span class="hlt">cloud</span> data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar <span class="hlt">clouds</span> and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for <span class="hlt">cloud</span> detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface <span class="hlt">types</span> with passive microwave, then temporal tests at each pixel location in the <span class="hlt">cloud</span> detection phase. <span class="hlt">Cloud</span> maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of <span class="hlt">cloud</span> pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of <span class="hlt">cloud</span> patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic <span class="hlt">cloud</span> cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002AAS...20111206L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002AAS...20111206L"><span>Variation of z-height of the molecular <span class="hlt">clouds</span> on the Galactic Plane</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, Y.; Stark, A. A.</p> <p>2002-12-01</p> <p>Using the Bell Laboratories Galactic plane in the J=1-0 transition of 13CO, (l, b) = (-5o to 117o, -1o to +1o), and <span class="hlt">cloud</span> identification code, 13CO <span class="hlt">clouds</span> have been <span class="hlt">identified</span> and cataloged as a function of threshold temperature. Distance estimates to the <span class="hlt">identified</span> <span class="hlt">clouds</span> have been made with several criteria. Minimum and maximum distances to each <span class="hlt">identified</span> <span class="hlt">cloud</span> are determined from a set of all the possible distances of a <span class="hlt">cloud</span>. Several physical parameters can be determined with distances, such as z-height [D sin (b)], CO luminosity, virial mass and so forth. We select the <span class="hlt">clouds</span> with a ratio of maximum and minimum of CO luminosities less than 3. The number of selected <span class="hlt">clouds</span> is 281 out of 1400 <span class="hlt">identified</span> <span class="hlt">clouds</span> with 1 K threshold temperature. These <span class="hlt">clouds</span> are mostly located on the tangential positions in the inner Galaxy, and some are in the Outer Galaxy. It is found that the z-height of lower luminosity <span class="hlt">clouds</span> (less massive <span class="hlt">clouds</span>) is systimatically larger than that of high-luminosity <span class="hlt">clouds</span> (more massive <span class="hlt">clouds</span>). We claim that this is the first observational evidence of the z-height variation depending on the luminosities (or masses) of molecular <span class="hlt">clouds</span> on the Galactic plane. Our results could be a basis explaining the formation mechanism of massive <span class="hlt">clouds</span>, such as giant molecular <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002120.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002120.html"><span>Wave <span class="hlt">Clouds</span> over Ireland</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>Visualization Date 2003-12-18 <span class="hlt">Clouds</span> ripple over Ireland and Scotland in a wave pattern, similar to the pattern of waves along a seashore. The similarity is not coincidental — the atmosphere behaves like a fluid, so when it encounters an obstacle, it must move around it. This movement forms a wave, and the wave movement can continue for long distances. In this case, the waves were caused by the air moving over and around the mountains of Scotland and Ireland. As the air crested a wave, it cooled, and <span class="hlt">clouds</span> formed. Then, as the air sank into the trough, the air warmed, and <span class="hlt">clouds</span> did not form. This pattern repeated itself, with <span class="hlt">clouds</span> appearing at the peak of every wave. Other <span class="hlt">types</span> of <span class="hlt">clouds</span> are also visible in the scene. Along the northwestern and southwestern edges of this true-color image from December 17, 2003, are normal mid-altitude <span class="hlt">clouds</span> with fairly uniform appearances. High altitude cirrus-<span class="hlt">clouds</span> float over these, casting their shadows on the lower <span class="hlt">clouds</span>. Open- and closed-cell <span class="hlt">clouds</span> formed off the coast of northwestern France, and thin contrail <span class="hlt">clouds</span> are visible just east of these. Contrail <span class="hlt">clouds</span> form around the particles carried in airplane exhaust. Fog is also visible in the valleys east of the Cambrian Mountains, along the border between northern/central Wales and England. This is an Aqua MODIS image. Sensor Aqua/MODIS Credit Jacques Descloitres, MODIS Rapid Response Team, NASA/GSFC For more information go to: visibleearth.nasa.gov/view_rec.php?id=6146</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PASJ...70S..59K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PASJ...70S..59K"><span>Star formation induced by <span class="hlt">cloud-cloud</span> collisions and galactic giant molecular <span class="hlt">cloud</span> evolution</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kobayashi, Masato I. N.; Kobayashi, Hiroshi; Inutsuka, Shu-ichiro; Fukui, Yasuo</p> <p>2018-05-01</p> <p>Recent millimeter/submillimeter observations towards nearby galaxies have started to map the whole disk and to <span class="hlt">identify</span> giant molecular <span class="hlt">clouds</span> (GMCs) even in the regions between galactic spiral structures. Observed variations of GMC mass functions in different galactic environments indicates that massive GMCs preferentially reside along galactic spiral structures whereas inter-arm regions have many small GMCs. Based on the phase transition dynamics from magnetized warm neutral medium to molecular <span class="hlt">clouds</span>, Kobayashi et al. (2017, ApJ, 836, 175) proposes a semi-analytical evolutionary description for GMC mass functions including a <span class="hlt">cloud-cloud</span> collision (CCC) process. Their results show that CCC is less dominant in shaping the mass function of GMCs than the accretion of dense H I gas driven by the propagation of supersonic shock waves. However, their formulation does not take into account the possible enhancement of star formation by CCC. Millimeter/submillimeter observations within the Milky Way indicate the importance of CCC in the formation of star clusters and massive stars. In this article, we reformulate the time-evolution equation largely modified from Kobayashi et al. (2017, ApJ, 836, 175) so that we additionally compute star formation subsequently taking place in CCC <span class="hlt">clouds</span>. Our results suggest that, although CCC events between smaller <span class="hlt">clouds</span> are more frequent than the ones between massive GMCs, CCC-driven star formation is mostly driven by massive GMCs ≳ 10^{5.5} M_{⊙} (where M⊙ is the solar mass). The resultant cumulative CCC-driven star formation may amount to a few 10 percent of the total star formation in the Milky Way and nearby galaxies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ACP....18.3065J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ACP....18.3065J"><span>Contrasting the co-variability of daytime <span class="hlt">cloud</span> and precipitation over tropical land and ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jin, Daeho; Oreopoulos, Lazaros; Lee, Dongmin; Cho, Nayeong; Tan, Jackson</p> <p>2018-03-01</p> <p>The co-variability of <span class="hlt">cloud</span> and precipitation in the extended tropics (35° N-35° S) is investigated using contemporaneous data sets for a 13-year period. The goal is to quantify potential relationships between <span class="hlt">cloud</span> <span class="hlt">type</span> fractions and precipitation events of particular strength. Particular attention is paid to whether the relationships exhibit different characteristics over tropical land and ocean. A primary analysis metric is the correlation coefficient between fractions of individual <span class="hlt">cloud</span> <span class="hlt">types</span> and frequencies within precipitation histogram bins that have been matched in time and space. The <span class="hlt">cloud</span> <span class="hlt">type</span> fractions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS) joint histograms of <span class="hlt">cloud</span> top pressure and <span class="hlt">cloud</span> optical thickness in 1° grid cells, and the precipitation frequencies come from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) data set aggregated to the same grid.<p class="p">It is found that the strongest coupling (positive correlation) between <span class="hlt">clouds</span> and precipitation occurs over ocean for cumulonimbus <span class="hlt">clouds</span> and the heaviest rainfall. While the same <span class="hlt">cloud</span> <span class="hlt">type</span> and rainfall bin are also best correlated over land compared to other combinations, the correlation magnitude is weaker than over ocean. The difference is attributed to the greater size of convective systems over ocean. It is also found that both over ocean and land the anti-correlation of strong precipitation with <q>weak</q> (i.e., thin and/or low) <span class="hlt">cloud</span> <span class="hlt">types</span> is of greater absolute strength than positive correlations between weak <span class="hlt">cloud</span> <span class="hlt">types</span> and weak precipitation. <span class="hlt">Cloud</span> <span class="hlt">type</span> co-occurrence relationships explain some of the <span class="hlt">cloud</span>-precipitation anti-correlations. Weak correlations between weaker rainfall and <span class="hlt">clouds</span> indicate poor predictability for precipitation when <span class="hlt">cloud</span> <span class="hlt">types</span> are known, and this is even more true over land than over ocean.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018Ap%26SS.363..151N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018Ap%26SS.363..151N"><span>Chemical evolution of the gas in C-<span class="hlt">type</span> shocks in dark <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nesterenok, A. V.</p> <p>2018-07-01</p> <p>A magnetohydrodynamic model of a steady, transverse C-<span class="hlt">type</span> shock in a dense molecular <span class="hlt">cloud</span> is presented. A complete gas-grain chemical network is taken into account: the gas-phase chemistry, the adsorption of gas species on dust grains, various desorption mechanisms, the grain surface chemistry, the ion neutralization on dust grains, the sputtering of grain mantles. The population densities of energy levels of ions CI, CII and OI and molecules H2, CO, H2O are computed in parallel with the dynamical and chemical rate equations. The large velocity gradient approximation is used in the line radiative transfer calculations. The simulations consist of two steps: (i) modelling of the chemical and thermal evolution of a static molecular <span class="hlt">cloud</span> and (ii) shock simulations. A comparison is made with the results of publicly available models of similar physical systems. The focus of the paper is on the chemical processing of gas material and ice mantles of dust grains by the shock. Sputtering of ice mantles takes place in the shock region close to the temperature peak of the neutral gas. At high shock speeds, molecules ejected from ice mantles are effectively destroyed in hot gas, and their survival time is low—of the order of dozens of years. After a passage of high-speed C-<span class="hlt">type</span> shock, a zone of high abundance of atomic hydrogen appears in the cooling postshock gas that triggers formation of complex organic species such as methanol. It is shown that abundances of some complex organic molecules (COMs) in the postshock region can be much higher than in the preshock gas. These results are important for interpretation of observations of COMs in protostellar outflows.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015MNRAS.446.3034R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015MNRAS.446.3034R"><span>The VMC Survey - XIII. <span class="hlt">Type</span> II Cepheids in the Large Magellanic <span class="hlt">Cloud</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ripepi, V.; Moretti, M. I.; Marconi, M.; Clementini, G.; Cioni, M.-R. L.; de Grijs, R.; Emerson, J. P.; Groenewegen, M. A. T.; Ivanov, V. D.; Muraveva, T.; Piatti, A. E.; Subramanian, S.</p> <p>2015-01-01</p> <p>The VISTA (Visible and Infrared Survey Telescope for Astronomy) survey of the Magellanic <span class="hlt">Clouds</span> System (VMC) is collecting deep Ks-band time-series photometry of the pulsating variable stars hosted in the system formed by the two Magellanic <span class="hlt">Clouds</span> and the Bridge connecting them. In this paper, we have analysed a sample of 130 Large Magellanic <span class="hlt">Cloud</span> (LMC) <span class="hlt">Type</span> II Cepheids (T2CEPs) found in tiles with complete or near-complete VMC observations for which identification and optical magnitudes were obtained from the OGLE III (Optical Gravitational Lensing Experiment) survey. We present J and Ks light curves for all 130 pulsators, including 41 BL Her, 62 W Vir (12 pW Vir) and 27 RV Tau variables. We complement our near-infrared photometry with the V magnitudes from the OGLE III survey, allowing us to build a variety of period-luminosity (PL), period-luminosity-colour (PLC) and period-Wesenheit (PW) relationships, including any combination of the V, J, Ks filters and valid for BL Her and W Vir classes. These relationships were calibrated in terms of the LMC distance modulus, while an independent absolute calibration of the PL(Ks) and the PW(Ks, V) was derived on the basis of distances obtained from Hubble Space Telescope parallaxes and Baade-Wesselink technique. When applied to the LMC and to the Galactic globular clusters hosting T2CEPs, these relations seem to show that (1) the two Population II standard candles RR Lyrae and T2CEPs give results in excellent agreement with each other; (2) there is a discrepancy of ˜0.1 mag between Population II standard candles and classical Cepheids when the distances are gauged in a similar way for all the quoted pulsators. However, given the uncertainties, this discrepancy is within the formal 1σ uncertainties.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20180000851','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20180000851"><span>Global Measurements of Optically Thin Ice <span class="hlt">Clouds</span> Using CALIOP</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ryan, R.; Avery, M.; Tackett, J.</p> <p>2017-01-01</p> <p>Optically thin ice <span class="hlt">clouds</span> have been shown to have a net warming effect on the globe but, because passive instruments are not sensitive to optically thin <span class="hlt">clouds</span>, the occurrence frequency of this class of <span class="hlt">clouds</span> is greatly underestimated in historical passive sensor <span class="hlt">cloud</span> climatology. One major strength of CALIOP (<span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization), onboard the CALIPSO (<span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spacecraft, is its ability to detect these thin <span class="hlt">clouds</span>, thus filling an important missing piece in the historical data record. This poster examines the full mission of CALIPSO Level 2 data, focusing on those CALIOP retrievals <span class="hlt">identified</span> as thin ice <span class="hlt">clouds</span> according to the definition shown to the right. Using this definition, thin ice <span class="hlt">clouds</span> are <span class="hlt">identified</span> and counted globally and vertically for each season. By examining the spatial and seasonal distributions of these thin <span class="hlt">clouds</span> we hope to gain a better understanding these thin ice <span class="hlt">clouds</span> and how their global distribution has changed over the mission. This poster showcases when and where CALIOP detects thin ice <span class="hlt">clouds</span> and examines a case study of the eastern pacific and the effects seen from the El Nino-Southern Oscillation (ENSO).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017APS..DFDQ15002S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017APS..DFDQ15002S"><span><span class="hlt">Cloud</span> regimes as phase transitions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stechmann, Samuel; Hottovy, Scott</p> <p>2017-11-01</p> <p><span class="hlt">Clouds</span> are repeatedly <span class="hlt">identified</span> as a leading source of uncertainty in future climate predictions. Of particular importance are stratocumulus <span class="hlt">clouds</span>, which can appear as either (i) closed cells that reflect solar radiation back to space or (ii) open cells that allow solar radiation to reach the Earth's surface. Here we show that these <span class="hlt">clouds</span> regimes - open versus closed cells - fit the paradigm of a phase transition. In addition, this paradigm characterizes pockets of open cells (POCs) as the interface between the open- and closed-cell regimes, and it <span class="hlt">identifies</span> shallow cumulus <span class="hlt">clouds</span> as a regime of higher variability. This behavior can be understood using an idealized model for the dynamics of atmospheric water as a stochastic diffusion process. Similar viewpoints of deep convection and self-organized criticality will also be discussed. With these new conceptual viewpoints, ideas from statistical mechanics could potentially be used for understanding uncertainties related to <span class="hlt">clouds</span> in the climate system and climate predictions. The research of S.N.S. is partially supported by a Sloan Research Fellowship, ONR Young Investigator Award N00014-12-1-0744, and ONR MURI Grant N00014-12-1-0912.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931..583S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931..583S"><span><span class="hlt">Cloud</span> Infrastructure & Applications - <span class="hlt">Cloud</span>IA</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank</p> <p></p> <p>The idea behind <span class="hlt">Cloud</span> Computing is to deliver Infrastructure-as-a-Services and Software-as-a-Service over the Internet on an easy pay-per-use business model. To harness the potentials of <span class="hlt">Cloud</span> Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called <span class="hlt">Cloud</span> Infrastructure & Applications (<span class="hlt">Cloud</span>IA). The <span class="hlt">Cloud</span>IA project is a market-oriented <span class="hlt">cloud</span> infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the <span class="hlt">Cloud</span>IA project in details and mentions our early experiences in building a private <span class="hlt">cloud</span> using an existing infrastructure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1132199-constructing-merged-cloud-precipitation-radar-dataset-tropical-convective-clouds-during-dynamo-amie-experiment-addu-atoll','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1132199-constructing-merged-cloud-precipitation-radar-dataset-tropical-convective-clouds-during-dynamo-amie-experiment-addu-atoll"><span>Constructing a Merged <span class="hlt">Cloud</span>-Precipitation Radar Dataset for Tropical Convective <span class="hlt">Clouds</span> during the DYNAMO/AMIE Experiment at Addu Atoll</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Feng, Zhe; McFarlane, Sally A.; Schumacher, Courtney</p> <p>2014-05-16</p> <p>To improve understanding of the convective processes key to the Madden-Julian-Oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and Atmospheric Radiation Measurement MJO Investigation Experiment (AMIE) collected four months of observations from three radars, the S-band Polarization Radar (S-Pol), the C-band Shared Mobile Atmospheric Research & Teaching Radar (SMART-R), and Ka-band Zenith Radar (KAZR) on Addu Atoll in the tropical Indian Ocean. This study compares the measurements from the S-Pol and SMART-R to those from the more sensitive KAZR in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars. Frequency comparisons for precipitating convective cloudsmore » and non-precipitating high <span class="hlt">clouds</span> agree much better than non-precipitating low <span class="hlt">clouds</span> for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high <span class="hlt">cloud</span> tops by 0.3 to 1.1 km, while S-Pol underestimates <span class="hlt">cloud</span> tops by less than 0.4 km for these <span class="hlt">cloud</span> <span class="hlt">types</span>. S-Pol shows excellent dynamic range in detecting various <span class="hlt">types</span> of <span class="hlt">clouds</span> and therefore its data are well suited for characterizing the evolution of the 3D <span class="hlt">cloud</span> structures, complementing the profiling KAZR measurements. For detecting non-precipitating low <span class="hlt">clouds</span> and thin cirrus <span class="hlt">clouds</span>, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates <span class="hlt">cloud</span> top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR <span class="hlt">cloud</span> top heights is described, and a merged radar dataset is produced to provide improved <span class="hlt">cloud</span> boundary estimates, microphysics and radiative heating retrievals.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AtmRe.183...73D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AtmRe.183...73D"><span><span class="hlt">Clouds</span> vertical properties over the Northern Hemisphere monsoon regions from <span class="hlt">Cloud</span>Sat-CALIPSO measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Das, Subrata Kumar; Golhait, R. B.; Uma, K. N.</p> <p>2017-01-01</p> <p>The <span class="hlt">Cloud</span>Sat spaceborne radar and <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) space-borne lidar measurements, provide opportunities to understand the intriguing behavior of the vertical structure of monsoon <span class="hlt">clouds</span>. The combined <span class="hlt">Cloud</span>Sat-CALIPSO data products have been used for the summer season (June-August) of 2006-2010 to present the statistics of <span class="hlt">cloud</span> macrophysical (such as <span class="hlt">cloud</span> occurrence frequency, distribution of <span class="hlt">cloud</span> top and base heights, geometrical thickness and <span class="hlt">cloud</span> <span class="hlt">types</span> base on occurrence height), and microphysical (such as ice water content, ice water path, and ice effective radius) properties of the Northern Hemisphere (NH) monsoon region. The monsoon regions considered in this work are the North American (NAM), North African (NAF), Indian (IND), East Asian (EAS), and Western North Pacific (WNP). The total <span class="hlt">cloud</span> fraction over the IND (mostly multiple-layered <span class="hlt">cloud</span>) appeared to be more frequent as compared to the other monsoon regions. Three distinctive modes of <span class="hlt">cloud</span> top height distribution are observed over all the monsoon regions. The high-level <span class="hlt">cloud</span> fraction is comparatively high over the WNP and IND. The ice water content and ice water path over the IND are maximum compared to the other monsoon regions. We found that the ice water content has little variations over the NAM, NAF, IND, and WNP as compared to their macrophysical properties and thus give an impression that the regional differences in dynamics and thermodynamics properties primarily cause changes in the <span class="hlt">cloud</span> frequency or coverage and only secondary in the <span class="hlt">cloud</span> ice properties. The background atmospheric dynamics using wind and relative humidity from the ERA-Interim reanalysis data have also been investigated which helps in understanding the variability of the <span class="hlt">cloud</span> properties over the different monsoon regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.5988L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.5988L"><span>Tropical <span class="hlt">cloud</span> and precipitation regimes as seen from near-simultaneous TRMM, <span class="hlt">Cloud</span>Sat, and CALIPSO observations and comparison with ISCCP</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Luo, Zhengzhao Johnny; Anderson, Ricardo C.; Rossow, William B.; Takahashi, Hanii</p> <p>2017-06-01</p> <p>Although Tropical Rainfall Measuring Mission (TRMM) and <span class="hlt">Cloud</span>Sat/CALIPSO fly in different orbits, they frequently cross each other so that for the period between 2006 and 2010, a total of 15,986 intersect lines occurred within 20 min of each other from 30°S to 30°N, providing a rare opportunity to study tropical <span class="hlt">cloud</span> and precipitation regimes and their internal vertical structure from near-simultaneous measurements by these active sensors. A k-means cluster analysis of TRMM and <span class="hlt">Cloud</span>Sat matchups <span class="hlt">identifies</span> three tropical <span class="hlt">cloud</span> and precipitation regimes: the first two regimes correspond to, respectively, organized deep convection with heavy rain and cirrus anvils with moderate rain; the third regime is a convectively suppressed regime that can be further divided into three subregimes, which correspond to, respectively, stratocumulus <span class="hlt">clouds</span> with drizzle, cirrus overlying low <span class="hlt">clouds</span>, and nonprecipitating cumulus. Inclusion of CALIPSO data adds to the dynamic range of <span class="hlt">cloud</span> properties and <span class="hlt">identifies</span> one more cluster; subcluster analysis further <span class="hlt">identifies</span> a thin, midlevel <span class="hlt">cloud</span> regime associated with tropical mountain ranges. The radar-lidar <span class="hlt">cloud</span> regimes are compared with the International Satellite <span class="hlt">Cloud</span> Climatology Project (ISCCP) weather states (WSs) for the extended tropics. Focus is placed on the four convectively active WSs, namely, WS1-WS4. ISCCP WS1 and WS2 are found to be counterparts of Regime 1 and Regime 2 in radar-lidar observations, respectively. ISCCP WS3 and WS4, which are mainly isolated convection and broken, detached cirrus, do not have a strong association with any individual radar and lidar regimes, a likely effect of the different sampling strategies between ISCCP and active sensors and patchy cloudiness of these WSs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045760&hterms=Avion&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DAvion','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045760&hterms=Avion&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3DAvion"><span><span class="hlt">Cloud</span> layer thicknesses from a combination of surface and upper-air observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Poore, Kirk D.; Wang, Junhong; Rossow, William B.</p> <p>1995-01-01</p> <p><span class="hlt">Cloud</span> layer thicknesses are derived from base and top altitudes by combining 14 years (1975-1988) of surface and upper-air observations at 63 sites in the Northern Hemisphere. Rawinsonde observations are employed to determine the locations of <span class="hlt">cloud</span>-layer top and base by testing for dewpoint temperature depressions below some threshold value. Surface observations serve as quality checks on the rawinsonde-determined <span class="hlt">cloud</span> properties and provide <span class="hlt">cloud</span> amount and <span class="hlt">cloud-type</span> information. The dataset provides layer-<span class="hlt">cloud</span> amount, <span class="hlt">cloud</span> <span class="hlt">type</span>, high, middle, or low height classes, <span class="hlt">cloud</span>-top heights, base heights and layer thicknesses, covering a range of latitudes from 0 deg to 80 deg N. All data comes from land sites: 34 are located in continental interiors, 14 are near coasts, and 15 are on islands. The uncertainties in the derived <span class="hlt">cloud</span> properties are discussed. For <span class="hlt">clouds</span> classified by low-, mid-, and high-top altitudes, there are strong latitudinal and seasonal variations in the layer thickness only for high <span class="hlt">clouds</span>. High-<span class="hlt">cloud</span> layer thickness increases with latitude and exhibits different seasonal variations in different latitude zones: in summer, high-<span class="hlt">cloud</span> layer thickness is a maximum in the Tropics but a minimum at high latitudes. For <span class="hlt">clouds</span> classified into three <span class="hlt">types</span> by base altitude or into six standard morphological <span class="hlt">types</span>, latitudinal and seasonal variations in layer thickness are very small. The thickness of the clear surface layer decreases with latitude and reaches a summer minimum in the Tropics and summer maximum at higher latitudes over land, but does not vary much over the ocean. Tropical <span class="hlt">clouds</span> occur in three base-altitude groups and the layer thickness of each group increases linearly with top altitude. Extratropical <span class="hlt">clouds</span> exhibit two groups, one with layer thickness proportional to their <span class="hlt">cloud</span>-top altitude and one with small (less than or equal to 1000 m) layer thickness independent of <span class="hlt">cloud</span>-top altitude.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040033935&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsimulation%2Bprocesses','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040033935&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dsimulation%2Bprocesses"><span>The Impact of Aerosols on <span class="hlt">Cloud</span> and Precipitation Processes: <span class="hlt">Cloud</span>-Resolving Model Simulations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tao, Wei-Kuo; Khain, A.; Simpson, S.; Johnson, D.; Li, X.; Remer, L.</p> <p>2003-01-01</p> <p><span class="hlt">Cloud</span> microphysics are inevitable affected by the smoke particle (CCN, <span class="hlt">cloud</span> condensation nuclei) size distributions below the <span class="hlt">clouds</span>. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on <span class="hlt">cloud</span> development, rainfall production, and rainfall rates convective <span class="hlt">clouds</span>. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., <span class="hlt">cloud</span> droplets and raindrops), and several <span class="hlt">types</span> of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each <span class="hlt">type</span> is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep <span class="hlt">cloud</span> systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less <span class="hlt">cloud</span> water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20030022687&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsimulation%2Bprocesses','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20030022687&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dsimulation%2Bprocesses"><span>The Impact of Aerosols on <span class="hlt">Cloud</span> and Precipitation Processes: <span class="hlt">Cloud</span>-Resolving Model Simulations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tao, Wei-Kuo; Khain, A.; Simpson, S.; Johnson, D.; Li, X.; Remer, L.</p> <p>2003-01-01</p> <p><span class="hlt">Cloud</span> microphysics are inevitably affected by the smoke particle (CCN, <span class="hlt">cloud</span> condensation nuclei) size distributions below the <span class="hlt">clouds</span>. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on <span class="hlt">cloud</span> development, rainfall production, and rainfall rates for convective <span class="hlt">clouds</span>. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., <span class="hlt">cloud</span> droplets and raindrops), and several <span class="hlt">types</span> of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each <span class="hlt">type</span> is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical <span class="hlt">clouds</span> in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less <span class="hlt">cloud</span> water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040090472','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040090472"><span>Evidence for Natural Variability in Marine Stratocumulus <span class="hlt">Cloud</span> Properties Due to <span class="hlt">Cloud</span>-Aerosol</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Albrecht, Bruce; Sharon, Tarah; Jonsson, Haf; Minnis, Patrick; Minnis, Patrick; Ayers, J. Kirk; Khaiyer, Mandana M.</p> <p>2004-01-01</p> <p>In this study, aircraft observations from the Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter are used to characterize the variability in drizzle, <span class="hlt">cloud</span>, and aerosol properties associated with <span class="hlt">cloud</span> rifts and the surrounding solid <span class="hlt">clouds</span> observed off the coast of California. A flight made on 16 July 1999 provided measurements directly across an interface between solid and rift <span class="hlt">cloud</span> conditions. Aircraft instrumentation allowed for measurements of aerosol, <span class="hlt">cloud</span> droplet, and drizzle spectra. CCN concentrations were measured in addition to standard thermodynamic variables and the winds. A Forward Scatter Spectrometer Probe (FSSP) measured size distribution of <span class="hlt">cloud</span>-sized droplets. A <span class="hlt">Cloud</span> Imaging Probe (CIP) was used to measure distributions of drizzle-sized droplets. Aerosol distributions were obtained from a <span class="hlt">Cloud</span> Aerosol Scatterprobe (CAS). The CAS probe measured aerosols, <span class="hlt">cloud</span> droplets and drizzle-sized drops; for this study. The CAS probe was used to measure aerosols in the size range of 0.5 micron - 1 micron. Smaller aerosols were characterized using an Ultrafine Condensation Particle Counter (CPC) sensor. The CPC was used to measure particles with diameters greater than 0.003 micron. By subtracting different count concentrations measured with the CPC, this probe was capable of <span class="hlt">identifying</span> ultrafine particles those falling in the size range of 3 nanometers - 7 nanometers that are believed to be associated with new particle production.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19820038370&hterms=early+laws&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dearly%2Blaws','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19820038370&hterms=early+laws&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dearly%2Blaws"><span>R associations. VI - The reddening law in dust <span class="hlt">clouds</span> and the nature of early-<span class="hlt">type</span> emission stars in nebulosity from a study of five associations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Herbst, W.; Warner, J. W.; Miller, D. P.; Herzog, A.</p> <p>1982-01-01</p> <p>Positions, identification charts, UBVRIKLMN photometry and spectral <span class="hlt">types</span> are given for stars, illuminating reflection nebulae that are visible on the POSS prints, which have been <span class="hlt">identified</span> in five associations. With a ratio of total to selective extinction of 4.2, the reddening law applicable to the dust <span class="hlt">clouds</span> in which the stars are embedded is steeper than normal. The five associations exhibit 18 early-<span class="hlt">type</span> stars with circumstellar shells, of which those with spectral <span class="hlt">types</span> earlier than B5 characteristically have weak IR excesses, in contrast to the strong excesses indicative of circumstellar dust, of later-<span class="hlt">type</span> stars. Color-magnitude charts show a distribution lying above the ZAMS by up to about 2 mag for both the circumstellar shell stars and those classified as rapid rotators. It is suggested that (1) rapid rotation accounts for the scatter in the color-magnitude diagram, and (2) many of the nebulous early-<span class="hlt">type</span> emission-line stars are rapid rotators rather than pre-main sequence objects.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A14B..07N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A14B..07N"><span>Entrainment and <span class="hlt">cloud</span> evaporation deduced from the stable isotope chemistry of <span class="hlt">clouds</span> during ORACLES</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Noone, D.; Henze, D.; Rainwater, B.; Toohey, D. W.</p> <p>2017-12-01</p> <p>The magnitude of the influence of biomass burning aerosols on <span class="hlt">cloud</span> and rain processes is controlled by a series of processes which are difficult to measure directly. A consequence of this limitation is the emergence of significant uncertainty in the representation of <span class="hlt">cloud</span>-aerosol interactions in models and the resulting <span class="hlt">cloud</span> radiative forcing. Interaction between <span class="hlt">cloud</span> and the regional atmosphere causes evaporation, and the rate of evaporation at <span class="hlt">cloud</span> top is controlled in part by entrainment of air from above which exposes saturated <span class="hlt">cloud</span> air to drier conditions. Similarly, the size of <span class="hlt">cloud</span> droplets also controls evaporation rates, which in turn is linked to the abundance of condensation nuclei. To quantify the dependence of <span class="hlt">cloud</span> properties on biomass burning aerosols the dynamic relationship between evaporation, drop size and entrainment on aerosol state, is evaluated for stratiform <span class="hlt">clouds</span> in the southeast Atlantic Ocean. These <span class="hlt">clouds</span> are seasonally exposed to biomass burning plumes from agricultural fires in southern Africa. Measurements of the stable isotope ratios of <span class="hlt">cloud</span> water and total water are used to deduce the disequilibrium responsible for evaporation within <span class="hlt">clouds</span>. Disequilibrium is <span class="hlt">identified</span> by the relationship between hydrogen and oxygen isotope ratios of water vapor and <span class="hlt">cloud</span> water in and near <span class="hlt">clouds</span>. To obtain the needed information, a custom-built, dual inlet system was deployed alongside isotopic gas analyzers on the NASA Orion aircraft as part of the Observations of Aerosols above <span class="hlt">Clouds</span> and their Interactions (ORACLES) campaign. The sampling system obtains both total water and <span class="hlt">cloud</span> liquid content for the population of droplets above 7 micrometer diameter. The thermodynamic modeling required to convert the observed equilibrium and kinetic isotopic is linked to evaporation and entrainment is described, and the performance of the measurement system is discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19970032262&hterms=baryonic+matter&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dbaryonic%2Bmatter','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19970032262&hterms=baryonic+matter&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dbaryonic%2Bmatter"><span>Precombination <span class="hlt">Cloud</span> Collapse and Baryonic Dark Matter</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hogan, Craig J.</p> <p>1993-01-01</p> <p>A simple spherical model of dense baryon <span class="hlt">clouds</span> in the hot big bang 'strongly nonlinear primordial isocurvature baryon fluctuations' is reviewed and used to describe the dependence of <span class="hlt">cloud</span> behavior on the model parameters, baryon mass, and initial over-density. Gravitational collapse of <span class="hlt">clouds</span> before and during recombination is considered including radiation diffusion and trapping, remnant <span class="hlt">type</span> and mass, and effects on linear large-scale fluctuation modes. Sufficiently dense <span class="hlt">clouds</span> collapse early into black holes with a minimum mass of approx. 1 solar mass, which behave dynamically like collisionless cold dark matter. <span class="hlt">Clouds</span> below a critical over-density, however, delay collapse until recombination, remaining until then dynamically coupled to the radiation like ordinary diffuse baryons, and possibly producing remnants of other kinds and lower mass. The mean density in either <span class="hlt">type</span> of baryonic remnant is unconstrained by observed element abundances. However, mixed or unmixed spatial variations in abundance may survive in the diffuse baryon and produce observable departures from standard predictions.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_7");'>7</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li class="active"><span>9</span></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_9 --> <div id="page_10" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="181"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017APS..DFDQ15001R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017APS..DFDQ15001R"><span>The fluid dynamics of atmospheric <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Randall, David A.</p> <p>2017-11-01</p> <p><span class="hlt">Clouds</span> of many <span class="hlt">types</span> are of leading-order importance for Earth's weather and climate. This importance is most often discussed in terms of the effects of <span class="hlt">clouds</span> on radiative transfer, but the fluid dynamics of <span class="hlt">clouds</span> are at least equally significant. Some very small-scale <span class="hlt">cloud</span> fluid-dynamical processes have significant consequences on the global scale. These include viscous dissipation near falling rain drops, and ``buoyancy reversal'' associated with the evaporation of liquid water. Major medium-scale <span class="hlt">cloud</span> fluid-dynamical processes include cumulus convection and convective aggregation. Planetary-scale processes that depend in an essential way on <span class="hlt">cloud</span> fluid dynamics include the Madden-Julian Oscillation, which is one of the largest and most consequential weather systems on Earth. I will attempt to give a coherent introductory overview of this broad range of phenomena.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19820037368&hterms=physical+chemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dphysical%2Bchemistry','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19820037368&hterms=physical+chemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dphysical%2Bchemistry"><span>Molecules in interstellar <span class="hlt">clouds</span>. [physical and chemical conditions of star formation and biological evolution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Irvine, W. M.; Hjalmarson, A.; Rydbeck, O. E. H.</p> <p>1981-01-01</p> <p>The physical conditions and chemical compositions of the gas in interstellar <span class="hlt">clouds</span> are reviewed in light of the importance of interstellar <span class="hlt">clouds</span> for star formation and the origin of life. The Orion A region is discussed as an example of a giant molecular <span class="hlt">cloud</span> where massive stars are being formed, and it is pointed out that conditions in the core of the <span class="hlt">cloud</span>, with a kinetic temperature of about 75 K and a density of 100,000-1,000,000 molecules/cu cm, may support gas phase ion-molecule chemistry. The Taurus Molecular <span class="hlt">Clouds</span> are then considered as examples of cold, dark, relatively dense interstellar <span class="hlt">clouds</span> which may be the birthplaces of solar-<span class="hlt">type</span> stars and which have been found to contain the heaviest interstellar molecules yet discovered. The molecular species <span class="hlt">identified</span> in each of these regions are tabulated, including such building blocks of biological monomers as H2O, NH3, H2CO, CO, H2S, CH3CN and H2, and more complex species such as HCOOCH3 and CH3CH2CN.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AIPC.1531..404S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AIPC.1531..404S"><span>GEWEX <span class="hlt">cloud</span> assessment: A review</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Stubenrauch, Claudia; Rossow, William B.; Kinne, Stefan; Ackerman, Steve; Cesana, Gregory; Chepfer, Hélène; Di Girolamo, Larry; Getzewich, Brian; Guignard, Anthony; Heidinger, Andy; Maddux, Brent; Menzel, Paul; Minnis, Patrick; Pearl, Cindy; Platnick, Steven; Poulsen, Caroline; Riedi, Jérôme; Sayer, Andrew; Sun-Mack, Sunny; Walther, Andi; Winker, Dave; Zeng, Shen; Zhao, Guangyu</p> <p>2013-05-01</p> <p><span class="hlt">Clouds</span> cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the entire globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite <span class="hlt">cloud</span> data records now exceed more than 25 years; however, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) <span class="hlt">Cloud</span> Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides the first coordinated intercomparison of publicly available, global <span class="hlt">cloud</span> products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders and lidar. <span class="hlt">Cloud</span> properties under study include <span class="hlt">cloud</span> amount, <span class="hlt">cloud</span> height (in terms of pressure, temperature or altitude), <span class="hlt">cloud</span> radiative properties (optical depth or emissivity), <span class="hlt">cloud</span> thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average <span class="hlt">cloud</span> properties, especially in the amount of high-level <span class="hlt">clouds</span>, are mostly explained by the inherent instrument measurement capability for detecting and/or <span class="hlt">identifying</span> optically thin cirrus, especially when overlying low-level <span class="hlt">clouds</span>. The study of long-term variations with these datasets requires consideration of many factors. The monthly, gridded database presented here facilitates further assessments, climate studies, and the evaluation of climate models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070020527&hterms=doi&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddoi%253A','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070020527&hterms=doi&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddoi%253A"><span>Multidecadal Changes in Near-Global <span class="hlt">Cloud</span> Cover and Estimated <span class="hlt">Cloud</span> Cover Radiative Forcing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Norris, Joel</p> <p>2005-01-01</p> <p>The first paper was Multidecadal changes in near-global <span class="hlt">cloud</span> cover and estimated <span class="hlt">cloud</span> cover radiative forcing, by J. R. Norris (2005, J. Geophys. Res. - Atmos., 110, D08206, doi: lO.l029/2004JD005600). This study examined variability in zonal mean surface-observed upper-level (combined midlevel and high-level) and low-level <span class="hlt">cloud</span> cover over land during 1971-1 996 and over ocean during 1952-1997. These data were averaged from individual synoptic reports in the Extended Edited <span class="hlt">Cloud</span> Report Archive (EECRA). Although substantial interdecadal variability is present in the time series, long-term decreases in upper-level <span class="hlt">cloud</span> cover occur over land and ocean at low and middle latitudes in both hemispheres. Near-global upper-level <span class="hlt">cloud</span> cover declined by 1.5%-sky-cover over land between 1971 and 1996 and by 1.3%-sky-cover over ocean between 1952 and 1997. Consistency between EECRA upper-level <span class="hlt">cloud</span> cover anomalies and those from the International Satellite <span class="hlt">Cloud</span> Climatology Project (ISCCP) during 1984-1 997 suggests the surface-observed trends are real. The reduction in surface-observed upper-level <span class="hlt">cloud</span> cover between the 1980s and 1990s is also consistent with the decadal increase in all-sky outgoing longwave radiation reported by the Earth Radiation Budget Satellite (EMS). Discrepancies occur between time series of EECRA and ISCCP low-level <span class="hlt">cloud</span> cover due to <span class="hlt">identified</span> and probable artifacts in satellite and surface <span class="hlt">cloud</span> data. Radiative effects of surface-observed <span class="hlt">cloud</span> cover anomalies, called "<span class="hlt">cloud</span> cover radiative forcing (CCRF) anomalies," are estimated based on a linear relationship to climatological <span class="hlt">cloud</span> radiative forcing per unit <span class="hlt">cloud</span> cover. Zonal mean estimated longwave CCRF has decreased over most of the globe. Estimated shortwave CCRF has become slightly stronger over northern midlatitude oceans and slightly weaker over northern midlatitude land areas. A long-term decline in the magnitude of estimated shortwave CCRF occurs over low-latitude land and ocean</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AMT....11.2863O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AMT....11.2863O"><span>Preliminary verification for application of a support vector machine-based <span class="hlt">cloud</span> detection method to GOSAT-2 CAI-2</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oishi, Yu; Ishida, Haruma; Nakajima, Takashi Y.; Nakamura, Ryosuke; Matsunaga, Tsuneo</p> <p>2018-05-01</p> <p> CLAUDIA3-CAI for various land cover <span class="hlt">types</span>, and evaluated the accuracy of CLAUDIA3-CAI by comparing both CLAUDIA1-CAI and CLAUDIA3-CAI with visual inspection (400 × 400 pixels) of the same CAI images in tropical rainforests. Comparative results between CLAUDIA1-CAI and CLAUDIA3-CAI for various land cover <span class="hlt">types</span> indicated that CLAUDIA3-CAI had a tendency to <span class="hlt">identify</span> bright surface and optically thin <span class="hlt">clouds</span>. However, CLAUDIA3-CAI had a tendency to misjudge the edges of <span class="hlt">clouds</span> compared with CLAUDIA1-CAI. The accuracy of CLAUDIA3-CAI was approximately 89.5 % in tropical rainforests, which is greater than that of CLAUDIA1-CAI (85.9 %) for the test cases presented here.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA631308','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA631308"><span><span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2009-11-12</p> <p>Service (IaaS) Software -as-a- Service ( SaaS ) <span class="hlt">Cloud</span> Computing <span class="hlt">Types</span> Platform-as-a- Service (PaaS) Based on <span class="hlt">Type</span> of Capability Based on access Based...Mellon University Software -as-a- Service ( SaaS ) Application-specific capabilities, e.g., service that provides customer management Allows organizations...as a Service ( SaaS ) Model of software deployment in which a provider licenses an application to customers for use as a service on</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT.......403B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT.......403B"><span>Morphological diagnostics of star formation in molecular <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beaumont, Christopher Norris</p> <p></p> <p>Molecular <span class="hlt">clouds</span> are the birth sites of all star formation in the present-day universe. They represent the initial conditions of star formation, and are the primary medium by which stars transfer energy and momentum back to parsec scales. Yet, the physical evolution of molecular <span class="hlt">clouds</span> remains poorly understood. This is not due to a lack of observational data, nor is it due to an inability to simulate the conditions inside molecular <span class="hlt">clouds</span>. Instead, the physics and structure of the interstellar medium are sufficiently complex that interpreting molecular <span class="hlt">cloud</span> data is very difficult. This dissertation mitigates this problem, by developing more sophisticated ways to interpret morphological information in molecular <span class="hlt">cloud</span> observations and simulations. In particular, I have focused on leveraging machine learning techniques to <span class="hlt">identify</span> physically meaningful substructures in the interstellar medium, as well as techniques to inter-compare molecular <span class="hlt">cloud</span> simulations to observations. These contributions make it easier to understand the interplay between molecular <span class="hlt">clouds</span> and star formation. Specific contributions include: new insight about the sheet-like geometry of molecular <span class="hlt">clouds</span> based on observations of stellar bubbles; a new algorithm to disambiguate overlapping yet morphologically distinct <span class="hlt">cloud</span> structures; a new perspective on the relationship between molecular <span class="hlt">cloud</span> column density distributions and the sizes of <span class="hlt">cloud</span> substructures; a quantitative analysis of how projection effects affect measurements of <span class="hlt">cloud</span> properties; and an automatically generated, statistically-calibrated catalog of bubbles <span class="hlt">identified</span> from their infrared morphologies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20140006010&hterms=vertical+height&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dvertical%2Bheight','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20140006010&hterms=vertical+height&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dvertical%2Bheight"><span>Vertical Structure of Ice <span class="hlt">Cloud</span> Layers From <span class="hlt">Cloud</span>Sat and CALIPSO Measurements and Comparison to NICAM Simulations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ham, Seung-Hee; Sohn, Byung-Ju; Kato, Seiji; Satoh, Masaki</p> <p>2013-01-01</p> <p>The shape of the vertical profile of ice <span class="hlt">cloud</span> layers is examined using 4 months of <span class="hlt">Cloud</span>Sat and <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) global measurements taken on January, April, July, and October 2007. Ice <span class="hlt">clouds</span> are selected using temperature profiles when the <span class="hlt">cloud</span> base is located above the 253K temperature level. The obtained ice water content (IWC), effective radius, or extinction coefficient profiles are normalized by their layer mean values and are expressed in the normalized vertical coordinate, which is defined as 0 and 1 at the <span class="hlt">cloud</span> base and top heights, respectively. Both <span class="hlt">Cloud</span>Sat and CALIPSO observations show that the maximum in the IWC and extinction profiles shifts toward the <span class="hlt">cloud</span> bottom, as the <span class="hlt">cloud</span> depth increases. In addition, <span class="hlt">clouds</span> with a base reaching the surface in a high-latitude region show that the maximum peak of the IWC and extinction profiles occurs near the surface, which is presumably due to snow precipitation. <span class="hlt">Cloud</span>Sat measurements show that the seasonal difference in normalized <span class="hlt">cloud</span> vertical profiles is not significant, whereas the normalized <span class="hlt">cloud</span> vertical profile significantly varies depending on the <span class="hlt">cloud</span> <span class="hlt">type</span> and the presence of precipitation. It is further examined if the 7 day Nonhydrostatic Icosahedral Atmospheric Model (NICAM) simulation results from 25 December 2006 to 1 January 2007 generate similar <span class="hlt">cloud</span> profile shapes. NICAM IWC profiles also show maximum peaks near the <span class="hlt">cloud</span> bottom for thick <span class="hlt">cloud</span> layers and maximum peaks at the <span class="hlt">cloud</span> bottom for low-level <span class="hlt">clouds</span> near the surface. It is inferred that oversized snow particles in the NICAM <span class="hlt">cloud</span> scheme produce a more vertically inhomogeneous IWC profile than observations due to quick sedimentation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A21O..01D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A21O..01D"><span>Effects of Environment Forcing on Marine Boundary Layer <span class="hlt">Cloud</span>-Drizzle Processes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dong, X.</p> <p>2017-12-01</p> <p>Determining the factors affecting drizzle formation in marine boundary layer (MBL) <span class="hlt">clouds</span> remains a challenge for both observation and modeling communities. To investigate the roles of vertical wind shear and buoyancy (static instability) in drizzle formation, ground-based observations from the Atmospheric Radiation Measurement (ARM) Program at the Azores are analyzed for two <span class="hlt">types</span> of conditions. The <span class="hlt">type</span> I <span class="hlt">clouds</span> should last for at least five hours and more than 90% time must be non-drizzling, and then followed by at least two hours of drizzling periods while the <span class="hlt">type</span> II <span class="hlt">clouds</span> are characterized by mesoscale convection cellular (MCC) structures with drizzle occur every two to four hours. By analyzing the boundary layer wind profiles (direction and speed), it was found that either directional or speed shear is required to promote drizzle production in the <span class="hlt">type</span> I <span class="hlt">clouds</span>. Observations and a recent model study both suggest that vertical wind shear helps the production of turbulent kinetic energy (TKE), stimulates turbulence within <span class="hlt">cloud</span> layer, and enhances drizzle formation near the <span class="hlt">cloud</span> top. The <span class="hlt">type</span> II <span class="hlt">clouds</span> do not require strong wind shear to produce drizzle. The small values of lower-tropospheric stability (LTS) and negative Richardson number (Ri) in the <span class="hlt">type</span> II cases suggest that boundary layer instability plays an important role in TKE production and <span class="hlt">cloud</span>-drizzle processes. By analyzing the relationships between LTS and wind shear for all cases and all time periods, a stronger connection was found between LTS and wind directional shear than that between LTS and wind speed shear.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20090014058&hterms=Good+Reason&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DGood%2BReason','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20090014058&hterms=Good+Reason&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DGood%2BReason"><span>Modeling the Diffuse <span class="hlt">Cloud</span>-Top Optical Emissions from Ground and <span class="hlt">Cloud</span> Flashes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Solakiewicz, Richard; Koshak, William</p> <p>2008-01-01</p> <p>A number of studies have indicated that the diffuse <span class="hlt">cloud</span>-top optical emissions from intra-<span class="hlt">cloud</span> (IC) lightning are brighter than that from normal negative <span class="hlt">cloud</span>-to-ground (CG) lightning, and hence would be easier to detect from a space-based sensor. The primary reason provided to substantiate this claim has been that the IC is at a higher altitude within the <span class="hlt">cloud</span> and therefore is less obscured by the <span class="hlt">cloud</span> multiple scattering medium. CGs at lower altitudes embedded deep within the <span class="hlt">cloud</span> are more obscured, so CG detection is thought to be more difficult. However, other authors claim that because the CG source current (and hence luminosity) is typically substantially larger than IC currents, the greater CG source luminosity is large enough to overcome the effects of multiple scattering. These investigators suggest that the diffuse <span class="hlt">cloud</span> top emissions from CGs are brighter than from ICs, and hence are easier to detect from space. Still other investigators claim that the detection efficiency of CGs and ICs is about the same because modern detector sensitivity is good enough to "see" either flash <span class="hlt">type</span> no matter which produces a brighter <span class="hlt">cloud</span> top emission. To better assess which of these opinions should be accepted, we introduce an extension of a Boltzmann lightning radiative transfer model previously developed. It considers characteristics of the <span class="hlt">cloud</span> (geometry, dimensions, scattering properties) and specific lightning channel properties (length, geometry, location, current, optical wave front propagation speed/direction). As such, it represents the most detailed modeling effort to date. At least in the few cases studied thus far, it was found that IC flashes appear brighter at <span class="hlt">cloud</span> top than the lower altitude negative ground flashes, but additional model runs are to be examined before finalizing our general conclusions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900041007&hterms=Xavier&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DXavier','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900041007&hterms=Xavier&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DXavier"><span>Molecular <span class="hlt">clouds</span> without detectable CO</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Blitz, Leo; Bazell, David; Desert, F. Xavier</p> <p>1990-01-01</p> <p>The <span class="hlt">clouds</span> <span class="hlt">identified</span> by Desert, Bazell, and Boulanger (DBB <span class="hlt">clouds</span>) in their search for high-latitude molecular <span class="hlt">clouds</span> were observed in the CO (J = 1-0) line, but only 13 percent of the sample was detected. The remaining 87 percent are diffuse molecular <span class="hlt">clouds</span> with CO abundances of about 10 to the -6th, a typical value for diffuse <span class="hlt">clouds</span>. This hypothesis is shown to be consistent with Copernicus data. The DBB <span class="hlt">clouds</span> are shown to ben an essentially complete catalog of diffuse molecular <span class="hlt">clouds</span> in the solar vicinity. The total molecular surface density in the vicinity of the sun is then only about 20 percent greater than the 1.3 solar masses/sq pc determined by Dame et al. (1987). Analysis of the CO detections indicates that there is a sharp threshold in extinction of 0.25 mag before CO is detectable and is derived from the IRAS I(100) micron threshold of 4 MJy/sr. This threshold is presumably where the CO abundance exhibits a sharp increase</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/7041156-molecular-clouds-without-detectable-co','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/7041156-molecular-clouds-without-detectable-co"><span>Molecular <span class="hlt">clouds</span> without detectable CO</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Blitz, L.; Bazell, D.; Desert, F.X.</p> <p>1990-03-01</p> <p>The <span class="hlt">clouds</span> <span class="hlt">identified</span> by Desert, Bazell, and Boulanger (DBB <span class="hlt">clouds</span>) in their search for high-latitude molecular <span class="hlt">clouds</span> were observed in the CO (J = 1-0) line, but only 13 percent of the sample was detected. The remaining 87 percent are diffuse molecular <span class="hlt">clouds</span> with CO abundances of about 10 to the -6th, a typical value for diffuse <span class="hlt">clouds</span>. This hypothesis is shown to be consistent with Copernicus data. The DBB <span class="hlt">clouds</span> are shown to be an essentially complete catalog of diffuse molecular <span class="hlt">clouds</span> in the solar vicinity. The total molecular surface density in the vicinity of the sun is thenmore » only about 20 percent greater than the 1.3 solar masses/sq pc determined by Dame et al. (1987). Analysis of the CO detections indicates that there is a sharp threshold in extinction of 0.25 mag before CO is detectable and is derived from the IRAS I(100) micron threshold of 4 MJy/sr. This threshold is presumably where the CO abundance exhibits a sharp increase 18 refs.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....16..505R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....16..505R"><span>Aerosol properties, source identification, and <span class="hlt">cloud</span> processing in orographic <span class="hlt">clouds</span> measured by single particle mass spectrometry on a central European mountain site during HCCT-2010</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Roth, A.; Schneider, J.; Klimach, T.; Mertes, S.; van Pinxteren, D.; Herrmann, H.; Borrmann, S.</p> <p>2016-01-01</p> <p><span class="hlt">Cloud</span> residues and out-of-<span class="hlt">cloud</span> aerosol particles with diameters between 150 and 900 nm were analysed by online single particle aerosol mass spectrometry during the 6-week study Hill Cap <span class="hlt">Cloud</span> Thuringia (HCCT)-2010 in September-October 2010. The measurement location was the mountain Schmücke (937 m a.s.l.) in central Germany. More than 160 000 bipolar mass spectra from out-of-<span class="hlt">cloud</span> aerosol particles and more than 13 000 bipolar mass spectra from <span class="hlt">cloud</span> residual particles were obtained and were classified using a fuzzy c-means clustering algorithm. Analysis of the uncertainty of the sorting algorithm was conducted on a subset of the data by comparing the clustering output with particle-by-particle inspection and classification by the operator. This analysis yielded a false classification probability between 13 and 48 %. Additionally, particle <span class="hlt">types</span> were <span class="hlt">identified</span> by specific marker ions. The results from the ambient aerosol analysis show that 63 % of the analysed particles belong to clusters having a diurnal variation, suggesting that local or regional sources dominate the aerosol, especially for particles containing soot and biomass burning particles. In the <span class="hlt">cloud</span> residues, the relative percentage of large soot-containing particles and particles containing amines was found to be increased compared to the out-of-<span class="hlt">cloud</span> aerosol, while, in general, organic particles were less abundant in the <span class="hlt">cloud</span> residues. In the case of amines, this can be explained by the high solubility of the amines, while the large soot-containing particles were found to be internally mixed with inorganics, which explains their activation as <span class="hlt">cloud</span> condensation nuclei. Furthermore, the results show that during <span class="hlt">cloud</span> processing, both sulfate and nitrate are added to the residual particles, thereby changing the mixing state and increasing the fraction of particles with nitrate and/or sulfate. This is expected to lead to higher hygroscopicity after <span class="hlt">cloud</span> evaporation, and therefore to an increase of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27531312','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27531312"><span>"Black <span class="hlt">cloud</span>" vs. "white <span class="hlt">cloud</span>" physicians - Myth or reality in apheresis medicine?</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Pham, Huy P; Raju, Dheeraj; Jiang, Ning; Williams, Lance A</p> <p>2017-08-01</p> <p>Many practitioners believe in the phenomenon of either being labeled a "black <span class="hlt">cloud</span>" or "white <span class="hlt">cloud</span>" while on-call. A "white-<span class="hlt">cloud</span>" physician is one who usually gets fewer cases. A "black-<span class="hlt">cloud</span>" is one who often has more cases. It is unclear if the designation is only superstitious or if there is some merit. Our aim is to objectively assess this phenomenon in apheresis medicine at our center. A one-year prospective study from 12/2014 to 11/2015 was designed to evaluate the number of times apheresis physicians and nurses were involved with emergent apheresis procedures between the hours from 10 PM and 7 AM. Other parameters collected include the names of the physician, apheresis nurse, <span class="hlt">type</span> of emergent apheresis procedure, day of the week, and season of the year. During the study period, 32 emergent procedures (or "black-<span class="hlt">cloud</span>" events) occurred. The median time between two consecutive events was 8 days (range: 1-34 days). We found no statistically significant association between the "black-<span class="hlt">cloud</span>" events and attending physicians, nurses, day of the week, or season of the year by Chi-square and Fisher's analyses. However, exploratory analysis using association rule demonstrated that "black-<span class="hlt">cloud</span>" events were more likely to happen on Thursday (2.19 times), with attending physician 2 (1.18 times), and during winter (1.15 times). The results of this pilot study may support the common perception that some physicians or nurses are either "black <span class="hlt">cloud</span>" or "white <span class="hlt">cloud</span>". A larger, multi-center study population is needed to validate the results of this pilot study. © 2016 Wiley Periodicals, Inc.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29792628','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29792628"><span>[The Key Technology Study on <span class="hlt">Cloud</span> Computing Platform for ECG Monitoring Based on Regional Internet of Things].</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Yang, Shu; Qiu, Yuyan; Shi, Bo</p> <p>2016-09-01</p> <p>This paper explores the methods of building the internet of things of a regional ECG monitoring, focused on the implementation of ECG monitoring center based on <span class="hlt">cloud</span> computing platform. It analyzes implementation principles of automatic <span class="hlt">identifi</span> cation in the <span class="hlt">types</span> of arrhythmia. It also studies the system architecture and key techniques of <span class="hlt">cloud</span> computing platform, including server load balancing technology, reliable storage of massive smalfi les and the implications of quick search function.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26955035','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26955035"><span>Visual Analysis of <span class="hlt">Cloud</span> Computing Performance Using Behavioral Lines.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Muelder, Chris; Zhu, Biao; Chen, Wei; Zhang, Hongxin; Ma, Kwan-Liu</p> <p>2016-02-29</p> <p><span class="hlt">Cloud</span> computing is an essential technology to Big Data analytics and services. A <span class="hlt">cloud</span> computing system is often comprised of a large number of parallel computing and storage devices. Monitoring the usage and performance of such a system is important for efficient operations, maintenance, and security. Tracing every application on a large <span class="hlt">cloud</span> system is untenable due to scale and privacy issues. But profile data can be collected relatively efficiently by regularly sampling the state of the system, including properties such as CPU load, memory usage, network usage, and others, creating a set of multivariate time series for each system. Adequate tools for studying such large-scale, multidimensional data are lacking. In this paper, we present a visual based analysis approach to understanding and analyzing the performance and behavior of <span class="hlt">cloud</span> computing systems. Our design is based on similarity measures and a layout method to portray the behavior of each compute node over time. When visualizing a large number of behavioral lines together, distinct patterns often appear suggesting particular <span class="hlt">types</span> of performance bottleneck. The resulting system provides multiple linked views, which allow the user to interactively explore the data by examining the data or a selected subset at different levels of detail. Our case studies, which use datasets collected from two different <span class="hlt">cloud</span> systems, show that this visual based approach is effective in <span class="hlt">identifying</span> trends and anomalies of the systems.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19740026923','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19740026923"><span>Mesoscale wake <span class="hlt">clouds</span> in Skylab pictures.</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Fujita, T. T.; Tecson, J. J.</p> <p>1974-01-01</p> <p>The recognition of <span class="hlt">cloud</span> patterns formed in the wake of orographic obstacles was investigated using pictures from Skylab, for the purpose of estimating atmospheric motions. The existence of ship-wake-<span class="hlt">type</span> wave <span class="hlt">clouds</span> in contrast to vortex sheets were revealed during examination of the pictures, and an attempt was made to characterize the pattern of waves as well as the transition between waves and vortices. Examples of mesoscale <span class="hlt">cloud</span> patterns which were analyzed photogrammetrically and meteorologically are presented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008hsf1.book..899C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008hsf1.book..899C"><span>The Monoceros R2 Molecular <span class="hlt">Cloud</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Carpenter, J. M.; Hodapp, K. W.</p> <p>2008-12-01</p> <p>The Monoceros R2 region was first recognized as a chain of reflection nebulae illuminated by A- and B-<span class="hlt">type</span> stars. These nebulae are associated with a giant molecular <span class="hlt">cloud</span> that is one of the closest massive star forming regions to the Sun. This chapter reviews the properties of the Mon R2 region, including the namesake reflection nebulae, the large scale molecula= r <span class="hlt">cloud</span>, global star formation activity, and properties of prominent star forming regions in the <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRD..11712210K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRD..11712210K"><span>An assessment of the <span class="hlt">cloud</span> signals simulated by NICAM using ISCCP, CALIPSO, and <span class="hlt">Cloud</span>Sat satellite simulators</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kodama, C.; Noda, A. T.; Satoh, M.</p> <p>2012-06-01</p> <p>This study presents an assessment of three-dimensional structures of hydrometeors simulated by the NICAM, global nonhydrostatic atmospheric model without cumulus parameterization, using multiple satellite data sets. A satellite simulator package (COSP: the CFMIP Observation Simulator Package) is employed to consistently compare model output with ISCCP, CALIPSO, and <span class="hlt">Cloud</span>Sat satellite observations. Special focus is placed on high thin <span class="hlt">clouds</span>, which are not observable in the conventional ISCCP data set, but can be detected by the CALIPSO observations. For the control run, the NICAM simulation qualitatively captures the geographical distributions of the high, middle, and low <span class="hlt">clouds</span>, even though the horizontal mesh spacing is as coarse as 14 km. The simulated low <span class="hlt">cloud</span> is very close to that of the CALIPSO low <span class="hlt">cloud</span>. Both the <span class="hlt">Cloud</span>Sat observations and NICAM simulation show a boomerang-<span class="hlt">type</span> pattern in the radar reflectivity-height histogram, suggesting that NICAM realistically simulates the deep <span class="hlt">cloud</span> development process. A striking difference was found in the comparisons of high thin cirrus, showing overestimated <span class="hlt">cloud</span> and higher <span class="hlt">cloud</span> top in the model simulation. Several model sensitivity experiments are conducted with different <span class="hlt">cloud</span> microphysical parameters to reduce the model-observation discrepancies in high thin cirrus. In addition, relationships among <span class="hlt">clouds</span>, Hadley circulation, outgoing longwave radiation and precipitation are discussed through the sensitivity experiments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A53R0468Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A53R0468Z"><span>Properties of Arctic Aerosol Particles and Residuals of Warm <span class="hlt">Clouds</span>: <span class="hlt">Cloud</span> Activation Efficiency and the Aerosol Indirect Effect</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zelenyuk, A.; Imre, D. G.; Leaitch, R.; Ovchinnikov, M.; Liu, P.; Macdonald, A.; Strapp, W.; Ghan, S. J.; Earle, M. E.</p> <p>2012-12-01</p> <p>Single particle mass spectrometer, SPLAT II, was used to characterize the size, composition, number concentration, density, and shape of individual Arctic spring aerosol. Background particles, particles above and below the <span class="hlt">cloud</span>, <span class="hlt">cloud</span> droplet residuals, and interstitial particles were characterized with goal to <span class="hlt">identify</span> the properties that separate <span class="hlt">cloud</span> condensation nuclei (CCN) from background aerosol particles. The analysis offers a comparison between warm <span class="hlt">clouds</span> formed on clean and polluted days, with clean days having maximum particle concentrations (Na) lower than ~250 cm-3, as compared with polluted days, in which maximum concentration was tenfold higher. On clean days, particles were composed of organics, organics mixed with sulfates, biomass burning (BB), sea salt (SS), and few soot and dust particles. On polluted days, BB, organics associated with BB, and their mixtures with sulfate dominated particle compositions. Based on the measured compositions and size distributions of <span class="hlt">cloud</span> droplet residuals, background aerosols, and interstitial particles, we conclude that these three particle <span class="hlt">types</span> had virtually the same compositions, which means that <span class="hlt">cloud</span> activation probabilities were surprisingly nearly composition independent. Moreover, these conclusions hold in cases in which less than 20% or more than 90% of background particles got activated. We concluded that for the warm <span class="hlt">clouds</span> interrogated in this study particle size played a more important factor on aerosol CCN activity. Comparative analysis of all studied <span class="hlt">clouds</span> reveals that aerosol activation efficiency strongly depends on the aerosol concentrations, such that at Na <200 cm-3, nearly all particles activate, and at higher concentrations the activation efficiency is lower. For example, when Na was greater than 1500 cm-3, less than ~30% of particles activated. The data suggest that as the number of nucleated droplets increases, condensation on existing droplets effectively competes with particle</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_8");'>8</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li class="active"><span>10</span></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_10 --> <div id="page_11" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="201"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3279223','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3279223"><span>Point <span class="hlt">Cloud</span> Generation from Aerial Image Data Acquired by a Quadrocopter <span class="hlt">Type</span> Micro Unmanned Aerial Vehicle and a Digital Still Camera</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Rosnell, Tomi; Honkavaara, Eija</p> <p>2012-01-01</p> <p>The objective of this investigation was to develop and investigate methods for point <span class="hlt">cloud</span> generation by image matching using aerial image data collected by quadrocopter <span class="hlt">type</span> micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point <span class="hlt">clouds</span> from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point <span class="hlt">cloud</span> generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point <span class="hlt">cloud</span> generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems’ SOCET SET classical commercial photogrammetric software and another is built using Microsoft®’s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point <span class="hlt">clouds</span> fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point <span class="hlt">clouds</span> that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point <span class="hlt">clouds</span> from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point <span class="hlt">cloud</span> generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point <span class="hlt">cloud</span> generation. PMID:22368479</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22368479','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22368479"><span>Point <span class="hlt">cloud</span> generation from aerial image data acquired by a quadrocopter <span class="hlt">type</span> micro unmanned aerial vehicle and a digital still camera.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rosnell, Tomi; Honkavaara, Eija</p> <p>2012-01-01</p> <p>The objective of this investigation was to develop and investigate methods for point <span class="hlt">cloud</span> generation by image matching using aerial image data collected by quadrocopter <span class="hlt">type</span> micro unmanned aerial vehicle (UAV) imaging systems. Automatic generation of high-quality, dense point <span class="hlt">clouds</span> from digital images by image matching is a recent, cutting-edge step forward in digital photogrammetric technology. The major components of the system for point <span class="hlt">cloud</span> generation are a UAV imaging system, an image data collection process using high image overlaps, and post-processing with image orientation and point <span class="hlt">cloud</span> generation. Two post-processing approaches were developed: one of the methods is based on Bae Systems' SOCET SET classical commercial photogrammetric software and another is built using Microsoft(®)'s Photosynth™ service available in the Internet. Empirical testing was carried out in two test areas. Photosynth processing showed that it is possible to orient the images and generate point <span class="hlt">clouds</span> fully automatically without any a priori orientation information or interactive work. The photogrammetric processing line provided dense and accurate point <span class="hlt">clouds</span> that followed the theoretical principles of photogrammetry, but also some artifacts were detected. The point <span class="hlt">clouds</span> from the Photosynth processing were sparser and noisier, which is to a large extent due to the fact that the method is not optimized for dense point <span class="hlt">cloud</span> generation. Careful photogrammetric processing with self-calibration is required to achieve the highest accuracy. Our results demonstrate the high performance potential of the approach and that with rigorous processing it is possible to reach results that are consistent with theory. We also point out several further research topics. Based on theoretical and empirical results, we give recommendations for properties of imaging sensor, data collection and processing of UAV image data to ensure accurate point <span class="hlt">cloud</span> generation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000038151&hterms=water+effects&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dwater%2Beffects','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000038151&hterms=water+effects&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dwater%2Beffects"><span>The Effect of <span class="hlt">Clouds</span> on Water Vapor Profiling from the Millimeter-Wave Radiometric Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wang, J. R.; Spinhirne, J. D.; Racette, P.; Chang, L. A.; Hart, W.</p> <p>1997-01-01</p> <p>Simultaneous measurements with the millimeter-wave imaging radiometer (MIR), <span class="hlt">cloud</span> lidar system (CLS), and the MODIS airborne simulator (MAS) were made aboard the NASA ER-2 aircraft over the western Pacific Ocean on 17-18 January 1993. These measurements were used to study the effects of <span class="hlt">clouds</span> on water vapor profile retrievals based on millimeter-wave radiometer measurements. The CLS backscatter measurements (at 0.532 and 1.064 am) provided information on the heights and a detailed structure of <span class="hlt">cloud</span> layers; the <span class="hlt">types</span> of <span class="hlt">clouds</span> could be positively <span class="hlt">identified</span>. All 12 MAS channels (0.6-13 Am) essentially respond to all <span class="hlt">types</span> of <span class="hlt">clouds</span>, while the six MIR channels (89-220 GHz) show little sensitivity to cirrus <span class="hlt">clouds</span>. The radiances from the 12-/Am and 0.875-gm channels of the MAS and the 89-GHz channel of the MIR were used to gauge the performance of the retrieval of water vapor profiles from the MIR observations under cloudy conditions. It was found that, for cirrus and absorptive (liquid) <span class="hlt">clouds</span>, better than 80% of the retrieval was convergent when one of the three criteria was satisfied; that is, the radiance at 0.875 Am is less than 100 W/cm.sr, or the brightness at 12 Am is greater than 260 K, or brightness at 89 GHz is less than 270 K (equivalent to <span class="hlt">cloud</span> liquid water of less than 0.04 g/cm). The range of these radiances for convergent retrieval increases markedly when the condition for convergent retrieval was somewhat relaxed. The algorithm of water vapor profiling from the MIR measurements could not perform adequately over the areas of storm-related <span class="hlt">clouds</span> that scatter radiation at millimeter wavelengths.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040012928&hterms=Ackerman&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D80%26Ntt%3DAckerman','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040012928&hterms=Ackerman&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D80%26Ntt%3DAckerman"><span>Global Multispectral <span class="hlt">Cloud</span> Retrievals from MODIS</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Riedi, Jerome C.; Baum, Bryan A.</p> <p>2003-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for <span class="hlt">cloud</span> masking and the retrieval of <span class="hlt">cloud</span> physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive <span class="hlt">cloud</span> mask, products include <span class="hlt">cloud</span>-top properties (temperature, pressure, effective emissivity), <span class="hlt">cloud</span> thermodynamic phase, <span class="hlt">cloud</span> optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various <span class="hlt">cloud</span> properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of <span class="hlt">cloud</span> optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar <span class="hlt">cloud</span> <span class="hlt">types</span> in various parts of the world.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JPRS..128..111W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JPRS..128..111W"><span>SigVox - A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo</p> <p>2017-06-01</p> <p>Urban road environments contain a variety of objects including different <span class="hlt">types</span> of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point <span class="hlt">clouds</span>. This work proposes a methodology for urban road object recognition from MLS point <span class="hlt">clouds</span>. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point <span class="hlt">clouds</span>. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically <span class="hlt">identifies</span> different <span class="hlt">types</span> of lamp poles and traffic signs. The workflow starts by tiling the raw point <span class="hlt">clouds</span> along the scanning trajectory and by <span class="hlt">identifying</span> non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically <span class="hlt">identified</span>. The feasibility and quality of the proposed method is verified on two point <span class="hlt">clouds</span> obtained in opposite direction of a stretch of road of 4 km. 6 <span class="hlt">types</span> of lamp pole and 4 <span class="hlt">types</span> of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AMT....11..593C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AMT....11..593C"><span>All-sky photogrammetry techniques to georeference a <span class="hlt">cloud</span> field</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Crispel, Pierre; Roberts, Gregory</p> <p>2018-01-01</p> <p>In this study, we present a novel method of <span class="hlt">identifying</span> and geolocalizing <span class="hlt">cloud</span> field elements from a portable all-sky camera stereo network based on the ground and oriented towards zenith. The methodology is mainly based on stereophotogrammetry which is a 3-D reconstruction technique based on triangulation from corresponding stereo pixels in rectified images. In cases where <span class="hlt">clouds</span> are horizontally separated, <span class="hlt">identifying</span> individual positions is performed with segmentation techniques based on hue filtering and contour detection algorithms. Macroscopic <span class="hlt">cloud</span> field characteristics such as <span class="hlt">cloud</span> layer base heights and velocity fields are also deduced. In addition, the methodology is fitted to the context of measurement campaigns which impose simplicity of implementation, auto-calibration, and portability. Camera internal geometry models are achieved a priori in the laboratory and validated to ensure a certain accuracy in the peripheral parts of the all-sky image. Then, stereophotogrammetry with dense 3-D reconstruction is applied with cameras spaced 150 m apart for two validation cases. The first validation case is carried out with cumulus <span class="hlt">clouds</span> having a <span class="hlt">cloud</span> base height at 1500 m a.g.l. The second validation case is carried out with two <span class="hlt">cloud</span> layers: a cumulus fractus layer with a base height at 1000 m a.g.l. and an altocumulus stratiformis layer with a base height of 2300 m a.g.l. Velocity fields at <span class="hlt">cloud</span> base are computed by tracking image rectangular patterns through successive shots. The height uncertainty is estimated by comparison with a Vaisala CL31 ceilometer located on the site. The uncertainty on the horizontal coordinates and on the velocity field are theoretically quantified by using the experimental uncertainties of the <span class="hlt">cloud</span> base height and camera orientation. In the first cumulus case, segmentation of the image is performed to <span class="hlt">identify</span> individuals <span class="hlt">clouds</span> in the <span class="hlt">cloud</span> field and determine the horizontal positions of the <span class="hlt">cloud</span> centers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009seao.book...81Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009seao.book...81Y"><span>Global Software Development with <span class="hlt">Cloud</span> Platforms</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yara, Pavan; Ramachandran, Ramaseshan; Balasubramanian, Gayathri; Muthuswamy, Karthik; Chandrasekar, Divya</p> <p></p> <p>Offshore and outsourced distributed software development models and processes are facing challenges, previously unknown, with respect to computing capacity, bandwidth, storage, security, complexity, reliability, and business uncertainty. <span class="hlt">Clouds</span> promise to address these challenges by adopting recent advances in virtualization, parallel and distributed systems, utility computing, and software services. In this paper, we envision a <span class="hlt">cloud</span>-based platform that addresses some of these core problems. We outline a generic <span class="hlt">cloud</span> architecture, its design and our first implementation results for three <span class="hlt">cloud</span> forms - a compute <span class="hlt">cloud</span>, a storage <span class="hlt">cloud</span> and a <span class="hlt">cloud</span>-based software service- in the context of global distributed software development (GSD). Our ”compute cloud” provides computational services such as continuous code integration and a compile server farm, ”storage cloud” offers storage (block or file-based) services with an on-line virtual storage service, whereas the on-line virtual labs represent a useful <span class="hlt">cloud</span> service. We note some of the use cases for <span class="hlt">clouds</span> in GSD, the lessons learned with our prototypes and <span class="hlt">identify</span> challenges that must be conquered before realizing the full business benefits. We believe that in the future, software practitioners will focus more on these <span class="hlt">cloud</span> computing platforms and see <span class="hlt">clouds</span> as a means to supporting a ecosystem of clients, developers and other key stakeholders.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/5104446-water-dense-molecular-clouds','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/5104446-water-dense-molecular-clouds"><span>Water in dense molecular <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wannier, P.G.; Kuiper, T.B.H.; Frerking, M.A.</p> <p>1991-08-01</p> <p>The G.P. Kuiper Airborne Observatory (KAO) was used to make initial observations of the half-millimeter ground-state transition of water in seven giant molecular <span class="hlt">clouds</span> and in two late-<span class="hlt">type</span> stars. No significant detections were made, and the resulting upper limits are significantly below those expected from other, indirect observations and from several theoretical models. The implied interstellar H2O/CO abundance is less than 0.003 in the cores of three giant molecular <span class="hlt">clouds</span>. This value is less than expected from <span class="hlt">cloud</span> chemistry models and also than estimates based on HDO and H3O(+) observations. 78 refs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080006497','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080006497"><span>Statistical Analyses of Satellite <span class="hlt">Cloud</span> Object Data from CERES. Part III; Comparison with <span class="hlt">Cloud</span>-Resolving Model Simulations of Tropical Convective <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Luo, Yali; Xu, Kuan-Man; Wielicki, Bruce A.; Wong, Takmeng; Eitzen, Zachary A.</p> <p>2007-01-01</p> <p>The present study evaluates the ability of a <span class="hlt">cloud</span>-resolving model (CRM) to simulate the physical properties of tropical deep convective <span class="hlt">cloud</span> objects <span class="hlt">identified</span> from a <span class="hlt">Clouds</span> and the Earth s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium- and large-size categories of <span class="hlt">cloud</span> objects observed during March 1998 and between the large-size categories of <span class="hlt">cloud</span> objects observed during March 1998 (strong El Ni o) and March 2000 (weak La Ni a). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. <span class="hlt">Cloud</span> physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all <span class="hlt">cloud</span> physical properties between the simulated and observed distributions. Each <span class="hlt">cloud</span> physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated <span class="hlt">cloud</span> tops are generally too high and <span class="hlt">cloud</span> top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of <span class="hlt">cloud</span> optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the <span class="hlt">cloud</span> microphysics parameterization and inputs such as <span class="hlt">cloud</span> ice effective size to the radiation calculation. Summary histograms of <span class="hlt">cloud</span> optical depth and TOA albedo from the CRM simulations of the large-size category of <span class="hlt">cloud</span> objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed <span class="hlt">cloud</span> top height while it overestimates the differences in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19920004371','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19920004371"><span>The chemistry of dense interstellar <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Irvine, W. M.</p> <p>1991-01-01</p> <p>The basic theme of this program is the study of molecular complexity and evolution in interstellar and circumstellar <span class="hlt">clouds</span> incorporating the biogenic elements. Recent results include the identification of a new astronomical carbon-chain molecule, C4Si. This species was detected in the envelope expelled from the evolved star IRC+10216 in observations at the Nobeyama Radio Observatory in Japan. C4Si is the carrier of six unidentified lines which had previously been observed. This detection reveals the existence of a new series of carbon-chain molecules, C sub n Si (n equals 1, 2, 4). Such molecules may well be formed from the reaction of Si(+) with acetylene and acetylene derivatives. Other recent research has concentrated on the chemical composition of the cold, dark interstellar <span class="hlt">clouds</span>, the nearest dense molecular <span class="hlt">clouds</span> to the solar system. Such regions have very low kinetic temperatures, on the order of 10 K, and are known to be formation sites for solar-<span class="hlt">type</span> stars. We have recently <span class="hlt">identified</span> for the first time in such regions the species of H2S, NO, HCOOH (formic acid). The H2S abundance appears to exceed that predicted by gas-phase models of ion-molecule chemistry, perhaps suggesting the importance of synthesis on grain surfaces. Additional observations in dark <span class="hlt">clouds</span> have studied the ratio of ortho- to para-thioformaldehyde. Since this ratio is expected to be unaffected by both radiative and ordinary collisional processes in the <span class="hlt">cloud</span>, it may well reflect the formation conditions for this molecule. The ratio is observed to depart from that expected under conditions of chemical equilibrium at formation, perhaps reflecting efficient interchange between cold dust grains in the gas phase.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950043412&hterms=sage&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dsage','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950043412&hterms=sage&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dsage"><span>Comparison between SAGE II and ISCCP high-level <span class="hlt">clouds</span>. 1: Global and zonal mean <span class="hlt">cloud</span> amounts</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liao, Xiaohan; Rossow, William B.; Rind, David</p> <p>1995-01-01</p> <p>Global high-level <span class="hlt">clouds</span> <span class="hlt">identified</span> in Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation measurements for January and July in the period 1985 to 1990 are compared with near-nadir-looking observations from the International Satellite <span class="hlt">Cloud</span> Climatology Project (ISCCP). Global and zonal mean high-level <span class="hlt">cloud</span> amounts from the two data sets agree very well, if <span class="hlt">clouds</span> with layer extinction coefficients of less than 0.008/km at 1.02 micrometers wavelength are removed from the SAGE II results and all detected <span class="hlt">clouds</span> are interpreted to have an average horizontal size of about 75 km along the 200 km transimission path length of the SAGE II observations. The SAGE II results are much more sensitive to variations of assumed <span class="hlt">cloud</span> size than to variations of detection threshold. The geographical distribution of <span class="hlt">cloud</span> fractions shows good agreement, but systematic regional differences also indicate that the average <span class="hlt">cloud</span> size varies somewhat among different climate regimes. The more sensitive SAGE II results show that about one third of all high-level <span class="hlt">clouds</span> are missed by ISCCP but that these <span class="hlt">clouds</span> have very low optical thicknesses (less than 0.1 at 0.6 micrometers wavelength). SAGE II sampling error in monthly zonal <span class="hlt">cloud</span> fraction is shown to produce no bias, to be less than the intraseasonal natural variability, but to be comparable with the natural variability at longer time scales.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AJ....155...11M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AJ....155...11M"><span><span class="hlt">Cloud</span> Atlas: Discovery of Rotational Spectral Modulations in a Low-mass, L-<span class="hlt">type</span> Brown Dwarf Companion to a Star</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Manjavacas, Elena; Apai, Dániel; Zhou, Yifan; Karalidi, Theodora; Lew, Ben W. P.; Schneider, Glenn; Cowan, Nicolas; Metchev, Stan; Miles-Páez, Paulo A.; Burgasser, Adam J.; Radigan, Jacqueline; Bedin, Luigi R.; Lowrance, Patrick J.; Marley, Mark S.</p> <p>2018-01-01</p> <p>Observations of rotational modulations of brown dwarfs and giant exoplanets allow the characterization of condensate <span class="hlt">cloud</span> properties. As of now, rotational spectral modulations have only been seen in three L-<span class="hlt">type</span> brown dwarfs. We report here the discovery of rotational spectral modulations in LP261-75B, an L6-<span class="hlt">type</span> intermediate surface gravity companion to an M4.5 star. As a part of the <span class="hlt">Cloud</span> Atlas Treasury program, we acquired time-resolved Wide Field Camera 3 grism spectroscopy (1.1–1.69 μm) of LP261-75B. We find gray spectral variations with the relative amplitude displaying only a weak wavelength dependence and no evidence for lower-amplitude modulations in the 1.4 μm water band than in the adjacent continuum. The likely rotational modulation period is 4.78 ± 0.95 hr, although the rotational phase is not well sampled. The minimum relative amplitude in the white light curve measured over the whole wavelength range is 2.41% ± 0.14%. We report an unusual light curve, which seems to have three peaks approximately evenly distributed in rotational phase. The spectral modulations suggests that the upper atmosphere <span class="hlt">cloud</span> properties in LP261-75B are similar to two other mid-L dwarfs of typical infrared colors, but differ from that of the extremely red L-dwarf WISE0047.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..11.5509M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..11.5509M"><span>A comparison between <span class="hlt">Cloud</span>Sat and aircraft data for mixed-phase and cirrus <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mioche, G.; Gayet, J.-F.; Minikin, A.; Herber, A.; Pelon, J.</p> <p>2009-04-01</p> <p> resolution <span class="hlt">Cloud</span> Particle Imager probe (CPI) for imaging the ice particle morphology (2.3 microns pixels size) and standard PMS probes: 2D-C, FSSP-100 and FSSP-300. This presentation focuses on the validation of the standard parameter of the <span class="hlt">Cloud</span> Profiling Radar (CPR) of <span class="hlt">Cloud</span>Sat (equivalent radar reflectivity factor Z). The different IWC(ice water content)-Z relationships determined from combined <span class="hlt">Cloud</span>Sat and in situ data are then discussed. The method to derive equivalent reflectivity factor from the CPI data is first presented. According to the particle shape, a mass-diameter relationship and thus a reflectivity factor is determined for each <span class="hlt">type</span> of ice crystal. This technique noticeably decreases the discrepancies of radar reflectivity-derived values due to the natural variability of ice crystal shapes. Comparisons of the reflectivity factor deduced from CPI and those from <span class="hlt">Cloud</span>Sat for various <span class="hlt">types</span> of <span class="hlt">clouds</span> are then discussed. The next step to the interpretation of the <span class="hlt">Cloud</span>Sat product is to derive IWC-Z relationships for assessing IWC distributions on a global scale, which is an important improvement to constrain global scale modelling. Several IWC-Z relationships are determined from in situ measurements according to the various case studies including Arctic mixed-phase <span class="hlt">clouds</span>, Arctic and mid-latitude cirrus. The improvements on the results by using the CPI data-processing method are discussed. Acknowledgements: This work was funded by the Centre National d'Etudes Spatiales (CNES), the Agence Nationale de la Recherche (ANR BLAN06-1_137670), the Institut National des Sciences de l'Univers (INSU/CNRS), the Institut Polaire Français Paul Emile Victor (IPEV), the Alfred Wegener Institute (AWI) and the Deutsches Zentrum für Luft-und Raumfahrt (DLR). The <span class="hlt">Cloud</span>Sat data are courtesy of the <span class="hlt">Cloud</span>Sat Data Processing Center.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA582008','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA582008"><span>Optical Algorithm for <span class="hlt">Cloud</span> Shadow Detection Over Water</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-02-01</p> <p>REPORT DATE (DD-MM-YYYY) 05-02-2013 2. REPORT <span class="hlt">TYPE</span> Journal Article 3. DATES COVERED (From ■ To) 4. TITLE AND SUBTITLE Optical Algorithm for <span class="hlt">Cloud</span>...particularly over humid tropical regions. Throughout the year, about two-thirds of the Earth’s surface is always covered by <span class="hlt">clouds</span> [1]. The problem...V. Khlopenkov and A. P. Trishchenko, "SPARC: New <span class="hlt">cloud</span>, snow , <span class="hlt">cloud</span> shadow detection scheme for historical I-km AVHHR data over Canada," / Atmos</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016NatGe...9..748M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016NatGe...9..748M"><span>Intensification of convective extremes driven by <span class="hlt">cloud-cloud</span> interaction</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Moseley, Christopher; Hohenegger, Cathy; Berg, Peter; Haerter, Jan O.</p> <p>2016-10-01</p> <p>In a changing climate, a key role may be played by the response of convective-<span class="hlt">type</span> <span class="hlt">cloud</span> and precipitation to temperature changes. Yet, it is unclear if convective precipitation intensities will increase mainly due to thermodynamic or dynamical processes. Here we perform large eddy simulations of convection by imposing a realistic diurnal cycle of surface temperature. We find convective events to gradually self-organize into larger <span class="hlt">cloud</span> clusters and those events occurring late in the day to produce the highest precipitation intensities. Tracking rain cells throughout their life cycles, we show that events which result from collisions respond strongly to changes in boundary conditions, such as temperature changes. Conversely, events not resulting from collisions remain largely unaffected by the boundary conditions. Increased surface temperature indeed leads to more interaction between events and stronger precipitation extremes. However, comparable intensification occurs when leaving temperature unchanged but simply granting more time for self-organization. These findings imply that the convective field as a whole acquires a memory of past precipitation and inter-<span class="hlt">cloud</span> dynamics, driving extremes. For global climate model projections, our results suggest that the interaction between convective <span class="hlt">clouds</span> must be incorporated to simulate convective extremes and the diurnal cycle more realistically.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19810049597&hterms=beans&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dbeans','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19810049597&hterms=beans&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dbeans"><span>Some new worldwide <span class="hlt">cloud</span>-cover models</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bean, S. J.; Somerville, P. N.</p> <p>1981-01-01</p> <p>Using daily measurements of day and night infrared, and incoming and absorbed solar radiation obtained from a Tiros satellite over a period of approximately 45 months, and integrated over 2.5 deg latitude-longitude grids, the proportion of <span class="hlt">cloud</span> cover over each grid each day was derived for the entire period. For each of four 3-month periods, for each grid location, estimates a and b of the two parameters of the best-fit beta distribution were obtained. The (a, b) plane was divided into a number of regions. All the geographical locations whose (a, b) estimates were in the same region in the (a, b) plane were said to have the same <span class="hlt">cloud</span> cover <span class="hlt">type</span> for that season. For each season, the world is thus divided into separate <span class="hlt">cloud</span>-cover <span class="hlt">types</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AIPC.1935r0003N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AIPC.1935r0003N"><span>Peltier-based <span class="hlt">cloud</span> chamber</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nar, Sevda Yeliz; Cakir, Altan</p> <p>2018-02-01</p> <p>Particles produced by nuclear decay, cosmic radiation and reactions can be <span class="hlt">identified</span> through various methods. One of these methods that has been effective in the last century is the <span class="hlt">cloud</span> chamber. The chamber makes visible cosmic particles that we are exposed to radiation per second. Diffusion <span class="hlt">cloud</span> chamber is a kind of <span class="hlt">cloud</span> chamber that is cooled by dry ice. This traditional model has some application difficulties. In this work, Peltier-based <span class="hlt">cloud</span> chamber cooled by thermoelectric modules is studied. The new model provided uniformly cooled base of the chamber, moreover, it has longer lifetime than the traditional chamber in terms of observation time. This gain has reduced the costs which spent each time for cosmic particle observation. The chamber is an easy-to-use system according to traditional diffusion <span class="hlt">cloud</span> chamber. The new model is portable, easier to make, and can be used in the nuclear physics experiments. In addition, it would be very useful to observe Muons which are the direct evidence for Lorentz contraction and time expansion predicted by Einsteins special relativity principle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA581730','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA581730"><span>An Evaluation of Northern Hemisphere Merged <span class="hlt">Cloud</span> Analyses from the United States Air Force <span class="hlt">Cloud</span> Depiction Forecasting System II</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-03-01</p> <p>layering and <span class="hlt">typing</span> to provide a vertical stratification of the <span class="hlt">cloud</span>-filled pixels detected in Level 2. Level 3 output is remapped to the standard AFWA...analyses are compared to one another to see if the most recent analysis also has the lowest estimated error. Optimum interpolation (OI) occurs when...NORTHERN HEMISPHERE MERGED <span class="hlt">CLOUD</span> ANALYSES FROM THE UNITED STATES AIR FORCE <span class="hlt">CLOUD</span> DEPICTION FORECASTING SYSTEM II by Chandra M. Pasillas March</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1051181-marine-cloud-brightening','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1051181-marine-cloud-brightening"><span>Marine <span class="hlt">Cloud</span> Brightening</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Latham, John; Bower, Keith; Choularton, Tom</p> <p>2012-09-07</p> <p>The idea behind the marine <span class="hlt">cloud</span>-brightening (MCB) geoengineering technique is that seeding marine stratocumulus <span class="hlt">clouds</span> with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the <span class="hlt">cloud</span> droplet number concentration, and thereby the <span class="hlt">cloud</span> albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could - subject to satisfactory resolution of technical and scientific problems <span class="hlt">identified</span> herein - have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involvesmore » (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in <span class="hlt">cloud</span> brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seedparticle salt-mass, air-mass characteristics, updraught speed and other parameters on <span class="hlt">cloud</span>-albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, <span class="hlt">cloud</span> albedo might be enhanced by seeding marine stratocumulus <span class="hlt">clouds</span> on a spatial scale of around 100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22869798','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22869798"><span>Marine <span class="hlt">cloud</span> brightening.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Latham, John; Bower, Keith; Choularton, Tom; Coe, Hugh; Connolly, Paul; Cooper, Gary; Craft, Tim; Foster, Jack; Gadian, Alan; Galbraith, Lee; Iacovides, Hector; Johnston, David; Launder, Brian; Leslie, Brian; Meyer, John; Neukermans, Armand; Ormond, Bob; Parkes, Ben; Rasch, Phillip; Rush, John; Salter, Stephen; Stevenson, Tom; Wang, Hailong; Wang, Qin; Wood, Rob</p> <p>2012-09-13</p> <p>The idea behind the marine <span class="hlt">cloud</span>-brightening (MCB) geoengineering technique is that seeding marine stratocumulus <span class="hlt">clouds</span> with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the <span class="hlt">cloud</span> droplet number concentration, and thereby the <span class="hlt">cloud</span> albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could-subject to satisfactory resolution of technical and scientific problems <span class="hlt">identified</span> herein-have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in <span class="hlt">cloud</span> brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seed-particle salt-mass, air-mass characteristics, updraught speed and other parameters on <span class="hlt">cloud</span>-albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, <span class="hlt">cloud</span> albedo might be enhanced by seeding marine stratocumulus <span class="hlt">clouds</span> on a spatial scale of around 100×100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_9");'>9</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li class="active"><span>11</span></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_11 --> <div id="page_12" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="221"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..1714682V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..1714682V"><span><span class="hlt">Cloud</span> radiative properties and aerosol - <span class="hlt">cloud</span> interaction</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Viviana Vladutescu, Daniela; Gross, Barry; Li, Clement; Han, Zaw</p> <p>2015-04-01</p> <p>The presented research discusses different techniques for improvement of <span class="hlt">cloud</span> properties measurements and analysis. The need for these measurements and analysis arises from the high errors noticed in existing methods that are currently used in retrieving <span class="hlt">cloud</span> properties and implicitly <span class="hlt">cloud</span> radiative forcing. The properties investigated are <span class="hlt">cloud</span> fraction (cf) and <span class="hlt">cloud</span> optical thickness (COT) measured with a suite of collocated remote sensing instruments. The novel approach makes use of a ground based "poor man's camera" to detect <span class="hlt">cloud</span> and sky radiation in red, green, and blue with a high spatial resolution of 30 mm at 1km. The surface-based high resolution photography provides a new and interesting view of <span class="hlt">clouds</span>. As the <span class="hlt">cloud</span> fraction cannot be uniquely defined or measured, it depends on threshold and resolution. However as resolution decreases, <span class="hlt">cloud</span> fraction tends to increase if the threshold is below the mean, and vice versa. Additionally <span class="hlt">cloud</span> fractal dimension also depends on threshold. Therefore these findings raise concerns over the ability to characterize <span class="hlt">clouds</span> by <span class="hlt">cloud</span> fraction or fractal dimension. Our analysis indicate that Principal Component analysis may lead to a robust means of quantifying <span class="hlt">cloud</span> contribution to radiance. The <span class="hlt">cloud</span> images are analyzed in conjunction with a collocated CIMEL sky radiometer, Microwave Radiometer and LIDAR to determine homogeneity and heterogeneity. Additionally, MFRSR measurements are used to determine the <span class="hlt">cloud</span> radiative properties as a validation tool to the results obtained from the other instruments and methods. The <span class="hlt">cloud</span> properties to be further studied are aerosol- <span class="hlt">cloud</span> interaction, <span class="hlt">cloud</span> particle radii, and vertical homogeneity.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160000959','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160000959"><span>Remote Sensing of <span class="hlt">Cloud</span> Top Heights Using the Research Scanning Polarimeter</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sinclair, Kenneth; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej</p> <p>2015-01-01</p> <p><span class="hlt">Clouds</span> cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered <span class="hlt">clouds</span> occur about half of the time and are predominantly two-layered. Changes in <span class="hlt">cloud</span> top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and <span class="hlt">cloud</span> microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure <span class="hlt">cloud</span> top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at <span class="hlt">cloud</span> altitude using a correlation function designed to <span class="hlt">identify</span> the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the <span class="hlt">Cloud</span> Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately <span class="hlt">identify</span> <span class="hlt">cloud</span> heights. Interestingly, the analysis reveals an ability for the approach to <span class="hlt">identify</span> multiple <span class="hlt">cloud</span> layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of <span class="hlt">identifying</span> single and multiple <span class="hlt">cloud</span> layers heights are explored. Special focus is given to sources of error in the method including optically thin <span class="hlt">clouds</span>, physically thick <span class="hlt">clouds</span>, multi</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAnIV-3..149L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAnIV-3..149L"><span><span class="hlt">Cloud</span> Detection by Fusing Multi-Scale Convolutional Features</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang</p> <p>2018-04-01</p> <p><span class="hlt">Clouds</span> detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of <span class="hlt">cloud</span> detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based <span class="hlt">cloud</span> detection method termed MSCN (multi-scale <span class="hlt">cloud</span> net), which segments <span class="hlt">cloud</span> by fusing multi-scale convolutional features. MSCN was trained on a global <span class="hlt">cloud</span> cover validation collection, and was tested in more than ten <span class="hlt">types</span> of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined <span class="hlt">cloud</span> detection method in accuracy, especially when in snow and other areas covered by bright non-<span class="hlt">cloud</span> objects. Besides, MSCN produced more detailed <span class="hlt">cloud</span> masks than the compared deep <span class="hlt">cloud</span> detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000847.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e000847.html"><span>Hole punch <span class="hlt">clouds</span> over the Bahamas</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-12-08</p> <p>In elementary school, students learn that water freezes at 0 degrees Celsius (32 degrees Fahrenheit). That is true most of the time, but there are exceptions to the rule. For instance, water with very few impurities (such as dust or pollution particles, fungal spores, bacteria) can be chilled to much cooler temperatures and still remain liquid—a process known as supercooling. Supercooling may sound exotic, but it occurs pretty routinely in Earth’s atmosphere. Altocumulus <span class="hlt">clouds</span>, a common <span class="hlt">type</span> of mid-altitude <span class="hlt">cloud</span>, are mostly composed of water droplets supercooled to a temperature of about -15 degrees C. Altocumulus <span class="hlt">clouds</span> with supercooled tops cover about 8 percent of Earth’s surface at any given time. Supercooled water droplets play a key role in the formation of hole-punch and canal <span class="hlt">clouds</span>, the distinctive <span class="hlt">clouds</span> shown in these satellite images. Hole-punch <span class="hlt">clouds</span> usually appear as circular gaps in decks of altocumulus <span class="hlt">clouds</span>; canal <span class="hlt">clouds</span> look similar but the gaps are longer and thinner. This true-color image shows hole-punch and canal <span class="hlt">clouds</span> off the coast of Florida, as observed on December 12, 2014, by the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Terra satellite. Both <span class="hlt">types</span> of <span class="hlt">cloud</span> form when aircraft fly through <span class="hlt">cloud</span> decks rich with supercooled water droplets and produce aerodynamic contrails. Air expands and cools as it moves around the wings and past the propeller, a process known as adiabatic cooling. Air temperatures over jet wings often cool by as much as 20 degrees Celsius, pushing supercooled water droplets to the point of freezing. As ice crystals form, they absorb nearby water droplets. Since ice crystals are relatively heavy, they tend to sink. This triggers tiny bursts of snow or rain that leave gaps in the <span class="hlt">cloud</span> cover. Whether a <span class="hlt">cloud</span> formation becomes a hole-punch or canal depends on the thickness of the <span class="hlt">cloud</span> layer, the air temperature, and the degree of horizontal wind shear. Both descending and ascending</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA532563','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA532563"><span>T-Check in System-of-Systems Technologies: <span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2010-09-01</p> <p>T-Check in System-of-Systems Technologies: <span class="hlt">Cloud</span> Computing Harrison D. Strowd Grace A. Lewis September 2010 TECHNICAL NOTE CMU/SEI-2010... <span class="hlt">Cloud</span> Computing 1 1.2 <span class="hlt">Types</span> of <span class="hlt">Cloud</span> Computing 2 1.3 Drivers and Barriers to <span class="hlt">Cloud</span> Computing Adoption 5 2 Using the T-Check Method 7 2.1 T-Check...Hypothesis 3 25 3.4.2 Deployment View of the Solution for Testing Hypothesis 3 27 3.5 Selecting <span class="hlt">Cloud</span> Computing Providers 30 3.6 Implementing the T-Check</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/20975157','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/20975157"><span>Spark<span class="hlt">Clouds</span>: visualizing trends in tag <span class="hlt">clouds</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Lee, Bongshin; Riche, Nathalie Henry; Karlson, Amy K; Carpendale, Sheelash</p> <p>2010-01-01</p> <p>Tag <span class="hlt">clouds</span> have proliferated over the web over the last decade. They provide a visual summary of a collection of texts by visually depicting the tag frequency by font size. In use, tag <span class="hlt">clouds</span> can evolve as the associated data source changes over time. Interesting discussions around tag <span class="hlt">clouds</span> often include a series of tag <span class="hlt">clouds</span> and consider how they evolve over time. However, since tag <span class="hlt">clouds</span> do not explicitly represent trends or support comparisons, the cognitive demands placed on the person for perceiving trends in multiple tag <span class="hlt">clouds</span> are high. In this paper, we introduce Spark<span class="hlt">Clouds</span>, which integrate sparklines into a tag <span class="hlt">cloud</span> to convey trends between multiple tag <span class="hlt">clouds</span>. We present results from a controlled study that compares Spark<span class="hlt">Clouds</span> with two traditional trend visualizations—multiple line graphs and stacked bar charts—as well as Parallel Tag <span class="hlt">Clouds</span>. Results show that Spark<span class="hlt">Clouds</span> ability to show trends compares favourably to the alternative visualizations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A13C0281K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A13C0281K"><span>Low-latitude variability of ice <span class="hlt">cloud</span> properties and <span class="hlt">cloud</span> thermodynamic phase observed by the Atmospheric Infrared Sounder (AIRS)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kahn, B. H.; Yue, Q.; Davis, S. M.; Fetzer, E. J.; Schreier, M. M.; Tian, B.; Wong, S.</p> <p>2016-12-01</p> <p>We will quantify the time and space dependence of ice <span class="hlt">cloud</span> effective radius (CER), optical thickness (COT), <span class="hlt">cloud</span> top temperature (CTT), effective <span class="hlt">cloud</span> fraction (ECF), and <span class="hlt">cloud</span> thermodynamic phase (ice, liquid, or unknown) with the Version 6 Atmospheric Infrared Sounder (AIRS) satellite observational data set from September 2002 until present. We show that <span class="hlt">cloud</span> frequency, CTT, COT, and ECF have substantially different responses to ENSO variations. Large-scale changes in ice CER are also observed with a several micron tropics-wide increase during the 2015-2016 El Niño and similar decreases during the La Niña phase. We show that the ice CER variations reflect fundamental changes in the spatial distributions and relative frequencies of different ice <span class="hlt">cloud</span> <span class="hlt">types</span>. Lastly, the high spatial and temporal resolution variability of the <span class="hlt">cloud</span> fields are explored and we show that these data capture a multitude of convectively coupled tropical waves such as Kelvin, westward and eastward intertio-gravity, equatorial Rossby, and mixed Rossby-gravity waves.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1133578-automated-detection-cloud-cloud-shadow-single-date-landsat-imagery-using-neural-networks-spatial-post-processing','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1133578-automated-detection-cloud-cloud-shadow-single-date-landsat-imagery-using-neural-networks-spatial-post-processing"><span>Automated detection of <span class="hlt">cloud</span> and <span class="hlt">cloud</span>-shadow in single-date Landsat imagery using neural networks and spatial post-processing</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Hughes, Michael J.; Hayes, Daniel J</p> <p>2014-01-01</p> <p>Use of Landsat data to answer ecological questions is contingent on the effective removal of <span class="hlt">cloud</span> and <span class="hlt">cloud</span> shadow from satellite images. We develop a novel algorithm to <span class="hlt">identify</span> and classify <span class="hlt">clouds</span> and <span class="hlt">cloud</span> shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of <span class="hlt">Cloud</span> and Shadow. The method uses neural networks to determine <span class="hlt">cloud</span>, <span class="hlt">cloud</span>-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality <span class="hlt">cloud</span> and <span class="hlt">cloud</span>-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for cloudsmore » (0.8% and 0.9%, respectively), substantially lower omission error for <span class="hlt">cloud</span>-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the <span class="hlt">cloud</span> and <span class="hlt">cloud</span>-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4896687','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4896687"><span><span class="hlt">Clouds</span> at Barbados are representative of <span class="hlt">clouds</span> across the trade wind regions in observations and climate models</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Nuijens, Louise</p> <p>2016-01-01</p> <p>Trade wind regions cover most of the tropical oceans, and the prevailing <span class="hlt">cloud</span> <span class="hlt">type</span> is shallow cumulus. These small <span class="hlt">clouds</span> are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these <span class="hlt">clouds</span> in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that <span class="hlt">clouds</span> in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados <span class="hlt">Cloud</span> Observatory are relevant to <span class="hlt">clouds</span> across the tropics. The same methods are applied to climate models to evaluate the simulated <span class="hlt">clouds</span>. The models generally capture the <span class="hlt">cloud</span> radiative effect, but underestimate <span class="hlt">cloud</span> cover and show an array of <span class="hlt">cloud</span> vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of <span class="hlt">cloud</span> and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to <span class="hlt">cloud</span> feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection. PMID:27185925</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27185925','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27185925"><span><span class="hlt">Clouds</span> at Barbados are representative of <span class="hlt">clouds</span> across the trade wind regions in observations and climate models.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Medeiros, Brian; Nuijens, Louise</p> <p>2016-05-31</p> <p>Trade wind regions cover most of the tropical oceans, and the prevailing <span class="hlt">cloud</span> <span class="hlt">type</span> is shallow cumulus. These small <span class="hlt">clouds</span> are parameterized by climate models, and changes in their radiative effects strongly and directly contribute to the spread in estimates of climate sensitivity. This study investigates the structure and variability of these <span class="hlt">clouds</span> in observations and climate models. The study builds upon recent detailed model evaluations using observations from the island of Barbados. Using a dynamical regimes framework, satellite and reanalysis products are used to compare the Barbados region and the broader tropics. It is shown that <span class="hlt">clouds</span> in the Barbados region are similar to those across the trade wind regions, implying that observational findings from the Barbados <span class="hlt">Cloud</span> Observatory are relevant to <span class="hlt">clouds</span> across the tropics. The same methods are applied to climate models to evaluate the simulated <span class="hlt">clouds</span>. The models generally capture the <span class="hlt">cloud</span> radiative effect, but underestimate <span class="hlt">cloud</span> cover and show an array of <span class="hlt">cloud</span> vertical structures. Some models show strong biases in the environment of the Barbados region in summer, weakening the connection between the regional biases and those across the tropics. Even bearing that limitation in mind, it is shown that covariations of <span class="hlt">cloud</span> and environmental properties in the models are inconsistent with observations. The models tend to misrepresent sensitivity to moisture variations and inversion characteristics. These model errors are likely connected to <span class="hlt">cloud</span> feedback in climate projections, and highlight the importance of the representation of shallow cumulus convection.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1454808-challenge-identifying-controls-cloud-properties-precipitation-onset-cumulus-congestus-sampled-during-mc3e','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1454808-challenge-identifying-controls-cloud-properties-precipitation-onset-cumulus-congestus-sampled-during-mc3e"><span>The Challenge of <span class="hlt">Identifying</span> Controls on <span class="hlt">Cloud</span> Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Mechem, David B.; Giangrande, Scott E.</p> <p>2018-03-01</p> <p>Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective <span class="hlt">Clouds</span> Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of <span class="hlt">cloud</span> fraction, precipitation area fraction, and evolution of <span class="hlt">cloud</span> topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper <span class="hlt">clouds</span>, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled <span class="hlt">cloud</span> properties (in particular, mean <span class="hlt">cloud</span> buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of <span class="hlt">cloud</span> systems by combining observational sampling of time–varying three–dimensional meteorological quantities and <span class="hlt">cloud</span> properties, along with detailed representation of <span class="hlt">cloud</span> microphysical and dynamical processes from numerical models.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1454808-challenge-identifying-controls-cloud-properties-precipitation-onset-cumulus-congestus-sampled-during-mc3e','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1454808-challenge-identifying-controls-cloud-properties-precipitation-onset-cumulus-congestus-sampled-during-mc3e"><span>The Challenge of <span class="hlt">Identifying</span> Controls on <span class="hlt">Cloud</span> Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Mechem, David B.; Giangrande, Scott E.</p> <p></p> <p>Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective <span class="hlt">Clouds</span> Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of <span class="hlt">cloud</span> fraction, precipitation area fraction, and evolution of <span class="hlt">cloud</span> topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper <span class="hlt">clouds</span>, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled <span class="hlt">cloud</span> properties (in particular, mean <span class="hlt">cloud</span> buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of <span class="hlt">cloud</span> systems by combining observational sampling of time–varying three–dimensional meteorological quantities and <span class="hlt">cloud</span> properties, along with detailed representation of <span class="hlt">cloud</span> microphysical and dynamical processes from numerical models.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRD..123.3126M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRD..123.3126M"><span>The Challenge of <span class="hlt">Identifying</span> Controls on <span class="hlt">Cloud</span> Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mechem, David B.; Giangrande, Scott E.</p> <p>2018-03-01</p> <p>Controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large-eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective <span class="hlt">Clouds</span> Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of <span class="hlt">cloud</span> fraction, precipitation area fraction, and evolution of <span class="hlt">cloud</span> top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper <span class="hlt">clouds</span>, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled <span class="hlt">cloud</span> properties (in particular, mean <span class="hlt">cloud</span> buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of <span class="hlt">cloud</span> systems by combining observational sampling of time-varying three-dimensional meteorological quantities and <span class="hlt">cloud</span> properties, along with detailed representation of <span class="hlt">cloud</span> microphysical and dynamical processes from numerical models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AnRFM..49..145M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AnRFM..49..145M"><span><span class="hlt">Cloud</span>-Top Entrainment in Stratocumulus <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mellado, Juan Pedro</p> <p>2017-01-01</p> <p><span class="hlt">Cloud</span> entrainment, the mixing between cloudy and clear air at the boundary of <span class="hlt">clouds</span>, constitutes one paradigm for the relevance of small scales in the Earth system: By regulating <span class="hlt">cloud</span> lifetimes, meter- and submeter-scale processes at <span class="hlt">cloud</span> boundaries can influence planetary-scale properties. Understanding <span class="hlt">cloud</span> entrainment is difficult given the complexity and diversity of the associated phenomena, which include turbulence entrainment within a stratified medium, convective instabilities driven by radiative and evaporative cooling, shear instabilities, and <span class="hlt">cloud</span> microphysics. Obtaining accurate data at the required small scales is also challenging, for both simulations and measurements. During the past few decades, however, high-resolution simulations and measurements have greatly advanced our understanding of the main mechanisms controlling <span class="hlt">cloud</span> entrainment. This article reviews some of these advances, focusing on stratocumulus <span class="hlt">clouds</span>, and indicates remaining challenges.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910052737&hterms=cold+chain&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dcold%2Bchain','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910052737&hterms=cold+chain&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dcold%2Bchain"><span>Chemical abundances in cold, dark interstellar <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Irvine, William M.; Kaifu, Norio; Ohishi, Masatoshi</p> <p>1991-01-01</p> <p>Current tabulations are presented of the entire range of known interstellar molecules, giving attention to that subset which has been <span class="hlt">identified</span> in the cold, dark interstellar <span class="hlt">clouds</span> out of which the sun has been suggested to have formed. The molecular abundances of two such <span class="hlt">clouds</span>, Taurus Molecular <span class="hlt">Cloud</span> 1 and Lynd's 134N, exhibit prepossessing chemical differences despite considerable physical similarities. This discrepancy may be accounted for by the two <span class="hlt">clouds</span>' differing evolutionary stages. Two novel classes of interstellar molecules are noted: sulfur-terminated carbon chains and silicon-terminated ones.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19950004204','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19950004204"><span>The sensitivity of tropospheric chemistry to <span class="hlt">cloud</span> interactions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jonson, Jan E.; Isaksen, Ivar S. A.</p> <p>1994-01-01</p> <p><span class="hlt">Clouds</span>, although only occupying a relatively small fraction of the troposphere volume, can have a substantial impact on the chemistry of the troposphere. In newly formed <span class="hlt">clouds</span>, or in <span class="hlt">clouds</span> with air rapidly flowing through, the chemistry is expected to be far more active than in aged <span class="hlt">clouds</span> with stagnant air. Thus, frequent cycling of air through shortlived <span class="hlt">clouds</span>, i.e. cumulus <span class="hlt">clouds</span>, is likely to be a much more efficient media for altering the composition of the atmosphere than an extensive <span class="hlt">cloud</span> cover i.e. frontal <span class="hlt">cloud</span> systems. The impact of <span class="hlt">clouds</span> is tested out in a 2-D channel model encircling the globe in a latitudinal belt from 30 to 60 deg N. The model contains a detailed gas phase chemistry. In addition physiochemical interactions between the gas and aqueous phases are included. For species as H2O2, CH2O, O3, and SO2, Henry's law equilibria are assumed, whereas HNO3 and H2SO4 are regarded as completed dissolved in the aqueous phase. Absorption of HO2 and OH is assumed to be mass-transport limited. The chemistry of the aqueous phase is characterized by rapid cycling of odd hydrogen, (H2O2, HO2, and OH). O2(-) (produced through dissociation of HO2) reacting with dissolved O3 is a major source of OH in the aqueous phase. This reaction can be a significant sink for O3 in the troposphere. In the interstitial <span class="hlt">cloud</span> air, odd hydrogen is depleted, whereas NO(x) remains in the gas phase, thus reducing ozone production due to the reaction between NO and HO2. Our calculations give markedly lower ozone levels when <span class="hlt">cloud</span> interactions are included. This may in part explain the overpredictions of ozone levels often experienced in models neglecting <span class="hlt">cloud</span> chemical interactions. In the present study, the existence of <span class="hlt">clouds</span>, <span class="hlt">cloud</span> <span class="hlt">types</span>, and their lifetimes are modeled as pseudo random variables. Such pseudo random sequences are in reality deterministic and may, given the same starting values, be reproduced. The effects of <span class="hlt">cloud</span> interactions on the overall chemistry of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014JGRD..119.5410A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014JGRD..119.5410A"><span>Evaluating the impact of aerosol particles above <span class="hlt">cloud</span> on <span class="hlt">cloud</span> optical depth retrievals from MODIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alfaro-Contreras, Ricardo; Zhang, Jianglong; Campbell, James R.; Holz, Robert E.; Reid, Jeffrey S.</p> <p>2014-05-01</p> <p>Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) <span class="hlt">cloud</span> optical depth (COD) retrievals (0.86 versus 1.6 µm), we evaluate the impact of above-<span class="hlt">cloud</span> smoke aerosol particles on near-IR (0.86 µm) COD retrievals. Aerosol Index (AI) from the collocated Ozone Monitoring Instrument (OMI) are used to <span class="hlt">identify</span> above-<span class="hlt">cloud</span> aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African subcontinent. Collocated <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation data constrain <span class="hlt">cloud</span> phase and provide contextual above-<span class="hlt">cloud</span> aerosol optical depth. The frequency of occurrence of above-<span class="hlt">cloud</span> aerosol events is depicted on a global scale for the spring and summer seasons from OMI and <span class="hlt">Cloud</span> Aerosol Lidar with Orthogonal Polarization. Seasonal frequencies for smoke-over-<span class="hlt">cloud</span> off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10-20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS 0.86 and 1.6 µm channels are vulnerable to radiance attenuation due to dust particles. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus <span class="hlt">clouds</span> and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-<span class="hlt">cloud</span> aerosol events for future studies using standard MODIS <span class="hlt">cloud</span> products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS 1.6 µm COD products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018MNRAS.476.2209G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018MNRAS.476.2209G"><span>A comparison of shock-<span class="hlt">cloud</span> and wind-<span class="hlt">cloud</span> interactions: effect of increased <span class="hlt">cloud</span> density contrast on <span class="hlt">cloud</span> evolution</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Goldsmith, K. J. A.; Pittard, J. M.</p> <p>2018-05-01</p> <p>The similarities, or otherwise, of a shock or wind interacting with a <span class="hlt">cloud</span> of density contrast χ = 10 were explored in a previous paper. Here, we investigate such interactions with <span class="hlt">clouds</span> of higher density contrast. We compare the adiabatic hydrodynamic interaction of a Mach 10 shock with a spherical <span class="hlt">cloud</span> of χ = 103 with that of a <span class="hlt">cloud</span> embedded in a wind with identical parameters to the post-shock flow. We find that initially there are only minor morphological differences between the shock-<span class="hlt">cloud</span> and wind-<span class="hlt">cloud</span> interactions, compared to when χ = 10. However, once the transmitted shock exits the <span class="hlt">cloud</span>, the development of a turbulent wake and fragmentation of the <span class="hlt">cloud</span> differs between the two simulations. On increasing the wind Mach number, we note the development of a thin, smooth tail of <span class="hlt">cloud</span> material, which is then disrupted by the fragmentation of the <span class="hlt">cloud</span> core and subsequent `mass-loading' of the flow. We find that the normalized <span class="hlt">cloud</span> mixing time (tmix) is shorter at higher χ. However, a strong Mach number dependence on tmix and the normalized <span class="hlt">cloud</span> drag time, t_{drag}^' }, is not observed. Mach-number-dependent values of tmix and t_{drag}^' } from comparable shock-<span class="hlt">cloud</span> interactions converge towards the Mach-number-independent time-scales of the wind-<span class="hlt">cloud</span> simulations. We find that high χ <span class="hlt">clouds</span> can be accelerated up to 80-90 per cent of the wind velocity and travel large distances before being significantly mixed. However, complete mixing is not achieved in our simulations and at late times the flow remains perturbed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A21B0040P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A21B0040P"><span>Assimilation of Satellite to Improve <span class="hlt">Cloud</span> Simulation in Wrf Model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Park, Y. H.; Pour Biazar, A.; McNider, R. T.</p> <p>2012-12-01</p> <p>A simple approach has been introduced to improve <span class="hlt">cloud</span> simulation spatially and temporally in a meteorological model. The first step for this approach is to use Geostationary Operational Environmental Satellite (GOES) observations to <span class="hlt">identify</span> <span class="hlt">clouds</span> and estimate the <span class="hlt">clouds</span> structure. Then by comparing GOES observations to model <span class="hlt">cloud</span> field, we <span class="hlt">identify</span> areas in which model has under-predicted or over-predicted <span class="hlt">clouds</span>. Next, by introducing subsidence in areas with over-prediction and lifting in areas with under-prediction, erroneous <span class="hlt">clouds</span> are removed and new <span class="hlt">clouds</span> are formed. The technique estimates a vertical velocity needed for the <span class="hlt">cloud</span> correction and then uses a one dimensional variation schemes (1D_Var) to calculate the horizontal divergence components and the consequent horizontal wind components needed to sustain such vertical velocity. Finally, the new horizontal winds are provided as a nudging field to the model. This nudging provides the dynamical support needed to create/clear <span class="hlt">clouds</span> in a sustainable manner. The technique was implemented and tested in the Weather Research and Forecast (WRF) Model and resulted in substantial improvement in model simulated <span class="hlt">clouds</span>. Some of the results are presented here.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....1614231B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....1614231B"><span><span class="hlt">Cloud</span> photogrammetry with dense stereo for fisheye cameras</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beekmans, Christoph; Schneider, Johannes; Läbe, Thomas; Lennefer, Martin; Stachniss, Cyrill; Simmer, Clemens</p> <p>2016-11-01</p> <p>We present a novel approach for dense 3-D <span class="hlt">cloud</span> reconstruction above an area of 10 × 10 km2 using two hemispheric sky imagers with fisheye lenses in a stereo setup. We examine an epipolar rectification model designed for fisheye cameras, which allows the use of efficient out-of-the-box dense matching algorithms designed for classical pinhole-<span class="hlt">type</span> cameras to search for correspondence information at every pixel. The resulting dense point <span class="hlt">cloud</span> allows to recover a detailed and more complete <span class="hlt">cloud</span> morphology compared to previous approaches that employed sparse feature-based stereo or assumed geometric constraints on the <span class="hlt">cloud</span> field. Our approach is very efficient and can be fully automated. From the obtained 3-D shapes, <span class="hlt">cloud</span> dynamics, size, motion, <span class="hlt">type</span> and spacing can be derived, and used for radiation closure under cloudy conditions, for example. Fisheye lenses follow a different projection function than classical pinhole-<span class="hlt">type</span> cameras and provide a large field of view with a single image. However, the computation of dense 3-D information is more complicated and standard implementations for dense 3-D stereo reconstruction cannot be easily applied. Together with an appropriate camera calibration, which includes internal camera geometry, global position and orientation of the stereo camera pair, we use the correspondence information from the stereo matching for dense 3-D stereo reconstruction of <span class="hlt">clouds</span> located around the cameras. We implement and evaluate the proposed approach using real world data and present two case studies. In the first case, we validate the quality and accuracy of the method by comparing the stereo reconstruction of a stratocumulus layer with reflectivity observations measured by a <span class="hlt">cloud</span> radar and the <span class="hlt">cloud</span>-base height estimated from a Lidar-ceilometer. The second case analyzes a rapid cumulus evolution in the presence of strong wind shear.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_10");'>10</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li class="active"><span>12</span></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_12 --> <div id="page_13" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="241"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMIN51C..02N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMIN51C..02N"><span><span class="hlt">Cloud</span> Computing for Geosciences--Geo<span class="hlt">Cloud</span> for standardized geospatial service platforms (Invited)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nebert, D. D.; Huang, Q.; Yang, C.</p> <p>2013-12-01</p> <p>The 21st century geoscience faces challenges of Big Data, spike computing requirements (e.g., when natural disaster happens), and sharing resources through cyberinfrastructure across different organizations (Yang et al., 2011). With flexibility and cost-efficiency of computing resources a primary concern, <span class="hlt">cloud</span> computing emerges as a promising solution to provide core capabilities to address these challenges. Many governmental and federal agencies are adopting <span class="hlt">cloud</span> technologies to cut costs and to make federal IT operations more efficient (Huang et al., 2010). However, it is still difficult for geoscientists to take advantage of the benefits of <span class="hlt">cloud</span> computing to facilitate the scientific research and discoveries. This presentation reports using Geo<span class="hlt">Cloud</span> to illustrate the process and strategies used in building a common platform for geoscience communities to enable the sharing, integration of geospatial data, information and knowledge across different domains. Geo<span class="hlt">Cloud</span> is an annual incubator project coordinated by the Federal Geographic Data Committee (FGDC) in collaboration with the U.S. General Services Administration (GSA) and the Department of Health and Human Services. It is designed as a staging environment to test and document the deployment of a common Geo<span class="hlt">Cloud</span> community platform that can be implemented by multiple agencies. With these standardized virtual geospatial servers, a variety of government geospatial applications can be quickly migrated to the <span class="hlt">cloud</span>. In order to achieve this objective, multiple projects are nominated each year by federal agencies as existing public-facing geospatial data services. From the initial candidate projects, a set of common operating system and software requirements was <span class="hlt">identified</span> as the baseline for platform as a service (PaaS) packages. Based on these developed common platform packages, each project deploys and monitors its web application, develops best practices, and documents cost and performance information. This</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045337&hterms=condensation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dcondensation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045337&hterms=condensation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dcondensation"><span>Measurements of <span class="hlt">cloud</span> condensation nuclei spectra within maritime cumulus <span class="hlt">cloud</span> droplets: Implications for mixing processes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Twohy, Cynthia H.; Hudson, James G.</p> <p>1995-01-01</p> <p>In a <span class="hlt">cloud</span> formed during adiabatic expansion, the droplet size distribution will be systematically related to the critical supersaturation of the <span class="hlt">cloud</span> condensation nuclei (CNN), but this relationship can be complicated in entraining <span class="hlt">clouds</span>. Useful information about <span class="hlt">cloud</span> processes, such as mixing, can be obtained from direct measurements of the CNN involved in droplet nucleation. This was accomplished by interfacing two instruments for a series of flights in maritime cumulus <span class="hlt">clouds</span>. One instrument, the counterflow virtual impactor, collected <span class="hlt">cloud</span> droplets, and the nonvolatile residual nuclei of the droplets was then passed to a CCN spectrometer, which measured the critical supersaturation (S(sub c)) spectrum of the droplet nuclei. The measured S(sub c) spectra of the droplet nuclei were compared with the S(sub c) spectra of ambient aerosol particles in order to <span class="hlt">identify</span> which CCN were actually incorporated into droplets and to determine when mixing processes were active at different <span class="hlt">cloud</span> levels. The droplet nuclei nearly always exhibited lower median S(sub c)'s than the ambient aerosol, as expected since droplets nucleate perferentially on particles with lower critical supersaturations. Critical supersaturation spectra from nuclei of droplets near <span class="hlt">cloud</span> base were similar to those predicted for <span class="hlt">cloud</span> regions formed adiabatically, but spectra of droplet nuclei from middle <span class="hlt">cloud</span> levels showed some evidence that mixing had occurred. Near <span class="hlt">cloud</span> top, the greatest variation in the spectra of the droplet nuclei was observed, and nuclei with high S(sub c)'s were sometimes present even within relatively large droplets. This suggests that the extent of mixing increases with height in cumulus <span class="hlt">clouds</span> and that inhomogeneous mixing may be important near <span class="hlt">cloud</span> top. These promising initial results suggest improvements to the experimental technique that will permit more quantitative results in future experiments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22346714','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22346714"><span>An Improved <span class="hlt">Cloud</span> Classification Algorithm for China's FY-2C Multi-Channel Images Using Artificial Neural Network.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Yu; Xia, Jun; Shi, Chun-Xiang; Hong, Yang</p> <p>2009-01-01</p> <p>The crowning objective of this research was to <span class="hlt">identify</span> a better <span class="hlt">cloud</span> classification method to upgrade the current window-based clustering algorithm used operationally for China's first operational geostationary meteorological satellite FengYun-2C (FY-2C) data. First, the capabilities of six widely-used Artificial Neural Network (ANN) methods are analyzed, together with the comparison of two other methods: Principal Component Analysis (PCA) and a Support Vector Machine (SVM), using 2864 <span class="hlt">cloud</span> samples manually collected by meteorologists in June, July, and August in 2007 from three FY-2C channel (IR1, 10.3-11.3 μm; IR2, 11.5-12.5 μm and WV 6.3-7.6 μm) imagery. The result shows that: (1) ANN approaches, in general, outperformed the PCA and the SVM given sufficient training samples and (2) among the six ANN networks, higher <span class="hlt">cloud</span> classification accuracy was obtained with the Self-Organizing Map (SOM) and Probabilistic Neural Network (PNN). Second, to compare the ANN methods to the present FY-2C operational algorithm, this study implemented SOM, one of the best ANN network <span class="hlt">identified</span> from this study, as an automated <span class="hlt">cloud</span> classification system for the FY-2C multi-channel data. It shows that SOM method has improved the results greatly not only in pixel-level accuracy but also in <span class="hlt">cloud</span> patch-level classification by more accurately <span class="hlt">identifying</span> <span class="hlt">cloud</span> <span class="hlt">types</span> such as cumulonimbus, cirrus and <span class="hlt">clouds</span> in high latitude. Findings of this study suggest that the ANN-based classifiers, in particular the SOM, can be potentially used as an improved Automated <span class="hlt">Cloud</span> Classification Algorithm to upgrade the current window-based clustering method for the FY-2C operational products.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170002305','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170002305"><span>CATS Aerosol <span class="hlt">Typing</span> and Future Directions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>McGill, Matt; Yorks, John; Scott, Stan; Palm, Stephen; Hlavka, Dennis; Hart, William; Nowottnick, Ed; Selmer, Patrick; Kupchock, Andrew; Midzak, Natalie; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20170002305'); toggleEditAbsImage('author_20170002305_show'); toggleEditAbsImage('author_20170002305_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20170002305_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20170002305_hide"></p> <p>2016-01-01</p> <p>The <span class="hlt">Cloud</span> Aerosol Transport System (CATS), launched in January of 2015, is a lidar remote sensing instrument that will provide range-resolved profile measurements of atmospheric aerosols and <span class="hlt">clouds</span> from the International Space Station (ISS). CATS is intended to operate on-orbit for at least six months, and up to three years. Status of CATS Level 2 and Plans for the Future:Version. 1. Aerosol <span class="hlt">Typing</span> (ongoing): Mode 1: L1B data released later this summer; L2 data released shortly after; <span class="hlt">Identify</span> algorithm biases (ex. striping, FOV (field of view) biases). Mode 2: Processed Released Currently working on correcting algorithm issues. Version 2 Aerosol <span class="hlt">Typing</span> (Fall, 2016): Implementation of version 1 modifications Integrate GEOS-5 aerosols for <span class="hlt">typing</span> guidance for non spherical aerosols. Version 3 Aerosol <span class="hlt">Typing</span> (2017): Implementation of 1-D Var Assimilation into GEOS-5 Dynamic lidar ratio that will evolve in conjunction with simulated aerosol mixtures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A42F..01M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A42F..01M"><span>The Dependence of Homo- and Heterogeneously Formed Cirrus <span class="hlt">Clouds</span> on Latitude, Season and Surface-<span class="hlt">type</span> based on a New CALIPSO Remote Sensing Method</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mitchell, D. L.; Garnier, A.; Mejia, J.; Avery, M. A.; Erfani, E.</p> <p>2016-12-01</p> <p>A new CALIPSO infrared retrieval method sensitive to small ice crystals has been developed to measure the temperature dependence of the layer-average number concentration N, effective diameter De and ice water content in single-layer cirrus <span class="hlt">clouds</span> (one <span class="hlt">cloud</span> layer in the atmospheric column) that have optical depths between 0.3 and 3.0 and <span class="hlt">cloud</span> base temperature T < 235 K. While retrievals of low N are not accurate, mid-to-high N can be retrieved with much lower uncertainty. This enables the retrieval to estimate the dominant ice nucleation mechanism (homo- or heterogeneous, henceforth hom and het) though which the cirrus formed. Based on N, hom or het cirrus can be estimated as a function of temperature, season, latitude and surface <span class="hlt">type</span>. The retrieved properties noted above compare favorably with spatial-temporal coincident cirrus <span class="hlt">cloud</span> in situ measurements from SPARTICUS case studies as well as the extensive in situ cirrus data set of Krämer et al. (2009, ACP). For our cirrus <span class="hlt">cloud</span> selection, these retrievals show a pronounced seasonal cycle in the N. Hemisphere over land north of 30°N latitude in terms of both <span class="hlt">cloud</span> amount and microphysics, with greater <span class="hlt">cloud</span> cover, higher N and smaller De during the winter season. We postulate that this is partially due to the seasonal cycle of deep convection that replenishes the supply of ice nuclei (IN) at cirrus levels, with hom more likely when deep convection is absent. Over oceans, heterogeneous ice nucleation appears to prevail based on the lower N and higher De observed. Due to the relatively smooth ocean surface, lower amplitude atmospheric waves at cirrus <span class="hlt">cloud</span> levels are expected. Over land outside the tropics during winter, hom cirrus tend to occur over mountainous terrain, possibly due to lower IN concentrations and stronger, more sustained updrafts in mountain-induced waves. Over pristine Antarctica, IN concentrations are minimal and the terrain near the coast is often high and rugged, allowing hom to dominate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A11B1884R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A11B1884R"><span>Global Measurements of Optically Thin Cirrus <span class="hlt">Clouds</span> Using CALIOP</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ryan, R. A.; Avery, M. A.; Vaughan, M.</p> <p>2017-12-01</p> <p>Optically thin cirrus <span class="hlt">clouds</span>, defined here as cold <span class="hlt">clouds</span> consisting of randomly oriented ice crystals and having optical depths (τ) less than 0.3, are difficult to measure accurately. Thin cirrus <span class="hlt">clouds</span> have been shown to have a net warming effect on the globe but, because passive instruments are not sensitive to optically thin <span class="hlt">clouds</span>, the occurrence frequency of thin cirrus is greatly underestimated in historical passive sensor <span class="hlt">cloud</span> climatology. One major strength of <span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization (CALIOP) is its ability to detect these thin cirrus <span class="hlt">clouds</span>, thus filling an important missing piece in the historical data record. This poster examines multiple years of CALIOP Level 2 data, focusing on those CALIOP retrievals <span class="hlt">identified</span> as being optically thin (τ < 0.3), having a cold centroid temperature (TC < -40°C), and consisting solely of randomly oriented ice crystals. Using this definition, thin cirrus are <span class="hlt">identified</span> and counted globally within each season. By examining the spatial, and seasonal distributions of these thin <span class="hlt">clouds</span> we hope to gain a better understanding of how thin cirrus affect the atmosphere. Understanding when and where these <span class="hlt">clouds</span> form and persist in the global atmosphere is the topic and focus of the presented poster.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27294176','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27294176"><span>Benchmark data for <span class="hlt">identifying</span> multi-functional <span class="hlt">types</span> of membrane proteins.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan</p> <p>2016-09-01</p> <p><span class="hlt">Identifying</span> membrane proteins and their multi-functional <span class="hlt">types</span> is an indispensable yet challenging topic in proteomics and bioinformatics. In this article, we provide data that are used for training and testing Mem-ADSVM (Wan et al., 2016. "Mem-ADSVM: a two-layer multi-label predictor for <span class="hlt">identifying</span> multi-functional <span class="hlt">types</span> of membrane proteins" [1]), a two-layer multi-label predictor for predicting multi-functional <span class="hlt">types</span> of membrane proteins.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/22518485-embedded-clusters-large-magellanic-cloud-using-vista-magellanic-clouds-survey','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/22518485-embedded-clusters-large-magellanic-cloud-using-vista-magellanic-clouds-survey"><span>EMBEDDED CLUSTERS IN THE LARGE MAGELLANIC <span class="hlt">CLOUD</span> USING THE VISTA MAGELLANIC <span class="hlt">CLOUDS</span> SURVEY</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Romita, Krista; Lada, Elizabeth; Cioni, Maria-Rosa, E-mail: k.a.romita@ufl.edu, E-mail: elada@ufl.edu, E-mail: mcioni@aip.de</p> <p></p> <p>We present initial results of the first large-scale survey of embedded star clusters in molecular <span class="hlt">clouds</span> in the Large Magellanic <span class="hlt">Cloud</span> (LMC) using near-infrared imaging from the Visible and Infrared Survey Telescope for Astronomy Magellanic <span class="hlt">Clouds</span> Survey. We explored a ∼1.65 deg{sup 2} area of the LMC, which contains the well-known star-forming region 30 Doradus as well as ∼14% of the galaxy’s CO <span class="hlt">clouds</span>, and <span class="hlt">identified</span> 67 embedded cluster candidates, 45 of which are newly discovered as clusters. We have determined the sizes, luminosities, and masses for these embedded clusters, examined the star formation rates (SFRs) of their corresponding molecularmore » <span class="hlt">clouds</span>, and made a comparison between the LMC and the Milky Way. Our preliminary results indicate that embedded clusters in the LMC are generally larger, more luminous, and more massive than those in the local Milky Way. We also find that the surface densities of both embedded clusters and molecular <span class="hlt">clouds</span> is ∼3 times higher than in our local environment, the embedded cluster mass surface density is ∼40 times higher, the SFR is ∼20 times higher, and the star formation efficiency is ∼10 times higher. Despite these differences, the SFRs of the LMC molecular <span class="hlt">clouds</span> are consistent with the SFR scaling law presented in Lada et al. This consistency indicates that while the conditions of embedded cluster formation may vary between environments, the overall process within molecular <span class="hlt">clouds</span> may be universal.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A33D0200C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A33D0200C"><span>A multi-satellite analysis of the direct radiative effects of absorbing aerosols above <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, Y. Y.; Christopher, S. A.</p> <p>2015-12-01</p> <p>Radiative effects of absorbing aerosols above liquid water <span class="hlt">clouds</span> in the southeast Atlantic as a function of fire sources are investigated using A-Train data coupled with the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard Suomi National Polar-orbiting Partnership (Suomi NPP). Both the VIIRS Active Fire product and the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies product (MYD14) are used to <span class="hlt">identify</span> the biomass burning fire origin in southern Africa. The <span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to assess the aerosol <span class="hlt">type</span>, aerosol altitude, and <span class="hlt">cloud</span> altitude. We use back trajectory information, wind data, and the Fire Locating and Modeling of Burning Emissions (FLAMBE) product to infer the transportation of aerosols from the fire source to the CALIOP swath in the southeast Atlantic during austral winter.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000JAtS...57.2591R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000JAtS...57.2591R"><span>Combustion Organic Aerosol as <span class="hlt">Cloud</span> Condensation Nuclei in Ship Tracks.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Russell, Lynn M.; Noone, Kevin J.; Ferek, Ronald J.; Pockalny, Robert A.; Flagan, Richard C.; Seinfeld, John H.</p> <p>2000-08-01</p> <p>Polycyclic aromatic hydrocarbons (PAHs) have been sampled in marine stratiform <span class="hlt">clouds</span> to <span class="hlt">identify</span> the contribution of anthropogenic combustion emissions in activation of aerosol to <span class="hlt">cloud</span> droplets. The Monterey Area Ship Track experiment provided an opportunity to acquire data on the role of organic compounds in ambient <span class="hlt">clouds</span> and in ship tracks <span class="hlt">identified</span> in satellite images. Identification of PAHs in <span class="hlt">cloud</span> droplet residual samples indicates that several PAHs are present in <span class="hlt">cloud</span> condensation nuclei in anthropogenically influenced air and do result in activated droplets in <span class="hlt">cloud</span>. These results establish the presence of combustion products, such as PAHs, in submicrometer aerosols in anthropogenically influenced marine air, with enhanced concentrations in air polluted by ship effluent. The presence of PAHs in droplet residuals in anthropogenically influenced air masses indicates that some fraction of those combustion products is present in the <span class="hlt">cloud</span> condensation nuclei that activate in <span class="hlt">cloud</span>. Although a sufficient mass of droplet residuals was not collected to establish a similar role for organics from measurements in satellite-<span class="hlt">identified</span> ship tracks, the available evidence from the fraction of organics present in the interstitial aerosol is consistent with part of the organic fraction partitioning to the droplet population. In addition, the probability that a compound will be found in <span class="hlt">cloud</span> droplets rather than in the unactivated aerosol and the compound's water solubility are compared. The PAHs studied are only weakly soluble in water, but most of the sparse data collected support more soluble compounds having a higher probability of activation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A51G0147C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A51G0147C"><span>In situ observations of Arctic <span class="hlt">cloud</span> properties across the Beaufort Sea marginal ice zone</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Corr, C.; Moore, R.; Winstead, E.; Thornhill, K. L., II; Crosbie, E.; Ziemba, L. D.; Beyersdorf, A. J.; Chen, G.; Martin, R.; Shook, M.; Corbett, J.; Smith, W. L., Jr.; Anderson, B. E.</p> <p>2016-12-01</p> <p><span class="hlt">Clouds</span> play an important role in Arctic climate. This is particularly true over the Arctic Ocean where feedbacks between <span class="hlt">clouds</span> and sea-ice impact the surface radiation budget through modifications of sea-ice extent, ice thickness, <span class="hlt">cloud</span> base height, and <span class="hlt">cloud</span> cover. This work summarizes measurements of Arctic <span class="hlt">cloud</span> properties made aboard the NASA C-130 aircraft over the Beaufort Sea during ARISE (Arctic Radiation - IceBridge Sea&Ice Experiment) in September 2014. The influence of surface-<span class="hlt">type</span> on <span class="hlt">cloud</span> properties is also investigated. Specifically, liquid water content (LWC), droplet concentrations, and droplet size distributions are compared for <span class="hlt">clouds</span> sampled over three distinct regimes in the Beaufort Sea: 1) open water, 2) the marginal ice zone, and 3) sea-ice. Regardless of surface <span class="hlt">type</span>, nearly all <span class="hlt">clouds</span> intercepted during ARISE were liquid-phase <span class="hlt">clouds</span>. However, differences in droplet size distributions and concentrations were evident for the surface <span class="hlt">types</span>; <span class="hlt">clouds</span> over the MIZ and sea-ice generally had fewer and larger droplets compared to those over open water. The potential implication these results have for understanding <span class="hlt">cloud</span>-surface albedo climate feedbacks in Arctic are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ACP....1712219C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ACP....1712219C"><span>Classification of Arctic, midlatitude and tropical <span class="hlt">clouds</span> in the mixed-phase temperature regime</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Costa, Anja; Meyer, Jessica; Afchine, Armin; Luebke, Anna; Günther, Gebhard; Dorsey, James R.; Gallagher, Martin W.; Ehrlich, Andre; Wendisch, Manfred; Baumgardner, Darrel; Wex, Heike; Krämer, Martina</p> <p>2017-10-01</p> <p>The degree of glaciation of mixed-phase <span class="hlt">clouds</span> constitutes one of the largest uncertainties in climate prediction. In order to better understand <span class="hlt">cloud</span> glaciation, <span class="hlt">cloud</span> spectrometer observations are presented in this paper, which were made in the mixed-phase temperature regime between 0 and -38 °C (273 to 235 K), where <span class="hlt">cloud</span> particles can either be frozen or liquid. The extensive data set covers four airborne field campaigns providing a total of 139 000 1 Hz data points (38.6 h within <span class="hlt">clouds</span>) over Arctic, midlatitude and tropical regions. We develop algorithms, combining the information on number concentration, size and asphericity of the observed <span class="hlt">cloud</span> particles to classify four <span class="hlt">cloud</span> <span class="hlt">types</span>: liquid <span class="hlt">clouds</span>, <span class="hlt">clouds</span> in which liquid droplets and ice crystals coexist, fully glaciated <span class="hlt">clouds</span> after the Wegener-Bergeron-Findeisen process and <span class="hlt">clouds</span> where secondary ice formation occurred. We quantify the occurrence of these <span class="hlt">cloud</span> groups depending on the geographical region and temperature and find that liquid <span class="hlt">clouds</span> dominate our measurements during the Arctic spring, while <span class="hlt">clouds</span> dominated by the Wegener-Bergeron-Findeisen process are most common in midlatitude spring. The coexistence of liquid water and ice crystals is found over the whole mixed-phase temperature range in tropical convective towers in the dry season. Secondary ice is found at midlatitudes at -5 to -10 °C (268 to 263 K) and at higher altitudes, i.e. lower temperatures in the tropics. The distribution of the <span class="hlt">cloud</span> <span class="hlt">types</span> with decreasing temperature is shown to be consistent with the theory of evolution of mixed-phase <span class="hlt">clouds</span>. With this study, we aim to contribute to a large statistical database on <span class="hlt">cloud</span> <span class="hlt">types</span> in the mixed-phase temperature regime.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122..966Y','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122..966Y"><span>On the response of MODIS <span class="hlt">cloud</span> coverage to global mean surface air temperature</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Yue, Qing; Kahn, Brian H.; Fetzer, Eric J.; Wong, Sun; Frey, Richard; Meyer, Kerry G.</p> <p>2017-01-01</p> <p>The global surface temperature change (ΔTs) mediated <span class="hlt">cloud</span> cover response is directly related to <span class="hlt">cloud</span>-climate feedback. Using satellite remote sensing data to relate <span class="hlt">cloud</span> and climate requires a well-calibrated, stable, and consistent long-term <span class="hlt">cloud</span> data record. The Collection 5.1 (C5) Moderate Resolution Imaging Spectroradiometer (MODIS) <span class="hlt">cloud</span> observations have been widely used for this purpose. However, the MODIS data quality varies greatly with the surface <span class="hlt">type</span>, spectral region, <span class="hlt">cloud</span> <span class="hlt">type</span>, and time periods of study, which calls for additional caution when applying such data to studies on <span class="hlt">cloud</span> cover temporal trends and variability. Using 15 years of <span class="hlt">cloud</span> observations made by Terra and Aqua MODIS, we analyze the ΔTs-mediated <span class="hlt">cloud</span> cover response for different <span class="hlt">cloud</span> <span class="hlt">types</span> by linearly regressing the monthly anomaly of <span class="hlt">cloud</span> cover (ΔC) with the monthly anomaly of global Ts. The Collection 6 (C6) Aqua data exhibit a similar <span class="hlt">cloud</span> response to the long-term counterpart simulated by advanced climate models. A robust increase in altitude with increasing ΔTs is found for high <span class="hlt">clouds</span>, while a robust decrease of ΔC is noticed for optically thick low <span class="hlt">clouds</span>. The large differences between C5 and C6 results are from improvements in calibration and <span class="hlt">cloud</span> retrieval algorithms. The large positive <span class="hlt">cloud</span> cover responses with data after 2010 and the strong sensitivity to time period obtained from the Terra (C5 and C6) data are likely due to calibration drift that has not been corrected, suggesting that the previous estimate of the short-term <span class="hlt">cloud</span> cover response from the these data should be revisited.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010EGUGA..1211035J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010EGUGA..1211035J"><span>Optically thin ice <span class="hlt">clouds</span> in Arctic; Formation processes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jouan, Caroline; Pelon, Jacques; Girard, Eric; Blanchet, Jean-Pierre; Wobrock, Wolfram; Gayet, Jean-Franćois; Schwarzenböck, Alfons; Gultepe, Ismail; Delanoë, Julien; Mioche, Guillaume</p> <p>2010-05-01</p> <p>Arctic ice <span class="hlt">cloud</span> formation during winter is poorly understood mainly due to lack of observations and the remoteness of this region. Yet, their influence on Northern Hemisphere weather and climate is of paramount importance, and the modification of their properties, linked to aerosol-<span class="hlt">cloud</span> interaction processes, needs to be better understood. Large concentration of aerosols in the Arctic during winter is associated to long-range transport of anthropogenic aerosols from the mid-latitudes to the Arctic. Observations show that sulphuric acid coats most of these aerosols. Laboratory and in-situ measurements show that at cold temperature (< -30°C), acidic coating lowers the freezing point and deactivates ice nuclei (IN). Therefore, the IN concentration is reduced in these regions and there is less competition for the same available moisture. As a result, large ice crystals form in relatively small concentrations. It is hypothesized that the observed low concentration of large ice crystals in thin ice <span class="hlt">clouds</span> is linked to the acidification of aerosols. To check this, it is necessary to analyse <span class="hlt">cloud</span> properties in the Arctic. Extensive measurements from ground-based sites and satellite remote sensing (<span class="hlt">Cloud</span>Sat and CALIPSO) reveal the existence of two <span class="hlt">types</span> of extended optically thin ice <span class="hlt">clouds</span> (TICs) in the Arctic during the polar night and early spring. The first <span class="hlt">type</span> (TIC-1) is seen only by the lidar, but not the radar, and is found in pristine environment whereas the second <span class="hlt">type</span> (TIC-2) is detected by both sensors, and is associated with high concentration of aerosols, possibly anthropogenic. TIC-2 is characterized by a low concentration of ice crystals that are large enough to precipitate. To further investigate the interactions between TICs <span class="hlt">clouds</span> and aerosols, in-situ, airborne and satellite measurements of specific cases observed during the POLARCAT and ISDAC field experiments are analyzed. These two field campaigns took place respectively over the North Slope of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.A52B..07J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.A52B..07J"><span>Optically thin ice <span class="hlt">clouds</span> in Arctic : Formation processes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jouan, C.; Girard, E.; Pelon, J.; Blanchet, J.; Wobrock, W.; Gultepe, I.; Gayet, J.; Delanoë, J.; Mioche, G.; Adam de Villiers, R.</p> <p>2010-12-01</p> <p>Arctic ice <span class="hlt">cloud</span> formation during winter is poorly understood mainly due to lack of observations and the remoteness of this region. Their influence on Northern Hemisphere weather and climate is of paramount importance, and the modification of their properties, linked to aerosol-<span class="hlt">cloud</span> interaction processes, needs to be better understood. Large concentration of aerosols in the Arctic during winter is associated to long-range transport of anthropogenic aerosols from the mid-latitudes to the Arctic. Observations show that sulphuric acid coats most of these aerosols. Laboratory and in-situ measurements show that at cold temperature (<-30°C), acidic coating lowers the freezing point and deactivates ice nuclei (IN). Therefore, the IN concentration is reduced in these regions and there is less competition for the same available moisture. As a result, large ice crystals form in relatively small concentrations. It is hypothesized that the observed low concentration of large ice crystals in thin ice <span class="hlt">clouds</span> is linked to the acidification of aerosols. Extensive measurements from ground-based sites and satellite remote sensing (<span class="hlt">Cloud</span>Sat and CALIPSO) reveal the existence of two <span class="hlt">types</span> of extended optically thin ice <span class="hlt">clouds</span> (TICs) in the Arctic during the polar night and early spring. The first <span class="hlt">type</span> (TIC-1) is seen only by the lidar, but not the radar, and is found in pristine environment whereas the second <span class="hlt">type</span> (TIC-2) is detected by both sensors, and is associated with high concentration of aerosols, possibly anthropogenic. TIC-2 is characterized by a low concentration of ice crystals that are large enough to precipitate. To further investigate the interactions between TICs <span class="hlt">clouds</span> and aerosols, in-situ, airborne and satellite measurements of specific cases observed during the POLARCAT and ISDAC field experiments are analyzed. These two field campaigns took place respectively over the North Slope of Alaska and Northern part of Sweden in April 2008. Analysis of <span class="hlt">cloud</span> <span class="hlt">type</span> can be</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4507733','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4507733"><span>Nocturnal Sleep Dynamics <span class="hlt">Identify</span> Narcolepsy <span class="hlt">Type</span> 1</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Pizza, Fabio; Vandi, Stefano; Iloti, Martina; Franceschini, Christian; Liguori, Rocco; Mignot, Emmanuel; Plazzi, Giuseppe</p> <p>2015-01-01</p> <p>Study Objectives: To evaluate the reliability of nocturnal sleep dynamics in the differential diagnosis of central disorders of hypersomnolence. Design: Cross-sectional. Setting: Sleep laboratory. Patients: One hundred seventy-five patients with hypocretin-deficient narcolepsy <span class="hlt">type</span> 1 (NT1, n = 79), narcolepsy <span class="hlt">type</span> 2 (NT2, n = 22), idiopathic hypersomnia (IH, n = 22), and “subjective” hypersomnolence (sHS, n = 52). Interventions: None. Methods: Polysomnographic (PSG) work-up included 48 h of continuous PSG recording. From nocturnal PSG conventional sleep macrostructure, occurrence of sleep onset rapid eye movement period (SOREMP), sleep stages distribution, and sleep stage transitions were calculated. Patient groups were compared, and receiver operating characteristic (ROC) curve analysis was used to test the diagnostic utility of nocturnal PSG data to <span class="hlt">identify</span> NT1. Results: Sleep macrostructure was substantially stable in the 2 nights of each diagnostic group. NT1 and NT2 patients had lower latency to rapid eye movement (REM) sleep, and NT1 patients showed the highest number of awakenings, sleep stage transitions, and more time spent in N1 sleep, as well as most SOREMPs at daytime PSG and at multiple sleep latency test (MSLT) than all other groups. ROC curve analysis showed that nocturnal SOREMP (area under the curve of 0.724 ± 0.041, P < 0.0001), percent of total sleep time spent in N1 (0.896 ± 0.023, P < 0.0001), and the wakefulness-sleep transition index (0.796 ± 0.034, P < 0.0001) had a good sensitivity and specificity profile to <span class="hlt">identify</span> NT1 sleep, especially when used in combination (0.903 ± 0.023, P < 0.0001), similarly to SOREMP number at continuous daytime PSG (0.899 ± 0.026, P < 0.0001) and at MSLT (0.956 ± 0.015, P < 0.0001). Conclusions: Sleep macrostructure (i.e. SOREMP, N1 timing) including stage transitions reliably <span class="hlt">identifies</span> hypocretin-deficient narcolepsy <span class="hlt">type</span> 1 among central disorders of hypersomnolence. Citation: Pizza F, Vandi S</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20050180589&hterms=library&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dlibrary','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20050180589&hterms=library&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dlibrary"><span>Coupled fvGCM-GCE Modeling System, 3D <span class="hlt">Cloud</span>-Resolving Model and <span class="hlt">Cloud</span> Library</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tao, Wei-Kuo</p> <p>2005-01-01</p> <p>Recent GEWEX <span class="hlt">Cloud</span> System Study (GCSS) model comparison projects have indicated that <span class="hlt">cloud</span>- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various <span class="hlt">types</span> of <span class="hlt">clouds</span> and <span class="hlt">cloud</span> systems from different geographic locations. Current and future NASA satellite programs can provide <span class="hlt">cloud</span>, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and <span class="hlt">cloud</span>-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign <span class="hlt">cloud</span> related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A <span class="hlt">cloud</span> library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global <span class="hlt">cloud</span> simulator.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AMT....11.1417K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AMT....11.1417K"><span>A simple biota removal algorithm for 35 GHz <span class="hlt">cloud</span> radar measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kalapureddy, Madhu Chandra R.; Sukanya, Patra; Das, Subrata K.; Deshpande, Sachin M.; Pandithurai, Govindan; Pazamany, Andrew L.; Ambuj K., Jha; Chakravarty, Kaustav; Kalekar, Prasad; Krishna Devisetty, Hari; Annam, Sreenivas</p> <p>2018-03-01</p> <p><span class="hlt">Cloud</span> radar reflectivity profiles can be an important measurement for the investigation of <span class="hlt">cloud</span> vertical structure (CVS). However, extracting intended meteorological <span class="hlt">cloud</span> content from the measurement often demands an effective technique or algorithm that can reduce error and observational uncertainties in the recorded data. In this work, a technique is proposed to <span class="hlt">identify</span> and separate <span class="hlt">cloud</span> and non-hydrometeor echoes using the radar Doppler spectral moments profile measurements. The point and volume target-based theoretical radar sensitivity curves are used for removing the receiver noise floor and <span class="hlt">identified</span> radar echoes are scrutinized according to the signal decorrelation period. Here, it is hypothesized that <span class="hlt">cloud</span> echoes are observed to be temporally more coherent and homogenous and have a longer correlation period than biota. That can be checked statistically using ˜ 4 s sliding mean and standard deviation value of reflectivity profiles. The above step helps in screen out <span class="hlt">clouds</span> critically by filtering out the biota. The final important step strives for the retrieval of <span class="hlt">cloud</span> height. The proposed algorithm potentially <span class="hlt">identifies</span> <span class="hlt">cloud</span> height solely through the systematic characterization of Z variability using the local atmospheric vertical structure knowledge besides to the theoretical, statistical and echo tracing tools. Thus, characterization of high-resolution <span class="hlt">cloud</span> radar reflectivity profile measurements has been done with the theoretical echo sensitivity curves and observed echo statistics for the true <span class="hlt">cloud</span> height tracking (TEST). TEST showed superior performance in screening out <span class="hlt">clouds</span> and filtering out isolated insects. TEST constrained with polarimetric measurements was found to be more promising under high-density biota whereas TEST combined with linear depolarization ratio and spectral width perform potentially to filter out biota within the highly turbulent shallow cumulus <span class="hlt">clouds</span> in the convective boundary layer (CBL). This TEST technique is</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1367982-using-regime-analysis-identify-contribution-clouds-surface-temperature-errors-weather-climate-models','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1367982-using-regime-analysis-identify-contribution-clouds-surface-temperature-errors-weather-climate-models"><span>Using regime analysis to <span class="hlt">identify</span> the contribution of <span class="hlt">clouds</span> to surface temperature errors in weather and climate models</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Van Weverberg, Kwinten; Morcrette, Cyril J.; Ma, Hsi -Yen; ...</p> <p>2015-06-17</p> <p>Many global circulation models (GCMs) exhibit a persistent bias in the 2 m temperature over the midlatitude continents, present in short-range forecasts as well as long-term climate simulations. A number of hypotheses have been proposed, revolving around deficiencies in the soil–vegetation–atmosphere energy exchange, poorly resolved low-level boundary-layer <span class="hlt">clouds</span> or misrepresentations of deep-convective storms. A common approach to evaluating model biases focuses on the model-mean state. However, this makes difficult an unambiguous interpretation of the origins of a bias, given that biases are the result of the superposition of impacts of <span class="hlt">clouds</span> and land-surface deficiencies over multiple time steps. This articlemore » presents a new methodology to objectively detect the role of <span class="hlt">clouds</span> in the creation of a surface warm bias. A unique feature of this study is its focus on temperature-error growth at the time-step level. It is shown that compositing the temperature-error growth by the coinciding bias in total downwelling radiation provides unambiguous evidence for the role that <span class="hlt">clouds</span> play in the creation of the surface warm bias during certain portions of the day. Furthermore, the application of an objective <span class="hlt">cloud</span>-regime classification allows for the detection of the specific <span class="hlt">cloud</span> regimes that matter most for the creation of the bias. We applied this method to two state-of-the-art GCMs that exhibit a distinct warm bias over the Southern Great Plains of the USA. Our analysis highlights that, in one GCM, biases in deep-convective and low-level <span class="hlt">clouds</span> contribute most to the temperature-error growth in the afternoon and evening respectively. In the second GCM, deep <span class="hlt">clouds</span> persist too long in the evening, leading to a growth of the temperature bias. In conclusion, the reduction of the temperature bias in both models in the morning and the growth of the bias in the second GCM in the afternoon could not be assigned to a <span class="hlt">cloud</span> issue, but are more likely caused by a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018A%26A...612A..51B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018A%26A...612A..51B"><span>Properties and rotation of molecular <span class="hlt">clouds</span> in M 33</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Braine, J.; Rosolowsky, E.; Gratier, P.; Corbelli, E.; Schuster, K.-F.</p> <p>2018-04-01</p> <p>The sample of 566 molecular <span class="hlt">clouds</span> <span class="hlt">identified</span> in the CO(2-1) IRAM survey covering the disk of M 33 is explored in detail. The <span class="hlt">clouds</span> were found using CPROPS and were subsequently catalogued in terms of their star-forming properties as non-star-forming (A), with embedded star formation (B), or with exposed star formation (C, e.g., presence of Hα emission). We find that the size-linewidth relation among the M 33 <span class="hlt">clouds</span> is quite weak but, when comparing with <span class="hlt">clouds</span> in other nearby galaxies, the linewidth scales with average metallicity. The linewidth and particularly the line brightness decrease with galactocentric distance. The large number of <span class="hlt">clouds</span> makes it possible to calculate well-sampled <span class="hlt">cloud</span> mass spectra and mass spectra of subsamples. As noted earlier, but considerably better defined here, the mass spectrum steepens (i.e., higher fraction of small <span class="hlt">clouds</span>) with galactocentric distance. A new finding is that the mass spectrum of A <span class="hlt">clouds</span> is much steeper than that of the star-forming <span class="hlt">clouds</span>. Further dividing the sample, this difference is strong at both large and small galactocentric distances and the A vs. C difference is a stronger effect than the inner vs. outer disk difference in mass spectra. Velocity gradients are <span class="hlt">identified</span> in the <span class="hlt">clouds</span> using standard techniques. The gradients are weak and are dominated by prograde rotation; the effect is stronger for the high signal-to-noise <span class="hlt">clouds</span>. A discussion of the uncertainties is presented. The angular momenta are low but compatible with at least some simulations. Finally, the <span class="hlt">cloud</span> velocity gradients are compared with the gradient of disk rotation. The <span class="hlt">cloud</span> and galactic gradients are similar; the <span class="hlt">cloud</span> rotation periods are much longer than <span class="hlt">cloud</span> lifetimes and comparable to the galactic rotation period. The rotational kinetic energy is 1-2% of the gravitational potential energy and the <span class="hlt">cloud</span> edge velocity is well below the escape velocity, such that <span class="hlt">cloud</span>-scale rotation probably has little influence on the</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_11");'>11</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li class="active"><span>13</span></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_13 --> <div id="page_14" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="261"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70031310','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70031310"><span><span class="hlt">Cloud</span> water in windward and leeward mountain forests: The stable isotope signature of orographic <span class="hlt">cloud</span> water</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Scholl, M.A.; Giambelluca, T.W.; Gingerich, S.B.; Nullet, M.A.; Loope, L.L.</p> <p>2007-01-01</p> <p><span class="hlt">Cloud</span> water can be a significant hydrologic input to mountain forests. Because it is a precipitation source that is vulnerable to climate change, it is important to quantify amounts of <span class="hlt">cloud</span> water input at watershed and regional scales. During this study, <span class="hlt">cloud</span> water and rain samples were collected monthly for 2 years at sites on windward and leeward East Maui. The difference in isotopic composition between volume‐weighted average <span class="hlt">cloud</span> water and rain samples was 1.4‰ δ18O and 12‰ δ2H for the windward site and 2.8‰ δ18O and 25‰ δ2H for the leeward site, with the <span class="hlt">cloud</span> water samples enriched in 18O and 2H relative to the rain samples. A summary of previous literature shows that fog and/or <span class="hlt">cloud</span> water is enriched in 18O and 2H compared to rain at many locations around the world; this study documents <span class="hlt">cloud</span> water and rain isotopic composition resulting from weather patterns common to montane environments in the trade wind latitudes. An end‐member isotopic composition for <span class="hlt">cloud</span> water was <span class="hlt">identified</span> for each site and was used in an isotopic mixing model to estimate the proportion of precipitation input from orographic <span class="hlt">clouds</span>. Orographic <span class="hlt">cloud</span> water input was 37% of the total precipitation at the windward site and 46% at the leeward site. This represents an estimate of water input to the forest that could be altered by changes in <span class="hlt">cloud</span> base altitude resulting from global climate change or deforestation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3405666','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3405666"><span>Marine <span class="hlt">cloud</span> brightening</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Latham, John; Bower, Keith; Choularton, Tom; Coe, Hugh; Connolly, Paul; Cooper, Gary; Craft, Tim; Foster, Jack; Gadian, Alan; Galbraith, Lee; Iacovides, Hector; Johnston, David; Launder, Brian; Leslie, Brian; Meyer, John; Neukermans, Armand; Ormond, Bob; Parkes, Ben; Rasch, Phillip; Rush, John; Salter, Stephen; Stevenson, Tom; Wang, Hailong; Wang, Qin; Wood, Rob</p> <p>2012-01-01</p> <p>The idea behind the marine <span class="hlt">cloud</span>-brightening (MCB) geoengineering technique is that seeding marine stratocumulus <span class="hlt">clouds</span> with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the <span class="hlt">cloud</span> droplet number concentration, and thereby the <span class="hlt">cloud</span> albedo and possibly longevity. This would produce a cooling, which general circulation model (GCM) computations suggest could—subject to satisfactory resolution of technical and scientific problems <span class="hlt">identified</span> herein—have the capacity to balance global warming up to the carbon dioxide-doubling point. We describe herein an account of our recent research on a number of critical issues associated with MCB. This involves (i) GCM studies, which are our primary tools for evaluating globally the effectiveness of MCB, and assessing its climate impacts on rainfall amounts and distribution, and also polar sea-ice cover and thickness; (ii) high-resolution modelling of the effects of seeding on marine stratocumulus, which are required to understand the complex array of interacting processes involved in <span class="hlt">cloud</span> brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seed-particle salt-mass, air-mass characteristics, updraught speed and other parameters on cloud–albedo change; (iv) sea water spray-production techniques; (v) computational fluid dynamics studies of possible large-scale periodicities in Flettner rotors; and (vi) the planning of a three-stage limited-area field research experiment, with the primary objectives of technology testing and determining to what extent, if any, <span class="hlt">cloud</span> albedo might be enhanced by seeding marine stratocumulus <span class="hlt">clouds</span> on a spatial scale of around 100×100 km. We stress that there would be no justification for deployment of MCB unless it was clearly established that no significant adverse consequences would result. There would also need to be an international agreement firmly in favour of such action</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19900018898','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900018898"><span>Lidar <span class="hlt">cloud</span> studies for FIRE and ECLIPS</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sassen, Kenneth; Grund, Christian J.; Spinhirne, James D.; Hardesty, Michael; Alvarez, James</p> <p>1990-01-01</p> <p>Optical remote sensing measurements of cirrus <span class="hlt">cloud</span> properties were collected by one airborne and four ground-based lidar systems over a 32 h period during this case study from the First ISCCP (International Satellite <span class="hlt">Cloud</span> Climatology Program) Regional Experiment (FIRE) Intensive Field Observation (IFO) program. The lidar systems were variously equipped to collect linear depolarization, intrinsically calibrated backscatter, and Doppler velocity information. Data presented describe the temporal evolution and spatial distribution of cirrus <span class="hlt">clouds</span> over an area encompassing southern and central Wisconsin. The cirrus <span class="hlt">cloud</span> <span class="hlt">types</span> include: dissipating subvisual and thin fibrous cirrus <span class="hlt">cloud</span> bands, an isolated mesoscale uncinus complex (MUC), a large-scale deep <span class="hlt">cloud</span> that developed into an organized cirrus structure within the lidar array, and a series of intensifying mesoscale cirrus <span class="hlt">cloud</span> masses. Although the cirrus frequently developed in the vertical from particle fall-streaks emanating from generating regions at or near <span class="hlt">cloud</span> tops, glaciating supercooled (-30 to -35 C) altocumulus <span class="hlt">clouds</span> contributed to the production of ice mass at the base of the deep cirrus <span class="hlt">cloud</span>, apparently even through riming, and other mechanisms involving evaporation, wave motions, and radiative effects are indicated. The generating regions ranged in scale from approximately 1.0 km cirrus uncinus cells, to organized MUC structures up to approximately 120 km across.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A21F3098K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A21F3098K"><span>Global aerosol <span class="hlt">typing</span> from a combination of A-Train satellite observations in clear-sky and above <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kacenelenbogen, M. S.; Russell, P. B.; Vaughan, M.; Redemann, J.; Shinozuka, Y.; Livingston, J. M.; Zhang, Q.</p> <p>2014-12-01</p> <p>According to the 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), the model estimates of Radiative Forcing due to aerosol-radiation interactions (RFari) for individual aerosol <span class="hlt">types</span> are less certain than the total RFari [Boucher et al., 2013]. For example, the RFari specific to Black Carbon (BC) is uncertain due to an underestimation of its mass concentration near source regions [Koch et al., 2009]. Several recent studies have evaluated chemical transport model (CTM) predictions using observations of aerosol optical properties such as Aerosol Optical Depth (AOD) or Single Scattering Albedo (SSA) from satellite or ground-based instruments (e.g., Huneeus et al., [2010]). However, most passive remote sensing instruments fail to provide a comprehensive assessment of the particle <span class="hlt">type</span> without further analysis and combination of measurements. To improve the predictions of aerosol composition in CTMs, we have developed an aerosol classification algorithm (called Specified Clustering and Mahalanobis Classification, SCMC) that assigns an aerosol <span class="hlt">type</span> to multi-parameter retrievals by spaceborne, airborne or ground based passive remote sensing instruments [Russell et al., 2014]. The aerosol <span class="hlt">types</span> <span class="hlt">identified</span> by our scheme are pure dust, polluted dust, urban-industrial/developed economy, urban-industrial/developing economy, dark biomass smoke, light biomass smoke and pure marine. First, we apply the SCMC method to five years of clear-sky space-borne POLDER observations over Greece. We then use the aerosol extinction and SSA spectra retrieved from a combination of MODIS, OMI and CALIOP clear-sky observations to infer the aerosol <span class="hlt">type</span> over the globe in 2007. Finally, we will extend the spaceborne aerosol classification from clear-sky to above low opaque water <span class="hlt">clouds</span> using a combination of CALIOP AOD and backscatter observations and OMI absorption AOD values from near-by clear-sky pixels.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AtmRe.205...70P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AtmRe.205...70P"><span>Rain-shadow: An area harboring "Gray Ocean" <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Padmakumari, B.; Maheskumar, R. S.; Harikishan, G.; Morwal, S. B.; Kulkarni, J. R.</p> <p>2018-06-01</p> <p>The characteristics of monsoon convective <span class="hlt">clouds</span> over the rain-shadow region of north peninsular India have been investigated using in situ aircraft <span class="hlt">cloud</span> microphysical observations collected during <span class="hlt">Cloud</span> Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX). The parameters considered for characterization are: liquid water content (LWC), <span class="hlt">cloud</span> vertical motion (updraft, downdraft: w), <span class="hlt">cloud</span> droplet number concentration (CDNC) and effective radius (Re). The results are based on 15 research flights which were conducted from the base station Hyderabad during summer monsoon season. The <span class="hlt">clouds</span> studied were developing congestus. The <span class="hlt">clouds</span> have low CDNC and low updraft values resembling the oceanic convective <span class="hlt">clouds</span>. The super-saturation in <span class="hlt">clouds</span> is found to be low (≤0.2%) due to low updrafts. The land surface behaves like ocean surface during monsoon as deduced from Bowen ratio. Microphysically the <span class="hlt">clouds</span> showed oceanic characteristics. However, these <span class="hlt">clouds</span> yield low rainfall due to their low efficiency (mean 14%). The <span class="hlt">cloud</span> parameters showed a large variability; hence their characteristic values are reported in terms of median values. These values will serve the numerical models for rainfall simulations over the region and also will be useful as a scientific basis for <span class="hlt">cloud</span> seeding operations to increase the rainfall efficiency. The study revealed that monsoon convective <span class="hlt">clouds</span> over the rain-shadow region are of oceanic <span class="hlt">type</span> over the gray land, and therefore we christen them as "Gray Ocean" <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013PhDT.......409A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013PhDT.......409A"><span>Evaluating the impact of above-<span class="hlt">cloud</span> aerosols on <span class="hlt">cloud</span> optical depth retrievals from MODIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Alfaro, Ricardo</p> <p></p> <p>Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) <span class="hlt">cloud</span> optical depth (COD) retrievals (visible and shortwave infrared), the impacts of above-<span class="hlt">cloud</span> absorbing aerosols on the standard COD retrievals are evaluated. For fine-mode aerosol particles, aerosol optical depth (AOD) values diminish sharply from the visible to the shortwave infrared channels. Thus, a suppressed above-<span class="hlt">cloud</span> particle radiance aliasing effect occurs for COD retrievals using shortwave infrared channels. Aerosol Index (AI) from the spatially and temporally collocated Ozone Monitoring Instrument (OMI) are used to <span class="hlt">identify</span> above-<span class="hlt">cloud</span> aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African sub-continent. MODIS and OMI Collocated <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to constrain <span class="hlt">cloud</span> phase and provide contextual above-<span class="hlt">cloud</span> AOD values. The frequency of occurrence of above-<span class="hlt">cloud</span> aerosols is depicted on a global scale for the spring and summer seasons from OMI and CALIOP, thus indicating the significance of the problem. Seasonal frequencies for smoke-over-<span class="hlt">cloud</span> off the southwestern Africa coastline reach 20--50% in boreal summer. We find a corresponding low COD bias of 10--20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1.0. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS visible and shortwave in channels are vulnerable to dust particle aliasing, and thus a COD impact cannot be isolated with this method. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus <span class="hlt">clouds</span> and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-<span class="hlt">cloud</span> aerosol events for future studies using standard MODIS <span class="hlt">cloud</span> products in biomass burning outflow regions, through the use of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3274136','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3274136"><span>An Improved <span class="hlt">Cloud</span> Classification Algorithm for China’s FY-2C Multi-Channel Images Using Artificial Neural Network</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Liu, Yu; Xia, Jun; Shi, Chun-Xiang; Hong, Yang</p> <p>2009-01-01</p> <p>The crowning objective of this research was to <span class="hlt">identify</span> a better <span class="hlt">cloud</span> classification method to upgrade the current window-based clustering algorithm used operationally for China’s first operational geostationary meteorological satellite FengYun-2C (FY-2C) data. First, the capabilities of six widely-used Artificial Neural Network (ANN) methods are analyzed, together with the comparison of two other methods: Principal Component Analysis (PCA) and a Support Vector Machine (SVM), using 2864 <span class="hlt">cloud</span> samples manually collected by meteorologists in June, July, and August in 2007 from three FY-2C channel (IR1, 10.3–11.3 μm; IR2, 11.5–12.5 μm and WV 6.3–7.6 μm) imagery. The result shows that: (1) ANN approaches, in general, outperformed the PCA and the SVM given sufficient training samples and (2) among the six ANN networks, higher <span class="hlt">cloud</span> classification accuracy was obtained with the Self-Organizing Map (SOM) and Probabilistic Neural Network (PNN). Second, to compare the ANN methods to the present FY-2C operational algorithm, this study implemented SOM, one of the best ANN network <span class="hlt">identified</span> from this study, as an automated <span class="hlt">cloud</span> classification system for the FY-2C multi-channel data. It shows that SOM method has improved the results greatly not only in pixel-level accuracy but also in <span class="hlt">cloud</span> patch-level classification by more accurately <span class="hlt">identifying</span> <span class="hlt">cloud</span> <span class="hlt">types</span> such as cumulonimbus, cirrus and <span class="hlt">clouds</span> in high latitude. Findings of this study suggest that the ANN-based classifiers, in particular the SOM, can be potentially used as an improved Automated <span class="hlt">Cloud</span> Classification Algorithm to upgrade the current window-based clustering method for the FY-2C operational products. PMID:22346714</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A43B2441H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A43B2441H"><span><span class="hlt">Cloud</span> Processed CCN Suppress Stratus <span class="hlt">Cloud</span> Drizzle</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hudson, J. G.; Noble, S. R., Jr.</p> <p>2017-12-01</p> <p>Conversion of sulfur dioxide to sulfate within <span class="hlt">cloud</span> droplets increases the sizes and decreases the critical supersaturation, Sc, of <span class="hlt">cloud</span> residual particles that had nucleated the droplets. Since other particles remain at the same sizes and Sc a size and Sc gap is often observed. Hudson et al. (2015) showed higher <span class="hlt">cloud</span> droplet concentrations (Nc) in stratus <span class="hlt">clouds</span> associated with bimodal high-resolution CCN spectra from the DRI CCN spectrometer compared to <span class="hlt">clouds</span> associated with unimodal CCN spectra (not <span class="hlt">cloud</span> processed). Here we show that CCN spectral shape (bimodal or unimodal) affects all aspects of stratus <span class="hlt">cloud</span> microphysics and drizzle. Panel A shows mean differential <span class="hlt">cloud</span> droplet spectra that have been divided according to traditional slopes, k, of the 131 measured CCN spectra in the Marine Stratus/Stratocumulus Experiment (MASE) off the Central California coast. K is generally high within the supersaturation, S, range of stratus <span class="hlt">clouds</span> (< 0.5%). Because <span class="hlt">cloud</span> processing decreases Sc of some particles, it reduces k. Panel A shows higher concentrations of small <span class="hlt">cloud</span> droplets apparently grown on lower k CCN than <span class="hlt">clouds</span> grown on higher k CCN. At small droplet sizes the concentrations follow the k order of the legend, black, red, green, blue (lowest to highest k). Above 13 µm diameter the lines cross and the hierarchy reverses so that blue (highest k) has the highest concentrations followed by green, red and black (lowest k). This reversed hierarchy continues into the drizzle size range (panel B) where the most drizzle drops, Nd, are in <span class="hlt">clouds</span> grown on the least <span class="hlt">cloud</span>-processed CCN (blue), while <span class="hlt">clouds</span> grown on the most processed CCN (black) have the lowest Nd. Suppression of stratus <span class="hlt">cloud</span> drizzle by <span class="hlt">cloud</span> processing is an additional 2nd indirect aerosol effect (IAE) that along with the enhancement of 1st IAE by higher Nc (panel A) are above and beyond original IAE. However, further similar analysis is needed in other <span class="hlt">cloud</span> regimes to determine if MASE was</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010PhDT.......211W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010PhDT.......211W"><span><span class="hlt">Cloud</span> cameras at the Pierre Auger Observatory</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Winnick, Michael G.</p> <p>2010-06-01</p> <p>This thesis presents the results of measurements made by infrared <span class="hlt">cloud</span> cameras installed at the Pierre Auger Observatory in Argentina. These cameras were used to record <span class="hlt">cloud</span> conditions during operation of the observatory's fluorescence detectors. As <span class="hlt">cloud</span> may affect the measurement of fluorescence from cosmic ray extensive air showers, the <span class="hlt">cloud</span> cameras provide a record of which measurements have been interfered with by <span class="hlt">cloud</span>. Several image processing algorithms were developed, along with a methodology for the detection of <span class="hlt">cloud</span> within infrared images taken by the <span class="hlt">cloud</span> cameras. A graphical user interface (GUI) was developed to expediate this, as a large number of images need to be checked for <span class="hlt">cloud</span>. A cross-check between images recorded by three of the observatory's <span class="hlt">cloud</span> cameras is presented, along with a comparison with independent <span class="hlt">cloud</span> measurements made by LIDAR. Despite the <span class="hlt">cloud</span> cameras and LIDAR observing different areas of the sky, a good agreement is observed in the measured <span class="hlt">cloud</span> fraction between the two instruments, particularly on very clear and overcast nights. <span class="hlt">Cloud</span> information recorded by the <span class="hlt">cloud</span> cameras, with <span class="hlt">cloud</span> height information measured by the LIDAR, was used to <span class="hlt">identify</span> those extensive air showers that were obscured by <span class="hlt">cloud</span>. These events were used to study the effectiveness of standard quality cuts at removing <span class="hlt">cloud</span> afflicted events. Of all of the standard quality cuts studied in this thesis, the LIDAR <span class="hlt">cloud</span> fraction cut was the most effective at preferentially removing <span class="hlt">cloud</span> obscured events. A 'cloudy pixel' veto is also presented, whereby <span class="hlt">cloud</span> obscured measurements are excluded during the standard hybrid analysis, and new extensive air shower reconstructed parameters determined. The application of such a veto would provide a slight increase to the number of events available for higher level analysis.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018SPIE10697E..1IL','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018SPIE10697E..1IL"><span>Research on <span class="hlt">cloud</span> background infrared radiation simulation based on fractal and statistical data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, Xingrun; Xu, Qingshan; Li, Xia; Wu, Kaifeng; Dong, Yanbing</p> <p>2018-02-01</p> <p><span class="hlt">Cloud</span> is an important natural phenomenon, and its radiation causes serious interference to infrared detector. Based on fractal and statistical data, a method is proposed to realize <span class="hlt">cloud</span> background simulation, and <span class="hlt">cloud</span> infrared radiation data field is assigned using satellite radiation data of <span class="hlt">cloud</span>. A <span class="hlt">cloud</span> infrared radiation simulation model is established using matlab, and it can generate <span class="hlt">cloud</span> background infrared images for different <span class="hlt">cloud</span> <span class="hlt">types</span> (low <span class="hlt">cloud</span>, middle <span class="hlt">cloud</span>, and high <span class="hlt">cloud</span>) in different months, bands and sensor zenith angles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003JGRE..108.5098C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003JGRE..108.5098C"><span>Mars aerosol studies with the MGS TES emission phase function observations: Optical depths, particle sizes, and ice <span class="hlt">cloud</span> <span class="hlt">types</span> versus latitude and solar longitude</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Clancy, R. Todd; Wolff, Michael J.; Christensen, Philip R.</p> <p>2003-09-01</p> <p>Emission phase function (EPF) observations taken in 1999-2001 by Mars Global Surveyor Thermal Emission Spectrometer (MGS TES) support the broadest study of Martian aerosol properties to date. TES solar band and infrared (IR) spectral EPF sequences are analyzed to obtain first-time seasonal/latitudinal distributions of visible optical depths, particle sizes, and single scattering phase functions. This combined angular and wavelength coverage enables identification of two distinct ice <span class="hlt">cloud</span> <span class="hlt">types</span> over 45°S-45°N. <span class="hlt">Type</span> 1 ice <span class="hlt">clouds</span> exhibit small particle sizes (reff = 1-2 μm) and a distinctive backscattering increase. They are most prevalent in the southern hemisphere during aphelion, but also appear more widely distributed in season and latitude as topographic and high-altitude (>=20 km) ice hazes. <span class="hlt">Type</span> 2 ice <span class="hlt">clouds</span> exhibit larger particle sizes (reff = 3-4 μm), a distinct side-scattering minimum at 90-100° phase angles (characteristic of a change in particle shape relative to the <span class="hlt">type</span> 1), and appear most prominently in the northern subtropical aphelion <span class="hlt">cloud</span> belt. The majority of retrieved dust visible-to-IR optical depth ratios are indicative of reff = 1.5 +/- 0.1 μm, consistent with Pathfinder and Viking/Mariner 9 reanalyses. However, increased ratios (2.7 versus 1.7) appear frequently in the northern hemisphere over LS = 50-200°, indicating substantially smaller dust particles sizes (reff = 1.0 +/- 0.2 μm) at this time. In addition, larger (reff = 1.8-2.5 μm) dust particles were observed locally in the southern hemisphere during the peak of the 2001 global dust storm. Detailed spectral modeling of the TES visible band pass indicates agreement of EPF-derived dust single scattering albedos (0.92-0.94) with the spectrally resolved results from Pathfinder observations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9142E..0XZ','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9142E..0XZ"><span><span class="hlt">Cloud</span> and aerosol polarimetric imager</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Junqiang; Shao, Jianbing; Yan, Changxiang</p> <p>2014-02-01</p> <p><span class="hlt">Cloud</span> and Aerosol Polarimetric Imager (CAPI), which is the first onboard <span class="hlt">cloud</span> and aerosol Polarimetric detector of CHINA, is developed to get <span class="hlt">cloud</span> and aerosol data of atmosphere to retrieve aerosol optical and microphysical properties to increase the reversion precision of greenhouse gasses (GHGs). The instrument is neither a Polarization and Direction of Earth's Reflectance (POLDER) nor a Directional Polarimetric Camera (DPC) <span class="hlt">type</span> polarized camera. It is a multispectral push broom system using linear detectors, and can get 5 bands spectral data, from ultraviolet (UV) to SWIR, of the same ground feature at the same time without any moving structure. This paper describes the CAPI instrument characteristics, composition, calibration, and the nearest development.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120003467','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120003467"><span>A Study of Rapidly Developing Low <span class="hlt">Cloud</span> Ceilings in a Stable Atmosphere at the Florida Spaceport</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wheeler, Mark M.; Case, Jonathan L.; Baggett, G. Wayne</p> <p>2006-01-01</p> <p>Forecasters at the Space Meteorology Group (SMG) issue 30 to 90 minute forecasts for low <span class="hlt">cloud</span> ceilings at the Shuttle Landing Facility (KTTS) in Kennedy Space Center, FL for all Space Shuttle missions. Mission verification statistics have shown <span class="hlt">cloud</span> ceilings to be the biggest forecast challenge. SMG forecasters are especially concerned with rapidly developing <span class="hlt">cloud</span> ceilings below 8000 ft. in a stable, capped thermodynamic environment because ceilings below 8000 ft restrict Shuttle landing operations and are the most challenging to predict accurately. This project involves the development of a database of these cases over east-central Florida in order to <span class="hlt">identify</span> the onset, location, and if possible, dissipation times of rapidly-developing low <span class="hlt">cloud</span> ceilings. Another goal is to document the atmospheric regimes favoring this <span class="hlt">type</span> of <span class="hlt">cloud</span> development to improve forecast skill of such events during Space Shuttle launch and landing operations. A 10-year database of stable, rapid low <span class="hlt">cloud</span> development days during the daylight hours was compiled for the Florida cool-season months by examining the Cape Canaveral Air Force Station sounding data, and <span class="hlt">identifying</span> days that had high boundary layer relative humidity associated with a thermally-capped environment below 8000 ft. Archived hourly surface observations from KTTS and Melbourne, Orlando, Sanford, and Ocala, FL were then examined for the onset of <span class="hlt">cloud</span> ceilings below 8000 ft between 1100 and 2000 UTC. Once the database was supplemented with the hourly surface <span class="hlt">cloud</span> observations, visible satellite imagery was examined in 30-minute intervals to confirm event occurrences. This paper will present results from some of the rapidly developing <span class="hlt">cloud</span> ceiling cases and the prevailing meteorological conditions associated with these events, focusing on potential pre-curser information that may help improve their prediction.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=266506','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=266506"><span>Comparison of 17 genome <span class="hlt">types</span> of adenovirus <span class="hlt">type</span> 3 <span class="hlt">identified</span> among strains recovered from six continents.</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Li, Q G; Wadell, G</p> <p>1988-01-01</p> <p>Restriction endonucleases BamHI, BclI, BglI, BglII, BstEII, EcoRI, HindIII, HpaI, SalI, SmalI, XbalI, and XholI were used to analyze 61 selected strains of adenovirus <span class="hlt">type</span> 3 (Ad3) isolated from Africa, Asia, Australia, Europe, North America, and South America. It was noted that the use of BamHI, BclI, BglII, HpaI, SalI, and SmaI was sufficient to distinguish 17 genome <span class="hlt">types</span>; 13 of them were newly <span class="hlt">identified</span>. All 17 Ad3 genome <span class="hlt">types</span> could be divided into three genomic clusters. Genome <span class="hlt">types</span> of Ad3 cluster 1 occurred in Africa, Europe, South America, and North America. Genomic cluster 2 was <span class="hlt">identified</span> in Africa; genomic cluster 3 was <span class="hlt">identified</span> in Africa, Asia, Australia, Europe (a few), and North America. This was of interest because 15 <span class="hlt">identified</span> genome <span class="hlt">types</span> of Ad7 could also be divided into three genomic clusters. The degree of genetic relatedness between the 17 Ad3 and the 15 Ad7 genome <span class="hlt">types</span> was analyzed and was expressed in a three-dimensional model. Images PMID:2838500</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFM.A13B0234T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFM.A13B0234T"><span>Comparison of <span class="hlt">Cloud</span> Detection Using the CERES-MODIS Ed4 and LaRC AVHRR <span class="hlt">Cloud</span> Masks and CALIPSO Vertical Feature Mask</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.</p> <p>2011-12-01</p> <p>Accurate detection of <span class="hlt">cloud</span> amount and distribution using satellite observations is crucial in determining <span class="hlt">cloud</span> radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 <span class="hlt">cloud</span> mask is a global <span class="hlt">cloud</span> detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's <span class="hlt">Cloud</span> and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR <span class="hlt">cloud</span> mask, which uses only five spectral channels, is based on a subset of the CM <span class="hlt">cloud</span> mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR <span class="hlt">cloud</span> masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving <span class="hlt">cloud</span> detection globally. They also help us understand the strengths and limitations of the various <span class="hlt">cloud</span> retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different <span class="hlt">types</span> of <span class="hlt">clouds</span> over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal <span class="hlt">cloud</span> occurrence and amount from the CERES Ed4, AVHRR <span class="hlt">cloud</span> masks and CALIPSO VFM will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8334E..2YV','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8334E..2YV"><span>Secure data sharing in public <span class="hlt">cloud</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Venkataramana, Kanaparti; Naveen Kumar, R.; Tatekalva, Sandhya; Padmavathamma, M.</p> <p>2012-04-01</p> <p>Secure multi-party protocols have been proposed for entities (organizations or individuals) that don't fully trust each other to share sensitive information. Many <span class="hlt">types</span> of entities need to collect, analyze, and disseminate data rapidly and accurately, without exposing sensitive information to unauthorized or untrusted parties. Solutions based on secure multiparty computation guarantee privacy and correctness, at an extra communication (too costly in communication to be practical) and computation cost. The high overhead motivates us to extend this SMC to <span class="hlt">cloud</span> environment which provides large computation and communication capacity which makes SMC to be used between multiple <span class="hlt">clouds</span> (i.e., it may between private or public or hybrid <span class="hlt">clouds).Cloud</span> may encompass many high capacity servers which acts as a hosts which participate in computation (IaaS and PaaS) for final result, which is controlled by <span class="hlt">Cloud</span> Trusted Authority (CTA) for secret sharing within the <span class="hlt">cloud</span>. The communication between two <span class="hlt">clouds</span> is controlled by High Level Trusted Authority (HLTA) which is one of the hosts in a <span class="hlt">cloud</span> which provides MgaaS (Management as a Service). Due to high risk for security in <span class="hlt">clouds</span>, HLTA generates and distributes public keys and private keys by using Carmichael-R-Prime- RSA algorithm for exchange of private data in SMC between itself and <span class="hlt">clouds</span>. In <span class="hlt">cloud</span>, CTA creates Group key for Secure communication between the hosts in <span class="hlt">cloud</span> based on keys sent by HLTA for exchange of Intermediate values and shares for computation of final result. Since this scheme is extended to be used in <span class="hlt">clouds</span>( due to high availability and scalability to increase computation power) it is possible to implement SMC practically for privacy preserving in data mining at low cost for the clients.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AAS...23131004K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AAS...23131004K"><span>An Observational Diagnostic for Distinguishing Between <span class="hlt">Clouds</span> and Haze in Hot Exoplanet Atmospheres</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kempton, Eliza; Bean, Jacob; Parmentier, Vivien</p> <p>2018-01-01</p> <p>The nature of aerosols in hot exoplanet atmospheres is one of the primary vexing questions facing the exoplanet field. The complex chemistry, multiple formation pathways, and lack of easily <span class="hlt">identifiable</span> spectral features associated with aerosols make it especially challenging to constrain their key properties. We present a transmission spectroscopy technique to <span class="hlt">identify</span> the primary aerosol formation mechanism for the most highly irradiated hot Jupiters (HIHJs). The technique is based on the idea that the two key <span class="hlt">types</span> of aerosols -- photochemically generated hazes and equilibrium condensate <span class="hlt">clouds</span> -- are expected to form and persist in different regions of a highly irradiated planet's atmosphere. Haze can only be produced on the permanent daysides of tidally-locked hot Jupiters, and will be carried downwind by atmospheric dynamics to the evening terminator (seen as the trailing limb during transit). <span class="hlt">Clouds</span> can only form in cooler regions on the night side and morning terminator of HIHJs (seen as the leading limb during transit). Because opposite limbs are expected to be impacted by different <span class="hlt">types</span> of aerosols, ingress and egress spectra, which primarily probe opposing sides of the planet, will reveal the dominant aerosol formation mechanism. We show that the benchmark HIHJ, WASP-121b, has a transmission spectrum consistent with partial aerosol coverage and that ingress-egress spectroscopy would constrain the location and formation mechanism of those aerosols. In general, we find that observations with JWST and potentially with HST should be able to distinguish between <span class="hlt">clouds</span> and haze for currently known HIHJs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19890006113','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19890006113"><span><span class="hlt">Cloud</span> cover determination in polar regions from satellite imagery</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barry, R. G.; Key, J. R.; Maslanik, J. A.</p> <p>1988-01-01</p> <p>The principal objectives of this project are: (1) to develop suitable validation data sets to evaluate the effectiveness of the International Satellite <span class="hlt">Cloud</span> Climatology Project (ISCCP) operational algorithm for <span class="hlt">cloud</span> retrieval in polar regions and to validate model simulations of polar <span class="hlt">cloud</span> cover; (2) to <span class="hlt">identify</span> limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers; and (3) to compare synoptic <span class="hlt">cloud</span> data from a control run experiment of the GISS climate model II with typical observed synoptic <span class="hlt">cloud</span> patterns.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008AGUSM.A33C..08K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008AGUSM.A33C..08K"><span><span class="hlt">Cloud</span> vertical profiles derived from CALIPSO and <span class="hlt">Cloud</span>Sat and a comparison with MODIS derived <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.</p> <p>2008-05-01</p> <p>CALIPSO and <span class="hlt">Cloud</span>Sat from the a-train provide detailed information of vertical distribution of <span class="hlt">clouds</span> and aerosols. The vertical distribution of <span class="hlt">cloud</span> occurrence is derived from one month of CALIPSO and <span class="hlt">Cloud</span>Sat data as a part of the effort of merging CALIPSO, <span class="hlt">Cloud</span>Sat and MODIS with CERES data. This newly derived <span class="hlt">cloud</span> profile is compared with the distribution of <span class="hlt">cloud</span> top height derived from MODIS on Aqua from <span class="hlt">cloud</span> algorithms used in the CERES project. The <span class="hlt">cloud</span> base from MODIS is also estimated using an empirical formula based on the <span class="hlt">cloud</span> top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level <span class="hlt">clouds</span> over the Arctic in April fairly well when they are the topmost <span class="hlt">cloud</span> layer, it underestimates high- level <span class="hlt">clouds</span>. In addition, because the CERES-MODIS <span class="hlt">cloud</span> algorithm is not able to detect multi-layer <span class="hlt">clouds</span> and the empirical formula significantly underestimates the depth of high <span class="hlt">clouds</span>, the occurrence of mid and low-level <span class="hlt">clouds</span> is underestimated. This comparison does not consider sensitivity difference to thin <span class="hlt">clouds</span> but we will impose an optical thickness threshold to CALIPSO derived <span class="hlt">clouds</span> for a further comparison. The effect of such differences in the <span class="hlt">cloud</span> profile to flux computations will also be discussed. In addition, the effect of <span class="hlt">cloud</span> cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4587428','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4587428"><span>Job Scheduling with Efficient Resource Monitoring in <span class="hlt">Cloud</span> Datacenter</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Loganathan, Shyamala; Mukherjee, Saswati</p> <p>2015-01-01</p> <p><span class="hlt">Cloud</span> computing is an on-demand computing model, which uses virtualization technology to provide <span class="hlt">cloud</span> resources to users in the form of virtual machines through internet. Being an adaptable technology, <span class="hlt">cloud</span> computing is an excellent alternative for organizations for forming their own private <span class="hlt">cloud</span>. Since the resources are limited in these private <span class="hlt">clouds</span> maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private <span class="hlt">cloud</span> environment and discusses a <span class="hlt">cloud</span> model. The proposed scheduling algorithm considers the <span class="hlt">types</span> of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using <span class="hlt">Cloud</span>Sim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms. PMID:26473166</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_12");'>12</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li class="active"><span>14</span></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_14 --> <div id="page_15" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="281"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26473166','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26473166"><span>Job Scheduling with Efficient Resource Monitoring in <span class="hlt">Cloud</span> Datacenter.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Loganathan, Shyamala; Mukherjee, Saswati</p> <p>2015-01-01</p> <p><span class="hlt">Cloud</span> computing is an on-demand computing model, which uses virtualization technology to provide <span class="hlt">cloud</span> resources to users in the form of virtual machines through internet. Being an adaptable technology, <span class="hlt">cloud</span> computing is an excellent alternative for organizations for forming their own private <span class="hlt">cloud</span>. Since the resources are limited in these private <span class="hlt">clouds</span> maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private <span class="hlt">cloud</span> environment and discusses a <span class="hlt">cloud</span> model. The proposed scheduling algorithm considers the <span class="hlt">types</span> of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using <span class="hlt">Cloud</span>Sim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1437109-theoretical-study-mixing-liquid-clouds-part-classical-concepts','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1437109-theoretical-study-mixing-liquid-clouds-part-classical-concepts"><span>Theoretical study of mixing in liquid <span class="hlt">clouds</span> – Part 1: Classical concepts</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Korolev, Alexei; Khain, Alex; Pinsky, Mark; ...</p> <p>2016-07-28</p> <p>The present study considers final stages of in-<span class="hlt">cloud</span> mixing in the framework of classical concept of homogeneous and extreme inhomogeneous mixing. Simple analytical relationships between basic microphysical parameters were obtained for homogeneous and extreme inhomogeneous mixing based on the adiabatic consideration. It was demonstrated that during homogeneous mixing the functional relationships between the moments of the droplets size distribution hold only during the primary stage of mixing. Subsequent random mixing between already mixed parcels and undiluted <span class="hlt">cloud</span> parcels breaks these relationships. However, during extreme inhomogeneous mixing the functional relationships between the microphysical parameters hold both for primary and subsequent mixing.more » The obtained relationships can be used to <span class="hlt">identify</span> the <span class="hlt">type</span> of mixing from in situ observations. The effectiveness of the developed method was demonstrated using in situ data collected in convective <span class="hlt">clouds</span>. It was found that for the specific set of in situ measurements the interaction between cloudy and entrained environments was dominated by extreme inhomogeneous mixing.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1440703-identification-program-signatures-from-cloud-computing-system-telemetry-data','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1440703-identification-program-signatures-from-cloud-computing-system-telemetry-data"><span>Identification of Program Signatures from <span class="hlt">Cloud</span> Computing System Telemetry Data</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Nichols, Nicole M.; Greaves, Mark T.; Smith, William P.</p> <p></p> <p>Malicious <span class="hlt">cloud</span> computing activity can take many forms, including running unauthorized programs in a virtual environment. Detection of these malicious activities while preserving the privacy of the user is an important research challenge. Prior work has shown the potential viability of using <span class="hlt">cloud</span> service billing metrics as a mechanism for proxy identification of malicious programs. Previously this novel detection method has been evaluated in a synthetic and isolated computational environment. In this paper we demonstrate the ability of billing metrics to <span class="hlt">identify</span> programs, in an active <span class="hlt">cloud</span> computing environment, including multiple virtual machines running on the same hypervisor. The openmore » source <span class="hlt">cloud</span> computing platform OpenStack, is used for private <span class="hlt">cloud</span> management at Pacific Northwest National Laboratory. OpenStack provides a billing tool (Ceilometer) to collect system telemetry measurements. We <span class="hlt">identify</span> four different programs running on four virtual machines under the same <span class="hlt">cloud</span> user account. Programs were <span class="hlt">identified</span> with up to 95% accuracy. This accuracy is dependent on the distinctiveness of telemetry measurements for the specific programs we tested. Future work will examine the scalability of this approach for a larger selection of programs to better understand the uniqueness needed to <span class="hlt">identify</span> a program. Additionally, future work should address the separation of signatures when multiple programs are running on the same virtual machine.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25785761','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25785761"><span><span class="hlt">Cloud</span> and traditional videoconferencing technology for telemedicine and distance learning.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Liu, Wei-Li; Zhang, Kai; Locatis, Craig; Ackerman, Michael</p> <p>2015-05-01</p> <p><span class="hlt">Cloud</span>-based videoconferencing versus traditional systems are described for possible use in telemedicine and distance learning. Differences between traditional and <span class="hlt">cloud</span>-based videoconferencing systems are examined, and the methods for <span class="hlt">identifying</span> and testing systems are explained. Findings are presented characterizing the <span class="hlt">cloud</span> conferencing genre and its attributes versus traditional H.323 conferencing. Because the technology is rapidly evolving and needs to be evaluated in reference to local needs, it is strongly recommended that this or other reviews not be considered substitutes for personal hands-on experience. This review <span class="hlt">identifies</span> key attributes of the technology that can be used to appraise the relevance of <span class="hlt">cloud</span> conferencing technology and to determine whether migration from traditional technology to a <span class="hlt">cloud</span> environment is warranted. An evaluation template is provided for assessing systems appropriateness.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A31E2221C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A31E2221C"><span>Study on Diagnosing Three Dimensional <span class="hlt">Cloud</span> Region</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cai, M., Jr.; Zhou, Y., Sr.</p> <p>2017-12-01</p> <p><span class="hlt">Cloud</span> mask and relative humidity (RH) provided by Cloudsat products from 2007 to 2008 are statistical analyzed to get RH Threshold between <span class="hlt">cloud</span> and clear sky and its variation with height. A diagnosis method is proposed based on reanalysis data and applied to three-dimensional <span class="hlt">cloud</span> field diagnosis of a real case. Diagnostic <span class="hlt">cloud</span> field was compared to satellite, radar and other <span class="hlt">cloud</span> precipitation observation. Main results are as follows. 1.<span class="hlt">Cloud</span> region where <span class="hlt">cloud</span> mask is bigger than 20 has a good space and time corresponding to the high value relative humidity region, which is provide by ECWMF AUX product. Statistical analysis of the RH frequency distribution within and outside <span class="hlt">cloud</span> indicated that, distribution of RH in <span class="hlt">cloud</span> at different height range shows single peak <span class="hlt">type</span>, and the peak is near a RH value of 100%. Local atmospheric environment affects the RH distribution outside <span class="hlt">cloud</span>, which leads to TH distribution vary in different region or different height. 2. RH threshold and its vertical distribution used for <span class="hlt">cloud</span> diagnostic was analyzed from Threat Score method. The method is applied to a three dimension <span class="hlt">cloud</span> diagnosis case study based on NCEP reanalysis data and th diagnostic <span class="hlt">cloud</span> field is compared to satellite, radar and <span class="hlt">cloud</span> precipitation observation on ground. It is found that, RH gradient is very big around <span class="hlt">cloud</span> region and diagnosed <span class="hlt">cloud</span> area by RH threshold method is relatively stable. Diagnostic <span class="hlt">cloud</span> area has a good corresponding to updraft region. The <span class="hlt">cloud</span> and clear sky distribution corresponds to satellite the TBB observations overall. Diagnostic <span class="hlt">cloud</span> depth, or sum <span class="hlt">cloud</span> layers distribution consists with optical thickness and precipitation on ground better. The <span class="hlt">cloud</span> vertical profile reveals the relation between <span class="hlt">cloud</span> vertical structure and weather system clearly. Diagnostic <span class="hlt">cloud</span> distribution correspond to <span class="hlt">cloud</span> observations on ground very well. 3. The method is improved by changing the vertical interval from altitude to temperature</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916473N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916473N"><span>Characterization of the <span class="hlt">cloud</span> conditions at Ny-Ålesund using sensor synergy and representativeness of the observed <span class="hlt">clouds</span> across Arctic sites</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nomokonova, Tatiana; Ebell, Kerstin; Löhnert, Ulrich; Maturilli, Marion</p> <p>2017-04-01</p> <p> structure of the atmosphere is obtained from long-term radiosonde launches. In addition, continuous vertical profiles of temperature and humidity are provided by the microwave radiometer HATPRO. A set of active remote sensing instruments performs <span class="hlt">cloud</span> observations at Ny-Ålesund: a ceilometer and a Doppler lidar operating since 2011 and 2013, respectively, are now complemented with a novel 94 GHz FMCW <span class="hlt">cloud</span> radar. As a first step, the CLOUDNET algorithms, including a target categorization and classification, are applied to the observations. In this study, we will present a first analysis of <span class="hlt">cloud</span> properties at Ny-Ålesund including for example <span class="hlt">cloud</span> occurrence, <span class="hlt">cloud</span> geometry (<span class="hlt">cloud</span> base, <span class="hlt">cloud</span> top, and thickness) and <span class="hlt">cloud</span> <span class="hlt">type</span> (liquid, ice, mixed-phase). The different <span class="hlt">types</span> of <span class="hlt">clouds</span> are set into context to the environmental conditions such as temperature, amount of water vapour, and liquid water. We also expect that the <span class="hlt">cloud</span> properties strongly depend on the wind direction. The first results of this analysis will be also shown.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AMT....10.4777R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AMT....10.4777R"><span>Simultaneous and synergistic profiling of <span class="hlt">cloud</span> and drizzle properties using ground-based observations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rusli, Stephanie P.; Donovan, David P.; Russchenberg, Herman W. J.</p> <p>2017-12-01</p> <p>Despite the importance of radar reflectivity (Z) measurements in the retrieval of liquid water <span class="hlt">cloud</span> properties, it remains nontrivial to interpret Z due to the possible presence of drizzle droplets within the <span class="hlt">clouds</span>. So far, there has been no published work that utilizes Z to <span class="hlt">identify</span> the presence of drizzle above the <span class="hlt">cloud</span> base in an optimized and a physically consistent manner. In this work, we develop a retrieval technique that exploits the synergy of different remote sensing systems to carry out this task and to subsequently profile the microphysical properties of the <span class="hlt">cloud</span> and drizzle in a unified framework. This is accomplished by using ground-based measurements of Z, lidar attenuated backscatter below as well as above the <span class="hlt">cloud</span> base, and microwave brightness temperatures. Fast physical forward models coupled to <span class="hlt">cloud</span> and drizzle structure parameterization are used in an optimal-estimation-<span class="hlt">type</span> framework in order to retrieve the best estimate for the <span class="hlt">cloud</span> and drizzle property profiles. The <span class="hlt">cloud</span> retrieval is first evaluated using synthetic signals generated from large-eddy simulation (LES) output to verify the forward models used in the retrieval procedure and the vertical parameterization of the liquid water content (LWC). From this exercise it is found that, on average, the <span class="hlt">cloud</span> properties can be retrieved within 5 % of the mean truth. The full <span class="hlt">cloud</span>-drizzle retrieval method is then applied to a selected ACCEPT (Analysis of the Composition of <span class="hlt">Clouds</span> with Extended Polarization Techniques) campaign dataset collected in Cabauw, the Netherlands. An assessment of the retrieval products is performed using three independent methods from the literature; each was specifically developed to retrieve only the <span class="hlt">cloud</span> properties, the drizzle properties below the <span class="hlt">cloud</span> base, or the drizzle fraction within the <span class="hlt">cloud</span>. One-to-one comparisons, taking into account the uncertainties or limitations of each retrieval, show that our results are consistent with what is derived</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A31E2232O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A31E2232O"><span>Assessment of 3D <span class="hlt">cloud</span> radiative transfer effects applied to collocated A-Train data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Okata, M.; Nakajima, T.; Suzuki, K.; Toshiro, I.; Nakajima, T. Y.; Okamoto, H.</p> <p>2017-12-01</p> <p>This study investigates broadband radiative fluxes in the 3D <span class="hlt">cloud</span>-laden atmospheres using a 3D radiative transfer (RT) model, MCstar, and the collocated A-Train <span class="hlt">cloud</span> data. The 3D extinction coefficients are constructed by a newly devised Minimum <span class="hlt">cloud</span> Information Deviation Profiling Method (MIDPM) that extrapolates CPR radar profiles at nadir into off-nadir regions within MODIS swath based on collocated information of MODIS-derived <span class="hlt">cloud</span> properties and radar reflectivity profiles. The method is applied to low level maritime water <span class="hlt">clouds</span>, for which the 3D-RT simulations are performed. The radiative fluxes thus simulated are compared to those obtained from CERES as a way to validate the MIDPM-constructed <span class="hlt">clouds</span> and our 3D-RT simulations. The results show that the simulated SW flux agrees with CERES values within 8 - 50 Wm-2. One of the large biases occurred by cyclic boundary condition that was required to pose into our computational domain limited to 20km by 20km with 1km resolution. Another source of the bias also arises from the 1D assumption for <span class="hlt">cloud</span> property retrievals particularly for thin <span class="hlt">clouds</span>, which tend to be affected by spatial heterogeneity leading to overestimate of the <span class="hlt">cloud</span> optical thickness. These 3D-RT simulations also serve to address another objective of this study, i.e. to characterize the "observed" specific 3D-RT effects by the <span class="hlt">cloud</span> morphology. We extend the computational domain to 100km by 100km for this purpose. The 3D-RT effects are characterized by errors of existing 1D approximations to 3D radiation field. The errors are investigated in terms of their dependence on solar zenith angle (SZA) for the satellite-constructed real <span class="hlt">cloud</span> cases, and we define two indices from the error tendencies. According to the indices, the 3D-RT effects are classified into three <span class="hlt">types</span> which correspond to different simple three morphologies <span class="hlt">types</span>, i.e. isolated <span class="hlt">cloud</span> <span class="hlt">type</span>, upper <span class="hlt">cloud</span>-roughened <span class="hlt">type</span> and lower <span class="hlt">cloud</span>-roughened <span class="hlt">type</span>. These 3D-RT effects linked</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25807597','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25807597"><span><span class="hlt">Cloud</span> computing and patient engagement: leveraging available technology.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Noblin, Alice; Cortelyou-Ward, Kendall; Servan, Rosa M</p> <p>2014-01-01</p> <p><span class="hlt">Cloud</span> computing technology has the potential to transform medical practices and improve patient engagement and quality of care. However, issues such as privacy and security and "fit" can make incorporation of the <span class="hlt">cloud</span> an intimidating decision for many physicians. This article summarizes the four most common <span class="hlt">types</span> of <span class="hlt">clouds</span> and discusses their ideal uses, how they engage patients, and how they improve the quality of care offered. This technology also can be used to meet Meaningful Use requirements 1 and 2; and, if speculation is correct, the <span class="hlt">cloud</span> will provide the necessary support needed for Meaningful Use 3 as well.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20070031219&hterms=kaufman&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dkaufman','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070031219&hterms=kaufman&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dkaufman"><span>Smoke and Pollution Aerosol Effect on <span class="hlt">Cloud</span> Cover</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kaufman, Yoram J.; Koren, Ilan</p> <p>2006-01-01</p> <p>Pollution and smoke aerosols can increase or decrease the <span class="hlt">cloud</span> cover. This duality in the effects of aerosols forms one of the largest uncertainties in climate research. Using solar measurements from Aerosol Robotic Network sites around the globe, we show an increase in <span class="hlt">cloud</span> cover with an increase in the aerosol column concentration and an inverse dependence on the aerosol absorption of sunlight. The emerging rule appears to be independent of geographical location or aerosol <span class="hlt">type</span>, thus increasing our confidence in the understanding of these aerosol effects on the <span class="hlt">clouds</span> and climate. Preliminary estimates suggest an increase of 5% in <span class="hlt">cloud</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1213814-unified-parameterization-clouds-turbulence-using-clubb-subcolumns-community-atmosphere-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1213814-unified-parameterization-clouds-turbulence-using-clubb-subcolumns-community-atmosphere-model"><span>A unified parameterization of <span class="hlt">clouds</span> and turbulence using CLUBB and subcolumns in the Community Atmosphere Model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Thayer-Calder, K.; Gettelman, A.; Craig, C.; ...</p> <p>2015-06-30</p> <p>Most global climate models parameterize separate <span class="hlt">cloud</span> <span class="hlt">types</span> using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified <span class="hlt">cloud</span> parameterization uses one equation set to represent all <span class="hlt">cloud</span> <span class="hlt">types</span>. Such <span class="hlt">cloud</span> <span class="hlt">types</span> include stratiform liquid and ice <span class="hlt">cloud</span>, shallow convective <span class="hlt">cloud</span>, and deep convective <span class="hlt">cloud</span>. Vital to the success of a unified parameterization is a general interface between <span class="hlt">clouds</span> and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, <span class="hlt">cloud</span> liquid, and <span class="hlt">cloud</span> ice, and feeding the sample points into amore » microphysics scheme.This study evaluates a unified <span class="hlt">cloud</span> parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave <span class="hlt">cloud</span> forcing, liquid water path, long-wave <span class="hlt">cloud</span> forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1227326-unified-parameterization-clouds-turbulence-using-clubb-subcolumns-community-atmosphere-model','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1227326-unified-parameterization-clouds-turbulence-using-clubb-subcolumns-community-atmosphere-model"><span>A unified parameterization of <span class="hlt">clouds</span> and turbulence using CLUBB and subcolumns in the Community Atmosphere Model</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Thayer-Calder, Katherine; Gettelman, A.; Craig, Cheryl; ...</p> <p>2015-12-01</p> <p>Most global climate models parameterize separate <span class="hlt">cloud</span> <span class="hlt">types</span> using separate parameterizations.This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified <span class="hlt">cloud</span> parameterization uses one equation set to represent all <span class="hlt">cloud</span> <span class="hlt">types</span>. Such <span class="hlt">cloud</span> <span class="hlt">types</span> include stratiform liquid and ice <span class="hlt">cloud</span>, shallow convective <span class="hlt">cloud</span>, and deep convective <span class="hlt">cloud</span>. Vital to the success of a unified parameterization is a general interface between <span class="hlt">clouds</span> and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, <span class="hlt">cloud</span> liquid, and <span class="hlt">cloud</span> ice, and feeding the sample points into a microphysicsmore » scheme. This study evaluates a unified <span class="hlt">cloud</span> parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. In conclusion, the new model shows a degradation in precipitation skill but improvements in short-wave <span class="hlt">cloud</span> forcing, liquid water path, long-wave <span class="hlt">cloud</span> forcing, perceptible water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2000JCli...13..245N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2000JCli...13..245N"><span>Low <span class="hlt">Cloud</span> <span class="hlt">Type</span> over the Ocean from Surface Observations. Part III: Relationship to Vertical Motion and the Regional Surface Synoptic Environment.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Norris, Joel R.; Klein, Stephen A.</p> <p>2000-01-01</p> <p>Composite large-scale dynamical fields contemporaneous with low <span class="hlt">cloud</span> <span class="hlt">types</span> observed at midlatitude Ocean Weather Station (OWS) C and eastern subtropical OWS N are used to establish representative relationships between low <span class="hlt">cloud</span> <span class="hlt">type</span> and the synoptic environment. The composites are constructed by averaging meteorological observations of surface wind and sea level pressure from volunteering observing ships (VOS) and analyses of sea level pressure, 1000-mb wind, and 700-mb pressure vertical velocity from the National Centers for Environmental Prediction-National Center for Atmospheric Research (NCEP-NCAR) reanalysis project on those dates and times of day when a particular low <span class="hlt">cloud</span> <span class="hlt">type</span> was reported at the OWS.VOS and NCEP results for OWS C during summer show that bad-weather stratus occurs with strong convergence and ascent slightly ahead of a surface low center and trough. Cumulus-under-stratocumulus and moderate and large cumulus occur with divergence and subsidence in the cold sector of an extratropical cyclone. Both sky-obscuring fog and no-low-<span class="hlt">cloud</span> typically occur with southwesterly flow from regions of warmer sea surface temperature and differ primarily according to slight surface convergence and stronger warm advection in the case of sky-obscuring fog or surface divergence and weaker warm advection in the case of no-low-<span class="hlt">cloud</span>. Fair-weather stratus and ordinary stratocumulus are associated with a mixture of meteorological conditions, but differ with respect to vertical motion in the environment. Fair-weather stratus occurs most commonly in the presence of slight convergence and ascent, while stratocumulus often occurs in the presence of divergence and subsidence.Surface divergence and estimated subsidence at the top of the boundary layer are calculated from VOS observations. At both OWS C and OWS N during summer and winter these values are large for ordinary stratocumulus, less for cumulus-under-stratocumulus, and least (and sometimes slightly negative) for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20050131814&hterms=library&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dlibrary','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20050131814&hterms=library&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dlibrary"><span>Coupled fvGCM-GCE Modeling System, 3D <span class="hlt">Cloud</span>-Resolving Model and <span class="hlt">Cloud</span> Library</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tao, Wei-Kuo</p> <p>2005-01-01</p> <p>Recent GEWEX <span class="hlt">Cloud</span> System Study (GCSS) model comparison projects have indicated that <span class="hlt">cloud</span>-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various <span class="hlt">types</span> of <span class="hlt">clouds</span> and <span class="hlt">cloud</span> systems from Merent geographic locations. Current and future NASA satellite programs can provide <span class="hlt">cloud</span>, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign <span class="hlt">cloud</span> related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A <span class="hlt">cloud</span> library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global <span class="hlt">cloud</span> simulator.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013282','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013282"><span>2D Radiative Processes Near <span class="hlt">Cloud</span> Edges</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Varnai, T.</p> <p>2012-01-01</p> <p>Because of the importance and complexity of dynamical, microphysical, and radiative processes taking place near <span class="hlt">cloud</span> edges, the transition zone between <span class="hlt">clouds</span> and <span class="hlt">cloud</span> free air has been the subject of intense research both in the ASR program and in the wider community. One challenge in this research is that the one-dimensional (1D) radiative models widely used in both remote sensing and dynamical simulations become less accurate near <span class="hlt">cloud</span> edges: The large horizontal gradients in particle concentrations imply that accurate radiative calculations need to consider multi-dimensional radiative interactions among areas that have widely different optical properties. This study examines the way the importance of multidimensional shortwave radiative interactions changes as we approach <span class="hlt">cloud</span> edges. For this, the study relies on radiative simulations performed for a multiyear dataset of <span class="hlt">clouds</span> observed over the NSA, SGP, and TWP sites. This dataset is based on Microbase <span class="hlt">cloud</span> profiles as well as wind measurements and ARM <span class="hlt">cloud</span> classification products. The study analyzes the way the difference between 1D and 2D simulation results increases near <span class="hlt">cloud</span> edges. It considers both monochromatic radiances and broadband radiative heating, and it also examines the influence of factors such as <span class="hlt">cloud</span> <span class="hlt">type</span> and height, and solar elevation. The results provide insights into the workings of radiative processes and may help better interpret radiance measurements and better estimate the radiative impacts of this critical region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080023775','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080023775"><span>The Aerosol/<span class="hlt">Cloud</span>/Ecosystems Mission (ACE)</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Schoeberl, Mark</p> <p>2008-01-01</p> <p>The goals and measurement strategy of the Aerosol/<span class="hlt">Cloud</span>/Ecosystems Mission (ACE) are described. ACE will help to answer fundamental science questions associated with aerosols, <span class="hlt">clouds</span>, air quality and global ocean ecosystems. Specifically, the goals of ACE are: 1) to quantify aerosol-<span class="hlt">cloud</span> interactions and to assess the impact of aerosols on the hydrological cycle and 2) determine Ocean Carbon Cycling and other ocean biological processes. It is expected that ACE will: narrow the uncertainty in aerosol-<span class="hlt">cloud</span>-precipitation interaction and quantify the role of aerosols in climate change; measure the ocean ecosystem changes and precisely quantify ocean carbon uptake; and, improve air quality forecasting by determining the height and <span class="hlt">type</span> of aerosols being transported long distances. Overviews are provided of the aerosol-<span class="hlt">cloud</span> community measurement strategy, aerosol and <span class="hlt">cloud</span> observations over South Asia, and ocean biology research goals. Instruments used in the measurement strategy of the ACE mission are also highlighted, including: multi-beam lidar, multiwavelength high spectra resolution lidar, the ocean color instrument (ORCA)--a spectroradiometer for ocean remote sensing, dual frequency <span class="hlt">cloud</span> radar and high- and low-frequency micron-wave radiometer. Future steps for the ACE mission include refining measurement requirements and carrying out additional instrument and payload studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFMIN24A..04R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFMIN24A..04R"><span>Unidata Cyberinfrastructure in the <span class="hlt">Cloud</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ramamurthy, M. K.; Young, J. W.</p> <p>2016-12-01</p> <p>Data services, software, and user support are critical components of geosciences cyber-infrastructure to help researchers to advance science. With the maturity of and significant advances in <span class="hlt">cloud</span> computing, it has recently emerged as an alternative new paradigm for developing and delivering a broad array of services over the Internet. <span class="hlt">Cloud</span> computing is now mature enough in usability in many areas of science and education, bringing the benefits of virtualized and elastic remote services to infrastructure, software, computation, and data. <span class="hlt">Cloud</span> environments reduce the amount of time and money spent to procure, install, and maintain new hardware and software, and reduce costs through resource pooling and shared infrastructure. Given the enormous potential of <span class="hlt">cloud</span>-based services, Unidata has been moving to augment its software, services, data delivery mechanisms to align with the <span class="hlt">cloud</span>-computing paradigm. To realize the above vision, Unidata has worked toward: * Providing access to many <span class="hlt">types</span> of data from a <span class="hlt">cloud</span> (e.g., via the THREDDS Data Server, RAMADDA and EDEX servers); * Deploying data-proximate tools to easily process, analyze, and visualize those data in a <span class="hlt">cloud</span> environment <span class="hlt">cloud</span> for consumption by any one, by any device, from anywhere, at any time; * Developing and providing a range of pre-configured and well-integrated tools and services that can be deployed by any university in their own private or public <span class="hlt">cloud</span> settings. Specifically, Unidata has developed Docker for "containerized applications", making them easy to deploy. Docker helps to create "disposable" installs and eliminates many configuration challenges. Containerized applications include tools for data transport, access, analysis, and visualization: THREDDS Data Server, Integrated Data Viewer, GEMPAK, Local Data Manager, RAMADDA Data Server, and Python tools; * Leveraging Jupyter as a central platform and hub with its powerful set of interlinking tools to connect interactively data servers</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1911287S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1911287S"><span>Examining the NZESM <span class="hlt">Cloud</span> representation with Self Organizing Maps</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Schuddeboom, Alex; McDonald, Adrian; Parsons, Simon; Morgenstern, Olaf; Harvey, Mike</p> <p>2017-04-01</p> <p>Several different <span class="hlt">cloud</span> regimes are <span class="hlt">identified</span> from MODIS satellite data and the representation of these regimes within the New Zealand Earth System Model (NZESM) is examined. For the development of our <span class="hlt">cloud</span> classification we utilize a neural network algorithm known as self organizing maps (SOMs) on MODIS <span class="hlt">cloud</span> top pressure - <span class="hlt">cloud</span> optical thickness joint histograms. To evaluate the representation of the <span class="hlt">cloud</span> within NZESM, the frequency and geographical distribution of the regimes is compared between the NZESM and satellite data. This approach has the advantage of not only <span class="hlt">identifying</span> differences, but also potentially giving additional information about the discrepancy such as in which regions or phases of <span class="hlt">cloud</span> the differences are most prominent. To allow for a more direct comparison between datasets, the COSP satellite simulation software is applied to NZESM output. COSP works by simulating the observational processes linked to a satellite, within the GCM, so that data can be generated in a way that shares the particular observational bias of specific satellites. By taking the COSP joint histograms and comparing them to our existing classifications we can easily search for discrepancies between the observational data and the simulations without having to be cautious of biases introduced by the satellite. Preliminary results, based on data for 2008, show a significant decrease in overall <span class="hlt">cloud</span> fraction in the NZESM compared to the MODIS satellite data. To better understand the nature of this discrepancy, the <span class="hlt">cloud</span> fraction related to different <span class="hlt">cloud</span> heights and phases were also analysed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1087265-reexamination-state-art-cloud-modeling-shows-real-improvements','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1087265-reexamination-state-art-cloud-modeling-shows-real-improvements"><span>Reexamination of the State of the Art <span class="hlt">Cloud</span> Modeling Shows Real Improvements</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Muehlbauer, Andreas D.; Grabowski, Wojciech W.; Malinowski, S. P.</p> <p></p> <p>Following up on an almost thirty year long history of International <span class="hlt">Cloud</span> Modeling Workshops, that started out with a meeting in Irsee, Germany in 1985, the 8th International <span class="hlt">Cloud</span> Modeling Workshop was held in July 2012 in Warsaw, Poland. The workshop, hosted by the Institute of Geophysics at the University of Warsaw, was organized by Szymon Malinowski and his local team of students and co-chaired by Wojciech Grabowski (NCAR/MMM) and Andreas Muhlbauer (University of Washington). International <span class="hlt">Cloud</span> Modeling Workshops have been held traditionally every four years typically during the week before the International Conference on <span class="hlt">Clouds</span> and Precipitation (ICCP) .more » Rooted in the World Meteorological Organization’s (WMO) weather modification program, the core objectives of the <span class="hlt">Cloud</span> Modeling Workshop have been centered at the numerical modeling of <span class="hlt">clouds</span>, <span class="hlt">cloud</span> microphysics, and the interactions between <span class="hlt">cloud</span> microphysics and <span class="hlt">cloud</span> dynamics. In particular, the goal of the workshop is to provide insight into the pertinent problems of today’s state-of-the-art of <span class="hlt">cloud</span> modeling and to <span class="hlt">identify</span> key deficiencies in the microphysical representation of <span class="hlt">clouds</span> in numerical models and <span class="hlt">cloud</span> parameterizations. In recent years, the workshop has increasingly shifted the focus toward modeling the interactions between aerosols and <span class="hlt">clouds</span> and provided case studies to investigate both the effects of aerosols on <span class="hlt">clouds</span> and precipitation as well as the impact of <span class="hlt">cloud</span> and precipitation processes on aerosols. This time, about 60 (?) scientists from about 10 (?) different countries participated in the workshop and contributed with discussions, oral and poster presentations to the workshop’s plenary and breakout sessions. Several case leaders contributed to the workshop by setting up five observationally-based case studies covering a wide range of <span class="hlt">cloud</span> <span class="hlt">types</span>, namely, marine stratocumulus, mid-latitude squall lines, mid-latitude cirrus <span class="hlt">clouds</span>, Arctic stratus and winter</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018MNRAS.tmp.1519V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018MNRAS.tmp.1519V"><span>Molecular <span class="hlt">Cloud</span> Evolution VI. Measuring <span class="hlt">cloud</span> ages</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vázquez-Semadeni, Enrique; Zamora-Avilés, Manuel; Galván-Madrid, Roberto; Forbrich, Jan</p> <p>2018-06-01</p> <p>In previous contributions, we have presented an analytical model describing the evolution of molecular <span class="hlt">clouds</span> (MCs) undergoing hierarchical gravitational contraction. The <span class="hlt">cloud</span>'s evolution is characterized by an initial increase in its mass, density, and star formation rate (SFR) and efficiency (SFE) as it contracts, followed by a decrease of these quantities as newly formed massive stars begin to disrupt the <span class="hlt">cloud</span>. The main parameter of the model is the maximum mass reached by the <span class="hlt">cloud</span> during its evolution. Thus, specifying the instantaneous mass and some other variable completely determines the <span class="hlt">cloud</span>'s evolutionary stage. We apply the model to interpret the observed scatter in SFEs of the <span class="hlt">cloud</span> sample compiled by Lada et al. as an evolutionary effect so that, although <span class="hlt">clouds</span> such as California and Orion A have similar masses, they are in very different evolutionary stages, causing their very different observed SFRs and SFEs. The model predicts that the California <span class="hlt">cloud</span> will eventually reach a significantly larger total mass than the Orion A <span class="hlt">cloud</span>. Next, we apply the model to derive estimated ages of the <span class="hlt">clouds</span> since the time when approximately 25% of their mass had become molecular. We find ages from ˜1.5 to 27 Myr, with the most inactive <span class="hlt">clouds</span> being the youngest. Further predictions of the model are that <span class="hlt">clouds</span> with very low SFEs should have massive atomic envelopes constituting the majority of their gravitational mass, and that low-mass <span class="hlt">clouds</span> (M ˜ 103-104M⊙) end their lives with a mini-burst of star formation, reaching SFRs ˜300-500 M⊙ Myr-1. By this time, they have contracted to become compact (˜1 pc) massive star-forming clumps, in general embedded within larger GMCs.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_13");'>13</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li class="active"><span>15</span></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_15 --> <div id="page_16" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="301"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012JGRD..11723207J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012JGRD..11723207J"><span>Characterization of Arctic ice <span class="hlt">cloud</span> properties observed during ISDAC</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jouan, Caroline; Girard, Eric; Pelon, Jacques; Gultepe, Ismail; Delanoë, Julien; Blanchet, Jean-Pierre</p> <p>2012-12-01</p> <p>Extensive measurements from ground-based sites and satellite remote sensing (<span class="hlt">Cloud</span>Sat and CALIPSO) reveal the existence of two <span class="hlt">types</span> of ice <span class="hlt">clouds</span> (TICs) in the Arctic during the polar night and early spring. The first <span class="hlt">type</span> (TIC-2A), being topped by a cover of nonprecipitating very small (radar unseen) ice crystals (TIC-1), is found more frequently in pristine environment, whereas the second <span class="hlt">type</span> (TIC-2B), detected by both sensors, is associated preferentially with a high concentration of aerosols. To further investigate the microphysical properties of TIC-1/2A and TIC-2B, airborne in situ and satellite measurements of specific cases observed during Indirect and Semi-Direct Aerosol Campaign (ISDAC) have been analyzed. For the first time, Arctic TIC-1/2A and TIC-2B microstructures are compared using in situ <span class="hlt">cloud</span> observations. Results show that the differences between them are confined in the upper part of the <span class="hlt">clouds</span> where ice nucleation occurs. TIC-2B <span class="hlt">clouds</span> are characterized by fewer (by more than 1 order of magnitude) and larger (by a factor of 2 to 3) ice crystals and a larger ice supersaturation (of 15-20%) compared to TIC-1/2A. Ice crystal growth in TIC-2B <span class="hlt">clouds</span> seems explosive, whereas it seems more gradual in TIC-1/2A. It is hypothesized that these differences are linked to the number concentration and the chemical composition of aerosols. The ice crystal growth rate in very cold conditions impinges on the precipitation efficiency, dehydration and radiation balance. These results represent an essential and important first step to relate previous modeling, remote sensing and laboratory studies with TICs <span class="hlt">cloud</span> in situ observations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AGUFM.A21D0127N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFM.A21D0127N"><span>Entrainment in Laboratory Simulations of Cumulus <span class="hlt">Cloud</span> Flows</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Narasimha, R.; Diwan, S.; Subrahmanyam, D.; Sreenivas, K. R.; Bhat, G. S.</p> <p>2010-12-01</p> <p>A variety of cumulus <span class="hlt">cloud</span> flows, including congestus (both shallow bubble and tall tower <span class="hlt">types</span>), mediocris and fractus have been generated in a water tank by simulating the release of latent heat in real <span class="hlt">clouds</span>. The simulation is achieved through ohmic heating, injected volumetrically into the flow by applying suitable voltages between diametral cross-sections of starting jets and plumes of electrically conducting fluid (acidified water). Dynamical similarity between atmospheric and laboratory <span class="hlt">cloud</span> flows is achieved by duplicating values of an appropriate non-dimensional heat release number. Velocity measurements, made by laser instrumentation, show that the Taylor entrainment coefficient generally increases just above the level of commencement of heat injection (corresponding to condensation level in the real <span class="hlt">cloud</span>). Subsequently the coefficient reaches a maximum before declining to the very low values that characterize tall cumulus towers. The experiments also simulate the protected core of real <span class="hlt">clouds</span>. Cumulus Congestus : Atmospheric <span class="hlt">cloud</span> (left), simulated laboratory <span class="hlt">cloud</span> (right). Panels below show respectively total heat injected and vertical profile of heating in the laboratory <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1402541-low-cloud-feedbacks-from-cloud-controlling-factors-review','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1402541-low-cloud-feedbacks-from-cloud-controlling-factors-review"><span>Low-<span class="hlt">Cloud</span> Feedbacks from <span class="hlt">Cloud</span>-Controlling Factors: A Review</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Klein, Stephen A.; Hall, Alex; Norris, Joel R.; ...</p> <p>2017-10-24</p> <p>Here, the response to warming of tropical low-level <span class="hlt">clouds</span> including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these <span class="hlt">clouds</span>. These inadequacies have led to alternative approaches to predict low-<span class="hlt">cloud</span> feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low <span class="hlt">clouds</span> and the “<span class="hlt">cloud</span>-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the <span class="hlt">cloud</span>-controlling factors change with climate warming,more » one can predict low-<span class="hlt">cloud</span> feedbacks without using any model simulation of low <span class="hlt">clouds</span>. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-<span class="hlt">cloud</span> feedback. Recent studies using this approach predict that the tropical low-<span class="hlt">cloud</span> feedback is positive mainly due to the observation that reflection of solar radiation by low <span class="hlt">clouds</span> decreases as temperature increases, holding all other <span class="hlt">cloud</span>-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other <span class="hlt">cloud</span>-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low <span class="hlt">clouds</span> to the global mean <span class="hlt">cloud</span> feedback is 0.25 ± 0.18 W m –2 K –1 (90% confidence interval), suggesting it is very unlikely that tropical low <span class="hlt">clouds</span> reduce total global <span class="hlt">cloud</span> feedback. Because the prediction of positive tropical low-<span class="hlt">cloud</span> feedback with this approach is consistent with independent evidence from low-<span class="hlt">cloud</span> feedback studies using high-resolution <span class="hlt">cloud</span> models, progress is being made in reducing this key climate uncertainty.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1402541-low-cloud-feedbacks-from-cloud-controlling-factors-review','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1402541-low-cloud-feedbacks-from-cloud-controlling-factors-review"><span>Low-<span class="hlt">Cloud</span> Feedbacks from <span class="hlt">Cloud</span>-Controlling Factors: A Review</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Klein, Stephen A.; Hall, Alex; Norris, Joel R.</p> <p></p> <p>Here, the response to warming of tropical low-level <span class="hlt">clouds</span> including both marine stratocumulus and trade cumulus is a major source of uncertainty in projections of future climate. Climate model simulations of the response vary widely, reflecting the difficulty the models have in simulating these <span class="hlt">clouds</span>. These inadequacies have led to alternative approaches to predict low-<span class="hlt">cloud</span> feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low <span class="hlt">clouds</span> and the “<span class="hlt">cloud</span>-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the <span class="hlt">cloud</span>-controlling factors change with climate warming,more » one can predict low-<span class="hlt">cloud</span> feedbacks without using any model simulation of low <span class="hlt">clouds</span>. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-<span class="hlt">cloud</span> feedback. Recent studies using this approach predict that the tropical low-<span class="hlt">cloud</span> feedback is positive mainly due to the observation that reflection of solar radiation by low <span class="hlt">clouds</span> decreases as temperature increases, holding all other <span class="hlt">cloud</span>-controlling factors fixed. The positive feedback from temperature is partially offset by a negative feedback from the tendency for the inversion strength to increase in a warming world, with other <span class="hlt">cloud</span>-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low <span class="hlt">clouds</span> to the global mean <span class="hlt">cloud</span> feedback is 0.25 ± 0.18 W m –2 K –1 (90% confidence interval), suggesting it is very unlikely that tropical low <span class="hlt">clouds</span> reduce total global <span class="hlt">cloud</span> feedback. Because the prediction of positive tropical low-<span class="hlt">cloud</span> feedback with this approach is consistent with independent evidence from low-<span class="hlt">cloud</span> feedback studies using high-resolution <span class="hlt">cloud</span> models, progress is being made in reducing this key climate uncertainty.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4432776','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4432776"><span><span class="hlt">Cloud</span> and Traditional Videoconferencing Technology for Telemedicine and Distance Learning</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Zhang, Kai; Locatis, Craig; Ackerman, Michael</p> <p>2015-01-01</p> <p>Abstract Introduction: <span class="hlt">Cloud</span>-based videoconferencing versus traditional systems are described for possible use in telemedicine and distance learning. Materials and Methods: Differences between traditional and <span class="hlt">cloud</span>-based videoconferencing systems are examined, and the methods for <span class="hlt">identifying</span> and testing systems are explained. Findings are presented characterizing the <span class="hlt">cloud</span> conferencing genre and its attributes versus traditional H.323 conferencing. Results: Because the technology is rapidly evolving and needs to be evaluated in reference to local needs, it is strongly recommended that this or other reviews not be considered substitutes for personal hands-on experience. Conclusions: This review <span class="hlt">identifies</span> key attributes of the technology that can be used to appraise the relevance of <span class="hlt">cloud</span> conferencing technology and to determine whether migration from traditional technology to a <span class="hlt">cloud</span> environment is warranted. An evaluation template is provided for assessing systems appropriateness. PMID:25785761</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ApJ...835..142T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ApJ...835..142T"><span>Triggered O Star Formation in M20 via <span class="hlt">Cloud-Cloud</span> Collision: Comparisons between High-resolution CO Observations and Simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Torii, K.; Hattori, Y.; Hasegawa, K.; Ohama, A.; Haworth, T. J.; Shima, K.; Habe, A.; Tachihara, K.; Mizuno, N.; Onishi, T.; Mizuno, A.; Fukui, Y.</p> <p>2017-02-01</p> <p>Understanding high-mass star formation is one of the top-priority issues in astrophysics. Recent observational studies have revealed that <span class="hlt">cloud-cloud</span> collisions may play a role in high-mass star formation in several places in the Milky Way and the Large Magellanic <span class="hlt">Cloud</span>. The Trifid Nebula M20 is a well-known Galactic H II region ionized by a single O7.5 star. In 2011, based on the CO observations with NANTEN2, we reported that the O star was formed by the collision between two molecular <span class="hlt">clouds</span> ˜0.3 Myr ago. Those observations <span class="hlt">identified</span> two molecular <span class="hlt">clouds</span> toward M20, traveling at a relative velocity of 7.5 {km} {{{s}}}-1. This velocity separation implies that the <span class="hlt">clouds</span> cannot be gravitationally bound to M20, but since the <span class="hlt">clouds</span> show signs of heating by the stars there they must be spatially coincident with it. A collision is therefore highly possible. In this paper we present the new CO J = 1-0 and J = 3-2 observations of the colliding <span class="hlt">clouds</span> in M20 performed with the Mopra and ASTE telescopes. The high-resolution observations revealed that the two molecular <span class="hlt">clouds</span> have peculiar spatial and velocity structures, I.e., a spatially complementary distribution between the two <span class="hlt">clouds</span> and a bridge feature that connects the two <span class="hlt">clouds</span> in velocity space. Based on a new comparison with numerical models, we find that this complementary distribution is an expected outcome of <span class="hlt">cloud-cloud</span> collisions, and that the bridge feature can be interpreted as the turbulent gas excited at the interface of the collision. Our results reinforce the <span class="hlt">cloud-cloud</span> collision scenario in M20.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008cosp...37.3208T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008cosp...37.3208T"><span>Comparison of <span class="hlt">Cloud</span> and Aerosol Detection between CERES Edition 3 <span class="hlt">Cloud</span> Mask and CALIPSO Version 2 Data Products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Trepte, Qing; Minnis, Patrick; Sun-Mack, Sunny; Trepte, Charles</p> <p></p> <p><span class="hlt">Clouds</span> and aerosol play important roles in the global climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a crucial first step in determining their influence on surface and top-of-atmosphere radiative fluxes. This paper presents a comparison analysis of a new version of the <span class="hlt">Clouds</span> and Earth's Radiant Energy System (CERES) Edition 3 <span class="hlt">cloud</span> detection algorithms using Aqua MODIS data with the recently released <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 2 Vertical Feature Mask (VFM). Improvements in CERES Edition 3 <span class="hlt">cloud</span> mask include dust detection, thin cirrus tests, enhanced low <span class="hlt">cloud</span> detection at night, and a smoother transition from mid-latitude to polar regions. For the CALIPSO Version 2 data set, changes to the lidar calibration can result in significant improvements to its identification of optically thick aerosol layers. The Aqua and CALIPSO satellites, part of the A-train satellite constellation, provide a unique opportunity for validating passive sensor <span class="hlt">cloud</span> and aerosol detection using an active sensor. In this paper, individual comparison cases will be discussed for different <span class="hlt">types</span> of <span class="hlt">clouds</span> and aerosols over various surfaces, for daytime and nighttime conditions, and for regions ranging from the tropics to the poles. Examples will include an assessment of the CERES detection algorithm for optically thin cirrus, marine stratus, and polar night <span class="hlt">clouds</span> as well as its ability to characterize Saharan dust plumes off the African coast. With the CALIPSO lidar's unique ability to probe the vertical structure of <span class="hlt">clouds</span> and aerosol layers, it provides an excellent validation data set for <span class="hlt">cloud</span> detection algorithms, especially for polar nighttime <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhRvA..96a3418B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhRvA..96a3418B"><span>Antiparticle <span class="hlt">cloud</span> temperatures for antihydrogen experiments</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bianconi, A.; Charlton, M.; Lodi Rizzini, E.; Mascagna, V.; Venturelli, L.</p> <p>2017-07-01</p> <p>A simple rate-equation description of the heating and cooling of antiparticle <span class="hlt">clouds</span> under conditions typical of those found in antihydrogen formation experiments is developed and analyzed. We include single-particle collisional, radiative, and <span class="hlt">cloud</span> expansion effects and, from the modeling calculations, <span class="hlt">identify</span> typical cooling phenomena and trends and relate these to the underlying physics. Some general rules of thumb of use to experimenters are derived.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A52D..03O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A52D..03O"><span>Insights from a Regime Decomposition Approach on CERES and <span class="hlt">Cloud</span>Sat-inferred <span class="hlt">Cloud</span> Radiative Effects</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oreopoulos, L.; Cho, N.; Lee, D.</p> <p>2015-12-01</p> <p>Our knowledge of the <span class="hlt">Cloud</span> Radiative Effect (CRE) not only at the Top-of-the-Atmosphere (TOA), but also (with the help of some modeling) at the surface (SFC) and within the atmospheric column (ATM) has been steadily growing in recent years. Not only do we have global values for these CREs, but we can now also plot global maps of their geographical distribution. The next step in our effort to advance our knowledge of CRE is to systematically assess the contributions of prevailing <span class="hlt">cloud</span> systems to the global values. The presentation addresses this issue directly. We <span class="hlt">identify</span> the world's prevailing <span class="hlt">cloud</span> systems, which we call "<span class="hlt">Cloud</span> Regimes" (CRs) via clustering analysis of MODIS (Aqua-Terra) daily joint histograms of <span class="hlt">Cloud</span> Top Pressure and <span class="hlt">Cloud</span> Optical Thickness (TAU) at 1 degree scales. We then composite CERES diurnal values of CRE (TOA, SFC, ATM) separately for each CR by averaging these values for each CR occurrence, and thus find the contribution of each CR to the global value of CRE. But we can do more. We can actually decompose vertical profiles of inferred instantaneous CRE from <span class="hlt">Cloud</span>Sat/CALIPSO (2B-FLXHR-LIDAR product) by averaging over Aqua CR occurrences (since A-Train formation flying allows collocation). Such an analysis greatly enhances our understanding of the radiative importance of prevailing <span class="hlt">cloud</span> mixtures at different atmospheric levels. We can, for example, in addition to examining whether the CERES findings on which CRs contribute to radiative cooling and warming of the atmospheric column are consistent with <span class="hlt">Cloud</span>Sat, also gain insight on why and where exactly this happens from the shape of the full instantaneous CRE vertical profiles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA626463','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA626463"><span>Security and Interdependency in a Public <span class="hlt">Cloud</span>: A Game Theoretic Approach</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2014-08-29</p> <p>maximum utility can be reached (i.e., Pareto efficiency). However, the examples of perverse incentives and information inequality (where this feedback...interdependent structure. <span class="hlt">Cloud</span> computing gives way to two <span class="hlt">types</span> of interdependent relationships: <span class="hlt">cloud</span> host-to- client and <span class="hlt">cloud</span> client -to- client ... Client -to- client interdependency is much less studied than to the above-mentioned <span class="hlt">cloud</span> host-to- client relationship. Although, it can still carry the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931...24B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931...24B"><span>Cloudbus Toolkit for Market-Oriented <span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Buyya, Rajkumar; Pandey, Suraj; Vecchiola, Christian</p> <p></p> <p>This keynote paper: (1) presents the 21st century vision of computing and <span class="hlt">identifies</span> various IT paradigms promising to deliver computing as a utility; (2) defines the architecture for creating market-oriented <span class="hlt">Clouds</span> and computing atmosphere by leveraging technologies such as virtual machines; (3) provides thoughts on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain SLA-oriented resource allocation; (4) presents the work carried out as part of our new <span class="hlt">Cloud</span> Computing initiative, called Cloudbus: (i) Aneka, a Platform as a Service software system containing SDK (Software Development Kit) for construction of <span class="hlt">Cloud</span> applications and deployment on private or public <span class="hlt">Clouds</span>, in addition to supporting market-oriented resource management; (ii) internetworking of <span class="hlt">Clouds</span> for dynamic creation of federated computing environments for scaling of elastic applications; (iii) creation of 3rd party <span class="hlt">Cloud</span> brokering services for building content delivery networks and e-Science applications and their deployment on capabilities of IaaS providers such as Amazon along with Grid mashups; (iv) <span class="hlt">Cloud</span>Sim supporting modelling and simulation of <span class="hlt">Clouds</span> for performance studies; (v) Energy Efficient Resource Allocation Mechanisms and Techniques for creation and management of Green <span class="hlt">Clouds</span>; and (vi) pathways for future research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26230400','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26230400"><span>Design and Implementation of a <span class="hlt">Cloud</span> Computing Adoption Decision Tool: Generating a <span class="hlt">Cloud</span> Road.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bildosola, Iñaki; Río-Belver, Rosa; Cilleruelo, Ernesto; Garechana, Gaizka</p> <p>2015-01-01</p> <p>Migrating to <span class="hlt">cloud</span> computing is one of the current enterprise challenges. This technology provides a new paradigm based on "on-demand payment" for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the <span class="hlt">cloud</span> is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a <span class="hlt">cloud</span> computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the <span class="hlt">cloud</span>, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular <span class="hlt">Cloud</span> Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: to ascertain the degree of knowledge on <span class="hlt">cloud</span> computing and to <span class="hlt">identify</span> the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4521817','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4521817"><span>Design and Implementation of a <span class="hlt">Cloud</span> Computing Adoption Decision Tool: Generating a <span class="hlt">Cloud</span> Road</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Bildosola, Iñaki; Río-Belver, Rosa; Cilleruelo, Ernesto; Garechana, Gaizka</p> <p>2015-01-01</p> <p>Migrating to <span class="hlt">cloud</span> computing is one of the current enterprise challenges. This technology provides a new paradigm based on “on-demand payment” for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the <span class="hlt">cloud</span> is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a <span class="hlt">cloud</span> computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the <span class="hlt">cloud</span>, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular <span class="hlt">Cloud</span> Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: to ascertain the degree of knowledge on <span class="hlt">cloud</span> computing and to <span class="hlt">identify</span> the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible. PMID:26230400</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27656330','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27656330"><span>Frequency and causes of failed MODIS <span class="hlt">cloud</span> property retrievals for liquid phase <span class="hlt">clouds</span> over global oceans.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S; Di Girolamo, Larry; C-Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E</p> <p>2015-05-16</p> <p>Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves <span class="hlt">cloud</span> droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed <span class="hlt">cloud</span> reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r e within the LUT can explain the observed <span class="hlt">cloud</span> reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) <span class="hlt">clouds</span> are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and <span class="hlt">Cloud</span>Sat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading <span class="hlt">type</span> of failure is the " r e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the " r e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP <span class="hlt">cloud</span> pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to <span class="hlt">cloud</span> masking, <span class="hlt">cloud</span> overlapping, and/or <span class="hlt">cloud</span> phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated <span class="hlt">Cloud</span>Sat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these <span class="hlt">clouds</span> are the consequence of true <span class="hlt">cloud</span> microphysics or still due to artifacts not included in this study.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5012132','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5012132"><span>Frequency and causes of failed MODIS <span class="hlt">cloud</span> property retrievals for liquid phase <span class="hlt">clouds</span> over global oceans</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.</p> <p>2015-01-01</p> <p>Abstract Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves <span class="hlt">cloud</span> droplet effective radius (r e) and optical thickness (τ) by projecting observed <span class="hlt">cloud</span> reflectances onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed <span class="hlt">cloud</span> reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) <span class="hlt">clouds</span> are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and <span class="hlt">Cloud</span>Sat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading <span class="hlt">type</span> of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP <span class="hlt">cloud</span> pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to <span class="hlt">cloud</span> masking, <span class="hlt">cloud</span> overlapping, and/or <span class="hlt">cloud</span> phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated <span class="hlt">Cloud</span>Sat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these <span class="hlt">clouds</span> are the consequence of true <span class="hlt">cloud</span> microphysics or still due to artifacts not included in this study. PMID:27656330</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970025054','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970025054"><span>The EOS CERES Global <span class="hlt">Cloud</span> Mask</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Berendes, T. A.; Welch, R. M.; Trepte, Q.; Schaaf, C.; Baum, B. A.</p> <p>1996-01-01</p> <p>To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global <span class="hlt">cloud</span> climatology data sets, such as the International Satellite <span class="hlt">Cloud</span> Climatology Experiment (ISCCP) or CLAVR (<span class="hlt">Clouds</span> from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a <span class="hlt">cloud</span> 'mask.' A <span class="hlt">cloud</span> mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The <span class="hlt">cloud</span> imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a <span class="hlt">cloud</span> masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting <span class="hlt">cloud</span> using multispectral narrowband radiance data. <span class="hlt">Clouds</span> generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the <span class="hlt">cloud</span> <span class="hlt">types</span>, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The <span class="hlt">cloud</span> mask effort builds upon operational experience of several groups that will now be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19920040060&hterms=textural+features&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dtextural%2Bfeatures','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19920040060&hterms=textural+features&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dtextural%2Bfeatures"><span>Pattern recognition analysis of polar <span class="hlt">clouds</span> during summer and winter</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ebert, Elizabeth E.</p> <p>1992-01-01</p> <p>A pattern recognition algorithm is demonstrated which classifies eighteen surface and <span class="hlt">cloud</span> <span class="hlt">types</span> in high-latitude AVHRR imagery based on several spectral and textural features, then estimates the <span class="hlt">cloud</span> properties (fractional coverage, albedo, and brightness temperature) using a hybrid histogram and spatial coherence technique. The summertime version of the algorithm uses both visible and infrared data (AVHRR channels 1-4), while the wintertime version uses only infrared data (AVHRR channels 3-5). Three days of low-resolution AVHRR imagery from the Arctic and Antarctic during January and July 1984 were analyzed for <span class="hlt">cloud</span> <span class="hlt">type</span> and fractional coverage. The analysis showed significant amounts of high cloudiness in the Arctic during one day in winter. The Antarctic summer scene was characterized by heavy <span class="hlt">cloud</span> cover in the southern ocean and relatively clear conditions in the continental interior. A large region of extremely low brightness temperatures in East Antarctica during winter suggests the presence of polar stratospheric <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3567015','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3567015"><span>Comparative Phylogeographic Analyses Illustrate the Complex Evolutionary History of Threatened <span class="hlt">Cloud</span> Forests of Northern Mesoamerica</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Ornelas, Juan Francisco; Sosa, Victoria; Soltis, Douglas E.; Daza, Juan M.; González, Clementina; Soltis, Pamela S.; Gutiérrez-Rodríguez, Carla; de los Monteros, Alejandro Espinosa; Castoe, Todd A.; Bell, Charles; Ruiz-Sanchez, Eduardo</p> <p>2013-01-01</p> <p>Comparative phylogeography can elucidate the influence of historical events on current patterns of biodiversity and can <span class="hlt">identify</span> patterns of co-vicariance among unrelated taxa that span the same geographic areas. Here we analyze temporal and spatial divergence patterns of <span class="hlt">cloud</span> forest plant and animal species and relate them to the evolutionary history of naturally fragmented <span class="hlt">cloud</span> forests–among the most threatened vegetation <span class="hlt">types</span> in northern Mesoamerica. We used comparative phylogeographic analyses to <span class="hlt">identify</span> patterns of co-vicariance in taxa that share geographic ranges across <span class="hlt">cloud</span> forest habitats and to elucidate the influence of historical events on current patterns of biodiversity. We document temporal and spatial genetic divergence of 15 species (including seed plants, birds and rodents), and relate them to the evolutionary history of the naturally fragmented <span class="hlt">cloud</span> forests. We used fossil-calibrated genealogies, coalescent-based divergence time inference, and estimates of gene flow to assess the permeability of putative barriers to gene flow. We also used the hierarchical Approximate Bayesian Computation (HABC) method implemented in the program msBayes to test simultaneous versus non-simultaneous divergence of the <span class="hlt">cloud</span> forest lineages. Our results show shared phylogeographic breaks that correspond to the Isthmus of Tehuantepec, Los Tuxtlas, and the Chiapas Central Depression, with the Isthmus representing the most frequently shared break among taxa. However, dating analyses suggest that the phylogeographic breaks corresponding to the Isthmus occurred at different times in different taxa. Current divergence patterns are therefore consistent with the hypothesis of broad vicariance across the Isthmus of Tehuantepec derived from different mechanisms operating at different times. This study, coupled with existing data on divergence <span class="hlt">cloud</span> forest species, indicates that the evolutionary history of contemporary <span class="hlt">cloud</span> forest lineages is complex and often lineage</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170003746','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170003746"><span>Overview of MPLNET Version 3 <span class="hlt">Cloud</span> Detection</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lewis, Jasper R.; Campbell, James; Welton, Ellsworth J.; Stewart, Sebastian A.; Haftings, Phillip</p> <p>2016-01-01</p> <p>The National Aeronautics and Space Administration Micro Pulse Lidar Network, version 3, <span class="hlt">cloud</span> detection algorithm is described and differences relative to the previous version are highlighted. <span class="hlt">Clouds</span> are <span class="hlt">identified</span> from normalized level 1 signal profiles using two complementary methods. The first method considers vertical signal derivatives for detecting low-level <span class="hlt">clouds</span>. The second method, which detects high-level <span class="hlt">clouds</span> like cirrus, is based on signal uncertainties necessitated by the relatively low signal-to-noise ratio exhibited in the upper troposphere by eye-safe network instruments, especially during daytime. Furthermore, a multitemporal averaging scheme is used to improve <span class="hlt">cloud</span> detection under conditions of a weak signal-to-noise ratio. Diurnal and seasonal cycles of <span class="hlt">cloud</span> occurrence frequency based on one year of measurements at the Goddard Space Flight Center (Greenbelt, Maryland) site are compared for the new and previous versions. The largest differences, and perceived improvement, in detection occurs for high <span class="hlt">clouds</span> (above 5 km, above MSL), which increase in occurrence by over 5%. There is also an increase in the detection of multilayered <span class="hlt">cloud</span> profiles from 9% to 19%. Macrophysical properties and estimates of <span class="hlt">cloud</span> optical depth are presented for a transparent cirrus dataset. However, the limit to which the cirrus <span class="hlt">cloud</span> optical depth could be reliably estimated occurs between 0.5 and 0.8. A comparison using collocated CALIPSO measurements at the Goddard Space Flight Center and Singapore Micro Pulse Lidar Network (MPLNET) sites indicates improvements in <span class="hlt">cloud</span> occurrence frequencies and layer heights.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140010838','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140010838"><span>B- and A-<span class="hlt">Type</span> Stars in the Taurus-Auriga Star-Forming Region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Mooley, Kunal; Hillenbrand, Lynne; Rebull, Luisa; Padgett, Deborah; Knapp, Gillian</p> <p>2013-01-01</p> <p>We describe the results of a search for early-<span class="hlt">type</span> stars associated with the Taurus-Auriga molecular <span class="hlt">cloud</span> complex, a diffuse nearby star-forming region noted as lacking young stars of intermediate and high mass. We investigate several sets of possible O, B, and early A spectral class members. The first is a group of stars for which mid-infrared images show bright nebulae, all of which can be associated with stars of spectral-<span class="hlt">type</span> B. The second group consists of early-<span class="hlt">type</span> stars compiled from (1) literature listings in SIMBAD, (2) B stars with infrared excesses selected from the Spitzer Space Telescope survey of the Taurus <span class="hlt">cloud</span>, (3) magnitude- and color-selected point sources from the Two Micron All Sky Survey, and (4) spectroscopically <span class="hlt">identified</span> early-<span class="hlt">type</span> stars from the Sloan Digital Sky Survey coverage of the Taurus region. We evaluated stars for membership in the Taurus-Auriga star formation region based on criteria involving: spectroscopic and parallactic distances, proper motions and radial velocities, and infrared excesses or line emission indicative of stellar youth. For selected objects, we also model the scattered and emitted radiation from reflection nebulosity and compare the results with the observed spectral energy distributions to further test the plausibility of physical association of the B stars with the Taurus <span class="hlt">cloud</span>. This investigation newly <span class="hlt">identifies</span> as probable Taurus members three B-<span class="hlt">type</span> stars: HR 1445 (HD 28929), t Tau (HD 29763), 72 Tau (HD 28149), and two A-<span class="hlt">type</span> stars: HD 31305 and HD 26212, thus doubling the number of stars A5 or earlier associated with the Taurus <span class="hlt">clouds</span>. Several additional early-<span class="hlt">type</span> sources including HD 29659 and HD 283815 meet some, but not all, of the membership criteria and therefore are plausible, though not secure, members.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_14");'>14</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li class="active"><span>16</span></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_16 --> <div id="page_17" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="321"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A51E2119L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A51E2119L"><span>Sources and Variability of Aerosols and Aerosol-<span class="hlt">Cloud</span> Interactions in the Arctic</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, H.; Zhang, B.; Taylor, P. C.; Moore, R.; Barahona, D.; Fairlie, T. D.; Chen, G.; Ham, S. H.; Kato, S.</p> <p>2017-12-01</p> <p>Arctic sea ice in recent decades has significantly declined. This requires understanding of the Arctic surface energy balance, of which <span class="hlt">clouds</span> are a major driver. However, the mechanisms for the formation and evolution of <span class="hlt">clouds</span> in the Arctic and the roles of aerosols therein are highly uncertain. Here we conduct data analysis and global model simulations to examine the sources and variability of aerosols and aerosol-<span class="hlt">cloud</span> interactions in the Arctic. We use the MERRA-2 reanalysis data (2006-present) from the NASA Global Modeling and Assimilation Office (GMAO) to (1) quantify contributions of different aerosol <span class="hlt">types</span> to the aerosol budget and aerosol optical depths in the Arctic, (2) ­examine aerosol distributions and variability and diagnose the major pathways for mid-latitude pollution transport to the Arctic, including their seasonal and interannual variability, and (3) characterize the distribution and variability of <span class="hlt">clouds</span> (<span class="hlt">cloud</span> optical depth, <span class="hlt">cloud</span> fraction, <span class="hlt">cloud</span> liquid and ice water path, <span class="hlt">cloud</span> top height) in the Arctic. We compare MERRA-2 aerosol and <span class="hlt">cloud</span> properties with those from C3M, a 3-D aerosol and <span class="hlt">cloud</span> data product developed at NASA Langley Research Center and merged from multiple A-Train satellite (CERES, <span class="hlt">Cloud</span>Sat, CALIPSO, and MODIS) observations. We also conduct perturbation experiments using the NASA GEOS-5 chemistry-climate model (with GOCART aerosol module coupled with two-moment <span class="hlt">cloud</span> microphysics), and discuss the roles of various <span class="hlt">types</span> of aerosols in the formation and evolution of <span class="hlt">clouds</span> in the Arctic.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29401656','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29401656"><span>Integrated Change Detection and Classification in Urban Areas Based on Airborne Laser Scanning Point <span class="hlt">Clouds</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Tran, Thi Huong Giang; Ressl, Camillo; Pfeifer, Norbert</p> <p>2018-02-03</p> <p>This paper suggests a new approach for change detection (CD) in 3D point <span class="hlt">clouds</span>. It combines classification and CD in one step using machine learning. The point <span class="hlt">cloud</span> data of both epochs are merged for computing features of four <span class="hlt">types</span>: features describing the point distribution, a feature relating to relative terrain elevation, features specific for the multi-target capability of laser scanning, and features combining the point <span class="hlt">clouds</span> of both epochs to <span class="hlt">identify</span> the change. All these features are merged in the points and then training samples are acquired to create the model for supervised classification, which is then applied to the whole study area. The final results reach an overall accuracy of over 90% for both epochs of eight classes: lost tree, new tree, lost building, new building, changed ground, unchanged building, unchanged tree, and unchanged ground.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1014755','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1014755"><span><span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2010-04-29</p> <p><span class="hlt">Cloud</span> Computing   The answer, my friend, is blowing in the wind.   The answer is blowing in the wind. 1Bingue ‐ Cook  <span class="hlt">Cloud</span>   Computing  STSC 2010... <span class="hlt">Cloud</span>   Computing  STSC 2010 Objectives • Define the <span class="hlt">cloud</span>    • Risks of  <span class="hlt">cloud</span>   computing f l d i• Essence o  c ou  comput ng • Deployed <span class="hlt">clouds</span> in DoD 3Bingue...Cook  <span class="hlt">Cloud</span>   Computing  STSC 2010 Definitions of <span class="hlt">Cloud</span> Computing       <span class="hlt">Cloud</span>   computing  is a model for enabling  b d d ku</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009EGUGA..1112471Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009EGUGA..1112471Z"><span>Comparasion of <span class="hlt">Cloud</span> Cover restituted by POLDER and MODIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.</p> <p>2009-04-01</p> <p>PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the <span class="hlt">cloud</span> cover with very different characteristics. These give us a good opportunity to study the <span class="hlt">clouds</span> system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global <span class="hlt">cloud</span> cover properties. This description is indeed of outermost importance to quantify and understand the effect of <span class="hlt">clouds</span> on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 <span class="hlt">cloud</span> products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global <span class="hlt">cloud</span> cover. This simple yet critical <span class="hlt">cloud</span> parameter need to be clearly understood to allow further comparison of the other <span class="hlt">cloud</span> parameters. From our study, we demonstrate that on average these two sensors both detect the <span class="hlt">clouds</span> fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of <span class="hlt">cloud</span> amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high <span class="hlt">cloud</span> cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small <span class="hlt">cloud</span> amounts that typically present over subtropical oceans and deserts in subsidence aeras are well <span class="hlt">identified</span> by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular <span class="hlt">cloud</span> <span class="hlt">types</span>. With higher spatial resolution, MODIS can better detect the fractional <span class="hlt">clouds</span> thus explaining as one part</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23920847','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23920847"><span>Development of the regional EPR and PACS sharing system on the infrastructure of <span class="hlt">cloud</span> computing technology controlled by patient <span class="hlt">identifier</span> cross reference manager.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Kondoh, Hiroshi; Teramoto, Kei; Kawai, Tatsurou; Mochida, Maki; Nishimura, Motohiro</p> <p>2013-01-01</p> <p>A Newly developed Oshidori-Net2, providing medical professionals with remote access to electronic patient record systems (EPR) and PACSs of four hospitals, of different venders, using <span class="hlt">cloud</span> computing technology and patient <span class="hlt">identifier</span> cross reference manager. The operation was started from April 2012. The patients moved to other hospital were applied. Objective is to show the merit and demerit of the new system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PASJ...70S..48H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PASJ...70S..48H"><span>High-mass star formation possibly triggered by <span class="hlt">cloud-cloud</span> collision in the H II region RCW 34</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hayashi, Katsuhiro; Sano, Hidetoshi; Enokiya, Rei; Torii, Kazufumi; Hattori, Yusuke; Kohno, Mikito; Fujita, Shinji; Nishimura, Atsushi; Ohama, Akio; Yamamoto, Hiroaki; Tachihara, Kengo; Hasegawa, Yutaka; Kimura, Kimihiro; Ogawa, Hideo; Fukui, Yasuo</p> <p>2018-05-01</p> <p>We report on the possibility that the high-mass star located in the H II region RCW 34 was formed by a triggering induced by a collision of molecular <span class="hlt">clouds</span>. Molecular gas distributions of the 12CO and 13CO J = 2-1 and 12CO J = 3-2 lines in the direction of RCW 34 were measured using the NANTEN2 and ASTE telescopes. We found two <span class="hlt">clouds</span> with velocity ranges of 0-10 km s-1 and 10-14 km s-1. Whereas the former <span class="hlt">cloud</span> is as massive as ˜1.4 × 104 M⊙ and has a morphology similar to the ring-like structure observed in the infrared wavelengths, the latter <span class="hlt">cloud</span>, with a mass of ˜600 M⊙, which has not been recognized by previous observations, is distributed to just cover the bubble enclosed by the other <span class="hlt">cloud</span>. The high-mass star with a spectral <span class="hlt">type</span> of O8.5V is located near the boundary of the two <span class="hlt">clouds</span>. The line intensity ratio of 12CO J = 3-2/J = 2-1 yields high values (≳1.0), suggesting that these <span class="hlt">clouds</span> are associated with the massive star. We also confirm that the obtained position-velocity diagram shows a similar distribution to that derived by a numerical simulation of the supersonic collision of two <span class="hlt">clouds</span>. Using the relative velocity between the two <span class="hlt">clouds</span> (˜5 km s-1), the collisional time scale is estimated to be ˜0.2 Myr with the assumption of a distance of 2.5 kpc. These results suggest that the high-mass star in RCW 34 was formed rapidly within a time scale of ˜0.2 Myr via a triggering of a <span class="hlt">cloud-cloud</span> collision.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981425','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5981425"><span>Registration of Laser Scanning Point <span class="hlt">Clouds</span>: A Review</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Cheng, Liang; Chen, Song; Xu, Hao; Wu, Yang; Li, Manchun</p> <p>2018-01-01</p> <p>The integration of multi-platform, multi-angle, and multi-temporal LiDAR data has become important for geospatial data applications. This paper presents a comprehensive review of LiDAR data registration in the fields of photogrammetry and remote sensing. At present, a coarse-to-fine registration strategy is commonly used for LiDAR point <span class="hlt">clouds</span> registration. The coarse registration method is first used to achieve a good initial position, based on which registration is then refined utilizing the fine registration method. According to the coarse-to-fine framework, this paper reviews current registration methods and their methodologies, and <span class="hlt">identifies</span> important differences between them. The lack of standard data and unified evaluation systems is <span class="hlt">identified</span> as a factor limiting objective comparison of different methods. The paper also describes the most commonly-used point <span class="hlt">cloud</span> registration error analysis methods. Finally, avenues for future work on LiDAR data registration in terms of applications, data, and technology are discussed. In particular, there is a need to address registration of multi-angle and multi-scale data from various newly available <span class="hlt">types</span> of LiDAR hardware, which will play an important role in diverse applications such as forest resource surveys, urban energy use, cultural heritage protection, and unmanned vehicles. PMID:29883397</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29883397','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29883397"><span>Registration of Laser Scanning Point <span class="hlt">Clouds</span>: A Review.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cheng, Liang; Chen, Song; Liu, Xiaoqiang; Xu, Hao; Wu, Yang; Li, Manchun; Chen, Yanming</p> <p>2018-05-21</p> <p>The integration of multi-platform, multi-angle, and multi-temporal LiDAR data has become important for geospatial data applications. This paper presents a comprehensive review of LiDAR data registration in the fields of photogrammetry and remote sensing. At present, a coarse-to-fine registration strategy is commonly used for LiDAR point <span class="hlt">clouds</span> registration. The coarse registration method is first used to achieve a good initial position, based on which registration is then refined utilizing the fine registration method. According to the coarse-to-fine framework, this paper reviews current registration methods and their methodologies, and <span class="hlt">identifies</span> important differences between them. The lack of standard data and unified evaluation systems is <span class="hlt">identified</span> as a factor limiting objective comparison of different methods. The paper also describes the most commonly-used point <span class="hlt">cloud</span> registration error analysis methods. Finally, avenues for future work on LiDAR data registration in terms of applications, data, and technology are discussed. In particular, there is a need to address registration of multi-angle and multi-scale data from various newly available <span class="hlt">types</span> of LiDAR hardware, which will play an important role in diverse applications such as forest resource surveys, urban energy use, cultural heritage protection, and unmanned vehicles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931...69L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931...69L"><span>Trust Model to Enhance Security and Interoperability of <span class="hlt">Cloud</span> Environment</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Wenjuan; Ping, Lingdi</p> <p></p> <p>Trust is one of the most important means to improve security and enable interoperability of current heterogeneous independent <span class="hlt">cloud</span> platforms. This paper first analyzed several trust models used in large and distributed environment and then introduced a novel <span class="hlt">cloud</span> trust model to solve security issues in cross-<span class="hlt">clouds</span> environment in which <span class="hlt">cloud</span> customer can choose different providers' services and resources in heterogeneous domains can cooperate. The model is domain-based. It divides one <span class="hlt">cloud</span> provider's resource nodes into the same domain and sets trust agent. It distinguishes two different roles <span class="hlt">cloud</span> customer and <span class="hlt">cloud</span> server and designs different strategies for them. In our model, trust recommendation is treated as one <span class="hlt">type</span> of <span class="hlt">cloud</span> services just like computation or storage. The model achieves both identity authentication and behavior authentication. The results of emulation experiments show that the proposed model can efficiently and safely construct trust relationship in cross-<span class="hlt">clouds</span> environment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA10076&hterms=ammonia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dammonia','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA10076&hterms=ammonia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dammonia"><span>Ammonia Ice <span class="hlt">Clouds</span> on Jupiter</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2007-01-01</p> <p><p/> The top <span class="hlt">cloud</span> layer on Jupiter is thought to consist of ammonia ice, but most of that ammonia 'hides' from spectrometers. It does not absorb light in the same way ammonia does. To many scientists, this implies that ammonia churned up from lower layers of the atmosphere 'ages' in some way after it condenses, possibly by being covered with a photochemically generated hydrocarbon mixture. The New Horizons Linear Etalon Imaging Spectral Array (LEISA), the half of the Ralph instrument that is able to 'see' in infrared wavelengths that are absorbed by ammonia ice, spotted these <span class="hlt">clouds</span> and watched them evolve over five Jupiter days (about 40 Earth hours). In these images, spectroscopically <span class="hlt">identified</span> fresh ammonia <span class="hlt">clouds</span> are shown in bright blue. The largest <span class="hlt">cloud</span> appeared as a localized source on day 1, intensified and broadened on day 2, became more diffuse on days 3 and 4, and disappeared on day 5. The diffusion seemed to follow the movement of a dark spot along the boundary of the oval region. Because the source of this ammonia lies deeper than the <span class="hlt">cloud</span>, images like these can tell scientists much about the dynamics and heat conduction in Jupiter's lower atmosphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25218122','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25218122"><span>Distributed denial of service (DDoS) attack in <span class="hlt">cloud</span>- assisted wireless body area networks: a systematic literature review.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Latif, Rabia; Abbas, Haider; Assar, Saïd</p> <p>2014-11-01</p> <p>Wireless Body Area Networks (WBANs) have emerged as a promising technology that has shown enormous potential in improving the quality of healthcare, and has thus found a broad range of medical applications from ubiquitous health monitoring to emergency medical response systems. The huge amount of highly sensitive data collected and generated by WBAN nodes requires an ascendable and secure storage and processing infrastructure. Given the limited resources of WBAN nodes for storage and processing, the integration of WBANs and <span class="hlt">cloud</span> computing may provide a powerful solution. However, despite the benefits of <span class="hlt">cloud</span>-assisted WBAN, several security issues and challenges remain. Among these, data availability is the most nagging security issue. The most serious threat to data availability is a distributed denial of service (DDoS) attack that directly affects the all-time availability of a patient's data. The existing solutions for standalone WBANs and sensor networks are not applicable in the <span class="hlt">cloud</span>. The purpose of this review paper is to <span class="hlt">identify</span> the most threatening <span class="hlt">types</span> of DDoS attacks affecting the availability of a <span class="hlt">cloud</span>-assisted WBAN and review the state-of-the-art detection mechanisms for the <span class="hlt">identified</span> DDoS attacks.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120011583','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011583"><span>The Impacts of an Observationally-Based <span class="hlt">Cloud</span> Fraction and Condensate Overlap Parameterization on a GCM's <span class="hlt">Cloud</span> Radiative Effect</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Lee, Dongmin; Norris, Peter; Yuan, Tianle</p> <p>2011-01-01</p> <p>It has been shown that the details of how <span class="hlt">cloud</span> fraction overlap is treated in GCMs has substantial impact on shortwave and longwave fluxes. Because <span class="hlt">cloud</span> condensate is also horizontally heterogeneous at GCM grid scales, another aspect of <span class="hlt">cloud</span> overlap should in principle also be assessed, namely the vertical overlap of hydrometeor distributions. This <span class="hlt">type</span> of overlap is usually examined in terms of rank correlations, i.e., linear correlations between hydrometeor amount ranks of the overlapping parts of <span class="hlt">cloud</span> layers at specific separation distances. The <span class="hlt">cloud</span> fraction overlap parameter and the rank correlation of hydrometeor amounts can be both expressed as inverse exponential functions of separation distance characterized by their respective decorrelation lengths (e-folding distances). Larger decorrelation lengths mean that hydrometeor fractions and probability distribution functions have high levels of vertical alignment. An analysis of <span class="hlt">Cloud</span>Sat and CALIPSO data reveals that the two aspects of <span class="hlt">cloud</span> overlap are related and their respective decorrelation lengths have a distinct dependence on latitude that can be parameterized and included in a GCM. In our presentation we will contrast the <span class="hlt">Cloud</span> Radiative Effect (CRE) of the GEOS-5 atmospheric GCM (AGCM) when the observationally-based parameterization of decorrelation lengths is used to represent overlap versus the simpler cases of maximum-random overlap and globally constant decorrelation lengths. The effects of specific overlap representations will be examined for both diagnostic and interactive radiation runs in GEOS-5 and comparisons will be made with observed CREs from CERES and <span class="hlt">Cloud</span>Sat (2B-FLXHR product). Since the radiative effects of overlap depend on the <span class="hlt">cloud</span> property distributions of the AGCM, the availability of two different <span class="hlt">cloud</span> schemes in GEOS-5 will give us the opportunity to assess a wide range of potential <span class="hlt">cloud</span> overlap consequences on the model's climate.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9229E..06B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9229E..06B"><span>Study of <span class="hlt">cloud</span> properties using airborne and satellite measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Boscornea, Andreea; Stefan, Sabina; Vajaiac, Sorin Nicolae</p> <p>2014-08-01</p> <p>The present study investigates <span class="hlt">cloud</span> microphysics properties using aircraft and satellite measurements. <span class="hlt">Cloud</span> properties were drawn from data acquired both from in situ measurements with state of the art airborne instrumentation and from satellite products of the MODIS06 System. The used aircraft was ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research, property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania, which is specially equipped for this kind of research. The main tool of the airborne laboratory is a <span class="hlt">Cloud</span>, Aerosol and Precipitation Spectrometer - CAPS (30 bins, 0.51- 50 μm). The data was recorded during two flights during the winter 2013-2014, over a flat region in the south-eastern part of Romania (between Bucharest and Constanta). The analysis of <span class="hlt">cloud</span> particle size variations and <span class="hlt">cloud</span> liquid water content provided by CAPS can explain <span class="hlt">cloud</span> processes, and can also indicate the extent of aerosols effects on <span class="hlt">clouds</span>. The results, such as <span class="hlt">cloud</span> coverage and/or <span class="hlt">cloud</span> <span class="hlt">types</span>, microphysical parameters of aerosols on the one side and the <span class="hlt">cloud</span> microphysics parameters obtained from aircraft flights on the other side, was used to illustrate the importance of microphysics <span class="hlt">cloud</span> properties for including the radiative effects of <span class="hlt">clouds</span> in the regional climate models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1994JApMe..33..107B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1994JApMe..33..107B"><span>Cirrus <span class="hlt">Cloud</span> Retrieval Using Infrared Sounding Data: Multilevel <span class="hlt">Cloud</span> Errors.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Baum, Bryan A.; Wielicki, Bruce A.</p> <p>1994-01-01</p> <p>In this study we perform an error analysis for <span class="hlt">cloud</span>-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-µm CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform <span class="hlt">cloud</span>. This analysis includes standard deviation and bias error due to instrument noise and the presence of two <span class="hlt">cloud</span> layers, the lower of which is opaque. Instantaneous <span class="hlt">cloud</span> pressure retrieval errors are determined for a range of <span class="hlt">cloud</span> amounts (0.1 1.0) and <span class="hlt">cloud</span>-top pressures (850250 mb). Large <span class="hlt">cloud</span>-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive <span class="hlt">cloud</span> layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-<span class="hlt">cloud</span> elective <span class="hlt">cloud</span> amount and with decreasing <span class="hlt">cloud</span> height (increasing pressure). Errors in retrieved upper-<span class="hlt">cloud</span> pressure result in corresponding errors in derived effective <span class="hlt">cloud</span> amount. For the case in which a HIRS FOV has two distinct <span class="hlt">cloud</span> layers, the difference between the retrieved and actual <span class="hlt">cloud</span>-top pressure is positive in all casts, meaning that the retrieved upper-<span class="hlt">cloud</span> height is lower than the actual upper-<span class="hlt">cloud</span> height. In addition, errors in retrieved <span class="hlt">cloud</span> pressure are found to depend upon the lapse rate between the low-level <span class="hlt">cloud</span> top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus <span class="hlt">cloud</span> height caused by instrument noise and by the presence of a lower-level <span class="hlt">cloud</span>. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300—500 mb minimize bias errors. For a <span class="hlt">cloud</span> climatology, the bias errors are most critical.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFM.A23F0336W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFM.A23F0336W"><span><span class="hlt">Cloud</span> Impacts on Pavement Temperature in Energy Balance Models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Walker, C. L.</p> <p>2013-12-01</p> <p>Forecast systems provide decision support for end-users ranging from the solar energy industry to municipalities concerned with road safety. Pavement temperature is an important variable when considering vehicle response to various weather conditions. A complex, yet direct relationship exists between tire and pavement temperatures. Literature has shown that as tire temperature increases, friction decreases which affects vehicle performance. Many forecast systems suffer from inaccurate radiation forecasts resulting in part from the inability to model different <span class="hlt">types</span> of <span class="hlt">clouds</span> and their influence on radiation. This research focused on forecast improvement by determining how <span class="hlt">cloud</span> <span class="hlt">type</span> impacts the amount of shortwave radiation reaching the surface and subsequent pavement temperatures. The study region was the Great Plains where surface solar radiation data were obtained from the High Plains Regional Climate Center's Automated Weather Data Network stations. Road pavement temperature data were obtained from the Meteorological Assimilation Data Ingest System. <span class="hlt">Cloud</span> properties and radiative transfer quantities were obtained from the <span class="hlt">Clouds</span> and Earth's Radiant Energy System mission via Aqua and Terra Moderate Resolution Imaging Spectroradiometer satellite products. An additional <span class="hlt">cloud</span> data set was incorporated from the Naval Research Laboratory <span class="hlt">Cloud</span> Classification algorithm. Statistical analyses using a modified nearest neighbor approach were first performed relating shortwave radiation variability with road pavement temperature fluctuations. Then statistical associations were determined between the shortwave radiation and <span class="hlt">cloud</span> property data sets. Preliminary results suggest that substantial pavement forecasting improvement is possible with the inclusion of <span class="hlt">cloud</span>-specific information. Future model sensitivity testing seeks to quantify the magnitude of forecast improvement.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2006AGUFM.A54B..06M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2006AGUFM.A54B..06M"><span>Evaluation of Passive Multilayer <span class="hlt">Cloud</span> Detection Using Preliminary <span class="hlt">Cloud</span>Sat and CALIPSO <span class="hlt">Cloud</span> Profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.</p> <p>2006-12-01</p> <p>During the last few years, several algorithms have been developed to detect and retrieve multilayered <span class="hlt">clouds</span> using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as <span class="hlt">cloud</span> radars and lidars that can "see" through different layers of <span class="hlt">clouds</span>. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and <span class="hlt">Cloud</span>Sat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated <span class="hlt">cloud</span> radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping <span class="hlt">cloud</span> systems and to retrieve the <span class="hlt">cloud</span> liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES <span class="hlt">cloud</span> retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing <span class="hlt">cloud</span> retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice <span class="hlt">clouds</span>. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary <span class="hlt">Cloud</span>Sat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water <span class="hlt">clouds</span> in overlapped conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUSM.A54B..06M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUSM.A54B..06M"><span>Evaluation of Passive Multilayer <span class="hlt">Cloud</span> Detection Using Preliminary <span class="hlt">Cloud</span>Sat and CALIPSO <span class="hlt">Cloud</span> Profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.</p> <p>2005-05-01</p> <p>During the last few years, several algorithms have been developed to detect and retrieve multilayered <span class="hlt">clouds</span> using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as <span class="hlt">cloud</span> radars and lidars that can "see" through different layers of <span class="hlt">clouds</span>. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and <span class="hlt">Cloud</span>Sat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated <span class="hlt">cloud</span> radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping <span class="hlt">cloud</span> systems and to retrieve the <span class="hlt">cloud</span> liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES <span class="hlt">cloud</span> retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing <span class="hlt">cloud</span> retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice <span class="hlt">clouds</span>. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary <span class="hlt">Cloud</span>Sat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water <span class="hlt">clouds</span> in overlapped conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-ast-01-042.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-ast-01-042.html"><span>Oblique view of <span class="hlt">cloud</span> patterns over Pacific Ocean</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>1975-07-16</p> <p>AST-01-042 (16 July 1975) --- An oblique view of unique <span class="hlt">cloud</span> patterns over the Pacific Ocean caused by aircraft contrail shadows altering cumulus <span class="hlt">clouds</span> and forming straight line <span class="hlt">clouds</span>, as photographed from the Apollo spacecraft in Earth orbit during the joint U.S.-USSR Apollo-Soyuz Test Project mission. This area is southwest of Los Angeles, California. This photograph was taken at an altitude of 177 kilometers (110 statute miles) with a 70mm Hasselblad camera using medium-speed Ektachrome QX-807 <span class="hlt">type</span> film.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.8852H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.8852H"><span><span class="hlt">Cloud</span> occurrences and <span class="hlt">cloud</span> radiative effects (CREs) from CERES-CALIPSO-<span class="hlt">Cloud</span>Sat-MODIS (CCCM) and <span class="hlt">Cloud</span>Sat radar-lidar (RL) products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Winker, David; L'Ecuyer, Tristan; Mace, Gerald G.; Painemal, David; Sun-Mack, Sunny; Chen, Yan; Miller, Walter F.</p> <p>2017-08-01</p> <p>Two kinds of <span class="hlt">cloud</span> products obtained from <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), <span class="hlt">Cloud</span>Sat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES)-CALIPSO-<span class="hlt">Cloud</span>Sat-MODIS (CCCM) product and <span class="hlt">Cloud</span>Sat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (<1 km) <span class="hlt">cloud</span> occurrences in CCCM are larger over tropical oceans because the CCCM algorithm uses a more relaxed threshold of <span class="hlt">cloud</span>-aerosol discrimination score for CALIPSO Vertical Feature Mask product. In contrast, midlevel (1-8 km) <span class="hlt">cloud</span> occurrences in GEOPROF-LIDAR are larger than CCCM at high latitudes (>40°). The difference occurs when hydrometeors are detected by CALIPSO lidar but are undetected by <span class="hlt">Cloud</span>Sat radar. In the comparison of <span class="hlt">cloud</span> radiative effects (CREs), global mean differences between CCCM and FLXHR-LIDAR are mostly smaller than 5 W m-2, while noticeable regional differences are found. For example, CCCM shortwave (SW) and longwave (LW) CREs are larger than FXLHR-LIDAR along the west coasts of Africa and America because the GEOPROF-LIDAR algorithm misses shallow marine boundary layer <span class="hlt">clouds</span>. In addition, FLXHR-LIDAR SW CREs are larger than the CCCM counterpart over tropical oceans away from the west coasts of America. Over midlatitude storm-track regions, CCCM SW and LW CREs are larger than the FLXHR-LIDAR counterpart.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMIN11A0029C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN11A0029C"><span>Lidar <span class="hlt">Cloud</span> Detection with Fully Convolutional Networks</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cromwell, E.; Flynn, D.</p> <p>2017-12-01</p> <p>The vertical distribution of <span class="hlt">clouds</span> from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of <span class="hlt">clouds</span> can be expressed as a binary <span class="hlt">cloud</span> mask and is a primary input for climate modeling efforts and <span class="hlt">cloud</span> formation studies. Current <span class="hlt">cloud</span> detection algorithms producing these masks do not accurately <span class="hlt">identify</span> the <span class="hlt">cloud</span> boundaries and tend to oversample or over-represent the <span class="hlt">cloud</span>. This translates as uncertainty for assessing the radiative impact of <span class="hlt">clouds</span> and tracking changes in <span class="hlt">cloud</span> climatologies. The Atmospheric Radiation Measurement (ARM) program has over 20 years of micro-pulse lidar (MPL) and High Spectral Resolution Lidar (HSRL) instrument data and companion automated <span class="hlt">cloud</span> mask product at the mid-latitude Southern Great Plains (SGP) and the polar North Slope of Alaska (NSA) atmospheric observatory. Using this data, we train a fully convolutional network (FCN) with semi-supervised learning to segment lidar imagery into geometric time-height <span class="hlt">cloud</span> locations for the SGP site and MPL instrument. We then use transfer learning to train a FCN for (1) the MPL instrument at the NSA site and (2) for the HSRL. In our semi-supervised approach, we pre-train the classification layers of the FCN with weakly labeled lidar data. Then, we facilitate end-to-end unsupervised pre-training and transition to fully supervised learning with ground truth labeled data. Our goal is to improve the <span class="hlt">cloud</span> mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current <span class="hlt">cloud</span> mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a <span class="hlt">cloud</span> mask accuracy of 90% and a precision of 80%.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_15");'>15</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li class="active"><span>17</span></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_17 --> <div id="page_18" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="341"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ACP....17.8473L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ACP....17.8473L"><span>In situ chemical composition measurement of individual <span class="hlt">cloud</span> residue particles at a mountain site, southern China</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lin, Qinhao; Zhang, Guohua; Peng, Long; Bi, Xinhui; Wang, Xinming; Brechtel, Fred J.; Li, Mei; Chen, Duohong; Peng, Ping'an; Sheng, Guoying; Zhou, Zhen</p> <p>2017-07-01</p> <p>To investigate how atmospheric aerosol particles interact with chemical composition of <span class="hlt">cloud</span> droplets, a ground-based counterflow virtual impactor (GCVI) coupled with a real-time single-particle aerosol mass spectrometer (SPAMS) was used to assess the chemical composition and mixing state of individual <span class="hlt">cloud</span> residue particles in the Nanling Mountains (1690 m a. s. l. ), southern China, in January 2016. The <span class="hlt">cloud</span> residues were classified into nine particle <span class="hlt">types</span>: aged elemental carbon (EC), potassium-rich (K-rich), amine, dust, Pb, Fe, organic carbon (OC), sodium-rich (Na-rich) and <q>Other</q>. The largest fraction of the total <span class="hlt">cloud</span> residues was the aged EC <span class="hlt">type</span> (49.3 %), followed by the K-rich <span class="hlt">type</span> (33.9 %). Abundant aged EC <span class="hlt">cloud</span> residues that mixed internally with inorganic salts were found in air masses from northerly polluted areas. The number fraction (NF) of the K-rich <span class="hlt">cloud</span> residues increased within southwesterly air masses from fire activities in Southeast Asia. When air masses changed from northerly polluted areas to southwesterly ocean and livestock areas, the amine particles increased from 0.2 to 15.1 % of the total <span class="hlt">cloud</span> residues. The dust, Fe, Pb, Na-rich and OC particle <span class="hlt">types</span> had a low contribution (0.5-4.1 %) to the total <span class="hlt">cloud</span> residues. Higher fraction of nitrate (88-89 %) was found in the dust and Na-rich <span class="hlt">cloud</span> residues relative to sulfate (41-42 %) and ammonium (15-23 %). Higher intensity of nitrate was found in the <span class="hlt">cloud</span> residues relative to the ambient particles. Compared with nonactivated particles, nitrate intensity decreased in all <span class="hlt">cloud</span> residues except for dust <span class="hlt">type</span>. To our knowledge, this study is the first report on in situ observation of the chemical composition and mixing state of individual <span class="hlt">cloud</span> residue particles in China.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940017840','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940017840"><span>Automated <span class="hlt">cloud</span> classification with a fuzzy logic expert system</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tovinkere, Vasanth; Baum, Bryan A.</p> <p>1993-01-01</p> <p>An unresolved problem in current <span class="hlt">cloud</span> retrieval algorithms concerns the analysis of scenes containing overlapping <span class="hlt">cloud</span> layers. <span class="hlt">Cloud</span> parameterizations are very important both in global climate models and in studies of the Earth's radiation budget. Most <span class="hlt">cloud</span> retrieval schemes, such as the bispectral method used by the International Satellite <span class="hlt">Cloud</span> Climatology Project (ISCCP), have no way of determining whether overlapping <span class="hlt">cloud</span> layers exist in any group of satellite pixels. One promising method uses fuzzy logic to determine whether mixed <span class="hlt">cloud</span> and/or surface <span class="hlt">types</span> exist within a group of pixels, such as cirrus, land, and water, or cirrus and stratus. When two or more class <span class="hlt">types</span> are present, fuzzy logic uses membership values to assign the group of pixels partially to the different class <span class="hlt">types</span>. The strength of fuzzy logic lies in its ability to work with patterns that may include more than one class, facilitating greater information extraction from satellite radiometric data. The development of the fuzzy logic rule-based expert system involves training the fuzzy classifier with spectral and textural features calculated from accurately labeled 32x32 regions of Advanced Very High Resolution Radiometer (AVHRR) 1.1-km data. The spectral data consists of AVHRR channels 1 (0.55-0.68 mu m), 2 (0.725-1.1 mu m), 3 (3.55-3.93 mu m), 4 (10.5-11.5 mu m), and 5 (11.5-12.5 mu m), which include visible, near-infrared, and infrared window regions. The textural features are based on the gray level difference vector (GLDV) method. A sophisticated new interactive visual image Classification System (IVICS) is used to label samples chosen from scenes collected during the FIRE IFO II. The training samples are chosen from predefined classes, chosen to be ocean, land, unbroken stratiform, broken stratiform, and cirrus. The November 28, 1991 NOAA overpasses contain complex multilevel <span class="hlt">cloud</span> situations ideal for training and validating the fuzzy logic expert system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA21054.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA21054.html"><span>Titan Mystery <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2016-12-21</p> <p>This comparison of two views from NASA's Cassini spacecraft, taken fairly close together in time, illustrates a peculiar mystery: Why would <span class="hlt">clouds</span> on Saturn's moon Titan be visible in some images, but not in others? In the top view, a near-infrared image from Cassini's imaging cameras, the skies above Saturn's moon Titan look relatively <span class="hlt">cloud</span> free. But in the bottom view, at longer infrared wavelengths, Cassini sees a large field of bright <span class="hlt">clouds</span>. Even though these views were taken at different wavelengths, researchers would expect at least a hint of the <span class="hlt">clouds</span> to show up in the upper image. Thus they have been trying to understand what's behind the difference. As northern summer approaches on Titan, atmospheric models have predicted that <span class="hlt">clouds</span> will become more common at high northern latitudes, similar to what was observed at high southern latitudes during Titan's late southern summer in 2004. Cassini's Imaging Science Subsystem (ISS) and Visual and Infrared Mapping Spectrometer (VIMS) teams have been observing Titan to document changes in weather patterns as the seasons change, and there is particular interest in following the onset of <span class="hlt">clouds</span> in the north polar region where Titan's lakes and seas are concentrated. Cassini's "T120" and "T121" flybys of Titan, on June 7 and July 25, 2016, respectively, provided views of high northern latitudes over extended time periods -- more than 24 hours during both flybys. Intriguingly, the ISS and VIMS observations appear strikingly different from each other. In the ISS observations (monochrome image at top), surface features are easily <span class="hlt">identifiable</span> and only a few small, isolated <span class="hlt">clouds</span> were detected. In contrast, the VIMS observations (color image at bottom) suggest widespread <span class="hlt">cloud</span> cover during both flybys. The observations were made over the same time period, so differences in illumination geometry or changes in the <span class="hlt">clouds</span> themselves are unlikely to be the cause for the apparent discrepancy: VIMS shows persistent</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA13386.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA13386.html"><span><span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2010-09-14</p> <p><span class="hlt">Clouds</span> are common near the north polar caps throughout the spring and summer. The <span class="hlt">clouds</span> typically cause a haze over the extensive dune fields. This image from NASA Mars Odyssey shows the edge of the <span class="hlt">cloud</span> front.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19950021443','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19950021443"><span>A study of surface temperatures, <span class="hlt">clouds</span> and net radiation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Dhuria, Harbans</p> <p>1994-01-01</p> <p>The study is continuing and it is focused on examining seasonal relationships between climate parameters such as the surface temperatures, the net radiation and <span class="hlt">cloud</span> <span class="hlt">types</span> and amount on a global basis for the period February 1985 to January 1987. The study consists of an analysis of the combined Earth Radiation Budget Experiment (ERBE) and International Satellite <span class="hlt">Cloud</span> Climatology Program (ISCCP) products. The main emphasis is on obtaining the information about the interactions and relationships of Earth Radiation Budget parameters, <span class="hlt">cloud</span> and temperature information. The purpose is to gain additional qualitative and quantitative insight into the <span class="hlt">cloud</span> climate relationship.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A11N..07A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A11N..07A"><span>The Q Continuum: Encounter with the <span class="hlt">Cloud</span> Mask</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ackerman, S. A.; Frey, R.; Holz, R.; Philips, C.; Dutcher, S.</p> <p>2017-12-01</p> <p>We are developing a common <span class="hlt">cloud</span> mask for MODIS and VIIRS observations, referred to as the MODIS VIIRS Continuity Mask (MVCM). Our focus is on extending the MODIS-heritage <span class="hlt">cloud</span> detection approach in order to generate appropriate climate data records for <span class="hlt">clouds</span> and climate studies. The MVCM is based on heritage from the MODIS <span class="hlt">cloud</span> mask (MOD35 and MYD35) and employs a series of tests on MODIS reflectances and brightness temperatures. <span class="hlt">Cloud</span> detection is based on contrasts (i.e., <span class="hlt">cloud</span> versus background surface) at pixel resolution. The MVCM follows the same approach. These <span class="hlt">cloud</span> masks use multiple <span class="hlt">cloud</span> detection tests to indicate the confidence level that the observation is of a clear-sky scene. The outcome of a test ranges from 0 (cloudy) to 1 (clear-sky scene). Because of overlap in the sensitivities of the various spectral tests to the <span class="hlt">type</span> of <span class="hlt">cloud</span>, each test is considered in one of several groups. The final <span class="hlt">cloud</span> mask is determined from the product of the minimum confidence of each group and is referred to as the Q value as defined in Ackerman et al (1998). In MOD35 and MYD35 processing, the Q value is not output, rather predetermined Q values determine the result: If Q ≥ .99 the scene is clear; .95 ≤ Q < .99 the pixel is probably a clear scene, .66 ≤ Q < .95 is probably cloudy and Q < .66 is cloudy. Thus representing Q discretely and not as a continuum. For the MVCM, the numerical value of the Q is output along with the classification of clear, probably clear, probably cloudy, and cloudy. Through comparisons with collocated CALIOP and MODIS observations, we will assess the categorization of the Q values as a function of scene <span class="hlt">type</span> ). While validation studies have indicated the utility and statistical correctness of the <span class="hlt">cloud</span> mask approach, the algorithm does not possess immeasurable power and perfection. This comparison will assess the time and space dependence of Q and assure that the laws of physics are followed, at least according to normal human</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010JGRD..115.0H28K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010JGRD..115.0H28K"><span>Relationships among <span class="hlt">cloud</span> occurrence frequency, overlap, and effective thickness derived from CALIPSO and <span class="hlt">Cloud</span>Sat merged <span class="hlt">cloud</span> vertical profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.</p> <p>2010-01-01</p> <p>A <span class="hlt">cloud</span> frequency of occurrence matrix is generated using merged <span class="hlt">cloud</span> vertical profiles derived from the satellite-borne <span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization (CALIOP) and <span class="hlt">cloud</span> profiling radar. The matrix contains vertical profiles of <span class="hlt">cloud</span> occurrence frequency as a function of the uppermost <span class="hlt">cloud</span> top. It is shown that the <span class="hlt">cloud</span> fraction and uppermost <span class="hlt">cloud</span> top vertical profiles can be related by a <span class="hlt">cloud</span> overlap matrix when the correlation length of <span class="hlt">cloud</span> occurrence, which is interpreted as an effective <span class="hlt">cloud</span> thickness, is introduced. The underlying assumption in establishing the above relation is that <span class="hlt">cloud</span> overlap approaches random overlap with increasing distance separating <span class="hlt">cloud</span> layers and that the probability of deviating from random overlap decreases exponentially with distance. One month of <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and <span class="hlt">Cloud</span>Sat data (July 2006) support these assumptions, although the correlation length sometimes increases with separation distance when the <span class="hlt">cloud</span> top height is large. The data also show that the correlation length depends on <span class="hlt">cloud</span> top hight and the maximum occurs when the <span class="hlt">cloud</span> top height is 8 to 10 km. The <span class="hlt">cloud</span> correlation length is equivalent to the decorrelation distance introduced by Hogan and Illingworth (2000) when <span class="hlt">cloud</span> fractions of both layers in a two-<span class="hlt">cloud</span> layer system are the same. The simple relationships derived in this study can be used to estimate the top-of-atmosphere irradiance difference caused by <span class="hlt">cloud</span> fraction, uppermost <span class="hlt">cloud</span> top, and <span class="hlt">cloud</span> thickness vertical profile differences.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1812426H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1812426H"><span>Advances in the TRIDEC <span class="hlt">Cloud</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hammitzsch, Martin; Spazier, Johannes; Reißland, Sven</p> <p>2016-04-01</p> <p>The TRIDEC <span class="hlt">Cloud</span> is a platform that merges several complementary <span class="hlt">cloud</span>-based services for instant tsunami propagation calculations and automated background computation with graphics processing units (GPU), for web-mapping of hazard specific geospatial data, and for serving relevant functionality to handle, share, and communicate threat specific information in a collaborative and distributed environment. The platform offers a modern web-based graphical user interface so that operators in warning centres and stakeholders of other involved parties (e.g. CPAs, ministries) just need a standard web browser to access a full-fledged early warning and information system with unique interactive features such as <span class="hlt">Cloud</span> Messages and Shared Maps. Furthermore, the TRIDEC <span class="hlt">Cloud</span> can be accessed in different modes, e.g. the monitoring mode, which provides important functionality required to act in a real event, and the exercise-and-training mode, which enables training and exercises with virtual scenarios re-played by a scenario player. The software system architecture and open interfaces facilitate global coverage so that the system is applicable for any region in the world and allow the integration of different sensor systems as well as the integration of other hazard <span class="hlt">types</span> and use cases different to tsunami early warning. Current advances of the TRIDEC <span class="hlt">Cloud</span> platform will be summarized in this presentation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMED43C..04G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMED43C..04G"><span>SatCam: A mobile application for coordinated ground/satellite observation of <span class="hlt">clouds</span> and validation of satellite-derived <span class="hlt">cloud</span> mask products.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gumley, L.; Parker, D.; Flynn, B.; Holz, R.; Marais, W.</p> <p>2011-12-01</p> <p> high hit rates will be <span class="hlt">identified</span> automatically and their observations will be used globally to evaluate the performance of the MODIS <span class="hlt">cloud</span> mask algorithm for Terra and Aqua and the VIIRS <span class="hlt">cloud</span> mask algorithm for NPP. The user's assessment of the ground conditions will also be used to evaluate the <span class="hlt">cloud</span> mask accuracy in selecting the correct surface <span class="hlt">type</span> at the user's location, which is an important element in the decision path used internally by the <span class="hlt">cloud</span> mask algorithm. This presentation will describe the SatCam application, how it is used, and show examples of SatCam observations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ApJ...854..154N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ApJ...854..154N"><span>Molecular <span class="hlt">Cloud</span> Structures and Massive Star Formation in N159</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nayak, O.; Meixner, M.; Fukui, Y.; Tachihara, K.; Onishi, T.; Saigo, K.; Tokuda, K.; Harada, R.</p> <p>2018-02-01</p> <p>The N159 star-forming region is one of the most massive giant molecular <span class="hlt">clouds</span> (GMCs) in the Large Magellanic <span class="hlt">Cloud</span> (LMC). We show the 12CO, 13CO, CS molecular gas lines observed with ALMA in N159 west (N159W) and N159 east (N159E). We relate the structure of the gas clumps to the properties of 24 massive young stellar objects (YSOs) that include 10 newly <span class="hlt">identified</span> YSOs based on our search. We use dendrogram analysis to <span class="hlt">identify</span> properties of the molecular clumps, such as flux, mass, linewidth, size, and virial parameter. We relate the YSO properties to the molecular gas properties. We find that the CS gas clumps have a steeper size–linewidth relation than the 12CO or 13CO gas clumps. This larger slope could potentially occur if the CS gas is tracing shocks. The virial parameters of the 13CO gas clumps in N159W and N159E are low (<1). The threshold for massive star formation in N159W is 501 M ⊙ pc‑2, and the threshold for massive star formation in N159E is 794 M ⊙ pc‑2. We find that 13CO is more photodissociated in N159E than N159W. The most massive YSO in N159E has cleared out a molecular gas hole in its vicinity. All the massive YSO candidates in N159E have a more evolved spectral energy distribution <span class="hlt">type</span> in comparison to the YSO candidates in N159W. These differences lead us to conclude that the giant molecular <span class="hlt">cloud</span> complex in N159E is more evolved than the giant molecular <span class="hlt">cloud</span> complex in N159W.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140012666','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140012666"><span>MODIS Collection 6 Clear Sky Restoral (CSR): Filtering <span class="hlt">Cloud</span> Mast 'Not Clear' Pixels</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Meyer, Kerry G.; Platnick, Steven Edward; Wind, Galina; Riedi, Jerome</p> <p>2014-01-01</p> <p>Correctly <span class="hlt">identifying</span> cloudy pixels appropriate for the MOD06 <span class="hlt">cloud</span> optical and microphysical property retrievals is accomplished in large part using results from the MOD35 1km <span class="hlt">cloud</span> mask tests (note there are also two 250m subpixel <span class="hlt">cloud</span> mask tests that can convert the 1km cloudy designations to clear sky). However, because MOD35 is by design clear sky conservative (i.e., it <span class="hlt">identifies</span> "not clear" pixels), certain situations exist in which pixels <span class="hlt">identified</span> by MOD35 as "cloudy" are nevertheless likely to be poor retrieval candidates. For instance, near the edge of <span class="hlt">clouds</span> or within broken <span class="hlt">cloud</span> fields, a given 1km MODIS field of view (FOV) may in fact only be partially cloudy. This can be problematic for the MOD06 retrievals because in these cases the assumptions of a completely overcast homogenous cloudy FOV and 1-dimensional plane-parallel radiative transfer no longer hold, and subsequent retrievals will be of low confidence. Furthermore, some pixels may be <span class="hlt">identified</span> by MOD35 as "cloudy" for reasons other than the presence of <span class="hlt">clouds</span>, such as scenes with thick smoke or lofted dust, and should therefore not be retrieved as <span class="hlt">clouds</span>. With such situations in mind, a Clear Sky Restoral (CSR) algorithm was introduced in C5 that attempts to <span class="hlt">identify</span> pixels expected to be poor retrieval candidates. Table 1 provides SDS locations for CSR and partly cloudy (PCL) pixels.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1992JGR....9720537Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1992JGR....9720537Z"><span>Clustering, randomness, and regularity in <span class="hlt">cloud</span> fields: 2. Cumulus <span class="hlt">cloud</span> fields</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.</p> <p>1992-12-01</p> <p>During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus <span class="hlt">clouds</span> form in clusters, in which <span class="hlt">cloud</span> spacing is closer than that found for the overall <span class="hlt">cloud</span> field and which maintains its identity over many <span class="hlt">cloud</span> lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus <span class="hlt">cloud</span> field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-<span class="hlt">cloud</span> cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small <span class="hlt">clouds</span> are included in the <span class="hlt">cloud</span> field distribution, the <span class="hlt">cloud</span> field always has a strong clustering signal. The strength of clustering is largest at <span class="hlt">cloud</span> diameters of about 200-300 m, diminishing with increasing <span class="hlt">cloud</span> diameter. In many cases, clusters of small <span class="hlt">clouds</span> are found which are not closely associated with large <span class="hlt">clouds</span>. As the small <span class="hlt">clouds</span> are eliminated from consideration, the <span class="hlt">cloud</span> field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large <span class="hlt">clouds</span>. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the <span class="hlt">cloud</span> size distributions. Since distinct <span class="hlt">clouds</span> are by definition nonoverlapping, <span class="hlt">cloud</span> size effects place a restriction upon the possible locations of <span class="hlt">clouds</span> in the <span class="hlt">cloud</span> field. The net effect of this analysis is that the large <span class="hlt">clouds</span> appear to be randomly distributed, with only weak tendencies towards</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011JGRD..116.0T07F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011JGRD..116.0T07F"><span>Representation of Arctic mixed-phase <span class="hlt">clouds</span> and the Wegener-Bergeron-Findeisen process in climate models: Perspectives from a <span class="hlt">cloud</span>-resolving study</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fan, Jiwen; Ghan, Steven; Ovchinnikov, Mikhail; Liu, Xiaohong; Rasch, Philip J.; Korolev, Alexei</p> <p>2011-01-01</p> <p>Two <span class="hlt">types</span> of Arctic mixed-phase <span class="hlt">clouds</span> observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional <span class="hlt">cloud</span>-resolving model (CRM) with size-resolved <span class="hlt">cloud</span> microphysics. The modeled <span class="hlt">cloud</span> properties agree reasonably well with aircraft measurements and surface-based retrievals. <span class="hlt">Cloud</span> properties such as the probability density function (PDF) of vertical velocity (w), <span class="hlt">cloud</span> liquid and ice, regimes of <span class="hlt">cloud</span> particle growth, including the Wegener-Bergeron-Findeisen (WBF) process, and the relationships among properties/processes in mixed-phase <span class="hlt">clouds</span> are examined to gain insights for improving their representation in General Circulation Models (GCMs). The PDF of the simulated w is well represented by a Gaussian function, validating, at least for arctic <span class="hlt">clouds</span>, the subgrid treatment used in GCMs. The PDFs of liquid and ice water contents can be approximated by Gamma functions, and a Gaussian function can describe the total water distribution, but a fixed variance assumption should be avoided in both cases. The CRM results support the assumption frequently used in GCMs that mixed phase <span class="hlt">clouds</span> maintain water vapor near liquid saturation. Thus, ice continues to grow throughout the stratiform <span class="hlt">cloud</span> but the WBF process occurs in about 50% of <span class="hlt">cloud</span> volume where liquid and ice co-exist, predominantly in downdrafts. In updrafts, liquid and ice particles grow simultaneously. The relationship between the ice depositional growth rate and <span class="hlt">cloud</span> ice strongly depends on the capacitance of ice particles. The simplified size-independent capacitance of ice particles used in GCMs could lead to large deviations in ice depositional growth.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5586241','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5586241"><span>Numerics and subgrid‐scale modeling in large eddy simulations of stratocumulus <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Mishra, Siddhartha; Schneider, Tapio; Kaul, Colleen M.; Tan, Zhihong</p> <p>2017-01-01</p> <p>Abstract Stratocumulus <span class="hlt">clouds</span> are the most common <span class="hlt">type</span> of boundary layer <span class="hlt">cloud</span>; their radiative effects strongly modulate climate. Large eddy simulations (LES) of stratocumulus <span class="hlt">clouds</span> often struggle to maintain fidelity to observations because of the sharp gradients occurring at the entrainment interfacial layer at the <span class="hlt">cloud</span> top. The challenge posed to LES by stratocumulus <span class="hlt">clouds</span> is evident in the wide range of solutions found in the LES intercomparison based on the DYCOMS‐II field campaign, where simulated liquid water paths for identical initial and boundary conditions varied by a factor of nearly 12. Here we revisit the DYCOMS‐II RF01 case and show that the wide range of previous LES results can be realized in a single LES code by varying only the numerical treatment of the equations of motion and the nature of subgrid‐scale (SGS) closures. The simulations that maintain the greatest fidelity to DYCOMS‐II observations are <span class="hlt">identified</span>. The results show that using weighted essentially non‐oscillatory (WENO) numerics for all resolved advective terms and no explicit SGS closure consistently produces the highest‐fidelity simulations. This suggests that the numerical dissipation inherent in WENO schemes functions as a high‐quality, implicit SGS closure for this stratocumulus case. Conversely, using oscillatory centered difference numerical schemes for momentum advection, WENO numerics for scalars, and explicitly modeled SGS fluxes consistently produces the lowest‐fidelity simulations. We attribute this to the production of anomalously large SGS fluxes near the <span class="hlt">cloud</span> tops through the interaction of numerical error in the momentum field with the scalar SGS model. PMID:28943997</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28943997','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28943997"><span>Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus <span class="hlt">clouds</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Pressel, Kyle G; Mishra, Siddhartha; Schneider, Tapio; Kaul, Colleen M; Tan, Zhihong</p> <p>2017-06-01</p> <p>Stratocumulus <span class="hlt">clouds</span> are the most common <span class="hlt">type</span> of boundary layer <span class="hlt">cloud</span>; their radiative effects strongly modulate climate. Large eddy simulations (LES) of stratocumulus <span class="hlt">clouds</span> often struggle to maintain fidelity to observations because of the sharp gradients occurring at the entrainment interfacial layer at the <span class="hlt">cloud</span> top. The challenge posed to LES by stratocumulus <span class="hlt">clouds</span> is evident in the wide range of solutions found in the LES intercomparison based on the DYCOMS-II field campaign, where simulated liquid water paths for identical initial and boundary conditions varied by a factor of nearly 12. Here we revisit the DYCOMS-II RF01 case and show that the wide range of previous LES results can be realized in a single LES code by varying only the numerical treatment of the equations of motion and the nature of subgrid-scale (SGS) closures. The simulations that maintain the greatest fidelity to DYCOMS-II observations are <span class="hlt">identified</span>. The results show that using weighted essentially non-oscillatory (WENO) numerics for all resolved advective terms and no explicit SGS closure consistently produces the highest-fidelity simulations. This suggests that the numerical dissipation inherent in WENO schemes functions as a high-quality, implicit SGS closure for this stratocumulus case. Conversely, using oscillatory centered difference numerical schemes for momentum advection, WENO numerics for scalars, and explicitly modeled SGS fluxes consistently produces the lowest-fidelity simulations. We attribute this to the production of anomalously large SGS fluxes near the <span class="hlt">cloud</span> tops through the interaction of numerical error in the momentum field with the scalar SGS model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3412548','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3412548"><span>Using <span class="hlt">Cloud</span> Computing infrastructure with <span class="hlt">Cloud</span>BioLinux, <span class="hlt">Cloud</span>Man and Galaxy</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James</p> <p>2012-01-01</p> <p><span class="hlt">Cloud</span> computing has revolutionized availability and access to computing and storage resources; making it possible to provision a large computational infrastructure with only a few clicks in a web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this protocol, we demonstrate how to utilize <span class="hlt">cloud</span> computing resources to perform open-ended bioinformatics analyses, with fully automated management of the underlying <span class="hlt">cloud</span> infrastructure. By combining three projects, <span class="hlt">Cloud</span>BioLinux, <span class="hlt">Cloud</span>Man, and Galaxy into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible <span class="hlt">cloud</span> computing infrastructure. The protocol demonstrates how to setup the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command line interface, and the web-based Galaxy interface. PMID:22700313</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22700313','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22700313"><span>Using <span class="hlt">cloud</span> computing infrastructure with <span class="hlt">Cloud</span>BioLinux, <span class="hlt">Cloud</span>Man, and Galaxy.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James</p> <p>2012-06-01</p> <p><span class="hlt">Cloud</span> computing has revolutionized availability and access to computing and storage resources, making it possible to provision a large computational infrastructure with only a few clicks in a Web browser. However, those resources are typically provided in the form of low-level infrastructure components that need to be procured and configured before use. In this unit, we demonstrate how to utilize <span class="hlt">cloud</span> computing resources to perform open-ended bioinformatic analyses, with fully automated management of the underlying <span class="hlt">cloud</span> infrastructure. By combining three projects, <span class="hlt">Cloud</span>BioLinux, <span class="hlt">Cloud</span>Man, and Galaxy, into a cohesive unit, we have enabled researchers to gain access to more than 100 preconfigured bioinformatics tools and gigabytes of reference genomes on top of the flexible <span class="hlt">cloud</span> computing infrastructure. The protocol demonstrates how to set up the available infrastructure and how to use the tools via a graphical desktop interface, a parallel command-line interface, and the Web-based Galaxy interface.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFMGC51E0480C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFMGC51E0480C"><span>Overview of the CERES Edition-4 Multilayer <span class="hlt">Cloud</span> Property Datasets</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chang, F. L.; Minnis, P.; Sun-Mack, S.; Chen, Y.; Smith, R. A.; Brown, R. R.</p> <p>2014-12-01</p> <p>Knowledge of the <span class="hlt">cloud</span> vertical distribution is important for understanding the role of <span class="hlt">clouds</span> on earth's radiation budget and climate change. Since high-level cirrus <span class="hlt">clouds</span> with low emission temperatures and small optical depths can provide a positive feedback to a climate system and low-level stratus <span class="hlt">clouds</span> with high emission temperatures and large optical depths can provide a negative feedback effect, the retrieval of multilayer <span class="hlt">cloud</span> properties using satellite observations, like Terra and Aqua MODIS, is critically important for a variety of <span class="hlt">cloud</span> and climate applications. For the objective of the <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES), new algorithms have been developed using Terra and Aqua MODIS data to allow separate retrievals of cirrus and stratus <span class="hlt">cloud</span> properties when the two dominant <span class="hlt">cloud</span> <span class="hlt">types</span> are simultaneously present in a multilayer system. In this paper, we will present an overview of the new CERES Edition-4 multilayer <span class="hlt">cloud</span> property datasets derived from Terra as well as Aqua. Assessment of the new CERES multilayer <span class="hlt">cloud</span> datasets will include high-level cirrus and low-level stratus <span class="hlt">cloud</span> heights, pressures, and temperatures as well as their optical depths, emissivities, and microphysical properties.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930071203&hterms=fog+appears&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dwhen%2Bfog%2Bappears','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930071203&hterms=fog+appears&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dwhen%2Bfog%2Bappears"><span>The seasonal cycle of low stratiform <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Klein, Stephen A.; Hartmann, Dennis L.</p> <p>1993-01-01</p> <p>The seasonal cycle of low stratiform <span class="hlt">clouds</span> is studied using data from surface-based <span class="hlt">cloud</span> climatologies. The impact of low <span class="hlt">clouds</span> on the radiation budget is illustrated by comparison of data from the Earth Radiation Budget Experiment with the <span class="hlt">cloud</span> climatologies. Ten regions of active stratocumulus convection are <span class="hlt">identified</span>. These regions fall into four categories: subtropical marine, midlatitude marine, Arctic stratus, and Chinese stratus. With the exception of the Chinese region, all the regions with high amounts of stratus <span class="hlt">clouds</span> are over the oceans. In all regions except the Arctic, the season of maximum stratus corresponds to the season of greatest lower-troposphere static stability. Interannual variations in stratus <span class="hlt">cloud</span> amount also are related to changes in static stability. A linear analysis indicates that a 6 percent increase in stratus fractional area coverage is associated with each 1 C increase in static stability. Over midlatitude oceans, sky-obscuring fog is a large component of the summertime stratus amount. The amount of fog appears to be related to warm advection across sharp gradients of SST.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1993JCli....6.1587K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1993JCli....6.1587K"><span>The Seasonal Cycle of Low Stratiform <span class="hlt">Clouds</span>.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klein, Stephen A.; Hartmann, Dennis L.</p> <p>1993-08-01</p> <p>The seasonal cycle of low stratiform <span class="hlt">clouds</span> is studied using data from surface-based <span class="hlt">cloud</span> climatologies. The impact of low <span class="hlt">clouds</span> on the radiation budget is illustrated by comparison of data from the Earth Radiation Budget Experiment with the <span class="hlt">cloud</span> climatologies. Ten regions of active stratocumulus convection are <span class="hlt">identified</span>. These regions fall into four categories: subtropical marine, midlatitude marine, Arctic stratus, and Chinese stratus. With the exception of the Chinese region, all the regions with high amounts of stratus <span class="hlt">clouds</span> are over the oceans.In all regions except the Arctic, the season of maximum stratus corresponds to the season of greatest lower-troposphere static stability. Interannual variations in stratus <span class="hlt">cloud</span> amount also are related to changes in static stability. A linear analysis indicates that a 6% increase in stratus fractional area coverage is associated with each 1°C increase in static stability. Over midlatitude oceans, sky-obscuring fog is a large component of the summertime stratus amount. The amount of fog appears to be related to warm advection across sharp gradients of SST.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_16");'>16</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li class="active"><span>18</span></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_18 --> <div id="page_19" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="361"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29902176','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29902176"><span><span class="hlt">Cloud</span> computing applications for biomedical science: A perspective.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Navale, Vivek; Bourne, Philip E</p> <p>2018-06-01</p> <p>Biomedical research has become a digital data-intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain <span class="hlt">types</span> of biomedical applications, <span class="hlt">cloud</span> computing has emerged as an alternative to locally maintained traditional computing approaches. <span class="hlt">Cloud</span> computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. <span class="hlt">Cloud</span> computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, <span class="hlt">cloud</span> services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on <span class="hlt">cloud</span> computing to help the reader determine its value to their own research.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=6002019','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=6002019"><span><span class="hlt">Cloud</span> computing applications for biomedical science: A perspective</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2018-01-01</p> <p>Biomedical research has become a digital data–intensive endeavor, relying on secure and scalable computing, storage, and network infrastructure, which has traditionally been purchased, supported, and maintained locally. For certain <span class="hlt">types</span> of biomedical applications, <span class="hlt">cloud</span> computing has emerged as an alternative to locally maintained traditional computing approaches. <span class="hlt">Cloud</span> computing offers users pay-as-you-go access to services such as hardware infrastructure, platforms, and software for solving common biomedical computational problems. <span class="hlt">Cloud</span> computing services offer secure on-demand storage and analysis and are differentiated from traditional high-performance computing by their rapid availability and scalability of services. As such, <span class="hlt">cloud</span> services are engineered to address big data problems and enhance the likelihood of data and analytics sharing, reproducibility, and reuse. Here, we provide an introductory perspective on <span class="hlt">cloud</span> computing to help the reader determine its value to their own research. PMID:29902176</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014AGUFM.A23P..02M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014AGUFM.A23P..02M"><span>Validating Satellite-Retrieved <span class="hlt">Cloud</span> Properties for Weather and Climate Applications</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.</p> <p>2014-12-01</p> <p><span class="hlt">Cloud</span> properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived <span class="hlt">cloud</span> parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and <span class="hlt">cloud</span> <span class="hlt">type</span> and structure. Because of the great variety of those conditions and of the sensors used to monitor <span class="hlt">clouds</span>, determining the accuracy or uncertainties in the retrieved <span class="hlt">cloud</span> parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular <span class="hlt">cloud</span> <span class="hlt">type</span> are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model <span class="hlt">clouds</span> that serve as the basis for the retrievals. Real world <span class="hlt">clouds</span>, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, <span class="hlt">cloud</span> properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. <span class="hlt">Cloud</span> properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite <span class="hlt">cloud</span> retrievals. These include, but are not limited to data from ARM sites, <span class="hlt">Cloud</span>Sat, and CALIPSO. This paper discusses the use of the various</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990115803&hterms=TES+system&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DTES%2Bsystem','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990115803&hterms=TES+system&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DTES%2Bsystem"><span>Mars Global Surveyor TES Results: Observations of Water Ice <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Pearl, John C.; Smith, M. D.; Conrath, B. J.; Bandfield, J. L.; Christensen, P. R.</p> <p>1999-01-01</p> <p>On July 31, 1999, Mars Global Surveyor completed its first martian year in orbit. During this time, the Thermal Emission Spectrometer (TES) experiment gathered extensive data on water ice <span class="hlt">clouds</span>. We report here on three <span class="hlt">types</span> of martian <span class="hlt">clouds</span>. 1) Martian southern summer has long been characterized as the season when the most severe dust storms occur. It is now apparent that northern spring/summer is characterized as a time of substantial low latitude ice <span class="hlt">clouds</span> [1]. TES observations beginning in the northern summer (Lsubs=107) show a well developed <span class="hlt">cloud</span> belt between 10S and 30N latitude; 12 micron opacities were typically 0.15. This system decreased dramatically after Lsubs= 130. Thereafter, remnants were most persistent over the Tharsis ridge. 2) <span class="hlt">Clouds</span> associated with major orographic features follow a different pattern [2]. <span class="hlt">Clouds</span> of this <span class="hlt">type</span> were present prior to the regional Noachis dust storm of 1997. They disappeared with the onset of the storm, but reappeared rather quickly following its decay. Typical infrared opacities were near 0.5. 3) Extensive, very thin <span class="hlt">clouds</span> are also widespread [3]. Found at high altitudes (above 35 km), their opacities are typically a few hundredths. At times, such as in northern spring, these <span class="hlt">clouds</span> are limited in their northern extent only by the southern edge of the polar vortex. We describe the distribution, infrared optical properties, and seasonal trends of these systems during the first martian year of TES operations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25845690','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25845690"><span>Nocturnal Sleep Dynamics <span class="hlt">Identify</span> Narcolepsy <span class="hlt">Type</span> 1.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Pizza, Fabio; Vandi, Stefano; Iloti, Martina; Franceschini, Christian; Liguori, Rocco; Mignot, Emmanuel; Plazzi, Giuseppe</p> <p>2015-08-01</p> <p>To evaluate the reliability of nocturnal sleep dynamics in the differential diagnosis of central disorders of hypersomnolence. Cross-sectional. Sleep laboratory. One hundred seventy-five patients with hypocretin-deficient narcolepsy <span class="hlt">type</span> 1 (NT1, n = 79), narcolepsy <span class="hlt">type</span> 2 (NT2, n = 22), idiopathic hypersomnia (IH, n = 22), and "subjective" hypersomnolence (sHS, n = 52). None. Polysomnographic (PSG) work-up included 48 h of continuous PSG recording. From nocturnal PSG conventional sleep macrostructure, occurrence of sleep onset rapid eye movement period (SOREMP), sleep stages distribution, and sleep stage transitions were calculated. Patient groups were compared, and receiver operating characteristic (ROC) curve analysis was used to test the diagnostic utility of nocturnal PSG data to <span class="hlt">identify</span> NT1. Sleep macrostructure was substantially stable in the 2 nights of each diagnostic group. NT1 and NT2 patients had lower latency to rapid eye movement (REM) sleep, and NT1 patients showed the highest number of awakenings, sleep stage transitions, and more time spent in N1 sleep, as well as most SOREMPs at daytime PSG and at multiple sleep latency test (MSLT) than all other groups. ROC curve analysis showed that nocturnal SOREMP (area under the curve of 0.724 ± 0.041, P < 0.0001), percent of total sleep time spent in N1 (0.896 ± 0.023, P < 0.0001), and the wakefulness-sleep transition index (0.796 ± 0.034, P < 0.0001) had a good sensitivity and specificity profile to <span class="hlt">identify</span> NT1 sleep, especially when used in combination (0.903 ± 0.023, P < 0.0001), similarly to SOREMP number at continuous daytime PSG (0.899 ± 0.026, P < 0.0001) and at MSLT (0.956 ± 0.015, P < 0.0001). Sleep macrostructure (i.e. SOREMP, N1 timing) including stage transitions reliably <span class="hlt">identifies</span> hypocretin-deficient narcolepsy <span class="hlt">type</span> 1 among central disorders of hypersomnolence. © 2015 Associated Professional Sleep Societies, LLC.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhDT........51N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhDT........51N"><span>Measurement Comparisons Towards Improving the Understanding of Aerosol-<span class="hlt">Cloud</span> Processing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Noble, Stephen R.</p> <p></p> <p><span class="hlt">Cloud</span> processing of aerosol is an aerosol-<span class="hlt">cloud</span> interaction that is not heavily researched but could have implications on climate. The three <span class="hlt">types</span> of <span class="hlt">cloud</span> processing are chemical processing, collision and coalescence processing, and Brownian capture of interstitial particles. All <span class="hlt">types</span> improve <span class="hlt">cloud</span> condensation nuclei (CCN) in size or hygroscopicity (kappa). These improved CCN affect subsequent <span class="hlt">clouds</span>. This dissertation focuses on measurement comparisons to improve our observations and understanding of aerosol-<span class="hlt">cloud</span> processing. Particle size distributions measured at the continental Southern Great Plains (SGP) site were compared with ground based measurements of <span class="hlt">cloud</span> fraction (CF) and <span class="hlt">cloud</span> base altitude (CBA). Particle size distributions were described by a new objective shape parameter to define bimodality rather than an old subjective one. Cloudy conditions at SGP were found to be correlated with lagged shape parameter. Horizontal wind speed and regional CF explained 42%+ of this lag time. Many of these surface particle size distributions were influenced by aerosol-<span class="hlt">cloud</span> processing. Thus, <span class="hlt">cloud</span> processing may be more widespread with more implications than previously thought. Particle size distributions measured during two aircraft field campaigns (MArine Stratus/stratocumulus Experiment; MASE; and Ice in <span class="hlt">Cloud</span> Experiment-Tropical; ICE-T) were compared to CCN distributions. Tuning particle size to critical supersaturation revealed hygroscopicity expressed as ? when the distributions were overlain. Distributions near cumulus <span class="hlt">clouds</span> (ICE-T) had a higher frequency of the same ?s (48% in ICE-T to 42% in MASE) between the accumulation (processed) and Aitken (unprocessed) modes. This suggested physical processing domination in ICE-T. More MASE (stratus <span class="hlt">cloud</span>) kappa differences between modes pointed to chemical <span class="hlt">cloud</span> processing. Chemistry measurements made in MASE showed increases in sulfates and nitrates with distributions that were more processed. This supported</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A31E2220O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A31E2220O"><span><span class="hlt">Cloud</span> Microphysics Parameterization in a Shallow Cumulus <span class="hlt">Cloud</span> Simulated by a Largrangian <span class="hlt">Cloud</span> Model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Oh, D.; Noh, Y.; Hoffmann, F.; Raasch, S.</p> <p>2017-12-01</p> <p>Lagrangian <span class="hlt">cloud</span> model (LCM) is a fundamentally new approach of <span class="hlt">cloud</span> simulation, in which the flow field is simulated by large eddy simulation and droplets are treated as Lagrangian particles undergoing <span class="hlt">cloud</span> microphysics. LCM enables us to investigate raindrop formation and examine the parameterization of <span class="hlt">cloud</span> microphysics directly by tracking the history of individual Lagrangian droplets simulated by LCM. Analysis of the magnitude of raindrop formation and the background physical conditions at the moment at which every Lagrangian droplet grows from <span class="hlt">cloud</span> droplets to raindrops in a shallow cumulus <span class="hlt">cloud</span> reveals how and under which condition raindrops are formed. It also provides information how autoconversion and accretion appear and evolve within a <span class="hlt">cloud</span>, and how they are affected by various factors such as <span class="hlt">cloud</span> water mixing ratio, rain water mixing ratio, aerosol concentration, drop size distribution, and dissipation rate. Based on these results, the parameterizations of autoconversion and accretion, such as Kessler (1969), Tripoli and Cotton (1980), Beheng (1994), and Kharioutdonov and Kogan (2000), are examined, and the modifications to improve the parameterizations are proposed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMED23C0643L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMED23C0643L"><span>Using Roving <span class="hlt">Cloud</span> Observations from the S'COOL Project to Engage Citizen Scientists</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lewis, P. M.; Oostra, D.; Moore, S. W.; Rogerson, T. M.; Crecelius, S. A.; Chambers, L. H.</p> <p>2011-12-01</p> <p>Students' <span class="hlt">Clouds</span> Observations On-Line (S'COOL) is a hands-on project, which supports NASA research on the Earth's climate. Through their observations, participants are engaged in <span class="hlt">identifying</span> <span class="hlt">cloud-types</span> and levels and sending that information to NASA. The two main groups of S'COOL observers are permanent locations such as regularly participating classrooms, and non-permanent locations or Rovers. These non-permanent locations can be a field trip, vacation, or just an occasional observation from a backyard. S'COOL welcomes participation from any interested observers, especially from places where official weather observations are few and far between. This program is offered to citizen scientists all over the world. They are participating in climate research by reporting <span class="hlt">cloud</span> <span class="hlt">types</span> and levels within +/- 15 minutes of a satellite overpass and sending that information back to NASA. When a participant's <span class="hlt">cloud</span> observation coincides with a satellite overpass, the project sends them an email with a MODIS image of the overpass location, and a comparison of the satellite's <span class="hlt">cloud</span> data results next to their ground-based report. This allows for the students and citizen scientists to participate in ground-truthing the CERES satellite data, to determine the level of agreement/disagreement. A new tool slated for future use in <span class="hlt">cloud</span> identification, developed by the S'COOL team, is a mobile application. The application is entitled "<span class="hlt">Cloud</span> Identification for Students" or "CITRUS". The mobile application utilizes a <span class="hlt">cloud</span> dichotomous key with images to help with <span class="hlt">cloud</span> identification. Also included in the application is a link to the project's <span class="hlt">cloud</span>-reporting page to help with data submission in the field. One of the project's recent and most unique roving observers is a solo ocean rower who has traversed many of the world's ocean basins alone in a rowboat. While rowing across the oceans, she has recently been making <span class="hlt">cloud</span> observations, which she sends back to us for analysis. In doing so</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AIPC.1527..696R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AIPC.1527..696R"><span>Observed aerosol effects on marine <span class="hlt">cloud</span> nucleation and supersaturation</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Russell, Lynn M.; Sorooshian, Armin; Seinfeld, John H.; Albrecht, Bruce A.; Nenes, Athanasios; Leaitch, W. Richard; Macdonald, Anne Marie; Ahlm, Lars; Chen, Yi-Chun; Coggon, Matthew; Corrigan, Ashley; Craven, Jill S.; Flagan, Richard C.; Frossard, Amanda A.; Hawkins, Lelia N.; Jonsson, Haflidi; Jung, Eunsil; Lin, Jack J.; Metcalf, Andrew R.; Modini, Robin; Mülmenstädt, Johannes; Roberts, Greg C.; Shingler, Taylor; Song, Siwon; Wang, Zhen; Wonaschütz, Anna</p> <p>2013-05-01</p> <p>Aerosol particles in the marine boundary layer include primary organic and salt particles from sea spray and combustion-derived particles from ships and coastal cities. These particle <span class="hlt">types</span> serve as nuclei for marine <span class="hlt">cloud</span> droplet activation, although the particles that activate depend on the particle size and composition as well as the supersaturation that results from <span class="hlt">cloud</span> updraft velocities. The Eastern Pacific Emitted Aerosol <span class="hlt">Cloud</span> Experiment (EPEACE) 2011 was a targeted aircraft campaign to assess how different particle <span class="hlt">types</span> nucleate <span class="hlt">cloud</span> droplets. As part of E-PEACE 2011, we studied the role of marine particles as <span class="hlt">cloud</span> droplet nuclei and used emitted particle sources to separate particle-induced feedbacks from dynamical variability. The emitted particle sources included shipboard smoke-generated particles with 0.05-1 μm diameters (which produced tracks measured by satellite and had drop composition characteristic of organic smoke) and combustion particles from container ships with 0.05-0.2 μm diameters (which were measured in a variety of conditions with droplets containing both organic and sulfate components) [1]. Three central aspects of the collaborative E-PEACE results are: (1) the size and chemical composition of the emitted smoke particles compared to ship-track-forming cargo ship emissions as well as background marine particles, with particular attention to the role of organic particles, (2) the characteristics of <span class="hlt">cloud</span> track formation for smoke and cargo ships, as well as the role of multi-layered low <span class="hlt">clouds</span>, and (3) the implications of these findings for quantifying aerosol indirect effects. For comparison with the E-PEACE results, the preliminary results of the Stratocumulus Observations of Los-Angeles Emissions Derived Aerosol-Droplets (SOLEDAD) 2012 provided evidence of the <span class="hlt">cloud</span>-nucleating roles of both marine organic particles and coastal urban pollution, with simultaneous measurements of the effective supersaturations of the <span class="hlt">clouds</span> in the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1810205C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1810205C"><span><span class="hlt">Cloud</span> Retrieval Information Content Studies with the Pre-Aerosol, <span class="hlt">Cloud</span> and ocean Ecosystem (PACE) Ocean Color Imager (OCI)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian</p> <p>2016-04-01</p> <p>The NASA Pre-Aerosol, <span class="hlt">Cloud</span> and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present <span class="hlt">cloud</span> retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low <span class="hlt">cloud</span> climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized <span class="hlt">cloud</span> reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated <span class="hlt">cloud</span> reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for <span class="hlt">Cloud</span> Mask, <span class="hlt">Cloud</span>-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of <span class="hlt">cloud</span> phase discrimination with shortwave-only <span class="hlt">cloud</span> reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface <span class="hlt">types</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19840051483&hterms=zoology&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dzoology','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19840051483&hterms=zoology&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dzoology"><span>The early-<span class="hlt">type</span> strong emission-line supergiants of the Magellanic <span class="hlt">Clouds</span> - A spectroscopic zoology</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Shore, S. N.; Sanduleak, N.</p> <p>1984-01-01</p> <p>The results of a spectroscopic survey of 21 early-<span class="hlt">type</span> extreme emission line supergiants of the Large and Small Magellanic <span class="hlt">Clouds</span> using IUE and optical spectra are presented. The combined observations are discussed and the literature on each star in the sample is summarized. The classification procedures and the methods by which effective temperatures, bolometric magnitudes, and reddenings were assigned are discussed. The derived reddening values are given along with some results concerning anomalous reddening among the sample stars. The derived mass, luminosity, and radius for each star are presented, and the ultraviolet emission lines are described. Mass-loss rates are derived and discussed, and the implications of these observations for the evolution of the most massive stars in the Local Group are addressed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21901085','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21901085"><span>Biomedical <span class="hlt">cloud</span> computing with Amazon Web Services.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fusaro, Vincent A; Patil, Prasad; Gafni, Erik; Wall, Dennis P; Tonellato, Peter J</p> <p>2011-08-01</p> <p>In this overview to biomedical computing in the <span class="hlt">cloud</span>, we discussed two primary ways to use the <span class="hlt">cloud</span> (a single instance or cluster), provided a detailed example using NGS mapping, and highlighted the associated costs. While many users new to the <span class="hlt">cloud</span> may assume that entry is as straightforward as uploading an application and selecting an instance <span class="hlt">type</span> and storage options, we illustrated that there is substantial up-front effort required before an application can make full use of the <span class="hlt">cloud</span>'s vast resources. Our intention was to provide a set of best practices and to illustrate how those apply to a typical application pipeline for biomedical informatics, but also general enough for extrapolation to other <span class="hlt">types</span> of computational problems. Our mapping example was intended to illustrate how to develop a scalable project and not to compare and contrast alignment algorithms for read mapping and genome assembly. Indeed, with a newer aligner such as Bowtie, it is possible to map the entire African genome using one m2.2xlarge instance in 48 hours for a total cost of approximately $48 in computation time. In our example, we were not concerned with data transfer rates, which are heavily influenced by the amount of available bandwidth, connection latency, and network availability. When transferring large amounts of data to the <span class="hlt">cloud</span>, bandwidth limitations can be a major bottleneck, and in some cases it is more efficient to simply mail a storage device containing the data to AWS (http://aws.amazon.com/importexport/). More information about <span class="hlt">cloud</span> computing, detailed cost analysis, and security can be found in references.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160007454','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160007454"><span>Background Noises Versus Intraseasonal Variation Signals: Small vs. Large Convective <span class="hlt">Cloud</span> Objects From CERES Aqua Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xu, Kuan-Man</p> <p>2015-01-01</p> <p>During inactive phases of Madden-Julian Oscillation (MJO), there are plenty of deep but small convective systems and far fewer deep and large ones. During active phases of MJO, a manifestation of an increase in the occurrence of large and deep <span class="hlt">cloud</span> clusters results from an amplification of large-scale motions by stronger convective heating. This study is designed to quantitatively examine the roles of small and large <span class="hlt">cloud</span> clusters during the MJO life cycle. We analyze the <span class="hlt">cloud</span> object data from Aqua CERES (<span class="hlt">Clouds</span> and the Earth's Radiant Energy System) observations between July 2006 and June 2010 for tropical deep convective (DC) and cirrostratus (CS) <span class="hlt">cloud</span> object <span class="hlt">types</span> according to the real-time multivariate MJO index, which assigns the tropics to one of the eight MJO phases each day. The <span class="hlt">cloud</span> object is a contiguous region of the earth with a single dominant <span class="hlt">cloud</span>-system <span class="hlt">type</span>. The criteria for defining these <span class="hlt">cloud</span> <span class="hlt">types</span> are overcast footprints and <span class="hlt">cloud</span> top pressures less than 400 hPa, but DC has higher <span class="hlt">cloud</span> optical depths (=10) than those of CS (<10). The size distributions, defined as the footprint numbers as a function of <span class="hlt">cloud</span> object diameters, for particular MJO phases depart greatly from the combined (8-phase) distribution at large <span class="hlt">cloud</span>-object diameters due to the reduced/increased numbers of <span class="hlt">cloud</span> objects related to changes in the large-scale environments. The medium diameter corresponding to the combined distribution is determined and used to partition all <span class="hlt">cloud</span> objects into "small" and "large" groups of a particular phase. The two groups corresponding to the combined distribution have nearly equal numbers of footprints. The medium diameters are 502 km for DC and 310 km for cirrostratus. The range of the variation between two extreme phases (typically, the most active and depressed phases) for the small group is 6-11% in terms of the numbers of <span class="hlt">cloud</span> objects and the total footprint numbers. The corresponding range for the large group is 19-44%. In</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012PhPro..33.1791Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012PhPro..33.1791Z"><span>Research on Key Technologies of <span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Shufen; Yan, Hongcan; Chen, Xuebin</p> <p></p> <p>With the development of multi-core processors, virtualization, distributed storage, broadband Internet and automatic management, a new <span class="hlt">type</span> of computing mode named <span class="hlt">cloud</span> computing is produced. It distributes computation task on the resource pool which consists of massive computers, so the application systems can obtain the computing power, the storage space and software service according to its demand. It can concentrate all the computing resources and manage them automatically by the software without intervene. This makes application offers not to annoy for tedious details and more absorbed in his business. It will be advantageous to innovation and reduce cost. It's the ultimate goal of <span class="hlt">cloud</span> computing to provide calculation, services and applications as a public facility for the public, So that people can use the computer resources just like using water, electricity, gas and telephone. Currently, the understanding of <span class="hlt">cloud</span> computing is developing and changing constantly, <span class="hlt">cloud</span> computing still has no unanimous definition. This paper describes three main service forms of <span class="hlt">cloud</span> computing: SAAS, PAAS, IAAS, compared the definition of <span class="hlt">cloud</span> computing which is given by Google, Amazon, IBM and other companies, summarized the basic characteristics of <span class="hlt">cloud</span> computing, and emphasized on the key technologies such as data storage, data management, virtualization and programming model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A51E2121Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A51E2121Z"><span>Aerosol Microphysical Effects on <span class="hlt">Cloud</span> Fraction over the Nighttime Arctic Ocean</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zamora, L. M.; Kahn, R. A.; Stohl, A.; Eckhardt, S.</p> <p>2017-12-01</p> <p><span class="hlt">Cloud</span> fraction is a key component affecting the surface energy balance in the Arctic. Aerosol microphysical processes can affect <span class="hlt">cloud</span> fraction, for example through <span class="hlt">cloud</span> lifetime effects. However, the importance of aerosol impacts on <span class="hlt">cloud</span> fraction is not well constrained on a regional scale at high latitudes. Here we discuss a new method for <span class="hlt">identifying</span> and comparing clean and aerosol-influenced <span class="hlt">cloud</span> characteristics using a combination of multi-year remote sensing data (CALIPSO, <span class="hlt">Cloud</span>Sat) and the FLEXPART aerosol model. We use this method to investigate a variety of aerosol microphysical impacts on nighttime Arctic Ocean <span class="hlt">clouds</span> on regional and local scales. We observe differences in factors that can impact <span class="hlt">cloud</span> lifetime, including <span class="hlt">cloud</span> thickness and phase, within a subset of clean vs. polluted <span class="hlt">clouds</span>. We will also discuss cumulative <span class="hlt">cloud</span> fraction differences in clean and non-clean environments, as well as their likely impact on longwave <span class="hlt">cloud</span> radiative effects at the Arctic Ocean surface during polar night.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19970027388','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19970027388"><span>Report on the Radar/PIREP <span class="hlt">Cloud</span> Top Discrepancy Study</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wheeler, Mark M.</p> <p>1997-01-01</p> <p>This report documents the results of the Applied Meteorology Unit's (AMU) investigation of inconsistencies between pilot reported <span class="hlt">cloud</span> top heights and weather radar indicated echo top heights (assumed to be <span class="hlt">cloud</span> tops) as <span class="hlt">identified</span> by the 45 Weather Squadron (45WS). The objective for this study is to document and understand the differences in echo top characteristics as displayed on both the WSR-88D and WSR-74C radars and <span class="hlt">cloud</span> top heights reported by the contract weather aircraft in support of space launch operations at Cape Canaveral Air Station (CCAS), Florida. These inconsistencies are of operational concern since various Launch Commit Criteria (LCC) and Flight Rules (FR) in part describe safe and unsafe conditions as a function of <span class="hlt">cloud</span> thickness. Some background radar information was presented. Scan strategies for the WSR-74C and WSR-88D were reviewed along with a description of normal radar beam propagation influenced by the Effective Earth Radius Model. Atmospheric conditions prior to and leading up to both launch operations were detailed. Through the analysis of rawinsonde and radar data, atmospheric refraction or bending of the radar beam was <span class="hlt">identified</span> as the cause of the discrepancies between reported <span class="hlt">cloud</span> top heights by the contract weather aircraft and those as <span class="hlt">identified</span> by both radars. The atmospheric refraction caused the radar beam to be further bent toward the Earth than normal. This radar beam bending causes the radar target to be displayed erroneously, with higher <span class="hlt">cloud</span> top heights and a very blocky or skewed appearance.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1076686-climatology-surface-cloud-radiative-effects-arm-tropical-western-pacific-sites','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1076686-climatology-surface-cloud-radiative-effects-arm-tropical-western-pacific-sites"><span>A Climatology of Surface <span class="hlt">Cloud</span> Radiative Effects at the ARM Tropical Western Pacific Sites</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>McFarlane, Sally A.; Long, Charles N.; Flaherty, Julia E.</p> <p></p> <p><span class="hlt">Cloud</span> radiative effects on surface downwelling fluxes are investigated using long-term datasets from the three Atmospheric Radiation Measurement (ARM) sites in the Tropical Western Pacific (TWP) region. The Nauru and Darwin sites show significant variability in sky cover, downwelling radiative fluxes, and surface <span class="hlt">cloud</span> radiative effect (CRE) due to El Niño and the Australian monsoon, respectively, while the Manus site shows little intra-seasonal or interannual variability. <span class="hlt">Cloud</span> radar measurement of <span class="hlt">cloud</span> base and top heights are used to define <span class="hlt">cloud</span> <span class="hlt">types</span> so that the effect of <span class="hlt">cloud</span> <span class="hlt">type</span> on the surface CRE can be examined. <span class="hlt">Clouds</span> with low bases contributemore » 71-75% of the surface shortwave (SW) CRE and 66-74% of the surface longwave (LW) CRE at the three TWP sites, while <span class="hlt">clouds</span> with mid-level bases contribute 8-9% of the SW CRE and 12-14% of the LW CRE, and <span class="hlt">clouds</span> with high bases contribute 16-19% of the SW CRE and 15-21% of the LW CRE.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ApJS..235...15L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ApJS..235...15L"><span>Molecular Gas toward the Gemini OB1 Molecular <span class="hlt">Cloud</span> Complex. II. CO Outflow Candidates with Possible WISE Associations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Yingjie; Li, Fa-Cheng; Xu, Ye; Wang, Chen; Du, Xin-Yu; Yang, Wenjin; Yang, Ji</p> <p>2018-03-01</p> <p>We present a large-scale survey of CO outflows in the Gem OB1 molecular <span class="hlt">cloud</span> complex and its surroundings, using the Purple Mountain Observatory Delingha 13.7 m telescope. A total of 198 outflow candidates were <span class="hlt">identified</span> over a large area (∼58.5 square degrees), of which 193 are newly detected. Approximately 68% (134/198) are associated with the Gem OB1 molecular <span class="hlt">cloud</span> complex, including <span class="hlt">clouds</span> GGMC 1, GGMC 2, BFS 52, GGMC 3, and GGMC 4. Other regions studied are: the Local arm (Local Lynds, West Front), Swallow, Horn, and Remote <span class="hlt">cloud</span>. Outflow candidates in GGMC 1, BFS 52, and Swallow are mainly located at ring-like or filamentary structures. To avoid excessive uncertainty in distant regions (≳3.8 kpc), we only estimated the physical parameters for <span class="hlt">clouds</span> in the Gem OB1 molecular <span class="hlt">cloud</span> complex and in the Local arm. In those <span class="hlt">clouds</span>, the total kinetic energy and the energy injection rate of the <span class="hlt">identified</span> outflow candidates are ≲1% and ≲3% of the turbulent energy and the turbulent dissipation rate of each <span class="hlt">cloud</span>, indicating that the <span class="hlt">identified</span> outflow candidates cannot provide enough energy to balance turbulence of their host <span class="hlt">cloud</span> at the scale of the entire <span class="hlt">cloud</span> (several to dozens of parsecs). The gravitational binding energy of each <span class="hlt">cloud</span> is ≳135 times the total kinetic energy of the <span class="hlt">identified</span> outflow candidates within the corresponding <span class="hlt">cloud</span>, indicating that the <span class="hlt">identified</span> outflow candidates cannot cause major disruptions to the integrity of their host <span class="hlt">cloud</span> at the scale of the entire <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9367E..0GD','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9367E..0GD"><span>Silicon photonics <span class="hlt">cloud</span> (Si<span class="hlt">Cloud</span>)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>DeVore, Peter T. S.; Jiang, Yunshan; Lynch, Michael; Miyatake, Taira; Carmona, Christopher; Chan, Andrew C.; Muniam, Kuhan; Jalali, Bahram</p> <p>2015-02-01</p> <p>We present Si<span class="hlt">Cloud</span> (Silicon Photonics <span class="hlt">Cloud</span>), the first free, instructional web-based research and education tool for silicon photonics. Si<span class="hlt">Cloud</span>'s vision is to provide a host of instructional and research web-based tools. Such interactive learning tools enhance traditional teaching methods by extending access to a very large audience, resulting in very high impact. Interactive tools engage the brain in a way different from merely reading, and so enhance and reinforce the learning experience. Understanding silicon photonics is challenging as the topic involves a wide range of disciplines, including material science, semiconductor physics, electronics and waveguide optics. This web-based calculator is an interactive analysis tool for optical properties of silicon and related material (SiO2, Si3N4, Al2O3, etc.). It is designed to be a one stop resource for students, researchers and design engineers. The first and most basic aspect of Silicon Photonics is the Material Parameters, which provides the foundation for the Device, Sub-System and System levels. Si<span class="hlt">Cloud</span> includes the common dielectrics and semiconductors for waveguide core, cladding, and photodetection, as well as metals for electrical contacts. Si<span class="hlt">Cloud</span> is a work in progress and its capability is being expanded. Si<span class="hlt">Cloud</span> is being developed at UCLA with funding from the National Science Foundation's Center for Integrated Access Networks (CIAN) Engineering Research Center.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100033763','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100033763"><span>Relation of <span class="hlt">Cloud</span> Occurrence Frequency, Overlap, and Effective Thickness Derived from CALIPSO and <span class="hlt">Cloud</span>Sat Merged <span class="hlt">Cloud</span> Vertical Profiles</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.</p> <p>2009-01-01</p> <p>A <span class="hlt">cloud</span> frequency of occurrence matrix is generated using merged <span class="hlt">cloud</span> vertical profile derived from <span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization (CALIOP) and <span class="hlt">Cloud</span> Profiling Radar (CPR). The matrix contains vertical profiles of <span class="hlt">cloud</span> occurrence frequency as a function of the uppermost <span class="hlt">cloud</span> top. It is shown that the <span class="hlt">cloud</span> fraction and uppermost <span class="hlt">cloud</span> top vertical pro les can be related by a set of equations when the correlation distance of <span class="hlt">cloud</span> occurrence, which is interpreted as an effective <span class="hlt">cloud</span> thickness, is introduced. The underlying assumption in establishing the above relation is that <span class="hlt">cloud</span> overlap approaches the random overlap with increasing distance separating <span class="hlt">cloud</span> layers and that the probability of deviating from the random overlap decreases exponentially with distance. One month of CALIPSO and <span class="hlt">Cloud</span>Sat data support these assumptions. However, the correlation distance sometimes becomes large, which might be an indication of precipitation. The <span class="hlt">cloud</span> correlation distance is equivalent to the de-correlation distance introduced by Hogan and Illingworth [2000] when <span class="hlt">cloud</span> fractions of both layers in a two-<span class="hlt">cloud</span> layer system are the same.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_17");'>17</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li class="active"><span>19</span></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_19 --> <div id="page_20" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="381"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACPD...15.2405P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACPD...15.2405P"><span>Microphysical processing of aerosol particles in orographic <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pousse-Nottelmann, S.; Zubler, E. M.; Lohmann, U.</p> <p>2015-01-01</p> <p>An explicit and detailed treatment of <span class="hlt">cloud</span>-borne particles allowing for the consideration of aerosol cycling in <span class="hlt">clouds</span> has been implemented in the regional weather forecast and climate model COSMO. The effects of aerosol scavenging, <span class="hlt">cloud</span> microphysical processing and regeneration upon <span class="hlt">cloud</span> evaporation on the aerosol population and on subsequent <span class="hlt">cloud</span> formation are investigated. For this, two-dimensional idealized simulations of moist flow over two bell-shaped mountains were carried out varying the treatment of aerosol scavenging and regeneration processes for a warm-phase and a mixed-phase orographic <span class="hlt">cloud</span>. The results allowed to <span class="hlt">identify</span> different aerosol cycling mechanisms. In the simulated non-precipitating warm-phase <span class="hlt">cloud</span>, aerosol mass is incorporated into <span class="hlt">cloud</span> droplets by activation scavenging and released back to the atmosphere upon <span class="hlt">cloud</span> droplet evaporation. In the mixed-phase <span class="hlt">cloud</span>, a first cycle comprises <span class="hlt">cloud</span> droplet activation and evaporation via the Wegener-Bergeron-Findeisen process. A second cycle includes below-<span class="hlt">cloud</span> scavenging by precipitating snow particles and snow sublimation and is connected to the first cycle via the riming process which transfers aerosol mass from <span class="hlt">cloud</span> droplets to snow flakes. In the simulated mixed-phase <span class="hlt">cloud</span>, only a negligible part of the total aerosol mass is incorporated into ice crystals. Sedimenting snow flakes reaching the surface remove aerosol mass from the atmosphere. The results show that aerosol processing and regeneration lead to a vertical redistribution of aerosol mass and number. However, the processes not only impact the total aerosol number and mass, but also the shape of the aerosol size distributions by enhancing the internally mixed/soluble accumulation mode and generating coarse mode particles. Concerning subsequent <span class="hlt">cloud</span> formation at the second mountain, accounting for aerosol processing and regeneration increases the <span class="hlt">cloud</span> droplet number concentration with possible implications for the ice</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015ACP....15.9217P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015ACP....15.9217P"><span>Microphysical processing of aerosol particles in orographic <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Pousse-Nottelmann, S.; Zubler, E. M.; Lohmann, U.</p> <p>2015-08-01</p> <p>An explicit and detailed treatment of <span class="hlt">cloud</span>-borne particles allowing for the consideration of aerosol cycling in <span class="hlt">clouds</span> has been implemented into COSMO-Model, the regional weather forecast and climate model of the Consortium for Small-scale Modeling (COSMO). The effects of aerosol scavenging, <span class="hlt">cloud</span> microphysical processing and regeneration upon <span class="hlt">cloud</span> evaporation on the aerosol population and on subsequent <span class="hlt">cloud</span> formation are investigated. For this, two-dimensional idealized simulations of moist flow over two bell-shaped mountains were carried out varying the treatment of aerosol scavenging and regeneration processes for a warm-phase and a mixed-phase orographic <span class="hlt">cloud</span>. The results allowed us to <span class="hlt">identify</span> different aerosol cycling mechanisms. In the simulated non-precipitating warm-phase <span class="hlt">cloud</span>, aerosol mass is incorporated into <span class="hlt">cloud</span> droplets by activation scavenging and released back to the atmosphere upon <span class="hlt">cloud</span> droplet evaporation. In the mixed-phase <span class="hlt">cloud</span>, a first cycle comprises <span class="hlt">cloud</span> droplet activation and evaporation via the Wegener-Bergeron-Findeisen (WBF) process. A second cycle includes below-<span class="hlt">cloud</span> scavenging by precipitating snow particles and snow sublimation and is connected to the first cycle via the riming process which transfers aerosol mass from <span class="hlt">cloud</span> droplets to snowflakes. In the simulated mixed-phase <span class="hlt">cloud</span>, only a negligible part of the total aerosol mass is incorporated into ice crystals. Sedimenting snowflakes reaching the surface remove aerosol mass from the atmosphere. The results show that aerosol processing and regeneration lead to a vertical redistribution of aerosol mass and number. Thereby, the processes impact the total aerosol number and mass and additionally alter the shape of the aerosol size distributions by enhancing the internally mixed/soluble Aitken and accumulation mode and generating coarse-mode particles. Concerning subsequent <span class="hlt">cloud</span> formation at the second mountain, accounting for aerosol processing and regeneration increases</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1980A%26A....87..328B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1980A%26A....87..328B"><span>Iron hydrides formation in interstellar <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Bar-Nun, A.; Pasternak, M.; Barrett, P. H.</p> <p>1980-07-01</p> <p>A recent Moessbauer study with Fe-57 in a solid hydrogen or hydrogen-argon matrix demonstrated the formation of an iron hydride molecule (FeH2) at 2.5-5 K. Following this and other studies, the possible existence of iron hydride molecules in interstellar <span class="hlt">clouds</span> is proposed. In <span class="hlt">clouds</span>, the iron hydrides FeH and FeH2 would be formed only on grains, by encounters of H atoms or H2 molecules with Fe atoms which are adsorbed on the grains. The other transition metals, Sc, Ti, V, Cr, Mn, Co, N, Cd and also Cu and Ca form hydrides of the <span class="hlt">type</span> M-H, which could be responsible, at least in part, for the depletion of these metals in <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011ici1.conf..565S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011ici1.conf..565S"><span>Enhancing Security by System-Level Virtualization in <span class="hlt">Cloud</span> Computing Environments</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sun, Dawei; Chang, Guiran; Tan, Chunguang; Wang, Xingwei</p> <p></p> <p>Many trends are opening up the era of <span class="hlt">cloud</span> computing, which will reshape the IT industry. Virtualization techniques have become an indispensable ingredient for almost all <span class="hlt">cloud</span> computing system. By the virtual environments, <span class="hlt">cloud</span> provider is able to run varieties of operating systems as needed by each <span class="hlt">cloud</span> user. Virtualization can improve reliability, security, and availability of applications by using consolidation, isolation, and fault tolerance. In addition, it is possible to balance the workloads by using live migration techniques. In this paper, the definition of <span class="hlt">cloud</span> computing is given; and then the service and deployment models are introduced. An analysis of security issues and challenges in implementation of <span class="hlt">cloud</span> computing is <span class="hlt">identified</span>. Moreover, a system-level virtualization case is established to enhance the security of <span class="hlt">cloud</span> computing environments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A51E2116G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A51E2116G"><span>Influence of Meteorological Regimes on <span class="hlt">Cloud</span> Microphysics Over Ross Island, Antarctica</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Glennon, C.; Wang, S. H.; Scott, R. C.; Bromwich, D. H.; Lubin, D.</p> <p>2017-12-01</p> <p>The Antarctic provides a sharp contrast in <span class="hlt">cloud</span> microphysics from the high Arctic, due to orographic lifting and resulting strong vertical motions induced by mountain ranges and other varying terrain on several spatial scales. The Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE) deployed advanced <span class="hlt">cloud</span> remote sensing equipment to Ross Island, Antarctica, from December 2015 until January 2016. This equipment included scanning and zenith radars operating in the Ka and X bands, a high spectral resolution lidar (HSRL), and a polarized micropulse lidar (MPL). A major AWARE objective is to provide state-of-the-art data for improving <span class="hlt">cloud</span> microphysical parameterizations in climate models. To further this objective we have organized and classified the local Ross Island meteorology into distinct regimes using k-means clustering on ERA-Interim reanalysis data. We <span class="hlt">identify</span> synoptic categories producing unique regimes of <span class="hlt">cloud</span> cover and <span class="hlt">cloud</span> microphysical properties over Ross Island. Each day of observations can then be associated with a specific meteorological regime, thus assisting modelers with <span class="hlt">identifying</span> case studies. High-resolution (1 km) weather forecasts from the Antarctic Mesoscale Prediction System (AMPS) are sorted into these categories. AMPS-simulated anomalies of <span class="hlt">cloud</span> fraction, near-surface air temperature, and vertical velocity at 500-mb are composited and compared with ground-based radar and lidar-derived <span class="hlt">cloud</span> properties to <span class="hlt">identify</span> mesoscale meteorological processes driving Antarctic <span class="hlt">cloud</span> formation. Synoptic lows over the Ross and Amundsen Seas drive anomalously warm conditions at Ross Island by injecting marine air masses inland over the West Antarctic Ice Sheet (WAIS). This results in ice and mixed-phase orographic <span class="hlt">cloud</span> systems arriving at Ross Island from the south to southeast along the Transantarctic Mountains. In contrast, blocking over the Amundsen Sea region brings classical liquid-dominated mixed-phase and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ISPAn42W4..393S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ISPAn42W4..393S"><span>Automatic Generation of Indoor Navigable Space Using a Point <span class="hlt">Cloud</span> and its Scanner Trajectory</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Staats, B. R.; Diakité, A. A.; Voûte, R. L.; Zlatanova, S.</p> <p>2017-09-01</p> <p>Automatic generation of indoor navigable models is mostly based on 2D floor plans. However, in many cases the floor plans are out of date. Buildings are not always built according to their blue prints, interiors might change after a few years because of modified walls and doors, and furniture may be repositioned to the user's preferences. Therefore, new approaches for the quick recording of indoor environments should be investigated. This paper concentrates on laser scanning with a Mobile Laser Scanner (MLS) device. The MLS device stores a point <span class="hlt">cloud</span> and its trajectory. If the MLS device is operated by a human, the trajectory contains information which can be used to distinguish different surfaces. In this paper a method is presented for the identification of walkable surfaces based on the analysis of the point <span class="hlt">cloud</span> and the trajectory of the MLS scanner. This method consists of several steps. First, the point <span class="hlt">cloud</span> is voxelized. Second, the trajectory is analysing and projecting to acquire seed voxels. Third, these seed voxels are generated into floor regions by the use of a region growing process. By <span class="hlt">identifying</span> dynamic objects, doors and furniture, these floor regions can be modified so that each region represents a specific navigable space inside a building as a free navigable voxel space. By combining the point <span class="hlt">cloud</span> and its corresponding trajectory, the walkable space can be <span class="hlt">identified</span> for any <span class="hlt">type</span> of building even if the interior is scanned during business hours.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ISPAnIV21..119P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ISPAnIV21..119P"><span>Smart Point <span class="hlt">Cloud</span>: Definition and Remaining Challenges</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Poux, F.; Hallot, P.; Neuville, R.; Billen, R.</p> <p>2016-10-01</p> <p>Dealing with coloured point <span class="hlt">cloud</span> acquired from terrestrial laser scanner, this paper <span class="hlt">identifies</span> remaining challenges for a new data structure: the smart point <span class="hlt">cloud</span>. This concept arises with the statement that massive and discretized spatial information from active remote sensing technology is often underused due to data mining limitations. The generalisation of point <span class="hlt">cloud</span> data associated with the heterogeneity and temporality of such datasets is the main issue regarding structure, segmentation, classification, and interaction for an immediate understanding. We propose to use both point <span class="hlt">cloud</span> properties and human knowledge through machine learning to rapidly extract pertinent information, using user-centered information (smart data) rather than raw data. A review of feature detection, machine learning frameworks and database systems indexed both for mining queries and data visualisation is studied. Based on existing approaches, we propose a new 3-block flexible framework around device expertise, analytic expertise and domain base reflexion. This contribution serves as the first step for the realisation of a comprehensive smart point <span class="hlt">cloud</span> data structure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001JGR...10622907F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001JGR...10622907F"><span>Analysis of smoke impact on <span class="hlt">clouds</span> in Brazilian biomass burning regions: An extension of Twomey's approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Feingold, Graham; Remer, Lorraine A.; Ramaprasad, Jaya; Kaufman, Yoram J.</p> <p>2001-10-01</p> <p>Satellite remote sensing of smoke aerosol-<span class="hlt">cloud</span> interaction during the recent Smoke, <span class="hlt">Clouds</span>, and Radiation-Brazil (SCAR-B) experiment is analyzed to explore the factors that determine the magnitude of the <span class="hlt">cloud</span> response to smoke aerosol. Analysis of 2 years worth of data revealed that the response is greatest in the north of Brazil where aerosol optical depth is smallest, and tends to decrease as one moves southward, and as aerosol optical depth increases. Saturation in this response occurs at an aerosol optical depth of 0.8 in 1987 and 0.4 in 1995. To explore the reasons for this, a framework is developed in which the satellite-measured response can be compared to simple analytical models of this response and to numerical models of smoke aerosol-<span class="hlt">cloud</span> interaction. Three <span class="hlt">types</span> of response are <span class="hlt">identified</span>: (1) <span class="hlt">cloud</span> droplet concentrations increase with increasing aerosol loading, followed by saturation in the response at high concentrations; (2) as in <span class="hlt">type</span> 1, followed by increasing droplet concentrations with further increases in aerosol loading. This increase in droplet concentration is due to the suppression of supersaturation by abundant large particles, which prevents the activation of smaller particles. This enables renewed activation of larger particles when smoke loadings exceed some threshold; (3) as in <span class="hlt">type</span> 1, followed by a decrease in droplet number concentrations with increasing aerosol loading as intense competition for vapor evaporates the smaller droplets. The latter implies an unexpected increase in drop size with increasing smoke loading. The conditions under which each of these responses are expected to occur are discussed. It is shown that although to first-order smoke optical depth is a good proxy for aerosol indirect forcing, under some conditions the size distribution and hygroscopicity can be important factors. We find no evidence that indirect forcing depends on precipitable water vapor.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19880014739','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19880014739"><span><span class="hlt">Cloud</span> cover determination in polar regions from satellite imagery</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barry, R. G.; Key, J. R.; Maslanik, J. A.</p> <p>1988-01-01</p> <p>The principal objectives of this project are: to develop suitable validation data sets to evaluate the effectiveness of the ISCCP operational algorithm for <span class="hlt">cloud</span> retrieval in polar regions and to validate model simulations of polar <span class="hlt">cloud</span> cover; to <span class="hlt">identify</span> limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers: and to compare synoptic <span class="hlt">cloud</span> data from a control run experiment of the Goddard Institute for Space Studies (GISS) climate model 2 with typical observed synoptic <span class="hlt">cloud</span> patterns. Current investigations underway are listed and the progress made to date is summarized.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015MNRAS.446.3608D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015MNRAS.446.3608D"><span>The frequency and nature of `<span class="hlt">cloud-cloud</span> collisions' in galaxies</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dobbs, C. L.; Pringle, J. E.; Duarte-Cabral, A.</p> <p>2015-02-01</p> <p>We investigate <span class="hlt">cloud-cloud</span> collisions and giant molecular <span class="hlt">cloud</span> evolution in hydrodynamic simulations of isolated galaxies. The simulations include heating and cooling of the interstellar medium (ISM), self-gravity and stellar feedback. Over time-scales <5 Myr most <span class="hlt">clouds</span> undergo no change, and mergers and splits are found to be typically two-body processes, but evolution over longer time-scales is more complex and involves a greater fraction of intercloud material. We find that mergers or collisions occur every 8-10 Myr (1/15th of an orbit) in a simulation with spiral arms, and once every 28 Myr (1/5th of an orbit) with no imposed spiral arms. Both figures are higher than expected from analytic estimates, as <span class="hlt">clouds</span> are not uniformly distributed in the galaxy. Thus, <span class="hlt">clouds</span> can be expected to undergo between zero and a few collisions over their lifetime. We present specific examples of <span class="hlt">cloud-cloud</span> interactions in our results, including synthetic CO maps. We would expect <span class="hlt">cloud-cloud</span> interactions to be observable, but find they appear to have little or no impact on the ISM. Due to a combination of the <span class="hlt">clouds</span>' typical geometries, and moderate velocity dispersions, <span class="hlt">cloud-cloud</span> interactions often better resemble a smaller <span class="hlt">cloud</span> nudging a larger <span class="hlt">cloud</span>. Our findings are consistent with the view that spiral arms make little difference to overall star formation rates in galaxies, and we see no evidence that collisions likely produce massive clusters. However, to confirm the outcome of such massive <span class="hlt">cloud</span> collisions we ideally need higher resolution simulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..1817632R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..1817632R"><span>Unidata cyberinfrastructure in the <span class="hlt">cloud</span>: A progress report</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ramamurthy, Mohan</p> <p>2016-04-01</p> <p>Data services, software, and committed support are critical components of geosciences cyber-infrastructure that can help scientists address problems of unprecedented complexity, scale, and scope. Unidata is currently working on innovative ideas, new paradigms, and novel techniques to complement and extend its offerings. Our goal is to empower users so that they can tackle major, heretofore difficult problems. Unidata recognizes that its products and services must evolve to support new approaches to research and education. After years of hype and ambiguity, <span class="hlt">cloud</span> computing is maturing in usability in many areas of science and education, bringing the benefits of virtualized and elastic remote services to infrastructure, software, computation, and data. <span class="hlt">Cloud</span> environments reduce the amount of time and money spent to procure, install, and maintain new hardware and software, and reduce costs through resource pooling and shared infrastructure. <span class="hlt">Cloud</span> services aimed at providing any resource, at any time, from any place, using any device are increasingly being embraced by all <span class="hlt">types</span> of organizations. Given this trend and the enormous potential of <span class="hlt">cloud</span>-based services, Unidata is moving to augment its products, services, data delivery mechanisms and applications to align with the <span class="hlt">cloud</span>-computing paradigm. To realize the above vision, Unidata is working toward: * Providing access to many <span class="hlt">types</span> of data from a <span class="hlt">cloud</span> (e.g., TDS, RAMADDA and EDEX); * Deploying data-proximate tools to easily process, analyze and visualize those data in a <span class="hlt">cloud</span> environment <span class="hlt">cloud</span> for consumption by any one, by any device, from anywhere, at any time; * Developing and providing a range of pre-configured and well-integrated tools and services that can be deployed by any university in their own private or public <span class="hlt">cloud</span> settings. Specifically, Unidata has developed Docker for "containerized applications", making them easy to deploy. Docker helps to create "disposable" installs and eliminates many</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1339855-vertical-overlap-probability-density-functions-cloud-precipitation-hydrometeors-cloud-precipitation-pdf-overlap','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1339855-vertical-overlap-probability-density-functions-cloud-precipitation-hydrometeors-cloud-precipitation-pdf-overlap"><span>Vertical overlap of probability density functions of <span class="hlt">cloud</span> and precipitation hydrometeors: <span class="hlt">CLOUD</span> AND PRECIPITATION PDF OVERLAP</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Ovchinnikov, Mikhail; Lim, Kyo-Sun Sunny; Larson, Vincent E.</p> <p></p> <p>Coarse-resolution climate models increasingly rely on probability density functions (PDFs) to represent subgrid-scale variability of prognostic variables. While PDFs characterize the horizontal variability, a separate treatment is needed to account for the vertical structure of <span class="hlt">clouds</span> and precipitation. When sub-columns are drawn from these PDFs for microphysics or radiation parameterizations, appropriate vertical correlations must be enforced via PDF overlap specifications. This study evaluates the representation of PDF overlap in the Subgrid Importance Latin Hypercube Sampler (SILHS) employed in the assumed PDF turbulence and <span class="hlt">cloud</span> scheme called the <span class="hlt">Cloud</span> Layers Unified By Binormals (CLUBB). PDF overlap in CLUBB-SILHS simulations of continentalmore » and tropical oceanic deep convection is compared with overlap of PDF of various microphysics variables in <span class="hlt">cloud</span>-resolving model (CRM) simulations of the same cases that explicitly predict the 3D structure of <span class="hlt">cloud</span> and precipitation fields. CRM results show that PDF overlap varies significantly between different hydrometeor <span class="hlt">types</span>, as well as between PDFs of mass and number mixing ratios for each species, - a distinction that the current SILHS implementation does not make. In CRM simulations that explicitly resolve <span class="hlt">cloud</span> and precipitation structures, faster falling species, such as rain and graupel, exhibit significantly higher coherence in their vertical distributions than slow falling <span class="hlt">cloud</span> liquid and ice. These results suggest that to improve the overlap treatment in the sub-column generator, the PDF correlations need to depend on hydrometeor properties, such as fall speeds, in addition to the currently implemented dependency on the turbulent convective length scale.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A43B0208W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A43B0208W"><span>Contrasting <span class="hlt">Cloud</span> Composition Between Coupled and Decoupled Marine Boundary Layer <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>WANG, Z.; Mora, M.; Dadashazar, H.; MacDonald, A.; Crosbie, E.; Bates, K. H.; Coggon, M. M.; Craven, J. S.; Xian, P.; Campbell, J. R.; AzadiAghdam, M.; Woods, R. K.; Jonsson, H.; Flagan, R. C.; Seinfeld, J.; Sorooshian, A.</p> <p>2016-12-01</p> <p>Marine stratocumulus <span class="hlt">clouds</span> often become decoupled from the vertical layer immediately above the ocean surface. This study contrasts <span class="hlt">cloud</span> chemical composition between coupled and decoupled marine stratocumulus <span class="hlt">clouds</span>. <span class="hlt">Cloud</span> water and droplet residual particle composition were measured in <span class="hlt">clouds</span> off the California coast during three airborne experiments in July-August of separate years (E-PEACE 2011, NiCE 2013, BOAS 2015). Decoupled <span class="hlt">clouds</span> exhibited significantly lower overall mass concentrations in both <span class="hlt">cloud</span> water and droplet residual particles, consistent with reduced <span class="hlt">cloud</span> droplet number concentration and sub-<span class="hlt">cloud</span> aerosol (Dp > 100 nm) number concentration, owing to detachment from surface sources. Non-refractory sub-micrometer aerosol measurements show that coupled <span class="hlt">clouds</span> exhibit higher sulfate mass fractions in droplet residual particles, owing to more abundant precursor emissions from the ocean and ships. Consequently, decoupled <span class="hlt">clouds</span> exhibited higher mass fractions of organics, nitrate, and ammonium in droplet residual particles, owing to effects of long-range transport from more distant sources. Total <span class="hlt">cloud</span> water mass concentration in coupled <span class="hlt">clouds</span> was dominated by sodium and chloride, and their mass fractions and concentrations exceeded those in decoupled <span class="hlt">clouds</span>. Conversely, with the exception of sea salt constituents (e.g., Cl, Na, Mg, K), <span class="hlt">cloud</span> water mass fractions of all species examined were higher in decoupled <span class="hlt">clouds</span> relative to coupled <span class="hlt">clouds</span>. These results suggest that an important variable is the extent to which <span class="hlt">clouds</span> are coupled to the surface layer when interpreting microphysical data relevant to <span class="hlt">clouds</span> and aerosol particles.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A43B0210N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A43B0210N"><span>Stratus <span class="hlt">Cloud</span> Radiative Effects from <span class="hlt">Cloud</span> Processed Bimodal CCN Distributions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Noble, S. R., Jr.; Hudson, J. G.</p> <p>2016-12-01</p> <p>Inability to understand <span class="hlt">cloud</span> processes is a large component of climate uncertainty. Increases in <span class="hlt">cloud</span> condensation nuclei (CCN) concentrations are known to increase <span class="hlt">cloud</span> droplet number concentrations (Nc). This aerosol-<span class="hlt">cloud</span> interaction (ACI) produces greater Nc at smaller sizes, which brightens <span class="hlt">clouds</span>. A lesser understood ACI is <span class="hlt">cloud</span> processing of CCN. This improves CCN that then more easily activate at lower <span class="hlt">cloud</span> supersaturations (S). Bimodal CCN distributions thus ensue from these evaporated <span class="hlt">cloud</span> droplets. Hudson et al. (2015) related CCN bimodality to Nc. In stratus <span class="hlt">clouds</span>, bimodal CCN created greater Nc whereas in cumulus less Nc. Thus, CCN distribution shape influences <span class="hlt">cloud</span> properties; microphysics and radiative properties. Measured uni- and bimodal CCN distributions were input into an adiabatic droplet growth model using various specified vertical wind speeds (W). Bimodal CCN produced greater Nc (Fig. 1a) and smaller mean diameters (MD; Fig. 1b) at lower W typical of stratus <span class="hlt">clouds</span> (<70 cm/s). Improved CCN (low critical S) were more easily activated at the lower S of stratus from low W, thus, creating greater Nc. Competition for condensate thus reduced MD and drizzle. At greater W, typical of cumulus <span class="hlt">clouds</span> (>70 cm/s), bimodal CCN made lower Nc with larger MD thus enhancing drizzle whereas unimodal CCN made greater Nc with smaller MD, thus reducing drizzle. Thus, theoretical predictions of Nc and MD for uni- and bimodal CCN agree with the sense of the observations. Radiative effects were determined using a <span class="hlt">cloud</span> grown to a 250-meter thickness. Bimodal CCN at low W reduced <span class="hlt">cloud</span> effective radius (re), made greater <span class="hlt">cloud</span> optical thickness (COT), and made greater <span class="hlt">cloud</span> albedo (Fig. 1c). At very low W changes were as much as +9% for albedo, +17% for COT, and -12% for re. Stratus <span class="hlt">clouds</span> typically have low W and cover large areas. Thus, these changes in <span class="hlt">cloud</span> radiative properties at low W impact climate. Stratus <span class="hlt">cloud</span> susceptibility to CCN distribution thus</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040121211','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040121211"><span>Daytime <span class="hlt">Cloud</span> Property Retrievals Over the Arctic from Multispectral MODIS Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spangenberg, Douglas A.; Trepte, Qing; Minnis, Patrick; Uttal, Taneil</p> <p>2004-01-01</p> <p>Improving climate model predictions over Earth's polar regions requires a complete understanding of polar <span class="hlt">clouds</span> properties. Passive satellite remote sensing techniques can be used to retrieve macro and microphysical properties of polar <span class="hlt">cloud</span> systems. However, over the Arctic, there is minimal contrast between <span class="hlt">clouds</span> and the background snow surface observed in satellite data, especially for visible wavelengths. This makes it difficult to <span class="hlt">identify</span> <span class="hlt">clouds</span> and retrieve their properties from space. Variable snow and ice cover, temperature inversions, and the predominance of mixed-phase <span class="hlt">clouds</span> further complicate <span class="hlt">cloud</span> property identification. For this study, the operational <span class="hlt">Clouds</span> and the Earth s Radiant Energy System (CERES) <span class="hlt">cloud</span> mask is first used to discriminate <span class="hlt">clouds</span> from the background surface in Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data. A solar-infrared infrared nearinfrared technique (SINT) first used by Platnick et al. (2001) is used here to retrieve <span class="hlt">cloud</span> properties over snow and ice covered regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JPhCS1025a2091A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JPhCS1025a2091A"><span>Hybrid <span class="hlt">cloud</span>: bridging of private and public <span class="hlt">cloud</span> computing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Aryotejo, Guruh; Kristiyanto, Daniel Y.; Mufadhol</p> <p>2018-05-01</p> <p><span class="hlt">Cloud</span> Computing is quickly emerging as a promising paradigm in the recent years especially for the business sector. In addition, through <span class="hlt">cloud</span> service providers, <span class="hlt">cloud</span> computing is widely used by Information Technology (IT) based startup company to grow their business. However, the level of most businesses awareness on data security issues is low, since some <span class="hlt">Cloud</span> Service Provider (CSP) could decrypt their data. Hybrid <span class="hlt">Cloud</span> Deployment Model (HCDM) has characteristic as open source, which is one of secure <span class="hlt">cloud</span> computing model, thus HCDM may solve data security issues. The objective of this study is to design, deploy and evaluate a HCDM as Infrastructure as a Service (IaaS). In the implementation process, Metal as a Service (MAAS) engine was used as a base to build an actual server and node. Followed by installing the vsftpd application, which serves as FTP server. In comparison with HCDM, public <span class="hlt">cloud</span> was adopted through public <span class="hlt">cloud</span> interface. As a result, the design and deployment of HCDM was conducted successfully, instead of having good security, HCDM able to transfer data faster than public <span class="hlt">cloud</span> significantly. To the best of our knowledge, Hybrid <span class="hlt">Cloud</span> Deployment model is one of secure <span class="hlt">cloud</span> computing model due to its characteristic as open source. Furthermore, this study will serve as a base for future studies about Hybrid <span class="hlt">Cloud</span> Deployment model which may relevant for solving big security issues of IT-based startup companies especially in Indonesia.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1994JAtS...51..397M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1994JAtS...51..397M"><span>Fractal Analyses of High-Resolution <span class="hlt">Cloud</span> Droplet Measurements.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Malinowski, Szymon P.; Leclerc, Monique Y.; Baumgardner, Darrel G.</p> <p>1994-02-01</p> <p>Fractal analyses of individual <span class="hlt">cloud</span> droplet distributions using aircraft measurements along one-dimensional horizontal cross sections through <span class="hlt">clouds</span> are performed. Box counting and cluster analyses are used to determine spatial scales of inhomogeneity of <span class="hlt">cloud</span> droplet spacing. These analyses reveal that droplet spatial distributions do not exhibit a fractal behavior. A high variability in local droplet concentration in <span class="hlt">cloud</span> volumes undergoing mixing was found. In these regions, thin filaments of cloudy air with droplet concentration close to those observed in <span class="hlt">cloud</span> cores were found. Results suggest that these filaments may be anisotropic. Additional box counting analyses performed for various classes of <span class="hlt">cloud</span> droplet diameters indicate that large and small droplets are similarly distributed, except for the larger characteristic spacing of large droplets.A <span class="hlt">cloud</span>-clear air interface defined by a certain threshold of total droplet count (TDC) was investigated. There are indications that this interface is a convoluted surface of a fractal nature, at least in actively developing cumuliform <span class="hlt">clouds</span>. In contrast, TDC in the <span class="hlt">cloud</span> interior does not have fractal or multifractal properties. Finally a random Cantor set (RCS) was introduced as a model of a fractal process with an ill-defined internal scale. A uniform measure associated with the RCS after several generations was introduced to simulate the TDC records. Comparison of the model with real TDC records indicates similar properties of both <span class="hlt">types</span> of data series.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25849093','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25849093"><span>Ace<span class="hlt">Cloud</span>: Molecular Dynamics Simulations in the <span class="hlt">Cloud</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Harvey, M J; De Fabritiis, G</p> <p>2015-05-26</p> <p>We present Ace<span class="hlt">Cloud</span>, an on-demand service for molecular dynamics simulations. Ace<span class="hlt">Cloud</span> is designed to facilitate the secure execution of large ensembles of simulations on an external <span class="hlt">cloud</span> computing service (currently Amazon Web Services). The Ace<span class="hlt">Cloud</span> client, integrated into the ACEMD molecular dynamics package, provides an easy-to-use interface that abstracts all aspects of interaction with the <span class="hlt">cloud</span> services. This gives the user the experience that all simulations are running on their local machine, minimizing the learning curve typically associated with the transition to using high performance computing services.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017PhLB..773..129F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017PhLB..773..129F"><span>Stationary scalar <span class="hlt">clouds</span> around a BTZ black hole</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ferreira, Hugo R. C.; Herdeiro, Carlos A. R.</p> <p>2017-10-01</p> <p>We establish the existence of stationary <span class="hlt">clouds</span> of massive test scalar fields around BTZ black holes. These <span class="hlt">clouds</span> are zero-modes of the superradiant instability and are possible when Robin boundary conditions (RBCs) are considered at the AdS boundary. These boundary conditions are the most general ones that ensure the AdS space is an isolated system, and include, as a particular case, the commonly considered Dirichlet or Neumann-<span class="hlt">type</span> boundary conditions (DBCs or NBCs). We obtain an explicit, closed form, resonance condition, relating the RBCs that allow the existence of normalizable (and regular on and outside the horizon) <span class="hlt">clouds</span> to the system's parameters. Such RBCs never include pure DBCs or NBCs. We illustrate the spatial distribution of these <span class="hlt">clouds</span>, their energy and angular momentum density for some cases. Our results show that BTZ black holes with scalar hair can be constructed, as the non-linear realization of these <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=S62-06021&hterms=friendship&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dfriendship','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=S62-06021&hterms=friendship&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dfriendship"><span>View of <span class="hlt">clouds</span> over Indian Ocean taken by Astronaut John Glenn during MA-6</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>1962-01-01</p> <p>A view of <span class="hlt">clouds</span> over the Indian Ocean as photographed by Astronaut John H. Glenn Jr. aboard the 'Friendship 7' spacecraft on February 20, 1962. The <span class="hlt">cloud</span> panorama illustrates the visibility of different <span class="hlt">cloud</span> <span class="hlt">types</span> and weather patterns. Shadows produced by the rising Sun aid in the determination of relative <span class="hlt">cloud</span> heights.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_18");'>18</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li class="active"><span>20</span></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_20 --> <div id="page_21" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="401"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ACPD...1016475A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ACPD...1016475A"><span>Deep convective <span class="hlt">clouds</span> at the tropopause</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Aumann, H. H.; Desouza-Machado, S. G.</p> <p>2010-07-01</p> <p>Data from the Advanced Infrared Sounder (AIRS) on the EOS Aqua spacecraft <span class="hlt">identify</span> thousands of <span class="hlt">cloud</span> tops colder than 225 K, loosely referred to as Deep Convective <span class="hlt">Clouds</span> (DCC). Many of these <span class="hlt">cloud</span> tops have "inverted" spectra, i.e. areas of strong water vapor, CO2 and ozone opacity, normally seen in absorption, are now seen in emission. We refer to these inverted spectra as DCCi. They are found in about 0.4% of all spectra from the tropical oceans excluding the Western Tropical Pacific (WTP), 1.1% in the WTP. The cold <span class="hlt">clouds</span> are the anvils capping thunderstorms and consist of optically thick cirrus ice <span class="hlt">clouds</span>. The precipitation rate associated with DCCi suggests that imbedded in these <span class="hlt">clouds</span>, protruding above them, and not spatially resolved by the AIRS 15 km FOV, are even colder bubbles, where strong convection pushes <span class="hlt">clouds</span> to within 5 hPa of the pressure level of the tropopause cold point. Associated with DCCi is a local upward displacement of the tropopause, a cold "bulge", which can be seen directly in the brightness temperatures of AIRS and AMSU channels with weighting function peaking between 40 and 2 hPa, without the need for a formal temperature retrieval. The bulge is not resolved by the analysis in numerical weather prediction models. The locally cold <span class="hlt">cloud</span> tops relative to the analysis give the appearance (in the sense of an "illusion") of <span class="hlt">clouds</span> overshooting the tropopause and penetrating into the stratosphere. Based on a simple model of optically thick cirrus <span class="hlt">clouds</span>, the spectral inversions seen in the AIRS data do not require these <span class="hlt">clouds</span> to penetrate into the stratosphere. However, the contents of the cold bulge may be left in the lower stratosphere as soon as the strong convection subsides. The heavy precipitation and the distortion of the temperature structure near the tropopause indicate that DCCi are associated with intense storms. Significant long-term trends in the statistical properties of DCCi could be interesting indicators of climate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A23L..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A23L..06S"><span>The Dependence of <span class="hlt">Cloud</span> Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.</p> <p>2016-12-01</p> <p>Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on <span class="hlt">cloud</span> property trend uncertainty. The <span class="hlt">cloud</span> properties studied were <span class="hlt">cloud</span> fraction, effective temperature, optical thickness, and effective radius retrieved using the <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES) <span class="hlt">Cloud</span> Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net <span class="hlt">cloud</span> feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave <span class="hlt">cloud</span> feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between <span class="hlt">cloud</span> property trend uncertainty, <span class="hlt">cloud</span> feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different <span class="hlt">cloud</span> <span class="hlt">types</span> have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by <span class="hlt">cloud</span> <span class="hlt">types</span> for a clearer understanding of instrument accuracy requirements needed to detect changes in their <span class="hlt">cloud</span> properties. Combining this information with the radiative impact of different <span class="hlt">cloud</span> <span class="hlt">types</span> helps to prioritize among requirements for future satellite sensors and understanding the climate detection</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19810054694&hterms=1095&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3D%2526%25231095','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19810054694&hterms=1095&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3D%2526%25231095"><span>Sensitivity analysis of upwelling thermal radiance in presence of <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Subramanian, S. V.; Tiwari, S. N.; Suttles, J. T.</p> <p>1981-01-01</p> <p>Total upwelling radiance at the top of the atmosphere is evaluated theoretically in the presence of <span class="hlt">clouds</span>. The influence of <span class="hlt">cloud</span> heights, thicknesses and different <span class="hlt">cloud</span> covers on the upwelling radiance is also investigated. The characteristics of the two <span class="hlt">cloud</span> <span class="hlt">types</span> considered in this study closely correspond to altocumulus and cirrus with the <span class="hlt">cloud</span> emissivity as a function of its liquid water (or ice) content. For calculation of the integrated transmittance of atmospheric gases such as, H2O, CO2, O3, and N2O, the Quasi Random Band (QRB) model approach is adopted. Results are obtained in three different spectral ranges and are compared with the clearsky radiance results. It is found that the difference between the clearsky and cloudy radiance increases with increasing <span class="hlt">cloud</span> height and liquid water content. This difference also decreases as the surface temperature approaches the value of the <span class="hlt">cloud</span> top temperature.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003PhDT.......154H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003PhDT.......154H"><span>Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-<span class="hlt">Cloud</span> Classification System</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hong, Yang</p> <p></p> <p>Precipitation estimation from satellite information (VISIBLE , IR, or microwave) is becoming increasingly imperative because of its high spatial/temporal resolution and board coverage unparalleled by ground-based data. After decades' efforts of rainfall estimation using IR imagery as basis, it has been explored and concluded that the limitations/uncertainty of the existing techniques are: (1) pixel-based local-scale feature extraction; (2) IR temperature threshold to define rain/no-rain <span class="hlt">clouds</span>; (3) indirect relationship between rain rate and <span class="hlt">cloud</span>-top temperature; (4) lumped techniques to model high variability of <span class="hlt">cloud</span>-precipitation processes; (5) coarse scales of rainfall products. As continuing studies, a new version of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN), called <span class="hlt">Cloud</span> Classification System (CCS), has been developed to cope with these limitations in this dissertation. CCS includes three consecutive components: (1) a hybrid segmentation algorithm, namely Hierarchically Topographical Thresholding and Stepwise Seeded Region Growing (HTH-SSRG), to segment satellite IR images into separated <span class="hlt">cloud</span> patches; (2) a 3D feature extraction procedure to retrieve both pixel-based local-scale and patch-based large-scale features of <span class="hlt">cloud</span> patch at various heights; (3) an ANN model, Self-Organizing Nonlinear Output (SONO) network, to classify <span class="hlt">cloud</span> patches into similarity-based clusters, using Self-Organizing Feature Map (SOFM), and then calibrate hundreds of multi-parameter nonlinear functions to <span class="hlt">identify</span> the relationship between every <span class="hlt">cloud</span> <span class="hlt">types</span> and their underneath precipitation characteristics using Probability Matching Method and Multi-Start Downhill Simplex optimization techniques. The model was calibrated over the Southwest of United States (100°--130°W and 25°--45°N) first and then adaptively adjusted to the study region of North America Monsoon Experiment (65°--135°W and 10°--50°N) using</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19780009489','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19780009489"><span>Analyses of the <span class="hlt">cloud</span> contents of multispectral imagery from LANDSAT 2: Mesoscale assessments of <span class="hlt">cloud</span> and rainfall over the British Isles</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Barrett, E. C.; Grant, C. K. (Principal Investigator)</p> <p>1977-01-01</p> <p>The author has <span class="hlt">identified</span> the following significant results. It was demonstrated that satellites with sufficiently high resolution capability in the visible region of the electromagnetic spectrum could be used to check the accuracy of estimates of total <span class="hlt">cloud</span> amount assessed subjectively from the ground, and to reveal areas of performance in which corrections should be made. It was also demonstrated that, in middle latitude in summer, <span class="hlt">cloud</span> shadow may obscure at least half as much again of the land surface covered by an individual LANDSAT frame as the <span class="hlt">cloud</span> itself. That proportion would increase with latitude and/or time of year towards the winter solstice. Analyses of sample multispectral images for six different categories of <span class="hlt">clouds</span> in summer revealed marked differences between the reflectance characteristics of <span class="hlt">cloud</span> fields in the visible/near infrared region of the spectrum.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070022448','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070022448"><span>Marine Boundary Layer <span class="hlt">Cloud</span> Properties From AMF Point Reyes Satellite Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jensen, Michael; Vogelmann, Andrew M.; Luke, Edward; Minnis, Patrick; Miller, Mark A.; Khaiyer, Mandana; Nguyen, Louis; Palikonda, Rabindra</p> <p>2007-01-01</p> <p><span class="hlt">Cloud</span> Diameter, C(sub D), offers a simple measure of Marine Boundary Layer (MBL) <span class="hlt">cloud</span> organization. The diurnal cycle of <span class="hlt">cloud</span>-physical properties and C(sub D) at Pt Reyes are consistent with previous work. The time series of C(sub D) can be used to <span class="hlt">identify</span> distinct mesoscale organization regimes within the Pt. Reyes observation period.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25032243','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25032243"><span>A study on strategic provisioning of <span class="hlt">cloud</span> computing services.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Whaiduzzaman, Md; Haque, Mohammad Nazmul; Rejaul Karim Chowdhury, Md; Gani, Abdullah</p> <p>2014-01-01</p> <p><span class="hlt">Cloud</span> computing is currently emerging as an ever-changing, growing paradigm that models "everything-as-a-service." Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the <span class="hlt">cloud</span>. The evolution in the adoption of <span class="hlt">cloud</span> computing is driven by clear and distinct promising features for both <span class="hlt">cloud</span> users and <span class="hlt">cloud</span> providers. However, the increasing number of <span class="hlt">cloud</span> providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the <span class="hlt">cloud</span> user and vitally important in <span class="hlt">cloud</span> computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of <span class="hlt">cloud</span> service provisioning is presented after the systematic review. Finally, future research directions and open research issues are <span class="hlt">identified</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4084594','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4084594"><span>A Study on Strategic Provisioning of <span class="hlt">Cloud</span> Computing Services</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Rejaul Karim Chowdhury, Md</p> <p>2014-01-01</p> <p><span class="hlt">Cloud</span> computing is currently emerging as an ever-changing, growing paradigm that models “everything-as-a-service.” Virtualised physical resources, infrastructure, and applications are supplied by service provisioning in the <span class="hlt">cloud</span>. The evolution in the adoption of <span class="hlt">cloud</span> computing is driven by clear and distinct promising features for both <span class="hlt">cloud</span> users and <span class="hlt">cloud</span> providers. However, the increasing number of <span class="hlt">cloud</span> providers and the variety of service offerings have made it difficult for the customers to choose the best services. By employing successful service provisioning, the essential services required by customers, such as agility and availability, pricing, security and trust, and user metrics can be guaranteed by service provisioning. Hence, continuous service provisioning that satisfies the user requirements is a mandatory feature for the <span class="hlt">cloud</span> user and vitally important in <span class="hlt">cloud</span> computing service offerings. Therefore, we aim to review the state-of-the-art service provisioning objectives, essential services, topologies, user requirements, necessary metrics, and pricing mechanisms. We synthesize and summarize different provision techniques, approaches, and models through a comprehensive literature review. A thematic taxonomy of <span class="hlt">cloud</span> service provisioning is presented after the systematic review. Finally, future research directions and open research issues are <span class="hlt">identified</span>. PMID:25032243</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010JGRD..115.0H16C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010JGRD..115.0H16C"><span>The GCM-Oriented CALIPSO <span class="hlt">Cloud</span> Product (CALIPSO-GOCCP)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chepfer, H.; Bony, S.; Winker, D.; Cesana, G.; Dufresne, J. L.; Minnis, P.; Stubenrauch, C. J.; Zeng, S.</p> <p>2010-01-01</p> <p>This article presents the GCM-Oriented <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) <span class="hlt">Cloud</span> Product (GOCCP) designed to evaluate the cloudiness simulated by general circulation models (GCMs). For this purpose, <span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization L1 data are processed following the same steps as in a lidar simulator used to diagnose the model <span class="hlt">cloud</span> cover that CALIPSO would observe from space if the satellite was flying above an atmosphere similar to that predicted by the GCM. Instantaneous profiles of the lidar scattering ratio (SR) are first computed at the highest horizontal resolution of the data but at the vertical resolution typical of current GCMs, and then <span class="hlt">cloud</span> diagnostics are inferred from these profiles: vertical distribution of <span class="hlt">cloud</span> fraction, horizontal distribution of low, middle, high, and total <span class="hlt">cloud</span> fractions, instantaneous SR profiles, and SR histograms as a function of height. Results are presented for different seasons (January-March 2007-2008 and June-August 2006-2008), and their sensitivity to parameters of the lidar simulator is investigated. It is shown that the choice of the vertical resolution and of the SR threshold value used for <span class="hlt">cloud</span> detection can modify the <span class="hlt">cloud</span> fraction by up to 0.20, particularly in the shallow cumulus regions. The tropical marine low-level <span class="hlt">cloud</span> fraction is larger during nighttime (by up to 0.15) than during daytime. The histograms of SR characterize the <span class="hlt">cloud</span> <span class="hlt">types</span> encountered in different regions. The GOCCP high-level <span class="hlt">cloud</span> amount is similar to that from the TIROS Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). The low-level and middle-level <span class="hlt">cloud</span> fractions are larger than those derived from passive remote sensing (International Satellite <span class="hlt">Cloud</span> Climatology Project, Moderate-Resolution Imaging Spectroradiometer-<span class="hlt">Cloud</span> and Earth Radiant Energy System Polarization and Directionality of Earth Reflectances, TOVS Path B, AIRS-Laboratoire de M</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/22348353-araucaria-project-distance-small-magellanic-cloud-from-late-type-eclipsing-binaries','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/22348353-araucaria-project-distance-small-magellanic-cloud-from-late-type-eclipsing-binaries"><span>The Araucaria project. The distance to the small Magellanic <span class="hlt">Cloud</span> from late-<span class="hlt">type</span> eclipsing binaries</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Graczyk, Dariusz; Pietrzyński, Grzegorz; Gieren, Wolfgang</p> <p>2014-01-01</p> <p>We present a distance determination to the Small Magellanic <span class="hlt">Cloud</span> (SMC) based on an analysis of four detached, long-period, late-<span class="hlt">type</span> eclipsing binaries discovered by the Optical Gravitational Lensing Experiment (OGLE) survey. The components of the binaries show negligible intrinsic variability. A consistent set of stellar parameters was derived with low statistical and systematic uncertainty. The absolute dimensions of the stars are calculated with a precision of better than 3%. The surface brightness-infrared color relation was used to derive the distance to each binary. The four systems clump around a distance modulus of (m – M) = 18.99 with a dispersionmore » of only 0.05 mag. Combining these results with the distance published by Graczyk et al. for the eclipsing binary OGLE SMC113.3 4007, we obtain a mean distance modulus to the SMC of 18.965 ± 0.025 (stat.) ± 0.048 (syst.) mag. This corresponds to a distance of 62.1 ± 1.9 kpc, where the error includes both uncertainties. Taking into account other recent published determinations of the SMC distance we calculated the distance modulus difference between the SMC and the Large Magellanic <span class="hlt">Cloud</span> equal to 0.458 ± 0.068 mag. Finally, we advocate μ{sub SMC} = 18.95 ± 0.07 as a new 'canonical' value of the distance modulus to this galaxy.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20140013289','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20140013289"><span>An Examination of the Nature of Global MODIS <span class="hlt">Cloud</span> Regimes</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin; Kato, Seiji; Huffman, George J.</p> <p>2014-01-01</p> <p>We introduce global <span class="hlt">cloud</span> regimes (previously also referred to as "weather states") derived from <span class="hlt">cloud</span> retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved <span class="hlt">cloud</span> top pressure and <span class="hlt">cloud</span> optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS <span class="hlt">cloud</span> regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of <span class="hlt">cloud</span> fraction and water content. When compositing radiative fluxes from the <span class="hlt">Clouds</span> and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the <span class="hlt">cloud</span> regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for <span class="hlt">cloud</span> system classification, clarify their association with standard <span class="hlt">cloud</span> <span class="hlt">types</span>, and underscore their distinct radiative and hydrological signatures.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.fs.usda.gov/treesearch/pubs/30060','TREESEARCH'); return false;" href="https://www.fs.usda.gov/treesearch/pubs/30060"><span>Creating <span class="hlt">cloud</span>-free Landsat ETM+ data sets in tropical landscapes: <span class="hlt">cloud</span> and <span class="hlt">cloud</span>-shadow removal</span></a></p> <p><a target="_blank" href="http://www.fs.usda.gov/treesearch/">Treesearch</a></p> <p>Sebastián Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez</p> <p>2007-01-01</p> <p><span class="hlt">Clouds</span> and <span class="hlt">cloud</span> shadows are common features of visible and infrared remotelysensed images collected from many parts of the world, particularly in humid and tropical regions. We have developed a simple and semiautomated method to mask <span class="hlt">clouds</span> and shadows in Landsat ETM+ imagery, and have developed a recent <span class="hlt">cloud</span>-free composite of multitemporal images for Puerto Rico and...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1913990A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1913990A"><span>Climatology of <span class="hlt">cloud</span> (radiative) parameters at two stations in Switzerland using hemispherical sky-cameras</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Aebi, Christine; Gröbner, Julian; Kämpfer, Niklaus; Vuilleumier, Laurent</p> <p>2017-04-01</p> <p>Our study analyses climatologies of <span class="hlt">cloud</span> fraction, <span class="hlt">cloud</span> <span class="hlt">type</span> and <span class="hlt">cloud</span> radiative effect depending on different parameters at two stations in Switzerland. The calculations have been performed for shortwave (0.3 - 3 μm) and longwave (3 - 100 μm) radiation separately. Information about fractional <span class="hlt">cloud</span> coverage and <span class="hlt">cloud</span> <span class="hlt">type</span> is automatically retrieved from images taken by visible all-sky cameras at the two stations Payerne (490 m asl) and Davos (1594 m asl) using a <span class="hlt">cloud</span> detection algorithm developed by PMOD/WRC (Wacker et al., 2015). Radiation data are retrieved from pyranometers and pyrgeometers, the <span class="hlt">cloud</span> base height from a ceilometer and IWV data from GPS measurements. Interestingly, Davos and Payerne show different trends in terms of <span class="hlt">cloud</span> coverage and <span class="hlt">cloud</span> fraction regarding seasonal variations. The absolute longwave <span class="hlt">cloud</span> radiative effect (LCE) for low-level <span class="hlt">clouds</span> and a <span class="hlt">cloud</span> coverage of 8 octas has a median value between 61 and 72 Wm-2. It is shown that the fractional <span class="hlt">cloud</span> coverage, the <span class="hlt">cloud</span> base height (CBH) and integrated water vapour (IWV) all have an influence on the magnitude of the LCE and will be illustrated with key examples. The relative values of the shortwave <span class="hlt">cloud</span> radiative effect (SCE) for low-level <span class="hlt">clouds</span> and a <span class="hlt">cloud</span> coverage of 8 octas are between -88 to -62 %. The SCE is also influenced by the latter parameters, but also if the sun is covered or not by <span class="hlt">clouds</span>. At both stations situations of shortwave radiation <span class="hlt">cloud</span> enhancements have been observed and will be discussed. Wacker S., J. Gröbner, C. Zysset, L. Diener, P. Tzoumanikas, A. Kazantzidis, L. Vuilleumier, R. Stöckli, S. Nyeki, and N. Kämpfer (2015) <span class="hlt">Cloud</span> observations in Switzerland using hemispherical sky cameras, J. Geophys. Res. Atmos, 120, 695-707.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ACP....12.3611W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ACP....12.3611W"><span>Banner <span class="hlt">clouds</span> observed at Mount Zugspitze</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wirth, V.; Kristen, M.; Leschner, M.; Reuder, J.; Schween, J. H.</p> <p>2012-04-01</p> <p>Systematic observations of banner <span class="hlt">clouds</span> at Mount Zugspitze in the Bavarian Alps are presented and discussed. One set of observations draws on daily time lapse movies, which were taken over several years at this mountain. <span class="hlt">Identifying</span> banner <span class="hlt">clouds</span> with the help of these movies and using simultaneous observations of standard variables at the summit of the mountain provides climatological information regarding the banner <span class="hlt">clouds</span>. In addition, a week-long measurement campaign with an entire suite of instruments was carried through yielding a comprehensive set of data for two specific banner <span class="hlt">cloud</span> events. The duration of banner <span class="hlt">cloud</span> events has a long-tailed distribution with a mean of about 40 min. The probability of occurrence has both a distinct diurnal and a distinct seasonal cycle, with a maximum in the afternoon and in the warm season, respectively. These cycles appear to correspond closely to analogous cycles of relative humidity, which maximize in the late afternoon and during the warm season. In addition, the dependence of banner <span class="hlt">cloud</span> occurrence on wind speed is weak. Both results suggest that moisture conditions are a key factor for banner <span class="hlt">cloud</span> occurrence. The distribution of wind direction during banner <span class="hlt">cloud</span> events slightly deviates from climatology, suggesting an influence from the specific Zugspitz orography. The two banner <span class="hlt">cloud</span> events during the campaign have a number of common features: the windward and the leeward side are characterized by different wind regimes, however, with mean upward flow on both sides; the leeward air is both moister and warmer than the windward air; the background atmosphere has an inversion just above the summit of Mt. Zugspitze; the lifting condensation level increases with altitude. The results are discussed, and it is argued that they are consistent with previous Large Eddy Simulations using idealized orography.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018SPIE10599E..0GH','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018SPIE10599E..0GH"><span>Combining the 3D model generated from point <span class="hlt">clouds</span> and thermography to <span class="hlt">identify</span> the defects presented on the facades of a building</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Huang, Yishuo; Chiang, Chih-Hung; Hsu, Keng-Tsang</p> <p>2018-03-01</p> <p>Defects presented on the facades of a building do have profound impacts on extending the life cycle of the building. How to <span class="hlt">identify</span> the defects is a crucial issue; destructive and non-destructive methods are usually employed to <span class="hlt">identify</span> the defects presented on a building. Destructive methods always cause the permanent damages for the examined objects; on the other hand, non-destructive testing (NDT) methods have been widely applied to detect those defects presented on exterior layers of a building. However, NDT methods cannot provide efficient and reliable information for <span class="hlt">identifying</span> the defects because of the huge examination areas. Infrared thermography is often applied to quantitative energy performance measurements for building envelopes. Defects on the exterior layer of buildings may be caused by several factors: ventilation losses, conduction losses, thermal bridging, defective services, moisture condensation, moisture ingress, and structure defects. Analyzing the collected thermal images can be quite difficult when the spatial variations of surface temperature are small. In this paper the authors employ image segmentation to cluster those pixels with similar surface temperatures such that the processed thermal images can be composed of limited groups. The surface temperature distribution in each segmented group is homogenous. In doing so, the regional boundaries of the segmented regions can be <span class="hlt">identified</span> and extracted. A terrestrial laser scanner (TLS) is widely used to collect the point <span class="hlt">clouds</span> of a building, and those point <span class="hlt">clouds</span> are applied to reconstruct the 3D model of the building. A mapping model is constructed such that the segmented thermal images can be projected onto the 2D image of the specified 3D building. In this paper, the administrative building in Chaoyang University campus is used as an example. The experimental results not only provide the defect information but also offer their corresponding spatial locations in the 3D model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JAMES...9..514P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JAMES...9..514P"><span>Redistribution of ice nuclei between <span class="hlt">cloud</span> and rain droplets: Parameterization and application to deep convective <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Paukert, M.; Hoose, C.; Simmel, M.</p> <p>2017-03-01</p> <p>In model studies of aerosol-dependent immersion freezing in <span class="hlt">clouds</span>, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one <span class="hlt">cloud</span> droplet. In contrast, the immersion freezing of larger drops—"rain"—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol <span class="hlt">types</span> and concentrations. This may lead to inconsistencies when aerosol effects on <span class="hlt">clouds</span> and precipitation shall be investigated, since raindrops consist of the <span class="hlt">cloud</span> droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. Here we introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation in raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective <span class="hlt">clouds</span>, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from <span class="hlt">cloud</span> droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100017248&hterms=classification&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dclassification','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100017248&hterms=classification&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dclassification"><span>Comparison of GOES <span class="hlt">Cloud</span> Classification Algorithms Employing Explicit and Implicit Physics</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bankert, Richard L.; Mitrescu, Cristian; Miller, Steven D.; Wade, Robert H.</p> <p>2009-01-01</p> <p><span class="hlt">Cloud-type</span> classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of the classifier output from two very different algorithms applied to Geostationary Operational Environmental Satellite (GOES) data over the course of one year. The first algorithm employs spectral channel thresholding and additional physically based tests. The second algorithm was developed through a supervised learning method with characteristic features of expertly labeled image samples used as training data for a 1-nearest-neighbor classification. The latter's ability to <span class="hlt">identify</span> classes is also based in physics, but those relationships are embedded implicitly within the algorithm. A pixel-to-pixel comparison analysis was done for hourly daytime scenes within a region in the northeastern Pacific Ocean. Considerable agreement was found in this analysis, with many of the mismatches or disagreements providing insight to the strengths and limitations of each classifier. Depending upon user needs, a rule-based or other postprocessing system that combines the output from the two algorithms could provide the most reliable <span class="hlt">cloud-type</span> classification.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110012471','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110012471"><span>Hyperspectrally-Resolved Surface Emissivity Derived Under Optically Thin <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, L. Larrabee; Yang, Ping</p> <p>2010-01-01</p> <p>Surface spectral emissivity derived from current and future satellites can and will reveal critical information about the Earth s ecosystem and land surface <span class="hlt">type</span> properties, which can be utilized as a means of long-term monitoring of global environment and climate change. Hyperspectrally-resolved surface emissivities are derived with an algorithm utilizes a combined fast radiative transfer model (RTM) with a molecular RTM and a <span class="hlt">cloud</span> RTM accounting for both atmospheric absorption and <span class="hlt">cloud</span> absorption/scattering. <span class="hlt">Clouds</span> are automatically detected and <span class="hlt">cloud</span> microphysical parameters are retrieved; and emissivity is retrieved under clear and optically thin <span class="hlt">cloud</span> conditions. This technique separates surface emissivity from skin temperature by representing the emissivity spectrum with eigenvectors derived from a laboratory measured emissivity database; in other words, using the constraint as a means for the emissivity to vary smoothly across atmospheric absorption lines. Here we present the emissivity derived under optically thin <span class="hlt">clouds</span> in comparison with that under clear conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045724&hterms=Electromagnetic+Pulse&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DElectromagnetic%2BPulse','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045724&hterms=Electromagnetic+Pulse&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3DElectromagnetic%2BPulse"><span>Microsecond-scale electric field pulses in <span class="hlt">cloud</span> lightning discharges</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Villanueva, Y.; Rakov, V. A.; Uman, M. A.; Brook, M.</p> <p>1994-01-01</p> <p>From wideband electric field records acquired using a 12-bit digitizing system with a 500-ns sampling interval, microsecond-scale pulses in different stages of <span class="hlt">cloud</span> flashes in Florida and New Mexico are analyzed. Pulse occurrence statistics and waveshape characteristics are presented. The larger pulses tend to occur early in the flash, confirming the results of Bils et al. (1988) and in contrast with the three-stage representation of <span class="hlt">cloud</span>-discharge electric fields suggested by Kitagawa and Brook (1960). Possible explanations for the discrepancy are discussed. The tendency for the larger pulses to occur early in the <span class="hlt">cloud</span> flash suggests that they are related to the initial in-<span class="hlt">cloud</span> channel formation processes and contradicts the common view found in the atmospheric radio-noise literature that the main sources of VLF/LF electromagnetic radiation in <span class="hlt">cloud</span> flashes are the K processes which occur in the final, or J <span class="hlt">type</span>, part of the <span class="hlt">cloud</span> discharge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAn.IV2..231R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAn.IV2..231R"><span>Fully Convolutional Networks for Ground Classification from LIDAR Point <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.</p> <p>2018-05-01</p> <p>Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point <span class="hlt">clouds</span> has also been recently studied. However, point <span class="hlt">clouds</span> need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point <span class="hlt">cloud</span> into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of <span class="hlt">type</span> I error, and 15.07 % of <span class="hlt">type</span> II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and <span class="hlt">type</span> I error (while <span class="hlt">type</span> II error is slightly higher). The method was also tested on a very high point density LIDAR point <span class="hlt">clouds</span> resulting in 4.02 % of total error, 2.15 % of <span class="hlt">type</span> I error and 6.14 % of <span class="hlt">type</span> II error.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_19");'>19</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li class="active"><span>21</span></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_21 --> <div id="page_22" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="421"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JASTP.172...24V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JASTP.172...24V"><span>Optical observations of electrical activity in <span class="hlt">cloud</span> discharges</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vayanganie, S. P. A.; Fernando, M.; Sonnadara, U.; Cooray, V.; Perera, C.</p> <p>2018-07-01</p> <p>Temporal variation of the luminosity of seven natural <span class="hlt">cloud-to-cloud</span> lightning channels were studied, and results were presented. They were recorded by using a high-speed video camera with the speed of 5000 fps (frames per second) and the pixel resolution of 512 × 512 in three locations in Sri Lanka in the tropics. Luminosity variation of the channel with time was obtained by analyzing the image sequences. Recorded video frames together with the luminosity variation were studied to understand the <span class="hlt">cloud</span> discharge process. Image analysis techniques also used to understand the characteristics of channels. <span class="hlt">Cloud</span> flashes show more luminosity variability than ground flashes. Most of the time it starts with a leader which do not have stepping process. Channel width and standard deviation of intensity variation across the channel for each <span class="hlt">cloud</span> flashes was obtained. Brightness variation across the channel shows a Gaussian distribution. The average time duration of the <span class="hlt">cloud</span> flashes which start with non stepped leader was 180.83 ms. <span class="hlt">Identified</span> characteristics are matched with the existing models to understand the process of <span class="hlt">cloud</span> flashes. The fact that <span class="hlt">cloud</span> discharges are not confined to a single process have been further confirmed from this study. The observations show that <span class="hlt">cloud</span> flash is a basic lightning discharge which transfers charge between two charge centers without using one specific mechanism.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012ApJ...753..173E','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012ApJ...753..173E"><span>A Rare Early-<span class="hlt">type</span> Star Revealed in the Wing of the Small Magellanic <span class="hlt">Cloud</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Evans, C. J.; Hainich, R.; Oskinova, L. M.; Gallagher, J. S., III; Chu, Y.-H.; Gruendl, R. A.; Hamann, W.-R.; Hénault-Brunet, V.; Todt, H.</p> <p>2012-07-01</p> <p>Sk 183 is the visually brightest star in the N90 nebula, a young star-forming region in the Wing of the Small Magellanic <span class="hlt">Cloud</span> (SMC). We present new optical spectroscopy from the Very Large Telescope which reveals Sk 183 to be one of the most massive O-<span class="hlt">type</span> stars in the SMC. Classified as an O3-<span class="hlt">type</span> dwarf on the basis of its nitrogen spectrum, the star also displays broadened He I absorption, which suggests a later <span class="hlt">type</span>. We propose that Sk 183 has a composite spectrum and that it is similar to another star in the SMC, MPG 324. This brings the number of rare O2- and O3-<span class="hlt">type</span> stars known in the whole of the SMC to a mere four. We estimate physical parameters for Sk 183 from analysis of its spectrum. For a single-star model, we estimate an effective temperature of 46 ± 2 kK, a low mass-loss rate of ~10-7 M ⊙ yr-1, and a spectroscopic mass of 46+9 -8 M ⊙ (for an adopted distance modulus of 18.7 mag to the young population in the SMC Wing). An illustrative binary model requires a slightly hotter temperature (~47.5 kK) for the primary component. In either scenario, Sk 183 is the earliest-<span class="hlt">type</span> star known in N90 and will therefore be the dominant source of hydrogen-ionizing photons. This suggests Sk 183 is the primary influence on the star formation along the inner edge of the nebula.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.8633A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.8633A"><span>Liquid water content variation with altitude in <span class="hlt">clouds</span> over Europe</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Andreea, Boscornea; Sabina, Stefan</p> <p>2013-04-01</p> <p><span class="hlt">Cloud</span> water content is one of the most fundamental measurements in <span class="hlt">cloud</span> physics. Knowledge of the vertical variability of <span class="hlt">cloud</span> microphysical characteristics is important for a variety of reasons. The profile of liquid water content (LWC) partially governs the radiative transfer for cloudy atmospheres, LWC profiles improves our understanding of processes acting to form and maintain <span class="hlt">cloud</span> systems and may lead to improvements in the representation of <span class="hlt">clouds</span> in numerical models. Presently, in situ airborne measurements provide the most accurate information about <span class="hlt">cloud</span> microphysical characteristics. This information can be used for verification of both numerical models and <span class="hlt">cloud</span> remote sensing techniques. The aim of this paper was to analyze the liquid water content (LWC) measurements in <span class="hlt">clouds</span>, in time of the aircraft flights. The aircraft and its platform ATMOSLAB - Airborne Laboratory for Environmental Atmospheric Research is property of the National Institute for Aerospace Research "Elie Carafoli" (INCAS), Bucharest, Romania. The airborne laboratory equipped for special research missions is based on a Hawker Beechcraft - King Air C90 GTx aircraft and is equipped with a sensors system CAPS - <span class="hlt">Cloud</span>, Aerosol and Precipitation Spectrometer (30 bins, 0.51-50 m). The processed and analyzed measurements are acquired during 4 flights from Romania (Bucharest, 44°25'57″N 26°06'14″E) to Germany (Berlin 52°30'2″N 13°23'56″E) above the same region of Europe. The flight path was starting from Bucharest to the western part of Romania above Hungary, Austria at a cruse altitude between 6000-8500 m, and after 5 hours reaching Berlin. In total we acquired data during approximately 20 flight hours and we presented the vertical and horizontal LWC variations for different <span class="hlt">cloud</span> <span class="hlt">types</span>. The LWC values are similar for each <span class="hlt">type</span> of <span class="hlt">cloud</span> to values from literature. The vertical LWC profiles in the atmosphere measured during takeoff and landing of the aircraft have shown their</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A43B2453D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A43B2453D"><span>Re-evaluating the <span class="hlt">Cloud</span> Lifetime Effect: Does Precipitation Suppression Always Lead to an Increased <span class="hlt">Cloud</span> Extent in Warm <span class="hlt">Clouds</span>?</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Douglas, A.; L'Ecuyer, T.</p> <p>2017-12-01</p> <p>Aerosol influences on <span class="hlt">cloud</span> lifetime remain a poorly understood pathway of aerosol-<span class="hlt">cloud</span>-radiation interaction with large margins of error according to the fifth IPCC report. Increases in <span class="hlt">cloud</span> lifetime are attributed to changes in <span class="hlt">cloud</span> extent due to the suppression of precipitation by increased aerosol concentrations. The dependence of changes in <span class="hlt">cloud</span> fraction and probability of precipitation on aerosol perturbations for controlled <span class="hlt">cloud</span> regimes will be investigated using A-Train measurements. <span class="hlt">Cloud</span>Sat, MODIS, and AMSR-E measurements from 2006 to 2010 are sorted into regimes established using stability to describe local meteorology, and relative humidity and liquid water path to describe <span class="hlt">cloud</span> morphology. Holding the thermodynamic and meteorological environments constant allows variations in precipitation and <span class="hlt">cloud</span> extent owing to regime-specific <span class="hlt">cloud</span> lifetime effects to be attributed to aerosol perturbations. The relationship between precipitation suppression, <span class="hlt">cloud</span> extent, and liquid water path will be analyzed. The <span class="hlt">cloud</span> lifetime effect will be constrained using regimes in the hopes of improving our understanding of precipitation-aerosol interactions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016JGRD..12111679W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016JGRD..12111679W"><span>Contrasting <span class="hlt">cloud</span> composition between coupled and decoupled marine boundary layer <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Zhen; Mora Ramirez, Marco; Dadashazar, Hossein; MacDonald, Alex B.; Crosbie, Ewan; Bates, Kelvin H.; Coggon, Matthew M.; Craven, Jill S.; Lynch, Peng; Campbell, James R.; Azadi Aghdam, Mojtaba; Woods, Roy K.; Jonsson, Haflidi; Flagan, Richard C.; Seinfeld, John H.; Sorooshian, Armin</p> <p>2016-10-01</p> <p>Marine stratocumulus <span class="hlt">clouds</span> often become decoupled from the vertical layer immediately above the ocean surface. This study contrasts <span class="hlt">cloud</span> chemical composition between coupled and decoupled marine stratocumulus <span class="hlt">clouds</span> for dissolved nonwater substances. <span class="hlt">Cloud</span> water and droplet residual particle composition were measured in <span class="hlt">clouds</span> off the California coast during three airborne experiments in July-August of separate years (Eastern Pacific Emitted Aerosol <span class="hlt">Cloud</span> Experiment 2011, Nucleation in California Experiment 2013, and Biological and Oceanic Atmospheric Study 2015). Decoupled <span class="hlt">clouds</span> exhibited significantly lower air-equivalent mass concentrations in both <span class="hlt">cloud</span> water and droplet residual particles, consistent with reduced <span class="hlt">cloud</span> droplet number concentration and subcloud aerosol (Dp > 100 nm) number concentration, owing to detachment from surface sources. Nonrefractory submicrometer aerosol measurements show that coupled <span class="hlt">clouds</span> exhibit higher sulfate mass fractions in droplet residual particles, owing to more abundant precursor emissions from the ocean and ships. Consequently, decoupled <span class="hlt">clouds</span> exhibited higher mass fractions of organics, nitrate, and ammonium in droplet residual particles, owing to effects of long-range transport from more distant sources. Sodium and chloride dominated in terms of air-equivalent concentration in <span class="hlt">cloud</span> water for coupled <span class="hlt">clouds</span>, and their mass fractions and concentrations exceeded those in decoupled <span class="hlt">clouds</span>. Conversely, with the exception of sea-salt constituents (e.g., Cl, Na, Mg, and K), <span class="hlt">cloud</span> water mass fractions of all species examined were higher in decoupled <span class="hlt">clouds</span> relative to coupled <span class="hlt">clouds</span>. Satellite and Navy Aerosol Analysis and Prediction System-based reanalysis data are compared with each other, and the airborne data to conclude that limitations in resolving boundary layer processes in a global model prevent it from accurately quantifying observed differences between coupled and decoupled <span class="hlt">cloud</span> composition.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009AIPC.1100..384H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009AIPC.1100..384H"><span>Retrieval of Ice <span class="hlt">Cloud</span> Properties Using Variable Phase Functions</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Heck, Patrick W.; Minnis, Patrick; Yang, Ping; Chang, Fu-Lung; Palikonda, Rabindra; Arduini, Robert F.; Sun-Mack, Sunny</p> <p>2009-03-01</p> <p>An enhancement to NASA Langley's Visible Infrared Solar-infrared Split-window Technique (VISST) is developed to <span class="hlt">identify</span> and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice <span class="hlt">cloud</span> phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, <span class="hlt">cloud</span> optical depths are reduced, hence, <span class="hlt">cloud</span> height is increased. <span class="hlt">Cloud</span> effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real-time retrievals at Langley.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/22948728','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22948728"><span>Genotyping in the <span class="hlt">cloud</span> with Crossbow.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Gurtowski, James; Schatz, Michael C; Langmead, Ben</p> <p>2012-09-01</p> <p>Crossbow is a scalable, portable, and automatic <span class="hlt">cloud</span> computing tool for <span class="hlt">identifying</span> SNPs from high-coverage, short-read resequencing data. It is built on Apache Hadoop, an implementation of the MapReduce software framework. Hadoop allows Crossbow to distribute read alignment and SNP calling subtasks over a cluster of commodity computers. Two robust tools, Bowtie and SOAPsnp, implement the fundamental alignment and variant calling operations respectively, and have demonstrated capabilities within Crossbow of analyzing approximately one billion short reads per hour on a commodity Hadoop cluster with 320 cores. Through protocol examples, this unit will demonstrate the use of Crossbow for <span class="hlt">identifying</span> variations in three different operating modes: on a Hadoop cluster, on a single computer, and on the Amazon Elastic MapReduce <span class="hlt">cloud</span> computing service.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AWUTP..58...64C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AWUTP..58...64C"><span><span class="hlt">Clouds</span> and the Near-Earth Environment: Possible Links</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Condurache-Bota, Simona; Voiculescu, Mirela; Dragomir, Carmelia</p> <p>2015-12-01</p> <p>Climate variability is a hot topic not only for scientists and policy-makers, but also for each and every one of us. The anthropogenic activities are considered to be responsible for most climate change, however there are large uncertainties about the magnitude of effects of solar variability and other extraterrestrial influences, such as galactic cosmic rays on terrestrial climate. <span class="hlt">Clouds</span> play an important role due to feedbacks of the radiation budget: variation of <span class="hlt">cloud</span> cover/composition affects climate, which, in turn, affects <span class="hlt">cloud</span> cover via atmospheric dynamics and sea temperature variations. <span class="hlt">Cloud</span> formation and evolution are still under scientific scrutiny, since their microphysics is still not understood. Besides atmospheric dynamics and other internal climatic parameters, extraterrestrial sources of <span class="hlt">cloud</span> cover variation are considered. One of these is the solar wind, whose effect on <span class="hlt">cloud</span> cover might be modulated by the global atmospheric electrical circuit. <span class="hlt">Clouds</span> height and composition, their seasonal variation and latitudinal distribution should be considered when trying to <span class="hlt">identify</span> possible mechanisms by which solar energy is transferred to <span class="hlt">clouds</span>. The influence of the solar wind on <span class="hlt">cloud</span> formation can be assessed also through the ap index - the geomagnetic storm index, which can be readily connected with interplanetary magnetic field, IMF structure. This paper proposes to assess the possible relationship between both <span class="hlt">cloud</span> cover and solar wind proxies, as the ap index, function of <span class="hlt">cloud</span> height and composition and also through seasonal studies. The data covers almost three solar cycles (1984-2009). Mechanisms are looked for by investigating observed trends or correlation at local/seasonal scale</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015SPIE.9446E..18G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015SPIE.9446E..18G"><span>Research on <span class="hlt">cloud</span>-based remote measurement and analysis system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gao, Zhiqiang; He, Lingsong; Su, Wei; Wang, Can; Zhang, Changfan</p> <p>2015-02-01</p> <p>The promising potential of <span class="hlt">cloud</span> computing and its convergence with technologies such as <span class="hlt">cloud</span> storage, <span class="hlt">cloud</span> push, mobile computing allows for creation and delivery of newer <span class="hlt">type</span> of <span class="hlt">cloud</span> service. Combined with the thought of <span class="hlt">cloud</span> computing, this paper presents a <span class="hlt">cloud</span>-based remote measurement and analysis system. This system mainly consists of three parts: signal acquisition client, web server deployed on the <span class="hlt">cloud</span> service, and remote client. This system is a special website developed using asp.net and Flex RIA technology, which solves the selective contradiction between two monitoring modes, B/S and C/S. This platform supplies customer condition monitoring and data analysis service by Internet, which was deployed on the <span class="hlt">cloud</span> server. Signal acquisition device is responsible for data (sensor data, audio, video, etc.) collection and pushes the monitoring data to the <span class="hlt">cloud</span> storage database regularly. Data acquisition equipment in this system is only conditioned with the function of data collection and network function such as smartphone and smart sensor. This system's scale can adjust dynamically according to the amount of applications and users, so it won't cause waste of resources. As a representative case study, we developed a prototype system based on Ali <span class="hlt">cloud</span> service using the rotor test rig as the research object. Experimental results demonstrate that the proposed system architecture is feasible.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950031822&hterms=qualitative+data+analysis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dqualitative%2Bdata%2Banalysis','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950031822&hterms=qualitative+data+analysis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dqualitative%2Bdata%2Banalysis"><span><span class="hlt">Cloud</span> properties inferred from 8-12 micron data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Strabala, Kathleen I.; Ackerman, Steven A.; Menzel, W. Paul</p> <p>1994-01-01</p> <p>A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting <span class="hlt">cloud</span> and <span class="hlt">cloud</span> properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate <span class="hlt">cloud</span>, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. <span class="hlt">Cloud</span> phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice <span class="hlt">cloud</span> shows a slope greater than 1 and water <span class="hlt">cloud</span> less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-<span class="hlt">cloud</span> and <span class="hlt">cloud</span>-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of <span class="hlt">cloud</span> property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the <span class="hlt">cloud</span> scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing <span class="hlt">cloud</span> and background scenes, from which a simple automated threshold technique was developed. <span class="hlt">Cloud</span> phase, clear-sky, and qualitative differences in <span class="hlt">cloud</span> emissivity and <span class="hlt">cloud</span> height were <span class="hlt">identified</span> on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further <span class="hlt">cloud</span> parameter clarification. The opportunities for global <span class="hlt">cloud</span> delineation with the Moderate-Resolution Imaging</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21638195','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21638195"><span>Obesogenic family <span class="hlt">types</span> <span class="hlt">identified</span> through latent profile analysis.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Martinson, Brian C; VazquezBenitez, Gabriela; Patnode, Carrie D; Hearst, Mary O; Sherwood, Nancy E; Parker, Emily D; Sirard, John; Pasch, Keryn E; Lytle, Leslie</p> <p>2011-10-01</p> <p>Obesity may cluster in families due to shared physical and social environments. This study aims to <span class="hlt">identify</span> family typologies of obesity risk based on family environments. Using 2007-2008 data from 706 parent/youth dyads in Minnesota, we applied latent profile analysis and general linear models to evaluate associations between family typologies and body mass index (BMI) of youth and parents. Three typologies described most families with 18.8% "Unenriched/Obesogenic," 16.9% "Risky Consumer," and 64.3% "Healthy Consumer/Salutogenic." After adjustment for demographic and socioeconomic factors, parent BMI and youth BMI Z-scores were higher in unenriched/obesogenic families (BMI difference = 2.7, p < 0.01 and BMI Z-score difference = 0.51, p < 0.01, respectively) relative to the healthy consumer/salutogenic typology. In contrast, parent BMI and youth BMI Z-scores were similar in the risky consumer families relative to those in healthy consumer/salutogenic <span class="hlt">type</span>. We can <span class="hlt">identify</span> family <span class="hlt">types</span> differing in obesity risks with implications for public health interventions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1394930','SCIGOV-DOEDE'); return false;" href="https://www.osti.gov/servlets/purl/1394930"><span>Extended Edited Synoptic <span class="hlt">Cloud</span> Reports from Ships and Land Stations Over the Globe, 1952-2009 (NDP-026C)</span></a></p> <p><a target="_blank" href="http://www.osti.gov/dataexplorer">DOE Data Explorer</a></p> <p>Hahn, C. J. [University of Arizona; Warren, S. G. [University of Washington; Eastman, R.</p> <p>1999-08-01</p> <p>This database contains surface synoptic weather reports for the entire globe, gathered from various available data sets. The reports were processed, edited, and rewritten to provide a single dataset of individual observations of <span class="hlt">clouds</span>, spanning the 57 years 1952-2008 for ship data and the 39 years 1971-2009 for land station data. In addition to the <span class="hlt">cloud</span> portion of the synoptic report, each edited report also includes the associated pressure, present weather, wind, air temperature, and dew point (and sea surface temperature over oceans). This data set is called the "Extended Edited <span class="hlt">Cloud</span> Report Archive" (EECRA). The EECRA is based solely on visual <span class="hlt">cloud</span> observations from weather stations, reported in the WMO synoptic code (WMO, 1974). Reports must contain <span class="hlt">cloud-type</span> information to be included in the archive. Past data sources include those from the Fleet Numerical Oceanographic Center (FNOC, 1971-1976) and the National Centers for Environmental Prediction (NCEP, 1977-1996). This update uses data from a new source, the 'Integrated Surface Database' (ISD, 1997-2009; Smith et al., 2011). Our past analyses of the EECRA <span class="hlt">identified</span> a subset of 5388 weather stations that were determined to produce reliable day and night observations of <span class="hlt">cloud</span> amount and <span class="hlt">type</span>. The update contains observations only from this subset of stations. Details concerning processing, previous problems, contents, and comments are available in the archive's original documentation . The EECRA contains about 81 million <span class="hlt">cloud</span> observations from ships and 380 million from land stations. The data files have been compressed using unix. Unix/linux users can "uncompress" or "gunzip" the files after downloading. If you're interested in the NDP-026C database, then you'll also want to explore its related data products, NDP-026D and NDP-026E.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/19434118','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/19434118"><span>Infrared <span class="hlt">cloud</span> imaging in support of Earth-space optical communication.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Nugent, Paul W; Shaw, Joseph A; Piazzolla, Sabino</p> <p>2009-05-11</p> <p>The increasing need for high data return from near-Earth and deep-space missions is driving a demand for the establishment of Earth-space optical communication links. These links will require a nearly obstruction-free path to the communication platform, so there is a need to measure spatial and temporal statistics of <span class="hlt">clouds</span> at potential ground-station sites. A technique is described that uses a ground-based thermal infrared imager to provide continuous day-night <span class="hlt">cloud</span> detection and classification according to the <span class="hlt">cloud</span> optical depth and potential communication channel attenuation. The benefit of retrieving <span class="hlt">cloud</span> optical depth and corresponding attenuation is illustrated through measurements that <span class="hlt">identify</span> cloudy times when optical communication may still be possible through thin <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EGUGA..17.3356S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EGUGA..17.3356S"><span>Mixed-phase altocumulus <span class="hlt">clouds</span> over Leipzig: Remote sensing measurements and spectral <span class="hlt">cloud</span> microphysics simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina</p> <p>2015-04-01</p> <p>The present work combines remote sensing observations and detailed microphysics <span class="hlt">cloud</span> modeling to investigate two altocumulus <span class="hlt">cloud</span> cases observed over Leipzig, Germany. A suite of remote sensing instruments was able to detect primary ice at rather warm temperatures of -6°C. For comparison, a second mixed phase case at about -25°C is introduced. To further look into the details of <span class="hlt">cloud</span> microphysical processes a simple dynamics model of the Asai-Kasahara <span class="hlt">type</span> is combined with detailed spectral microphysics forming the model system AK-SPECS. Temperature and humidity profiles are taken either from observation (radiosonde) or GDAS reanalysis. Vertical velocities are prescribed to force the dynamics as well as main <span class="hlt">cloud</span> features to be close to the observations. Subsequently, sensitivity studies with respect to dynamical as well as ice microphysical parameters are carried out with the aim to quantify the most important sensitivities for the cases investigated. For the cases selected, the liquid phase is mainly determined by the model dynamics (location and strength of vertical velocity) whereas the ice phase is much more sensitive to the microphysical parameters (ice nuclei (IN) number, ice particle shape). The choice of ice particle shape may induce large uncertainties which are in the same order as those for the temperature-dependent IN number distribution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008NJPh...10g5012F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008NJPh...10g5012F"><span>EDITORIAL: Focus on <span class="hlt">Cloud</span> Physics FOCUS ON <span class="hlt">CLOUD</span> PHYSICS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Falkovich, Gregory; Malinowski, Szymon P.</p> <p>2008-07-01</p> <p><span class="hlt">Cloud</span> physics has for a long time been an important segment of atmospheric science. It is common knowledge that <span class="hlt">clouds</span> are crucial for our understanding of weather and climate. <span class="hlt">Clouds</span> are also interesting by themselves (not to mention that they are beautiful). Complexity is hidden behind the common picture of these beautiful and interesting objects. The typical school textbook definition that a <span class="hlt">cloud</span> is 'a set of droplets or particles suspended in the atmosphere' is not adequate. <span class="hlt">Clouds</span> are complicated phenomena in which dynamics, turbulence, microphysics, thermodynamics and radiative transfer interact on a wide range of scales, from sub-micron to kilometres. Some of these interactions are subtle and others are more straightforward. Large and small-scale motions lead to activation of <span class="hlt">cloud</span> condensation nuclei, condensational growth and collisions; small changes in composition and concentration of atmospheric aerosol lead to significant differences in radiative properties of the <span class="hlt">clouds</span> and influence rainfall formation. It is justified to look at a <span class="hlt">cloud</span> as a composite, nonlinear system which involves many interactions and feedback. This system is actively linked into a web of atmospheric, oceanic and even cosmic interactions. Due to the complexity of the <span class="hlt">cloud</span> system, present-day descriptions of <span class="hlt">clouds</span> suffer from simplifications, inadequate parameterizations, and omissions. Sometimes the most fundamental physics hidden behind these simplifications and parameterizations is not known, and a wide scope of view can sometimes prevent a 'microscopic', deep insight into the detail. Only the expertise offered by scientists focused on particular elementary processes involved in this complicated pattern of interactions allows us to shape elements of the puzzle from which a general picture of <span class="hlt">clouds</span> can be created. To be useful, every element of the puzzle must be shaped precisely. This often creates problems in communication between the sciences responsible for shaping</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/225054','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/225054"><span>Edited synoptic <span class="hlt">cloud</span> reports from ships and land stations over the globe, 1982--1991</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Hahn, C.J.; Warren, S.G.; London, J.</p> <p>1996-02-01</p> <p>Surface synoptic weather reports for the entire globe for the 10-year period from December 1981 through November 1991 have been processed, edited, and rewritten to provide a data set designed for use in <span class="hlt">cloud</span> analyses. The information in these reports relating to <span class="hlt">clouds</span>, including the present weather information, was extracted and put through a series of quality control checks. Correctable inconsistencies within reports were edited for consistency, so that the ``edited <span class="hlt">cloud</span> report`` can be used for <span class="hlt">cloud</span> analysis. Cases of ``sky obscured`` were interpreted by reference to the present weather code as to whether they indicated fog, rain ormore » snow and were given appropriate <span class="hlt">cloud</span> <span class="hlt">type</span> designations. Nimbostratus <span class="hlt">clouds</span> were also given a special designation. Changes made to an original report are indicated in the edited report so that the original report can be reconstructed if desired. While low <span class="hlt">cloud</span> amount is normally given directly in the synoptic report, the edited <span class="hlt">cloud</span> report also includes the amounts, either directly reported or inferred, of middle and high <span class="hlt">clouds</span>, both the non-overlapped amounts and the ``actual`` amounts. Since illumination from the moon is important for the adequate detection of <span class="hlt">clouds</span> at night, both the relative lunar illuminance and the solar altitude are given; well as a parameter that indicates whether our recommended illuminance criterion was satisfied. This data set contains 124 million reports from land stations and 15 million reports from ships. Each report is 56 characters in length. The archive consists of 240 files, one file for each month of data for land and ocean separately. With this data set a user can develop a climatology for any particular <span class="hlt">cloud</span> <span class="hlt">type</span> or group of <span class="hlt">types</span>, for any geographical region and any spatial and temporal resolution desired.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1988ApL%26C..26..167I','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1988ApL%26C..26..167I"><span>Newly detected molecules in dense interstellar <span class="hlt">clouds</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Irvine, William M.; Avery, L. W.; Friberg, P.; Matthews, H. E.; Ziurys, L. M.</p> <p></p> <p>Several new interstellar molecules have been <span class="hlt">identified</span> including C2S, C3S, C5H, C6H and (probably) HC2CHO in the cold, dark <span class="hlt">cloud</span> TMC-1; and the discovery of the first interstellar phosphorus-containing molecule, PN, in the Orion "plateau" source. Further results include the observations of 13C3H2 and C3HD, and the first detection of HCOOH (formic acid) in a cold <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5191133','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5191133"><span>Classification of <span class="hlt">Clouds</span> in Satellite Imagery Using Adaptive Fuzzy Sparse Representation</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi</p> <p>2016-01-01</p> <p>Automatic <span class="hlt">cloud</span> detection and classification using satellite <span class="hlt">cloud</span> imagery have various meteorological applications such as weather forecasting and climate monitoring. <span class="hlt">Cloud</span> pattern analysis is one of the research hotspots recently. Since satellites sense the <span class="hlt">clouds</span> remotely from space, and different <span class="hlt">cloud</span> <span class="hlt">types</span> often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite <span class="hlt">cloud</span> imagery. Satellite observation is susceptible to noises, while traditional <span class="hlt">cloud</span> classification methods are sensitive to noises and outliers; it is hard for traditional <span class="hlt">cloud</span> classification methods to achieve reliable results. To deal with these problems, a satellite <span class="hlt">cloud</span> classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite <span class="hlt">cloud</span> imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for <span class="hlt">cloud</span> classification is proposed. Experiment results on FY-2G satellite <span class="hlt">cloud</span> image show that, the proposed method not only improves the accuracy of <span class="hlt">cloud</span> classification, but also has strong stability and adaptability with high computational efficiency. PMID:27999261</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27999261','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27999261"><span>Classification of <span class="hlt">Clouds</span> in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi</p> <p>2016-12-16</p> <p>Automatic <span class="hlt">cloud</span> detection and classification using satellite <span class="hlt">cloud</span> imagery have various meteorological applications such as weather forecasting and climate monitoring. <span class="hlt">Cloud</span> pattern analysis is one of the research hotspots recently. Since satellites sense the <span class="hlt">clouds</span> remotely from space, and different <span class="hlt">cloud</span> <span class="hlt">types</span> often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite <span class="hlt">cloud</span> imagery. Satellite observation is susceptible to noises, while traditional <span class="hlt">cloud</span> classification methods are sensitive to noises and outliers; it is hard for traditional <span class="hlt">cloud</span> classification methods to achieve reliable results. To deal with these problems, a satellite <span class="hlt">cloud</span> classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite <span class="hlt">cloud</span> imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for <span class="hlt">cloud</span> classification is proposed. Experiment results on FY-2G satellite <span class="hlt">cloud</span> image show that, the proposed method not only improves the accuracy of <span class="hlt">cloud</span> classification, but also has strong stability and adaptability with high computational efficiency.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..15.8486K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..15.8486K"><span>Aerosol-<span class="hlt">Cloud</span> Interactions During Puijo <span class="hlt">Cloud</span> Experiments - The effects of weather and local sources</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Komppula, Mika; Portin, Harri; Leskinen, Ari; Romakkaniemi, Sami; Brus, David; Neitola, Kimmo; Hyvärinen, Antti-Pekka; Kortelainen, Aki; Hao, Liqing; Miettinen, Pasi; Jaatinen, Antti; Ahmad, Irshad; Lihavainen, Heikki; Laaksonen, Ari; Lehtinen, Kari E. J.</p> <p>2013-04-01</p> <p>The Puijo measurement station has provided continuous data on aerosol-<span class="hlt">cloud</span> interactions since 2006. The station is located on top of the Puijo observation tower (306 m a.s.l, 224 m above the surrounding lake level) in Kuopio, Finland. The top of the tower is covered by <span class="hlt">cloud</span> about 15 % of the time, offering perfect conditions for studying aerosol-<span class="hlt">cloud</span> interactions. With a twin-inlet setup (total and interstitial inlets) we are able to separate the activated particles from the interstitial (non-activated) particles. The continuous twin-inlet measurements include aerosol size distribution, scattering and absorption. In addition <span class="hlt">cloud</span> droplet number and size distribution are measured continuously with weather parameters. During the campaigns the twin-inlet system was additionally equipped with aerosol mass spectrometer (AMS) and Single Particle Soot Photometer (SP-2). This way we were able to define the differences in chemical composition of the activated and non-activated particles. Potential <span class="hlt">cloud</span> condensation nuclei (CCN) in different supersaturations were measured with two CCN counters (CCNC). The other CCNC was operated with a Differential Mobility Analyzer (DMA) to obtain size selected CCN spectra. Other additional measurements included Hygroscopic Tandem Differential Mobility Analyzer (HTDMA) for particle hygroscopicity. Additionally the valuable vertical wind profiles (updraft velocities) are available from Halo Doppler lidar during the 2011 campaign. <span class="hlt">Cloud</span> properties (droplet number and effective radius) from MODIS instrument onboard Terra and Aqua satellites were retrieved and compared with the measured values. This work summarizes the two latest intensive campaigns, Puijo <span class="hlt">Cloud</span> Experiments (PuCE) 2010 & 2011. We study especially the effect of the local sources on the <span class="hlt">cloud</span> activation behaviour of the aerosol particles. The main local sources include a paper mill, a heating plant, traffic and residential areas. The sources can be categorized and <span class="hlt">identified</span></p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_20");'>20</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li class="active"><span>22</span></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_22 --> <div id="page_23" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="441"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/940809','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/940809"><span>A High Resolution Hydrometer Phase Classifier Based on Analysis of <span class="hlt">Cloud</span> Radar Doppler Spectra.</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Luke,E.; Kollias, P.</p> <p>2007-08-06</p> <p> excellent sensitivity that enables the detection of thin <span class="hlt">cloud</span> layers and their ability to penetrate several non-precipitating <span class="hlt">cloud</span> layers. However, in mixed-phase <span class="hlt">clouds</span> conditions, the observed Doppler moments are dominated by the highly reflecting ice crystals and thus can not be used to <span class="hlt">identify</span> the <span class="hlt">cloud</span> phase. This limits our ability to <span class="hlt">identify</span> the spatial distribution of <span class="hlt">cloud</span> phase and our ability to <span class="hlt">identify</span> the conditions under which mixed-phase <span class="hlt">clouds</span> form.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JPhCS.898i2010L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JPhCS.898i2010L"><span>Improved <span class="hlt">Cloud</span> resource allocation: how INDIGO-Data<span class="hlt">Cloud</span> is overcoming the current limitations in <span class="hlt">Cloud</span> schedulers</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lopez Garcia, Alvaro; Zangrando, Lisa; Sgaravatto, Massimo; Llorens, Vincent; Vallero, Sara; Zaccolo, Valentina; Bagnasco, Stefano; Taneja, Sonia; Dal Pra, Stefano; Salomoni, Davide; Donvito, Giacinto</p> <p>2017-10-01</p> <p>Performing efficient resource provisioning is a fundamental aspect for any resource provider. Local Resource Management Systems (LRMS) have been used in data centers for decades in order to obtain the best usage of the resources, providing their fair usage and partitioning for the users. In contrast, current <span class="hlt">cloud</span> schedulers are normally based on the immediate allocation of resources on a first-come, first-served basis, meaning that a request will fail if there are no resources (e.g. OpenStack) or it will be trivially queued ordered by entry time (e.g. OpenNebula). Moreover, these scheduling strategies are based on a static partitioning of the resources, meaning that existing quotas cannot be exceeded, even if there are idle resources allocated to other projects. This is a consequence of the fact that <span class="hlt">cloud</span> instances are not associated with a maximum execution time and leads to a situation where the resources are under-utilized. These facts have been <span class="hlt">identified</span> by the INDIGO-Data<span class="hlt">Cloud</span> project as being too simplistic for accommodating scientific workloads in an efficient way, leading to an underutilization of the resources, a non desirable situation in scientific data centers. In this work, we will present the work done in the scheduling area during the first year of the INDIGO project and the foreseen evolutions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015335','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015335"><span>The NASA Decadal Survey Aerosol, <span class="hlt">Cloud</span>, Ecosystems Mission</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>McClain, Charles R.; Bontempi, Paula; Maring, Hal</p> <p>2011-01-01</p> <p>In 2007, the National Academy of Sciences delivered a Decadal Survey (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond) for NASA, NOAA, and USGS, which is a prioritization of future satellite Earth observations. The recommendations included 15 missions (13 for NASA, two for NOAA), which were prioritized into three groups or tiers. One of the second tier missions is the Aerosol, <span class="hlt">Cloud</span>, (ocean) Ecosystems (ACE) mission, which focuses on climate forcing, <span class="hlt">cloud</span> and aerosol properties and interactions, and ocean ecology, carbon cycle science, and fluxes. The baseline instruments recommended for ACE are a <span class="hlt">cloud</span> radar, an aerosol/<span class="hlt">cloud</span> lidar, an aerosol/<span class="hlt">cloud</span> polarimeter, and an ocean radiometer. The instrumental heritage for these measurements are derived from the Cloudsat, CALIPSO, Glory, SeaWiFS and Aqua (MODIS) missions. In 2008, NASA HQ, lead by Hal Maring and Paula Bontempi, organized an interdisciplinary science working group to help formulate the ACE mission by refining the science objectives and approaches, <span class="hlt">identifying</span> measurement (satellite and field) and mission (e.g., orbit, data processing) requirements, technology requirements, and mission costs. Originally, the disciplines included the <span class="hlt">cloud</span>, aerosol, and ocean biogeochemistry communities. Subsequently, an ocean-aerosol interaction science working group was formed to ensure the mission addresses the broadest range of science questions possible given the baseline measurements, The ACE mission is a unique opportunity for ocean scientists to work closely with the aerosol and <span class="hlt">cloud</span> communities. The science working groups are collaborating on science objectives and are defining joint field studies and modeling activities. The presentation will outline the present status of the ACE mission, the science questions each discipline has defined, the measurement requirements <span class="hlt">identified</span> to date, the current ACE schedule, and future opportunities for broader community</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19780003577','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19780003577"><span>Some physical and thermodynamic properties of rocket exhaust <span class="hlt">clouds</span> measured with infrared scanners</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Gomberg, R. I.; Kantsios, A. G.; Rosensteel, F. J.</p> <p>1977-01-01</p> <p>Measurements using infrared scanners were made of the radiation from exhaust <span class="hlt">clouds</span> from liquid- and solid-propellant rocket boosters. Field measurements from four launches were discussed. These measurements were intended to explore the physical and thermodynamic properties of these exhaust <span class="hlt">clouds</span> during their formation and subsequent dispersion. Information was obtained concerning the initial <span class="hlt">cloud</span>'s buoyancy, the stabilized <span class="hlt">cloud</span>'s shape and trajectory, the <span class="hlt">cloud</span> volume as a function of time, and it's initial and stabilized temperatures. Differences in radiation intensities at various wavelengths from ambient and stabilized exhaust <span class="hlt">clouds</span> were investigated as a method of distinguishing between the two <span class="hlt">types</span> of <span class="hlt">clouds</span>. The infrared remote sensing method used can be used at night when visible range cameras are inadequate. Infrared scanning techniques developed in this project can be applied directly to natural <span class="hlt">clouds</span>, <span class="hlt">clouds</span> containing certain radionuclides, or <span class="hlt">clouds</span> of industrial pollution.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/978304','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/978304"><span>Diagnosing causes of <span class="hlt">cloud</span> parameterization deficiencies using ARM measurements over SGP site</span></a></p> <p><a target="_blank" href="http://www.osti.gov/search">DOE Office of Scientific and Technical Information (OSTI.GOV)</a></p> <p>Wu, W.; Liu, Y.; Betts, A. K.</p> <p>2010-03-15</p> <p>Decade-long continuous surface-based measurements at Great Southern Plains (SGP) collected by the US Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility are first used to evaluate the three major reanalyses (i.e., ERA-Interim, NCEP/NCAR Reanalysis I and NCEP/DOE Reanalysis II) to <span class="hlt">identify</span> model biases in simulating surface shortwave <span class="hlt">cloud</span> forcing and total <span class="hlt">cloud</span> fraction. The results show large systematic lower biases in the modeled surface shortwave <span class="hlt">cloud</span> forcing and <span class="hlt">cloud</span> fraction from all the three reanalysis datasets. Then we focus on diagnosing the causes of these model biases using the Active Remote Sensing of <span class="hlt">Clouds</span> (ARSCL) products (e.g., verticalmore » distribution of <span class="hlt">cloud</span> fraction, <span class="hlt">cloud</span>-base and <span class="hlt">cloud</span>-top heights, and <span class="hlt">cloud</span> optical depth) and meteorological measurements (temperature, humidity and stability). Efforts are made to couple <span class="hlt">cloud</span> properties with boundary processes in the diagnosis.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010068934','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010068934"><span><span class="hlt">Cloud</span> Modeling</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)</p> <p>2001-01-01</p> <p>Numerical <span class="hlt">cloud</span> models have been developed and applied extensively to study <span class="hlt">cloud</span>-scale and mesoscale processes during the past four decades. The distinctive aspect of these <span class="hlt">cloud</span> models is their ability to treat explicitly (or resolve) <span class="hlt">cloud</span>-scale dynamics. This requires the <span class="hlt">cloud</span> models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by <span class="hlt">clouds</span>, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The <span class="hlt">cloud</span> resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, <span class="hlt">cloud</span>-resolving processes poorly parameterized in climate models and numerical prediction models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20010013812','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20010013812"><span>Comparison of Cirrus <span class="hlt">Cloud</span> Models: A Project of the GEWEX <span class="hlt">Cloud</span> System Study (GCSS) Working Group on Cirrus <span class="hlt">Cloud</span> Systems</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Starr, David OC.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric; Khvorostyanov, Vitaly; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20010013812'); toggleEditAbsImage('author_20010013812_show'); toggleEditAbsImage('author_20010013812_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20010013812_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20010013812_hide"></p> <p>2000-01-01</p> <p>The GEWEX <span class="hlt">Cloud</span> System Study (GCSS, GEWEX is the Global Energy and Water Cycle Experiment) is a community activity aiming to promote development of improved <span class="hlt">cloud</span> parameterizations for application in the large-scale general circulation models (GCMs) used for climate research and for numerical weather prediction (Browning et al, 1994). The GCSS strategy is founded upon the use of <span class="hlt">cloud</span>-system models (CSMs). These are "process" models with sufficient spatial and temporal resolution to represent individual <span class="hlt">cloud</span> elements, but spanning a wide range of space and time scales to enable statistical analysis of simulated <span class="hlt">cloud</span> systems. GCSS also employs single-column versions of the parametric <span class="hlt">cloud</span> models (SCMs) used in GCMs. GCSS has working groups on boundary-layer <span class="hlt">clouds</span>, cirrus <span class="hlt">clouds</span>, extratropical layer <span class="hlt">cloud</span> systems, precipitating deep convective <span class="hlt">cloud</span> systems, and polar <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000070722','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000070722"><span>Comparison of Cirrus <span class="hlt">Cloud</span> Models: A Project of the GEWEX <span class="hlt">Cloud</span> System Study (GCSS) Working Group on Cirrus <span class="hlt">Cloud</span> Systems</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Starr, David O'C.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric</p> <p>2000-01-01</p> <p>The GEWEX <span class="hlt">Cloud</span> System Study (GCSS, GEWEX is the Global Energy and Water Cycle Experiment) is a community activity aiming to promote development of improved <span class="hlt">cloud</span> parameterizations for application in the large-scale general circulation models (GCMs) used for climate research and for numerical weather prediction. The GCSS strategy is founded upon the use of <span class="hlt">cloud</span>-system models (CSMs). These are "process" models with sufficient spatial and temporal resolution to represent individual <span class="hlt">cloud</span> elements, but spanning a wide range of space and time scales to enable statistical analysis of simulated <span class="hlt">cloud</span> systems. GCSS also employs single-column versions of the parametric <span class="hlt">cloud</span> models (SCMs) used in GCMs. GCSS has working groups on boundary-layer <span class="hlt">clouds</span>, cirrus <span class="hlt">clouds</span>, extratropical layer <span class="hlt">cloud</span> systems, precipitating deep convective <span class="hlt">cloud</span> systems, and polar <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015299','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015299"><span><span class="hlt">Identifying</span> Aerosol <span class="hlt">Type</span>/Mixture from Aerosol Absorption Properties Using AERONET</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Giles, D. M.; Holben, B. N.; Eck, T. F.; Sinyuk, A.; Dickerson, R. R.; Thompson, A. M.; Slutsker, I.; Li, Z.; Tripathi, S. N.; Singh, R. P.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20110015299'); toggleEditAbsImage('author_20110015299_show'); toggleEditAbsImage('author_20110015299_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20110015299_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20110015299_hide"></p> <p>2010-01-01</p> <p>Aerosols are generated in the atmosphere through anthropogenic and natural mechanisms. These sources have signatures in the aerosol optical and microphysical properties that can be used to <span class="hlt">identify</span> the aerosol <span class="hlt">type</span>/mixture. Spectral aerosol absorption information (absorption Angstrom exponent; AAE) used in conjunction with the particle size parameterization (extinction Angstrom exponent; EAE) can only <span class="hlt">identify</span> the dominant absorbing aerosol <span class="hlt">type</span> in the sample volume (e.g., black carbon vs. iron oxides in dust). This AAE/EAE relationship can be expanded to also <span class="hlt">identify</span> non-absorbing aerosol <span class="hlt">types</span>/mixtures by applying an absorption weighting. This new relationship provides improved aerosol <span class="hlt">type</span> distinction when the magnitude of absorption is not equal (e.g, black carbon vs. sulfates). The Aerosol Robotic Network (AERONET) data provide spectral aerosol optical depth and single scattering albedo - key parameters used to determine EAE and AAE. The proposed aerosol <span class="hlt">type</span>/mixture relationship is demonstrated using the long-term data archive acquired at AERONET sites within various source regions. The preliminary analysis has found that dust, sulfate, organic carbon, and black carbon aerosol <span class="hlt">types</span>/mixtures can be determined from this AAE/EAE relationship when applying the absorption weighting for each available wavelength (Le., 440, 675, 870nm). Large, non-spherical dust particles absorb in the shorter wavelengths and the application of 440nm wavelength absorption weighting produced the best particle <span class="hlt">type</span> definition. Sulfate particles scatter light efficiently and organic carbon particles are small near the source and aggregate over time to form larger less absorbing particles. Both sulfates and organic carbon showed generally better definition using the 870nm wavelength absorption weighting. Black carbon generation results from varying combustion rates from a number of sources including industrial processes and biomass burning. Cases with primarily black carbon showed</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931..632Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931..632Z"><span>Integrating <span class="hlt">Cloud</span>-Computing-Specific Model into Aircraft Design</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhimin, Tian; Qi, Lin; Guangwen, Yang</p> <p></p> <p><span class="hlt">Cloud</span> Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many <span class="hlt">types</span> of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of <span class="hlt">cloud</span> services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate <span class="hlt">cloud</span> computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110012679','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110012679"><span>Comparisons of Satellite-Deduced Overlapping <span class="hlt">Cloud</span> Properties and CALIPSO <span class="hlt">Cloud</span>Sat Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny</p> <p>2010-01-01</p> <p>Introduction to the overlapped <span class="hlt">cloud</span> properties derived from polar-orbiting (MODIS) and geostationary (GOES-12, -13, Meteosat-8, -9, etc.) meteorological satellites, which are produced at the NASA Langley Research Center (LaRC) <span class="hlt">cloud</span> research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped <span class="hlt">cloud</span> properties to the CALIPSO and the <span class="hlt">Cloud</span>Sat active sensing data. High <span class="hlt">clouds</span> and overlapped <span class="hlt">clouds</span> occur frequently as deduced by CALIPSO (44 & 25%), <span class="hlt">Cloud</span>Sat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped <span class="hlt">clouds</span> are deduced from CALIPSO, but much smaller fractions are from <span class="hlt">Cloud</span>Sat and MODIS. For overlapped <span class="hlt">clouds</span>, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (<span class="hlt">Cloud</span>Sat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (<span class="hlt">Cloud</span>Sat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer <span class="hlt">cloud</span> properties as deduced from the MODIS, CALIPSO and <span class="hlt">Cloud</span>Sat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped <span class="hlt">cloud</span> properties are needed and are under development.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFMNG33A0185C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMNG33A0185C"><span>Improving the Accuracy of <span class="hlt">Cloud</span> Detection Using Machine Learning</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Craddock, M. E.; Alliss, R. J.; Mason, M.</p> <p>2017-12-01</p> <p><span class="hlt">Cloud</span> detection from geostationary satellite imagery has long been accomplished through multi-spectral channel differencing in comparison to the Earth's surface. The distinction of clear/<span class="hlt">cloud</span> is then determined by comparing these differences to empirical thresholds. Using this methodology, the probability of detecting <span class="hlt">clouds</span> exceeds 90% but performance varies seasonally, regionally and temporally. The <span class="hlt">Cloud</span> Mask Generator (CMG) database developed under this effort, consists of 20 years of 4 km, 15minute clear/<span class="hlt">cloud</span> images based on GOES data over CONUS and Hawaii. The algorithms to determine cloudy pixels in the imagery are based on well-known multi-spectral techniques and defined thresholds. These thresholds were produced by manually studying thousands of images and thousands of man-hours to determine the success and failure of the algorithms to fine tune the thresholds. This study aims to investigate the potential of improving <span class="hlt">cloud</span> detection by using Random Forest (RF) ensemble classification. RF is the ideal methodology to employ for <span class="hlt">cloud</span> detection as it runs efficiently on large datasets, is robust to outliers and noise and is able to deal with highly correlated predictors, such as multi-spectral satellite imagery. The RF code was developed using Python in about 4 weeks. The region of focus selected was Hawaii and includes the use of visible and infrared imagery, topography and multi-spectral image products as predictors. The development of the <span class="hlt">cloud</span> detection technique is realized in three steps. First, tuning of the RF models is completed to <span class="hlt">identify</span> the optimal values of the number of trees and number of predictors to employ for both day and night scenes. Second, the RF models are trained using the optimal number of trees and a select number of random predictors <span class="hlt">identified</span> during the tuning phase. Lastly, the model is used to predict <span class="hlt">clouds</span> for an independent time period than used during training and compared to truth, the CMG <span class="hlt">cloud</span> mask. Initial results</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19780022772','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19780022772"><span>Rocket exhaust ground <span class="hlt">cloud</span>/atmospheric interactions</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hwang, B.; Gould, R. K.</p> <p>1978-01-01</p> <p>An attempt to <span class="hlt">identify</span> and minimize the uncertainties and potential inaccuracies of the NASA Multilayer Diffusion Model (MDM) is performed using data from selected Titan 3 launches. The study is based on detailed parametric calculations using the MDM code and a comparative study of several other diffusion models, the NASA measurements, and the MDM. The results are discussed and evaluated. In addition, the physical/chemical processes taking place during the rocket <span class="hlt">cloud</span> rise are analyzed. The exhaust properties and the deluge water effects are evaluated. A time-dependent model for two aerosol coagulations is developed and documented. Calculations using this model for dry deposition during <span class="hlt">cloud</span> rise are made. A simple model for calculating physical properties such as temperature and air mass entrainment during <span class="hlt">cloud</span> rise is also developed and incorporated with the aerosol model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=clouds&pg=5&id=EJ775121','ERIC'); return false;" href="https://eric.ed.gov/?q=clouds&pg=5&id=EJ775121"><span>Estimating <span class="hlt">Cloud</span> Cover</span></a></p> <p><a target="_blank" href="http://www.eric.ed.gov/ERICWebPortal/search/extended.jsp?_pageLabel=advanced">ERIC Educational Resources Information Center</a></p> <p>Moseley, Christine</p> <p>2007-01-01</p> <p>The purpose of this activity was to help students understand the percentage of <span class="hlt">cloud</span> cover and make more accurate <span class="hlt">cloud</span> cover observations. Students estimated the percentage of <span class="hlt">cloud</span> cover represented by simulated <span class="hlt">clouds</span> and assigned a <span class="hlt">cloud</span> cover classification to those simulations. (Contains 2 notes and 3 tables.)</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1917295G','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1917295G"><span>Investigating mixed phase <span class="hlt">clouds</span> using a synergy of ground based remote sensing measurements</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Gierens, Rosa; Kneifel, Stefan; Löhnert, Ulrich</p> <p>2017-04-01</p> <p> obtained from a Doppler wind lidar. Furthermore, the Cloudnet scheme (www.<span class="hlt">cloud</span>-net.org), that combines radar, lidar and microwave radiometer observations with a forecast model to provide a best estimate of <span class="hlt">cloud</span> properties, is used for <span class="hlt">identifying</span> mixed phase <span class="hlt">clouds</span>. The continuous measurements carried out at AWIPEV make it possible to characterize the macro- and micro- physical properties of mixed-phase <span class="hlt">clouds</span> on a long-term, statistical basis. The Arctic observations are compared to a 5-year observational data set from Jülich Observatory for <span class="hlt">Cloud</span> Evolution (JOYCE) in Western Germany. The occurrence of different <span class="hlt">types</span> of <span class="hlt">clouds</span> (with focus on mixed-phase and super-cooled <span class="hlt">clouds</span>), the distribution of ice and liquid within the <span class="hlt">clouds</span>, the turbulent environment as well as the temperatures where the different phases are occurring are investigated.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2002SPIE.4539...33P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2002SPIE.4539...33P"><span>Identification of <span class="hlt">cloud</span> fields by the nonparametric algorithm of pattern recognition from normalized video data recorded with the AVHRR instrument</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Protasov, Konstantin T.; Pushkareva, Tatyana Y.; Artamonov, Evgeny S.</p> <p>2002-02-01</p> <p>The problem of <span class="hlt">cloud</span> field recognition from the NOAA satellite data is urgent for solving not only meteorological problems but also for resource-ecological monitoring of the Earth's underlying surface associated with the detection of thunderstorm <span class="hlt">clouds</span>, estimation of the liquid water content of <span class="hlt">clouds</span> and the moisture of the soil, the degree of fire hazard, etc. To solve these problems, we used the AVHRR/NOAA video data that regularly displayed the situation in the territory. The complexity and extremely nonstationary character of problems to be solved call for the use of information of all spectral channels, mathematical apparatus of testing statistical hypotheses, and methods of pattern recognition and identification of the informative parameters. For a class of detection and pattern recognition problems, the average risk functional is a natural criterion for the quality and the information content of the synthesized decision rules. In this case, to solve efficiently the problem of <span class="hlt">identifying</span> <span class="hlt">cloud</span> field <span class="hlt">types</span>, the informative parameters must be determined by minimization of this functional. Since the conditional probability density functions, representing mathematical models of stochastic patterns, are unknown, the problem of nonparametric reconstruction of distributions from the leaning samples arises. To this end, we used nonparametric estimates of distributions with the modified Epanechnikov kernel. The unknown parameters of these distributions were determined by minimization of the risk functional, which for the learning sample was substituted by the empirical risk. After the conditional probability density functions had been reconstructed for the examined hypotheses, a cloudiness <span class="hlt">type</span> was <span class="hlt">identified</span> using the Bayes decision rule.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2003JGRD..108.4439Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003JGRD..108.4439Z"><span>Sensitivity of single column model simulations of Arctic springtime <span class="hlt">clouds</span> to different <span class="hlt">cloud</span> cover and mixed phase <span class="hlt">cloud</span> parameterizations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Junhua; Lohmann, Ulrike</p> <p>2003-08-01</p> <p>The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring <span class="hlt">cloud</span> properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five <span class="hlt">cloud</span> parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase <span class="hlt">cloud</span> parameterizations is studied. Using the original mixed phase <span class="hlt">cloud</span> parameterization of the model, the statistical <span class="hlt">cloud</span> schemes produce more <span class="hlt">cloud</span> cover, <span class="hlt">cloud</span> water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase <span class="hlt">cloud</span> parameterization from ECMWF decreases the initial saturation specific humidity threshold of <span class="hlt">cloud</span> formation. This improves the simulated <span class="hlt">cloud</span> cover in the explicit schemes and reduces the difference between the different <span class="hlt">cloud</span> schemes. On the other hand, because the ECMWF mixed phase <span class="hlt">cloud</span> scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23230157','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23230157"><span>RAPPORT: running scientific high-performance computing applications on the <span class="hlt">cloud</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Cohen, Jeremy; Filippis, Ioannis; Woodbridge, Mark; Bauer, Daniela; Hong, Neil Chue; Jackson, Mike; Butcher, Sarah; Colling, David; Darlington, John; Fuchs, Brian; Harvey, Matt</p> <p>2013-01-28</p> <p><span class="hlt">Cloud</span> computing infrastructure is now widely used in many domains, but one area where there has been more limited adoption is research computing, in particular for running scientific high-performance computing (HPC) software. The Robust Application Porting for HPC in the <span class="hlt">Cloud</span> (RAPPORT) project took advantage of existing links between computing researchers and application scientists in the fields of bioinformatics, high-energy physics (HEP) and digital humanities, to investigate running a set of scientific HPC applications from these domains on <span class="hlt">cloud</span> infrastructure. In this paper, we focus on the bioinformatics and HEP domains, describing the applications and target <span class="hlt">cloud</span> platforms. We conclude that, while there are many factors that need consideration, there is no fundamental impediment to the use of <span class="hlt">cloud</span> infrastructure for running many <span class="hlt">types</span> of HPC applications and, in some cases, there is potential for researchers to benefit significantly from the flexibility offered by <span class="hlt">cloud</span> platforms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110012138','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110012138"><span>Performance Analysis of <span class="hlt">Cloud</span> Computing Architectures Using Discrete Event Simulation</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Stocker, John C.; Golomb, Andrew M.</p> <p>2011-01-01</p> <p><span class="hlt">Cloud</span> computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of <span class="hlt">cloud</span> computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. <span class="hlt">Cloud</span> computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and <span class="hlt">cloud</span> computing architectures. The two part model framework characterizes both the demand using a probability distribution for each <span class="hlt">type</span> of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in <span class="hlt">cloud</span> computing architectures and findings on the appropriateness of <span class="hlt">cloud</span> computing in various applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150000783','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150000783"><span>CALIPSO Observations of Near-<span class="hlt">Cloud</span> Aerosol Properties as a Function of <span class="hlt">Cloud</span> Fraction</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yang, Weidong; Marshak, Alexander; Varnai, Tamas; Wood, Robert</p> <p>2015-01-01</p> <p>This paper uses spaceborne lidar data to study how near-<span class="hlt">cloud</span> aerosol statistics of attenuated backscatter depend on <span class="hlt">cloud</span> fraction. The results for a large region around the Azores show that: (1) far-from-<span class="hlt">cloud</span> aerosol statistics are dominated by samples from scenes with lower <span class="hlt">cloud</span> fractions, while near-<span class="hlt">cloud</span> aerosol statistics are dominated by samples from scenes with higher <span class="hlt">cloud</span> fractions; (2) near-<span class="hlt">cloud</span> enhancements of attenuated backscatter occur for any <span class="hlt">cloud</span> fraction but are most pronounced for higher <span class="hlt">cloud</span> fractions; (3) the difference in the enhancements for different <span class="hlt">cloud</span> fractions is most significant within 5km from <span class="hlt">clouds</span>; (4) near-<span class="hlt">cloud</span> enhancements can be well approximated by logarithmic functions of <span class="hlt">cloud</span> fraction and distance to <span class="hlt">clouds</span>. These findings demonstrate that if variability in <span class="hlt">cloud</span> fraction across the scenes used to composite aerosol statistics are not considered, a sampling artifact will affect these statistics calculated as a function of distance to <span class="hlt">clouds</span>. For the Azores-region dataset examined here, this artifact occurs mostly within 5 km from <span class="hlt">clouds</span>, and exaggerates the near-<span class="hlt">cloud</span> enhancements of lidar backscatter and color ratio by about 30. This shows that for accurate characterization of the changes in aerosol properties with distance to <span class="hlt">clouds</span>, it is important to account for the impact of changes in <span class="hlt">cloud</span> fraction.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li class="active"><span>23</span></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_23 --> <div id="page_24" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="461"> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4466495','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4466495"><span>A Framework and Improvements of the Korea <span class="hlt">Cloud</span> Services Certification System</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Jeon, Hangoo</p> <p>2015-01-01</p> <p><span class="hlt">Cloud</span> computing service is an evolving paradigm that affects a large part of the ICT industry and provides new opportunities for ICT service providers such as the deployment of new business models and the realization of economies of scale by increasing efficiency of resource utilization. However, despite benefits of <span class="hlt">cloud</span> services, there are some obstacles to adopt such as lack of assessing and comparing the service quality of <span class="hlt">cloud</span> services regarding availability, security, and reliability. In order to adopt the successful <span class="hlt">cloud</span> service and activate it, it is necessary to establish the <span class="hlt">cloud</span> service certification system to ensure service quality and performance of <span class="hlt">cloud</span> services. This paper proposes a framework and improvements of the Korea certification system of <span class="hlt">cloud</span> service. In order to develop it, the critical issues related to service quality, performance, and certification of <span class="hlt">cloud</span> service are <span class="hlt">identified</span> and the systematic framework for the certification system of <span class="hlt">cloud</span> services and service provider domains are developed. Improvements of the developed Korea certification system of <span class="hlt">cloud</span> services are also proposed. PMID:26125049</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26125049','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26125049"><span>A Framework and Improvements of the Korea <span class="hlt">Cloud</span> Services Certification System.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Jeon, Hangoo; Seo, Kwang-Kyu</p> <p>2015-01-01</p> <p><span class="hlt">Cloud</span> computing service is an evolving paradigm that affects a large part of the ICT industry and provides new opportunities for ICT service providers such as the deployment of new business models and the realization of economies of scale by increasing efficiency of resource utilization. However, despite benefits of <span class="hlt">cloud</span> services, there are some obstacles to adopt such as lack of assessing and comparing the service quality of <span class="hlt">cloud</span> services regarding availability, security, and reliability. In order to adopt the successful <span class="hlt">cloud</span> service and activate it, it is necessary to establish the <span class="hlt">cloud</span> service certification system to ensure service quality and performance of <span class="hlt">cloud</span> services. This paper proposes a framework and improvements of the Korea certification system of <span class="hlt">cloud</span> service. In order to develop it, the critical issues related to service quality, performance, and certification of <span class="hlt">cloud</span> service are <span class="hlt">identified</span> and the systematic framework for the certification system of <span class="hlt">cloud</span> services and service provider domains are developed. Improvements of the developed Korea certification system of <span class="hlt">cloud</span> services are also proposed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19940036369&hterms=dark+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddark%2Benergy','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19940036369&hterms=dark+energy&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Ddark%2Benergy"><span>The new Be-<span class="hlt">type</span> star HD 147196 in the Rho Ophiuchi dark <span class="hlt">cloud</span> region</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>The, P. S.; Perez, M. R.; De Winter, D.; Van Den Ancker, M. E.</p> <p>1993-01-01</p> <p>The newly discovered hot-emission line star, HD 147196 in the Rho Oph dark <span class="hlt">cloud</span> region was observed spectroscopically and photometrically and high and low resolution IUE spectra were obtained. The finding of Irvine (1990) that this relatively bright star show its H-alpha-line in emission is confirmed. Previous H-alpha-surveys of the Rho Oph star-forming region did not detect HD 147196 as an H-alpha-emission star, meaning that it must recently be very active and has perhaps transformed itself from a B-<span class="hlt">type</span> star at shell phase to a Be-phase. The Mg II h + k resonance lines are in absorption and they appear to be interstellar in nature, which means that either the abundance of Mg in the extended atmosphere of the star is low or that the shell is not extended enough to produce emission lines of Mg II. Photometric observations of this B8 V <span class="hlt">type</span> star do not show any variations during at least the years covered by our monitoring or any excess of NIR radiation in its spectral energy distribution up to the M-passband at 4.8 microns.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050212444','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050212444"><span>A Hierarchical Modeling Study of the Interactions Among Turbulence, <span class="hlt">Cloud</span> Microphysics, and Radiative Transfer in the Evolution of Cirrus <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Curry, Judith; Khvorostyanov, V. I.</p> <p>2005-01-01</p> <p>This project used a hierarchy of <span class="hlt">cloud</span> resolving models to address the following science issues of relevance to CRYSTAL-FACE: What ice crystal nucleation mechanisms are active in the different <span class="hlt">types</span> of cirrus <span class="hlt">clouds</span> in the Florida area and how do these different nucleation processes influence the evolution of the <span class="hlt">cloud</span> system and the upper tropospheric humidity? How does the feedback between supersaturation and nucleation impact the evolution of the <span class="hlt">cloud</span>? What is the relative importance of the large-scale vertical motion and the turbulent motions in the evolution of the crystal size spectra? How does the size spectra impact the life-cycle of the <span class="hlt">cloud</span>, stratospheric dehydration, and <span class="hlt">cloud</span> radiative forcing? What is the nature of the turbulence and waves in the upper troposphere generated by precipitating deep convective <span class="hlt">cloud</span> systems? How do cirrus microphysical and optical properties vary with the small-scale dynamics? How do turbulence and waves in the upper troposphere influence the cross-tropopause mixing and stratospheric and upper tropospheric humidity? The models used in this study were: 2-D hydrostatic model with explicit microphysics that can account for 30 size bins for both the droplet and crystal size spectra. Notably, a new ice crystal nucleation scheme has been incorporated into the model. Parcel model with explicit microphysics, for developing and evaluating microphysical parameterizations. Single column model for testing bulk microphysics parameterizations</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ThApC.tmp..509V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ThApC.tmp..509V"><span>Atlantic Multidecadal Oscillation footprint on global high <span class="hlt">cloud</span> cover</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Vaideanu, Petru; Dima, Mihai; Voiculescu, Mirela</p> <p>2017-12-01</p> <p>Due to the complexity of the physical processes responsible for <span class="hlt">cloud</span> formation and to the relatively short satellite database of continuous data records, <span class="hlt">cloud</span> behavior in a warming climate remains uncertain. <span class="hlt">Identifying</span> physical links between climate modes and <span class="hlt">clouds</span> would contribute not only to a better understanding of the physical processes governing their formation and dynamics, but also to an improved representation of the <span class="hlt">clouds</span> in climate models. Here, we <span class="hlt">identify</span> the global footprint of the Atlantic Multidecadal Oscillation (AMO) on high <span class="hlt">cloud</span> cover, with focus on the tropical and North Atlantic, tropical Pacific and on the circum-Antarctic sector. In the tropical band, the sea surface temperature (SST) and high <span class="hlt">cloud</span> cover (HCC) anomalies are positively correlated, indicating a dominant role played by convection in mediating the influence of the AMO-related SST anomalies on the HCC field. The negative SST-HCC correlation observed in North Atlantic could be explained by the reduced meridional temperature gradient induced by the AMO positive phase, which would be reflected in less storms and negative HCC anomalies. A similar negative SST-HCC correlation is observed around Antarctica. The corresponding negative correlation around Antarctica could be generated dynamically, as a response to the intensified upward motion in the Ferrel cell. Despite the inherent imperfection of the observed and reanalysis data sets, the AMO footprint on HCC is found to be robust to the choice of dataset, statistical method, and specific time period considered.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3947867','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3947867"><span><span class="hlt">Cloud</span> Service Selection Using Multicriteria Decision Analysis</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Israat Tanzeena</p> <p>2014-01-01</p> <p><span class="hlt">Cloud</span> computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to <span class="hlt">cloud</span> customers in a pay-as-you-go, anytime, anywhere manner. <span class="hlt">Cloud</span> services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The <span class="hlt">cloud</span> customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We <span class="hlt">identify</span> and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in <span class="hlt">cloud</span> computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the <span class="hlt">cloud</span> computing service selections in different scenarios. PMID:24696645</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24696645','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24696645"><span><span class="hlt">Cloud</span> service selection using multicriteria decision analysis.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Whaiduzzaman, Md; Gani, Abdullah; Anuar, Nor Badrul; Shiraz, Muhammad; Haque, Mohammad Nazmul; Haque, Israat Tanzeena</p> <p>2014-01-01</p> <p><span class="hlt">Cloud</span> computing (CC) has recently been receiving tremendous attention from the IT industry and academic researchers. CC leverages its unique services to <span class="hlt">cloud</span> customers in a pay-as-you-go, anytime, anywhere manner. <span class="hlt">Cloud</span> services provide dynamically scalable services through the Internet on demand. Therefore, service provisioning plays a key role in CC. The <span class="hlt">cloud</span> customer must be able to select appropriate services according to his or her needs. Several approaches have been proposed to solve the service selection problem, including multicriteria decision analysis (MCDA). MCDA enables the user to choose from among a number of available choices. In this paper, we analyze the application of MCDA to service selection in CC. We <span class="hlt">identify</span> and synthesize several MCDA techniques and provide a comprehensive analysis of this technology for general readers. In addition, we present a taxonomy derived from a survey of the current literature. Finally, we highlight several state-of-the-art practical aspects of MCDA implementation in <span class="hlt">cloud</span> computing service selection. The contributions of this study are four-fold: (a) focusing on the state-of-the-art MCDA techniques, (b) highlighting the comparative analysis and suitability of several MCDA methods, (c) presenting a taxonomy through extensive literature review, and (d) analyzing and summarizing the <span class="hlt">cloud</span> computing service selections in different scenarios.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8405E..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8405E..06S"><span>Military <span class="hlt">clouds</span>: utilization of <span class="hlt">cloud</span> computing systems at the battlefield</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Süleyman, Sarıkürk; Volkan, Karaca; İbrahim, Kocaman; Ahmet, Şirzai</p> <p>2012-05-01</p> <p><span class="hlt">Cloud</span> computing is known as a novel information technology (IT) concept, which involves facilitated and rapid access to networks, servers, data saving media, applications and services via Internet with minimum hardware requirements. Use of information systems and technologies at the battlefield is not new. Information superiority is a force multiplier and is crucial to mission success. Recent advances in information systems and technologies provide new means to decision makers and users in order to gain information superiority. These developments in information technologies lead to a new term, which is known as network centric capability. Similar to network centric capable systems, <span class="hlt">cloud</span> computing systems are operational today. In the near future extensive use of military <span class="hlt">clouds</span> at the battlefield is predicted. Integrating <span class="hlt">cloud</span> computing logic to network centric applications will increase the flexibility, cost-effectiveness, efficiency and accessibility of network-centric capabilities. In this paper, <span class="hlt">cloud</span> computing and network centric capability concepts are defined. Some commercial <span class="hlt">cloud</span> computing products and applications are mentioned. Network centric capable applications are covered. <span class="hlt">Cloud</span> computing supported battlefield applications are analyzed. The effects of <span class="hlt">cloud</span> computing systems on network centric capability and on the information domain in future warfare are discussed. Battlefield opportunities and novelties which might be introduced to network centric capability by <span class="hlt">cloud</span> computing systems are researched. The role of military <span class="hlt">clouds</span> in future warfare is proposed in this paper. It was concluded that military <span class="hlt">clouds</span> will be indispensible components of the future battlefield. Military <span class="hlt">clouds</span> have the potential of improving network centric capabilities, increasing situational awareness at the battlefield and facilitating the settlement of information superiority.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1994JGR....9914461L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1994JGR....9914461L"><span>Clustering, randomness, and regularity in <span class="hlt">cloud</span> fields. 4. Stratocumulus <span class="hlt">cloud</span> fields</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.</p> <p>1994-07-01</p> <p>To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing <span class="hlt">cloud</span> size; the clusters themselves consist of a few <span class="hlt">clouds</span> (less than 10), occupy a small percentage of the <span class="hlt">cloud</span> field area (less than 5%), contain between 20% and 60% of the <span class="hlt">cloud</span> field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus <span class="hlt">cloud</span> fields. For instance, stratocumulus clusters contain more <span class="hlt">clouds</span> per cluster, occupy a larger percentage of the total area, and have a larger percentage of <span class="hlt">clouds</span> participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) <span class="hlt">clouds</span> in stratocumulus and cumulus <span class="hlt">cloud</span> fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-<span class="hlt">cloud</span> cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus <span class="hlt">cloud</span> distributions. A hypothesis regarding the underlying physical mechanisms responsible for <span class="hlt">cloud</span> clustering is presented. It is suggested that <span class="hlt">cloud</span> clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the <span class="hlt">cloud</span> field. As the size of the <span class="hlt">cloud</span> surpasses the scale of the triggering region, the clustering signal weakens and the larger <span class="hlt">cloud</span> locations become more random.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045731&hterms=Clustering&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DClustering','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045731&hterms=Clustering&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DClustering"><span>Clustering, randomness, and regularity in <span class="hlt">cloud</span> fields. 4: Stratocumulus <span class="hlt">cloud</span> fields</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.</p> <p>1994-01-01</p> <p>To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing <span class="hlt">cloud</span> size; the clusters themselves consist of a few <span class="hlt">clouds</span> (less than 10), occupy a small percentage of the <span class="hlt">cloud</span> field area (less than 5%), contain between 20% and 60% of the <span class="hlt">cloud</span> field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus <span class="hlt">cloud</span> fields. For instance, stratocumulus clusters contain more <span class="hlt">clouds</span> per cluster, occupy a larger percentage of the total area, and have a larger percentage of <span class="hlt">clouds</span> participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) <span class="hlt">clouds</span> in stratocumulus and cumulus <span class="hlt">cloud</span> fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-<span class="hlt">cloud</span> cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus <span class="hlt">cloud</span> distributions. A hypothesis regarding the underlying physical mechanisms responsible for <span class="hlt">cloud</span> clustering is presented. It is suggested that <span class="hlt">cloud</span> clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the <span class="hlt">cloud</span> field. As the size of the <span class="hlt">cloud</span> surpasses the scale of the triggering region, the clustering signal weakens and the larger <span class="hlt">cloud</span> locations become more random.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ClDy..tmp..353T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ClDy..tmp..353T"><span>Evaluating rainfall errors in global climate models through <span class="hlt">cloud</span> regimes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho</p> <p>2017-07-01</p> <p>Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, <span class="hlt">clouds</span> are precursors to rainfall and the distribution of <span class="hlt">clouds</span> is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the <span class="hlt">cloud</span> regime concept. In observations, these <span class="hlt">cloud</span> regimes are derived from cluster analysis of joint-histograms of <span class="hlt">cloud</span> properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable <span class="hlt">cloud</span> regimes can be defined in models. This enables us to contrast the rainfall distributions of <span class="hlt">cloud</span> regimes in 11 CMIP5 models to observations and decompose the rainfall errors by <span class="hlt">cloud</span> regimes. Many models underestimate the rainfall from the organized convective <span class="hlt">cloud</span> regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this <span class="hlt">cloud</span> regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the <span class="hlt">cloud</span> regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different <span class="hlt">cloud</span> <span class="hlt">types</span> and regions. The fact that a good representation of <span class="hlt">clouds</span> does not lead to appreciable improvement in rainfall suggests a certain disconnect in the <span class="hlt">cloud</span>-precipitation processes of global climate models.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21358005','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21358005"><span>Superposition and alignment of labeled point <span class="hlt">clouds</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Fober, Thomas; Glinca, Serghei; Klebe, Gerhard; Hüllermeier, Eyke</p> <p>2011-01-01</p> <p>Geometric objects are often represented approximately in terms of a finite set of points in three-dimensional euclidean space. In this paper, we extend this representation to what we call labeled point <span class="hlt">clouds</span>. A labeled point <span class="hlt">cloud</span> is a finite set of points, where each point is not only associated with a position in three-dimensional space, but also with a discrete class label that represents a specific property. This <span class="hlt">type</span> of model is especially suitable for modeling biomolecules such as proteins and protein binding sites, where a label may represent an atom <span class="hlt">type</span> or a physico-chemical property. Proceeding from this representation, we address the question of how to compare two labeled points <span class="hlt">clouds</span> in terms of their similarity. Using fuzzy modeling techniques, we develop a suitable similarity measure as well as an efficient evolutionary algorithm to compute it. Moreover, we consider the problem of establishing an alignment of the structures in the sense of a one-to-one correspondence between their basic constituents. From a biological point of view, alignments of this kind are of great interest, since mutually corresponding molecular constituents offer important information about evolution and heredity, and can also serve as a means to explain a degree of similarity. In this paper, we therefore develop a method for computing pairwise or multiple alignments of labeled point <span class="hlt">clouds</span>. To this end, we proceed from an optimal superposition of the corresponding point <span class="hlt">clouds</span> and construct an alignment which is as much as possible in agreement with the neighborhood structure established by this superposition. We apply our methods to the structural analysis of protein binding sites.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21210983','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21210983"><span>Galaxy <span class="hlt">Cloud</span>Man: delivering <span class="hlt">cloud</span> compute clusters.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James</p> <p>2010-12-21</p> <p>Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is "<span class="hlt">cloud</span> computing", which, in principle, offers on demand access to flexible computational infrastructure. However, <span class="hlt">cloud</span> computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a <span class="hlt">cloud</span> resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 <span class="hlt">cloud</span> infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of <span class="hlt">cloud</span> resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available <span class="hlt">cloud</span> system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 <span class="hlt">cloud</span> is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120009892','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120009892"><span>Comparative Study of Aerosol and <span class="hlt">Cloud</span> Detected by CALIPSO and OMI</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Chen, Zhong; Torres, Omar; McCormick, M. Patrick; Smith, William; Ahn, Changwoo</p> <p>2012-01-01</p> <p>The Ozone Monitoring Instrument (OMI) on the Aura Satellite detects the presence of desert dust and smoke particles (also known as aerosols) in terms of a parameter known as the UV Aerosol Index (UV AI). The <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission measures the vertical distribution of aerosols and <span class="hlt">clouds</span>. Aerosols and <span class="hlt">clouds</span> play important roles in the atmosphere and climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a very important task. This paper presents a comparative analysis of the CALIPSO Version 2 Vertical Feature Mask (VFM) product with the (OMI) UV Aerosol Index (UV AI) and reflectivity datasets for a full year of 2007. The comparison is done at regional and global scales. Based on CALIPSO arid OMI observations, the vertical and horizontal extent of <span class="hlt">clouds</span> and aerosols are determined and the effects of aerosol <span class="hlt">type</span> selection, load, <span class="hlt">cloud</span> fraction on aerosol identification are discussed. It was found that the spatial-temporal correlation found between CALIPSO and OMI observations, is strongly dependent on aerosol <span class="hlt">types</span> and <span class="hlt">cloud</span> contamination. CALIPSO is more sensitivity to <span class="hlt">cloud</span> and often misidentifies desert dust aerosols as <span class="hlt">cloud</span>, while some small scale aerosol layers as well as some pollution aerosols are unidentified by OMI UV AI. Large differences in aerosol distribution patterns between CALIPSO and OMI are observed, especially for the smoke and pollution aerosol dominated areas. In addition, the results found a significant correlation between CALIPSO lidar 1064 nm backscatter and the OMI UV AI over the study regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21895057','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21895057"><span>Sound, infrasound, and sonic boom absorption by atmospheric <span class="hlt">clouds</span>.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Baudoin, Michaël; Coulouvrat, François; Thomas, Jean-Louis</p> <p>2011-09-01</p> <p>This study quantifies the influence of atmospheric <span class="hlt">clouds</span> on propagation of sound and infrasound, based on an existing model [Gubaidulin and Nigmatulin, Int. J. Multiphase Flow 26, 207-228 (2000)]. <span class="hlt">Clouds</span> are considered as a dilute and polydisperse suspension of liquid water droplets within a mixture of dry air and water vapor, both considered as perfect gases. The model is limited to low and medium altitude <span class="hlt">clouds</span>, with a small ice content. Four physical mechanisms are taken into account: viscoinertial effects, heat transfer, water phase changes (evaporation and condensation), and vapor diffusion. Physical properties of atmospheric <span class="hlt">clouds</span> (altitude, thickness, water content and droplet size distribution) are collected, along with values of the thermodynamical coefficients. Different <span class="hlt">types</span> of <span class="hlt">clouds</span> have been selected. Quantitative evaluation shows that, for low audible and infrasound frequencies, absorption within <span class="hlt">clouds</span> is several orders of magnitude larger than classical absorption. The importance of phase changes and vapor diffusion is outlined. Finally, numerical simulations for nonlinear propagation of sonic booms indicate that, for thick <span class="hlt">clouds</span>, attenuation can lead to a very large decay of the boom at the ground level. © 2011 Acoustical Society of America</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2001nrao.pres...11.','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2001nrao.pres...11."><span>Adolescent Interstellar <span class="hlt">Cloud</span> Poised to Make Star-forming Debut</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p></p> <p>2001-06-01</p> <p> respects. First, it was uncharacteristically massive, about 500 light- years across and containing nearly 100,000 times the mass of the sun in atomic hydrogen. The gas in <span class="hlt">clouds</span> this large and massive has typically undergone the transition to the molecular phase, and has begun making stars. The size and mass of this <span class="hlt">cloud</span> indicate that it is gravitationally bound, which means that it should be collapsing and forming new stars. "When you find a <span class="hlt">cloud</span> that is as massive as the one we detected, and one that is gravitationally bound as this structure indicates, then you would expect to see areas of star formation," said Lockman. The scientists were able to <span class="hlt">identify</span> a few indicators of star formation, but not at the rate that one would expect. "We think we have caught something in a special state." Lockman said, "It could be one of the missing links in the cycle of star formation." The core of the <span class="hlt">cloud</span> also gives off radio signals at 1720 MHz from the molecule OH in an unusual state of excitation. Since other astronomers have detected similar signals throughout the Galactic plane, the researchers believe that these emissions may be an indication that this previously undetected <span class="hlt">type</span> of <span class="hlt">cloud</span> may turn out to be fairly common. "We suspect that this <span class="hlt">cloud</span> may be the first example of an object that may be fairly common in the inner Galactic plane," said Lockman, "but has not been recognized. That is, a <span class="hlt">cloud</span> that is observed while entering a spiral shock and is in the transition between atomic to molecular hydrogen." The NRAO 140-Foot Telescope The scientists caution, however, that additional research is needed to confirm their speculations. "The presence of anomalous OH through the Galactic plane does suggest that other <span class="hlt">clouds</span> of this nature can be detected," said Lockman, "and it would be particularly valuable if a similar <span class="hlt">cloud</span> could be detected entering the 'spiral shock' on the opposite side of the Galactic center." The patterns of velocities of atomic and molecular gas should</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ISPAr42.3.1079L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ISPAr42.3.1079L"><span>Thin <span class="hlt">Cloud</span> Detection Method by Linear Combination Model of <span class="hlt">Cloud</span> Image</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.</p> <p>2018-04-01</p> <p>The existing <span class="hlt">cloud</span> detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into <span class="hlt">cloud</span> or other things. But when the <span class="hlt">cloud</span> is thin and small, these methods will be inaccurate. In this paper, a linear combination model of <span class="hlt">cloud</span> images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the <span class="hlt">cloud</span> detection result can become more accurate. Firstly, the automatic <span class="hlt">cloud</span> detection program in this paper uses the linear combination model to split the <span class="hlt">cloud</span> information and surface information in the transparent <span class="hlt">cloud</span> images, then uses different image features to recognize the <span class="hlt">cloud</span> parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a <span class="hlt">cloud</span> classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a <span class="hlt">cloud</span> detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed <span class="hlt">cloud</span> detection program in this paper has high accuracy and fast calculation speed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19780040454&hterms=attention+size&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dattention%2Bsize','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19780040454&hterms=attention+size&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dattention%2Bsize"><span>Effects of <span class="hlt">cloud</span> size and <span class="hlt">cloud</span> particles on satellite-observed reflected brightness</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Reynolds, D. W.; Mckee, T. B.; Danielson, K. S.</p> <p>1978-01-01</p> <p>Satellite observations allowed obtaining data on the visible brightness of cumulus <span class="hlt">clouds</span> over South Park, Colorado, while aircraft observations were made in <span class="hlt">cloud</span> to obtain the drop size distributions and liquid water content of the <span class="hlt">cloud</span>. Attention is focused on evaluating the relationship between <span class="hlt">cloud</span> brightness, horizontal dimension, and internal microphysical structure. A Monte Carlo <span class="hlt">cloud</span> model for finite <span class="hlt">clouds</span> was run using different distributions of drop sizes and numbers, while varying the <span class="hlt">cloud</span> depth and width to determine how theory would predict what the satellite would view from its given location in space. Comparison of these results to the satellite observed reflectances is presented. Theoretical results are found to be in good agreement with observations. For <span class="hlt">clouds</span> of optical thickness between 20 and 60, monitoring <span class="hlt">cloud</span> brightness changes in <span class="hlt">clouds</span> of uniform depth and variable width gives adequate information about a <span class="hlt">cloud</span>'s liquid water content. A <span class="hlt">cloud</span> having a 10:1 width to depth ratio is almost reaching its maximum brightness for a specified optical thickness.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006588','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006588"><span>Small vs. Large Convective <span class="hlt">Cloud</span> Objects from CERES Aqua Observations: Where are the Intraseasonal Variation Signals?</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xu, Kuan-Man</p> <p>2016-01-01</p> <p>During inactive phases of Madden-Julian oscillation (MJO), there are plenty of deep but small convective systems and far fewer deep and large ones. During active phases of MJO, a manifestation of an increase in the occurrence of large and deep <span class="hlt">cloud</span> clusters results from an amplification of large-scale motions by stronger convective heating. This study is designed to quantitatively examine the roles of small and large <span class="hlt">cloud</span> clusters during the MJO life cycle. We analyze the <span class="hlt">cloud</span> object data from Aqua CERES observations for tropical deep convective (DC) and cirrostratus (CS) <span class="hlt">cloud</span> object <span class="hlt">types</span> according to the real-time multivariate MJO index. The <span class="hlt">cloud</span> object is a contiguous region of the earth with a single dominant <span class="hlt">cloud</span>-system <span class="hlt">type</span>. The size distributions, defined as the footprint numbers as a function of <span class="hlt">cloud</span> object diameters, for particular MJO phases depart greatly from the combined (8-phase) distribution at large <span class="hlt">cloud</span>-object diameters due to the reduced/increased numbers of <span class="hlt">cloud</span> objects related to changes in the large-scale environments. The medium diameter corresponding to the combined distribution is determined and used to partition all <span class="hlt">cloud</span> objects into "small" and "large" groups of a particular phase. The two groups corresponding to the combined distribution have nearly equal numbers of footprints. The medium diameters are 502 km for DC and 310 km for cirrostratus. The range of the variation between two extreme phases (typically, the most active and depressed phases) for the small group is 6-11% in terms of the numbers of <span class="hlt">cloud</span> objects and the total footprint numbers. The corresponding range for the large group is 19-44%. In terms of the probability density functions of radiative and <span class="hlt">cloud</span> physical properties, there are virtually no differences between the MJO phases for the small group, but there are significant differences for the large groups for both DC and CS <span class="hlt">types</span>. These results suggest that the intreseasonal variation signals reside at the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A51E0105H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A51E0105H"><span>Alterations of <span class="hlt">Cloud</span> Microphysics Due to <span class="hlt">Cloud</span> Processed CCN</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hudson, J. G.; Tabor, S. S.; Noble, S. R., Jr.</p> <p>2015-12-01</p> <p>High-resolution CCN spectra have revealed bimodality (Hudson et al. 2015) similar to aerosol size spectra (e.g., Hoppel et al. 1985). Bimodality is caused by chemical and physical <span class="hlt">cloud</span> processes that increase mass or hygroscopicity of only CCN that produced activated <span class="hlt">cloud</span> droplets. Bimodality is categorized by relative CCN concentrations (NCCN) within the two modes, Nu-Np; i.e., NCCN within the higher critical supersaturation, Sc, mode that did not undergo <span class="hlt">cloud</span> processing minus NCCN within the lower Sc mode that was <span class="hlt">cloud</span> processed. Lower, especially negative, Nu-Np designates greater processing. The table shows regressions between Nu-Np and characteristics of <span class="hlt">clouds</span> nearest the CCN measurements. ICE-T MASE parameter R SL R SL Nc 0.17 93.24 -0.26 98.65 MD -0.31 99.69 0.33 99.78 σ -0.27 99.04 0.48 100.00 Ld -0.31 99.61 0.38 99.96 Table. Correlation coefficients, R, and one-tailed significance levels in percent, SL, for Nu-Np with microphysics of the <span class="hlt">clouds</span> closest to each CCN measurement, 75 ICE-T and 74 MASE cases. Nc is <span class="hlt">cloud</span> droplet concentration, MD is <span class="hlt">cloud</span> droplet mean diameter, σ is standard deviation of <span class="hlt">cloud</span> droplet spectra, Ldis drizzle drop LWC. Two aircraft field campaigns, Ice in <span class="hlt">Clouds</span> Experiment-Tropical (ICE-T) and Marine Stratus/Stratocumulus Experiment (MASE) show opposite R signs because coalescence dominated <span class="hlt">cloud</span> processing in low altitude ICE-T cumuli whereas chemical transformations predominated in MASE low altitude polluted stratus. Coalescence reduces Nc and NCCN, which thus increases MD, and σ, which promote Ld. Chemical transformations, e.g., SO2 to SO4, increase CCN hygroscopicity, thus reducing Sc, but not affecting Nc or NCCN. Lower Sc CCN are capable of producing greater Nc in subsequent <span class="hlt">cloud</span> cycles, which leads to lower MD and σ which reduce Ld (figure). These observations are consistent with <span class="hlt">cloud</span> droplet growth models for the higher vertical wind (W) of cumuli and lower W of stratus. Coalescence thus reduces the indirect</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li class="active"><span>24</span></li> <li><a href="#" onclick='return showDiv("page_25");'>25</a></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_24 --> <div id="page_25" class="hiddenDiv"> <div class="row"> <div class="col-sm-12"> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div> </div> <div class="row"> <div class="col-sm-12"> <ol class="result-class" start="481"> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018nova.pres.3673K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018nova.pres.3673K"><span>Featured Image: A Molecular <span class="hlt">Cloud</span> Outside Our Galaxy</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kohler, Susanna</p> <p>2018-06-01</p> <p>What do molecular <span class="hlt">clouds</span> look like outside of our own galaxy? See for yourself in the images above and below of N55, a molecular <span class="hlt">cloud</span> located in the Large Magellanic <span class="hlt">Cloud</span> (LMC). In a recent study led by Naslim Neelamkodan (Academia Sinica Institute of Astronomy and Astrophysics, Taiwan), a team of scientists explore N55 to determine how its <span class="hlt">cloud</span> properties differ from <span class="hlt">clouds</span> within the Milky Way. The image above reveals the distribution of infrared-emitting gas and dust observed in three bands by the Spitzer Space Telescope. Overplotted in cyan are observations from the Atacama Submillimeter Telescope Experiment tracing the clumpy, warm molecular gas. Below, new observations from the Atacama Large Millimeter/submillimeter Array (ALMA) reveal the sub-parsec-scale molecular clumps in greater detail, showing the correlation of massive clumps with Spitzer-<span class="hlt">identified</span> young stellar objects (crosses). The study presented here indicates that this <span class="hlt">cloud</span> in the LMC is the site of massive star formation, with properties similar to equivalent <span class="hlt">clouds</span> in the Milky Way. To learn more about the authors findings, check out the article linked below.CitationNaslim N. et al 2018 ApJ 853 175. doi:10.3847/1538-4357/aaa5b0</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017SPIE10424E..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017SPIE10424E..08S"><span>Detection of single and multilayer <span class="hlt">clouds</span> in an artificial neural network approach</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Hong, Gang; Chen, Yan</p> <p>2017-10-01</p> <p>Determining whether a scene observed with a satellite imager is composed of a thin cirrus over a water <span class="hlt">cloud</span> or thick cirrus contiguous with underlying layers of ice and water <span class="hlt">clouds</span> is often difficult because of similarities in the observed radiance values. In this paper an artificial neural network (ANN) algorithm, employing several Aqua MODIS infrared channels and the retrieved total <span class="hlt">cloud</span> visible optical depth, is trained to detect multilayer ice-over-water <span class="hlt">cloud</span> systems as <span class="hlt">identified</span> by matched April 2009 <span class="hlt">Cloud</span>Sat and CALIPSO (CC) data. The CC lidar and radar profiles provide the vertical structure that serves as output truth for a multilayer ANN, or MLANN, algorithm. Applying the trained MLANN to independent July 2008 MODIS data resulted in a combined ML and single layer hit rate of 75% (72%) for nonpolar regions during the day (night). The results are comparable to or more accurate than currently available methods. Areas of improvement are <span class="hlt">identified</span> and will be addressed in future versions of the MLANN.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29945681','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29945681"><span>Monte Carlo verification of radiotherapy treatments with <span class="hlt">Cloud</span>MC.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Miras, Hector; Jiménez, Rubén; Perales, Álvaro; Terrón, José Antonio; Bertolet, Alejandro; Ortiz, Antonio; Macías, José</p> <p>2018-06-27</p> <p>A new implementation has been made on <span class="hlt">Cloud</span>MC, a <span class="hlt">cloud</span>-based platform presented in a previous work, in order to provide services for radiotherapy treatment verification by means of Monte Carlo in a fast, easy and economical way. A description of the architecture of the application and the new developments implemented is presented together with the results of the tests carried out to validate its performance. <span class="hlt">Cloud</span>MC has been developed over Microsoft Azure <span class="hlt">cloud</span>. It is based on a map/reduce implementation for Monte Carlo calculations distribution over a dynamic cluster of virtual machines in order to reduce calculation time. <span class="hlt">Cloud</span>MC has been updated with new methods to read and process the information related to radiotherapy treatment verification: CT image set, treatment plan, structures and dose distribution files in DICOM format. Some tests have been designed in order to determine, for the different tasks, the most suitable <span class="hlt">type</span> of virtual machines from those available in Azure. Finally, the performance of Monte Carlo verification in <span class="hlt">Cloud</span>MC is studied through three real cases that involve different treatment techniques, linac models and Monte Carlo codes. Considering computational and economic factors, D1_v2 and G1 virtual machines were selected as the default <span class="hlt">type</span> for the Worker Roles and the Reducer Role respectively. Calculation times up to 33 min and costs of 16 € were achieved for the verification cases presented when a statistical uncertainty below 2% (2σ) was required. The costs were reduced to 3-6 € when uncertainty requirements are relaxed to 4%. Advantages like high computational power, scalability, easy access and pay-per-usage model, make Monte Carlo <span class="hlt">cloud</span>-based solutions, like the one presented in this work, an important step forward to solve the long-lived problem of truly introducing the Monte Carlo algorithms in the daily routine of the radiotherapy planning process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1916752K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1916752K"><span>Relating rainfall characteristics to <span class="hlt">cloud</span> top temperatures at different scales</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Klein, Cornelia; Belušić, Danijel; Taylor, Christopher</p> <p>2017-04-01</p> <p> wavelets to decompose <span class="hlt">cloud</span> top temperatures into power spectra at scales between 15 and 200km. From these, <span class="hlt">cloud</span> sub-structures are <span class="hlt">identified</span> as circular areas of respective scale with local power maxima in their centre. These areas are then mapped onto coinciding TRMM rainfall, allowing us to assign rainfall fields to sub-<span class="hlt">cloud</span> features of different scales. We find a higher probability for extreme rainfall for <span class="hlt">cloud</span> features above a scale of 30km, with features 100km contributing most to the number of extreme rainfall pixels. Over the average diurnal cycle, the number of smaller <span class="hlt">cloud</span> features between 15-60km shows an increase between 15 - 1700UTC, gradually developing into larger ones. The maximum of extreme rainfall pixels around 1900UTC coincides with a peak for scales 100km, suggesting a dominant role of these scales for intense rain for the analysed <span class="hlt">cloud</span> <span class="hlt">type</span>. Our results demonstrate the suitability of 2D wavelet decomposition for the analysis of sub-<span class="hlt">cloud</span> structures and their relation to rainfall characteristics, and help us to understand long-term changes in the properties of MCS.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015PASJ...67..109T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015PASJ...67..109T"><span><span class="hlt">Cloud-cloud</span> collision in the Galactic center 50 km s-1 molecular <span class="hlt">cloud</span></span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Tsuboi, Masato; Miyazaki, Atsushi; Uehara, Kenta</p> <p>2015-12-01</p> <p>We performed a search of star-forming sites influenced by external factors, such as SNRs, H II regions, and <span class="hlt">cloud-cloud</span> collisions (CCCs), to understand the star-forming activity in the Galactic center region using the NRO Galactic Center Survey in SiO v = 0, J = 2-1, H13CO+J = 1-0, and CS J = 1-0 emission lines obtained with the Nobeyama 45 m telescope. We found a half-shell-like feature (HSF) with a high integrated line intensity ratio of ∫TB(SiO v = 0, J = 2-1)dv/∫TB(H13CO+J = 1-0)dv ˜ 6-8 in the 50 km s-1 molecular <span class="hlt">cloud</span>; the HSF is a most conspicuous molecular <span class="hlt">cloud</span> in the region and harbors an active star-forming site where several compact H II regions can be seen. The high ratio in the HSF indicates that the <span class="hlt">cloud</span> contains huge shocked molecular gas. The HSF can be also seen as a half-shell feature in the position-velocity diagram. A hypothesis explaining the chemical and kinetic properties of the HSF is that the feature originates from a CCC. We analyzed the CS J = 1-0 emission line data obtained with the Nobeyama Millimeter Array to reveal the relation between the HSF and the molecular <span class="hlt">cloud</span> cores in the <span class="hlt">cloud</span>. We made a cumulative core mass function (CMF) of the molecular <span class="hlt">cloud</span> cores within the HSF. The CMF in the CCC region is not truncated at least up to ˜2500 M⊙, although the CMF of the non-CCC region reaches the upper limit of ˜1500 M⊙. Most massive molecular cores with Mgas > 750 M⊙ are located only around the ridge of the HSF and adjoin the compact H II region. These may be a sign of massive star formation induced by CCCs in the Galactic center region.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.2826C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.2826C"><span>Point <span class="hlt">Cloud</span> Based Change Detection - an Automated Approach for <span class="hlt">Cloud</span>-based Services</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Collins, Patrick; Bahr, Thomas</p> <p>2016-04-01</p> <p>The fusion of stereo photogrammetric point <span class="hlt">clouds</span> with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point <span class="hlt">cloud</span> generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePoint<span class="hlt">Clouds</span>ByDenseImageMatching" was implemented to extract passive point <span class="hlt">clouds</span> in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to <span class="hlt">identify</span> corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "Point<span class="hlt">Cloud</span>FeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point <span class="hlt">clouds</span> (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1197909-photolysis-rates-correlated-overlapping-cloud-fields-cloud','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1197909-photolysis-rates-correlated-overlapping-cloud-fields-cloud"><span>Photolysis rates in correlated overlapping <span class="hlt">cloud</span> fields: <span class="hlt">Cloud</span>-J 7.3</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Prather, M. J.</p> <p>2015-05-27</p> <p>A new approach for modeling photolysis rates ( J values) in atmospheres with fractional <span class="hlt">cloud</span> cover has been developed and implemented as <span class="hlt">Cloud</span>-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of <span class="hlt">cloud</span> layers, <span class="hlt">Cloud</span>-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated <span class="hlt">cloud</span> groups with the integration over all <span class="hlt">cloud</span> combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations.more » <span class="hlt">Cloud</span>-J is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated <span class="hlt">cloud</span> groups, or 1 call with the simplest <span class="hlt">cloud</span> approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into <span class="hlt">Cloud</span>-J.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1349434-microspectroscopic-imaging-characterization-individually-identified-ice-nucleating-particles-from-case-field-study','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1349434-microspectroscopic-imaging-characterization-individually-identified-ice-nucleating-particles-from-case-field-study"><span>Microspectroscopic imaging and characterization of individually <span class="hlt">identified</span> ice nucleating particles from a case field study</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Knopf, Daniel A.; Alpert, P. A.; Wang, B.; ...</p> <p>2014-08-11</p> <p>The effect of anthropogenic and biogenic organic particles on atmospheric glaciation processes is poorly understood. We use an optical microscopy setup to <span class="hlt">identify</span> the ice nuclei (IN) active in immersion freezing (IMF) and deposition ice nucleation within a large population of particles collected on a substrate from an ambient environment in central California dominated by urban and marine aerosols. Multimodal microspectroscopy methods are applied to characterize the physicochemical properties and mixing state of the individual IN and particle populations to <span class="hlt">identify</span> particle-<span class="hlt">type</span> classes. The temperature onsets of water uptake occurred between 235 and 257 K at subsaturated conditions, and themore » onsets of IMF proceeded at subsaturated and saturated conditions for 235–247 K, relevant for ice nucleation in mixed-phase <span class="hlt">clouds</span>. Particles also took up water and nucleated ice between 226 and 235 K and acted as deposition IN with onset temperatures below 226 K, a temperature range relevant to cirrus <span class="hlt">cloud</span> formation. The <span class="hlt">identified</span> IN belong to the most common particle-<span class="hlt">type</span> classes observed in the field samples: organic coated sea salt and Na-rich, secondary, and refractory carbonaceous particles. Based on these observations, we suggest that the IN are not always particles with unique chemical composition and exceptional ice nucleation propensity; rather, they are common particles in the ambient particle population. Lastly, the results suggest that particle-<span class="hlt">type</span> abundance and total particle surface area are also crucial factors, in addition to particle-<span class="hlt">type</span> ice nucleation efficiency, in determining ice formation within the particle population.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010sucs.conf..279K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010sucs.conf..279K"><span>Design for Run-Time Monitor on <span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kang, Mikyung; Kang, Dong-In; Yun, Mira; Park, Gyung-Leen; Lee, Junghoon</p> <p></p> <p><span class="hlt">Cloud</span> computing is a new information technology trend that moves computing and data away from desktops and portable PCs into large data centers. The basic principle of <span class="hlt">cloud</span> computing is to deliver applications as services over the Internet as well as infrastructure. A <span class="hlt">cloud</span> is the <span class="hlt">type</span> of a parallel and distributed system consisting of a collection of inter-connected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources. The large-scale distributed applications on a <span class="hlt">cloud</span> require adaptive service-based software, which has the capability of monitoring the system status change, analyzing the monitored information, and adapting its service configuration while considering tradeoffs among multiple QoS features simultaneously. In this paper, we design Run-Time Monitor (RTM) which is a system software to monitor the application behavior at run-time, analyze the collected information, and optimize resources on <span class="hlt">cloud</span> computing. RTM monitors application software through library instrumentation as well as underlying hardware through performance counter optimizing its computing configuration based on the analyzed data.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3182732','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3182732"><span>Laboratory simulations show diabatic heating drives cumulus-<span class="hlt">cloud</span> evolution and entrainment</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Narasimha, Roddam; Diwan, Sourabh Suhas; Duvvuri, Subrahmanyam; Sreenivas, K. R.; Bhat, G. S.</p> <p>2011-01-01</p> <p><span class="hlt">Clouds</span> are the largest source of uncertainty in climate science, and remain a weak link in modeling tropical circulation. A major challenge is to establish connections between particulate microphysics and macroscale turbulent dynamics in cumulus <span class="hlt">clouds</span>. Here we address the issue from the latter standpoint. First we show how to create bench-scale flows that reproduce a variety of cumulus-<span class="hlt">cloud</span> forms (including two genera and three species), and track complete <span class="hlt">cloud</span> life cycles—e.g., from a “cauliflower” congestus to a dissipating fractus. The flow model used is a transient plume with volumetric diabatic heating scaled dynamically to simulate latent-heat release from phase changes in <span class="hlt">clouds</span>. Laser-based diagnostics of steady plumes reveal Riehl–Malkus <span class="hlt">type</span> protected cores. They also show that, unlike the constancy implied by early self-similar plume models, the diabatic heating raises the Taylor entrainment coefficient just above <span class="hlt">cloud</span> base, depressing it at higher levels. This behavior is consistent with <span class="hlt">cloud</span>-dilution rates found in recent numerical simulations of steady deep convection, and with aircraft-based observations of homogeneous mixing in <span class="hlt">clouds</span>. In-<span class="hlt">cloud</span> diabatic heating thus emerges as the key driver in <span class="hlt">cloud</span> development, and could well provide a major link between microphysics and <span class="hlt">cloud</span>-scale dynamics. PMID:21918112</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-s62-06021.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-s62-06021.html"><span>View of <span class="hlt">clouds</span> over Indian Ocean taken by Astronaut John Glenn during MA-6</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>1962-02-20</p> <p>S62-06021 (20 Feb. 1962) --- A view of <span class="hlt">clouds</span> over the Indian Ocean as photographed by astronaut John H. Glenn Jr. aboard the "Friendship 7" spacecraft during his Mercury Atlas 6 (MA-6) spaceflight on Feb. 20, 1962. The <span class="hlt">cloud</span> panorama illustrates the visibility of different <span class="hlt">cloud</span> <span class="hlt">types</span> and weather patterns. Shadows produced by the rising sun aid in the determination of relative <span class="hlt">cloud</span> heights. Photo credit: NASA</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3040530','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3040530"><span>Galaxy <span class="hlt">Cloud</span>Man: delivering <span class="hlt">cloud</span> compute clusters</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p></p> <p>2010-01-01</p> <p>Background Widespread adoption of high-throughput sequencing has greatly increased the scale and sophistication of computational infrastructure needed to perform genomic research. An alternative to building and maintaining local infrastructure is “<span class="hlt">cloud</span> computing”, which, in principle, offers on demand access to flexible computational infrastructure. However, <span class="hlt">cloud</span> computing resources are not yet suitable for immediate “as is” use by experimental biologists. Results We present a <span class="hlt">cloud</span> resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon’s EC2 <span class="hlt">cloud</span> infrastructure without any informatics requirements. Within this system, an entire suite of biological tools packaged by the NERC Bio-Linux team (http://nebc.nerc.ac.uk/tools/bio-linux) is available for immediate consumption. The provided solution makes it possible, using only a web browser, to create a completely configured compute cluster ready to perform analysis in less than five minutes. Moreover, we provide an automated method for building custom deployments of <span class="hlt">cloud</span> resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available <span class="hlt">cloud</span> system to better meet their needs. Conclusions The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 <span class="hlt">cloud</span> is not trivial. The solution presented in this paper eliminates these barriers, making it possible for researchers to deploy exactly the amount of computing power they need, combined with a wealth of existing analysis software, to handle the ongoing data deluge. PMID:21210983</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20110015997&hterms=air+contamination&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dair%2Bcontamination','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20110015997&hterms=air+contamination&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dair%2Bcontamination"><span>Spectral <span class="hlt">Cloud</span>-Filtering of AIRS Data: Non-Polar Ocean</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Aumann, Hartmut H.; Gregorich, David; Barron, Diana</p> <p>2004-01-01</p> <p>The Atmospheric Infrared Sounder (AIRS) is a grating array spectrometer which covers the thermal infrared spectral range between 640 and 1700/cm. In order to retain the maximum radiometric accuracy of the AIRS data, the effects of <span class="hlt">cloud</span> contamination have to be minimized. We discuss <span class="hlt">cloud</span> filtering which uses the high spectral resolution of AIRS to <span class="hlt">identify</span> about 100,000 of 500,000 non-polar ocean spectra per day as relatively "<span class="hlt">cloud</span>-free". Based on the comparison of surface channels with the NCEP provided global real time sst (rtg.sst), AIRS surface sensitive channels have a cold bias ranging from O.5K during the day to 0.8K during the night. Day and night spatial coherence tests show that the cold bias is due to <span class="hlt">cloud</span> contamination. During the day the <span class="hlt">cloud</span> contamination is due to a 2-3% broken <span class="hlt">cloud</span> cover at the 1-2 km altitude, characteristic of low stratus <span class="hlt">clouds</span>. The <span class="hlt">cloud</span>-contamination effects surface sensitive channels only. <span class="hlt">Cloud</span> contamination can be reduced to 0.2K by combining the spectral filter with a spatial coherence threshold, but the yield drops to 16,000 spectra per day. AIRS was launched in May 2002 on the Earth Observing System (EOS) Aqua satellite. Since September 2002 it has returned 4 million spectra of the globe each day.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050243529','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050243529"><span>Antarctica <span class="hlt">Cloud</span> Cover for October 2003 from GLAS Satellite Lidar Profiling</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spinhirne, J. D.; Palm, S. P.; Hart, W. D.</p> <p>2005-01-01</p> <p>Seeing <span class="hlt">clouds</span> in polar regions has been a problem for the imagers used on satellites. Both <span class="hlt">clouds</span> and snow and ice are white, which makes <span class="hlt">clouds</span> over snow hard to see. And for thermal infrared imaging both the surface and the <span class="hlt">clouds</span> cold. The Geoscience Laser Altimeter System (GLAS) launched in 2003 gives an entirely new way to see <span class="hlt">clouds</span> from space. Pulses of laser light scatter from <span class="hlt">clouds</span> giving a signal that is separated in time from the signal from the surface. The scattering from <span class="hlt">clouds</span> is thus a sensitive and direct measure of the presence and height of <span class="hlt">clouds</span>. The GLAS instrument orbits over Antarctica 16 times a day. All of the <span class="hlt">cloud</span> observations for October 2003 were summarized and compared to the results from the MODIS imager for the same month. There are two basic <span class="hlt">cloud</span> <span class="hlt">types</span> that are observed, low stratus with tops below 3 km and high cirrus form <span class="hlt">clouds</span> with <span class="hlt">cloud</span> top altitude and thickness tending at 12 km and 1.3 km respectively. The average <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> fractions are compared to the MODIS <span class="hlt">cloud</span> fraction data product, differences in the amount of <span class="hlt">cloud</span> cover are as much as 40% over the continent. The results will be used to improve the way <span class="hlt">clouds</span> are detected from the imager observations. These measurements give a much improved understanding of distribution of <span class="hlt">clouds</span> over Antarctica and may show how they are changing as a result of global warming.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1984SciAm.251b..52M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1984SciAm.251b..52M"><span>A superluminous object in the Large <span class="hlt">Cloud</span> of Magellan</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Mathis, J. S.; Savage, B. D.; Cassinelli, J. P.</p> <p>1984-08-01</p> <p>The superluminous object R136a of the nebula 30 Dor in the Large <span class="hlt">Cloud</span> of Magellan is characterized, summarizing the results of recent optical and (IUE) UV observations. Photographs, spectra, and diagrams are provided; and the techniques used to determine the parameters of the object are explained. The UV spectra exhibit a typical P Cygni profile like that of O-<span class="hlt">type</span> stars, but R136a is much brighter (5 x 10 to the 7th solar luminosity). Speckle interferometry has <span class="hlt">identified</span> a main component and two fainter objects at distances of 0.5 and 0.1 arcsec. The main component R136a1 is probably either a very massive single star (400-1000 solar mass) or a tight cluster of stars of known <span class="hlt">types</span>. Evidence for the existence of other similar objects is reviewed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170011693','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170011693"><span>An A-Train Climatology of Extratropical Cyclone <span class="hlt">Clouds</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Posselt, Derek J.; van den Heever, Susan C.; Booth, James F.; Del Genio, Anthony D.; Kahn, Brian; Bauer, Mike</p> <p>2016-01-01</p> <p>Extratropical cyclones (ETCs) are the main purveyors of precipitation in the mid-latitudes, especially in winter, and have a significant radiative impact through the <span class="hlt">clouds</span> they generate. However, general circulation models (GCMs) have trouble representing precipitation and <span class="hlt">clouds</span> in ETCs, and this might partly explain why current GCMs disagree on to the evolution of these systems in a warming climate. Collectively, the A-train observations of MODIS, <span class="hlt">Cloud</span>Sat, CALIPSO, AIRS and AMSR-E have given us a unique perspective on ETCs: over the past 10 years these observations have allowed us to construct a climatology of <span class="hlt">clouds</span> and precipitation associated with these storms. This has proved very useful for model evaluation as well in studies aimed at improving understanding of moist processes in these dynamically active conditions. Using the A-train observational suite and an objective cyclone and front identification algorithm we have constructed cyclone centric datasets that consist of an observation-based characterization of <span class="hlt">clouds</span> and precipitation in ETCs and their sensitivity to large scale environments. In this presentation, we will summarize the advances in our knowledge of the climatological properties of <span class="hlt">cloud</span> and precipitation in ETCs acquired with this unique dataset. In particular, we will present what we have learned about southern ocean ETCs, for which the A-train observations have filled a gap in this data sparse region. In addition, <span class="hlt">Cloud</span>Sat and CALIPSO have for the first time provided information on the vertical distribution of <span class="hlt">clouds</span> in ETCs and across warm and cold fronts. We will also discuss how these observations have helped <span class="hlt">identify</span> key areas for improvement in moist processes in recent GCMs. Recently, we have begun to explore the interaction between aerosol and <span class="hlt">cloud</span> cover in ETCs using MODIS, <span class="hlt">Cloud</span>Sat and CALIPSO. We will show how aerosols are climatologically distributed within northern hemisphere ETCs, and how this relates to <span class="hlt">cloud</span> cover.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080000873&hterms=Geostationary&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DGeostationary','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080000873&hterms=Geostationary&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3DGeostationary"><span>Comparison of <span class="hlt">Cloud</span> Properties from CALIPSO-<span class="hlt">Cloud</span>Sat and Geostationary Satellite Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.</p> <p>2007-01-01</p> <p><span class="hlt">Cloud</span> properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived <span class="hlt">cloud</span> parameters is essential for confident use of the products. Determination of <span class="hlt">cloud</span> amount, <span class="hlt">cloud</span> top height, and <span class="hlt">cloud</span> layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of <span class="hlt">clouds</span> as a function of altitude has become a central component of efforts to evaluate climate model <span class="hlt">cloud</span> simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as <span class="hlt">cloud</span> radars or lidars, have been available on a regular basis. Retrievals of <span class="hlt">cloud</span> properties are sensitive to the surface background, time of day, and the <span class="hlt">clouds</span> themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of <span class="hlt">cloud</span> radar data from <span class="hlt">Cloud</span>Sat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, <span class="hlt">Cloud</span>Sat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with <span class="hlt">cloud</span> products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in <span class="hlt">cloud</span>-top heights and <span class="hlt">cloud</span> amounts derived from the geostationary satellite data using the <span class="hlt">Clouds</span> and the Earth s Radiant Energy System (CERES) <span class="hlt">cloud</span> retrieval algorithms. The CERES multi-layer <span class="hlt">cloud</span> detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20090011855&hterms=SCG&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DSCG','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20090011855&hterms=SCG&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3DSCG"><span>A Climatology of Midlatitude Continental <span class="hlt">Clouds</span> from the ARM SGP Site. Part II; <span class="hlt">Cloud</span> Fraction and Surface Radiative Forcing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Xi, B.; Minnis, P.</p> <p>2006-01-01</p> <p>Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of <span class="hlt">cloud</span> fraction and radiative forcing between January 1997 and December 2002. <span class="hlt">Cloud</span> fractions are estimated for total <span class="hlt">cloud</span> cover and for single-layered low (0-3 km), middle (3-6 km), and high <span class="hlt">clouds</span> (more than 6 km) using ARM SCG ground-based paired lidar-radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of approximately 10 Wm(exp -2). The annual averages of total, and single-layered low, middle and high <span class="hlt">cloud</span> fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total and low <span class="hlt">cloud</span> amounts peak during January and February and reach a minimum during July and August, high <span class="hlt">clouds</span> occur more frequently than other <span class="hlt">types</span> of <span class="hlt">clouds</span> with a peak in summer. The average annual downwelling surface SW fluxes for total and low <span class="hlt">clouds</span> (151 and 138 Wm(exp-2), respectively) are less than those under middle and high <span class="hlt">clouds</span> (188 and 201 Wm(exp -2), respectively), but the downwelling LW fluxes (349 and 356 Wm(exp -2)) underneath total and low <span class="hlt">clouds</span> are greater than those from middle and high <span class="hlt">clouds</span> (337 and 333 Wm(exp -2)). Low <span class="hlt">clouds</span> produce the largest LW warming (55 Wm(exp -2) and SW cooling (-91 Wm(exp -2)) effects with maximum and minimum absolute values in spring and summer, respectively. High <span class="hlt">clouds</span> have the smallest LW warming (17 Wm(exp -2)) and SW cooling (-37 Wm(exp -2)) effects at the surface. All-sky SW CRF decreases and LW CRF increases with increasing <span class="hlt">cloud</span> fraction with mean slopes of -0.984 and 0.616 Wm(exp -2)%(exp -1), respectively. Over the entire diurnal cycle, <span class="hlt">clouds</span> deplete the amount of surface insolation more than they add to the downwelling LW flux. The calculated CRFs do not appear to be significantly</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1991BAMS...72..587C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1991BAMS...72..587C"><span>Illinois Precipitation Research: A Focus on <span class="hlt">Cloud</span> and Precipitation Modification.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Changnon, Stanley A.; Czys, Robert R.; Scott, Robert W.; Westcott, Nancy E.</p> <p>1991-05-01</p> <p>At the heart of the 40-year atmospheric research endeavors of the Illinois State Water Survey have been studies to understand precipitation processes in order to learn how precipitation is modified purposefully and accidentally, and to measure the physical and socio-economic consequences of <span class="hlt">cloud</span> and precipitation modification. Major field and laboratory activities of past years or briefly treated as a basis for describing the key findings of the past ten years. Recent studies of inadvertent and purposeful <span class="hlt">cloud</span> and rain modification and their effects are emphasized, including a 1989 field project conducted in Illinois and key findings from an on-going exploratory experiment addressing <span class="hlt">cloud</span> and rain modification. Results are encouraging for the use of dynamic seeding on summer cumuliform <span class="hlt">clouds</span> of the Midwest.Typical in-<span class="hlt">cloud</span> results at 10°C reveal multiple updrafts that tend to be filled with large amounts of supercooled drizzle and raindrops. Natural ice production is vigorous, and initial concentrations are larger than expected from ice nuclei. However, natural ice production is not so vigorous as to preclude opportunities for seeding. Radar-based studies of such <span class="hlt">clouds</span> reveal that their echo cores usually can be <span class="hlt">identified</span> prior to desired seeding times, which is significant for the evaluation of their behavior. Cell characteristics show considerable variance under different <span class="hlt">types</span> of meteorological conditions. Analysis of cell mergers reveals that under conditions of weak vertical shear, mid-level intercell flow at 4 km occurs as the reflectivity bridge between cells rapidly intensifies. The degree of intensification of single-echo cores after they merge is strongly related to the age and vigor of the cores before they join. Hence, <span class="hlt">cloud</span> growth may be enhanced if seeding can encourage echo cores to merge at critical times. Forecasting research has developed a technique for objectively distinguishing between operational seeding and nonoperational days and for</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014EGUGA..16.5527H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014EGUGA..16.5527H"><span>Estimating the Influence of Biological Ice Nuclei on <span class="hlt">Clouds</span> with Regional Scale Simulations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hummel, Matthias; Hoose, Corinna; Schaupp, Caroline; Möhler, Ottmar</p> <p>2014-05-01</p> <p> both simulations is a result of the heterogeneous ice nucleation of PBAP. In the chosen case setup, two effects can be <span class="hlt">identified</span> which are occurring at different altitudes. Additional PBAP IN directly enhance the ice crystal concentration at lower parts of a mixed-phase <span class="hlt">cloud</span>. This increase comes with a decrease in liquid droplet concentration in this part of a <span class="hlt">cloud</span>. Therefore, a second effect takes place, where less ice crystals are formed by dust-driven heterogeneous as well as homogeneous ice nucleation in upper parts of a <span class="hlt">cloud</span>, probably due to a lack of liquid water reaching these altitudes. Overall, diagnostic PBAP IN concentrations are very low compared to typical IN concentration, but reach maxima at temperatures where typical IN are not very ice-active. PBAP IN can therefore influence <span class="hlt">clouds</span> to some extent. Iannone, R., Chernoff, D. I., Pringle, A., Martin, S. T., and Bertram, A. K.: The ice nucleation ability of one of the most abundant <span class="hlt">types</span> of fungal spores found in the atmosphere, Atmos. Chem. Phys., 11, 1191-1201, 10.5194/acp-11-1191-2011, 2011. Schaupp, C.: Untersuchungen zur Rolle von Bakterien und Pollen als Wolkenkondensations- und Eiskeime in troposphärischen Wolken, Ph.D. thesis, Institute of Environmental Physics, Heidelberg University, Heidelberg, Germany, 2013.</p> </li> </ol> <div class="pull-right"> <ul class="pagination"> <li><a href="#" onclick='return showDiv("page_1");'>«</a></li> <li><a href="#" onclick='return showDiv("page_21");'>21</a></li> <li><a href="#" onclick='return showDiv("page_22");'>22</a></li> <li><a href="#" onclick='return showDiv("page_23");'>23</a></li> <li><a href="#" onclick='return showDiv("page_24");'>24</a></li> <li class="active"><span>25</span></li> <li><a href="#" onclick='return showDiv("page_25");'>»</a></li> </ul> </div> </div><!-- col-sm-12 --> </div><!-- row --> </div><!-- page_25 --> <div class="footer-extlink text-muted" style="margin-bottom:1rem; text-align:center;">Some links on this page may take you to non-federal websites. 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