Sample records for clouds

  1. Cloud Infrastructure & Applications - CloudIA

    NASA Astrophysics Data System (ADS)

    Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank

    The idea behind Cloud 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 Cloud Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called Cloud Infrastructure & Applications (CloudIA). The CloudIA project is a market-oriented cloud infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the CloudIA project in details and mentions our early experiences in building a private cloud using an existing infrastructure.

  2. Cloud radiative properties and aerosol - cloud interaction

    NASA Astrophysics Data System (ADS)

    Viviana Vladutescu, Daniela; Gross, Barry; Li, Clement; Han, Zaw

    2015-04-01

    The presented research discusses different techniques for improvement of cloud 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 cloud properties and implicitly cloud radiative forcing. The properties investigated are cloud fraction (cf) and cloud 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 cloud 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 clouds. As the cloud fraction cannot be uniquely defined or measured, it depends on threshold and resolution. However as resolution decreases, cloud fraction tends to increase if the threshold is below the mean, and vice versa. Additionally cloud fractal dimension also depends on threshold. Therefore these findings raise concerns over the ability to characterize clouds by cloud fraction or fractal dimension. Our analysis indicate that Principal Component analysis may lead to a robust means of quantifying cloud contribution to radiance. The cloud 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 cloud radiative properties as a validation tool to the results obtained from the other instruments and methods. The cloud properties to be further studied are aerosol- cloud interaction, cloud particle radii, and vertical homogeneity.

  3. SparkClouds: visualizing trends in tag clouds.

    PubMed

    Lee, Bongshin; Riche, Nathalie Henry; Karlson, Amy K; Carpendale, Sheelash

    2010-01-01

    Tag clouds 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 clouds can evolve as the associated data source changes over time. Interesting discussions around tag clouds often include a series of tag clouds and consider how they evolve over time. However, since tag clouds do not explicitly represent trends or support comparisons, the cognitive demands placed on the person for perceiving trends in multiple tag clouds are high. In this paper, we introduce SparkClouds, which integrate sparklines into a tag cloud to convey trends between multiple tag clouds. We present results from a controlled study that compares SparkClouds with two traditional trend visualizations—multiple line graphs and stacked bar charts—as well as Parallel Tag Clouds. Results show that SparkClouds ability to show trends compares favourably to the alternative visualizations.

  4. Cloud-Top Entrainment in Stratocumulus Clouds

    NASA Astrophysics Data System (ADS)

    Mellado, Juan Pedro

    2017-01-01

    Cloud entrainment, the mixing between cloudy and clear air at the boundary of clouds, constitutes one paradigm for the relevance of small scales in the Earth system: By regulating cloud lifetimes, meter- and submeter-scale processes at cloud boundaries can influence planetary-scale properties. Understanding cloud 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 cloud 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 cloud entrainment. This article reviews some of these advances, focusing on stratocumulus clouds, and indicates remaining challenges.

  5. A comparison of shock-cloud and wind-cloud interactions: effect of increased cloud density contrast on cloud evolution

    NASA Astrophysics Data System (ADS)

    Goldsmith, K. J. A.; Pittard, J. M.

    2018-05-01

    The similarities, or otherwise, of a shock or wind interacting with a cloud of density contrast χ = 10 were explored in a previous paper. Here, we investigate such interactions with clouds of higher density contrast. We compare the adiabatic hydrodynamic interaction of a Mach 10 shock with a spherical cloud of χ = 103 with that of a cloud 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-cloud and wind-cloud interactions, compared to when χ = 10. However, once the transmitted shock exits the cloud, the development of a turbulent wake and fragmentation of the cloud differs between the two simulations. On increasing the wind Mach number, we note the development of a thin, smooth tail of cloud material, which is then disrupted by the fragmentation of the cloud core and subsequent `mass-loading' of the flow. We find that the normalized cloud mixing time (tmix) is shorter at higher χ. However, a strong Mach number dependence on tmix and the normalized cloud drag time, t_{drag}^' }, is not observed. Mach-number-dependent values of tmix and t_{drag}^' } from comparable shock-cloud interactions converge towards the Mach-number-independent time-scales of the wind-cloud simulations. We find that high χ clouds 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.

  6. 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.

  7. Cloud Processed CCN Suppress Stratus Cloud Drizzle

    NASA Astrophysics Data System (ADS)

    Hudson, J. G.; Noble, S. R., Jr.

    2017-12-01

    Conversion of sulfur dioxide to sulfate within cloud droplets increases the sizes and decreases the critical supersaturation, Sc, of cloud 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 cloud droplet concentrations (Nc) in stratus clouds associated with bimodal high-resolution CCN spectra from the DRI CCN spectrometer compared to clouds associated with unimodal CCN spectra (not cloud processed). Here we show that CCN spectral shape (bimodal or unimodal) affects all aspects of stratus cloud microphysics and drizzle. Panel A shows mean differential cloud 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 clouds (< 0.5%). Because cloud processing decreases Sc of some particles, it reduces k. Panel A shows higher concentrations of small cloud droplets apparently grown on lower k CCN than clouds 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 clouds grown on the least cloud-processed CCN (blue), while clouds grown on the most processed CCN (black) have the lowest Nd. Suppression of stratus cloud drizzle by cloud 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 cloud regimes to determine if MASE was

  8. Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

    NASA Astrophysics Data System (ADS)

    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.

    2008-05-01

    CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

  9. Molecular Cloud Evolution VI. Measuring cloud ages

    NASA Astrophysics Data System (ADS)

    Vázquez-Semadeni, Enrique; Zamora-Avilés, Manuel; Galván-Madrid, Roberto; Forbrich, Jan

    2018-06-01

    In previous contributions, we have presented an analytical model describing the evolution of molecular clouds (MCs) undergoing hierarchical gravitational contraction. The cloud'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 cloud. The main parameter of the model is the maximum mass reached by the cloud during its evolution. Thus, specifying the instantaneous mass and some other variable completely determines the cloud's evolutionary stage. We apply the model to interpret the observed scatter in SFEs of the cloud sample compiled by Lada et al. as an evolutionary effect so that, although clouds 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 cloud will eventually reach a significantly larger total mass than the Orion A cloud. Next, we apply the model to derive estimated ages of the clouds 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 clouds being the youngest. Further predictions of the model are that clouds with very low SFEs should have massive atomic envelopes constituting the majority of their gravitational mass, and that low-mass clouds (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.

  10. Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

    DOE PAGES

    Klein, Stephen A.; Hall, Alex; Norris, Joel R.; ...

    2017-10-24

    Here, the response to warming of tropical low-level clouds 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 clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming,more » one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-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 cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m –2 K –1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.« less

  11. Low-Cloud Feedbacks from Cloud-Controlling Factors: A Review

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

    Klein, Stephen A.; Hall, Alex; Norris, Joel R.

    Here, the response to warming of tropical low-level clouds 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 clouds. These inadequacies have led to alternative approaches to predict low-cloud feedbacks. Here, we review an observational approach that relies on the assumption that observed relationships between low clouds and the “cloud-controlling factors” of the large-scale environment are invariant across time-scales. With this assumption, and given predictions of how the cloud-controlling factors change with climate warming,more » one can predict low-cloud feedbacks without using any model simulation of low clouds. We discuss both fundamental and implementation issues with this approach and suggest steps that could reduce uncertainty in the predicted low-cloud feedback. Recent studies using this approach predict that the tropical low-cloud feedback is positive mainly due to the observation that reflection of solar radiation by low clouds decreases as temperature increases, holding all other cloud-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 cloud-controlling factors playing a smaller role. A consensus estimate from these studies for the contribution of tropical low clouds to the global mean cloud feedback is 0.25 ± 0.18 W m –2 K –1 (90% confidence interval), suggesting it is very unlikely that tropical low clouds reduce total global cloud feedback. Because the prediction of positive tropical low-cloud feedback with this approach is consistent with independent evidence from low-cloud feedback studies using high-resolution cloud models, progress is being made in reducing this key climate uncertainty.« less

  12. 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.

  13. 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.

  14. Cloud Computing

    DTIC Science & Technology

    2010-04-29

    Cloud Computing   The answer, my friend, is blowing in the wind.   The answer is blowing in the wind. 1Bingue ‐ Cook  Cloud   Computing  STSC 2010... Cloud   Computing  STSC 2010 Objectives • Define the cloud    • Risks of  cloud   computing f l d i• Essence o  c ou  comput ng • Deployed clouds in DoD 3Bingue...Cook  Cloud   Computing  STSC 2010 Definitions of Cloud Computing       Cloud   computing  is a model for enabling  b d d ku

  15. 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

  16. 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.

  17. 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.


  18. Cirrus Cloud Retrieval Using Infrared Sounding Data: Multilevel Cloud Errors.

    NASA Astrophysics Data System (ADS)

    Baum, Bryan A.; Wielicki, Bruce A.

    1994-01-01

    In this study we perform an error analysis for cloud-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 cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1 1.0) and cloud-top pressures (850250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud elective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all casts, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. 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 cloud climatology, the bias errors are most critical.

  19. Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

    NASA Astrophysics Data System (ADS)

    Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

    2006-12-01

    During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud 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 Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud 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 clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat 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 clouds in overlapped conditions.

  20. Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

    NASA Astrophysics Data System (ADS)

    Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

    2005-05-01

    During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud 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 Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud 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 clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat 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 clouds in overlapped conditions.

  1. Cloud occurrences and cloud radiative effects (CREs) from CERES-CALIPSO-CloudSat-MODIS (CCCM) and CloudSat radar-lidar (RL) products

    NASA Astrophysics Data System (ADS)

    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.

    2017-08-01

    Two kinds of cloud products obtained from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), CloudSat, and Moderate Resolution Imaging Spectroradiometer (MODIS) are compared and analyzed in this study: Clouds and the Earth's Radiant Energy System (CERES)-CALIPSO-CloudSat-MODIS (CCCM) product and CloudSat radar-lidar products such as GEOPROF-LIDAR and FLXHR-LIDAR. Compared to GEOPROF-LIDAR, low-level (<1 km) cloud occurrences in CCCM are larger over tropical oceans because the CCCM algorithm uses a more relaxed threshold of cloud-aerosol discrimination score for CALIPSO Vertical Feature Mask product. In contrast, midlevel (1-8 km) cloud 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 CloudSat radar. In the comparison of cloud 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 clouds. 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.

  2. 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.

  3. Clouds

    NASA Image and Video Library

    2010-09-14

    Clouds are common near the north polar caps throughout the spring and summer. The clouds typically cause a haze over the extensive dune fields. This image from NASA Mars Odyssey shows the edge of the cloud front.

  4. Relationships among cloud occurrence frequency, overlap, and effective thickness derived from CALIPSO and CloudSat merged cloud vertical profiles

    NASA Astrophysics Data System (ADS)

    Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.

    2010-01-01

    A cloud frequency of occurrence matrix is generated using merged cloud vertical profiles derived from the satellite-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and cloud profiling radar. The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical profiles can be related by a cloud overlap matrix when the correlation length of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches random overlap with increasing distance separating cloud layers and that the probability of deviating from random overlap decreases exponentially with distance. One month of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat data (July 2006) support these assumptions, although the correlation length sometimes increases with separation distance when the cloud top height is large. The data also show that the correlation length depends on cloud top hight and the maximum occurs when the cloud top height is 8 to 10 km. The cloud correlation length is equivalent to the decorrelation distance introduced by Hogan and Illingworth (2000) when cloud fractions of both layers in a two-cloud 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 cloud fraction, uppermost cloud top, and cloud thickness vertical profile differences.

  5. Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields

    NASA Astrophysics Data System (ADS)

    Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.

    1992-12-01

    During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud 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 cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards

  6. Using Cloud Computing infrastructure with CloudBioLinux, CloudMan and Galaxy

    PubMed Central

    Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

    2012-01-01

    Cloud 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 cloud computing resources to perform open-ended bioinformatics analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, 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 cloud 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

  7. Using cloud computing infrastructure with CloudBioLinux, CloudMan, and Galaxy.

    PubMed

    Afgan, Enis; Chapman, Brad; Jadan, Margita; Franke, Vedran; Taylor, James

    2012-06-01

    Cloud 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 cloud computing resources to perform open-ended bioinformatic analyses, with fully automated management of the underlying cloud infrastructure. By combining three projects, CloudBioLinux, CloudMan, 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 cloud 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.

  8. Cloud Microphysics Parameterization in a Shallow Cumulus Cloud Simulated by a Largrangian Cloud Model

    NASA Astrophysics Data System (ADS)

    Oh, D.; Noh, Y.; Hoffmann, F.; Raasch, S.

    2017-12-01

    Lagrangian cloud model (LCM) is a fundamentally new approach of cloud simulation, in which the flow field is simulated by large eddy simulation and droplets are treated as Lagrangian particles undergoing cloud microphysics. LCM enables us to investigate raindrop formation and examine the parameterization of cloud 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 cloud droplets to raindrops in a shallow cumulus cloud reveals how and under which condition raindrops are formed. It also provides information how autoconversion and accretion appear and evolve within a cloud, and how they are affected by various factors such as cloud 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.

  9. Silicon photonics cloud (SiCloud)

    NASA Astrophysics Data System (ADS)

    DeVore, Peter T. S.; Jiang, Yunshan; Lynch, Michael; Miyatake, Taira; Carmona, Christopher; Chan, Andrew C.; Muniam, Kuhan; Jalali, Bahram

    2015-02-01

    We present SiCloud (Silicon Photonics Cloud), the first free, instructional web-based research and education tool for silicon photonics. SiCloud'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. SiCloud includes the common dielectrics and semiconductors for waveguide core, cladding, and photodetection, as well as metals for electrical contacts. SiCloud is a work in progress and its capability is being expanded. SiCloud is being developed at UCLA with funding from the National Science Foundation's Center for Integrated Access Networks (CIAN) Engineering Research Center.

  10. Relation of Cloud Occurrence Frequency, Overlap, and Effective Thickness Derived from CALIPSO and CloudSat Merged Cloud Vertical Profiles

    NASA Technical Reports Server (NTRS)

    Kato, Seiji; Sun-Mack, Sunny; Miller, Walter F.; Rose, Fred G.; Chen, Yan; Minnis, Patrick; Wielicki, Bruce A.

    2009-01-01

    A cloud frequency of occurrence matrix is generated using merged cloud vertical profile derived from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR). The matrix contains vertical profiles of cloud occurrence frequency as a function of the uppermost cloud top. It is shown that the cloud fraction and uppermost cloud top vertical pro les can be related by a set of equations when the correlation distance of cloud occurrence, which is interpreted as an effective cloud thickness, is introduced. The underlying assumption in establishing the above relation is that cloud overlap approaches the random overlap with increasing distance separating cloud layers and that the probability of deviating from the random overlap decreases exponentially with distance. One month of CALIPSO and CloudSat data support these assumptions. However, the correlation distance sometimes becomes large, which might be an indication of precipitation. The cloud correlation distance is equivalent to the de-correlation distance introduced by Hogan and Illingworth [2000] when cloud fractions of both layers in a two-cloud layer system are the same.

  11. The frequency and nature of `cloud-cloud collisions' in galaxies

    NASA Astrophysics Data System (ADS)

    Dobbs, C. L.; Pringle, J. E.; Duarte-Cabral, A.

    2015-02-01

    We investigate cloud-cloud collisions and giant molecular cloud 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 clouds 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 clouds are not uniformly distributed in the galaxy. Thus, clouds can be expected to undergo between zero and a few collisions over their lifetime. We present specific examples of cloud-cloud interactions in our results, including synthetic CO maps. We would expect cloud-cloud interactions to be observable, but find they appear to have little or no impact on the ISM. Due to a combination of the clouds' typical geometries, and moderate velocity dispersions, cloud-cloud interactions often better resemble a smaller cloud nudging a larger cloud. 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 cloud collisions we ideally need higher resolution simulations.

  12. Contrasting Cloud Composition Between Coupled and Decoupled Marine Boundary Layer Clouds

    NASA Astrophysics Data System (ADS)

    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.

    2016-12-01

    Marine stratocumulus clouds often become decoupled from the vertical layer immediately above the ocean surface. This study contrasts cloud chemical composition between coupled and decoupled marine stratocumulus clouds. Cloud water and droplet residual particle composition were measured in clouds off the California coast during three airborne experiments in July-August of separate years (E-PEACE 2011, NiCE 2013, BOAS 2015). Decoupled clouds exhibited significantly lower overall mass concentrations in both cloud water and droplet residual particles, consistent with reduced cloud droplet number concentration and sub-cloud aerosol (Dp > 100 nm) number concentration, owing to detachment from surface sources. Non-refractory sub-micrometer aerosol measurements show that coupled clouds exhibit higher sulfate mass fractions in droplet residual particles, owing to more abundant precursor emissions from the ocean and ships. Consequently, decoupled clouds 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 cloud water mass concentration in coupled clouds was dominated by sodium and chloride, and their mass fractions and concentrations exceeded those in decoupled clouds. Conversely, with the exception of sea salt constituents (e.g., Cl, Na, Mg, K), cloud water mass fractions of all species examined were higher in decoupled clouds relative to coupled clouds. These results suggest that an important variable is the extent to which clouds are coupled to the surface layer when interpreting microphysical data relevant to clouds and aerosol particles.

  13. Stratus Cloud Radiative Effects from Cloud Processed Bimodal CCN Distributions

    NASA Astrophysics Data System (ADS)

    Noble, S. R., Jr.; Hudson, J. G.

    2016-12-01

    Inability to understand cloud processes is a large component of climate uncertainty. Increases in cloud condensation nuclei (CCN) concentrations are known to increase cloud droplet number concentrations (Nc). This aerosol-cloud interaction (ACI) produces greater Nc at smaller sizes, which brightens clouds. A lesser understood ACI is cloud processing of CCN. This improves CCN that then more easily activate at lower cloud supersaturations (S). Bimodal CCN distributions thus ensue from these evaporated cloud droplets. Hudson et al. (2015) related CCN bimodality to Nc. In stratus clouds, bimodal CCN created greater Nc whereas in cumulus less Nc. Thus, CCN distribution shape influences cloud 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 clouds (<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 clouds (>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 cloud grown to a 250-meter thickness. Bimodal CCN at low W reduced cloud effective radius (re), made greater cloud optical thickness (COT), and made greater cloud albedo (Fig. 1c). At very low W changes were as much as +9% for albedo, +17% for COT, and -12% for re. Stratus clouds typically have low W and cover large areas. Thus, these changes in cloud radiative properties at low W impact climate. Stratus cloud susceptibility to CCN distribution thus

  14. Hybrid cloud: bridging of private and public cloud computing

    NASA Astrophysics Data System (ADS)

    Aryotejo, Guruh; Kristiyanto, Daniel Y.; Mufadhol

    2018-05-01

    Cloud Computing is quickly emerging as a promising paradigm in the recent years especially for the business sector. In addition, through cloud service providers, cloud 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 Cloud Service Provider (CSP) could decrypt their data. Hybrid Cloud Deployment Model (HCDM) has characteristic as open source, which is one of secure cloud 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 cloud was adopted through public cloud 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 cloud significantly. To the best of our knowledge, Hybrid Cloud Deployment model is one of secure cloud computing model due to its characteristic as open source. Furthermore, this study will serve as a base for future studies about Hybrid Cloud Deployment model which may relevant for solving big security issues of IT-based startup companies especially in Indonesia.

  15. 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.

  16. AceCloud: Molecular Dynamics Simulations in the Cloud.

    PubMed

    Harvey, M J; De Fabritiis, G

    2015-05-26

    We present AceCloud, an on-demand service for molecular dynamics simulations. AceCloud is designed to facilitate the secure execution of large ensembles of simulations on an external cloud computing service (currently Amazon Web Services). The AceCloud client, integrated into the ACEMD molecular dynamics package, provides an easy-to-use interface that abstracts all aspects of interaction with the cloud 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.

  17. 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

  18. 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.

  19. 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

  20. Creating cloud-free Landsat ETM+ data sets in tropical landscapes: cloud and cloud-shadow removal

    Treesearch

    Sebastián Martinuzzi; William A. Gould; Olga M. Ramos Gonzalez

    2007-01-01

    Clouds and cloud 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 clouds and shadows in Landsat ETM+ imagery, and have developed a recent cloud-free composite of multitemporal images for Puerto Rico and...

  1. Re-evaluating the Cloud Lifetime Effect: Does Precipitation Suppression Always Lead to an Increased Cloud Extent in Warm Clouds?

    NASA Astrophysics Data System (ADS)

    Douglas, A.; L'Ecuyer, T.

    2017-12-01

    Aerosol influences on cloud lifetime remain a poorly understood pathway of aerosol-cloud-radiation interaction with large margins of error according to the fifth IPCC report. Increases in cloud lifetime are attributed to changes in cloud extent due to the suppression of precipitation by increased aerosol concentrations. The dependence of changes in cloud fraction and probability of precipitation on aerosol perturbations for controlled cloud regimes will be investigated using A-Train measurements. CloudSat, 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 cloud morphology. Holding the thermodynamic and meteorological environments constant allows variations in precipitation and cloud extent owing to regime-specific cloud lifetime effects to be attributed to aerosol perturbations. The relationship between precipitation suppression, cloud extent, and liquid water path will be analyzed. The cloud lifetime effect will be constrained using regimes in the hopes of improving our understanding of precipitation-aerosol interactions.

  2. Contrasting cloud composition between coupled and decoupled marine boundary layer clouds

    NASA Astrophysics Data System (ADS)

    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

    2016-10-01

    Marine stratocumulus clouds often become decoupled from the vertical layer immediately above the ocean surface. This study contrasts cloud chemical composition between coupled and decoupled marine stratocumulus clouds for dissolved nonwater substances. Cloud water and droplet residual particle composition were measured in clouds off the California coast during three airborne experiments in July-August of separate years (Eastern Pacific Emitted Aerosol Cloud Experiment 2011, Nucleation in California Experiment 2013, and Biological and Oceanic Atmospheric Study 2015). Decoupled clouds exhibited significantly lower air-equivalent mass concentrations in both cloud water and droplet residual particles, consistent with reduced cloud droplet number concentration and subcloud aerosol (Dp > 100 nm) number concentration, owing to detachment from surface sources. Nonrefractory submicrometer aerosol measurements show that coupled clouds exhibit higher sulfate mass fractions in droplet residual particles, owing to more abundant precursor emissions from the ocean and ships. Consequently, decoupled clouds 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 cloud water for coupled clouds, and their mass fractions and concentrations exceeded those in decoupled clouds. Conversely, with the exception of sea-salt constituents (e.g., Cl, Na, Mg, and K), cloud water mass fractions of all species examined were higher in decoupled clouds relative to coupled clouds. 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 cloud composition.

  3. 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.

  4. EDITORIAL: Focus on Cloud Physics FOCUS ON CLOUD PHYSICS

    NASA Astrophysics Data System (ADS)

    Falkovich, Gregory; Malinowski, Szymon P.

    2008-07-01

    Cloud physics has for a long time been an important segment of atmospheric science. It is common knowledge that clouds are crucial for our understanding of weather and climate. Clouds 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 cloud is 'a set of droplets or particles suspended in the atmosphere' is not adequate. Clouds 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 cloud condensation nuclei, condensational growth and collisions; small changes in composition and concentration of atmospheric aerosol lead to significant differences in radiative properties of the clouds and influence rainfall formation. It is justified to look at a cloud 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 cloud system, present-day descriptions of clouds 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 clouds 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

  5. 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

  6. Cloud Modeling

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

    2001-01-01

    Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud 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 clouds, 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 cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

  7. Comparison of Cirrus Cloud Models: A Project of the GEWEX Cloud System Study (GCSS) Working Group on Cirrus Cloud Systems

    NASA Technical Reports Server (NTRS)

    Starr, David OC.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric; Khvorostyanov, Vitaly; hide

    2000-01-01

    The GEWEX Cloud System Study (GCSS, GEWEX is the Global Energy and Water Cycle Experiment) is a community activity aiming to promote development of improved cloud 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 cloud-system models (CSMs). These are "process" models with sufficient spatial and temporal resolution to represent individual cloud elements, but spanning a wide range of space and time scales to enable statistical analysis of simulated cloud systems. GCSS also employs single-column versions of the parametric cloud models (SCMs) used in GCMs. GCSS has working groups on boundary-layer clouds, cirrus clouds, extratropical layer cloud systems, precipitating deep convective cloud systems, and polar clouds.

  8. Comparison of Cirrus Cloud Models: A Project of the GEWEX Cloud System Study (GCSS) Working Group on Cirrus Cloud Systems

    NASA Technical Reports Server (NTRS)

    Starr, David O'C.; Benedetti, Angela; Boehm, Matt; Brown, Philip R. A.; Gierens, Klaus M.; Girard, Eric; Giraud, Vincent; Jakob, Christian; Jensen, Eric

    2000-01-01

    The GEWEX Cloud System Study (GCSS, GEWEX is the Global Energy and Water Cycle Experiment) is a community activity aiming to promote development of improved cloud 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 cloud-system models (CSMs). These are "process" models with sufficient spatial and temporal resolution to represent individual cloud elements, but spanning a wide range of space and time scales to enable statistical analysis of simulated cloud systems. GCSS also employs single-column versions of the parametric cloud models (SCMs) used in GCMs. GCSS has working groups on boundary-layer clouds, cirrus clouds, extratropical layer cloud systems, precipitating deep convective cloud systems, and polar clouds.

  9. Comparisons of Satellite-Deduced Overlapping Cloud Properties and CALIPSO CloudSat Data

    NASA Technical Reports Server (NTRS)

    Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny

    2010-01-01

    Introduction to the overlapped cloud 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) cloud research & development team (NASA lead scientist: Dr. Patrick Minnis). Comparison of the LaRC CERES MODIS Edition-3 overlapped cloud properties to the CALIPSO and the CloudSat active sensing data. High clouds and overlapped clouds occur frequently as deduced by CALIPSO (44 & 25%), CloudSat (25 & 4%), and MODIS (37 & 6%). Large fractions of optically-thin cirrus and overlapped clouds are deduced from CALIPSO, but much smaller fractions are from CloudSat and MODIS. For overlapped clouds, the averaged upper-layer CTHs are about 12.8 (CALIPSO), 10.9 (CloudSat) and 10 km (MODIS), and the averaged lower-layer CTHs are about 3.6 (CALIPSO), 3.2 (CloudSat) and 3.9 km (MODIS). Based on comparisons of upper and lower-layer cloud properties as deduced from the MODIS, CALIPSO and CloudSat data, more enhanced passive satellite methods for retrieving thin cirrus and overlapped cloud properties are needed and are under development.

  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. Estimating Cloud Cover

    ERIC Educational Resources Information Center

    Moseley, Christine

    2007-01-01

    The purpose of this activity was to help students understand the percentage of cloud cover and make more accurate cloud cover observations. Students estimated the percentage of cloud cover represented by simulated clouds and assigned a cloud cover classification to those simulations. (Contains 2 notes and 3 tables.)

  12. 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.

  13. Sensitivity of single column model simulations of Arctic springtime clouds to different cloud cover and mixed phase cloud parameterizations

    NASA Astrophysics Data System (ADS)

    Zhang, Junhua; Lohmann, Ulrike

    2003-08-01

    The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud 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 cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud 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.

  14. CALIPSO Observations of Near-Cloud Aerosol Properties as a Function of Cloud Fraction

    NASA Technical Reports Server (NTRS)

    Yang, Weidong; Marshak, Alexander; Varnai, Tamas; Wood, Robert

    2015-01-01

    This paper uses spaceborne lidar data to study how near-cloud aerosol statistics of attenuated backscatter depend on cloud fraction. The results for a large region around the Azores show that: (1) far-from-cloud aerosol statistics are dominated by samples from scenes with lower cloud fractions, while near-cloud aerosol statistics are dominated by samples from scenes with higher cloud fractions; (2) near-cloud enhancements of attenuated backscatter occur for any cloud fraction but are most pronounced for higher cloud fractions; (3) the difference in the enhancements for different cloud fractions is most significant within 5km from clouds; (4) near-cloud enhancements can be well approximated by logarithmic functions of cloud fraction and distance to clouds. These findings demonstrate that if variability in cloud 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 clouds. For the Azores-region dataset examined here, this artifact occurs mostly within 5 km from clouds, and exaggerates the near-cloud 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 clouds, it is important to account for the impact of changes in cloud fraction.

  15. Military clouds: utilization of cloud computing systems at the battlefield

    NASA Astrophysics Data System (ADS)

    Süleyman, Sarıkürk; Volkan, Karaca; İbrahim, Kocaman; Ahmet, Şirzai

    2012-05-01

    Cloud 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, cloud computing systems are operational today. In the near future extensive use of military clouds at the battlefield is predicted. Integrating cloud computing logic to network centric applications will increase the flexibility, cost-effectiveness, efficiency and accessibility of network-centric capabilities. In this paper, cloud computing and network centric capability concepts are defined. Some commercial cloud computing products and applications are mentioned. Network centric capable applications are covered. Cloud computing supported battlefield applications are analyzed. The effects of cloud 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 cloud computing systems are researched. The role of military clouds in future warfare is proposed in this paper. It was concluded that military clouds will be indispensible components of the future battlefield. Military clouds have the potential of improving network centric capabilities, increasing situational awareness at the battlefield and facilitating the settlement of information superiority.

  16. Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields

    NASA Astrophysics Data System (ADS)

    Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

    1994-07-01

    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 cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds 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) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

  17. Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

    NASA Technical Reports Server (NTRS)

    Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.

    1994-01-01

    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 cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds 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) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

  18. Galaxy CloudMan: delivering cloud compute clusters.

    PubMed

    Afgan, Enis; Baker, Dannon; Coraor, Nate; Chapman, Brad; Nekrutenko, Anton; Taylor, James

    2010-12-21

    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 "cloud computing", which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate "as is" use by experimental biologists. We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon's EC2 cloud 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 cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud 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.

  19. Thin Cloud Detection Method by Linear Combination Model of Cloud Image

    NASA Astrophysics Data System (ADS)

    Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

    2018-04-01

    The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud 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 cloud detection program in this paper has high accuracy and fast calculation speed.

  20. Effects of cloud size and cloud particles on satellite-observed reflected brightness

    NASA Technical Reports Server (NTRS)

    Reynolds, D. W.; Mckee, T. B.; Danielson, K. S.

    1978-01-01

    Satellite observations allowed obtaining data on the visible brightness of cumulus clouds over South Park, Colorado, while aircraft observations were made in cloud to obtain the drop size distributions and liquid water content of the cloud. Attention is focused on evaluating the relationship between cloud brightness, horizontal dimension, and internal microphysical structure. A Monte Carlo cloud model for finite clouds was run using different distributions of drop sizes and numbers, while varying the cloud 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 clouds of optical thickness between 20 and 60, monitoring cloud brightness changes in clouds of uniform depth and variable width gives adequate information about a cloud's liquid water content. A cloud having a 10:1 width to depth ratio is almost reaching its maximum brightness for a specified optical thickness.

  1. Alterations of Cloud Microphysics Due to Cloud Processed CCN

    NASA Astrophysics Data System (ADS)

    Hudson, J. G.; Tabor, S. S.; Noble, S. R., Jr.

    2015-12-01

    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 cloud processes that increase mass or hygroscopicity of only CCN that produced activated cloud 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 cloud processing minus NCCN within the lower Sc mode that was cloud processed. Lower, especially negative, Nu-Np designates greater processing. The table shows regressions between Nu-Np and characteristics of clouds 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 clouds closest to each CCN measurement, 75 ICE-T and 74 MASE cases. Nc is cloud droplet concentration, MD is cloud droplet mean diameter, σ is standard deviation of cloud droplet spectra, Ldis drizzle drop LWC. Two aircraft field campaigns, Ice in Clouds Experiment-Tropical (ICE-T) and Marine Stratus/Stratocumulus Experiment (MASE) show opposite R signs because coalescence dominated cloud 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 cloud cycles, which leads to lower MD and σ which reduce Ld (figure). These observations are consistent with cloud droplet growth models for the higher vertical wind (W) of cumuli and lower W of stratus. Coalescence thus reduces the indirect

  2. Cloud-cloud collision in the Galactic center 50 km s-1 molecular cloud

    NASA Astrophysics Data System (ADS)

    Tsuboi, Masato; Miyazaki, Atsushi; Uehara, Kenta

    2015-12-01

    We performed a search of star-forming sites influenced by external factors, such as SNRs, H II regions, and cloud-cloud 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 cloud; the HSF is a most conspicuous molecular cloud 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 cloud 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 cloud cores in the cloud. We made a cumulative core mass function (CMF) of the molecular cloud 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.

  3. Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3

    DOE PAGES

    Prather, M. J.

    2015-05-27

    A new approach for modeling photolysis rates ( J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud 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 » Cloud-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 cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.« less

  4. Galaxy CloudMan: delivering cloud compute clusters

    PubMed Central

    2010-01-01

    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 “cloud computing”, which, in principle, offers on demand access to flexible computational infrastructure. However, cloud computing resources are not yet suitable for immediate “as is” use by experimental biologists. Results We present a cloud resource management system that makes it possible for individual researchers to compose and control an arbitrarily sized compute cluster on Amazon’s EC2 cloud 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 cloud resources. This approach promotes reproducibility of results and, if desired, allows individuals and labs to add or customize an otherwise available cloud system to better meet their needs. Conclusions The expected knowledge and associated effort with deploying a compute cluster in the Amazon EC2 cloud 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

  5. Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

    NASA Technical Reports Server (NTRS)

    Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

    2007-01-01

    Cloud 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 cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud 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 clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud 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 cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for

  6. Formation of massive, dense cores by cloud-cloud collisions

    NASA Astrophysics Data System (ADS)

    Takahira, Ken; Shima, Kazuhiro; Habe, Asao; Tasker, Elizabeth J.

    2018-03-01

    We performed sub-parsec (˜ 0.014 pc) scale simulations of cloud-cloud collisions of two idealized turbulent molecular clouds (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 identified as pre-stellar cores and tracked through the simulation to investigate the effects of the mass of colliding clouds and the collision speeds on the resulting core population. Our results demonstrate that the smaller cloud property is more important for the results of cloud-cloud collisions. The mass function of formed cores can be approximated by a power-law relation with an index γ = -1.6 in slower cloud-cloud 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 clouds. 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.

  7. Formation of massive, dense cores by cloud-cloud collisions

    NASA Astrophysics Data System (ADS)

    Takahira, Ken; Shima, Kazuhiro; Habe, Asao; Tasker, Elizabeth J.

    2018-05-01

    We performed sub-parsec (˜ 0.014 pc) scale simulations of cloud-cloud collisions of two idealized turbulent molecular clouds (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 identified as pre-stellar cores and tracked through the simulation to investigate the effects of the mass of colliding clouds and the collision speeds on the resulting core population. Our results demonstrate that the smaller cloud property is more important for the results of cloud-cloud collisions. The mass function of formed cores can be approximated by a power-law relation with an index γ = -1.6 in slower cloud-cloud 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 clouds. 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.

  8. Improved Thin Cirrus and Terminator Cloud Detection in CERES Cloud Mask

    NASA Technical Reports Server (NTRS)

    Trepte, Qing; Minnis, Patrick; Palikonda, Rabindra; Spangenberg, Doug; Haeffelin, Martial

    2006-01-01

    Thin cirrus clouds account for about 20-30% of the total cloud coverage and affect the global radiation budget by increasing the Earth's albedo and reducing infrared emissions. Thin cirrus, however, are often underestimated by traditional satellite cloud detection algorithms. This difficulty is caused by the lack of spectral contrast between optically thin cirrus and the surface in techniques that use visible (0.65 micron ) and infrared (11 micron ) channels. In the Clouds and the Earth s Radiant Energy System (CERES) Aqua Edition 1 (AEd1) and Terra Edition 3 (TEd3) Cloud Masks, thin cirrus detection is significantly improved over both land and ocean using a technique that combines MODIS high-resolution measurements from the 1.38 and 11 micron channels and brightness temperature differences (BTDs) of 11-12, 8.5-11, and 3.7-11 micron channels. To account for humidity and view angle dependencies, empirical relationships were derived with observations from the 1.38 micron reflectance and the 11-12 and 8.5-11 micron BTDs using 70 granules of MODIS data in 2002 and 2003. Another challenge in global cloud detection algorithms occurs near the day/night terminator where information from the visible 0.65 micron channel and the estimated solar component of 3.7 micron channel becomes less reliable. As a result, clouds are often underestimated or misidentified near the terminator over land and ocean. Comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 N indicate significant amounts of missing clouds from CLAVR-x because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products (MOD06) and GLAS in the same region also show similar difficulties with MODIS cloud retrievals. The consistent detection of clouds through out the day is needed to provide reliable cloud and radiation products for CERES

  9. Cloud Collaboration: Cloud-Based Instruction for Business Writing Class

    ERIC Educational Resources Information Center

    Lin, Charlie; Yu, Wei-Chieh Wayne; Wang, Jenny

    2014-01-01

    Cloud computing technologies, such as Google Docs, Adobe Creative Cloud, Dropbox, and Microsoft Windows Live, have become increasingly appreciated to the next generation digital learning tools. Cloud computing technologies encourage students' active engagement, collaboration, and participation in their learning, facilitate group work, and support…

  10. The Oort cloud

    NASA Technical Reports Server (NTRS)

    Marochnik, Leonid S.; Mukhin, Lev M.; Sagdeev, Roald Z.

    1991-01-01

    Views of the large-scale structure of the solar system, consisting of the Sun, the nine planets and their satellites, changed when Oort demonstrated that a gigantic cloud of comets (the Oort cloud) is located on the periphery of the solar system. The following subject areas are covered: (1) the Oort cloud's mass; (2) Hill's cloud mass; (3) angular momentum distribution in the solar system; and (4) the cometary cloud around other stars.

  11. Comparison between SAGE II and ISCCP high-level clouds. 2: Locating clouds tops

    NASA Technical Reports Server (NTRS)

    Liao, Xiaohan; Rossow, William B.; Rind, David

    1995-01-01

    A comparison is made of the vertical distribution of high-level cloud tops derived from the Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation measurements and from the International Satellite Cloud Climatology Project (ISCCP) for all Julys and Januarys in 1985 to 1990. The results suggest that ISCCP overestimates the pressure of high-level clouds by up to 50-150 mbar, particularly at low latitudes. This is caused by the frequent presence of clouds with diffuse tops (greater than 50% time when cloudy events are observed). The averaged vertical extent of the diffuse top is about 1.5 km. At midlatitudes where the SAGE II and ISCCP cloud top pressure agree best, clouds with distinct tops reach a maximum relative proportion of the total level cloud amount (about 30-40%), and diffuse-topped clouds are reduced to their minimum (30-40%). The ISCCP-defined cloud top pressure should be regarded not as the material physical height of the clouds but as the level which emits the same infrared radiance as observed. SAGE II and ISCCP cloud top pressures agree for clouds with distinct tops. There is also an indication that the cloud top pressures of optically thin clouds not overlying thicker clouds are poorly estimated by ISCCP at middle latitudes. The average vertical extent of these thin clouds is about 2.5 km.

  12. Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

    NASA Technical Reports Server (NTRS)

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

    2015-01-01

    To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

  13. Cloud Size Distributions from Multi-sensor Observations of Shallow Cumulus Clouds

    NASA Astrophysics Data System (ADS)

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

    2017-12-01

    Combined radar-lidar observations have been used for almost two decades to document temporal changes of shallow cumulus clouds at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Facility's Southern Great Plains (SGP) site in Oklahoma, USA. Since the ARM zenith-pointed radars and lidars have a narrow field-of-view (FOV), the documented cloud statistics, such as distributions of cloud chord length (or horizontal length scale), represent only a slice along the wind direction of a region surrounding the SGP site, and thus may not be representative for this region. To investigate this impact, we compare cloud statistics obtained from wide-FOV sky images collected by ground-based observations at the SGP site to those from the narrow FOV active sensors. The main wide-FOV cloud statistics considered are cloud area distributions of shallow cumulus clouds, which are frequently required to evaluate model performance, such as routine large eddy simulation (LES) currently being conducted by the ARM LASSO (LES ARM Symbiotic Simulation and Observation) project. We obtain complementary macrophysical properties of shallow cumulus clouds, such as cloud chord length, base height and thickness, from the combined radar-lidar observations. To better understand the broader observational context where these narrow FOV cloud statistics occur, we compare them to collocated and coincident cloud area distributions from wide-FOV sky images and high-resolution satellite images. We discuss the comparison results and illustrate the possibility to generate a long-term climatology of cloud size distributions from multi-sensor observations at the SGP site.

  14. 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.

  15. 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.

  16. Limits to Cloud Susceptibility

    NASA Technical Reports Server (NTRS)

    Coakley, James A., Jr.

    2002-01-01

    1-kilometer AVHRR observations of ship tracks in low-level clouds off the west coast of the U S. were used to determine limits for the degree to which clouds might be altered by increases in anthropogenic aerosols. Hundreds of tracks were analyzed to determine whether the changes in droplet radii, visible optical depths, and cloud top altitudes that result from the influx of particles from underlying ships were consistent with expectations based on simple models for the indirect effect of aerosols. The models predict substantial increases in sunlight reflected by polluted clouds due to the increases in droplet numbers and cloud liquid water that result from the elevated particle concentrations. Contrary to the model predictions, the analysis of ship tracks revealed a 15-20% reduction in liquid water for the polluted clouds. Studies performed with a large-eddy cloud simulation model suggested that the shortfall in cloud liquid water found in the satellite observations might be attributed to the restriction that the 1-kilometer pixels be completely covered by either polluted or unpolluted cloud. The simulation model revealed that a substantial fraction of the indirect effect is caused by a horizontal redistribution of cloud water in the polluted clouds. Cloud-free gaps in polluted clouds fill in with cloud water while the cloud-free gaps in the surrounding unpolluted clouds remain cloud-free. By limiting the analysis to only overcast pixels, the current study failed to account for the gap-filling predicted by the simulation model. This finding and an analysis of the spatial variability of marine stratus suggest new ways to analyze ship tracks to determine the limit to which particle pollution will alter the amount of sunlight reflected by clouds.

  17. New Cloud Science from the New ARM Cloud Radar Systems (Invited)

    NASA Astrophysics Data System (ADS)

    Wiscombe, W. J.

    2010-12-01

    The DOE ARM Program is deploying over $30M worth of scanning polarimetric Doppler radars at its four fixed and two mobile sites, with the object of advancing cloud lifecycle science, and cloud-aerosol-precipitation interaction science, by a quantum leap. As of 2011, there will be 13 scanning radar systems to complement its existing array of profiling cloud radars: C-band for precipitation, X-band for drizzle and precipitation, and two-frequency radars for cloud droplets and drizzle. This will make ARM the world’s largest science user of, and largest provider of data from, ground-based cloud radars. The philosophy behind this leap is actually quite simple, to wit: dimensionality really does matter. Just as 2D turbulence is fundamentally different from 3D turbulence, so observing clouds only at zenith provides a dimensionally starved, and sometimes misleading, picture of real clouds. In particular, the zenith view can say little or nothing about cloud lifecycle and the second indirect effect, nor about aerosol-precipitation interactions. It is not even particularly good at retrieving the cloud fraction (no matter how that slippery quantity is defined). This talk will review the history that led to this development and then discuss the aspirations for how this will propel cloud-aerosol-precipitation science forward. The step by step plan for translating raw radar data into information that is useful to cloud and aerosol scientists and climate modelers will be laid out, with examples from ARM’s recent scanning cloud radar deployments in the Azores and Oklahoma . In the end, the new systems should allow cloud systems to be understood as 4D coherent entities rather than dimensionally crippled 2D or 3D entities such as observed by satellites and zenith-pointing radars.

  18. Screaming Clouds

    NASA Astrophysics Data System (ADS)

    Fikke, Svein; Egill Kristjánsson, Jón; Nordli, Øyvind

    2017-04-01

    "Mother-of-pearl clouds" appear irregularly in the winter stratosphere at high northern latitudes, about 20-30 km above the surface of the Earth. The size range of the cloud particles is near that of visible light, which explains their extraordinary beautiful colours. We argue that the Norwegian painter Edvard Munch could well have been terrified when the sky all of a sudden turned "bloodish red" after sunset, when darkness was expected. Hence, there is a high probability that it was an event of mother-of-pearl clouds which was the background for Munch's experience in nature, and for his iconic Scream. Currently, the leading hypothesis for explaining the dramatic colours of the sky in Munch's famous painting is that the artist was captivated by colourful sunsets following the enormous Krakatoa eruption in 1883. After carefully considering the historical accounts of some of Munch's contemporaries, especially the physicist Carl Störmer, we suggest an alternative hypothesis, namely that Munch was inspired by spectacular occurrences of mother-of-pearl clouds. Such clouds, which have a wave-like structure akin to that seen in the Scream were first observed and described only a few years before the first version of this motive was released in 1892. Unlike clouds related to conventional weather systems in the troposphere, mother-of-pearl clouds appear in the stratosphere, where significantly different physical conditions prevail. This result in droplet sizes within the range of visible light, creating the spectacular colour patterns these clouds are famous for. Carl Störmer observed such clouds, and described them in minute details at the age of 16, but already with a profound interest in science. He later noted that "..these mother-of-pearl clouds was a vision of indescribable beauty!" The authors find it logical that the same vision could appear scaring in the sensible mind of a young artist unknown to such phenomena.

  19. New insights about cloud vertical structure from CloudSat and CALIPSO observations

    NASA Astrophysics Data System (ADS)

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

    2017-09-01

    Active cloud observations from A-Train's CloudSat and CALIPSO satellites offer new opportunities to examine the vertical structure of hydrometeor layers. We use the 2B-CLDCLASS-LIDAR merged CloudSat-CALIPSO product to examine global aspects of hydrometeor vertical stratification. We group the data into major cloud vertical structure (CVS) classes based on our interpretation of how clouds in three standard atmospheric layers overlap and provide their global frequency of occurrence. The two most frequent CVS classes are single-layer (per our definition) low and high clouds that represent 53% of cloudy skies, followed by high clouds overlying low clouds, and vertically extensive clouds that occupy near-contiguously a large portion of the troposphere. The prevalence of these configurations changes seasonally and geographically, between daytime and nighttime, and between continents and oceans. The radiative effects of the CVS classes reveal the major radiative warmers and coolers from the perspective of the planet as a whole, the surface, and the atmosphere. Single-layer low clouds dominate planetary and atmospheric cooling and thermal infrared surface warming. We also investigate the consistency between passive and active views of clouds by providing the CVS breakdowns of Moderate Resolution Imaging Spectroradiometer cloud regimes for spatiotemporally coincident MODIS-Aqua (also on the A-Train) and CloudSat-CALIPSO daytime observations. When the analysis is expanded for a more in-depth look at the most heterogeneous of the MODIS cloud regimes, it ultimately confirms previous interpretations of their makeup that did not have the benefit of collocated active observations.

  20. 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.

  1. The role of orbital dynamics and cloud-cloud collisions in the formation of giant molecular clouds in global spiral structures

    NASA Technical Reports Server (NTRS)

    Roberts, William W., Jr.; Stewart, Glen R.

    1987-01-01

    The role of orbit crowding and cloud-cloud collisions in the formation of GMCs and their organization in global spiral structure is investigated. Both N-body simulations of the cloud system and a detailed analysis of individual particle orbits are used to develop a conceptual understanding of how individual clouds participate in the collective density response. Detailed comparisons are made between a representative cloud-particle simulation in which the cloud particles collide inelastically with one another and give birth to and subsequently interact with young star associations and stripped down simulations in which the cloud particles are allowed to follow ballistic orbits in the absence of cloud-cloud collisions or any star formation processes. Orbit crowding is then related to the behavior of individual particle trajectories in the galactic potential field. The conceptual picture of how GMCs are formed in the clumpy ISMs of spiral galaxies is formulated, and the results are compared in detail with those published by other authors.

  2. 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

  3. Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c

    DOE PAGES

    Prather, M. J.

    2015-08-14

    A new approach for modeling photolysis rates ( J values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations by four quadrature atmospheres produces mean J values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 %more » errors using simpler approximations. Cloud-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 cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections, is also incorporated into Cloud-J.« less

  4. Volcanic explosion clouds - Density, temperature, and particle content estimates from cloud motion

    NASA Technical Reports Server (NTRS)

    Wilson, L.; Self, S.

    1980-01-01

    Photographic records of 10 vulcanian eruption clouds produced during the 1978 eruption of Fuego Volcano in Guatemala have been analyzed to determine cloud velocity and acceleration at successive stages of expansion. Cloud motion is controlled by air drag (dominant during early, high-speed motion) and buoyancy (dominant during late motion when the cloud is convecting slowly). Cloud densities in the range 0.6 to 1.2 times that of the surrounding atmosphere were obtained by fitting equations of motion for two common cloud shapes (spheres and vertical cylinders) to the observed motions. Analysis of the heat budget of a cloud permits an estimate of cloud temperature and particle weight fraction to be made from the density. Model results suggest that clouds generally reached temperatures within 10 K of that of the surrounding air within 10 seconds of formation and that dense particle weight fractions were less than 2% by this time. The maximum sizes of dense particles supported by motion in the convecting clouds range from 140 to 1700 microns.

  5. Cloud microstructure studies

    NASA Technical Reports Server (NTRS)

    Blau, H. H., Jr.; Fowler, M. G.; Chang, D. T.; Ryan, R. T.

    1972-01-01

    Over two thousand individual cloud droplet size distributions were measured with an optical cloud particle spectrometer flown on the NASA Convair 990 aircraft. Representative droplet spectra and liquid water content, L (gm/cu m) were obtained for oceanic stratiform and cumuliform clouds. For non-precipitating clouds, values of L range from 0.1 gm/cu m to 0.5 gm/cu m; with precipitation, L is often greater than 1 gm/cu m. Measurements were also made in a newly formed contrail and in cirrus clouds.

  6. Diurnal and Seasonal Cloud Base Patterns Highlight Small-Mountain Tropical Cloud Forest Vulnerability

    NASA Astrophysics Data System (ADS)

    Van Beusekom, A.; Gonzalez, G.; Scholl, M. A.

    2016-12-01

    The degree to which cloud immersion sustains tropical montane cloud forests (TMCFs) during rainless periods and the amount these clouds are affected by urban areas is not well understood, as cloud base is rarely quantified near mountains. We found that a healthy small-mountain TMCF in Puerto Rico had lowest cloud base during the mid-summer dry season. In addition, we observed that cloud bases were lower than the mountaintops as often in the winter dry season as in the wet seasons, based on 2.5 years of direct and 16 years of indirect observations. The low clouds during dry season appear to be explained by proximity to the oceanic cloud system where lower clouds are seasonally invariant in altitude and cover; along with orographic lifting and trade-wind control over cloud formation. These results suggest that climate change impacts on small-mountain TMCFs may not be limited to the dry season; changes in regional-scale patterns that cause drought periods during the wet seasons will likely have higher cloud base, and thus may threaten cloud water support to sensitive mountain ecosystems. Strong El Niño's can cause drought in Puerto Rico; we will report results from the summer of 2015 that examined El Niño effects on cloud base altitudes. Looking at regionally collected airport cloud data, we see indicators that diurnal urban effects may already be raising the low cloud bases.

  7. Integrated Cloud-Aerosol-Radiation Product using CERES, MODIS, CALIPSO and CloudSat Data

    NASA Technical Reports Server (NTRS)

    Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave

    2007-01-01

    This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3- dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

  8. Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

    NASA Astrophysics Data System (ADS)

    Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

    2007-10-01

    This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

  9. Modeling Cloud Phase Fraction Based on In-situ Observations in Stratiform Clouds

    NASA Astrophysics Data System (ADS)

    Boudala, F. S.; Isaac, G. A.

    2005-12-01

    Mixed-phase clouds influence weather and climate in several ways. Due to the fact that they exhibit very different optical properties as compared to ice or liquid only clouds, they play an important role in the earth's radiation balance by modifying the optical properties of clouds. Precipitation development in clouds is also enhanced under mixed-phase conditions and these clouds may contain large supercooled drops that freeze quickly in contact with aircraft surfaces that may be a hazard to aviation. The existence of ice and liquid phase clouds together in the same environment is thermodynamically unstable, and thus they are expected to disappear quickly. However, several observations show that mixed-phase clouds are relatively stable in the natural environment and last for several hours. Although there have been some efforts being made in the past to study the microphysical properties of mixed-phase clouds, there are still a number of uncertainties in modeling these clouds particularly in large scale numerical models. In most models, very simple temperature dependent parameterizations of cloud phase fraction are being used to estimate the fraction of ice or liquid phase in a given mixed-phase cloud. In this talk, two different parameterizations of ice fraction using in-situ aircraft measurements of cloud microphysical properties collected in extratropical stratiform clouds during several field programs will be presented. One of the parameterizations has been tested using a single prognostic equation developed by Tremblay et al. (1996) for application in the Canadian regional weather prediction model. The addition of small ice particles significantly increased the vapor deposition rate when the natural atmosphere is assumed to be water saturated, and thus this enhanced the glaciation of simulated mixed-phase cloud via the Bergeron-Findeisen process without significantly affecting the other cloud microphysical processes such as riming and particle sedimentation

  10. Aerosol-cloud interactions in mixed-phase convective clouds - Part 1: Aerosol perturbations

    NASA Astrophysics Data System (ADS)

    Miltenberger, Annette K.; Field, Paul R.; Hill, Adrian A.; Rosenberg, Phil; Shipway, Ben J.; Wilkinson, Jonathan M.; Scovell, Robert; Blyth, Alan M.

    2018-03-01

    Changes induced by perturbed aerosol conditions in moderately deep mixed-phase convective clouds (cloud top height ˜ 5 km) developing along sea-breeze convergence lines are investigated with high-resolution numerical model simulations. The simulations utilise the newly developed Cloud-AeroSol Interacting Microphysics (CASIM) module for the Unified Model (UM), which allows for the representation of the two-way interaction between cloud and aerosol fields. Simulations are evaluated against observations collected during the COnvective Precipitation Experiment (COPE) field campaign over the southwestern peninsula of the UK in 2013. The simulations compare favourably with observed thermodynamic profiles, cloud base cloud droplet number concentrations (CDNC), cloud depth, and radar reflectivity statistics. Including the modification of aerosol fields by cloud microphysical processes improves the correspondence with observed CDNC values and spatial variability, but reduces the agreement with observations for average cloud size and cloud top height. Accumulated precipitation is suppressed for higher-aerosol conditions before clouds become organised along the sea-breeze convergence lines. Changes in precipitation are smaller in simulations with aerosol processing. The precipitation suppression is due to less efficient precipitation production by warm-phase microphysics, consistent with parcel model predictions. In contrast, after convective cells organise along the sea-breeze convergence zone, accumulated precipitation increases with aerosol concentrations. Condensate production increases with the aerosol concentrations due to higher vertical velocities in the convective cores and higher cloud top heights. However, for the highest-aerosol scenarios, no further increase in the condensate production occurs, as clouds grow into an upper-level stable layer. In these cases, the reduced precipitation efficiency (PE) dominates the precipitation response and no further

  11. 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.

  12. A cloud model simulation of space shuttle exhaust clouds in different atmospheric conditions

    NASA Technical Reports Server (NTRS)

    Chen, C.; Zak, J. A.

    1989-01-01

    A three-dimensional cloud model was used to characterize the dominant influence of the environment on the Space Shuttle exhaust cloud. The model was modified to accept the actual heat and moisture from rocket exhausts and deluge water as initial conditions. An upper-air sounding determined the ambient atmosphere in which the cloud could grow. The model was validated by comparing simulated clouds with observed clouds from four actual Shuttle launches. The model successfully produced clouds with dimensions, rise, decay, liquid water contents and vertical motion fields very similar to observed clouds whose dimensions were calculated from 16 mm film frames. Once validated, the model was used in a number of different atmospheric conditions ranging from very unstable to very stable. In moist, unstable atmospheres simulated clouds rose to about 3.5 km in the first 4 to 8 minutes then decayed. Liquid water contents ranged from 0.3 to 1.0 g kg-1 mixing ratios and vertical motions were from 2 to 10 ms-1. An inversion served both to reduce entrainment (and erosion) at the top and to prevent continued cloud rise. Even in the most unstable atmospheres, the ground cloud did not rise beyond 4 km and in stable atmospheres with strong low level inversions the cloud could be trapped below 500 m. Wind shear strongly affected the appearance of both the ground cloud and vertical column cloud. The ambient low-level atmospheric moisture governed the amount of cloud water in model clouds. Some dry atmospheres produced little or no cloud water. One case of a simulated TITAN rocket explosion is also discussed.

  13. Uncover the Cloud for Geospatial Sciences and Applications to Adopt Cloud Computing

    NASA Astrophysics Data System (ADS)

    Yang, C.; Huang, Q.; Xia, J.; Liu, K.; Li, J.; Xu, C.; Sun, M.; Bambacus, M.; Xu, Y.; Fay, D.

    2012-12-01

    Cloud computing is emerging as the future infrastructure for providing computing resources to support and enable scientific research, engineering development, and application construction, as well as work force education. On the other hand, there is a lot of doubt about the readiness of cloud computing to support a variety of scientific research, development and educations. This research is a project funded by NASA SMD to investigate through holistic studies how ready is the cloud computing to support geosciences. Four applications with different computing characteristics including data, computing, concurrent, and spatiotemporal intensities are taken to test the readiness of cloud computing to support geosciences. Three popular and representative cloud platforms including Amazon EC2, Microsoft Azure, and NASA Nebula as well as a traditional cluster are utilized in the study. Results illustrates that cloud is ready to some degree but more research needs to be done to fully implemented the cloud benefit as advertised by many vendors and defined by NIST. Specifically, 1) most cloud platform could help stand up new computing instances, a new computer, in a few minutes as envisioned, therefore, is ready to support most computing needs in an on demand fashion; 2) the load balance and elasticity, a defining characteristic, is ready in some cloud platforms, such as Amazon EC2, to support bigger jobs, e.g., needs response in minutes, while some are not ready to support the elasticity and load balance well. All cloud platform needs further research and development to support real time application at subminute level; 3) the user interface and functionality of cloud platforms vary a lot and some of them are very professional and well supported/documented, such as Amazon EC2, some of them needs significant improvement for the general public to adopt cloud computing without professional training or knowledge about computing infrastructure; 4) the security is a big concern in

  14. Community Cloud Computing

    NASA Astrophysics Data System (ADS)

    Marinos, Alexandros; Briscoe, Gerard

    Cloud Computing is rising fast, with its data centres growing at an unprecedented rate. However, this has come with concerns over privacy, efficiency at the expense of resilience, and environmental sustainability, because of the dependence on Cloud vendors such as Google, Amazon and Microsoft. Our response is an alternative model for the Cloud conceptualisation, providing a paradigm for Clouds in the community, utilising networked personal computers for liberation from the centralised vendor model. Community Cloud Computing (C3) offers an alternative architecture, created by combing the Cloud with paradigms from Grid Computing, principles from Digital Ecosystems, and sustainability from Green Computing, while remaining true to the original vision of the Internet. It is more technically challenging than Cloud Computing, having to deal with distributed computing issues, including heterogeneous nodes, varying quality of service, and additional security constraints. However, these are not insurmountable challenges, and with the need to retain control over our digital lives and the potential environmental consequences, it is a challenge we must pursue.

  15. Influence of Subpixel Scale Cloud Top Structure on Reflectances from Overcast Stratiform Cloud Layers

    NASA Technical Reports Server (NTRS)

    Loeb, N. G.; Varnai, Tamas; Winker, David M.

    1998-01-01

    Recent observational studies have shown that satellite retrievals of cloud optical depth based on plane-parallel model theory suffer from systematic biases that depend on viewing geometry, even when observations are restricted to overcast marine stratus layers, arguably the closest to plane parallel in nature. At moderate to low sun elevations, the plane-parallel model significantly overestimates the reflectance dependence on view angle in the forward-scattering direction but shows a similar dependence in the backscattering direction. Theoretical simulations are performed that show that the likely cause for this discrepancy is because the plane-parallel model assumption does not account for subpixel, scale variations in cloud-top height (i.e., "cloud bumps"). Monte Carlo simulation, comparing ID model radiances to radiances from overcast cloud field with 1) cloud-top height variation, but constant cloud volume extinction; 2) flat tops but horizontal variations in cloud volume extinction; and 3) variations in both cloud top height and cloud extinction are performed over a approximately equal to 4 km x 4 km domain (roughly the size of an individual GAC AVHRR pixel). The comparisons show that when cloud-top height variations are included, departures from 1D theory are remarkably similar (qualitatively) to those obtained observationally. In contrast, when clouds are assumed flat and only cloud extinction is variable, reflectance differences are much smaller and do not show any view-angle dependence. When both cloud-top height and cloud extinction variations are included, however, large increases in cloud extinction variability can enhance reflectance difference. The reason 3D-1D reflectance differences are more sensitive to cloud-top height variations in the forward-scattering direction (at moderate to low, sun elevations) is because photons leaving the cloud field in that direction experience fewer scattering events (low-order scattering) and are restricted to the

  16. Tropical High Cloud Fraction Controlled by Cloud Lifetime Rather Than Clear-sky Convergence

    NASA Astrophysics Data System (ADS)

    Seeley, J.; Jeevanjee, N.; Romps, D. M.

    2016-12-01

    Observations and simulations show a peak in cloud fraction below the tropopause. This peak is usually attributed to a roughly co-located peak in radiatively-driven clear-sky convergence, which is presumed to force convective detrainment and thus promote large cloud fraction. Using simulations of radiative-convective equilibrium forced by various radiative cooling profiles, we refute this mechanism by showing that an upper-tropospheric peak in cloud fraction persists even in simulations with no peak in clear-sky convergence. Instead, cloud fraction profiles seem to be controlled by cloud lifetimes — i.e., how long it takes for clouds to dissipate after they have detrained. A simple model of cloud evaporation shows that the small saturation deficit in the upper troposphere greatly extends cloud lifetimes there, while the large saturation deficit in the lower troposphere causes condensate to evaporate quickly. Since cloud mass flux must go to zero at the tropopause, a peak in cloud fraction emerges at a "sweet spot" below the tropopause where cloud lifetimes are long and there is still sufficient mass flux to be detrained.

  17. 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

  18. Cloud Resolving Modeling

    NASA Technical Reports Server (NTRS)

    Tao, Wei-Kuo

    2007-01-01

    One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with cloud-resolving models (CRMs). CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (with sizes ranging from about 2-200 km). CRMs also allow for explicit interaction between clouds, outgoing longwave (cooling) and incoming solar (heating) radiation, and ocean and land surface processes. Observations are required to initialize CRMs and to validate their results. This paper provides a brief discussion and review of the main characteristics of CRMs as well as some of their major applications. These include the use of CRMs to improve our understanding of: (1) convective organization, (2) cloud temperature and water vapor budgets, and convective momentum transport, (3) diurnal variation of precipitation processes, (4) radiative-convective quasi-equilibrium states, (5) cloud-chemistry interaction, (6) aerosol-precipitation interaction, and (7) improving moist processes in large-scale models. In addition, current and future developments and applications of CRMs will be presented.

  19. The Exoplanet Cloud Atlas

    NASA Astrophysics Data System (ADS)

    Gao, Peter; Marley, Mark S.; Morley, Caroline; Fortney, Jonathan J.

    2017-10-01

    Clouds have been readily inferred from observations of exoplanet atmospheres, and there exists great variability in cloudiness between planets, such that no clear trend in exoplanet cloudiness has so far been discerned. Equilibrium condensation calculations suggest a myriad of species - salts, sulfides, silicates, and metals - could condense in exoplanet atmospheres, but how they behave as clouds is uncertain. The behavior of clouds - their formation, evolution, and equilibrium size distribution - is controlled by cloud microphysics, which includes processes such as nucleation, condensation, and evaporation. In this work, we explore the cloudy exoplanet phase space by using a cloud microphysics model to simulate a suite of cloud species ranging from cooler condensates such as KCl/ZnS, to hotter condensates like perovskite and corundum. We investigate how the cloudiness and cloud particle sizes of exoplanets change due to variations in temperature, metallicity, gravity, and cloud formation mechanisms, and how these changes may be reflected in current and future observations. In particular, we will evaluate where in phase space could cloud spectral features be observable using JWST MIRI at long wavelengths, which will be dependent on the cloud particle size distribution and cloud species.

  20. Cloud4Psi: cloud computing for 3D protein structure similarity searching.

    PubMed

    Mrozek, Dariusz; Małysiak-Mrozek, Bożena; Kłapciński, Artur

    2014-10-01

    Popular methods for 3D protein structure similarity searching, especially those that generate high-quality alignments such as Combinatorial Extension (CE) and Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists (FATCAT) are still time consuming. As a consequence, performing similarity searching against large repositories of structural data requires increased computational resources that are not always available. Cloud computing provides huge amounts of computational power that can be provisioned on a pay-as-you-go basis. We have developed the cloud-based system that allows scaling of the similarity searching process vertically and horizontally. Cloud4Psi (Cloud for Protein Similarity) was tested in the Microsoft Azure cloud environment and provided good, almost linearly proportional acceleration when scaled out onto many computational units. Cloud4Psi is available as Software as a Service for testing purposes at: http://cloud4psi.cloudapp.net/. For source code and software availability, please visit the Cloud4Psi project home page at http://zti.polsl.pl/dmrozek/science/cloud4psi.htm. © The Author 2014. Published by Oxford University Press.

  1. Cloud4Psi: cloud computing for 3D protein structure similarity searching

    PubMed Central

    Mrozek, Dariusz; Małysiak-Mrozek, Bożena; Kłapciński, Artur

    2014-01-01

    Summary: Popular methods for 3D protein structure similarity searching, especially those that generate high-quality alignments such as Combinatorial Extension (CE) and Flexible structure Alignment by Chaining Aligned fragment pairs allowing Twists (FATCAT) are still time consuming. As a consequence, performing similarity searching against large repositories of structural data requires increased computational resources that are not always available. Cloud computing provides huge amounts of computational power that can be provisioned on a pay-as-you-go basis. We have developed the cloud-based system that allows scaling of the similarity searching process vertically and horizontally. Cloud4Psi (Cloud for Protein Similarity) was tested in the Microsoft Azure cloud environment and provided good, almost linearly proportional acceleration when scaled out onto many computational units. Availability and implementation: Cloud4Psi is available as Software as a Service for testing purposes at: http://cloud4psi.cloudapp.net/. For source code and software availability, please visit the Cloud4Psi project home page at http://zti.polsl.pl/dmrozek/science/cloud4psi.htm. Contact: dariusz.mrozek@polsl.pl PMID:24930141

  2. Lost in Cloud

    NASA Technical Reports Server (NTRS)

    Maluf, David A.; Shetye, Sandeep D.; Chilukuri, Sri; Sturken, Ian

    2012-01-01

    Cloud computing can reduce cost significantly because businesses can share computing resources. In recent years Small and Medium Businesses (SMB) have used Cloud effectively for cost saving and for sharing IT expenses. With the success of SMBs, many perceive that the larger enterprises ought to move into Cloud environment as well. Government agency s stove-piped environments are being considered as candidates for potential use of Cloud either as an enterprise entity or pockets of small communities. Cloud Computing is the delivery of computing as a service rather than as a product, whereby shared resources, software, and information are provided to computers and other devices as a utility over a network. Underneath the offered services, there exists a modern infrastructure cost of which is often spread across its services or its investors. As NASA is considered as an Enterprise class organization, like other enterprises, a shift has been occurring in perceiving its IT services as candidates for Cloud services. This paper discusses market trends in cloud computing from an enterprise angle and then addresses the topic of Cloud Computing for NASA in two possible forms. First, in the form of a public Cloud to support it as an enterprise, as well as to share it with the commercial and public at large. Second, as a private Cloud wherein the infrastructure is operated solely for NASA, whether managed internally or by a third-party and hosted internally or externally. The paper addresses the strengths and weaknesses of both paradigms of public and private Clouds, in both internally and externally operated settings. The content of the paper is from a NASA perspective but is applicable to any large enterprise with thousands of employees and contractors.

  3. Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

    NASA Technical Reports Server (NTRS)

    Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.

    2012-01-01

    The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.

  4. Parameterization of Cirrus Cloud Vertical Profiles and Geometrical Thickness Using CALIPSO and CloudSat Data

    NASA Astrophysics Data System (ADS)

    Khatri, P.; Iwabuchi, H.; Saito, M.

    2017-12-01

    High-level cirrus clouds, 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 clouds and their geometrical thickness are relatively poorer compared to low-level water clouds. Knowledge regarding cloud vertical structure is especially important in passive remote sensing of cloud properties using infrared channels or channels strongly influenced by gaseous absorption when clouds are geometrically thick and optically thin. Such information is also very useful for validating cloud resolving numerical models. This study analyzes global scale data of ice clouds identified by Cloud profiling Radar (CPR) onboard CloudSat and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO to parameterize (i) vertical profiles of ice water content (IWC), cloud-particle effective radius (CER), and ice-particle number concentration for varying ice water path (IWP) values and (ii) the relation of cloud geometrical thickness (CGT) with IWP and CER for varying cloud top temperature (CTT) values. It is found that the maxima in IWC and CER profile shifts towards cloud base with the increase of IWP. Similarly, if the cloud properties remain same, CGT shows an increasing trend with the decrease of CTT. The implementation of such cloud vertical inhomogeneity parameterization in the forward model used in the Integrated Cloud Analysis System ICAS (Iwabuchi et al., 2016) generally shows increase of brightness temperatures in infrared channels compared to vertically homogeneous cloud assumption. The cloud vertical inhomogeneity is found to bring noticeable changes in retrieved cloud properties. Retrieved CER and cloud top height become larger for optically thick cloud. We will show results of comparison of cloud properties retrieved from infrared measurements and active remote sensing.

  5. AstroCloud, a Cyber-Infrastructure for Astronomy Research: Cloud Computing Environments

    NASA Astrophysics Data System (ADS)

    Li, C.; Wang, J.; Cui, C.; He, B.; Fan, D.; Yang, Y.; Chen, J.; Zhang, H.; Yu, C.; Xiao, J.; Wang, C.; Cao, Z.; Fan, Y.; Hong, Z.; Li, S.; Mi, L.; Wan, W.; Wang, J.; Yin, S.

    2015-09-01

    AstroCloud is a cyber-Infrastructure for Astronomy Research initiated by Chinese Virtual Observatory (China-VO) under funding support from NDRC (National Development and Reform commission) and CAS (Chinese Academy of Sciences). Based on CloudStack, an open source software, we set up the cloud computing environment for AstroCloud Project. It consists of five distributed nodes across the mainland of China. Users can use and analysis data in this cloud computing environment. Based on GlusterFS, we built a scalable cloud storage system. Each user has a private space, which can be shared among different virtual machines and desktop systems. With this environments, astronomer can access to astronomical data collected by different telescopes and data centers easily, and data producers can archive their datasets safely.

  6. Comparison of cloud optical depth and cloud mask applying BRDF model-based background surface reflectance

    NASA Astrophysics Data System (ADS)

    Kim, H. W.; Yeom, J. M.; Woo, S. H.

    2017-12-01

    Over the thin cloud region, satellite can simultaneously detect the reflectance from thin clouds and land surface. Since the mixed reflectance is not the exact cloud information, the background surface reflectance should be eliminated to accurately distinguish thin cloud such as cirrus. In the previous research, Kim et al (2017) was developed the cloud masking algorithm using the Geostationary Ocean Color Imager (GOCI), which is one of significant instruments for Communication, Ocean, and Meteorology Satellite (COMS). Although GOCI has 8 spectral channels including visible and near infra-red spectral ranges, the cloud masking has quantitatively reasonable result when comparing with MODIS cloud mask (Collection 6 MYD35). Especially, we noticed that this cloud masking algorithm is more specialized in thin cloud detections through the validation with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. Because this cloud masking method was concentrated on eliminating background surface effects from the top-of-atmosphere (TOA) reflectance. Applying the difference between TOA reflectance and the bi-directional reflectance distribution function (BRDF) model-based background surface reflectance, cloud areas both thick cloud and thin cloud can be discriminated without infra-red channels which were mostly used for detecting clouds. Moreover, when the cloud mask result was utilized as the input data when simulating BRDF model and the optimized BRDF model-based surface reflectance was used for the optimized cloud masking, the probability of detection (POD) has higher value than POD of the original cloud mask. In this study, we examine the correlation between cloud optical depth (COD) and its cloud mask result. Cloud optical depths mostly depend on the cloud thickness, the characteristic of contents, and the size of cloud contents. COD ranges from less than 0.1 for thin clouds to over 1000 for the huge cumulus due to scattering by droplets. With

  7. Interpretation of multi-wavelength-retrieved cloud droplet effective radii in terms of cloud vertical inhomogeneity based on water cloud simulations using a spectral-bin microphysics cloud model

    NASA Astrophysics Data System (ADS)

    Matsui, T. N.; Suzuki, K.; Nakajima, T. Y.; Matsumae, Y.

    2011-12-01

    Clouds play an import role in energy balance and climate changes of the Earth. IPCC AR4, however, pointed out that cloud feedback is still the large source of uncertainty in climate estimates. In the recent decade, the new satellites with the active instruments (e.g. Cloudsat) represented a new epoch in earth observations. The active remote sensing is powerful for illustrating the vertical structures of clouds, but the passive remote sensing from satellite images also contribute to better understating of cloud system. For instance, Nakajima et al. (2010a) and Suzuki et al. (2010) illustrated transition of cloud growth, from cloud droplet to drizzle to rain, using the combine analysis of the cloud droplet size retrieved from passive images (MODIS) and the reflectivity profiles from Cloudsat. Furthermore, EarthCARE that is a new satellite launched years later is composed of not only the active but also passive instruments for the combined analysis. On the other hands, the methods to retrieve the advanced information of cloud properties are also required because many imagers have been operated and are now planned (e.g. GCOM-C/SGLI), and have the advantages such as wide observation width and more observation channels. Cloud droplet effective radius (CDR) and cloud optical thickness (COT) can be retrieved using a non-water-absorbing band (e.g. 0.86μm) and a water-absorbing band (1.6, 2.1, 3.7μm) of imagers under the assumptions such as the log-normal droplet size distribution and the plane-parallel cloud structure. However, the differences between three retrieved CDRs using 1.6, 2.1 or 3.7μm (R16, R21 and R37) are found in the satellite observations. Several studies pointed out that vertical/horizontal inhomogeneity of cloud structure, difference of penetration depth of water-absorbing bands, multi-modal droplet distribution and/or 3-D radiative transfer effect cause the CDR differences. In other words, the advanced information of clouds may lie hidden in the

  8. 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.

  9. Statistical Analyses of Satellite Cloud Object Data from CERES. Part III; Comparison with Cloud-Resolving Model Simulations of Tropical Convective Clouds

    NASA Technical Reports Server (NTRS)

    Luo, Yali; Xu, Kuan-Man; Wielicki, Bruce A.; Wong, Takmeng; Eitzen, Zachary A.

    2007-01-01

    The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds 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 cloud objects observed during March 1998 and between the large-size categories of cloud 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. Cloud 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 cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud 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 cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud 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 cloud top height while it overestimates the differences in the

  10. Cloud Computing Value Chains: Understanding Businesses and Value Creation in the Cloud

    NASA Astrophysics Data System (ADS)

    Mohammed, Ashraf Bany; Altmann, Jörn; Hwang, Junseok

    Based on the promising developments in Cloud Computing technologies in recent years, commercial computing resource services (e.g. Amazon EC2) or software-as-a-service offerings (e.g. Salesforce. com) came into existence. However, the relatively weak business exploitation, participation, and adoption of other Cloud Computing services remain the main challenges. The vague value structures seem to be hindering business adoption and the creation of sustainable business models around its technology. Using an extensive analyze of existing Cloud business models, Cloud services, stakeholder relations, market configurations and value structures, this Chapter develops a reference model for value chains in the Cloud. Although this model is theoretically based on porter's value chain theory, the proposed Cloud value chain model is upgraded to fit the diversity of business service scenarios in the Cloud computing markets. Using this model, different service scenarios are explained. Our findings suggest new services, business opportunities, and policy practices for realizing more adoption and value creation paths in the Cloud.

  11. Cloud vertical structure, precipitation, and cloud radiative effects over Tibetan Plateau

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Yan, Y.; Lu, J.

    2017-12-01

    The vertical structure of clouds and its connection with precipitation and cloud radiative effects (CRE) over the Tibetan Plateau (TP) are analyzed and compared with its neighboring land and tropical oceans based on CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) products and the Tropical Rainfall Measuring Mission (TRMM) precipitation data. Unique characteristics of cloud vertical structure and CRE over the TP are found. The cloud amount shows seasonal variation over the TP, which presents a single peak (located in 7-11 km) during January to April and two peaks (located in 5-8 km and 11-17 km separately) after mid-June, and then resumes to one peak (located in 5-10 km) after mid-August. Topography-induced restriction on moisture supply leads to a compression effect on clouds, i.e., the reduction in both cloud thickness and number of cloud layers, over the TP. The topography-induced compression effect is also shown in the range in the variation of cloud thickness and cloud-top height corresponding to different precipitation intensity, which is much smaller over the TP than its neighboring regions. In summer, cloud ice particles over the TP are mostly located at lower altitude (5-10 km) with richer variety of sizes and aggregation in no rain conditions compared to other regions. Ice water content becomes abundant and the number concentration tends to be dense at higher levels when precipitation is enhanced. The longwave CRE in the atmosphere over the TP is a net cooling effect. The vertical structure of CRE over the TP is unique compared to other regions: there exists a strong cooling layer of net CRE at the altitude of 8 km, from June to the beginning of October; the net radiative heating layer above the surface is shallower but stronger underneath 7 km and with a stronger seasonal variation over the TP.

  12. Cloud microphysical background for the Israel-4 cloud seeding experiment

    NASA Astrophysics Data System (ADS)

    Freud, Eyal; Koussevitzky, Hagai; Goren, Tom; Rosenfeld, Daniel

    2015-05-01

    The modest amount of rainfall in Israel occurs in winter storms that bring convective clouds from the Mediterranean Sea when the cold post frontal air interacts with its relatively warm surface. These clouds were seeded in the Israel-1 and Israel-2 cloud glaciogenic seeding experiments, which have shown statistically significant positive effect of added rainfall of at least 13% in northern Israel, whereas the Israel-3 experiment showed no added rainfall in the south. This was followed by operational seeding in the north since 1975. The lack of physical evidence for the causes of the positive effects in the north caused a lack of confidence in the statistical results and led to the Israel-4 randomized seeding experiment in northern Israel. This experiment started in the winter of 2013/14. The main difference from the previous experiments is the focus on the orographic clouds in the catchment of the Sea of Galilee. The decision to commence the experiment was partially based on evidence supporting the existence of seeding potential, which is reported here. Aircraft and satellite microphysical and dynamic measurements of the clouds document the critical roles of aerosols, especially sea spray, on cloud microstructure and precipitation forming processes. It was found that the convective clouds over sea and coastal areas are naturally seeded hygroscopically by sea spray and develop precipitation efficiently. The diminution of the large sea spray aerosols farther inland along with the increase in aerosol concentrations causes the clouds to develop precipitation more slowly. The short time available for the precipitation forming processes in super-cooled orographic clouds over the Golan Heights farthest inland represents the best glaciogenic seeding potential.

  13. Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

    DOE PAGES

    Yang, Fan; Luke, Edward P.; Kollias, Pavlos; ...

    2018-04-20

    Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

  14. Scaling of drizzle virga depth with cloud thickness for marine stratocumulus clouds

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

    Yang, Fan; Luke, Edward P.; Kollias, Pavlos

    Drizzle plays a crucial role in cloud lifetime and radiation properties of marine stratocumulus clouds. Understanding where drizzle exists in the sub-cloud layer, which depends on drizzle virga depth, can help us better understand where below-cloud scavenging and evaporative cooling and moisturizing occur. In this study, we examine the statistical properties of drizzle frequency and virga depth of marine stratocumulus based on unique ground-based remote sensing data. Results show that marine stratocumulus clouds are drizzling nearly all the time. In addition, we derive a simple scaling analysis between drizzle virga thickness and cloud thickness. Our analytical expression agrees with themore » observational data reasonable well, which suggests that our formula provides a simple parameterization for drizzle virga of stratocumulus clouds suitable for use in other models.« less

  15. Cloud and circulation feedbacks in a near-global aquaplanet cloud-resolving model

    DOE PAGES

    Narenpitak, Pornampai; Bretherton, Christopher S.; Khairoutdinov, Marat F.

    2017-05-08

    A near-global aquaplanet cloud-resolving model (NGAqua) with fixed meridionally varying sea-surface temperature (SST) is used to investigate cloud feedbacks due to three climate perturbations: a uniform 4 K SST increase, a quadrupled-CO2 concentration, and both combined. NGAqua has a horizontal resolution of 4 km with no cumulus parameterization. Its domain is a zonally periodic 20,480 km-long tropical channel, spanning 46°S–N. It produces plausible mean distributions of clouds, rainfall, and winds. After spin-up, 80 days are analyzed for the control and increased-SST simulations, and 40 days for those with quadrupled CO 2. The Intertropical Convergence Zone width and tropical cloud covermore » are not strongly affected by SST warming or CO 2 increase, except for the expected upward shift in high clouds with warming, but both perturbations weaken the Hadley circulation. Increased SST induces a statistically significant increase in subtropical low cloud fraction and in-cloud liquid water content but decreases midlatitude cloud, yielding slightly positive domain-mean shortwave cloud feedbacks. CO 2 quadrupling causes a slight shallowing and a statistically insignificant reduction of subtropical low cloud fraction. Warming-induced low cloud changes are strongly correlated with changes in estimated inversion strength, which increases modestly in the subtropics but decreases in the midlatitudes. Enhanced clear-sky boundary layer radiative cooling in the warmer climate accompanies the robust subtropical low cloud increase. The probability distribution of column relative humidity across the tropics and subtropics is compared between the control and increased-SST simulations. It shows no evidence of bimodality or increased convective aggregation in a warmer climate.« less

  16. Cloud and circulation feedbacks in a near-global aquaplanet cloud-resolving model

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

    Narenpitak, Pornampai; Bretherton, Christopher S.; Khairoutdinov, Marat F.

    A near-global aquaplanet cloud-resolving model (NGAqua) with fixed meridionally varying sea-surface temperature (SST) is used to investigate cloud feedbacks due to three climate perturbations: a uniform 4 K SST increase, a quadrupled-CO2 concentration, and both combined. NGAqua has a horizontal resolution of 4 km with no cumulus parameterization. Its domain is a zonally periodic 20,480 km-long tropical channel, spanning 46°S–N. It produces plausible mean distributions of clouds, rainfall, and winds. After spin-up, 80 days are analyzed for the control and increased-SST simulations, and 40 days for those with quadrupled CO 2. The Intertropical Convergence Zone width and tropical cloud covermore » are not strongly affected by SST warming or CO 2 increase, except for the expected upward shift in high clouds with warming, but both perturbations weaken the Hadley circulation. Increased SST induces a statistically significant increase in subtropical low cloud fraction and in-cloud liquid water content but decreases midlatitude cloud, yielding slightly positive domain-mean shortwave cloud feedbacks. CO 2 quadrupling causes a slight shallowing and a statistically insignificant reduction of subtropical low cloud fraction. Warming-induced low cloud changes are strongly correlated with changes in estimated inversion strength, which increases modestly in the subtropics but decreases in the midlatitudes. Enhanced clear-sky boundary layer radiative cooling in the warmer climate accompanies the robust subtropical low cloud increase. The probability distribution of column relative humidity across the tropics and subtropics is compared between the control and increased-SST simulations. It shows no evidence of bimodality or increased convective aggregation in a warmer climate.« less

  17. Spectral Dependence of MODIS Cloud Droplet Effective Radius Retrievals for Marine Boundary Layer Clouds

    NASA Technical Reports Server (NTRS)

    Zhang, Zhibo; Platnick, Steven E.; Ackerman, Andrew S.; Cho, Hyoun-Myoung

    2014-01-01

    Low-level warm marine boundary layer (MBL) clouds cover large regions of Earth's surface. They have a significant role in Earth's radiative energy balance and hydrological cycle. Despite the fundamental role of low-level warm water clouds in climate, our understanding of these clouds is still limited. In particular, connections between their properties (e.g. cloud fraction, cloud water path, and cloud droplet size) and environmental factors such as aerosol loading and meteorological conditions continue to be uncertain or unknown. Modeling these clouds in climate models remains a challenging problem. As a result, the influence of aerosols on these clouds in the past and future, and the potential impacts of these clouds on global warming remain open questions leading to substantial uncertainty in climate projections. To improve our understanding of these clouds, we need continuous observations of cloud properties on both a global scale and over a long enough timescale for climate studies. At present, satellite-based remote sensing is the only means of providing such observations.

  18. Risk in the Clouds?: Security Issues Facing Government Use of Cloud Computing

    NASA Astrophysics Data System (ADS)

    Wyld, David C.

    Cloud computing is poised to become one of the most important and fundamental shifts in how computing is consumed and used. Forecasts show that government will play a lead role in adopting cloud computing - for data storage, applications, and processing power, as IT executives seek to maximize their returns on limited procurement budgets in these challenging economic times. After an overview of the cloud computing concept, this article explores the security issues facing public sector use of cloud computing and looks to the risk and benefits of shifting to cloud-based models. It concludes with an analysis of the challenges that lie ahead for government use of cloud resources.

  19. GIANT MOLECULAR CLOUD FORMATION IN DISK GALAXIES: CHARACTERIZING SIMULATED VERSUS OBSERVED CLOUD CATALOGS

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

    Benincasa, Samantha M.; Pudritz, Ralph E.; Wadsley, James

    We present the results of a study of simulated giant molecular clouds (GMCs) formed in a Milky Way-type galactic disk with a flat rotation curve. This simulation, which does not include star formation or feedback, produces clouds with masses ranging between 10{sup 4} M{sub ☉} and 10{sup 7} M{sub ☉}. We compare our simulated cloud 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 cloud properties as well as a comparison of Larson's scaling relations is carried out. We find that simulatedmore » cloud properties agree well with the observed cloud properties, with the closest agreement occurring between the clouds at comparable resolution in M33. Our clouds are highly filamentary—a property that derives both from their formation due to gravitational instability in the sheared galactic environment, as well as to cloud-cloud 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 clouds of roughly 10{sup 6} M{sub ☉}. This suggests that star formation rates in observed clouds are related to the rates at which gas can be accumulated into dense subregions within GMCs via filamentary flows. The most internally well-resolved clouds are chosen for listing in a catalog of simulated GMCs—the first of its kind. The cataloged clouds are available as an extracted data set from the global simulation.« less

  20. The Influence of Aerosols on the Shortwave Cloud Radiative Forcing from North Pacific Oceanic Clouds: Results from the Cloud Indirect Forcing Experiment (CIFEX)

    NASA Technical Reports Server (NTRS)

    Wilcox, Eric M.; Roberts, Greg; Ramanathan, V.

    2006-01-01

    Aerosols over the Northeastern Pacific Ocean enhance the cloud drop number concentration and reduce the drop size for marine stratocumulus and cumulus clouds. These microphysical effects result in brighter clouds, as evidenced by a combination of aircraft and satellite observations. In-situ measurements from the Cloud Indirect Forcing Experiment (CIFEX) indicate that the mean cloud drop number concentration in low clouds over the polluted marine boundary layer is greater by 53/cu cm compared to clean clouds, and the mean cloud drop effective radius is smaller by 4 microns. We link these in-situ measurements of cloud modification by aerosols, for the first time, with collocated satellite broadband radiative flux observations from the Clouds and the Earth's Radiant Energy System (CERES) to show that these microphysical effects of aerosols enhance the top-of-atmosphere cooling by -9.9+/-4.3 W/sq m for overcast conditions.

  1. Climate Cloud Height

    Atmospheric Science Data Center

    2017-11-27

    article title:  Is Climate Changing Cloud Heights? Too Soon to Say Climate change may eventually change global cloud heights, but scientists need ... whether that's happening already. For details see: Is Climate Changing Cloud Heights? Too Soon to Say . Climate ...

  2. Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

    NASA Technical Reports Server (NTRS)

    Uttal, Taneil; Frisch, Shelby; Wang, Xuan-Ji; Key, Jeff; Schweiger, Axel; Sun-Mack, Sunny; Minnis, Patrick

    2005-01-01

    A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

  3. Star formation induced by cloud-cloud collisions and galactic giant molecular cloud evolution

    NASA Astrophysics Data System (ADS)

    Kobayashi, Masato I. N.; Kobayashi, Hiroshi; Inutsuka, Shu-ichiro; Fukui, Yasuo

    2018-05-01

    Recent millimeter/submillimeter observations towards nearby galaxies have started to map the whole disk and to identify giant molecular clouds (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 clouds, Kobayashi et al. (2017, ApJ, 836, 175) proposes a semi-analytical evolutionary description for GMC mass functions including a cloud-cloud 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 clouds. Our results suggest that, although CCC events between smaller clouds 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.

  4. 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.

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

    NASA Technical Reports Server (NTRS)

    Sharon, Tarah M.; Albrecht, Bruce A.; Jonsson, Haflidi H.; Minnis, Patrick; Khaiyer, Mandana M.; Van Reken, Timothy; Seinfeld, John; Flagan, Rick

    2008-01-01

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

  6. A cloud-resolving model study of aerosol-cloud correlation in a pristine maritime environment

    NASA Astrophysics Data System (ADS)

    Nishant, Nidhi; Sherwood, Steven C.

    2017-06-01

    In convective clouds, satellite-observed deepening or increased amount of clouds with increasing aerosol concentration has been reported and is sometimes interpreted as aerosol-induced invigoration of the clouds. However, such correlations can be affected by meteorological factors that affect both aerosol and clouds, as well as observational issues. In this study, we examine the behavior in a 660 × 660 km2 region of the South Pacific during June 2007, previously found by Koren et al. (2014) to show strong correlation between cloud fraction, cloud top pressure, and aerosols, using a cloud-resolving model with meteorological boundary conditions specified from a reanalysis. The model assumes constant aerosol loading, yet reproduces vigorous clouds at times of high real-world aerosol concentrations. Days with high- and low-aerosol loading exhibit deep-convective and shallow clouds, respectively, in both observations and the simulation. Synoptic analysis shows that vigorous clouds occur at times of strong surface troughs, which are associated with high winds and advection of boundary layer air from the Southern Ocean where sea-salt aerosol is abundant, thus accounting for the high correlation. Our model results show that aerosol-cloud relationships can be explained by coexisting but independent wind-aerosol and wind-cloud relationships and that no cloud condensation nuclei effect is required.

  7. Marine cloud brightening – as effective without clouds

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

    Ahlm, Lars; Jones, Andy; Stjern, Camilla W.

    Marine cloud brightening through sea spray injection has been proposed as a climate engineering method for avoiding the most severe consequences of global warming. A limitation of most of the previous modelling studies on marine cloud brightening is that they have either considered individual models or only investigated the effects of a specific increase in the number of cloud droplets. Here we present results from coordinated simulations with three Earth system models (ESMs) participating in the Geoengineering Model Intercomparison Project (GeoMIP) G4sea-salt experiment. Injection rates of accumulation-mode sea spray aerosol particles over ocean between 30°N and 30°S are set in each model tomore » generate a global-mean effective radiative forcing (ERF) of –2.0 W m –2 at the top of the atmosphere. We find that the injection increases the cloud droplet number concentration in lower layers, reduces the cloud-top effective droplet radius, and increases the cloud optical depth over the injection area. We also find, however, that the global-mean clear-sky ERF by the injected particles is as large as the corresponding total ERF in all three ESMs, indicating a large potential of the aerosol direct effect in regions of low cloudiness. The largest enhancement in ERF due to the presence of clouds occur as expected in the subtropical stratocumulus regions off the west coasts of the American and African continents. However, outside these regions, the ERF is in general equally large in cloudy and clear-sky conditions. Lastly, these findings suggest a more important role of the aerosol direct effect in sea spray climate engineering than previously thought.« less

  8. Marine cloud brightening – as effective without clouds

    DOE PAGES

    Ahlm, Lars; Jones, Andy; Stjern, Camilla W.; ...

    2017-11-06

    Marine cloud brightening through sea spray injection has been proposed as a climate engineering method for avoiding the most severe consequences of global warming. A limitation of most of the previous modelling studies on marine cloud brightening is that they have either considered individual models or only investigated the effects of a specific increase in the number of cloud droplets. Here we present results from coordinated simulations with three Earth system models (ESMs) participating in the Geoengineering Model Intercomparison Project (GeoMIP) G4sea-salt experiment. Injection rates of accumulation-mode sea spray aerosol particles over ocean between 30°N and 30°S are set in each model tomore » generate a global-mean effective radiative forcing (ERF) of –2.0 W m –2 at the top of the atmosphere. We find that the injection increases the cloud droplet number concentration in lower layers, reduces the cloud-top effective droplet radius, and increases the cloud optical depth over the injection area. We also find, however, that the global-mean clear-sky ERF by the injected particles is as large as the corresponding total ERF in all three ESMs, indicating a large potential of the aerosol direct effect in regions of low cloudiness. The largest enhancement in ERF due to the presence of clouds occur as expected in the subtropical stratocumulus regions off the west coasts of the American and African continents. However, outside these regions, the ERF is in general equally large in cloudy and clear-sky conditions. Lastly, these findings suggest a more important role of the aerosol direct effect in sea spray climate engineering than previously thought.« less

  9. Quantitative Measures of Immersion in Cloud and the Biogeography of Cloud Forests

    NASA Technical Reports Server (NTRS)

    Lawton, R. O.; Nair, U. S.; Ray, D.; Regmi, A.; Pounds, J. A.; Welch, R. M.

    2010-01-01

    Sites described as tropical montane cloud forests differ greatly, in part because observers tend to differ in their opinion as to what constitutes frequent and prolonged immersion in cloud. This definitional difficulty interferes with hydrologic analyses, assessments of environmental impacts on ecosystems, and biogeographical analyses of cloud forest communities and species. Quantitative measurements of cloud immersion can be obtained on site, but the observations are necessarily spatially limited, although well-placed observers can examine 10 50 km of a mountain range under rainless conditions. Regional analyses, however, require observations at a broader scale. This chapter discusses remote sensing and modeling approaches that can provide quantitative measures of the spatiotemporal patterns of cloud cover and cloud immersion in tropical mountain ranges. These approaches integrate remote sensing tools of various spatial resolutions and frequencies of observation, digital elevation models, regional atmospheric models, and ground-based observations to provide measures of cloud cover, cloud base height, and the intersection of cloud and terrain. This combined approach was applied to the Monteverde region of northern Costa Rica to illustrate how the proportion of time the forest is immersed in cloud may vary spatially and temporally. The observed spatial variation was largely due to patterns of airflow over the mountains. The temporal variation reflected the diurnal rise and fall of the orographic cloud base, which was influenced in turn by synoptic weather conditions, the seasonal movement of the Intertropical Convergence Zone and the north-easterly trade winds. Knowledge of the proportion of the time that sites are immersed in clouds should facilitate ecological comparisons and biogeographical analyses, as well as land use planning and hydrologic assessments in areas where intensive on-site work is not feasible.

  10. Cloud/climate sensitivity experiments

    NASA Technical Reports Server (NTRS)

    Roads, J. O.; Vallis, G. K.; Remer, L.

    1982-01-01

    A study of the relationships between large-scale cloud fields and large scale circulation patterns is presented. The basic tool is a multi-level numerical model comprising conservation equations for temperature, water vapor and cloud water and appropriate parameterizations for evaporation, condensation, precipitation and radiative feedbacks. Incorporating an equation for cloud water in a large-scale model is somewhat novel and allows the formation and advection of clouds to be treated explicitly. The model is run on a two-dimensional, vertical-horizontal grid with constant winds. It is shown that cloud cover increases with decreased eddy vertical velocity, decreased horizontal advection, decreased atmospheric temperature, increased surface temperature, and decreased precipitation efficiency. The cloud field is found to be well correlated with the relative humidity field except at the highest levels. When radiative feedbacks are incorporated and the temperature increased by increasing CO2 content, cloud amounts decrease at upper-levels or equivalently cloud top height falls. This reduces the temperature response, especially at upper levels, compared with an experiment in which cloud cover is fixed.

  11. JINR cloud infrastructure evolution

    NASA Astrophysics Data System (ADS)

    Baranov, A. V.; Balashov, N. A.; Kutovskiy, N. A.; Semenov, R. N.

    2016-09-01

    To fulfil JINR commitments in different national and international projects related to the use of modern information technologies such as cloud and grid computing as well as to provide a modern tool for JINR users for their scientific research a cloud infrastructure was deployed at Laboratory of Information Technologies of Joint Institute for Nuclear Research. OpenNebula software was chosen as a cloud platform. Initially it was set up in simple configuration with single front-end host and a few cloud nodes. Some custom development was done to tune JINR cloud installation to fit local needs: web form in the cloud web-interface for resources request, a menu item with cloud utilization statistics, user authentication via Kerberos, custom driver for OpenVZ containers. Because of high demand in that cloud service and its resources over-utilization it was re-designed to cover increasing users' needs in capacity, availability and reliability. Recently a new cloud instance has been deployed in high-availability configuration with distributed network file system and additional computing power.

  12. Evaluating Clouds in Long-Term Cloud-Resolving Model Simulations with Observational Data

    NASA Technical Reports Server (NTRS)

    Zeng, Xiping; Tao, Wei-Kuo; Zhang, Minghua; Peters-Lidard, Christa; Lang, Stephen; Simpson, Joanne; Kumar, Sujay; Xie, Shaocheng; Eastman, Joseph L.; Shie, Chung-Lin; hide

    2006-01-01

    Two 20-day, continental midlatitude cases are simulated with a three-dimensional (3D) cloud-resolving model (CRM) and compared to Atmospheric Radiation Measurement (ARM) data. This evaluation of long-term cloud-resolving model simulations focuses on the evaluation of clouds and surface fluxes. All numerical experiments, as compared to observations, simulate surface precipitation well but over-predict clouds, especially in the upper troposphere. The sensitivity of cloud properties to dimensionality and other factors is studied to isolate the origins of the over prediction of clouds. Due to the difference in buoyancy damping between 2D and 3D models, surface precipitation fluctuates rapidly with time, and spurious dehumidification occurs near the tropopause in the 2D CRM. Surface fluxes from a land data assimilation system are compared with ARM observations. They are used in place of the ARM surface fluxes to test the sensitivity of simulated clouds to surface fluxes. Summertime simulations show that surface fluxes from the assimilation system bring about a better simulation of diurnal cloud variation in the lower troposphere.

  13. Cloud fraction and cloud base measurements from scanning Doppler lidar during WFIP-2

    NASA Astrophysics Data System (ADS)

    Bonin, T.; Long, C.; Lantz, K. O.; Choukulkar, A.; Pichugina, Y. L.; McCarty, B.; Banta, R. M.; Brewer, A.; Marquis, M.

    2017-12-01

    The second Wind Forecast Improvement Project (WFIP-2) consisted of an 18-month field deployment of a variety of instrumentation with the principle objective of validating and improving NWP forecasts for wind energy applications in complex terrain. As a part of the set of instrumentation, several scanning Doppler lidars were installed across the study domain to primarily measure profiles of the mean wind and turbulence at high-resolution within the planetary boundary layer. In addition to these measurements, Doppler lidar observations can be used to directly quantify the cloud fraction and cloud base, since clouds appear as a high backscatter return. These supplementary measurements of clouds can then be used to validate cloud cover and other properties in NWP output. Herein, statistics of the cloud fraction and cloud base height from the duration of WFIP-2 are presented. Additionally, these cloud fraction estimates from Doppler lidar are compared with similar measurements from a Total Sky Imager and Radiative Flux Analysis (RadFlux) retrievals at the Wasco site. During mostly cloudy to overcast conditions, estimates of the cloud radiating temperature from the RadFlux methodology are also compared with Doppler lidar measured cloud base height.

  14. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

    PubMed Central

    Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; Pöhlker, Mira L.; Jefferson, Anne; Pöhlker, Christopher; Yu, Xing; Zhu, Yannian; Liu, Guihua; Yue, Zhiguo; Fischman, Baruch; Li, Zhanqing; Giguzin, David; Goren, Tom; Artaxo, Paulo; Pöschl, Ulrich

    2016-01-01

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day. PMID:26944081

  15. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers.

    PubMed

    Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; Pöhlker, Mira L; Jefferson, Anne; Pöhlker, Christopher; Yu, Xing; Zhu, Yannian; Liu, Guihua; Yue, Zhiguo; Fischman, Baruch; Li, Zhanqing; Giguzin, David; Goren, Tom; Artaxo, Paulo; Barbosa, Henrique M J; Pöschl, Ulrich; Andreae, Meinrat O

    2016-05-24

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day.

  16. 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

  17. The relationships among cloud microphysics, chemistry, and precipitation rate in cold mountain clouds

    NASA Astrophysics Data System (ADS)

    Borys, Randolph D.; Lowenthal, Douglas H.; Mitchell, David L.

    A study was conducted to examine the relationships among air pollutant loadings, cloud microphysics, and snowfall rates in cold mountain clouds. It was hypothesized that variations in pollutant loadings would be reflected in shifts in the cloud droplet size distribution. A field program was conducted at Storm Peak Laboratory (SPL) at an elevation of 3210 m MSL in northwestern Colorado. Cold precipitating clouds were sampled during January, 1995. Cloud water was collected and analyzed for major ion and trace element chemistry. Cloud droplet concentrations and size were measured continuously using a PMS FSSP-100. The results indicate a direct relationship between clear-air equivalent (CAE) sulfate concentrations in cloud water and cloud droplet concentrations, an indirect relationship between droplet number and droplet size, a direct relationship between droplet size and snowfall rate, and an indirect relationship between CAE sulfate concentration and snowfall rate.

  18. Fresh clouds: A parameterized updraft method for calculating cloud densities in one-dimensional models

    NASA Astrophysics Data System (ADS)

    Wong, Michael H.; Atreya, Sushil K.; Kuhn, William R.; Romani, Paul N.; Mihalka, Kristen M.

    2015-01-01

    Models of cloud condensation under thermodynamic equilibrium in planetary atmospheres are useful for several reasons. These equilibrium cloud condensation models (ECCMs) calculate the wet adiabatic lapse rate, determine saturation-limited mixing ratios of condensing species, calculate the stabilizing effect of latent heat release and molecular weight stratification, and locate cloud base levels. Many ECCMs trace their heritage to Lewis (Lewis, J.S. [1969]. Icarus 10, 365-378) and Weidenschilling and Lewis (Weidenschilling, S.J., Lewis, J.S. [1973]. Icarus 20, 465-476). Calculation of atmospheric structure and gas mixing ratios are correct in these models. We resolve errors affecting the cloud density calculation in these models by first calculating a cloud density rate: the change in cloud density with updraft length scale. The updraft length scale parameterizes the strength of the cloud-forming updraft, and converts the cloud density rate from the ECCM into cloud density. The method is validated by comparison with terrestrial cloud data. Our parameterized updraft method gives a first-order prediction of cloud densities in a “fresh” cloud, where condensation is the dominant microphysical process. Older evolved clouds may be better approximated by another 1-D method, the diffusive-precipitative Ackerman and Marley (Ackerman, A.S., Marley, M.S. [2001]. Astrophys. J. 556, 872-884) model, which represents a steady-state equilibrium between precipitation and condensation of vapor delivered by turbulent diffusion. We re-evaluate observed cloud densities in the Galileo Probe entry site (Ragent, B. et al. [1998]. J. Geophys. Res. 103, 22891-22910), and show that the upper and lower observed clouds at ∼0.5 and ∼3 bars are consistent with weak (cirrus-like) updrafts under conditions of saturated ammonia and water vapor, respectively. The densest observed cloud, near 1.3 bar, requires unexpectedly strong updraft conditions, or higher cloud density rates. The cloud

  19. Multidecadal Changes in Near-Global Cloud Cover and Estimated Cloud Cover Radiative Forcing

    NASA Technical Reports Server (NTRS)

    Norris, Joel

    2005-01-01

    The first paper was Multidecadal changes in near-global cloud cover and estimated cloud 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 cloud 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 Cloud Report Archive (EECRA). Although substantial interdecadal variability is present in the time series, long-term decreases in upper-level cloud cover occur over land and ocean at low and middle latitudes in both hemispheres. Near-global upper-level cloud 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 cloud cover anomalies and those from the International Satellite Cloud Climatology Project (ISCCP) during 1984-1 997 suggests the surface-observed trends are real. The reduction in surface-observed upper-level cloud 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 cloud cover due to identified and probable artifacts in satellite and surface cloud data. Radiative effects of surface-observed cloud cover anomalies, called "cloud cover radiative forcing (CCRF) anomalies," are estimated based on a linear relationship to climatological cloud radiative forcing per unit cloud 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

  20. ATLAS Cloud R&D

    NASA Astrophysics Data System (ADS)

    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

    2014-06-01

    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 cloud computing technologies bring attractive features to improve the operations and elasticity of scientific distributed computing. ATLAS sees grid and cloud 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 Cloud Computing R&D has been able to demonstrate the feasibility of offloading work from grid to cloud sites and, as of today, is able to integrate transparently various cloud resources into the PanDA workload management system. The ATLAS Cloud 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 Cloud Computing R&D group has gained a significant insight into the cloud computing landscape and has identified points that still need to be addressed in order to fully utilize this technology. This contribution will explain the cloud integration models that are being evaluated and will discuss ATLAS' learning during the collaboration with leading commercial and academic cloud providers.

  1. Entrainment and cloud evaporation deduced from the stable isotope chemistry of clouds during ORACLES

    NASA Astrophysics Data System (ADS)

    Noone, D.; Henze, D.; Rainwater, B.; Toohey, D. W.

    2017-12-01

    The magnitude of the influence of biomass burning aerosols on cloud 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 cloud-aerosol interactions in models and the resulting cloud radiative forcing. Interaction between cloud and the regional atmosphere causes evaporation, and the rate of evaporation at cloud top is controlled in part by entrainment of air from above which exposes saturated cloud air to drier conditions. Similarly, the size of cloud droplets also controls evaporation rates, which in turn is linked to the abundance of condensation nuclei. To quantify the dependence of cloud properties on biomass burning aerosols the dynamic relationship between evaporation, drop size and entrainment on aerosol state, is evaluated for stratiform clouds in the southeast Atlantic Ocean. These clouds are seasonally exposed to biomass burning plumes from agricultural fires in southern Africa. Measurements of the stable isotope ratios of cloud water and total water are used to deduce the disequilibrium responsible for evaporation within clouds. Disequilibrium is identified by the relationship between hydrogen and oxygen isotope ratios of water vapor and cloud water in and near clouds. 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 Clouds and their Interactions (ORACLES) campaign. The sampling system obtains both total water and cloud 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.

  2. CloudSat-Constrained Cloud Ice Water Path and Cloud Top Height Retrievals from MHS 157 and 183.3 GHz Radiances

    NASA Technical Reports Server (NTRS)

    Gong, J.; Wu, D. L.

    2014-01-01

    Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3+/-3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a lookup table (LUT) of Tcir-IWP relationships as a function of ht and the frequency channel.With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg/sq m, and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir-IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

  3. Cloud Computing for radiologists.

    PubMed

    Kharat, Amit T; Safvi, Amjad; Thind, Ss; Singh, Amarjit

    2012-07-01

    Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future.

  4. Cloud Computing for radiologists

    PubMed Central

    Kharat, Amit T; Safvi, Amjad; Thind, SS; Singh, Amarjit

    2012-01-01

    Cloud computing is a concept wherein a computer grid is created using the Internet with the sole purpose of utilizing shared resources such as computer software, hardware, on a pay-per-use model. Using Cloud computing, radiology users can efficiently manage multimodality imaging units by using the latest software and hardware without paying huge upfront costs. Cloud computing systems usually work on public, private, hybrid, or community models. Using the various components of a Cloud, such as applications, client, infrastructure, storage, services, and processing power, Cloud computing can help imaging units rapidly scale and descale operations and avoid huge spending on maintenance of costly applications and storage. Cloud computing allows flexibility in imaging. It sets free radiology from the confines of a hospital and creates a virtual mobile office. The downsides to Cloud computing involve security and privacy issues which need to be addressed to ensure the success of Cloud computing in the future. PMID:23599560

  5. ProteoCloud: a full-featured open source proteomics cloud computing pipeline.

    PubMed

    Muth, Thilo; Peters, Julian; Blackburn, Jonathan; Rapp, Erdmann; Martens, Lennart

    2013-08-02

    We here present the ProteoCloud pipeline, a freely available, full-featured cloud-based platform to perform computationally intensive, exhaustive searches in a cloud environment using five different peptide identification algorithms. ProteoCloud is entirely open source, and is built around an easy to use and cross-platform software client with a rich graphical user interface. This client allows full control of the number of cloud instances to initiate and of the spectra to assign for identification. It also enables the user to track progress, and to visualize and interpret the results in detail. Source code, binaries and documentation are all available at http://proteocloud.googlecode.com. Copyright © 2012 Elsevier B.V. All rights reserved.

  6. CloudMC: a cloud computing application for Monte Carlo simulation.

    PubMed

    Miras, H; Jiménez, R; Miras, C; Gomà, C

    2013-04-21

    This work presents CloudMC, a cloud computing application-developed in Windows Azure®, the platform of the Microsoft® cloud-for the parallelization of Monte Carlo simulations in a dynamic virtual cluster. CloudMC is a web application designed to be independent of the Monte Carlo code in which the simulations are based-the simulations just need to be of the form: input files → executable → output files. To study the performance of CloudMC in Windows Azure®, Monte Carlo simulations with penelope were performed on different instance (virtual machine) sizes, and for different number of instances. The instance size was found to have no effect on the simulation runtime. It was also found that the decrease in time with the number of instances followed Amdahl's law, with a slight deviation due to the increase in the fraction of non-parallelizable time with increasing number of instances. A simulation that would have required 30 h of CPU on a single instance was completed in 48.6 min when executed on 64 instances in parallel (speedup of 37 ×). Furthermore, the use of cloud computing for parallel computing offers some advantages over conventional clusters: high accessibility, scalability and pay per usage. Therefore, it is strongly believed that cloud computing will play an important role in making Monte Carlo dose calculation a reality in future clinical practice.

  7. A comparison between CloudSat and aircraft data for a multilayer, mixed phase cloud system during the Canadian CloudSat-CALIPSO Validation Project

    NASA Astrophysics Data System (ADS)

    Barker, H. W.; Korolev, A. V.; Hudak, D. R.; Strapp, J. W.; Strawbridge, K. B.; Wolde, M.

    2008-04-01

    Reflectivities recorded by the W-band Cloud Profiling Radar (CPR) aboard NASA's CloudSat satellite and some of CloudSat's retrieval products are compared to Ka-band radar reflectivities and in situ cloud properties gathered by instrumentation on the NRC's Convair-580 aircraft. On 20 February 2007, the Convair flew several transects along a 60 nautical mile stretch of CloudSat's afternoon ground track over southern Quebec. On one of the transects it was well within CloudSat's radar's footprint while in situ sampling a mixed phase boundary layer cloud. A cirrus cloud was also sampled before and after overpass. Air temperature and humidity profiles from ECMWF reanalyses, as employed in CloudSat's retrieval stream, agree very well with those measured by the Convair. The boundary layer cloud was clearly visible, to the eye and lidar, and dominated the region's solar radiation budget. It was, however, often below or near the Ka-band's distance-dependent minimum detectable signal. In situ samples at overpass revealed it to be composed primarily of small, supercooled droplets at the south end and increasingly intermixed with ice northward. Convair and CloudSat CPR reflectivities for the low cloud agree well, but while CloudSat properly ascribed it as overcast, mixed phase, and mostly liquid near the south end, its estimates of liquid water content LWC (and visible extinction coefficient κ) and droplet effective radii are too small and large, respectively. The cirrus consisted largely of irregular crystals with typical effective radii ˜150 μm. While both CPR reflectivities agree nicely, CloudSat's estimates of crystal number concentrations are too large by a factor of 5. Nevertheless, distributions of ice water content and κ deduced from in situ data agree quite well with values retrieved from CloudSat algorithms.

  8. Cloud Computing Explained

    ERIC Educational Resources Information Center

    Metz, Rosalyn

    2010-01-01

    While many talk about the cloud, few actually understand it. Three organizations' definitions come to the forefront when defining the cloud: Gartner, Forrester, and the National Institutes of Standards and Technology (NIST). Although both Gartner and Forrester provide definitions of cloud computing, the NIST definition is concise and uses…

  9. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

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

    Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities ( Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. In this paper, our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation ( S) is determined by Wb and the satellite-retrieved cloud basemore » drop concentrations ( Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. Finally, the limitation for small solar backscattering angles of <25° restricts the satellite coverage to ~25% of the world area in a single day.« less

  10. Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

    DOE PAGES

    Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; ...

    2016-03-04

    Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities ( Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. In this paper, our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation ( S) is determined by Wb and the satellite-retrieved cloud basemore » drop concentrations ( Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. Finally, the limitation for small solar backscattering angles of <25° restricts the satellite coverage to ~25% of the world area in a single day.« less

  11. Deep Clouds

    NASA Image and Video Library

    2008-05-27

    Bright puffs and ribbons of cloud drift lazily through Saturn's murky skies. In contrast to the bold red, orange and white clouds of Jupiter, Saturn's clouds are overlain by a thick layer of haze. The visible cloud tops on Saturn are deeper in its atmosphere due to the planet's cooler temperatures. This view looks toward the unilluminated side of the rings from about 18 degrees above the ringplane. Images taken using red, green and blue spectral filters were combined to create this natural color view. The images were acquired with the Cassini spacecraft wide-angle camera on April 15, 2008 at a distance of approximately 1.5 million kilometers (906,000 miles) from Saturn. Image scale is 84 kilometers (52 miles) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA09910

  12. Characteristic Vertical Profiles of Cloud Water Composition in Marine Stratocumulus Clouds and Relationships With Precipitation

    NASA Astrophysics Data System (ADS)

    MacDonald, Alexander B.; Dadashazar, Hossein; Chuang, Patrick Y.; Crosbie, Ewan; Wang, Hailong; Wang, Zhen; Jonsson, Haflidi H.; Flagan, Richard C.; Seinfeld, John H.; Sorooshian, Armin

    2018-04-01

    This study uses airborne cloud water composition measurements to characterize the vertical structure of air-equivalent mass concentrations of water-soluble species in marine stratocumulus clouds off the California coast. A total of 385 cloud water samples were collected in the months of July and August between 2011 and 2016 and analyzed for water-soluble ionic and elemental composition. Three characteristic profiles emerge: (i) a reduction of concentration with in-cloud altitude for particulate species directly emitted from sources below cloud without in-cloud sources (e.g., Cl- and Na+), (ii) an increase of concentration with in-cloud altitude (e.g., NO2- and formate), and (iii) species exhibiting a peak in concentration in the middle of cloud (e.g., non-sea-salt SO42-, NO3-, and organic acids). Vertical profiles of rainout parameters such as loss frequency, lifetime, and change in concentration with respect to time show that the scavenging efficiency throughout the cloud depth depends strongly on the thickness of the cloud. Thin clouds exhibit a greater scavenging loss frequency at cloud top, while thick clouds have a greater scavenging loss frequency at cloud base. The implications of these results for treatment of wet scavenging in models are discussed.

  13. Characteristic Vertical Profiles of Cloud Water Composition in Marine Stratocumulus Clouds and Relationships With Precipitation

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

    MacDonald, Alexander B.; Dadashazar, Hossein; Chuang, Patrick Y.

    This study uses airborne cloud water composition measurements to characterize the vertical structure of air-equivalent mass concentrations of water-soluble species in marine stratocumulus clouds off the California coast. A total of 385 cloud water samples were collected in the months of July and August between 2011 and 2016 and analyzed for water-soluble ionic and elemental composition. Three characteristic profiles emerge: (i) a reduction of concentration with in-cloud altitude for particulate species directly emitted from sources below cloud without in-cloud sources (e.g., Cl-, Na+); (ii) an increase of concentration with in-cloud altitude (e.g., NO2-, formate); and (iii) species exhibiting a peakmore » in concentration in the middle of cloud (e.g., non-sea salt SO42-, NO3-, organic acids). Vertical profiles of rainout parameters such as loss frequency, lifetime, and change in concentration with respect to time show that the scavenging efficiency throughout the cloud depth depends strongly on the thickness of the cloud. Thin clouds exhibit a greater scavenging loss frequency at cloud top, while thick clouds have a greater scavenging loss frequency at cloud base. The implications of these results for treatment of wet scavenging in models are discussed.« less

  14. A Cloud Mask for AIRS

    NASA Technical Reports Server (NTRS)

    Brubaker, N.; Jedlovec, G. J.

    2004-01-01

    With the preliminary release of AIRS Level 1 and 2 data to the scientific community, there is a growing need for an accurate AIRS cloud mask for data assimilation studies and in producing products derived from cloud free radiances. Current cloud information provided with the AIRS data are limited or based on simplified threshold tests. A multispectral cloud detection approach has been developed for AIRS that utilizes the hyper-spectral capabilities to detect clouds based on specific cloud signatures across the short wave and long wave infrared window regions. This new AIRS cloud mask has been validated against the existing AIRS Level 2 cloud product and cloud information derived from MODIS. Preliminary results for both day and night applications over the continental U.S. are encouraging. Details of the cloud detection approach and validation results will be presented at the conference.

  15. Titan Lingering Clouds

    NASA Image and Video Library

    2009-06-03

    Lots of clouds are visible in this infrared image of Saturn's moon Titan. These clouds form and move much like those on Earth, but in a much slower, more lingering fashion, new results from NASA's Cassini spacecraft show. Scientists have monitored Titan's atmosphere for three-and-a-half years, between July 2004 and December 2007, and observed more than 200 clouds. The way these clouds are distributed around Titan matches scientists' global circulation models. The only exception is timing—clouds are still noticeable in the southern hemisphere while fall is approaching. Three false-color images make up this mosaic and show the clouds at 40 to 50 degrees mid-latitude. The images were taken by Cassini's visual and infrared mapping spectrometer during a close flyby of Titan on Sept. 7, 2006, known as T17. For a similar view see PIA12005. Each image is a color composite, with red shown at the 2-micron wavelength, green at 1.6 microns, and blue at 2.8 microns. An infrared color mosaic is also used as a background (red at 5 microns, green at 2 microns and blue at 1.3 microns). The characteristic elongated mid-latitude clouds, which are easily visible in bright bluish tones are still active even late into 2006-2007. According to climate models, these clouds should have faded out since 2005. http://photojournal.jpl.nasa.gov/catalog/PIA12004

  16. An Integrated Cloud-Aerosol-Radiation Product Using CERES, MODIS, CALIPSO and CloudSat Data

    NASA Astrophysics Data System (ADS)

    Sun-Mack, S.; Gibson, S.; Chen, Y.; Wielicki, B.; Minnis, P.

    2006-12-01

    The goal of this paper is to provide the first integrated data set of global vertical profiles of aerosols, clouds, and radiation using the combined NASA A-Train data from Aqua CERES and MODIS, CALIPSO, and CloudSat. All of these instruments are flying in formation as part of the Aqua Train, or A-Train. This paper will present the preliminary results of merging aerosol and cloud data from the CALIPSO active lidar, cloud data from CloudSat, integrated column aerosol and cloud data from the MODIS CERES analyses, and surface and top-of-atmosphere broadband radiation fluxes from CERES. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

  17. Clouds vertical properties over the Northern Hemisphere monsoon regions from CloudSat-CALIPSO measurements

    NASA Astrophysics Data System (ADS)

    Das, Subrata Kumar; Golhait, R. B.; Uma, K. N.

    2017-01-01

    The CloudSat spaceborne radar and Cloud-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 clouds. The combined CloudSat-CALIPSO data products have been used for the summer season (June-August) of 2006-2010 to present the statistics of cloud macrophysical (such as cloud occurrence frequency, distribution of cloud top and base heights, geometrical thickness and cloud types 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 cloud fraction over the IND (mostly multiple-layered cloud) appeared to be more frequent as compared to the other monsoon regions. Three distinctive modes of cloud top height distribution are observed over all the monsoon regions. The high-level cloud 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 cloud frequency or coverage and only secondary in the cloud 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 cloud properties over the different monsoon regions.

  18. Exploring the Effects of Cloud Vertical Structure on Cloud Microphysical Retrievals based on Polarized Reflectances

    NASA Astrophysics Data System (ADS)

    Miller, D. J.; Zhang, Z.; Platnick, S. E.; Ackerman, A. S.; Cornet, C.; Baum, B. A.

    2013-12-01

    A polarized cloud reflectance simulator was developed by coupling an LES cloud model with a polarized radiative transfer model to assess the capabilities of polarimetric cloud retrievals. With future remote sensing campaigns like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important for the cloud remote sensing community to understand the retrievable information available and the related systematic/methodical limitations. The cloud retrieval simulator we have developed allows us to probe these important questions in a realistically relevant test bed. Our simulator utilizes a polarized adding-doubling radiative transfer model and an LES cloud field from a DHARMA simulation (Ackerman et al. 2004) with cloud properties based on the stratocumulus clouds observed during the DYCOMS-II field campaign. In this study we will focus on how the vertical structure of cloud microphysics can influence polarized cloud effective radius retrievals. Numerous previous studies have explored how retrievals based on total reflectance are affected by cloud vertical structure (Platnick 2000, Chang and Li 2002) but no such studies about the effects of vertical structure on polarized retrievals exist. Unlike the total cloud reflectance, which is predominantly multiply scattered light, the polarized reflectance is primarily the result of singly scattered photons. Thus the polarized reflectance is sensitive to only the uppermost region of the cloud (tau~<1) where photons can scatter once and still escape before being scattered again. This means that retrievals based on polarized reflectance have the potential to reveal behaviors specific to the cloud top. For example cloud top entrainment of dry air, a major influencer on the microphysical development of cloud droplets, can be potentially studied with polarimetric retrievals.

  19. A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications.

    PubMed

    Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

    2017-03-01

    This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model.

  20. Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

    NASA Astrophysics Data System (ADS)

    Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

    2003-12-01

    Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each

  1. Wave Clouds over Ireland

    NASA Image and Video Library

    2017-12-08

    Visualization Date 2003-12-18 Clouds 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 clouds formed. Then, as the air sank into the trough, the air warmed, and clouds did not form. This pattern repeated itself, with clouds appearing at the peak of every wave. Other types of clouds 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 clouds with fairly uniform appearances. High altitude cirrus-clouds float over these, casting their shadows on the lower clouds. Open- and closed-cell clouds formed off the coast of northwestern France, and thin contrail clouds are visible just east of these. Contrail clouds 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

  2. Cloud Computing

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

    Pete Beckman and Ian Foster

    Chicago Matters: Beyond Burnham (WTTW). Chicago has become a world center of "cloud computing." Argonne experts Pete Beckman and Ian Foster explain what "cloud computing" is and how you probably already use it on a daily basis.

  3. 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

  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. The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

    NASA Technical Reports Server (NTRS)

    Welch, Ronald M.

    1993-01-01

    A series of cloud and sea ice retrieval algorithms are being developed in support of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Science Team objectives. These retrievals include the following: cloud fractional area, cloud optical thickness, cloud phase (water or ice), cloud particle effective radius, cloud top heights, cloud base height, cloud top temperature, cloud emissivity, cloud 3-D structure, cloud field scales of organization, sea ice fractional area, sea ice temperature, sea ice albedo, and sea surface temperature. Due to the problems of accurately retrieving cloud properties over bright surfaces, an advanced cloud classification method was developed which is based upon spectral and textural features and artificial intelligence classifiers.

  6. Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions

    PubMed Central

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

    2018-01-01

    Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious. PMID:29651373

  7. Using MODIS Cloud Regimes to Sort Diagnostic Signals of Aerosol-Cloud-Precipitation Interactions.

    PubMed

    Oreopoulos, Lazaros; Cho, Nayeong; Lee, Dongmin

    2017-05-27

    Coincident multi-year measurements of aerosol, cloud, precipitation and radiation at near-global scales are analyzed to diagnose their apparent relationships as suggestive of interactions previously proposed based on theoretical, observational, and model constructs. Specifically, we examine whether differences in aerosol loading in separate observations go along with consistently different precipitation, cloud properties, and cloud radiative effects. Our analysis uses a cloud regime (CR) framework to dissect and sort the results. The CRs come from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and are defined as distinct groups of cloud systems with similar co-variations of cloud top pressure and cloud optical thickness. Aerosol optical depth used as proxy for aerosol loading comes from two sources, MODIS observations, and the MERRA-2 re-analysis, and its variability is defined with respect to local seasonal climatologies. The choice of aerosol dataset impacts our results substantially. We also find that the responses of the marine and continental component of a CR are frequently quite disparate. Overall, CRs dominated by warm clouds tend to exhibit less ambiguous signals, but also have more uncertainty with regard to precipitation changes. Finally, we find weak, but occasionally systematic co-variations of select meteorological indicators and aerosol, which serves as a sober reminder that ascribing changes in cloud and cloud-affected variables solely to aerosol variations is precarious.

  8. What does reflection from cloud sides tell us about vertical distribution of cloud droplets?

    NASA Technical Reports Server (NTRS)

    Marshak, A.; Kaufman, Yoram; Martins, V.; Zubko, Victor

    2006-01-01

    In order to accurately measure the interaction of clouds with aerosols, we have to resolve the vertical distribution of cloud droplet sizes and determine the temperature of glaciation for clean and polluted clouds. Knowledge of the droplet vertical profile is also essential for understanding precipitation. So far, all existing satellites either measure cloud microphysics only at cloud top (e.g., MODIS) or give a vertical profile of precipitation sized droplets (e.g., Cloudsat). What if one measures cloud microphysical properties in the vertical by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides? This was the idea behind CLAIM-3D (A 3D - cloud aerosol interaction mission) recently proposed by NASA GSFC. This presentation will focus on the interpretation of the radiation reflected from cloud sides. In contrast to plane-parallel approximation, a conventional approach to all current operational retrievals, 3D radiative transfer will be used for interpreting the observed reflectances. As a proof of concept, we will show a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with prescribed microphysics. Instead of fixed values of the retrieved effective radii, the probability density functions of droplet size distributions will serve as possible retrievals.

  9. The first observed cloud echoes and microphysical parameter retrievals by China's 94-GHz cloud radar

    NASA Astrophysics Data System (ADS)

    Wu, Juxiu; Wei, Ming; Hang, Xin; Zhou, Jie; Zhang, Peichang; Li, Nan

    2014-06-01

    By using the cloud echoes first successfully observed by China's indigenous 94-GHz SKY cloud radar, the macrostructure and microphysical properties of drizzling stratocumulus clouds in Anhui Province on 8 June 2013 are analyzed, and the detection capability of this cloud radar is discussed. The results are as follows. (1) The cloud radar is able to observe the time-varying macroscopic and microphysical parameters of clouds, and it can reveal the microscopic structure and small-scale changes of clouds. (2) The velocity spectral width of cloud droplets is small, but the spectral width of the cloud containing both cloud droplets and drizzle is large. When the spectral width is more than 0.4 m s-1, the radar reflectivity factor is larger (over -10 dBZ). (3) The radar's sensitivity is comparatively higher because the minimum radar reflectivity factor is about -35 dBZ in this experiment, which exceeds the threshold for detecting the linear depolarized ratio (LDR) of stratocumulus (commonly -11 to -14 dBZ; decreases with increasing turbulence). (4) After distinguishing of cloud droplets from drizzle, cloud liquid water content and particle effective radius are retrieved. The liquid water content of drizzle is lower than that of cloud droplets at the same radar reflectivity factor.

  10. What does Reflection from Cloud Sides tell us about Vertical Distribution of Cloud Droplet Sizes?

    NASA Technical Reports Server (NTRS)

    Marshak, A.; Martins, J. V.; Zubko, V.; Kaufman, Y. J.

    2006-01-01

    Cloud development, the onset of precipitation and the effect of aerosol on clouds depend on the structure of the cloud profiles of droplet size and phase. Aircraft measurements of cloud profiles are limited in their temporal and spatial extent. Satellites were used to observe cloud tops not cloud profiles with vertical profiles of precipitation-sized droplets anticipated from CloudSat. The recently proposed CLAIM-3D satellite mission (cloud aerosol interaction mission in 3-D) suggests to measure profiles of cloud microphysical properties by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides. Inversion of measurements from the cloud sides requires rigorous understanding of the 3-dimentional(3-D) properties of clouds. Here we discuss the reflected sunlight from the cloud sides and top at two wavelengths: one nonabsorbing to solar radiation (0.67 microns) and one with liquid water efficient absorption of solar radiation (2.1 microns). In contrast to the plane-parallel approximation, a conventional approach to all current operational retrievals, 3-D radiative transfer is used for interpreting the observed reflectances. General properties of the radiation reflected from the sides of an isolated cloud are discussed. As a proof of concept, the paper shows a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with the prescribed vertically resolved microphysics. To retrieve the information about droplet sizes, we propose to use the probability density function of the droplet size distribution and its first two moments instead of the assumption about fixed values of the droplet effective radius. The retrieval algorithm is based on the Bayesian theorem that combines prior information about cloud structure and microphysics with radiative transfer calculations.

  11. Impact of different cloud deployments on real-time video applications for mobile video cloud users

    NASA Astrophysics Data System (ADS)

    Khan, Kashif A.; Wang, Qi; Luo, Chunbo; Wang, Xinheng; Grecos, Christos

    2015-02-01

    The latest trend to access mobile cloud services through wireless network connectivity has amplified globally among both entrepreneurs and home end users. Although existing public cloud service vendors such as Google, Microsoft Azure etc. are providing on-demand cloud services with affordable cost for mobile users, there are still a number of challenges to achieve high-quality mobile cloud based video applications, especially due to the bandwidth-constrained and errorprone mobile network connectivity, which is the communication bottleneck for end-to-end video delivery. In addition, existing accessible clouds networking architectures are different in term of their implementation, services, resources, storage, pricing, support and so on, and these differences have varied impact on the performance of cloud-based real-time video applications. Nevertheless, these challenges and impacts have not been thoroughly investigated in the literature. In our previous work, we have implemented a mobile cloud network model that integrates localized and decentralized cloudlets (mini-clouds) and wireless mesh networks. In this paper, we deploy a real-time framework consisting of various existing Internet cloud networking architectures (Google Cloud, Microsoft Azure and Eucalyptus Cloud) and a cloudlet based on Ubuntu Enterprise Cloud over wireless mesh networking technology for mobile cloud end users. It is noted that the increasing trend to access real-time video streaming over HTTP/HTTPS is gaining popularity among both research and industrial communities to leverage the existing web services and HTTP infrastructure in the Internet. To study the performance under different deployments using different public and private cloud service providers, we employ real-time video streaming over the HTTP/HTTPS standard, and conduct experimental evaluation and in-depth comparative analysis of the impact of different deployments on the quality of service for mobile video cloud users. Empirical

  12. A Study of Global Cirrus Cloud Morphology with AIRS Cloud-clear Radiances (CCRs)

    NASA Technical Reports Server (NTRS)

    Wu, Dong L.; Gong, Jie

    2012-01-01

    Version 6 (V6) AIRS cloud-clear radiances (CCR) are used to derive cloud-induced radiance (Tcir=Tb-CCR) at the infrared frequencies of weighting functions peaked in the middle troposphere. The significantly improved V 6 CCR product allows a more accurate estimation of the expected clear-sky radiance as if clouds are absent. In the case where strong cloud scattering is present, the CCR becomes unreliable, which is reflected by its estimated uncertainty, and interpolation is employed to replace this CCR value. We find that Tcir derived from this CCR method are much better than other methods and detect more clouds in the upper and lower troposphere as well as in the polar regions where cloud detection is particularly challenging. The cloud morphology derived from the V6 test month, as well as some artifacts, will be shown.

  13. Cloud-edge mixing: Direct numerical simulation and observations in Indian Monsoon clouds

    NASA Astrophysics Data System (ADS)

    Kumar, Bipin; Bera, Sudarsan; Prabha, Thara V.; Grabowski, Wojceich W.

    2017-03-01

    A direct numerical simulation (DNS) with the decaying turbulence setup has been carried out to study cloud-edge mixing and its impact on the droplet size distribution (DSD) applying thermodynamic conditions observed in monsoon convective clouds over Indian subcontinent during the Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX). Evaporation at the cloud-edges initiates mixing at small scale and gradually introduces larger-scale fluctuations of the temperature, moisture, and vertical velocity due to droplet evaporation. Our focus is on early evolution of simulated fields that show intriguing similarities to the CAIPEEX cloud observations. A strong dilution at the cloud edge, accompanied by significant spatial variations of the droplet concentration, mean radius, and spectral width, are found in both the DNS and in observations. In DNS, fluctuations of the mean radius and spectral width come from the impact of small-scale turbulence on the motion and evaporation of inertial droplets. These fluctuations decrease with the increase of the volume over which DNS data are averaged, as one might expect. In cloud observations, these fluctuations also come from other processes, such as entrainment/mixing below the observation level, secondary CCN activation, or variations of CCN activation at the cloud base. Despite large differences in the spatial and temporal scales, the mixing diagram often used in entrainment/mixing studies with aircraft data is remarkably similar for both DNS and cloud observations. We argue that the similarity questions applicability of heuristic ideas based on mixing between two air parcels (that the mixing diagram is designed to properly represent) to the evolution of microphysical properties during turbulent mixing between a cloud and its environment.

  14. Giant molecular cloud scaling relations: the role of the cloud definition

    NASA Astrophysics Data System (ADS)

    Khoperskov, S. A.; Vasiliev, E. O.; Ladeyschikov, D. A.; Sobolev, A. M.; Khoperskov, A. V.

    2016-01-01

    We investigate the physical properties of molecular clouds 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 clouds, or so-called Larson's relations, are studied for two types of cloud 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 cloud populations obtained using both cloud extraction methods generally have similar physical parameters, except that for the CO data the mass spectrum of clouds 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 clouds for PPV data are almost insensitive to the galactic morphology, whereas the spectra for PP data demonstrate significant variation.

  15. Clouds in a Bottle: Qualitative and Quantiative Demonstrations for Cloud Formation in a Learning Environment

    NASA Astrophysics Data System (ADS)

    Ellis, T. D.

    2015-12-01

    The NASA CloudSat mission has been revealing the inner secrets of clouds since 2006 using its one-of-a-kind spaceborne cloud radar. During its mission, the CloudSat Education Network, consisting of schools in Asia, Europe, and North America, have been collecting data on Clouds when CloudSat passes overhead. The education team has spent many hours researching and presenting different methods for making clouds for demonstrations in formal and informal settings. In this presentation, we will present several variations on methods for doing the cloud in a bottle demonstration, including strengths and weaknesses for each, and a brief overview of the science involved in the various demonstrations.

  16. Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing

    NASA Astrophysics Data System (ADS)

    Klems, Markus; Nimis, Jens; Tai, Stefan

    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. Cloud Computing promises to deliver on this objective: consumers are able to rent infrastructure in the Cloud as needed, deploy applications and store data, and access them via Web protocols on a pay-per-use basis. The acceptance of Cloud Computing, however, depends on the ability for Cloud Computing providers and consumers to implement a model for business value co-creation. Therefore, a systematic approach to measure costs and benefits of Cloud Computing is needed. In this paper, we discuss the need for valuation of Cloud Computing, identify key components, and structure these components in a framework. The framework assists decision makers in estimating Cloud 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.

  17. Relationship between cloud-to-ground discharge and penetrative clouds: A multi-channel satellite application

    NASA Astrophysics Data System (ADS)

    Machado, Luiz A. T.; Lima, Wagner F. A.; Pinto, Osmar; Morales, Carlos A.

    This work presents a relationship between atmospheric cloud-to-ground discharges and penetrative convective clouds. It combines Infrared and Water Vapor channels from the GOES-12 geostationary satellite with cloud-to-ground discharge data from the Brazilian Integrated Lightning Detection Network (RINDAT) during the period from January to February 2005. The difference between water vapor and infrared brightness temperature is a tracer penetrating clouds. Due to the water vapor channel's strong absorption, this difference is positive only during overshooting cases, when convective clouds penetrate the stratosphere. From this difference and the cloud-to-ground, discharge measured on the ground by RINDAT, it was possible to adjust exponential curves that relate the brightness temperature difference from these two channels to the probability of occurrence of cloud-to-ground discharges, with a very large coefficient of determination. If WV-IR brightness temperature difference is greater than - 15 K there is a large potential for cloud-to-ground discharge activity. As this difference increases the cloud-to-ground discharge probably increases, for example: if this difference is equal to zero, the probability of having at least one cloud-to-ground discharge is 10.9%, 7.0% for two, 4.4% for four, 2.7% for eight and 1.5% for sixteen cloud-to-ground discharges. Through this process, was developed a scheme that estimates the probability of occurrence of cloud-to-ground discharge over all the continental region of South America.

  18. Aerosol-Cloud Interactions and Cloud Microphysical Properties in the Asir Region of Saudi Arabia

    NASA Astrophysics Data System (ADS)

    Kucera, P. A.; Axisa, D.; Burger, R. P.; Li, R.; Collins, D. R.; Freney, E. J.; Buseck, P. R.

    2009-12-01

    In recent advertent and inadvertent weather modification studies, a considerable effort has been made to understand the impact of varying aerosol properties and concentration on cloud properties. Significant uncertainties exist with aerosol-cloud interactions for which complex microphysical processes link the aerosol and cloud properties. Under almost all environmental conditions, increased aerosol concentrations within polluted air masses will enhance cloud droplet concentration relative to that in unperturbed regions. The interaction between dust particles and clouds are significant, yet the conditions in which dust particles become cloud condensation nuclei (CCN) are uncertain. In order to quantify this aerosol effect on clouds and precipitation, a field campaign was launched in the Asir region, located adjacent to the Red Sea in the southwest region of Saudi Arabia. Ground measurements of aerosol size distributions, hygroscopic growth factors, CCN concentrations as well as aircraft measurements of cloud hydrometeor size distributions were observed in the Asir region in August 2009. The presentation will include a summary of the analysis and results with a focus on aerosol-cloud interactions and cloud microphysical properties observed during the convective season in the Asir region.

  19. 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

  20. 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

  1. GEWEX Cloud Systems Study (GCSS)

    NASA Technical Reports Server (NTRS)

    Moncrieff, Mitch

    1993-01-01

    The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.

  2. Validation of CERES-MODIS Arctic cloud properties using CloudSat/CALIPSO and ARM NSA observations

    NASA Astrophysics Data System (ADS)

    Giannecchini, K.; Dong, X.; Xi, B.; Minnis, P.; Kato, S.

    2011-12-01

    The traditional passive satellite studies of cloud properties in the Arctic are often affected by the complex surface features present across the region. Nominal visual and thermal contrast exists between Arctic clouds and the snow- and ice-covered surfaces beneath them, which can lead to difficulties in satellite retrievals of cloud properties. However, the addition of active sensors to the A-Train constellation of satellites has increased the availability of validation sources for cloud properties derived from passive sensors in the data-sparse high-latitude regions. In this study, Arctic cloud fraction and cloud heights derived from the NASA CERES team (CERES-MODIS) have been compared with CloudSat/CALIPSO and DOE ARM NSA radar-lidar observations over Barrow, AK, for the two-year period from 2007 to 2008. An Arctic-wide comparison of cloud fraction and height between CERES-MODIS and CloudSat/CALIPSO was then conducted for the same time period. The CERES-MODIS cloud properties, which include cloud fraction and cloud effective heights, were retrieved using the 4-channel VISST (Visible Infrared Solar-Infrared Split-window Technique) [Minnis et al.,1995]. CloudSat/CALIPSO cloud fraction and cloud-base and -top heights were from version RelB1 data products determined by both the 94 GHz radar onboard CloudSat and the lidar on CALIPSO with a vertical resolution of 30 m below 8.2 km and 60 m above. To match the surface and satellite observations/retrievals, the ARM surface observations were averaged into 3-hour intervals centered at the time of the satellite overpass, while satellite observations were averaged within a 3°x3° grid box centered on the Barrow site. The preliminary results have shown that all observed CFs have peaks during April-May and September-October, and dips during winter months (January-February) and summer months (June-July) during the study period of 2007-2008. ARM radar-lidar and CloudSat/CALIPSO show generally good agreement in CF (0.79 vs. 0

  3. Operational implications of a cloud model simulation of space shuttle exhaust clouds in different atmospheric conditions

    NASA Technical Reports Server (NTRS)

    Zak, J. A.

    1989-01-01

    A three-dimensional cloud model was used to characterize the dominant influence of the environment on the Space Shuttle exhaust cloud. The model was modified to accept the actual heat and moisture from rocket exhausts and deluge water as initial conditions. An upper-air sounding determined the ambient atmosphere in which the cloud would grow. The model was validated by comparing simulated clouds with observed clouds from four actual Shuttle launches. Results are discussed with operational weather forecasters in mind. The model successfully produced clouds with dimensions, rise, decay, liquid water contents, and vertical motion fields very similar to observed clouds whose dimensions were calculated from 16 mm film frames. Once validated, the model was used in a number of different atmospheric conditions ranging from very unstable to very stable. Wind shear strongly affected the appearance of both the ground cloud and vertical column cloud. The ambient low-level atmospheric moisture governed the amount of cloud water in model clouds. Some dry atmospheres produced little or no cloud water. An empirical forecast technique for Shuttle cloud rise is presented and differences between natural atmospheric convection and exhaust clouds are discussed.

  4. Improvements in Night-Time Low Cloud Detection and MODIS-Style Cloud Optical Properties from MSG SEVIRI

    NASA Technical Reports Server (NTRS)

    Wind, Galina (Gala); Platnick, Steven; Riedi, Jerome

    2011-01-01

    The MODIS cloud optical properties algorithm (MOD06IMYD06 for Terra and Aqua MODIS, respectively) slated for production in Data Collection 6 has been adapted to execute using available channels on MSG SEVIRI. Available MODIS-style retrievals include IR Window-derived cloud top properties, using the new Collection 6 cloud top properties algorithm, cloud optical thickness from VISINIR bands, cloud effective radius from 1.6 and 3.7Jlm and cloud ice/water path. We also provide pixel-level uncertainty estimate for successful retrievals. It was found that at nighttime the SEVIRI cloud mask tends to report unnaturally low cloud fraction for marine stratocumulus clouds. A correction algorithm that improves detection of such clouds has been developed. We will discuss the improvements to nighttime low cloud detection for SEVIRI and show examples and comparisons with MODIS and CALIPSO. We will also show examples of MODIS-style pixel-level (Level-2) cloud retrievals for SEVIRI with comparisons to MODIS.

  5. BlueSky Cloud Framework: An E-Learning Framework Embracing Cloud Computing

    NASA Astrophysics Data System (ADS)

    Dong, Bo; Zheng, Qinghua; Qiao, Mu; Shu, Jian; Yang, Jie

    Currently, E-Learning has grown into a widely accepted way of learning. With the huge growth of users, services, education contents and resources, E-Learning systems are facing challenges of optimizing resource allocations, dealing with dynamic concurrency demands, handling rapid storage growth requirements and cost controlling. In this paper, an E-Learning framework based on cloud computing is presented, namely BlueSky cloud framework. Particularly, the architecture and core components of BlueSky cloud framework are introduced. In BlueSky cloud framework, physical machines are virtualized, and allocated on demand for E-Learning systems. Moreover, BlueSky cloud framework combines with traditional middleware functions (such as load balancing and data caching) to serve for E-Learning systems as a general architecture. It delivers reliable, scalable and cost-efficient services to E-Learning systems, and E-Learning organizations can establish systems through these services in a simple way. BlueSky cloud framework solves the challenges faced by E-Learning, and improves the performance, availability and scalability of E-Learning systems.

  6. Cloud condensation nucleus-sulfate mass relationship and cloud albedo

    NASA Technical Reports Server (NTRS)

    Hegg, Dean A.

    1994-01-01

    Analysis of previously published, simultaneous measurements of cloud condensation nucleus number concentration and sulfate mass concentration suggest a nonlinear relationship between the two variables. This nonlinearity reduces the sensitivity of cloud albedo to changes in the sulfur cycle.

  7. What Does Reflection from Cloud Sides Tell Us About Vertical Distribution of Cloud Droplet Sizes?

    NASA Technical Reports Server (NTRS)

    Marshak, Alexander; Martins, J. Vanderlei; Zubko, Victor; Kaufman, Yoram, J.

    2005-01-01

    Cloud development, the onset of precipitation and the effect of aerosol on clouds depend on the structure of the cloud profiles of droplet size and phase. Aircraft measurements of cloud profiles are limited in their temporal and spatial extent. Satellites were used to observe cloud tops not cloud profiles with vertical profiles of precipitation-sized droplets anticipated from Cloudsat. The recently proposed CLAIM-3D satellite mission (cloud aerosol interaction mission in 3D) suggests to measure profiles of cloud microphysical properties by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides. Inversion of measurements from the cloud sides requires rigorous understanding of the 3-dimensional (3D) properties of clouds. Here we discuss the reflected sunlight from the cloud sides and top at two wavelengths: one nonabsorbing to solar radiation (0.67 micrometers) and one with liquid water efficient absorption of solar radiation (2.1 micrometers). In contrast to the plane-parallel approximation, a conventional approach to all current operational retrievals, 3D radiative transfer is used for interpreting the observed reflectances. General properties of the radiation reflected from the sides of an isolated cloud are discussed. As a proof of concept, the paper shows a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with the prescribed vertically resolved microphysics. To retrieve the information about droplet sizes, we propose to use the probability density function of the droplet size distribution and its first two moments instead of the assumption about fixed values of the droplet effective radius. The retrieval algorithm is based on the Bayesian theorem that combines prior information about cloud structure and microphysics with radiative transfer calculations.

  8. Entrainment, Drizzle, and Cloud Albedo

    NASA Technical Reports Server (NTRS)

    Ackerman, A. S.; Kirkpatrick, J. P.; Stevens, D. E.; Toon, O. B.

    2004-01-01

    Increased aerosol and hence droplet concentrations in polluted clouds are expected to inhibit precipitation and thereby increase cloud water, leading to more reflective clouds that partially offset global warming. Yet polluted clouds are not generally observed to hold more water. Much of the uncertainty regarding the indirect aerosol effect stems from inadequate understanding of such changes in cloud water. Detailed simulations show that the relative humidity of air overlying stratocumulus is a leading factor determining whether cloud water increases or decreases when precipitation is suppressed. When the overlying air is dry, cloud water can decrease as droplet concentrations increase.

  9. Microphysical Cloud Regimes used as a tool to study Aerosol-Cloud-Precipitation-Radiation interactions

    NASA Astrophysics Data System (ADS)

    Cho, N.; Oreopoulos, L.; Lee, D.

    2017-12-01

    The presentation will examine whether the diagnostic relationships between aerosol and cloud-affected quantities (precipitation, radiation) obtained from sparse temporal resolution measurements from polar orbiting satellites can potentially demonstrate actual aerosol effects on clouds with appropriate analysis. The analysis relies exclusively on Level-3 (gridded) data and comprises systematic cloud classification in terms of "microphysical cloud regimes" (µCRs), aerosol optical depth (AOD) variations relative to a region's local seasonal climatology, and exploitation of the 3-hour difference between Terra (morning) and Aqua (afternoon) overpasses. Specifically, our presentation will assess whether Aerosol-Cloud-Precipitation-Radiation interactions (ACPRI) can be diagnosed by investigating: (a) The variations with AOD of afternoon cloud-affected quantities composited by afternoon or morning µCRs; (b) µCR transition diagrams composited by morning AOD quartiles; (c) whether clouds represented by ensemble cloud effective radius - cloud optical thickness joint histograms look distinct under low and high AOD conditions when preceded or followed by specific µCRs. We will explain how our approach addresses long-standing themes of the ACPRI problem such as the optimal ways to decompose the problem by cloud class, the prevalence and detectability of 1st/2nd aerosol indirect effects and invigoration, and the effectiveness of aerosol changes in inducing cloud modification at different segments of the AOD distribution.

  10. Cloud Computing for Geosciences--GeoCloud for standardized geospatial service platforms (Invited)

    NASA Astrophysics Data System (ADS)

    Nebert, D. D.; Huang, Q.; Yang, C.

    2013-12-01

    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, cloud computing emerges as a promising solution to provide core capabilities to address these challenges. Many governmental and federal agencies are adopting cloud 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 cloud computing to facilitate the scientific research and discoveries. This presentation reports using GeoCloud 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. GeoCloud 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 GeoCloud 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 cloud. 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 identified 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

  11. Study Pollution Impacts on Upper-Tropospheric Clouds with Aura, CloudSat, and CALIPSO Data

    NASA Technical Reports Server (NTRS)

    Wu, Dong

    2007-01-01

    This viewgraph presentation reviews the impact of pollution on clouds in the Upper Troposphere. Using the data from the Aura Microwave Limb Sounder (MLS), CloudSat, CALIPSO the presentation shows signatures of pollution impacts on clouds in the upper troposphere. The presentation demonstrates the complementary sensitivities of MLS , CloudSat and CALIPSO to upper tropospheric clouds. It also calls for careful analysis required to sort out microphysical changes from dynamical changes.

  12. Modeling the Diffuse Cloud-Top Optical Emissions from Ground and Cloud Flashes

    NASA Technical Reports Server (NTRS)

    Solakiewicz, Richard; Koshak, William

    2008-01-01

    A number of studies have indicated that the diffuse cloud-top optical emissions from intra-cloud (IC) lightning are brighter than that from normal negative cloud-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 cloud and therefore is less obscured by the cloud multiple scattering medium. CGs at lower altitudes embedded deep within the cloud 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 cloud 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 type no matter which produces a brighter cloud 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 cloud (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 cloud top than the lower altitude negative ground flashes, but additional model runs are to be examined before finalizing our general conclusions.

  13. Vertical Structures of Anvil Clouds of Tropical Mesoscale Convective Systems Observed by CloudSat

    NASA Technical Reports Server (NTRS)

    Hence, Deanna A.; Houze, Robert A.

    2011-01-01

    A global study of the vertical structures of the clouds of tropical mesoscale convective systems (MCSs) has been carried out with data from the CloudSat Cloud Profiling Radar. Tropical MCSs are found to be dominated by cloud-top heights greater than 10 km. Secondary cloud layers sometimes occur in MCSs, but outside their primary raining cores. The secondary layers have tops at 6 8 and 1 3 km. High-topped clouds extend outward from raining cores of MCSs to form anvil clouds. Closest to the raining cores, the anvils tend to have broader distributions of reflectivity at all levels, with the modal values at higher reflectivity in their lower levels. Portions of anvil clouds far away from the raining core are thin and have narrow frequency distributions of reflectivity at all levels with overall weaker values. This difference likely reflects ice particle fallout and therefore cloud age. Reflectivity histograms of MCS anvil clouds vary little across the tropics, except that (i) in continental MCS anvils, broader distributions of reflectivity occur at the uppermost levels in the portions closest to active raining areas; (ii) the frequency of occurrence of stronger reflectivity in the upper part of anvils decreases faster with increasing distance in continental MCSs; and (iii) narrower-peaked ridges are prominent in reflectivity histograms of thick anvil clouds close to the raining areas of connected MCSs (superclusters). These global results are consistent with observations at ground sites and aircraft data. They present a comprehensive test dataset for models aiming to simulate process-based upper-level cloud structure around the tropics.

  14. Vertical Structures of Anvil Clouds of Tropical Mesoscale Convective Systems Observed by CloudSat

    NASA Technical Reports Server (NTRS)

    Yuan, J.; Houze, R. A., Jr.; Heymsfield, A.

    2011-01-01

    A global study of the vertical structures of the clouds of tropical mesoscale convective systems (MCSs) has been carried out with data from the CloudSat Cloud Profiling Radar. Tropical MCSs are found to be dominated by cloud-top heights greater than 10 km. Secondary cloud layers sometimes occur in MCSs, but outside their primary raining cores. The secondary layers have tops at 6--8 and 1--3 km. High-topped clouds extend outward from raining cores of MCSs to form anvil clouds. Closest to the raining cores, the anvils tend to have broader distributions of reflectivity at all levels, with the modal values at higher reflectivity in their lower levels. Portions of anvil clouds far away from the raining core are thin and have narrow frequency distributions of reflectivity at all levels with overall weaker values. This difference likely reflects ice particle fallout and therefore cloud age. Reflectivity histograms of MCS anvil clouds vary little across the tropics, except that (i) in continental MCS anvils, broader distributions of reflectivity occur at the uppermost levels in the portions closest to active raining areas; (ii) the frequency of occurrence of stronger reflectivity in the upper part of anvils decreases faster with increasing distance in continental MCSs; and (iii) narrower-peaked ridges are prominent in reflectivity histograms of thick anvil clouds close to the raining areas of connected MCSs (superclusters). These global results are consistent with observations at ground sites and aircraft data. They present a comprehensive test dataset for models aiming to simulate process-based upper-level cloud structure around the tropics.

  15. Cloud-Resolving Model Simulations of Aerosol-Cloud Interactions Triggered by Strong Aerosol Emissions in the Arctic

    NASA Astrophysics Data System (ADS)

    Wang, H.; Kravitz, B.; Rasch, P. J.; Morrison, H.; Solomon, A.

    2014-12-01

    Previous process-oriented modeling studies have highlighted the dependence of effectiveness of cloud brightening by aerosols on cloud regimes in warm marine boundary layer. Cloud microphysical processes in clouds that contain ice, and hence the mechanisms that drive aerosol-cloud interactions, are more complicated than in warm clouds. Interactions between ice particles and liquid drops add additional levels of complexity to aerosol effects. A cloud-resolving model is used to study aerosol-cloud interactions in the Arctic triggered by strong aerosol emissions, through either geoengineering injection or concentrated sources such as shipping and fires. An updated cloud microphysical scheme with prognostic aerosol and cloud particle numbers is employed. Model simulations are performed in pure super-cooled liquid and mixed-phase clouds, separately, with or without an injection of aerosols into either a clean or a more polluted Arctic boundary layer. Vertical mixing and cloud scavenging of particles injected from the surface is still quite efficient in the less turbulent cold environment. Overall, the injection of aerosols into the Arctic boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. The pure liquid clouds are more susceptible to the increase in aerosol number concentration than the mixed-phase clouds. Rain production processes are more effectively suppressed by aerosol injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. Aerosol injection into a clean boundary layer results in a greater cloud albedo increase than injection into a polluted one, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, the impact of dynamical feedback due to precipitation changes is small. According to these results, which are dependent upon the representation of ice nucleation

  16. Looking Down Through the Clouds – Optical Attenuation through Real-Time Clouds

    NASA Astrophysics Data System (ADS)

    Burley, J.; Lazarewicz, A.; Dean, D.; Heath, N.

    Detecting and identifying 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 clouds. Clouds 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 cloud 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 clouds using the U.S. Air Force’s World Wide Merged Cloud Analysis (WWMCA) cloud data in a new toolset that enables radiance calculations through clouds from UV to RF wavelengths.

  17. USGEO DMWG Cloud Computing Recommendations

    NASA Astrophysics Data System (ADS)

    de la Beaujardiere, J.; McInerney, M.; Frame, M. T.; Summers, C.

    2017-12-01

    The US Group on Earth Observations (USGEO) Data Management Working Group (DMWG) has been developing Cloud Computing Recommendations for Earth Observations. This inter-agency report is currently in draft form; DMWG hopes to have released the report as a public Request for Information (RFI) by the time of AGU. The recommendations are geared toward organizations that have already decided to use the Cloud for some of their activities (i.e., the focus is not on "why you should use the Cloud," but rather "If you plan to use the Cloud, consider these suggestions.") The report comprises Introductory Material, including Definitions, Potential Cloud Benefits, and Potential Cloud Disadvantages, followed by Recommendations in several areas: Assessing When to Use the Cloud, Transferring Data to the Cloud, Data and Metadata Contents, Developing Applications in the Cloud, Cost Minimization, Security Considerations, Monitoring and Metrics, Agency Support, and Earth Observations-specific recommendations. This talk will summarize the recommendations and invite comment on the RFI.

  18. Cloud GIS Based Watershed Management

    NASA Astrophysics Data System (ADS)

    Bediroğlu, G.; Colak, H. E.

    2017-11-01

    In this study, we generated a Cloud GIS based watershed management system with using Cloud Computing architecture. Cloud GIS is used as SAAS (Software as a Service) and DAAS (Data as a Service). We applied GIS analysis on cloud in terms of testing SAAS and deployed GIS datasets on cloud in terms of DAAS. We used Hybrid cloud computing model in manner of using ready web based mapping services hosted on cloud (World Topology, Satellite Imageries). We uploaded to system after creating geodatabases including Hydrology (Rivers, Lakes), Soil Maps, Climate Maps, Rain Maps, Geology and Land Use. Watershed of study area has been determined on cloud using ready-hosted topology maps. After uploading all the datasets to systems, we have applied various GIS analysis and queries. Results shown that Cloud GIS technology brings velocity and efficiency for watershed management studies. Besides this, system can be easily implemented for similar land analysis and management studies.

  19. Development of methods for inferring cloud thickness and cloud-base height from satellite radiance data

    NASA Technical Reports Server (NTRS)

    Smith, William L., Jr.; Minnis, Patrick; Alvarez, Joseph M.; Uttal, Taneil; Intrieri, Janet M.; Ackerman, Thomas P.; Clothiaux, Eugene

    1993-01-01

    Cloud-top height is a major factor determining the outgoing longwave flux at the top of the atmosphere. The downwelling radiation from the cloud strongly affects the cooling rate within the atmosphere and the longwave radiation incident at the surface. Thus, determination of cloud-base temperature is important for proper calculation of fluxes below the cloud. Cloud-base altitude is also an important factor in aircraft operations. Cloud-top height or temperature can be derived in a straightforward manner using satellite-based infrared data. Cloud-base temperature, however, is not observable from the satellite, but is related to the height, phase, and optical depth of the cloud in addition to other variables. This study uses surface and satellite data taken during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (13 Nov. - 7 Dec. 1991, to improve techniques for deriving cloud-base height from conventional satellite data.

  20. Evidence for Natural Variability in Marine Stratocumulus Cloud Properties Due to Cloud-Aerosol

    NASA Technical Reports Server (NTRS)

    Albrecht, Bruce; Sharon, Tarah; Jonsson, Haf; Minnis, Patrick; Minnis, Patrick; Ayers, J. Kirk; Khaiyer, Mandana M.

    2004-01-01

    In this study, aircraft observations from the Interdisciplinary Remotely-Piloted Aircraft Studies (CIRPAS) Twin Otter are used to characterize the variability in drizzle, cloud, and aerosol properties associated with cloud rifts and the surrounding solid clouds observed off the coast of California. A flight made on 16 July 1999 provided measurements directly across an interface between solid and rift cloud conditions. Aircraft instrumentation allowed for measurements of aerosol, cloud 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 cloud-sized droplets. A Cloud Imaging Probe (CIP) was used to measure distributions of drizzle-sized droplets. Aerosol distributions were obtained from a Cloud Aerosol Scatterprobe (CAS). The CAS probe measured aerosols, cloud 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 identifying ultrafine particles those falling in the size range of 3 nanometers - 7 nanometers that are believed to be associated with new particle production.

  1. 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.

  2. A physically based algorithm for non-blackbody correction of the cloud top temperature for the convective clouds

    NASA Astrophysics Data System (ADS)

    Wang, C.; Luo, Z. J.; Chen, X.; Zeng, X.; Tao, W.; Huang, X.

    2012-12-01

    Cloud top temperature is a key parameter to retrieval in the remote sensing of convective clouds. Passive remote sensing cannot directly measure the temperature at the cloud tops. Here we explore a synergistic way of estimating cloud top temperature by making use of the simultaneous passive and active remote sensing of clouds (in this case, CloudSat and MODIS). Weighting function of the MODIS 11μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat retrievals and temperature and humidity profiles based on ECMWF ERA-interim reanalysis into a radiation transfer model. Among 19,699 tropical deep convective clouds observed by the CloudSat in 2008, the averaged effective emission level (EEL, where the weighting function attains its maximum) is at optical depth 0.91 with a standard deviation of 0.33. Furthermore, the vertical gradient of CloudSat radar reflectivity, an indicator of the fuzziness of convective cloud top, is linearly proportional to, d_{CTH-EEL}, the distance between the EEL of 11μm channel and cloud top height (CTH) determined by the CloudSat when d_{CTH-EEL}<0.6km. Beyond 0.6km, the distance has little sensitivity to the vertical gradient of CloudSat radar reflectivity. Based on these findings, we derive a formula between the fuzziness in the cloud top region, which is measurable by CloudSat, and the MODIS 11μm brightness temperature assuming that the difference between effective emission temperature and the 11μm brightness temperature is proportional to the cloud top fuzziness. This formula is verified using the simulated deep convective cloud profiles by the Goddard Cumulus Ensemble model. We further discuss the application of this formula in estimating cloud top buoyancy as well as the error characteristics of the radiative calculation within such deep-convective clouds.

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

    NASA Technical Reports Server (NTRS)

    Ham, Seung-Hee; Sohn, Byung-Ju; Kato, Seiji; Satoh, Masaki

    2013-01-01

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

  4. GEWEX cloud assessment: A review

    NASA Astrophysics Data System (ADS)

    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

    2013-05-01

    Clouds 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 cloud 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) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provides the first coordinated intercomparison of publicly available, global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multi-angle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. 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.

  5. Mapping Titan Cloud Coverage

    NASA Image and Video Library

    2010-09-21

    This graphic, constructed from data obtained by NASA Cassini spacecraft, shows the percentage of cloud coverage across the surface of Saturn moon Titan. The color scale from black to yellow signifies no cloud coverage to complete cloud coverage.

  6. "Black cloud" vs. "white cloud" physicians - Myth or reality in apheresis medicine?

    PubMed

    Pham, Huy P; Raju, Dheeraj; Jiang, Ning; Williams, Lance A

    2017-08-01

    Many practitioners believe in the phenomenon of either being labeled a "black cloud" or "white cloud" while on-call. A "white-cloud" physician is one who usually gets fewer cases. A "black-cloud" 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, type of emergent apheresis procedure, day of the week, and season of the year. During the study period, 32 emergent procedures (or "black-cloud" 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-cloud" 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-cloud" 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 cloud" or "white cloud". A larger, multi-center study population is needed to validate the results of this pilot study. © 2016 Wiley Periodicals, Inc.

  7. Marine Cloud Brightening

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

    Latham, John; Bower, Keith; Choularton, Tom

    2012-09-07

    The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud 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 identified 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 cloud brightening; (iii) microphysical modelling sensitivity studies, examining the influence of seeding amount, seedparticle 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, cloud albedo might be enhanced by seeding marine stratocumulus clouds 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

  8. Marine cloud brightening.

    PubMed

    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

    2012-09-13

    The idea behind the marine cloud-brightening (MCB) geoengineering technique is that seeding marine stratocumulus clouds with copious quantities of roughly monodisperse sub-micrometre sea water particles might significantly enhance the cloud droplet number concentration, and thereby the cloud 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 identified 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 cloud 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, cloud albedo might be enhanced by seeding marine stratocumulus clouds 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.

  9. Islands in the Sky: Ecophysiological Cloud-Vegetation Linkages in Southern Appalachian Mountain Cloud Forests

    NASA Astrophysics Data System (ADS)

    Reinhardt, K.; Emanuel, R. E.; Johnson, D. M.

    2013-12-01

    Mountain cloud forest (MCF) ecosystems are characterized by a high frequency of cloud fog, with vegetation enshrouded in fog. The altitudinal boundaries of cloud-fog zones co-occur with conspicuous, sharp vegetation ecotones between MCF- and non-MCF-vegetation. This suggests linkages between cloud-fog and vegetation physiology and ecosystem functioning. However, very few studies have provided a mechanistic explanation for the sharp changes in vegetation communities, or how (if) cloud-fog and vegetation are linked. We investigated ecophysiological linkages between clouds and trees in Southern Appalachian spruce-fir MCF. These refugial forests occur in only six mountain-top, sky-island populations, and are immersed in clouds on up to 80% of all growing season days. Our fundamental research questions was: How are cloud-fog and cloud-forest trees linked? We measured microclimate and physiology of canopy tree species across a range of sky conditions (cloud immersed, partly cloudy, sunny). Measurements included: 1) sunlight intensity and spectral quality; 2) carbon gain and photosynthetic capacity at leaf (gas exchange) and ecosystem (eddy covariance) scales; and 3) relative limitations to carbon gain (biochemical, stomatal, hydraulic). RESULTS: 1) Midday sunlight intensity ranged from very dark (<30 μmol m-2 s-1, under cloud-immersed conditions) to very bright (>2500 μmol m-2 s-1), and was highly variable on minute-to-minute timescales whenever clouds were present in the sky. Clouds and cloud-fog increased the proportion of blue-light wavelengths 5-15% compared to sunny conditions, and altered blue:red and red:far red ratios, both of which have been shown to strongly affect stomatal functioning. 2) Cloud-fog resulted in ~50% decreased carbon gain at leaf and ecosystem scales, due to sunlight levels below photosynthetic light-saturation-points. However, greenhouse studies and light-response-curve analyses demonstrated that MCF tree species have low light

  10. Titan Mystery Clouds

    NASA Image and Video Library

    2016-12-21

    This comparison of two views from NASA's Cassini spacecraft, taken fairly close together in time, illustrates a peculiar mystery: Why would clouds 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 cloud free. But in the bottom view, at longer infrared wavelengths, Cassini sees a large field of bright clouds. Even though these views were taken at different wavelengths, researchers would expect at least a hint of the clouds 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 clouds 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 clouds 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 identifiable and only a few small, isolated clouds were detected. In contrast, the VIMS observations (color image at bottom) suggest widespread cloud cover during both flybys. The observations were made over the same time period, so differences in illumination geometry or changes in the clouds themselves are unlikely to be the cause for the apparent discrepancy: VIMS shows persistent

  11. Mobile Cloud Learning for Higher Education: A Case Study of Moodle in the Cloud

    ERIC Educational Resources Information Center

    Wang, Minjuan; Chen, Yong; Khan, Muhammad Jahanzaib

    2014-01-01

    Mobile cloud learning, a combination of mobile learning and cloud computing, is a relatively new concept that holds considerable promise for future development and delivery in the education sectors. Cloud computing helps mobile learning overcome obstacles related to mobile computing. The main focus of this paper is to explore how cloud computing…

  12. A Simple Model for the Cloud Adjacency Effect and the Apparent Bluing of Aerosols Near Clouds

    NASA Technical Reports Server (NTRS)

    Marshak, Alexander; Wen, Guoyong; Coakley, James A., Jr.; Remer, Lorraine A.; Loeb,Norman G.; Cahalan, Robert F.

    2008-01-01

    In determining aerosol-cloud interactions, the properties of aerosols must be characterized in the vicinity of clouds. Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. The paper provides a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. The enhancement in Rayleigh scattering is estimated using a stochastic cloud model to obtain the radiative flux reflected by broken clouds and comparing this flux with that obtained with the molecules in the atmosphere causing extinction, but no scattering.

  13. A Location-Based Interactive Model of Internet of Things and Cloud (IoT-Cloud) for Mobile Cloud Computing Applications †

    PubMed Central

    Dinh, Thanh; Kim, Younghan; Lee, Hyukjoon

    2017-01-01

    This paper presents a location-based interactive model of Internet of Things (IoT) and cloud integration (IoT-cloud) for mobile cloud computing applications, in comparison with the periodic sensing model. In the latter, sensing collections are performed without awareness of sensing demands. Sensors are required to report their sensing data periodically regardless of whether or not there are demands for their sensing services. This leads to unnecessary energy loss due to redundant transmission. In the proposed model, IoT-cloud provides sensing services on demand based on interest and location of mobile users. By taking advantages of the cloud as a coordinator, sensing scheduling of sensors is controlled by the cloud, which knows when and where mobile users request for sensing services. Therefore, when there is no demand, sensors are put into an inactive mode to save energy. Through extensive analysis and experimental results, we show that the location-based model achieves a significant improvement in terms of network lifetime compared to the periodic model. PMID:28257067

  14. Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence

    NASA Astrophysics Data System (ADS)

    Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; Wyant, Matthew C.; Khairoutdinov, Marat

    2017-07-01

    Systematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called "ultraparameterization" (UP) is developed, in which the grid spacing of the cloud-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated clouds, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (˜14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers. Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and cloud vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) clouds, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL cloud-climate and cloud-aerosol feedback.

  15. A simple model for the cloud adjacency effect and the apparent bluing of aerosols near clouds

    NASA Astrophysics Data System (ADS)

    Marshak, Alexander; Wen, Guoyong; Coakley, James A.; Remer, Lorraine A.; Loeb, Norman G.; Cahalan, Robert F.

    2008-07-01

    In determining aerosol-cloud interactions, the properties of aerosols must be characterized in the vicinity of clouds. Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3-D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. The paper only addresses the cloud-clear sky radiative transfer interaction part. It provides a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. This assumption leads to a larger increase of AOT for shorter wavelengths, or to a "bluing" of aerosols near clouds. The assumption that contribution from molecular scattering dominates over aerosol scattering and surface reflection is justified for the case of shorter wavelengths, dark surfaces, and an aerosol layer below the cloud tops. The enhancement in Rayleigh scattering is estimated using a stochastic cloud model to obtain the radiative flux reflected by broken clouds and comparing this flux with that obtained with the molecules in the atmosphere causing extinction, but no scattering.

  16. 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.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/2060/19870005631','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19870005631"><span>Lower mass limit of an evolving interstellar <span class="hlt">cloud</span> and chemistry in an evolving oscillatory <span class="hlt">cloud</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Tarafdar, S. P.</p> <p>1986-01-01</p> <p>Simultaneous solution of the equation of motion, equation of state and energy equation including heating and cooling processes for interstellar medium gives for a collapsing <span class="hlt">cloud</span> a lower mass limit which is significantly smaller than the Jeans mass for the same initial density. The <span class="hlt">clouds</span> with higher mass than this limiting mass collapse whereas <span class="hlt">clouds</span> with smaller than critical mass pass through a maximum central density giving apparently similar <span class="hlt">clouds</span> (i.e., same Av, size and central density) at two different phases of its evolution (i.e., with different life time). Preliminary results of chemistry in such an evolving oscillatory <span class="hlt">cloud</span> show significant difference in abundances of some of the molecules in two physically similar <span class="hlt">clouds</span> with different life times. The problems of depletion and short life time of evolving <span class="hlt">clouds</span> appear to be less severe in such an oscillatory <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20130000799&hterms=cloud+database&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dcloud%2Bdatabase','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20130000799&hterms=cloud+database&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dcloud%2Bdatabase"><span>Validation of Satellite-Based Objective Overshooting <span class="hlt">Cloud</span>-Top Detection Methods Using <span class="hlt">Cloud</span>Sat <span class="hlt">Cloud</span> Profiling Radar Observations</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne</p> <p>2012-01-01</p> <p>Two satellite infrared-based overshooting convective <span class="hlt">cloud</span>-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 <span class="hlt">Cloud</span>Sat <span class="hlt">Cloud</span> 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. <span class="hlt">Cloud</span>Sat data were manually examined over a 1.5-yr period to identify cases in which the <span class="hlt">cloud</span> top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA560891','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA560891"><span><span class="hlt">Cloud</span> Computing for DoD</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2012-05-01</p> <p><span class="hlt">cloud</span> computing 17 NASA Nebula Platform •  <span class="hlt">Cloud</span> computing pilot program at NASA Ames •  Integrates open-source components into seamless, self...Mission support •  Education and public outreach (NASA Nebula , 2010) 18 NSF Supported <span class="hlt">Cloud</span> Research •  Support for <span class="hlt">Cloud</span> Computing in...Mell, P. & Grance, T. (2011). The NIST Definition of <span class="hlt">Cloud</span> Computing. NIST Special Publication 800-145 •  NASA Nebula (2010). Retrieved from</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1225112-evaluation-high-level-clouds-cloud-resolving-model-simulations-arm-kwajex-observations','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1225112-evaluation-high-level-clouds-cloud-resolving-model-simulations-arm-kwajex-observations"><span>Evaluation of high-level <span class="hlt">clouds</span> in <span class="hlt">cloud</span> resolving model simulations with ARM and KWAJEX observations</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas</p> <p>2015-11-05</p> <p>In this paper, we evaluate high-level <span class="hlt">clouds</span> in a <span class="hlt">cloud</span> resolving model during two convective cases, ARM9707 and KWAJEX. The simulated joint histograms of <span class="hlt">cloud</span> occurrence and radar reflectivity compare well with <span class="hlt">cloud</span> radar and satellite observations when using a two-moment microphysics scheme. However, simulations performed with a single moment microphysical scheme exhibit low biases of approximately 20 dB. During convective events, two-moment microphysical overestimate the amount of high-level <span class="hlt">cloud</span> and one-moment microphysics precipitate too readily and underestimate the amount and height of high-level <span class="hlt">cloud</span>. For ARM9707, persistent large positive biases in high-level <span class="hlt">cloud</span> are found, which are not sensitivemore » to changes in ice particle fall velocity and ice nuclei number concentration in the two-moment microphysics. These biases are caused by biases in large-scale forcing and maintained by the periodic lateral boundary conditions. The combined effects include significant biases in high-level <span class="hlt">cloud</span> amount, radiation, and high sensitivity of <span class="hlt">cloud</span> amount to nudging time scale in both convective cases. The high sensitivity of high-level <span class="hlt">cloud</span> amount to the thermodynamic nudging time scale suggests that thermodynamic nudging can be a powerful ‘‘tuning’’ parameter for the simulated <span class="hlt">cloud</span> and radiation but should be applied with caution. The role of the periodic lateral boundary conditions in reinforcing the biases in <span class="hlt">cloud</span> and radiation suggests that reducing the uncertainty in the large-scale forcing in high levels is important for similar convective cases and has far reaching implications for simulating high-level <span class="hlt">clouds</span> in super-parameterized global climate models such as the multiscale modeling framework.« less</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/2015IAUGA..2256499O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015IAUGA..2256499O"><span>Formation of compact HII regions possibly triggered by <span class="hlt">cloud-cloud</span> collision</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ohama, Akio; Torii, Kazufumi; Hasegawa, Keisuke; Fukui, Yasuo</p> <p>2015-08-01</p> <p>Compact HII regions are ionized by young high-mass star(s) and ~1000 compact HII regions are cataloged in the Galaxy (Urquhart et al. MNRAS 443, 1555-1586 (2014)). Compact HII regions are one of the major populations of Galactic HII regions. The molecular environments around compact HII regions are however not well understood due to lack of extensive molecular surveys. In order to better understand formation of exciting stars and compact HII regions, we have carried out a systematic study of molecular <span class="hlt">clouds</span> toward compact HII regions by using the 12CO datasets obtained with the JCMT and NANTEN2 telescopes for l = 10 - 56, and present here the first results.In one of the present samples, RCW166, we have discovered that the HII region is associated with two molecular <span class="hlt">clouds</span> whose velocity separation is ~10 km s-1 the two <span class="hlt">clouds</span> show complimentary spatial distributions, where one of the <span class="hlt">clouds</span> have a cavity-like distribution apparently embracing the other. We present an interpretation that the two <span class="hlt">clouds</span> collided with each other and the cavity-like distribution represents a hole created by the collision in the larger <span class="hlt">cloud</span> as modeled by Habe and Ohta (1992). Similar molecular distributions are often found in the other compact HII regions in the present study.A recent study by Torii et al. (2015, arXiv:1503.00070) indicates that the Spitzer bubble RCW120 was formed by <span class="hlt">cloud-cloud</span> collision where the inside of the cavity is fully ionized by the exiting stars. RCW166, on the other hand, shows that only a small part of the cavity, the compact HII region, is ionized. We thus suggest that RCW166 represents an evolutionary stage corresponding to an earlier phase of RCW120 in the collision scenario.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19910051324&hterms=acid+reflux&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dacid%2Breflux','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19910051324&hterms=acid+reflux&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dacid%2Breflux"><span>Prebiotic chemistry in <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>Oberbeck, Verne R.; Marshall, John; Shen, Thomas</p> <p>1991-01-01</p> <p>The chemical evolution hypothesis of Woese (1979), according to which prebiotic reactions occurred rapidly in droplets in giant atmospheric reflux columns was criticized by Scherer (1985). This paper proposes a mechanism for prebiotic chemistry in <span class="hlt">clouds</span> that answers Scherer's concerns and supports Woese's hypothesis. According to this mechanism, rapid prebiotic chemical evolution was facilitated on the primordial earth by cycles of condensation and evaporation of <span class="hlt">cloud</span> drops containing clay condensation nuclei and nonvolatile monomers. For example, amino acids supplied by, or synthesized during entry of meteorites, comets, and interplanetary dust, would have been scavenged by <span class="hlt">cloud</span> drops containing clay condensation nuclei and would be polymerized within <span class="hlt">cloud</span> systems during cycles of condensation, freezing, melting, and evaporation of <span class="hlt">cloud</span> drops.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080031138','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080031138"><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; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne</p> <p>2008-01-01</p> <p>Aerosols and especially their effect on <span class="hlt">clouds</span> are one of the key components of the climate system and the hydrological cycle [Ramanathan et al., 2001]. Yet, the aerosol effect on <span class="hlt">clouds</span> 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 <span class="hlt">clouds</span> [NRC, 2001]." The aerosol effect on <span class="hlt">clouds</span> is often categorized into the traditional "first indirect (i.e., Twomey)" effect on the <span class="hlt">cloud</span> droplet sizes for a constant liquid water path [Twomey, 1977] and the "semi-direct" effect on <span class="hlt">cloud</span> 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 <span class="hlt">clouds</span>. Table 1 summarizes the key observational studies identifying the microphysical properties, <span class="hlt">cloud</span> characteristics, thermodynamics and dynamics associated with <span class="hlt">cloud</span> systems from high-aerosol continental environments. For example, atmospheric aerosol concentrations can influence <span class="hlt">cloud</span> droplet size distributions, warm-rain process, cold-rain process, <span class="hlt">cloud</span>-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 <span class="hlt">cloud</span> 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</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70044500','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70044500"><span>Stable water isotopologue ratios in fog and <span class="hlt">cloud</span> droplets of liquid <span class="hlt">clouds</span> are not size-dependent</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Spiegel, J.K.; Aemisegger, F.; Scholl, M.; Wienhold, F.G.; Collett, J.L.; Lee, T.; van Pinxteren, D.; Mertes, S.; Tilgner, A.; Herrmann, H.; Werner, Roland A.; Buchmann, N.; Eugster, W.</p> <p>2012-01-01</p> <p>In this work, we present the first observations of stable water isotopologue ratios in <span class="hlt">cloud</span> droplets of different sizes collected simultaneously. We address the question whether the isotope ratio of droplets in a liquid <span class="hlt">cloud</span> varies as a function of droplet size. Samples were collected from a ground intercepted <span class="hlt">cloud</span> (= fog) during the Hill Cap <span class="hlt">Cloud</span> Thuringia 2010 campaign (HCCT-2010) using a three-stage Caltech Active Strand <span class="hlt">Cloud</span> water Collector (CASCC). An instrument test revealed that no artificial isotopic fractionation occurs during sample collection with the CASCC. Furthermore, we could experimentally confirm the hypothesis that the δ values of <span class="hlt">cloud</span> droplets of the relevant droplet sizes (μm-range) were not significantly different and thus can be assumed to be in isotopic equilibrium immediately with the surrounding water vapor. However, during the dissolution period of the <span class="hlt">cloud</span>, when the supersaturation inside the <span class="hlt">cloud</span> decreased and the <span class="hlt">cloud</span> began to clear, differences in isotope ratios of the different droplet sizes tended to be larger. This is likely to result from the <span class="hlt">cloud</span>'s heterogeneity, implying that larger and smaller <span class="hlt">cloud</span> droplets have been collected at different moments in time, delivering isotope ratios from different collection times.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20050210129&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dsimulation%2Bprocesses','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20050210129&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%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; Li, X.; Khain, A.; Simpson, S.</p> <p>2005-01-01</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 distributions 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 for convective <span class="hlt">clouds</span>. 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., <span class="hlt">cloud</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017NatCC...7..674Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017NatCC...7..674Z"><span>Clearing <span class="hlt">clouds</span> of uncertainty</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zelinka, Mark D.; Randall, David A.; Webb, Mark J.; Klein, Stephen A.</p> <p>2017-10-01</p> <p>Since 1990, the wide range in model-based estimates of equilibrium climate warming has been attributed to disparate <span class="hlt">cloud</span> responses to warming. However, major progress in our ability to understand, observe, and simulate <span class="hlt">clouds</span> has led to the conclusion that global <span class="hlt">cloud</span> feedback is likely positive.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA21051.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA21051.html"><span>Watching Summer <span class="hlt">Clouds</span> on Titan</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2016-11-04</p> <p>NASA's Cassini spacecraft watched <span class="hlt">clouds</span> of methane moving across the far northern regions of Saturn's largest moon, Titan, on Oct. 29 and 30, 2016. Several sets of <span class="hlt">clouds</span> develop, move over the surface and fade during the course of this movie sequence, which spans 11 hours, with one frame taken every 20 minutes. Most prominent are long <span class="hlt">cloud</span> streaks that lie between 49 and 55 degrees north latitude. While the general region of <span class="hlt">cloud</span> activity is persistent over the course of the observation, individual streaks appear to develop then fade. These <span class="hlt">clouds</span> are measured to move at a speed of about 14 to 22 miles per hour (7 to 10 meters per second). There are also some small <span class="hlt">clouds</span> over the region of small lakes farther north, including a bright <span class="hlt">cloud</span> between Neagh Lacus and Punga Mare, which fade over the course of the movie. This small grouping of <span class="hlt">clouds</span> is moving at a speed of about 0.7 to 1.4 miles per hour (1 to 2 meters per second). Time-lapse movies like this allow scientists to observe the dynamics of <span class="hlt">clouds</span> as they develop, move over the surface and fade. A time-lapse movie can also help to distinguish between noise in images (for example from cosmic rays hitting the detector) and faint <span class="hlt">clouds</span> or fog. In 2016, Cassini has intermittently observed <span class="hlt">clouds</span> across the northern mid-latitudes of Titan, as well as within the north polar region -- an area known to contain numerous methane/ethane lakes and seas see PIA19657 and PIA17655. However, most of this year's observations designed for <span class="hlt">cloud</span> monitoring have been short snapshots taken days, or weeks, apart. This observation provides Cassini's best opportunity in 2016 to study short-term <span class="hlt">cloud</span> dynamics. Models of Titan's climate have predicted more <span class="hlt">cloud</span> activity during early northern summer than what Cassini has observed so far, suggesting that the current understanding of the giant moon's changing seasons is incomplete. The mission will continue monitoring Titan's weather around the 2017 summer solstice in Titan</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20110015527','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20110015527"><span>Fast Simulators for Satellite <span class="hlt">Cloud</span> Optical Centroid Pressure Retrievals, 1. Evaluation of OMI <span class="hlt">Cloud</span> Retrievals</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert</p> <p>2011-01-01</p> <p>We have developed a relatively simple scheme for simulating retrieved <span class="hlt">cloud</span> optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of <span class="hlt">cloud</span> OCPs from the two OMI algorithms using collocated data from <span class="hlt">Cloud</span>Sat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated <span class="hlt">Cloud</span>Sat data. This indicates that patchy snow/ice, <span class="hlt">cloud</span> 3D, and aerosol effects not simulated with the <span class="hlt">Cloud</span>Sat data are affecting both algorithms similarly. We note that the collocation with <span class="hlt">Cloud</span>Sat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI <span class="hlt">cloud</span> OCP retrievals. Our fast simulator may also be used to simulate <span class="hlt">cloud</span> OCP from output generated by general circulation models (GCM) with appropriate account of <span class="hlt">cloud</span> overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19990028514','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19990028514"><span>FIRE Arctic <span class="hlt">Clouds</span> Experiment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Curry, J. A.; Hobbs, P. V.; King, M. D.; Randall, D. A.; Minnis, P.; Issac, G. A.; Pinto, J. O.; Uttal, T.; Bucholtz, A.; Cripe, D. G.; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_19990028514'); toggleEditAbsImage('author_19990028514_show'); toggleEditAbsImage('author_19990028514_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_19990028514_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_19990028514_hide"></p> <p>1998-01-01</p> <p>An overview is given of the First ISCCP Regional Experiment (FIRE) Arctic <span class="hlt">Clouds</span> Experiment that was conducted in the Arctic during April through July, 1998. The principal goal of the field experiment was to gather the data needed to examine the impact of arctic <span class="hlt">clouds</span> on the radiation exchange between the surface, atmosphere, and space, and to study how the surface influences the evolution of boundary layer <span class="hlt">clouds</span>. The observations will be used to evaluate and improve climate model parameterizations of <span class="hlt">cloud</span> and radiation processes, satellite remote sensing of <span class="hlt">cloud</span> and surface characteristics, and understanding of <span class="hlt">cloud</span>-radiation feedbacks in the Arctic. The experiment utilized four research aircraft that flew over surface-based observational sites in the Arctic Ocean and Barrow, Alaska. In this paper we describe the programmatic and science objectives of the project, the experimental design (including research platforms and instrumentation), conditions that were encountered during the field experiment, and some highlights of preliminary observations, modelling, and satellite remote sensing studies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006463','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006463"><span>The ENSO Effects on Tropical <span class="hlt">Clouds</span> and Top-of-Atmosphere <span class="hlt">Cloud</span> Radiative Effects in CMIP5 Models</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Su, Wenying; Wang, Hailan</p> <p>2015-01-01</p> <p>The El Nino-Southern Oscillation (ENSO) effects on tropical <span class="hlt">clouds</span> and top-of-atmosphere (TOA) <span class="hlt">cloud</span> radiative effects (CREs) in Coupled Model Intercomparison Project Phase5 (CMIP5) models are evaluated using satellite-based observations and International Satellite <span class="hlt">Cloud</span> Climatology Project satellite simulator output. Climatologically, most CMIP5 models produce considerably less total <span class="hlt">cloud</span> amount with higher <span class="hlt">cloud</span> top and notably larger reflectivity than observations in tropical Indo-Pacific (60 degrees East - 200 degrees East; 10 degrees South - 10 degrees North). During ENSO, most CMIP5 models considerably underestimate TOA CRE and <span class="hlt">cloud</span> changes over western tropical Pacific. Over central tropical Pacific, while the multi-model mean resembles observations in TOA CRE and <span class="hlt">cloud</span> amount anomalies, it notably overestimates <span class="hlt">cloud</span> top pressure (CTP) decreases; there are also substantial inter-model variations. The relative effects of changes in <span class="hlt">cloud</span> properties, temperature and humidity on TOA CRE anomalies during ENSO in the CMIP5 models are assessed using <span class="hlt">cloud</span> radiative kernels. The CMIP5 models agree with observations in that their TOA shortwave CRE anomalies are primarily contributed by total <span class="hlt">cloud</span> amount changes, and their TOA longwave CRE anomalies are mostly contributed by changes in both total <span class="hlt">cloud</span> amount and CTP. The model biases in TOA CRE anomalies particularly the strong underestimations over western tropical Pacific are, however, mainly explained by model biases in CTP and <span class="hlt">cloud</span> optical thickness (tau) changes. Despite the distinct model <span class="hlt">cloud</span> biases particularly in tau regime, the TOA CRE anomalies from <span class="hlt">cloud</span> amount changes are comparable between the CMIP5 models and observations, because of the strong compensations between model underestimation of TOA CRE anomalies from thin <span class="hlt">clouds</span> and overestimation from medium and thick <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100033542','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100033542"><span>Characterization of <span class="hlt">Cloud</span> Water-Content Distribution</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Lee, Seungwon</p> <p>2010-01-01</p> <p>The development of realistic <span class="hlt">cloud</span> parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize <span class="hlt">cloud</span> water-content distributions in climate-model sub-grid scales. This software characterizes distributions of <span class="hlt">cloud</span> water content with respect to <span class="hlt">cloud</span> phase, <span class="hlt">cloud</span> type, precipitation occurrence, and geo-location using <span class="hlt">Cloud</span>Sat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the <span class="hlt">cloud</span> water content.</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>Nowadays, space remote sensing measurements are a very useful way to study the atmosphere on a global scale. Among the numerous scientific satellites in space, the A-Train is a constellation of 6 satellites flying together with on board complementary instruments of new generation (radiometers, radar, lidar, spectrometers…) to study all parts of the atmosphere: gas composition, <span class="hlt">clouds</span> and aerosols distribution and properties, and radiation budget. Among these satellites, two of them where launched in 2006: CALIPSO and <span class="hlt">Cloud</span>Sat, respectively with a Lidar (532 and 1064 nm channels with depolarization) and a 94 GHz radar on board. They are especially dedicated to the study of <span class="hlt">clouds</span> and aerosols, and will allow to obtain for the first time the vertical profiles of <span class="hlt">clouds</span> and aerosols on a global scale during 3 years. However, to determine <span class="hlt">clouds</span> and aerosols properties from space raw data, retrieval methods need to be developed. In order to validate these retrieved techniques, and thus the <span class="hlt">clouds</span> and aerosols properties, numerous validation plans take place around the world, included different ways as ground based measurements, in situ measurements, or airborne remote sensing instruments in collocation with the satellite tracks. In this context, the ASTAR-2007 and POLARCAT-2008 campaigns took place respectively in the Arctic region of Spitzbergen-Norway in April 2007 and in North part of Sweden in April 2008 to study mixed-phase <span class="hlt">clouds</span> and the CIRCLE-2 campaign was carried out in Western Europe in May 2007 to sample mid-latitude cirrus <span class="hlt">clouds</span>. The main objectives are the study of microphysical and optical properties of mixed-phase and ice <span class="hlt">clouds</span> with particular interest on the validation of <span class="hlt">clouds</span> products derived from <span class="hlt">Cloud</span>Sat and CALIPSO data during co-located remote and in situ observations. The airborne microphysical instruments include the Polar Nephelometer probe to measure the scattering phase function and asymmetry parameter of <span class="hlt">cloud</span> particles, the high</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 identify 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://eric.ed.gov/?q=full+AND+cloud+AND+computing&id=EJ959893','ERIC'); return false;" href="https://eric.ed.gov/?q=full+AND+cloud+AND+computing&id=EJ959893"><span><span class="hlt">Cloud</span> Control</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>Ramaswami, Rama; Raths, David; Schaffhauser, Dian; Skelly, Jennifer</p> <p>2011-01-01</p> <p>For many IT shops, the <span class="hlt">cloud</span> offers an opportunity not only to improve operations but also to align themselves more closely with their schools' strategic goals. The <span class="hlt">cloud</span> is not a plug-and-play proposition, however--it is a complex, evolving landscape that demands one's full attention. Security, privacy, contracts, and contingency planning are all…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=cloud+AND+computing+AND+article&id=EJ991845','ERIC'); return false;" href="https://eric.ed.gov/?q=cloud+AND+computing+AND+article&id=EJ991845"><span><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>Schaffhauser, Dian</p> <p>2012-01-01</p> <p>This article features a major statewide initiative in North Carolina that is showing how a consortium model can minimize risks for districts and help them exploit the advantages of <span class="hlt">cloud</span> computing. Edgecombe County Public Schools in Tarboro, North Carolina, intends to exploit a major <span class="hlt">cloud</span> initiative being refined in the state and involving every…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1425466','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1425466"><span>Toward low-<span class="hlt">cloud</span>-permitting <span class="hlt">cloud</span> superparameterization with explicit boundary layer turbulence</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>Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.</p> <p></p> <p>Systematic biases in the representation of boundary layer (BL) <span class="hlt">clouds</span> are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the <span class="hlt">cloud</span>-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated <span class="hlt">clouds</span>, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and <span class="hlt">cloud</span> vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) <span class="hlt">clouds</span>, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL <span class="hlt">cloud</span>-climate and <span class="hlt">cloud</span>-aerosol feedback.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1425466-toward-low-cloud-permitting-cloud-superparameterization-explicit-boundary-layer-turbulence','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1425466-toward-low-cloud-permitting-cloud-superparameterization-explicit-boundary-layer-turbulence"><span>Toward low-<span class="hlt">cloud</span>-permitting <span class="hlt">cloud</span> superparameterization with explicit boundary layer turbulence</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Parishani, Hossein; Pritchard, Michael S.; Bretherton, Christopher S.; ...</p> <p>2017-06-19</p> <p>Systematic biases in the representation of boundary layer (BL) <span class="hlt">clouds</span> are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the <span class="hlt">cloud</span>-resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL turbulence, associated <span class="hlt">clouds</span>, and entrainment in a global climate model capable of multiyear simulations. UP is implemented within the Community Atmosphere Model using 2° resolution (~14,000 embedded CRMs) with one-moment microphysics. By using a small domain and mean-state acceleration, UP is computationally feasible today and promising for exascale computers.more » Short-duration global UP hindcasts are compared with SP and satellite observations of top-of-atmosphere radiation and <span class="hlt">cloud</span> vertical structure. The most encouraging improvement is a deeper BL and more realistic vertical structure of subtropical stratocumulus (Sc) <span class="hlt">clouds</span>, due to stronger vertical eddy motions that promote entrainment. Results from 90 day integrations show climatological errors that are competitive with SP, with a significant improvement in the diurnal cycle of offshore Sc liquid water. Ongoing concerns with the current UP implementation include a dim bias for near-coastal Sc that also occurs less prominently in SP and a bright bias over tropical continental deep convection zones. Nevertheless, UP makes global eddy-permitting simulation a feasible and interesting alternative to conventionally parameterized GCMs or SP-GCMs with turbulence parameterizations for studying BL <span class="hlt">cloud</span>-climate and <span class="hlt">cloud</span>-aerosol feedback.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016EGUGA..18.9318F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016EGUGA..18.9318F"><span>Delivering Unidata Technology via 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>Fisher, Ward; Oxelson Ganter, Jennifer</p> <p>2016-04-01</p> <p>Over the last two years, Docker has emerged as the clear leader in open-source containerization. Containerization technology provides a means by which software can be pre-configured and packaged into a single unit, i.e. a container. This container can then be easily deployed either on local or remote systems. Containerization is particularly advantageous when moving software into the <span class="hlt">cloud</span>, as it simplifies the process. Unidata is adopting containerization as part of our commitment to migrate our technologies to the <span class="hlt">cloud</span>. We are using a two-pronged approach in this endeavor. In addition to migrating our data-portal services to a <span class="hlt">cloud</span> environment, we are also exploring new and novel ways to use <span class="hlt">cloud</span>-specific technology to serve our community. This effort has resulted in several new <span class="hlt">cloud</span>/Docker-specific projects at Unidata: "<span class="hlt">Cloud</span>Stream," "<span class="hlt">Cloud</span>IDV," and "<span class="hlt">Cloud</span>Control." <span class="hlt">Cloud</span>Stream is a docker-based technology stack for bringing legacy desktop software to new computing environments, without the need to invest significant engineering/development resources. <span class="hlt">Cloud</span>Stream helps make it easier to run existing software in a <span class="hlt">cloud</span> environment via a technology called "Application Streaming." <span class="hlt">Cloud</span>IDV is a <span class="hlt">Cloud</span>Stream-based implementation of the Unidata Integrated Data Viewer (IDV). <span class="hlt">Cloud</span>IDV serves as a practical example of application streaming, and demonstrates how traditional software can be easily accessed and controlled via a web browser. Finally, <span class="hlt">Cloud</span>Control is a web-based dashboard which provides administrative controls for running docker-based technologies in the <span class="hlt">cloud</span>, as well as providing user management. In this work we will give an overview of these three open-source technologies and the value they offer to our community.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015EntIS...9..186R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015EntIS...9..186R"><span><span class="hlt">Cloud</span> manufacturing: from concept to practice</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ren, Lei; Zhang, Lin; Tao, Fei; Zhao, Chun; Chai, Xudong; Zhao, Xinpei</p> <p>2015-02-01</p> <p>The concept of <span class="hlt">cloud</span> manufacturing is emerging as a new promising manufacturing paradigm, as well as a business model, which is reshaping the service-oriented, highly collaborative, knowledge-intensive and eco-efficient manufacturing industry. However, the basic concepts about <span class="hlt">cloud</span> manufacturing are still in discussion. Both academia and industry will need to have a commonly accepted definition of <span class="hlt">cloud</span> manufacturing, as well as further guidance and recommendations on how to develop and implement <span class="hlt">cloud</span> manufacturing. In this paper, we review some of the research work and clarify some fundamental terminologies in this field. Further, we developed a <span class="hlt">cloud</span> manufacturing systems which may serve as an application example. From a systematic and practical perspective, the key requirements of <span class="hlt">cloud</span> manufacturing platforms are investigated, and then we propose a <span class="hlt">cloud</span> manufacturing platform prototype, Mfg<span class="hlt">Cloud</span>. Finally, a public <span class="hlt">cloud</span> manufacturing system for small- and medium-sized enterprises (SME) is presented. This paper presents a new perspective for <span class="hlt">cloud</span> manufacturing, as well as a <span class="hlt">cloud</span>-to-ground solution. The integrated solution proposed in this paper, including the terminology, Mfg<span class="hlt">Cloud</span>, and applications, can push forward this new paradigm from concept to practice.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ACP....1713151C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ACP....1713151C"><span>Unveiling aerosol-<span class="hlt">cloud</span> interactions - Part 1: <span class="hlt">Cloud</span> contamination in satellite products enhances the aerosol indirect forcing estimate</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.</p> <p>2017-11-01</p> <p>Increased concentrations of aerosol can enhance the albedo of warm low-level <span class="hlt">cloud</span>. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near <span class="hlt">clouds</span>. Aerosol retrievals near <span class="hlt">clouds</span> can be influenced by stray <span class="hlt">cloud</span> particles in areas assumed to be <span class="hlt">cloud</span>-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) <span class="hlt">clouds</span>. To screen for this contamination we have developed a new <span class="hlt">cloud</span>-aerosol pairing algorithm (CAPA) to link <span class="hlt">cloud</span> observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest <span class="hlt">cloud</span> is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the <span class="hlt">clouds</span> (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest <span class="hlt">cloud</span> (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to <span class="hlt">cloud</span> artificially enhance the relationship between aerosol-loading, <span class="hlt">cloud</span> albedo, and <span class="hlt">cloud</span> fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near <span class="hlt">clouds</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_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('https://www.osti.gov/pages/biblio/1410034-clearing-clouds-uncertainty','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1410034-clearing-clouds-uncertainty"><span>Clearing <span class="hlt">clouds</span> of uncertainty</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Zelinka, Mark D.; Randall, David A.; Webb, Mark J.; ...</p> <p>2017-09-29</p> <p>We report that since 1990, the wide range in model-based estimates of equilibrium climate warming has been attributed to disparate <span class="hlt">cloud</span> responses to warming. However, major progress in our ability to understand, observe, and simulate <span class="hlt">clouds</span> has led to the conclusion that global <span class="hlt">cloud</span> feedback is likely positive.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA21074.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA21074.html"><span><span class="hlt">Clouds</span> on Hot Jupiters Illustration</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2016-10-18</p> <p>Hot Jupiters are exoplanets that orbit their stars so tightly that their temperatures are extremely high, reaching over 2,400 degrees Fahrenheit (1600 Kelvin). They are also tidally locked, so one side of the planet always faces the sun and the other is in permanent darkness. Research suggests that the "dayside" is largely free of <span class="hlt">clouds</span>, while the "nightside" is heavily <span class="hlt">clouded</span>. This illustration represents how hot Jupiters of different temperatures and different <span class="hlt">cloud</span> compositions might appear to a person flying over the dayside of these planets on a spaceship, based on computer modeling. Cooler planets are entirely cloudy, whereas hotter planets have morning <span class="hlt">clouds</span> only. <span class="hlt">Clouds</span> of different composition have different colors, whereas the clear sky is bluer than on Earth. For the hottest planets, the atmosphere is hot enough on the evening side to glow like a charcoal. Figure 1 shows an approximation of what various hot Jupiters might look like based on a combination of computer modeling and data from NASA's Kepler Space Telescope. From left to right it shows: sodium sulfide <span class="hlt">clouds</span> (1000 to 1200 Kelvin), manganese sulfide <span class="hlt">clouds</span> (1200 to 1600 Kelvin), magnesium silicate <span class="hlt">clouds</span> (1600 to 1800 Kelvin), magnesium silicate and aluminum oxide <span class="hlt">clouds</span> (1800 Kelvin) and <span class="hlt">clouds</span> composed of magnesium silicate, aluminum oxide, iron and calcium titanate (1900 to 2200 Kelvin). http://photojournal.jpl.nasa.gov/catalog/PIA21074</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4055364','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4055364"><span><span class="hlt">Cloud</span> Model Bat Algorithm</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi</p> <p>2014-01-01</p> <p>Bat algorithm (BA) is a novel stochastic global optimization algorithm. <span class="hlt">Cloud</span> model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of <span class="hlt">cloud</span> model on uncertainty knowledge representation, a new <span class="hlt">cloud</span> model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of <span class="hlt">cloud</span> model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the <span class="hlt">cloud</span> model bat algorithm has good performance on functions optimization. PMID:24967425</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/25977891','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/25977891"><span>Exploring the factors influencing the <span class="hlt">cloud</span> computing adoption: a systematic study on <span class="hlt">cloud</span> migration.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Rai, Rashmi; Sahoo, Gadadhar; Mehfuz, Shabana</p> <p>2015-01-01</p> <p>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, <span class="hlt">cloud</span> services offer a more agile and cost effective platform, to support business applications and IT infrastructure. As the adoption of <span class="hlt">cloud</span> services has been increasing recently and so has been the academic research in <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> migration. The paper has also endeavored to consolidate the research on Security issues, which is prime factor hindering the adoption of <span class="hlt">cloud</span> through classifying the studies on secure <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> migration which has resulted in a resource base of existing solutions for <span class="hlt">cloud</span> migration. This study concludes that <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> migration and facilitate necessary tool support to automate the migration process.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=cloud+AND+computing&pg=3&id=EJ901485','ERIC'); return false;" href="https://eric.ed.gov/?q=cloud+AND+computing&pg=3&id=EJ901485"><span>Embracing the <span class="hlt">Cloud</span>: Six Ways to Look at the Shift to <span class="hlt">Cloud</span> Computing</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>Ullman, David F.; Haggerty, Blake</p> <p>2010-01-01</p> <p><span class="hlt">Cloud</span> computing is the latest paradigm shift for the delivery of IT services. Where previous paradigms (centralized, decentralized, distributed) were based on fairly straightforward approaches to technology and its management, <span class="hlt">cloud</span> computing is radical in comparison. The literature on <span class="hlt">cloud</span> computing, however, suffers from many divergent…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=silk+AND+road&id=EJ989799','ERIC'); return false;" href="https://eric.ed.gov/?q=silk+AND+road&id=EJ989799"><span><span class="hlt">Cloud</span> Control</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>Weinstein, Margery</p> <p>2012-01-01</p> <p>Your learning curriculum needs a new technological platform, but you don't have the expertise or IT equipment to pull it off in-house. The answer is a learning system that exists online, "in the <span class="hlt">cloud</span>," where learners can access it anywhere, anytime. For trainers, <span class="hlt">cloud</span>-based coursework often means greater ease of instruction resulting in greater…</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 identify 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/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 identify 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://ntrs.nasa.gov/search.jsp?R=19830056199&hterms=ia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dia','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19830056199&hterms=ia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dia"><span>The <span class="hlt">clouds</span> are hazes of Venus</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Esposito, L. W.; Knollenberg, R. G.; Marov, M. IA.; Toon, O. B.; Turco, R. P.</p> <p>1983-01-01</p> <p>Pioneer Venus and Venera probe data for the <span class="hlt">clouds</span> of Venus are considered. These <span class="hlt">clouds</span> consist of a main <span class="hlt">cloud</span> deck at 45-70 km altitude, with thinner hazes above and below, although the microphysical properties of the main <span class="hlt">cloud</span> are further subdivided into upper, middle and lower <span class="hlt">cloud</span> levels. Much of the <span class="hlt">cloud</span> exhibits a multimodal particle size distribution, with the mode most visible from the earth being H2SO4 droplets having 2-3 micron diameters. Despite variations, the vertical structure of the <span class="hlt">clouds</span> indicates persistent features at sites separated by years and by great distances. The <span class="hlt">clouds</span> are more strongly affected by radiation than by latent heat release, and the small particle size and weak convective activity observed are incompatible with lightning of <span class="hlt">cloud</span> origin.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/21863719','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/21863719"><span>Security 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>Degaspari, John</p> <p>2011-08-01</p> <p>As more provider organizations look to the <span class="hlt">cloud</span> computing model, they face a host of security-related questions. What are the appropriate applications for the <span class="hlt">cloud</span>, what is the best <span class="hlt">cloud</span> model, and what do they need to know to choose the best vendor? Hospital CIOs and security experts weigh in.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012AGUFM.A54B..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A54B..08S"><span><span class="hlt">Cloud</span> evaluation using satellite simulators and <span class="hlt">cloud</span> changes for global nonhydrostatic simulations with NICAM</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Satoh, M.; Noda, A. T.; Kodama, C.; Yamada, Y.; Hashino, T.</p> <p>2012-12-01</p> <p>Global <span class="hlt">cloud</span> distributions and properties simulated by the global nonhydrostatic model, NICAM (Nonhydrostatic Icosahedral Atmospheric Model), are evaluated and their future changes are discussed. First, we evaluated the simulated <span class="hlt">cloud</span> properties produced by a case study of the 3.5km mesh experiment of NICAM using the satellite simulator package (the Joint-simulator) with <span class="hlt">cloud</span> microphysics oriented approach (Hashino et al. 2012). Then, we analyzed future <span class="hlt">cloud</span> changes using various sets of simulations under the present and the future global warming conditions. The results show that the zonal averaged ice water path (IWP) generally decreases or marginally unchanged in the tropics, while IWP in the extra-tropics increases. The upper <span class="hlt">cloud</span> fraction increases both in the tropics and in the extra-tropics in general. We further analyzed contributions of <span class="hlt">cloud</span> systems such as <span class="hlt">cloud</span> clusters, tropical cyclones (TCs), and storm-tracks to these changes. Probability distribution of the larger <span class="hlt">cloud</span> clusters decreases, while that of the smaller ones increases, consistent with the decrease in the number of tropical cyclones in the future climate. Average liquid water path (LWP) and IWP associated with each tropical cyclone are diagnosed, and it is found that both the associated LWP and IWP increase under the warmer condition. Even though, since the number of the intensive <span class="hlt">cloud</span> systems decrease, the average IWP decreases. It should be remarked that the change in TC tracks largely contribute to the change in the horizontal distribution of <span class="hlt">clouds</span>. The NICAM simulations also show that the storm-tracks shift poleward, and the storms become less frequent and stronger in the extra-tropics, similar to the results of other general circulation models. Both LWP and IWP associated with the storms also increase in the warmer climate in the NICAM simulations. This results in increase in the upper <span class="hlt">clouds</span> under the warmer climate condition, as described by Miura et al. (2005). References</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MS%26E..263d2016A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MS%26E..263d2016A"><span>Dynamic virtual machine allocation policy in <span class="hlt">cloud</span> computing complying with service level agreement using <span class="hlt">Cloud</span>Sim</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Aneri, Parikh; Sumathy, S.</p> <p>2017-11-01</p> <p><span class="hlt">Cloud</span> computing provides services over the internet and provides application resources and data to the users based on their demand. Base of the <span class="hlt">Cloud</span> Computing is consumer provider model. <span class="hlt">Cloud</span> provider provides resources which consumer can access using <span class="hlt">cloud</span> computing model in order to build their application based on their demand. <span class="hlt">Cloud</span> data center is a bulk of resources on shared pool architecture for <span class="hlt">cloud</span> user to access. Virtualization is the heart of the <span class="hlt">Cloud</span> computing model, it provides virtual machine as per application specific configuration and those applications are free to choose their own configuration. On one hand, there is huge number of resources and on other hand it has to serve huge number of requests effectively. Therefore, resource allocation policy and scheduling policy play very important role in allocation and managing resources in this <span class="hlt">cloud</span> computing model. This paper proposes the load balancing policy using Hungarian algorithm. Hungarian Algorithm provides dynamic load balancing policy with a monitor component. Monitor component helps to increase <span class="hlt">cloud</span> resource utilization by managing the Hungarian algorithm by monitoring its state and altering its state based on artificial intelligent. <span class="hlt">Cloud</span>Sim used in this proposal is an extensible toolkit and it simulates <span class="hlt">cloud</span> computing environment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017nova.pres.2768K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017nova.pres.2768K"><span>Making and Breaking <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>Kohler, Susanna</p> <p>2017-10-01</p> <p>Molecular <span class="hlt">clouds</span> which youre likely familiar with from stunning popular astronomy imagery lead complicated, tumultuous lives. A recent study has now found that these features must be rapidly built and destroyed.Star-Forming CollapseA Hubble view of a molecular <span class="hlt">cloud</span>, roughly two light-years long, that has broken off of the Carina Nebula. [NASA/ESA, N. Smith (University of California, Berkeley)/The Hubble Heritage Team (STScI/AURA)]Molecular gas can be found throughout our galaxy in the form of eminently photogenic <span class="hlt">clouds</span> (as featured throughout this post). Dense, cold molecular gas makes up more than 20% of the Milky Ways total gas mass, and gravitational instabilities within these <span class="hlt">clouds</span> lead them to collapse under their own weight, resulting in the formation of our galaxys stars.How does this collapse occur? The simplest explanation is that the <span class="hlt">clouds</span> simply collapse in free fall, with no source of support to counter their contraction. But if all the molecular gas we observe collapsed on free-fall timescales, star formation in our galaxy would churn a rate thats at least an order of magnitude higher than the observed 12 solar masses per year in the Milky Way.Destruction by FeedbackAstronomers have theorized that there may be some mechanism that supports these <span class="hlt">clouds</span> against gravity, slowing their collapse. But both theoretical studies and observations of the <span class="hlt">clouds</span> have ruled out most of these potential mechanisms, and mounting evidence supports the original interpretation that molecular <span class="hlt">clouds</span> are simply gravitationally collapsing.A sub-mm image from ESOs APEX telescope of part of the Taurus molecular <span class="hlt">cloud</span>, roughly ten light-years long, superimposed on a visible-light image of the region. [ESO/APEX (MPIfR/ESO/OSO)/A. Hacar et al./Digitized Sky Survey 2. Acknowledgment: Davide De Martin]If this is indeed the case, then one explanation for our low observed star formation rate could be that molecular <span class="hlt">clouds</span> are rapidly destroyed by feedback from the very stars</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> typing 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('http://adsabs.harvard.edu/abs/2017JGRD..122.7086F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.7086F"><span>Analysis of albedo versus <span class="hlt">cloud</span> fraction relationships in liquid water <span class="hlt">clouds</span> using heuristic models and large eddy simulation</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; Balsells, Joseph; Glassmeier, Franziska; Yamaguchi, Takanobu; Kazil, Jan; McComiskey, Allison</p> <p>2017-07-01</p> <p>The relationship between the albedo of a cloudy scene A and <span class="hlt">cloud</span> fraction fc is studied with the aid of heuristic models of stratocumulus and cumulus <span class="hlt">clouds</span>. Existing work has shown that scene albedo increases monotonically with increasing <span class="hlt">cloud</span> fraction but that the relationship varies from linear to superlinear. The reasons for these differences in functional dependence are traced to the relationship between <span class="hlt">cloud</span> deepening and <span class="hlt">cloud</span> widening. When <span class="hlt">clouds</span> deepen with no significant increase in fc (e.g., in solid stratocumulus), the relationship between A and fc is linear. When <span class="hlt">clouds</span> widen as they deepen, as in cumulus <span class="hlt">cloud</span> fields, the relationship is superlinear. A simple heuristic model of a cumulus <span class="hlt">cloud</span> field with a power law size distribution shows that the superlinear A-fc behavior is traced out either through random variation in <span class="hlt">cloud</span> size distribution parameters or as the <span class="hlt">cloud</span> field oscillates between a relative abundance of small <span class="hlt">clouds</span> (steep slopes on a log-log plot) and a relative abundance of large <span class="hlt">clouds</span> (flat slopes). Oscillations of this kind manifest in large eddy simulation of trade wind cumulus where the slope and intercept of the power law fit to the <span class="hlt">cloud</span> size distribution are highly correlated. Further analysis of the large eddy model-generated <span class="hlt">cloud</span> fields suggests that cumulus <span class="hlt">clouds</span> grow larger and deeper as their underlying plumes aggregate; this is followed by breakup of large plumes and a tendency to smaller <span class="hlt">clouds</span>. The <span class="hlt">cloud</span> and thermal size distributions oscillate back and forth approximately in unison.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A41J..05C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A41J..05C"><span>Aerosol-<span class="hlt">cloud</span> feedbacks in a turbulent environment: Laboratory measurements representative of conditions in 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>Cantrell, W. H.; Chandrakar, K. K.; Karki, S.; Kinney, G.; Shaw, R.</p> <p>2017-12-01</p> <p>Many of the climate impacts of boundary layer <span class="hlt">clouds</span> are modulated by aerosol particles. As two examples, their interactions with incoming solar and upwelling terrestrial radiation and their propensity for precipitation are both governed by the population of aerosol particles upon which the <span class="hlt">cloud</span> droplets formed. In turn, <span class="hlt">clouds</span> are the primary removal mechanism for aerosol particles smaller than a few micrometers and larger than a few nanometers. Aspects of these interconnected phenomena are known in exquisite detail (e.g. Köhler theory), but other parts have not been as amenable to study in the laboratory (e.g. scavenging of aerosol particles by <span class="hlt">cloud</span> droplets). As a complicating factor, boundary layer <span class="hlt">clouds</span> are ubiquitously turbulent, which introduces fluctuations in the water vapor concentration and temperature, which govern the saturation ratio which mediates aerosol-<span class="hlt">cloud</span> interactions. We have performed laboratory measurements of aerosol-<span class="hlt">cloud</span> coupling and feedbacks, using Michigan Tech's Pi Chamber (Chang et al., 2016). In conditions representative of boundary layer <span class="hlt">clouds</span>, our data suggest that the lifetime of most interstitial particles in the accumulation mode is governed by <span class="hlt">cloud</span> activation - particles are removed from the Pi Chamber when they activate and settle out of the chamber as <span class="hlt">cloud</span> droplets. As <span class="hlt">cloud</span> droplets are removed, these interstitial particles activate until the initially polluted <span class="hlt">cloud</span> cleans itself and all particulates are removed from the chamber. At that point, the <span class="hlt">cloud</span> collapses. Our data also indicate that smaller particles, Dp < ˜ 20 nm are not activated, but are instead removed through diffusion, enhanced by the fact that droplets are moving relative to the suspended aerosol. I will discuss results from both warm (i.e. liquid water only) and mixed phase <span class="hlt">clouds</span>, showing that <span class="hlt">cloud</span> and aerosol properties are coupled through fluctuations in the supersaturation, and that threshold behaviors can be defined through the use of the D</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013EGUGA..1511300W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1511300W"><span>Global aerosol effects on 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>Wagner, Till; Stier, Philip</p> <p>2013-04-01</p> <p>Atmospheric aerosols affect <span class="hlt">cloud</span> properties, and thereby the radiation balance of the planet and the water cycle. The influence of aerosols on <span class="hlt">clouds</span> is dominated by increase of <span class="hlt">cloud</span> droplet and ice crystal numbers (CDNC/ICNC) due to enhanced aerosols acting as <span class="hlt">cloud</span> condensation and ice nuclei. In deep convective <span class="hlt">clouds</span> this increase in CDNC/ICNC is hypothesised to increase precipitation because of <span class="hlt">cloud</span> invigoration through enhanced freezing and associated increased latent heat release caused by delayed warm rain formation. Satellite studies robustly show an increase of <span class="hlt">cloud</span> top height (CTH) and precipitation with increasing aerosol optical depth (AOD, as proxy for aerosol amount). To represent aerosol effects and study their influence on convective <span class="hlt">clouds</span> in the global climate aerosol model ECHAM-HAM, we substitute the standard convection parameterisation, which uses one mean convective <span class="hlt">cloud</span> for each grid column, with the convective <span class="hlt">cloud</span> field model (CCFM), which simulates a spectrum of convective <span class="hlt">clouds</span>, each with distinct values of radius, mixing ratios, vertical velocity, height and en/detrainment. Aerosol activation and droplet nucleation in convective updrafts at <span class="hlt">cloud</span> base is the primary driver for microphysical aerosol effects. To produce realistic estimates for vertical velocity at <span class="hlt">cloud</span> base we use an entraining dry parcel sub <span class="hlt">cloud</span> model which is triggered by perturbations of sensible and latent heat at the surface. Aerosol activation at <span class="hlt">cloud</span> base is modelled with a mechanistic, Köhler theory based, scheme, which couples the aerosols to the convective microphysics. Comparison of relationships between CTH and AOD, and precipitation and AOD produced by this novel model and satellite based estimates show general agreement. Through model experiments and analysis of the model <span class="hlt">cloud</span> processes we are able to investigate the main drivers for the relationship between CTH / precipitation and AOD.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/22663902-condensationcoalescence-cloud-model-exoplanetary-atmospheres-formulation-test-applications-terrestrial-jovian-clouds','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/22663902-condensationcoalescence-cloud-model-exoplanetary-atmospheres-formulation-test-applications-terrestrial-jovian-clouds"><span>A Condensation–coalescence <span class="hlt">Cloud</span> Model for Exoplanetary Atmospheres: Formulation and Test Applications to Terrestrial and Jovian <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>Ohno, Kazumasa; Okuzumi, Satoshi</p> <p></p> <p>A number of transiting exoplanets have featureless transmission spectra that might suggest the presence of <span class="hlt">clouds</span> at high altitudes. A realistic <span class="hlt">cloud</span> model is necessary to understand the atmospheric conditions under which such high-altitude <span class="hlt">clouds</span> can form. In this study, we present a new <span class="hlt">cloud</span> model that takes into account the microphysics of both condensation and coalescence. Our model provides the vertical profiles of the size and density of <span class="hlt">cloud</span> and rain particles in an updraft for a given set of physical parameters, including the updraft velocity and the number density of <span class="hlt">cloud</span> condensation nuclei (CCNs). We test our modelmore » by comparing with observations of trade-wind cumuli on Earth and ammonia ice <span class="hlt">clouds</span> in Jupiter. For trade-wind cumuli, the model including both condensation and coalescence gives predictions that are consistent with observations, while the model including only condensation overestimates the mass density of <span class="hlt">cloud</span> droplets by up to an order of magnitude. For Jovian ammonia <span class="hlt">clouds</span>, the condensation–coalescence model simultaneously reproduces the effective particle radius, <span class="hlt">cloud</span> optical thickness, and <span class="hlt">cloud</span> geometric thickness inferred from Voyager observations if the updraft velocity and CCN number density are taken to be consistent with the results of moist convection simulations and Galileo probe measurements, respectively. These results suggest that the coalescence of condensate particles is important not only in terrestrial water <span class="hlt">clouds</span> but also in Jovian ice <span class="hlt">clouds</span>. Our model will be useful to understand how the dynamics, compositions, and nucleation processes in exoplanetary atmospheres affect the vertical extent and optical thickness of exoplanetary <span class="hlt">clouds</span> via <span class="hlt">cloud</span> microphysics.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ApJ...835..261O','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ApJ...835..261O"><span>A Condensation-coalescence <span class="hlt">Cloud</span> Model for Exoplanetary Atmospheres: Formulation and Test Applications to Terrestrial and Jovian <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>Ohno, Kazumasa; Okuzumi, Satoshi</p> <p>2017-02-01</p> <p>A number of transiting exoplanets have featureless transmission spectra that might suggest the presence of <span class="hlt">clouds</span> at high altitudes. A realistic <span class="hlt">cloud</span> model is necessary to understand the atmospheric conditions under which such high-altitude <span class="hlt">clouds</span> can form. In this study, we present a new <span class="hlt">cloud</span> model that takes into account the microphysics of both condensation and coalescence. Our model provides the vertical profiles of the size and density of <span class="hlt">cloud</span> and rain particles in an updraft for a given set of physical parameters, including the updraft velocity and the number density of <span class="hlt">cloud</span> condensation nuclei (CCNs). We test our model by comparing with observations of trade-wind cumuli on Earth and ammonia ice <span class="hlt">clouds</span> in Jupiter. For trade-wind cumuli, the model including both condensation and coalescence gives predictions that are consistent with observations, while the model including only condensation overestimates the mass density of <span class="hlt">cloud</span> droplets by up to an order of magnitude. For Jovian ammonia <span class="hlt">clouds</span>, the condensation-coalescence model simultaneously reproduces the effective particle radius, <span class="hlt">cloud</span> optical thickness, and <span class="hlt">cloud</span> geometric thickness inferred from Voyager observations if the updraft velocity and CCN number density are taken to be consistent with the results of moist convection simulations and Galileo probe measurements, respectively. These results suggest that the coalescence of condensate particles is important not only in terrestrial water <span class="hlt">clouds</span> but also in Jovian ice <span class="hlt">clouds</span>. Our model will be useful to understand how the dynamics, compositions, and nucleation processes in exoplanetary atmospheres affect the vertical extent and optical thickness of exoplanetary <span class="hlt">clouds</span> via <span class="hlt">cloud</span> microphysics.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950048987&hterms=observational+research+methods&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dobservational%2Bresearch%2Bmethods','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950048987&hterms=observational+research+methods&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dobservational%2Bresearch%2Bmethods"><span>The Experimental <span class="hlt">Cloud</span> Lidar Pilot Study (ECLIPS) for <span class="hlt">cloud</span>-radiation research</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platt, C. M.; Young, S. A.; Carswell, A. I.; Pal, S. R.; Mccormick, M. P.; Winker, D. M.; Delguasta, M.; Stefanutti, L.; Eberhard, W. L.; Hardesty, M.</p> <p>1994-01-01</p> <p>The Experimental <span class="hlt">Cloud</span> Lidar Pilot Study (ECLIPS) was initiated to obtain statistics on <span class="hlt">cloud</span>-base height, extinction, optical depth, <span class="hlt">cloud</span> brokenness, and surface fluxes. Two observational phases have taken place, in October-December 1989 and April-July 1991, with intensive 30-day periods being selected within the two time intervals. Data are being archived at NASA Langley Research Center and, once there, are readily available to the international scientific community. This article describes the scale of the study in terms of its international involvement and in the range of data being recorded. Lidar observations of <span class="hlt">cloud</span> height and backscatter coefficient have been taken from a number of ground-based stations spread around the globe. Solar shortwave and infrared longwave fluxes and infrared beam radiance have been measured at the surface wherever possible. The observations have been tailored to occur around the overpass times of the NOAA weather satellites. This article describes in some detail the various retrieval methods used to obtain results on <span class="hlt">cloud</span>-base height, extinction coefficient, and infrared emittance, paying particular attention to the uncertainties involved.</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://ntrs.nasa.gov/search.jsp?R=20070031943&hterms=physics+pdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dphysics%2Bpdf','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20070031943&hterms=physics+pdf&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dphysics%2Bpdf"><span><span class="hlt">Clouds</span> in GEOS-5</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Bacmeister, Julio; Rienecker, Michele; Suarez, Max; Norris, Peter</p> <p>2007-01-01</p> <p>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 <span class="hlt">cloud</span> fraction. Two separate <span class="hlt">cloud</span> types are distinguished by their source: "anvil" <span class="hlt">cloud</span> originates in detraining convection, and large-scale <span class="hlt">cloud</span> originates in a PDF-based condensation calculation. Ice and liquid phases for each <span class="hlt">cloud</span> type are considered. Once created, condensate and fraction from the anvil and statistical <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span>-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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2008ACP.....8.1661F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2008ACP.....8.1661F"><span>Robust relations between CCN and the vertical evolution of <span class="hlt">cloud</span> drop size distribution in 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>Freud, E.; Rosenfeld, D.; Andreae, M. O.; Costa, A. A.; Artaxo, P.</p> <p>2008-03-01</p> <p>In-situ measurements in convective <span class="hlt">clouds</span> (up to the freezing level) over the Amazon basin show that smoke from deforestation fires prevents <span class="hlt">clouds</span> from precipitating until they acquire a vertical development of at least 4 km, compared to only 1-2 km in clean <span class="hlt">clouds</span>. The average <span class="hlt">cloud</span> depth required for the onset of warm rain increased by ~350 m for each additional 100 <span class="hlt">cloud</span> condensation nuclei per cm3 at a super-saturation of 0.5% (CCN0.5%). In polluted <span class="hlt">clouds</span>, the diameter of modal liquid water content grows much slower with <span class="hlt">cloud</span> depth (at least by a factor of ~2), due to the large number of droplets that compete for available water and to the suppressed coalescence processes. Contrary to what other studies have suggested, we did not observe this effect to reach saturation at 3000 or more accumulation mode particles per cm3. The CCN0.5% concentration was found to be a very good predictor for the <span class="hlt">cloud</span> depth required for the onset of warm precipitation and other microphysical factors, leaving only a secondary role for the updraft velocities in determining the <span class="hlt">cloud</span> drop size distributions. The effective radius of the <span class="hlt">cloud</span> droplets (re) was found to be a quite robust parameter for a given environment and <span class="hlt">cloud</span> depth, showing only a small effect of partial droplet evaporation from the <span class="hlt">cloud</span>'s mixing with its drier environment. This supports one of the basic assumptions of satellite analysis of <span class="hlt">cloud</span> microphysical processes: the ability to look at different <span class="hlt">cloud</span> top heights in the same region and regard their re as if they had been measured inside one well developed <span class="hlt">cloud</span>. The dependence of re on the adiabatic fraction decreased higher in the <span class="hlt">clouds</span>, especially for cleaner conditions, and disappeared at re≥~10 μm. We propose that droplet coalescence, which is at its peak when warm rain is formed in the <span class="hlt">cloud</span> at re=~10 μm, continues to be significant during the <span class="hlt">cloud</span>'s mixing with the entrained air, cancelling out the decrease in re due to evaporation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005ACPD....510155F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005ACPD....510155F"><span>Robust relations between CCN and the vertical evolution of <span class="hlt">cloud</span> drop size distribution in 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>Freud, E.; Rosenfeld, D.; Andreae, M. O.; Costa, A. A.; Artaxo, P.</p> <p>2005-10-01</p> <p>In-situ measurements in convective <span class="hlt">clouds</span> (up to the freezing level) over the Amazon basin show that smoke from deforestation fires prevents <span class="hlt">clouds</span> from precipitating until they acquire a vertical development of at least 4 km, compared to only 1-2 km in clean <span class="hlt">clouds</span>. The average <span class="hlt">cloud</span> depth required for the onset of warm rain increased by ~350 m for each additional 100 <span class="hlt">cloud</span> condensation nuclei per cm3 at a super-saturation of 0.5% (CCN0.5%). In polluted <span class="hlt">clouds</span>, the diameter of modal liquid water content grows much slower with <span class="hlt">cloud</span> depth (at least by a factor of ~2), due to the large number of droplets that compete for available water and to the suppressed coalescence processes. Contrary to what other studies have suggested, we did not observe this effect to reach saturation at 3000 or more accumulation mode particles per cm3. The CCN0.5% concentration was found to be a very good predictor for the <span class="hlt">cloud</span> depth required for the onset of warm precipitation and other microphysical factors, leaving only a secondary role for the updraft velocities in determining the <span class="hlt">cloud</span> drop size distributions. The effective radius of the <span class="hlt">cloud</span> droplets (re) was found to be a quite robust parameter for a given environment and <span class="hlt">cloud</span> depth, showing only a small effect of partial droplet evaporation from the <span class="hlt">cloud</span>'s mixing with its drier environment. This supports one of the basic assumptions of satellite analysis of <span class="hlt">cloud</span> microphysical processes: the ability to look at different <span class="hlt">cloud</span> top heights in the same region and regard their re as if they had been measured inside one well developed <span class="hlt">cloud</span>. The dependence of re on the adiabatic fraction decreased higher in the <span class="hlt">clouds</span>, especially for cleaner conditions, and disappeared at re≥~10 µm. We propose that droplet coalescence, which is at its peak when warm rain is formed in the <span class="hlt">cloud</span> at re~10 µm, continues to be significant during the <span class="hlt">cloud</span>'s mixing with the entrained air, canceling out the decrease in re due to evaporation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/AD1033489','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1033489"><span>Charting a Security Landscape in the <span class="hlt">Clouds</span>: Data Protection and Collaboration in <span class="hlt">Cloud</span> Storage</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2016-07-01</p> <p><span class="hlt">cloud</span> computing is perhaps the most revolutionary force in the information technology industry today. This field encompasses many different domains...characteristic shared by all <span class="hlt">cloud</span> computing tasks is that they involve storing data in the <span class="hlt">cloud</span> . In this report, we therefore aim to describe and rank the...CONCLUSION The advent of <span class="hlt">cloud</span> computing has caused government organizations to rethink their IT architectures so that they can take advantage of the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA12810.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA12810.html"><span>Equatorial Titan <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>2011-03-17</p> <p>NASA Cassini spacecraft chronicles the change of seasons as it captures <span class="hlt">clouds</span> concentrated near the equator of Saturn largest moon, Titan. Methane <span class="hlt">clouds</span> in the troposphere, the lowest part of the atmosphere, appear white here.</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 identify <span class="hlt">cloud</span> shadows in different regions with correct</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://www.dtic.mil/docs/citations/ADA615951','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA615951"><span><span class="hlt">Cloud</span>-Induced Uncertainty for Visual Navigation</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2014-12-26</p> <p>images at the pixel level. The result is a method that can overlay <span class="hlt">clouds</span> with various structures on top of any desired image to produce realistic...<span class="hlt">cloud</span>-shaped structures . The primary contribution of this research, however, is to investigate and quantify the errors in features due to <span class="hlt">clouds</span>. The...of <span class="hlt">clouds</span> types, this method does not emulate the true structure of <span class="hlt">clouds</span>. An alternative popular modern method of creating synthetic <span class="hlt">clouds</span> is known</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/28605406','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/28605406"><span><span class="hlt">Cloud</span>Neo: a <span class="hlt">cloud</span> pipeline for identifying patient-specific tumor neoantigens.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bais, Preeti; Namburi, Sandeep; Gatti, Daniel M; Zhang, Xinyu; Chuang, Jeffrey H</p> <p>2017-10-01</p> <p>We present <span class="hlt">Cloud</span>Neo, a <span class="hlt">cloud</span>-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 <span class="hlt">cloud</span>-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 <span class="hlt">cloud</span> instances through the Seven Bridges Genomics implementation of the NCI Cancer Genomics <span class="hlt">Cloud</span>, 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/<span class="hlt">Cloud</span>Neo. For users who have obtained licenses for all internal software, integrated versions in CWL and on the Seven Bridges Cancer Genomics <span class="hlt">Cloud</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=cloud+AND+database&id=EJ946036','ERIC'); return false;" href="https://eric.ed.gov/?q=cloud+AND+database&id=EJ946036"><span>Edu<span class="hlt">Cloud</span>: PaaS versus IaaS <span class="hlt">Cloud</span> Usage for an Advanced Computer Science Course</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>Vaquero, L. M.</p> <p>2011-01-01</p> <p>The <span class="hlt">cloud</span> has become a widely used term in academia and the industry. Education has not remained unaware of this trend, and several educational solutions based on <span class="hlt">cloud</span> technologies are already in place, especially for software as a service <span class="hlt">cloud</span>. However, an evaluation of the educational potential of infrastructure and platform <span class="hlt">clouds</span> has not…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..1919488R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..1919488R"><span>Opportunities for understanding of aerosol <span class="hlt">cloud</span> interactions in the context of Marine <span class="hlt">Cloud</span> Brightening Experiments</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Rasch, Philip J.; Wood, Robert; Ackerman, Thomas P.</p> <p>2017-04-01</p> <p>Anthropogenic aerosol impacts on <span class="hlt">clouds</span> constitute the largest source of uncertainty in radiative forcing of climate, confounding estimates of climate sensitivity to increases in greenhouse gases. Projections of future warming are also thus strongly dependent on estimates of aerosol effects on <span class="hlt">clouds</span>. I will discuss the opportunities for improving estimates of aerosol effects on <span class="hlt">clouds</span> from controlled field experiments where aerosol with well understood size, composition, amount, and injection altitude could be introduced to deliberately change <span class="hlt">cloud</span> properties. This would allow scientific investigation to be performed in a manner much closer to a lab environment, and facilitate the use of models to predict <span class="hlt">cloud</span> responses ahead of time, testing our understanding of aerosol <span class="hlt">cloud</span> interactions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=GL-2002-001441&hterms=images+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dimages%2BMODIS','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=GL-2002-001441&hterms=images+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dimages%2BMODIS"><span>MODIS Views Variations in <span class="hlt">Cloud</span> Types</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2002-01-01</p> <p>This MODIS image, centered over the Great Lakes region in North America, shows a variety of <span class="hlt">cloud</span> types. The <span class="hlt">clouds</span> at the top of the image, colored pink, are cold, high-level snow and ice <span class="hlt">clouds</span>, while the neon green <span class="hlt">clouds</span> are lower-level water <span class="hlt">clouds</span>. Because different <span class="hlt">cloud</span> types reflect and emit radiant energy differently, scientists can use MODIS' unique data set to measure the sizes of <span class="hlt">cloud</span> particles and distinguish between water, snow, and ice <span class="hlt">clouds</span>. 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</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A11I1996B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A11I1996B"><span>The sensitivities of in <span class="hlt">cloud</span> and <span class="hlt">cloud</span> top phase distributions to primary ice formation in ICON-LEM</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Beydoun, H.; Karrer, M.; Tonttila, J.; Hoose, C.</p> <p>2017-12-01</p> <p>Mixed phase <span class="hlt">clouds</span> remain a leading source of uncertainty in our attempt to quantify <span class="hlt">cloud</span>-climate and aerosol-<span class="hlt">cloud</span> climate interactions. Nevertheless, recent advances in parametrizing the primary ice formation process, high resolution <span class="hlt">cloud</span> modelling, and retrievals of <span class="hlt">cloud</span> phase distributions from satellite data offer an excellent opportunity to conduct closure studies on the sensitivity of the <span class="hlt">cloud</span> phase to microphysical and dynamical processes. Particularly, the reliability of satellite data to resolve the phase at the top of the <span class="hlt">cloud</span> provides a promising benchmark to compare model output to. We run large eddy simulations with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) to place bounds on the sensitivity of in <span class="hlt">cloud</span> and <span class="hlt">cloud</span> top phase to the primary ice formation process. State of the art primary ice formation parametrizations in the form of the cumulative ice active site density ns are implemented in idealized deep convective <span class="hlt">cloud</span> simulations. We exploit the ability of ICON-LEM to switch between a two moment microphysics scheme and the newly developed Predicted Particle Properties (P3) scheme by running our simulations in both configurations for comparison. To quantify the sensitivity of <span class="hlt">cloud</span> phase to primary ice formation, <span class="hlt">cloud</span> ice content is evaluated against order of magnitude changes in ns at variable convective strengths. Furthermore, we assess differences between in <span class="hlt">cloud</span> and <span class="hlt">cloud</span> top phase distributions as well as the potential impact of updraft velocity on the suppression of the Wegener-Bergeron-Findeisen process. The study aims to evaluate our practical understanding of primary ice formation in the context of predicting the structure and evolution of mixed phase <span class="hlt">clouds</span>.</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> identified 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('https://eric.ed.gov/?q=cloud+AND+computing&pg=4&id=EJ901489','ERIC'); return false;" href="https://eric.ed.gov/?q=cloud+AND+computing&pg=4&id=EJ901489"><span>If It's in the <span class="hlt">Cloud</span>, Get It on Paper: <span class="hlt">Cloud</span> Computing Contract Issues</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>Trappler, Thomas J.</p> <p>2010-01-01</p> <p>Much recent discussion has focused on the pros and cons of <span class="hlt">cloud</span> computing. Some institutions are attracted to <span class="hlt">cloud</span> computing benefits such as rapid deployment, flexible scalability, and low initial start-up cost, while others are concerned about <span class="hlt">cloud</span> computing risks such as those related to data location, level of service, and security…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AMT....10..221B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AMT....10..221B"><span>Observing relationships between lightning and <span class="hlt">cloud</span> profiles by means of a satellite-borne <span class="hlt">cloud</span> radar</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Buiat, Martina; Porcù, Federico; Dietrich, Stefano</p> <p>2017-01-01</p> <p><span class="hlt">Cloud</span> electrification and related lightning activity in thunderstorms have their origin in the charge separation and resulting distribution of charged iced particles within the <span class="hlt">cloud</span>. So far, the ice distribution within convective <span class="hlt">clouds</span> has been investigated mainly by means of ground-based meteorological radars. In this paper we show how the products from <span class="hlt">Cloud</span> Profiling Radar (CPR) on board <span class="hlt">Cloud</span>Sat, a polar satellite of NASA's Earth System Science Pathfinder (ESSP), can be used to obtain information from space on the vertical distribution of ice particles and ice content and relate them to the lightning activity. The analysis has been carried out, focusing on 12 convective events over Italy that crossed <span class="hlt">Cloud</span>Sat overpasses during significant lightning activity. The CPR products considered here are the vertical profiles of <span class="hlt">cloud</span> ice water content (IWC) and the effective radius (ER) of ice particles, which are compared with the number of strokes as measured by a ground lightning network (LINET). Results show a strong correlation between the number of strokes and the vertical distribution of ice particles as depicted by the 94 GHz CPR products: in particular, <span class="hlt">cloud</span> upper and middle levels, high IWC content and relatively high ER seem to be favourable contributory causes for CG (<span class="hlt">cloud</span> to ground) stroke occurrence.</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 type, 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('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 identified 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://adsabs.harvard.edu/abs/2016ACP....16.5091S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....16.5091S"><span><span class="hlt">Cloud</span> chamber experiments on the origin of ice crystal complexity in 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>Schnaiter, Martin; Järvinen, Emma; Vochezer, Paul; Abdelmonem, Ahmed; Wagner, Robert; Jourdan, Olivier; Mioche, Guillaume; Shcherbakov, Valery N.; Schmitt, Carl G.; Tricoli, Ugo; Ulanowski, Zbigniew; Heymsfield, Andrew J.</p> <p>2016-04-01</p> <p>This study reports on the origin of small-scale ice crystal complexity and its influence on the angular light scattering properties of cirrus <span class="hlt">clouds</span>. <span class="hlt">Cloud</span> simulation experiments were conducted at the AIDA (Aerosol Interactions and Dynamics in the Atmosphere) <span class="hlt">cloud</span> chamber of the Karlsruhe Institute of Technology (KIT). A new experimental procedure was applied to grow and sublimate ice particles at defined super- and subsaturated ice conditions and for temperatures in the -40 to -60 °C range. The experiments were performed for ice <span class="hlt">clouds</span> generated via homogeneous and heterogeneous initial nucleation. Small-scale ice crystal complexity was deduced from measurements of spatially resolved single particle light scattering patterns by the latest version of the Small Ice Detector (SID-3). It was found that a high crystal complexity dominates the microphysics of the simulated <span class="hlt">clouds</span> and the degree of this complexity is dependent on the available water vapor during the crystal growth. Indications were found that the small-scale crystal complexity is influenced by unfrozen H2SO4 / H2O residuals in the case of homogeneous initial ice nucleation. Angular light scattering functions of the simulated ice <span class="hlt">clouds</span> were measured by the two currently available airborne polar nephelometers: the polar nephelometer (PN) probe of Laboratoire de Métérologie et Physique (LaMP) and the Particle Habit Imaging and Polar Scattering (PHIPS-HALO) probe of KIT. The measured scattering functions are featureless and flat in the side and backward scattering directions. It was found that these functions have a rather low sensitivity to the small-scale crystal complexity for ice <span class="hlt">clouds</span> that were grown under typical atmospheric conditions. These results have implications for the microphysical properties of cirrus <span class="hlt">clouds</span> and for the radiative transfer through these <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002158.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-GSFC_20171208_Archive_e002158.html"><span><span class="hlt">Clouds</span> off the Aleutian Islands</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>March 23, 2010 - <span class="hlt">Clouds</span> off the Aleutian Islands Interesting <span class="hlt">cloud</span> patterns were visible over the Aleutian Islands in this image, captured by the MODIS on the Aqua satellite on March 14, 2010. Turbulence, caused by the wind passing over the highest points of the islands, is producing the pronounced eddies that swirl the <span class="hlt">clouds</span> into a pattern called a vortex "street". In this image, the <span class="hlt">clouds</span> have also aligned in parallel rows or streets. <span class="hlt">Cloud</span> streets form when low-level winds move between and over obstacles causing the <span class="hlt">clouds</span> to line up into rows (much like streets) that match the direction of the winds. At the point where the <span class="hlt">clouds</span> first form streets, they're very narrow and well-defined. But as they age, they lose their definition, and begin to spread out and rejoin each other into a larger <span class="hlt">cloud</span> mass. The Aleutians are a chain of islands that extend from Alaska toward the Kamchatka Peninsula in Russia. For more information related to this image go to: modis.gsfc.nasa.gov/gallery/individual.php?db_date=2010-0... For more information about Goddard Space Flight Center go here: www.nasa.gov/centers/goddard/home/index.html</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006613','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006613"><span>Evaluation of Multilayer <span class="hlt">Cloud</span> Detection Using a MODIS CO2-Slicing Algorithm With CALIPSO-<span class="hlt">Cloud</span>Sat Measurements</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Viudez-Mora, Antonio; Kato, Seiji</p> <p>2015-01-01</p> <p>This work evaluates the multilayer <span class="hlt">cloud</span> (MCF) algorithm based on CO2-slicing techniques against CALISPO-<span class="hlt">Cloud</span>Sat (CLCS) measurement. This evaluation showed that the MCF underestimates the presence of multilayered <span class="hlt">clouds</span> compared with CLCS and are retrained to <span class="hlt">cloud</span> emissivities below 0.8 and <span class="hlt">cloud</span> optical septs no larger than 0.3.</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/26886482','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26886482"><span>The Ethics of <span class="hlt">Cloud</span> Computing.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>de Bruin, Boudewijn; Floridi, Luciano</p> <p>2017-02-01</p> <p><span class="hlt">Cloud</span> computing is rapidly gaining traction in business. It offers businesses online services on demand (such as Gmail, i<span class="hlt">Cloud</span> and Salesforce) and allows them to cut costs on hardware and IT support. This is the first paper in business ethics dealing with this new technology. It analyzes the informational duties of hosting companies that own and operate <span class="hlt">cloud</span> computing datacentres (e.g., Amazon). It considers the <span class="hlt">cloud</span> services providers leasing 'space in the <span class="hlt">cloud</span>' from hosting companies (e.g., Dropbox, Salesforce). And it examines the business and private 'clouders' using these services. The first part of the paper argues that hosting companies, services providers and clouders have mutual informational (epistemic) obligations to provide and seek information about relevant issues such as consumer privacy, reliability of services, data mining and data ownership. The concept of interlucency is developed as an epistemic virtue governing ethically effective communication. The second part considers potential forms of government restrictions on or proscriptions against the development and use of <span class="hlt">cloud</span> computing technology. Referring to the concept of technology neutrality, it argues that interference with hosting companies and <span class="hlt">cloud</span> services providers is hardly ever necessary or justified. It is argued, too, however, that businesses using <span class="hlt">cloud</span> services (e.g., banks, law firms, hospitals etc. storing client data in the <span class="hlt">cloud</span>) will have to follow rather more stringent regulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1155096','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1155096"><span><span class="hlt">Cloud</span> Based Applications and Platforms (Presentation)</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>Brodt-Giles, D.</p> <p>2014-05-15</p> <p>Presentation to the <span class="hlt">Cloud</span> Computing East 2014 Conference, where we are highlighting our <span class="hlt">cloud</span> computing strategy, describing the platforms on the <span class="hlt">cloud</span> (including Smartgrid.gov), and defining our process for implementing <span class="hlt">cloud</span> based applications.</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 identify 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('https://www.ncbi.nlm.nih.gov/pubmed/22289098','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/22289098"><span><span class="hlt">Cloud</span> computing basics for librarians.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hoy, Matthew B</p> <p>2012-01-01</p> <p>"<span class="hlt">Cloud</span> computing" is the name for the recent trend of moving software and computing resources to an online, shared-service model. This article briefly defines <span class="hlt">cloud</span> computing, discusses different models, explores the advantages and disadvantages, and describes some of the ways <span class="hlt">cloud</span> computing can be used in libraries. Examples of <span class="hlt">cloud</span> services are included at the end of the article. Copyright © Taylor & Francis Group, LLC</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160006671','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160006671"><span>Long Term <span class="hlt">Cloud</span> Property Datasets From MODIS and AVHRR Using the CERES <span class="hlt">Cloud</span> Algorithm</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan; <a style="text-decoration: none; " href="javascript:void(0); " onClick="displayelement('author_20160006671'); toggleEditAbsImage('author_20160006671_show'); toggleEditAbsImage('author_20160006671_hide'); "> <img style="display:inline; width:12px; height:12px; " src="images/arrow-up.gif" width="12" height="12" border="0" alt="hide" id="author_20160006671_show"> <img style="width:12px; height:12px; display:none; " src="images/arrow-down.gif" width="12" height="12" border="0" alt="hide" id="author_20160006671_hide"></p> <p>2015-01-01</p> <p><span class="hlt">Cloud</span> properties play a critical role in climate change. Monitoring <span class="hlt">cloud</span> properties over long time periods is needed to detect changes and to validate and constrain models. The <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES) project has developed several <span class="hlt">cloud</span> datasets from Aqua and Terra MODIS data to better interpret broadband radiation measurements and improve understanding of the role of <span class="hlt">clouds</span> in the radiation budget. The algorithms applied to MODIS data have been adapted to utilize various combinations of channels on the Advanced Very High Resolution Radiometer (AVHRR) on the long-term time series of NOAA and MetOp satellites to provide a new <span class="hlt">cloud</span> climate data record. These datasets can be useful for a variety of studies. This paper presents results of the MODIS and AVHRR analyses covering the period from 1980-2014. Validation and comparisons with other datasets are also given.</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 identify 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/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 identified 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/2011AIPC.1414..149K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AIPC.1414..149K"><span><span class="hlt">Cloud</span> Computing Security Issue: Survey</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kamal, Shailza; Kaur, Rajpreet</p> <p>2011-12-01</p> <p><span class="hlt">Cloud</span> computing is the growing field in IT industry since 2007 proposed by IBM. Another company like Google, Amazon, and Microsoft provides further products to <span class="hlt">cloud</span> computing. The <span class="hlt">cloud</span> computing is the internet based computing that shared recourses, information on demand. It provides the services like SaaS, IaaS and PaaS. The services and recourses are shared by virtualization that run multiple operation applications on <span class="hlt">cloud</span> computing. This discussion gives the survey on the challenges on security issues during <span class="hlt">cloud</span> computing and describes some standards and protocols that presents how security can be managed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ACP....17.7245V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ACP....17.7245V"><span>Analyzing <span class="hlt">cloud</span> base at local and regional scales to understand tropical montane <span class="hlt">cloud</span> forest vulnerability to climate change</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Van Beusekom, Ashley E.; González, Grizelle; Scholl, Martha A.</p> <p>2017-06-01</p> <p>The degree to which <span class="hlt">cloud</span> immersion provides water in addition to rainfall, suppresses transpiration, and sustains tropical montane <span class="hlt">cloud</span> forests (TMCFs) during rainless periods is not well understood. Climate and land use changes represent a threat to these forests if <span class="hlt">cloud</span> base altitude rises as a result of regional warming or deforestation. To establish a baseline for quantifying future changes in <span class="hlt">cloud</span> base, we installed a ceilometer at 100 m altitude in the forest upwind of the TMCF that occupies an altitude range from ˜ 600 m to the peaks at 1100 m in the Luquillo Mountains of eastern Puerto Rico. Airport Automated Surface Observing System (ASOS) ceilometer data, radiosonde data, and <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite data were obtained to investigate seasonal <span class="hlt">cloud</span> base dynamics, altitude of the trade-wind inversion (TWI), and typical <span class="hlt">cloud</span> thickness for the surrounding Caribbean region. <span class="hlt">Cloud</span> base is rarely quantified near mountains, so these results represent a first look at seasonal and diurnal <span class="hlt">cloud</span> base dynamics for the TMCF. From May 2013 to August 2016, <span class="hlt">cloud</span> base was lowest during the midsummer dry season, and <span class="hlt">cloud</span> bases were lower than the mountaintops as often in the winter dry season as in the wet seasons. The lowest <span class="hlt">cloud</span> bases most frequently occurred at higher elevation than 600 m, from 740 to 964 m. The Luquillo forest low <span class="hlt">cloud</span> base altitudes were higher than six other sites in the Caribbean by ˜ 200-600 m, highlighting the importance of site selection to measure topographic influence on <span class="hlt">cloud</span> height. Proximity to the oceanic <span class="hlt">cloud</span> system where shallow cumulus <span class="hlt">clouds</span> are seasonally invariant in altitude and cover, along with local trade-wind orographic lifting and <span class="hlt">cloud</span> formation, may explain the dry season low <span class="hlt">clouds</span>. The results indicate that climate change threats to low-elevation TMCFs are not limited to the dry season; changes in synoptic-scale weather patterns that increase frequency</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23733936','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23733936"><span>Laser-induced plasma <span class="hlt">cloud</span> interaction and ice multiplication under cirrus <span class="hlt">cloud</span> conditions.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Leisner, Thomas; Duft, Denis; Möhler, Ottmar; Saathoff, Harald; Schnaiter, Martin; Henin, Stefano; Stelmaszczyk, Kamil; Petrarca, Massimo; Delagrange, Raphaëlle; Hao, Zuoqiang; Lüder, Johannes; Petit, Yannick; Rohwetter, Philipp; Kasparian, Jérôme; Wolf, Jean-Pierre; Wöste, Ludger</p> <p>2013-06-18</p> <p>Potential impacts of lightning-induced plasma on <span class="hlt">cloud</span> ice formation and precipitation have been a subject of debate for decades. Here, we report on the interaction of laser-generated plasma channels with water and ice <span class="hlt">clouds</span> observed in a large <span class="hlt">cloud</span> simulation chamber. Under the conditions of a typical storm <span class="hlt">cloud</span>, in which ice and supercooled water coexist, no direct influence of the plasma channels on ice formation or precipitation processes could be detected. Under conditions typical for thin cirrus ice <span class="hlt">clouds</span>, however, the plasma channels induced a surprisingly strong effect of ice multiplication. Within a few minutes, the laser action led to a strong enhancement of the total ice particle number density in the chamber by up to a factor of 100, even though only a 10(-9) fraction of the chamber volume was exposed to the plasma channels. The newly formed ice particles quickly reduced the water vapor pressure to ice saturation, thereby increasing the <span class="hlt">cloud</span> optical thickness by up to three orders of magnitude. A model relying on the complete vaporization of ice particles in the laser filament and the condensation of the resulting water vapor on plasma ions reproduces our experimental findings. This surprising effect might open new perspectives for remote sensing of water vapor and ice in the upper troposphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160002953','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160002953"><span><span class="hlt">Cloud</span> Regimes as a Tool for Systematic Study of Various Aerosol-<span class="hlt">Cloud</span>-Precipitation Interactions</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</p> <p>2016-01-01</p> <p>Systematic changes of <span class="hlt">clouds</span> and precipitation are notoriously difficult to ascribe to aerosols. This presentation will showcase yet one more attempt to at least credibly detect the signal of aerosol-<span class="hlt">cloud</span>-precipitation interactions. We surmise that the concept of <span class="hlt">cloud</span> regimes (CRs) is appropriate to conduct such an investigation. Previous studies focused on what we call here dynamical CRs, and while we continue to adopt those too for our analysis, we have found that a different way of organizing <span class="hlt">cloud</span> systems, namely via microphysical regimes is also promising. Our analysis relies on MODIS Collection 6 Level-3 data for <span class="hlt">clouds</span> and aerosols, and TRMM-TMPA data for precipitation. The regimes are derived by applying clustering analysis on MODIS joint histograms, and once each grid cell is assigned a regime, aerosol and precipitation data can be spatiotemporally matched and composited by regime. The composites of various <span class="hlt">cloud</span> and precipitation variables for high (upper quartile of distribution) and low (lower quartile) aerosol loadings can then be contrasted. We seek evidence of aerosol effects both in regimes with large fractions of deep ice-rich <span class="hlt">clouds</span>, as well as regimes where low liquid phase <span class="hlt">clouds</span> dominate. Signals can be seen, especially when the analysis is broken by land-ocean and when additional filters are applied, but there are of course caveats which will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080022439','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080022439"><span>Statistical Analyses of Satellite <span class="hlt">Cloud</span> Object Data From CERES. Part 4; Boundary-layer <span class="hlt">Cloud</span> Objects During 1998 El Nino</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; Wong, Takmeng; Wielicki, Bruce A.; Parker, Lindsay</p> <p>2006-01-01</p> <p>Three boundary-layer <span class="hlt">cloud</span> object types, stratus, stratocumulus and cumulus, that occurred over the Pacific Ocean during January-August 1998, are identified from the CERES (<span class="hlt">Clouds</span> 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 <span class="hlt">cloud</span>-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 <span class="hlt">cloud</span> physical properties are analyzed. In terms of frequencies of occurrence, stratocumulus <span class="hlt">clouds</span> dominate the entire boundary layer <span class="hlt">cloud</span> population in all regions and among all size categories. Stratus <span class="hlt">clouds</span> are more prevalent in the subtropics and near the coastal regions, while cumulus <span class="hlt">clouds</span> are relatively prevalent over open ocean and the equatorial regions, particularly, within the small size categories. The largest size category of stratus <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> object types exhibits small differences in statistical distributions of <span class="hlt">cloud</span> optical depth, liquid water path, TOA albedo and perhaps <span class="hlt">cloud</span>-top height, but large differences in those of <span class="hlt">cloud</span>-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 <span class="hlt">cloud</span> macrophysical properties, but <span class="hlt">cloud</span> microphysical properties and albedo for each <span class="hlt">cloud</span> object type are likely determined by (local) boundary-layer dynamics and structures. Systematic variations of <span class="hlt">cloud</span> optical depth, TOA albedo, <span class="hlt">cloud</span>-top height, OLR and SST with <span class="hlt">cloud</span> object sizes are pronounced for the stratocumulus and stratus types, which are related to systematic</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ACP....10.8173M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ACP....10.8173M"><span>Intercomparison of aerosol-<span class="hlt">cloud</span>-precipitation interactions in stratiform orographic mixed-phase <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>Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.</p> <p>2010-09-01</p> <p>Anthropogenic aerosols serve as a source of both <span class="hlt">cloud</span> condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of <span class="hlt">clouds</span>. Increasing aerosol number concentrations is hypothesized to retard the <span class="hlt">cloud</span> droplet coalescence and the riming in mixed-phase <span class="hlt">clouds</span>, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-<span class="hlt">cloud</span>-precipitation interactions in stratiform orographic mixed-phase <span class="hlt">clouds</span>. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analysed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as coalescence, aggregation, riming and diffusional growth to changes in the aerosol number concentrations are evaluated and compared. The participating numerical models are the model from the Consortium for Small-Scale Modeling (COSMO) with bulk microphysics, the Weather Research and Forecasting (WRF) model with bin microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice habit prediction microphysics scheme. All models are operated on a <span class="hlt">cloud</span>-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others, which implies that a decrease in riming with increasing aerosol load is not a robust result</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26357328','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26357328"><span>RBio<span class="hlt">Cloud</span>: A Light-Weight Framework for Bioconductor and R-based Jobs 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>Varghese, Blesson; Patel, Ishan; Barker, Adam</p> <p>2015-01-01</p> <p>Large-scale ad hoc analytics of genomic data is popular using the R-programming language supported by over 700 software packages provided by Bioconductor. More recently, analytical jobs are benefitting from on-demand computing and storage, their scalability and their low maintenance cost, all of which are offered by the <span class="hlt">cloud</span>. While biologists and bioinformaticists can take an analytical job and execute it on their personal workstations, it remains challenging to seamlessly execute the job on the <span class="hlt">cloud</span> infrastructure without extensive knowledge of the <span class="hlt">cloud</span> dashboard. How analytical jobs can not only with minimum effort be executed on the <span class="hlt">cloud</span>, but also how both the resources and data required by the job can be managed is explored in this paper. An open-source light-weight framework for executing R-scripts using Bioconductor packages, referred to as `RBio<span class="hlt">Cloud</span>', is designed and developed. RBio<span class="hlt">Cloud</span> offers a set of simple command-line tools for managing the <span class="hlt">cloud</span> resources, the data and the execution of the job. Three biological test cases validate the feasibility of RBio<span class="hlt">Cloud</span>. The framework is available from http://www.rbiocloud.com.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20120013648','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120013648"><span>Effect of CALIPSO <span class="hlt">Cloud</span> Aerosol Discrimination (CAD) Confidence Levels on Observations of Aerosol Properties near <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>Yang, Weidong; Marshak, Alexander; Varnai, Tamas; Liu, Zhaoyan</p> <p>2012-01-01</p> <p>CALIPSO aerosol backscatter enhancement in the transition zone between <span class="hlt">clouds</span> and clear sky areas is revisited with particular attention to effects of data selection based on the confidence level of <span class="hlt">cloud</span>-aerosol discrimination (CAD). The results show that backscatter behavior in the transition zone strongly depends on the CAD confidence level. Higher confidence level data has a flatter backscatter far away from <span class="hlt">clouds</span> and a much sharper increase near <span class="hlt">clouds</span> (within 4 km), thus a smaller transition zone. For high confidence level data it is shown that the overall backscatter enhancement is more pronounced for small clear-air segments and horizontally larger <span class="hlt">clouds</span>. The results suggest that data selection based on CAD reduces the possible effects of <span class="hlt">cloud</span> contamination when studying aerosol properties in the vicinity of <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20160010516','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20160010516"><span>Progress in Understanding the Impacts of 3-D <span class="hlt">Cloud</span> Structure on MODIS <span class="hlt">Cloud</span> Property Retrievals for Marine Boundary Layer <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>Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu</p> <p>2016-01-01</p> <p>Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How <span class="hlt">cloud</span> vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS <span class="hlt">cloud</span> property retrievals. (Cho et al. 2015). <span class="hlt">Cloud</span> property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ISPAr42W4..105C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ISPAr42W4..105C"><span>Point <span class="hlt">Cloud</span> Management Through the Realization of the Intelligent <span class="hlt">Cloud</span> Viewer Software</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Costantino, D.; Angelini, M. G.; Settembrini, F.</p> <p>2017-05-01</p> <p>The paper presents a software dedicated to the elaboration of point <span class="hlt">clouds</span>, called Intelligent <span class="hlt">Cloud</span> Viewer (ICV), made in-house by AESEI software (Spin-Off of Politecnico di Bari), allowing to view point <span class="hlt">cloud</span> of several tens of millions of points, also on of "no" very high performance systems. The elaborations are carried out on the whole point <span class="hlt">cloud</span> and managed by means of the display only part of it in order to speed up rendering. It is designed for 64-bit Windows and is fully written in C ++ and integrates different specialized modules for computer graphics (Open Inventor by SGI, Silicon Graphics Inc), maths (BLAS, EIGEN), computational geometry (CGAL, Computational Geometry Algorithms Library), registration and advanced algorithms for point <span class="hlt">clouds</span> (PCL, Point <span class="hlt">Cloud</span> Library), advanced data structures (BOOST, Basic Object Oriented Supporting Tools), etc. ICV incorporates a number of features such as, for example, cropping, transformation and georeferencing, matching, registration, decimation, sections, distances calculation between <span class="hlt">clouds</span>, etc. It has been tested on photographic and TLS (Terrestrial Laser Scanner) data, obtaining satisfactory results. The potentialities of the software have been tested by carrying out the photogrammetric survey of the Castel del Monte which was already available in previous laser scanner survey made from the ground by the same authors. For the aerophotogrammetric survey has been adopted a flight height of approximately 1000ft AGL (Above Ground Level) and, overall, have been acquired over 800 photos in just over 15 minutes, with a covering not less than 80%, the planned speed of about 90 knots.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20070034740','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20070034740"><span>Microphysical Timescales in <span class="hlt">Clouds</span> and their Application in <span class="hlt">Cloud</span>-Resolving Modeling</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Zeng, Xiping; Tao, Wei-Kuo; Simpson, Joanne</p> <p>2007-01-01</p> <p>Independent prognostic variables in <span class="hlt">cloud</span>-resolving modeling are chosen on the basis of the analysis of microphysical timescales in <span class="hlt">clouds</span> versus a time step for numerical integration. Two of them are the moist entropy and the total mixing ratio of airborne water with no contributions from precipitating particles. As a result, temperature can be diagnosed easily from those prognostic variables, and <span class="hlt">cloud</span> microphysics be separated (or modularized) from moist thermodynamics. Numerical comparison experiments show that those prognostic variables can work well while a large time step (e.g., 10 s) is used for numerical integration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870038108&hterms=1076&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3D%2526%25231076','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870038108&hterms=1076&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3D%2526%25231076"><span>Molecular <span class="hlt">clouds</span> in galaxies with different Z - Fragmentation of diffuse <span class="hlt">clouds</span> driven by opacity</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Franco, Jose; Cox, Donald P.</p> <p>1986-01-01</p> <p>Molecular <span class="hlt">clouds</span> are formed from diffuse interstellar <span class="hlt">clouds</span> when the external ultraviolet radiation field is prevented from penetrating into the <span class="hlt">cloud</span>. The opacity is provided mainly by dust grains and the required column density to the <span class="hlt">cloud</span> center is larger than about 5 x 10 to the 20th (solar Z/Z)/sq cm. This high-opacity criterion could have a significant impact on the radial trends observed in spiral galaxies, and on the distinctions between spiral and dwarf irregular galaxies.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040171375','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040171375"><span><span class="hlt">Cloud</span> Inhomogeneity from MODIS</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Oreopoulos, Lazaros; Cahalan, Robert F.</p> <p>2004-01-01</p> <p>Two full months (July 2003 and January 2004) of MODIS Atmosphere Level-3 data from the Terra and Aqua satellites are analyzed in order to characterize the horizontal variability of <span class="hlt">cloud</span> optical thickness and water path at global scales. Various options to derive <span class="hlt">cloud</span> variability parameters are discussed. The climatology of <span class="hlt">cloud</span> inhomogeneity is built by first calculating daily parameter values at spatial scales of l degree x 1 degree, and then at zonal and global scales, followed by averaging over monthly time scales. Geographical, diurnal, and seasonal changes of inhomogeneity parameters are examined separately for the two <span class="hlt">cloud</span> phases, and separately over land and ocean. We find that <span class="hlt">cloud</span> inhomogeneity is weaker in summer than in winter, weaker over land than ocean for liquid <span class="hlt">clouds</span>, weaker for local morning than local afternoon, about the same for liquid and ice <span class="hlt">clouds</span> on a global scale, but with wider probability distribution functions (PDFs) and larger latitudinal variations for ice, and relatively insensitive to whether water path or optical thickness products are used. Typical mean values at hemispheric and global scales of the inhomogeneity parameter nu (roughly the mean over the standard deviation of water path or optical thickness), range from approximately 2.5 to 3, while for the inhomogeneity parameter chi (the ratio of the logarithmic to linear mean) from approximately 0.7 to 0.8. Values of chi for zonal averages can occasionally fall below 0.6 and for individual gridpoints below 0.5. Our results demonstrate that MODIS is capable of revealing significant fluctuations in <span class="hlt">cloud</span> horizontal inhomogenity and stress the need to model their global radiative effect in future studies.</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('https://ntrs.nasa.gov/search.jsp?R=19860035883&hterms=Cox&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DCox%25E2%2580%2599s','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860035883&hterms=Cox&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DCox%25E2%2580%2599s"><span>Cirrus <span class="hlt">clouds</span>. I - A cirrus <span class="hlt">cloud</span> model. II - Numerical experiments on the formation and maintenance of cirrus</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Starr, D. OC.; Cox, S. K.</p> <p>1985-01-01</p> <p>A simplified cirrus <span class="hlt">cloud</span> model is presented which may be used to investigate the role of various physical processes in the life cycle of a cirrus <span class="hlt">cloud</span>. The model is a two-dimensional, time-dependent, Eulerian numerical model where the focus is on <span class="hlt">cloud</span>-scale processes. Parametrizations are developed to account for phase changes of water, radiative processes, and the effects of microphysical structure on the vertical flux of ice water. The results of a simulation of a thin cirrostratus <span class="hlt">cloud</span> are given. The results of numerical experiments performed with the model are described in order to demonstrate the important role of <span class="hlt">cloud</span>-scale processes in determining the <span class="hlt">cloud</span> properties maintained in response to larger scale forcing. The effects of microphysical composition and radiative processes are considered, as well as their interaction with thermodynamic and dynamic processes within the <span class="hlt">cloud</span>. It is shown that cirrus <span class="hlt">clouds</span> operate in an entirely different manner than liquid phase stratiform <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040172171&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsimulation%2Bprocesses','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040172171&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%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; Li, X.; Khain, A.; Simpson, S.</p> <p>2004-01-01</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 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 <span class="hlt">cloud</span> 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.</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-type 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/2018JAMES..10..320Q','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JAMES..10..320Q"><span>A Diagnostic PDF <span class="hlt">Cloud</span> Scheme to Improve Subtropical Low <span class="hlt">Clouds</span> in NCAR Community Atmosphere Model (CAM5)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Qin, Yi; Lin, Yanluan; Xu, Shiming; Ma, Hsi-Yen; Xie, Shaocheng</p> <p>2018-02-01</p> <p>Low <span class="hlt">clouds</span> strongly impact the radiation budget of the climate system, but their simulation in most GCMs has remained a challenge, especially over the subtropical stratocumulus region. Assuming a Gaussian distribution for the subgrid-scale total water and liquid water potential temperature, a new statistical <span class="hlt">cloud</span> scheme is proposed and tested in NCAR Community Atmospheric Model version 5 (CAM5). The subgrid-scale variance is diagnosed from the turbulent and shallow convective processes in CAM5. The approach is able to maintain the consistency between <span class="hlt">cloud</span> fraction and <span class="hlt">cloud</span> condensate and thus alleviates the adjustment needed in the default relative humidity-based <span class="hlt">cloud</span> fraction scheme. Short-term forecast simulations indicate that low <span class="hlt">cloud</span> fraction and liquid water content, including their diurnal cycle, are improved due to a proper consideration of subgrid-scale variance over the southeastern Pacific Ocean region. Compared with the default <span class="hlt">cloud</span> scheme, the new approach produced the mean climate reasonably well with improved shortwave <span class="hlt">cloud</span> forcing (SWCF) due to more reasonable low <span class="hlt">cloud</span> fraction and liquid water path over regions with predominant low <span class="hlt">clouds</span>. Meanwhile, the SWCF bias over the tropical land regions is also alleviated. Furthermore, the simulated marine boundary layer <span class="hlt">clouds</span> with the new approach extend further offshore and agree better with observations. The new approach is able to obtain the top of atmosphere (TOA) radiation balance with a slightly alleviated double ITCZ problem in preliminary coupled simulations. This study implies that a close coupling of <span class="hlt">cloud</span> processes with other subgrid-scale physical processes is a promising approach to improve <span class="hlt">cloud</span> simulations.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19880060438&hterms=Storage+cloud&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DStorage%2Bcloud','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19880060438&hterms=Storage+cloud&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3DStorage%2Bcloud"><span>Satellite remote sensing and <span class="hlt">cloud</span> modeling of St. Anthony, Minnesota storm <span class="hlt">clouds</span> and dew point depression</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hung, R. J.; Tsao, Y. D.</p> <p>1988-01-01</p> <p>Rawinsonde data and geosynchronous satellite imagery were used to investigate the life cycles of St. Anthony, Minnesota's severe convective storms. It is found that the fully developed storm <span class="hlt">clouds</span>, with overshooting <span class="hlt">cloud</span> tops penetrating above the tropopause, collapsed about three minutes before the touchdown of the tornadoes. Results indicate that the probability of producing an outbreak of tornadoes causing greater damage increases when there are higher values of potential energy storage per unit area for overshooting <span class="hlt">cloud</span> tops penetrating the tropopause. It is also found that there is less chance for <span class="hlt">clouds</span> with a lower moisture content to be outgrown as a storm <span class="hlt">cloud</span> than <span class="hlt">clouds</span> with a higher moisture content.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080006610','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080006610"><span>Ice <span class="hlt">Cloud</span> Properties in Ice-Over-Water <span class="hlt">Cloud</span> Systems Using TRMM VIRS and TMI Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Minnis, Patrick; Huang, Jianping; Lin, Bing; Yi, Yuhong; Arduini, Robert F.; Fan, Tai-Fang; Ayers, J. Kirk; Mace, Gerald G.</p> <p>2007-01-01</p> <p>A multi-layered <span class="hlt">cloud</span> retrieval system (MCRS) is updated and used to estimate ice water path in maritime ice-over-water <span class="hlt">clouds</span> using Visible and Infrared Scanner (VIRS) and TRMM Microwave Imager (TMI) measurements from the Tropical Rainfall Measuring Mission spacecraft between January and August 1998. Lookup tables of top-of-atmosphere 0.65- m reflectance are developed for ice-over-water <span class="hlt">cloud</span> systems using radiative transfer calculations with various combinations of ice-over-water <span class="hlt">cloud</span> layers. The liquid and ice water paths, LWP and IWP, respectively, are determined with the MCRS using these lookup tables with a combination of microwave (MW), visible (VIS), and infrared (IR) data. LWP, determined directly from the TMI MW data, is used to define the lower-level <span class="hlt">cloud</span> properties to select the proper lookup table. The properties of the upper-level ice <span class="hlt">clouds</span>, such as optical depth and effective size, are then derived using the Visible Infrared Solar-infrared Split-window Technique (VISST), which matches the VIRS IR, 3.9- m, and VIS data to the multilayer-<span class="hlt">cloud</span> lookup table reflectances and a set of emittance parameterizations. Initial comparisons with surface-based radar retrievals suggest that this enhanced MCRS can significantly improve the accuracy and decrease the IWP in overlapped <span class="hlt">clouds</span> by 42% and 13% compared to using the single-layer VISST and an earlier simplified MW-VIS-IR (MVI) differencing method, respectively, for ice-over-water <span class="hlt">cloud</span> systems. The tropical distribution of ice-over-water <span class="hlt">clouds</span> is the same as derived earlier from combined TMI and VIRS data, but the new values of IWP and optical depth are slightly larger than the older MVI values, and exceed those of single-layered layered <span class="hlt">clouds</span> by 7% and 11%, respectively. The mean IWP from the MCRS is 8-14% greater than that retrieved from radar retrievals of overlapped <span class="hlt">clouds</span> over two surface sites and the standard deviations of the differences are similar to those for single-layered <span class="hlt">clouds</span>. Examples</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931..626Q','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931..626Q"><span><span class="hlt">Cloud</span> Computing: An Overview</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Qian, Ling; Luo, Zhiguo; Du, Yujian; Guo, Leitao</p> <p></p> <p>In order to support the maximum number of user and elastic service with the minimum resource, the Internet service provider invented the <span class="hlt">cloud</span> computing. within a few years, emerging <span class="hlt">cloud</span> computing has became the hottest technology. From the publication of core papers by Google since 2003 to the commercialization of Amazon EC2 in 2006, and to the service offering of AT&T Synaptic Hosting, the <span class="hlt">cloud</span> computing has been evolved from internal IT system to public service, from cost-saving tools to revenue generator, and from ISP to telecom. This paper introduces the concept, history, pros and cons of <span class="hlt">cloud</span> computing as well as the value chain and standardization effort.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/26739003','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/26739003"><span>Life in the <span class="hlt">clouds</span>: are tropical montane <span class="hlt">cloud</span> forests responding to changes in climate?</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Hu, Jia; Riveros-Iregui, Diego A</p> <p>2016-04-01</p> <p>The humid tropics represent only one example of the many places worldwide where anthropogenic disturbance and climate change are quickly affecting the feedbacks between water and trees. In this article, we address the need for a more long-term perspective on the effects of climate change on tropical montane <span class="hlt">cloud</span> forests (TMCF) in order to fully assess the combined vulnerability and long-term response of tropical trees to changes in precipitation regimes, including <span class="hlt">cloud</span> immersion. We first review the ecophysiological benefits that <span class="hlt">cloud</span> water interception offers to trees in TMCF and then examine current climatological evidence that suggests changes in <span class="hlt">cloud</span> base height and impending changes in <span class="hlt">cloud</span> immersion for TMCF. Finally, we propose an experimental approach to examine the long-term dynamics of tropical trees in TMCF in response to environmental conditions on decade-to-century time scales. This information is important to assess the vulnerability and long-term response of TMCF to changes in <span class="hlt">cloud</span> cover and fog frequency and duration.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A33N..06S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A33N..06S"><span>On the existence of tropical anvil <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>Seeley, J.; Jeevanjee, N.; Langhans, W.; Romps, D.</p> <p>2017-12-01</p> <p>In the deep tropics, extensive anvil <span class="hlt">clouds</span> produce a peak in <span class="hlt">cloud</span> cover below the tropopause. The dominant paradigm for <span class="hlt">cloud</span> cover attributes this anvil peak to a layer of enhanced mass convergence in the clear-sky upper-troposphere, which is presumed to force frequent detrainment of convective anvils. However, <span class="hlt">cloud</span> cover also depends on the lifetime of cloudy air after it detrains, which raises the possibility that anvil <span class="hlt">clouds</span> may be the signature of slow <span class="hlt">cloud</span> decay rather than enhanced detrainment. Here we measure the <span class="hlt">cloud</span> decay timescale in <span class="hlt">cloud</span>-resolving simulations, and find that cloudy updrafts that detrain in the upper troposphere take much longer to dissipate than their shallower counterparts. We show that <span class="hlt">cloud</span> lifetimes are long in the upper troposphere because the saturation specific humidity becomes orders of magnitude smaller than the typical condensed water loading of cloudy updrafts. This causes evaporative <span class="hlt">cloud</span> decay to act extremely slowly, thereby prolonging <span class="hlt">cloud</span> lifetimes in the upper troposphere. As a consequence, extensive anvil <span class="hlt">clouds</span> still occur in a convecting atmosphere that is forced to have no preferential clear-sky convergence layer. On the other hand, when <span class="hlt">cloud</span> lifetimes are fixed at a characteristic lower-tropospheric value, extensive anvil <span class="hlt">clouds</span> do not form. Our results support a revised understanding of tropical anvil <span class="hlt">clouds</span>, which attributes their existence to the microphysics of slow <span class="hlt">cloud</span> decay rather than a peak in clear-sky convergence.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018oeps.book..114M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018oeps.book..114M"><span><span class="hlt">Clouds</span> in the Martian Atmosphere</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Määttänen, Anni; Montmessin, Franck</p> <p>2018-01-01</p> <p>Although resembling an extremely dry desert, planet Mars hosts <span class="hlt">clouds</span> 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 <span class="hlt">clouds</span>. The existence of water ice <span class="hlt">clouds</span> 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 <span class="hlt">clouds</span> 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 <span class="hlt">clouds</span> 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 <span class="hlt">clouds</span> on Earth. The mesospheric <span class="hlt">clouds</span> are a fairly recent discovery and have put our understanding of the Martian atmosphere to a test. On Mars, <span class="hlt">cloud</span> crystals form on ice nuclei, mostly provided by the omnipresent dust. Thus, the <span class="hlt">clouds</span> 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.</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> identified 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> identified 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/2013EGUGA..1512183N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013EGUGA..1512183N"><span>Inhomogeneities in frontal 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>Neis, Patrick; Krämer, Martina; Hoor, Peter; Reutter, Philipp; Spichtinger, Peter</p> <p>2013-04-01</p> <p>Frontal cirrus <span class="hlt">clouds</span> have a scientifically proven effect on the Earth's radiation budget and thereby an influence on the weather and climate change in regional scale. The formation processes and structures of frontal cirrus <span class="hlt">clouds</span> are still not fully understood. For a close investigation of typical frontal cirrus <span class="hlt">clouds</span>, we use in situ measurements from the CIRRUS-III campaign over Germany and Northern Europe in November 2006. Besides water vapour, <span class="hlt">cloud</span> ice water content, ice particle size distributions, condensation nuclei, and reactive nitrogen were measured during 6 flights. In this work the data of the 24th November flight is used to detect and to analyze warm frontal cirrus <span class="hlt">clouds</span> in the mid latitudes on small temporal and spatial scale. Further, these results are compared with large-scale meteorological analyses from ECMWF and satellite data. Combining these data, the formation and evolution of inhomogeneities in the cirrus <span class="hlt">cloud</span> structure are investigated. One important result is a qualitative agreement between the occurrence of cirrus <span class="hlt">clouds</span> and the 'sharpness' of the Tropopause Inversion Layer (TIL).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19790038545&hterms=pyranometer&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dpyranometer','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19790038545&hterms=pyranometer&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dpyranometer"><span><span class="hlt">Cloud</span> effects on ultraviolet photoclimatology</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Green, A. E. S.; Spinhirne, J. D.</p> <p>1978-01-01</p> <p>The purpose of this study is to quantify for the needs of photobiology the influence of <span class="hlt">clouds</span> upon the ultraviolet spectral irradiance reaching the ground. Towards this end, analytic formulas are developed which approximately characterize the influence of <span class="hlt">clouds</span> upon total solar radiation. These may be used in conjunction with a solar pyranometer to assign an effective visual optical depth for the <span class="hlt">cloud</span> cover. A formula is also developed which characterizes the influence of the optical depth of <span class="hlt">clouds</span> upon the UV spectral irradiance in the 280-340 nm region. Thus total solar energy observations to assign <span class="hlt">cloud</span> optical properties can be used to calculate the UV spectral irradiance at the ground in the presence of these <span class="hlt">clouds</span>. As incidental by-products of this effort, convenient formulas are found for the direct and diffuse components of total solar energy.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040074248&hterms=visa&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dvisa','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040074248&hterms=visa&qs=N%3D0%26Ntk%3DAll%26Ntx%3Dmode%2Bmatchall%26Ntt%3Dvisa"><span>Above-<span class="hlt">Cloud</span> Precipitable Water Retrievals using the MODIS 0.94 micron Band with Applications for Multi-Layer <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>Platnick, S.; Wind, G.</p> <p>2004-01-01</p> <p>In order to perform satellite retrievals of <span class="hlt">cloud</span> properties, it is important to account for the effect of the above-<span class="hlt">cloud</span> atmosphere on the observations. The solar bands used in the operational MODIS Terra and Aqua <span class="hlt">cloud</span> optical and microphysical algorithms (visible, NIR, and SWIR spectral windows) are primarily affected by water vapor, and to a lesser extent by well-mixed gases. For water vapor, the above-<span class="hlt">cloud</span> column amount, or precipitable water, provides adequate information for an atmospheric correction; details of the vertical vapor distribution are not typically necessary for the level of correction required. <span class="hlt">Cloud</span>-top pressure has a secondary effect due to pressure broadening influences. For well- mixed gases, <span class="hlt">cloud</span>-top pressure is also required for estimates of above-<span class="hlt">cloud</span> abundances. We present a method for obtaining above-<span class="hlt">cloud</span> precipitable water over dark Ocean surfaces using the MODIS 0.94 pm vapor absorption band. The retrieval includes an iterative procedure for establishing <span class="hlt">cloud</span>-top temperature and pressure, and is useful for both single layer water and ice <span class="hlt">clouds</span>. Knowledge of <span class="hlt">cloud</span> thermodynamic phase is fundamental in retrieving <span class="hlt">cloud</span> optical and microphysical properties. However, in cases of optically thin cirrus overlapping lower water <span class="hlt">clouds</span>, the concept of a single unique phase is ill- defined and depends, at least, on the spectral region of interest. We will present a method for multi-layer and multi-phase <span class="hlt">cloud</span> detection which uses above-<span class="hlt">cloud</span> precipitable water retrievals along with several existing MODIS operational <span class="hlt">cloud</span> products (<span class="hlt">cloud</span>-top pressure derived from a C02 slicing algorithm, IR and SWIR phase retrievals). Results are catagorized by whether the radiative signature in the MODIS solar bands is primarily that of a water <span class="hlt">cloud</span> with ice <span class="hlt">cloud</span> contamination, or visa-versa. Examples in polar and mid-latitude regions will be shown.</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> type 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> type 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://ntrs.nasa.gov/search.jsp?R=19930039219&hterms=clustering&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dclustering','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930039219&hterms=clustering&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dclustering"><span>Clustering, randomness and regularity in <span class="hlt">cloud</span> fields. I - Theoretical considerations. II - 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>Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.</p> <p>1992-01-01</p> <p>The current controversy existing in reference to the regularity vs. clustering in <span class="hlt">cloud</span> fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus <span class="hlt">cloud</span> field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small <span class="hlt">clouds</span> are included in the <span class="hlt">cloud</span> field distributions, the <span class="hlt">cloud</span> field always has a strong clustering signal.</p> </li> <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 identified 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('http://adsabs.harvard.edu/abs/2009LNCS.5931..451A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931..451A"><span>Green <span class="hlt">Cloud</span> on the Horizon</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Ali, Mufajjul</p> <p></p> <p>This paper proposes a Green <span class="hlt">Cloud</span> model for mobile <span class="hlt">Cloud</span> computing. The proposed model leverage on the current trend of IaaS (Infrastructure as a Service), PaaS (Platform as a Service) and SaaS (Software as a Service), and look at new paradigm called "Network as a Service" (NaaS). The Green <span class="hlt">Cloud</span> model proposes various Telco's revenue generating streams and services with the CaaS (<span class="hlt">Cloud</span> as a Service) for the near future.</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('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 types 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/2010AGUFMAE33B0282F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AGUFMAE33B0282F"><span>Ice in Volcanic <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>Few, A. A.</p> <p>2010-12-01</p> <p>It is widely recognized that lightning activity in thunderstorm <span class="hlt">clouds</span> is associated with ice in the <span class="hlt">clouds</span>. In volcanic plumes the lower electrical discharges near the vent are clearly not associated with ice; however, the electrical discharges from the upper volcanic <span class="hlt">clouds</span> very likely are associated with ice. There is ample water in volcanic plumes and <span class="hlt">clouds</span>. The explosive volcanic eruption is produced by volatile components in the rising magma. Researchers estimate that the water content of the volatiles is up to 99% by mole; other gases are mainly sulfur and chlorine species. These volatiles carry with them a wide range of hot magma melts and solids, importantly silicate particles and tephra. The more massive components fall out near the vent carrying with them much of the heat from the plume; these large components are not in thermodynamic equilibrium with the gases, ash, and lapilli; thus the heat removed does not lower the temperature of the materials carried aloft in the plume. Upward motion is initially provided by the thrust from the volcanic eruption, then by buoyancy of the hot plume. The rising plume is cooled by entrainment of environmental air, which contains water, and by adiabatic expansion; the plume transitions into a volcanic <span class="hlt">cloud</span>. Further lifting and cooling produces supercooled water droplets (T ~ -5 C) in a limited zone (z ~ 9 km) before the fast updraft (~ 60 m/s) rapidly transforms them into ice. Computer models of volcanic <span class="hlt">clouds</span> that include water and ice microphysics indicate that the latent heat of condensation is not significant in <span class="hlt">cloud</span> dynamics because it occurs in a region where buoyancy is provided by the original hot plume material. The latent heat of ice formation occurs at higher and colder levels and seems to contribute to the final lifting of the <span class="hlt">cloud</span> top by ~1.5km. Laboratory results indicate that the fine silicate ash particles, which are abundant, are good ice nuclei, IN. Because of the abundance of the silicate ash</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://pubs.er.usgs.gov/publication/70192187','USGSPUBS'); return false;" href="https://pubs.er.usgs.gov/publication/70192187"><span>Analyzing <span class="hlt">cloud</span> base at local and regional scales to understand tropical montane <span class="hlt">cloud</span> forest vulnerability to climate change</span></a></p> <p><a target="_blank" href="http://pubs.er.usgs.gov/pubs/index.jsp?view=adv">USGS Publications Warehouse</a></p> <p>Van Beusekom, Ashley E.; González, Grizelle; Scholl, Martha A.</p> <p>2017-01-01</p> <p>The degree to which <span class="hlt">cloud</span> immersion provides water in addition to rainfall, suppresses transpiration, and sustains tropical montane <span class="hlt">cloud</span> forests (TMCFs) during rainless periods is not well understood. Climate and land use changes represent a threat to these forests if <span class="hlt">cloud</span> base altitude rises as a result of regional warming or deforestation. To establish a baseline for quantifying future changes in <span class="hlt">cloud</span> base, we installed a ceilometer at 100 m altitude in the forest upwind of the TMCF that occupies an altitude range from ∼ 600 m to the peaks at 1100 m in the Luquillo Mountains of eastern Puerto Rico. Airport Automated Surface Observing System (ASOS) ceilometer data, radiosonde data, and <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite data were obtained to investigate seasonal <span class="hlt">cloud</span> base dynamics, altitude of the trade-wind inversion (TWI), and typical <span class="hlt">cloud</span> thickness for the surrounding Caribbean region. <span class="hlt">Cloud</span> base is rarely quantified near mountains, so these results represent a first look at seasonal and diurnal <span class="hlt">cloud</span> base dynamics for the TMCF. From May 2013 to August 2016, <span class="hlt">cloud</span> base was lowest during the midsummer dry season, and <span class="hlt">cloud</span> bases were lower than the mountaintops as often in the winter dry season as in the wet seasons. The lowest <span class="hlt">cloud</span> bases most frequently occurred at higher elevation than 600 m, from 740 to 964 m. The Luquillo forest low <span class="hlt">cloud</span> base altitudes were higher than six other sites in the Caribbean by ∼ 200–600 m, highlighting the importance of site selection to measure topographic influence on <span class="hlt">cloud</span> height. Proximity to the oceanic <span class="hlt">cloud</span> system where shallow cumulus <span class="hlt">clouds</span> are seasonally invariant in altitude and cover, along with local trade-wind orographic lifting and <span class="hlt">cloud</span> formation, may explain the dry season low <span class="hlt">clouds</span>. The results indicate that climate change threats to low-elevation TMCFs are not limited to the dry season; changes in synoptic-scale weather patterns</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A44F..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A44F..08S"><span>Top-down and Bottom-up aerosol-<span class="hlt">cloud</span>-closure: towards understanding sources of unvertainty in deriving <span class="hlt">cloud</span> radiative flux</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.</p> <p>2017-12-01</p> <p>Top-down and bottom-up aerosol-<span class="hlt">cloud</span> shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, <span class="hlt">clouds</span> and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and <span class="hlt">cloud</span> condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-<span class="hlt">cloud</span> parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a <span class="hlt">cloud</span> sensor to measure <span class="hlt">cloud</span> extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ <span class="hlt">cloud</span> extinction measurements from UAVs to quantify closure in terms of <span class="hlt">cloud</span> shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the <span class="hlt">cloud</span>, which suggests that entrainment processes affect <span class="hlt">cloud</span> microphysical properties and lead to an overestimate of simulated <span class="hlt">cloud</span> shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved <span class="hlt">cloud</span>-top radiative closure. Entrainment reduced the difference between simulated and observation-derived <span class="hlt">cloud</span>-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived <span class="hlt">cloud</span> droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for <span class="hlt">cloud</span>-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, <span class="hlt">cloud</span> microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A44F..08S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A44F..08S"><span>Top-down and Bottom-up aerosol-<span class="hlt">cloud</span>-closure: towards understanding sources of unvertainty in deriving <span class="hlt">cloud</span> radiative flux</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.</p> <p>2016-12-01</p> <p>Top-down and bottom-up aerosol-<span class="hlt">cloud</span> shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, <span class="hlt">clouds</span> and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and <span class="hlt">cloud</span> condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-<span class="hlt">cloud</span> parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a <span class="hlt">cloud</span> sensor to measure <span class="hlt">cloud</span> extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ <span class="hlt">cloud</span> extinction measurements from UAVs to quantify closure in terms of <span class="hlt">cloud</span> shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the <span class="hlt">cloud</span>, which suggests that entrainment processes affect <span class="hlt">cloud</span> microphysical properties and lead to an overestimate of simulated <span class="hlt">cloud</span> shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved <span class="hlt">cloud</span>-top radiative closure. Entrainment reduced the difference between simulated and observation-derived <span class="hlt">cloud</span>-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived <span class="hlt">cloud</span> droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for <span class="hlt">cloud</span>-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, <span class="hlt">cloud</span> microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/10174017','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/10174017"><span>Simulation of seasonal <span class="hlt">cloud</span> forcing anomalies</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>Randall, D.A.</p> <p>1990-08-01</p> <p>One useful way to classify <span class="hlt">clouds</span> is according to the processes that generate them. There are three main <span class="hlt">cloud</span>-formation agencies: deep convection; surface evaporation; large-scale lifting in the absence of conditional instability. Although traditionally <span class="hlt">clouds</span> have been viewed as influencing the atmospheric general circulation primarily through the release of latent heat, the atmospheric science literature contains abundant evidence that, in reality, <span class="hlt">clouds</span> influence the general circulation through four more or less equally important effects: interactions with the solar and terrestrial radiation fields; condensation and evaporation; precipitation; small-scale circulations within the atmosphere. The most advanced of the current generation of GCMsmore » include parameterizations of all four effects. Until recently there has been lingering skepticism, in the general circulation modeling community, that the radiative effects of <span class="hlt">clouds</span> significantly influence the atmospheric general circulation. GCMs have provided the proof that the radiative effects of <span class="hlt">clouds</span> are important for the general circulation of the atmosphere. An important concept in analysis of the effects of <span class="hlt">clouds</span> on climate is the <span class="hlt">cloud</span> radiative forcing (CRF), which is defined as the difference between the radiative flux which actually occurs in the presence of <span class="hlt">clouds</span>, and that which would occur if the <span class="hlt">clouds</span> were removed but the atmospheric state were otherwise unchanged. We also use the term CRF to denote warming or cooling tendencies due to <span class="hlt">cloud</span>-radiation interactions. <span class="hlt">Cloud</span> feedback is the change in CRF that accompanies a climate change. The present study concentrates on the planetary CRF and its response to external forcing, i.e. seasonal change.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931..621Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931..621Z"><span>IBM <span class="hlt">Cloud</span> Computing Powering a Smarter Planet</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhu, Jinzy; Fang, Xing; Guo, Zhe; Niu, Meng Hua; Cao, Fan; Yue, Shuang; Liu, Qin Yu</p> <p></p> <p>With increasing need for intelligent systems supporting the world's businesses, <span class="hlt">Cloud</span> Computing has emerged as a dominant trend to provide a dynamic infrastructure to make such intelligence possible. The article introduced how to build a smarter planet with <span class="hlt">cloud</span> computing technology. First, it introduced why we need <span class="hlt">cloud</span>, and the evolution of <span class="hlt">cloud</span> technology. Secondly, it analyzed the value of <span class="hlt">cloud</span> computing and how to apply <span class="hlt">cloud</span> technology. Finally, it predicted the future of <span class="hlt">cloud</span> in the smarter planet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1999SPIE.3867....2C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1999SPIE.3867....2C"><span>MONET: multidimensional radiative <span class="hlt">cloud</span> scene model</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chervet, Patrick</p> <p>1999-12-01</p> <p>All <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> medium, to study these influences on radiative quantities. We have developed a complete radiative <span class="hlt">cloud</span> scene generator, called MONET (French acronym for: MOdelisation des Nuages En Tridim.) to compute radiative <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> medium generator (CSSM -- <span class="hlt">Cloud</span> 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, <span class="hlt">cloud</span> types)... For the same <span class="hlt">cloud</span> scene, we can output different viewing conditions, or/and various wavelengths. Shadowing effects on <span class="hlt">clouds</span> or grounds are taken into account. This code is useful to study heterogeneity effects on satellite data for various <span class="hlt">cloud</span> types and spatial resolutions, and to determine specifications of new imaging sensor.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20000070391&hterms=Crystal+wave+frequency&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DCrystal%2Bwave%2Bfrequency','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20000070391&hterms=Crystal+wave+frequency&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DCrystal%2Bwave%2Bfrequency"><span>Submillimeter-Wave <span class="hlt">Cloud</span> Ice Radiometry</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Walter, Steven J.</p> <p>1999-01-01</p> <p>Submillimeter-wave <span class="hlt">cloud</span> ice radiometry is a new and innovative technique for characterizing cirrus ice <span class="hlt">clouds</span>. Cirrus <span class="hlt">clouds</span> affect Earth's climate and hydrological cycle by reflecting incoming solar energy, trapping outgoing IR radiation, sublimating into vapor, and influencing atmospheric circulation. Since uncertainties in the global distribution of <span class="hlt">cloud</span> ice restrict the accuracy of both climate and weather models, successful development of this technique could provide a valuable tool for investigating how <span class="hlt">clouds</span> affect climate and weather. <span class="hlt">Cloud</span> ice radiometry could fill an important gap in the observational capabilities of existing and planned Earth-observing systems. Using submillimeter-wave radiometry to retrieve properties of ice <span class="hlt">clouds</span> can be understood with a simple model. There are a number of submillimeter-wavelength spectral regions where the upper troposphere is transparent. At lower tropospheric altitudes water vapor emits a relatively uniform flux of thermal radiation. When cirrus <span class="hlt">clouds</span> are present, they scatter a portion of the upwelling flux of submillimeter-wavelength radiation back towards the Earth as shown in the diagram, thus reducing the upward flux o f energy. Hence, the power received by a down-looking radiometer decreases when a cirrus <span class="hlt">cloud</span> passes through the field of view causing the cirrus <span class="hlt">cloud</span> to appear radiatively cool against the warm lower atmospheric thermal emissions. The reduction in upwelling thermal flux is a function of both the total <span class="hlt">cloud</span> ice content and mean crystal size. Radiometric measurements made at multiple widely spaced frequencies permit flux variations caused by changes in crystal size to be distinguished from changes in ice content, and polarized measurements can be used to constrain mean crystal shape. The goal of the <span class="hlt">cloud</span> ice radiometry program is to further develop and validate this technique of characterizing cirrus. A multi-frequency radiometer is being designed to support airborne science and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3690880','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3690880"><span>Laser-induced plasma <span class="hlt">cloud</span> interaction and ice multiplication under cirrus <span class="hlt">cloud</span> conditions</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Leisner, Thomas; Duft, Denis; Möhler, Ottmar; Saathoff, Harald; Schnaiter, Martin; Henin, Stefano; Stelmaszczyk, Kamil; Petrarca, Massimo; Delagrange, Raphaëlle; Hao, Zuoqiang; Lüder, Johannes; Petit, Yannick; Rohwetter, Philipp; Kasparian, Jérôme; Wolf, Jean-Pierre; Wöste, Ludger</p> <p>2013-01-01</p> <p>Potential impacts of lightning-induced plasma on <span class="hlt">cloud</span> ice formation and precipitation have been a subject of debate for decades. Here, we report on the interaction of laser-generated plasma channels with water and ice <span class="hlt">clouds</span> observed in a large <span class="hlt">cloud</span> simulation chamber. Under the conditions of a typical storm <span class="hlt">cloud</span>, in which ice and supercooled water coexist, no direct influence of the plasma channels on ice formation or precipitation processes could be detected. Under conditions typical for thin cirrus ice <span class="hlt">clouds</span>, however, the plasma channels induced a surprisingly strong effect of ice multiplication. Within a few minutes, the laser action led to a strong enhancement of the total ice particle number density in the chamber by up to a factor of 100, even though only a 10−9 fraction of the chamber volume was exposed to the plasma channels. The newly formed ice particles quickly reduced the water vapor pressure to ice saturation, thereby increasing the <span class="hlt">cloud</span> optical thickness by up to three orders of magnitude. A model relying on the complete vaporization of ice particles in the laser filament and the condensation of the resulting water vapor on plasma ions reproduces our experimental findings. This surprising effect might open new perspectives for remote sensing of water vapor and ice in the upper troposphere. PMID:23733936</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 types 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('https://ntrs.nasa.gov/search.jsp?R=GL-2002-001440&hterms=How+get+human+cloud&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DHow%2Bget%2Bhuman%2Bcloud%253F','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=GL-2002-001440&hterms=How+get+human+cloud&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3DHow%2Bget%2Bhuman%2Bcloud%253F"><span>Invisible 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></p> <p>2002-01-01</p> <p>The Moderate-resolution Imaging Spectroradiometer's (MODIS') <span class="hlt">cloud</span> detection capability is so sensitive that it can detect <span class="hlt">clouds</span> that would be indistinguishable to the human eye. This pair of images highlights MODIS' ability to detect what scientists call 'sub-visible cirrus.' The image on top shows the scene using data collected in the visible part of the electromagnetic spectrum-the part our eyes can see. <span class="hlt">Clouds</span> are apparent in the center and lower right of the image, while the rest of the image appears to be relatively clear. However, data collected at 1.38um (lower image) show that a thick layer of previously undetected cirrus <span class="hlt">clouds</span> obscures the entire scene. These kinds of cirrus are called 'sub-visible' because they can't be detected using only visible light. MODIS' 1.38um channel detects electromagnetic radiation in the infrared region of the spectrum. These images were made from data collected on April 4, 2000. Image courtesy Mark Gray, MODIS Atmosphere Team</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 types 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/2017ApJ...850..139W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ApJ...850..139W"><span>ALMA Observations of a Quiescent Molecular <span class="hlt">Cloud</span> 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>Wong, Tony; Hughes, Annie; Tokuda, Kazuki; Indebetouw, Rémy; Bernard, Jean-Philippe; Onishi, Toshikazu; Wojciechowski, Evan; Bandurski, Jeffrey B.; Kawamura, Akiko; Roman-Duval, Julia; Cao, Yixian; Chen, C.-H. Rosie; Chu, You-hua; Cui, Chaoyue; Fukui, Yasuo; Montier, Ludovic; Muller, Erik; Ott, Juergen; Paradis, Deborah; Pineda, Jorge L.; Rosolowsky, Erik; Sewiło, Marta</p> <p>2017-12-01</p> <p>We present high-resolution (subparsec) observations of a giant molecular <span class="hlt">cloud</span> in the nearest star-forming galaxy, the Large Magellanic <span class="hlt">Cloud</span>. ALMA Band 6 observations trace the bulk of the molecular gas in 12CO(2-1) and the high column density regions in 13CO(2-1). Our target is a quiescent <span class="hlt">cloud</span> (PGCC G282.98-32.40, which we refer to as the “Planck cold cloud” or PCC) in the southern outskirts of the galaxy where star formation activity is very low and largely confined to one location. We decompose the <span class="hlt">cloud</span> into structures using a dendrogram and apply an identical analysis to matched-resolution cubes of the 30 Doradus molecular <span class="hlt">cloud</span> (located near intense star formation) for comparison. Structures in the PCC exhibit roughly 10 times lower surface density and five times lower velocity dispersion than comparably sized structures in 30 Dor, underscoring the non-universality of molecular <span class="hlt">cloud</span> properties. In both <span class="hlt">clouds</span>, structures with relatively higher surface density lie closer to simple virial equilibrium, whereas lower surface-density structures tend to exhibit supervirial line widths. In the PCC, relatively high line widths are found in the vicinity of an infrared source whose properties are consistent with a luminous young stellar object. More generally, we find that the smallest resolved structures (“leaves”) of the dendrogram span close to the full range of line widths observed across all scales. As a result, while the bulk of the kinetic energy is found on the largest scales, the small-scale energetics tend to be dominated by only a few structures, leading to substantial scatter in observed size-line-width relationships.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3698982','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3698982"><span>The AppScale <span class="hlt">Cloud</span> Platform</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Krintz, Chandra</p> <p>2013-01-01</p> <p>AppScale is an open source distributed software system that implements a <span class="hlt">cloud</span> platform as a service (PaaS). AppScale makes <span class="hlt">cloud</span> applications easy to deploy and scale over disparate <span class="hlt">cloud</span> fabrics, implementing a set of APIs and architecture that also makes apps portable across the services they employ. AppScale is API-compatible with Google App Engine (GAE) and thus executes GAE applications on-premise or over other <span class="hlt">cloud</span> infrastructures, without modification. PMID:23828721</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29515125','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29515125"><span>Aerosol effects on <span class="hlt">cloud</span> water amounts were successfully simulated by a global <span class="hlt">cloud</span>-system resolving model.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Sato, Yousuke; Goto, Daisuke; Michibata, Takuro; Suzuki, Kentaroh; Takemura, Toshihiko; Tomita, Hirofumi; Nakajima, Teruyuki</p> <p>2018-03-07</p> <p>Aerosols affect climate by modifying <span class="hlt">cloud</span> properties through their role as <span class="hlt">cloud</span> condensation nuclei or ice nuclei, called aerosol-<span class="hlt">cloud</span> interactions. In most global climate models (GCMs), the aerosol-<span class="hlt">cloud</span> interactions are represented by empirical parameterisations, in which the mass of <span class="hlt">cloud</span> liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of <span class="hlt">cloud</span> microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of <span class="hlt">cloud</span> microphysics in global scale modelling reduces the uncertainty of climate prediction.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040084629&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%26Ntt%3Dsimulation%2Bprocesses','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040084629&hterms=simulation+processes&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D30%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; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.</p> <p>2004-01-01</p> <p><span class="hlt">Cloud</span> microphysics is 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 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., <span class="hlt">cloud</span> 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 <span class="hlt">clouds</span> 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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040082183&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=20040082183&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; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.</p> <p>2004-01-01</p> <p><span class="hlt">Cloud</span> microphysics is 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, r d a U production, and rainfall rates for convective <span class="hlt">clouds</span>. 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., <span class="hlt">cloud</span> 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 <span class="hlt">clouds</span> 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.</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 identified 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 identified 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://www.dtic.mil/docs/citations/ADA589768','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/ADA589768"><span>LiDAR Point <span class="hlt">Cloud</span> and Stereo Image Point <span class="hlt">Cloud</span> Fusion</span></a></p> <p><a target="_blank" href="http://www.dtic.mil/">DTIC Science & Technology</a></p> <p></p> <p>2013-09-01</p> <p>LiDAR point <span class="hlt">cloud</span> (right) highlighting linear edge features ideal for automatic registration...point <span class="hlt">cloud</span> (right) highlighting linear edge features ideal for automatic registration. Areas where topography is being derived, unfortunately, do...with the least amount of automatic correlation errors was used. The following graphic (Figure 12) shows the coverage of the WV1 stereo triplet as</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('https://ntrs.nasa.gov/search.jsp?R=20150008798&hterms=cloud+computing&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dcloud%2Bcomputing','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20150008798&hterms=cloud+computing&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dcloud%2Bcomputing"><span>Enabling Earth Science Through <span class="hlt">Cloud</span> Computing</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hardman, Sean; Riofrio, Andres; Shams, Khawaja; Freeborn, Dana; Springer, Paul; Chafin, Brian</p> <p>2012-01-01</p> <p><span class="hlt">Cloud</span> Computing holds tremendous potential for missions across the National Aeronautics and Space Administration. Several flight missions are already benefiting from an investment in <span class="hlt">cloud</span> computing for mission critical pipelines and services through faster processing time, higher availability, and drastically lower costs available on <span class="hlt">cloud</span> systems. However, these processes do not currently extend to general scientific algorithms relevant to earth science missions. The members of the Airborne <span class="hlt">Cloud</span> Computing Environment task at the Jet Propulsion Laboratory have worked closely with the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) mission to integrate <span class="hlt">cloud</span> computing into their science data processing pipeline. This paper details the efforts involved in deploying a science data system for the CARVE mission, evaluating and integrating <span class="hlt">cloud</span> computing solutions with the system and porting their science algorithms for execution in a <span class="hlt">cloud</span> environment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=clouds&pg=4&id=EJ1040150','ERIC'); return false;" href="https://eric.ed.gov/?q=clouds&pg=4&id=EJ1040150"><span>Get Your Head into the <span class="hlt">Clouds</span>: Using Word <span class="hlt">Clouds</span> for Analyzing Qualitative Assessment Data</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>DePaolo, Concetta A.; Wilkinson, Kelly</p> <p>2014-01-01</p> <p>Word <span class="hlt">clouds</span> (or tag <span class="hlt">clouds</span>) are popular, fun ways to display text data in graphical form; however, we contend that they can also be useful tools in assessment. Using word <span class="hlt">clouds</span>, instructors can quickly and easily produce graphical depictions of text representing student knowledge. By investigating the patterns of words or phrases, or lack…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A41J..03P','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A41J..03P"><span>Efficacy of <span class="hlt">Cloud</span>-Radiative Perturbations in Deep Open- and Closed-Cell Stratocumulus <span class="hlt">Clouds</span> due to Aerosol Perturbations</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Possner, A.; Wang, H.; Caldeira, K.; Wood, R.; Ackerman, T. P.</p> <p>2017-12-01</p> <p>Aerosol-<span class="hlt">cloud</span> interactions (ACIs) in marine stratocumulus remain a significant source of uncertainty in constraining the <span class="hlt">cloud</span>-radiative effect in a changing climate. Ship tracks are undoubted manifestations of ACIs embedded within stratocumulus <span class="hlt">cloud</span> decks and have proven to be a useful framework to study the effect of aerosol perturbations on <span class="hlt">cloud</span> morphology, macrophysical, microphyiscal and <span class="hlt">cloud</span>-radiative properties. However, so far most observational (Christensen et al. 2012, Chen et al. 2015) and numerical studies (Wang et al. 2011, Possner et al. 2015, Berner et al. 2015) have concentrated on ship tracks in shallow boundary layers of depths between 300 - 800 m, while most stratocumulus decks form in significantly deeper boundary layers (Muhlbauer et al. 2014). In this study we investigate the efficacy of aerosol perturbations in deep open and closed cell stratocumulus. Multi-day idealised <span class="hlt">cloud</span>-resolving simulations are performed for the RF06 flight of the VOCALS-Rex field campaign (Wood et al. 2011). During this flight pockets of deep open and closed cells were observed in a 1410 m deep boundary layer. The efficacy of aerosol perturbations of varied concentration and spatial gradients in altering the <span class="hlt">cloud</span> micro- and macrophysical state and <span class="hlt">cloud</span>-radiative effect is determined in both <span class="hlt">cloud</span> regimes. Our simulations show that a continued point source emission flux of 1.16*1011 particles m-2 s-1 applied within a 300x300 m2 gridbox induces pronounced <span class="hlt">cloud</span> cover changes in approximately a third of the simulated 80x80 km2 domain, a weakening of the diurnal cycle in the open-cell regime and a resulting increase in domain-mean <span class="hlt">cloud</span> albedo of 0.2. Furthermore, we contrast the efficacy of equal strength near-surface or above-<span class="hlt">cloud</span> aerosol perturbations in altering the <span class="hlt">cloud</span> state.</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> types in various parts of the world.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/17121992','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/17121992"><span>The dynamics behind Titan's methane <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>Mitchell, Jonathan L; Pierrehumbert, Raymond T; Frierson, Dargan M W; Caballero, Rodrigo</p> <p>2006-12-05</p> <p>We present results of an axisymmetric global circulation model of Titan with a simplified suite of atmospheric physics forced by seasonally varying insolation. The recent discovery of midlatitude tropospheric <span class="hlt">clouds</span> on Titan has caused much excitement about the roles of surface sources of methane and the global circulation in forming <span class="hlt">clouds</span>. Although localized surface sources, such as methane geysers or "cryovolcanoes," have been invoked to explain these <span class="hlt">clouds</span>, we find in this work that <span class="hlt">clouds</span> appear in regions of convergence by the mean meridional circulation and over the poles during solstices, where the solar forcing reaches its seasonal maximum. Other regions are inhibited from forming <span class="hlt">clouds</span> because of dynamical transports of methane and strong subsidence. We find that for a variety of moist regimes, i.e., with the effect of methane thermodynamics included, the observed <span class="hlt">cloud</span> features can be explained by the large-scale dynamics of the atmosphere. <span class="hlt">Clouds</span> at the solsticial pole are found to be a robust feature of Titan's dynamics, whereas isolated midlatitude <span class="hlt">clouds</span> are present exclusively in a variety of moist dynamical regimes. In all cases, even without including methane thermodynamics, our model ceases to produce polar <span class="hlt">clouds</span> approximately 4-6 terrestrial years after solstices.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA00582&hterms=level&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DA%2Blevel','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA00582&hterms=level&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DA%2Blevel"><span>Jupiter's Multi-level <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></p> <p>1997-01-01</p> <p><span class="hlt">Clouds</span> and hazes at various altitudes within the dynamic Jovian atmosphere are revealed by multi-color imaging taken by the Near-Infrared Mapping Spectrometer (NIMS) onboard the Galileo spacecraft. These images were taken during the second orbit (G2) on September 5, 1996 from an early-morning vantage point 2.1 million kilometers (1.3 million miles) above Jupiter. They show the planet's appearance as viewed at various near-infrared wavelengths, with distinct differences due primarily to variations in the altitudes and opacities of the <span class="hlt">cloud</span> systems. The top left and right images, taken at 1.61 microns and 2.73 microns respectively, show relatively clear views of the deep atmosphere, with <span class="hlt">clouds</span> down to a level about three times the atmospheric pressure at the Earth's surface.<p/>By contrast, the middle image in top row, taken at 2.17 microns, shows only the highest altitude <span class="hlt">clouds</span> and hazes. This wavelength is severely affected by the absorption of light by hydrogen gas, the main constituent of Jupiter's atmosphere. Therefore, only the Great Red Spot, the highest equatorial <span class="hlt">clouds</span>, a small feature at mid-northern latitudes, and thin, high photochemical polar hazes can be seen. In the lower left image, at 3.01 microns, deeper <span class="hlt">clouds</span> can be seen dimly against gaseous ammonia and methane absorption. In the lower middle image, at 4.99 microns, the light observed is the planet's own indigenous heat from the deep, warm atmosphere.<p/>The false color image (lower right) succinctly shows various <span class="hlt">cloud</span> and haze levels seen in the Jovian atmosphere. This image indicates the temperature and altitude at which the light being observed is produced. Thermally-rich red areas denote high temperatures from photons in the deep atmosphere leaking through minimal <span class="hlt">cloud</span> cover; green denotes cool temperatures of the tropospheric <span class="hlt">clouds</span>; blue denotes cold of the upper troposphere and lower stratosphere. The polar regions appear purplish, because small-particle hazes allow leakage and</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018PASJ...70S..55W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018PASJ...70S..55W"><span>Bipolar H II regions produced 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>Whitworth, Anthony; Lomax, Oliver; Balfour, Scott; Mège, Pierre; Zavagno, Annie; Deharveng, Lise</p> <p>2018-05-01</p> <p>We suggest that bipolar H II regions may be the aftermath of collisions between <span class="hlt">clouds</span>. Such a collision will produce a shock-compressed layer, and a star cluster can then condense out of the dense gas near the center of the layer. If the <span class="hlt">clouds</span> are sufficiently massive, the star cluster is likely to contain at least one massive star, which emits ionizing radiation, and excites an H II region, which then expands, sweeping up the surrounding neutral gas. Once most of the matter in the <span class="hlt">clouds</span> has accreted onto the layer, expansion of the H II region meets little resistance in directions perpendicular to the midplane of the layer, and so it expands rapidly to produce two lobes of ionized gas, one on each side of the layer. Conversely, in directions parallel to the midplane of the layer, expansion of the H II region stalls due to the ram pressure of the gas that continues to fall towards the star cluster from the outer parts of the layer; a ring of dense neutral gas builds up around the waist of the bipolar H II region, and may spawn a second generation of star formation. We present a dimensionless model for the flow of ionized gas in a bipolar H II region created according to the above scenario, and predict the characteristics of the resulting free-free continuum and recombination-line emission. This dimensionless model can be scaled to the physical parameters of any particular system. Our intention is that these predictions will be useful in testing the scenario outlined above, and thereby providing indirect support for the role of <span class="hlt">cloud-cloud</span> collisions in triggering star formation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19850043975&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=19850043975&hterms=physical+chemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D70%26Ntt%3Dphysical%2Bchemistry"><span>Chemistry in dynamically evolving <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>Tarafdar, S. P.; Prasad, S. S.; Huntress, W. T., Jr.; Villere, K. R.; Black, D. C.</p> <p>1985-01-01</p> <p>A unified model of chemical and dynamical evolution of isolated, initially diffuse and quiescent interstellar <span class="hlt">clouds</span> is presented. The model uses a semiempirically derived dependence of the observed <span class="hlt">cloud</span> temperatures on the visual extinction and density. Even low-mass, low-density, diffuse <span class="hlt">clouds</span> can collapse in this model, because the inward pressure gradient force assists gravitational contraction. In contrast, previous isothermal collapse models required the low-mass diffuse <span class="hlt">clouds</span> to be unrealistically cold before gravitational contraction could start. Theoretically predicted dependences of the column densities of various atoms and molecules, such as C and CO, on visual extinction in diffuse <span class="hlt">clouds</span> are in accord with observations. Similarly, the predicted dependences of the fractional abundances of various chemical species (e.g., CO, H2CO, HCN, HCO(+)) on the total hydrogen density in the core of the dense <span class="hlt">clouds</span> also agree with observations reported to date in the literature. Compared with previous models of interstellar chemistry, the present model has the potential to explain the wide spectrum of chemical and physical properties of both diffuse and dense <span class="hlt">clouds</span> with a common formalism employing only a few simple initial conditions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AGUFM.A23A0182V','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AGUFM.A23A0182V"><span>Evaluation of multi-layer <span class="hlt">cloud</span> detection based on MODIS CO2-slicing algorithm with CALIPSO-<span class="hlt">Cloud</span>Sat measurements.</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Viudez-Mora, A.; Kato, S.; Smith, W. L., Jr.; Chang, F. L.</p> <p>2016-12-01</p> <p>Knowledge of the vertical <span class="hlt">cloud</span> distribution is important for a variety of climate and weather applications. The <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> algorithm (Chang et al. 2005) based on MODIS measurements aboard Aqua satellite (MCF). This algorithm uses the CO2-slicing technique combined with <span class="hlt">cloud</span> properties determined from VIS, IR and NIR channels to locate high thin <span class="hlt">clouds</span> over low-level <span class="hlt">clouds</span>, and retrieve the τ of each layer. We use CALIPSO (Winker et. al, 2010) and <span class="hlt">Cloud</span>Sat (Stephens et. al, 2002) (CLCS) derived <span class="hlt">cloud</span> vertical profiles included in the C3M data product (Kato et al. 2010) to evaluate MCF derived multi-layer <span class="hlt">cloud</span> properties. We focus on 2 layer overlapping and 1-layer <span class="hlt">clouds</span> 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 <span class="hlt">clouds</span> 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 <span class="hlt">cloud</span> 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 <span class="hlt">clouds</span> and determination of their optical properties. J. Atmos. Sci., 62. Kato, S., et al. (2010), Relationships among <span class="hlt">cloud</span> occurrence frequency</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-type <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://www.ncbi.nlm.nih.gov/pubmed/27655341','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27655341"><span>Automating NEURON Simulation Deployment in <span class="hlt">Cloud</span> Resources.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Stockton, David B; Santamaria, Fidel</p> <p>2017-01-01</p> <p>Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, <span class="hlt">cloud</span> computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and <span class="hlt">cloud</span> resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three <span class="hlt">clouds</span>: Chameleon <span class="hlt">Cloud</span>, a hybrid private academic <span class="hlt">cloud</span> for <span class="hlt">cloud</span> technology research based on the OpenStack software; Rackspace, a public commercial <span class="hlt">cloud</span>, also based on OpenStack; and Amazon Elastic <span class="hlt">Cloud</span> Computing, based on Amazon's proprietary software. We describe the manual procedures and how to automate <span class="hlt">cloud</span> operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private <span class="hlt">cloud</span>, public <span class="hlt">cloud</span>, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5669366','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=5669366"><span>Automating NEURON Simulation Deployment in <span class="hlt">Cloud</span> Resources</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Santamaria, Fidel</p> <p>2016-01-01</p> <p>Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, <span class="hlt">cloud</span> computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and <span class="hlt">cloud</span> resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three <span class="hlt">clouds</span>: Chameleon <span class="hlt">Cloud</span>, a hybrid private academic <span class="hlt">cloud</span> for <span class="hlt">cloud</span> technology research based on the Open-Stack software; Rackspace, a public commercial <span class="hlt">cloud</span>, also based on OpenStack; and Amazon Elastic <span class="hlt">Cloud</span> Computing, based on Amazon’s proprietary software. We describe the manual procedures and how to automate <span class="hlt">cloud</span> operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private <span class="hlt">cloud</span>, public <span class="hlt">cloud</span>, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model. PMID:27655341</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018MNRAS.473.3454B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018MNRAS.473.3454B"><span>Filament formation in wind-<span class="hlt">cloud</span> interactions- II. <span class="hlt">Clouds</span> with turbulent density, velocity, and magnetic fields</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Banda-Barragán, W. E.; Federrath, C.; Crocker, R. M.; Bicknell, G. V.</p> <p>2018-01-01</p> <p>We present a set of numerical experiments designed to systematically investigate how turbulence and magnetic fields influence the morphology, energetics, and dynamics of filaments produced in wind-<span class="hlt">cloud</span> interactions. We cover 3D, magnetohydrodynamic systems of supersonic winds impacting <span class="hlt">clouds</span> with turbulent density, velocity, and magnetic fields. We find that lognormal density distributions aid shock propagation through <span class="hlt">clouds</span>, increasing their velocity dispersion and producing filaments with expanded cross-sections and highly magnetized knots and subfilaments. In self-consistently turbulent scenarios, the ratio of filament to initial <span class="hlt">cloud</span> magnetic energy densities is ∼1. The effect of Gaussian velocity fields is bound to the turbulence Mach number: Supersonic velocities trigger a rapid <span class="hlt">cloud</span> expansion; subsonic velocities only have a minor impact. The role of turbulent magnetic fields depends on their tension and is similar to the effect of radiative losses: the stronger the magnetic field or the softer the gas equation of state, the greater the magnetic shielding at wind-filament interfaces and the suppression of Kelvin-Helmholtz instabilities. Overall, we show that including turbulence and magnetic fields is crucial to understanding cold gas entrainment in multiphase winds. While <span class="hlt">cloud</span> porosity and supersonic turbulence enhance the acceleration of <span class="hlt">clouds</span>, magnetic shielding protects them from ablation and causes Rayleigh-Taylor-driven subfilamentation. Wind-swept <span class="hlt">clouds</span> in turbulent models reach distances ∼15-20 times their core radius and acquire bulk speeds ∼0.3-0.4 of the wind speed in one <span class="hlt">cloud</span>-crushing time, which are three times larger than in non-turbulent models. In all simulations, the ratio of turbulent magnetic to kinetic energy densities asymptotes at ∼0.1-0.4, and convergence of all relevant dynamical properties requires at least 64 cells per <span class="hlt">cloud</span> radius.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20100032400&hterms=multilayer&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dmultilayer','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20100032400&hterms=multilayer&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dmultilayer"><span>Evaluation of Satellite-Based Upper Troposphere <span class="hlt">Cloud</span> Top Height Retrievals in Multilayer <span class="hlt">Cloud</span> Conditions During TC4</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; Ayers, J. Kirk; McGill, Matthew J.; Palikonda, Rabindra; Spangenberg, Douglas A.; Smith, William L., Jr.; Yost, Christopher R.</p> <p>2010-01-01</p> <p>Upper troposphere <span class="hlt">cloud</span> top heights (CTHs), restricted to <span class="hlt">cloud</span> top pressures (CTPs) less than 500 hPa, inferred using four satellite retrieval methods applied to Twelfth Geostationary Operational Environmental Satellite (GOES-12) data are evaluated using measurements during the July August 2007 Tropical Composition, <span class="hlt">Cloud</span> and Climate Coupling Experiment (TC4). The four methods are the single-layer CO2-absorption technique (SCO2AT), a modified CO2-absorption technique (MCO2AT) developed for improving both single-layered and multilayered <span class="hlt">cloud</span> retrievals, a standard version of the Visible Infrared Solar-infrared Split-window Technique (old VISST), and a new version of VISST (new VISST) recently developed to improve <span class="hlt">cloud</span> property retrievals. They are evaluated by comparing with ER-2 aircraft-based <span class="hlt">Cloud</span> Physics Lidar (CPL) data taken during 9 days having extensive upper troposphere cirrus, anvil, and convective <span class="hlt">clouds</span>. Compared to the 89% coverage by upper tropospheric <span class="hlt">clouds</span> detected by the CPL, the SCO2AT, MCO2AT, old VISST, and new VISST retrieved CTPs less than 500 hPa in 76, 76, 69, and 74% of the matched pixels, respectively. Most of the differences are due to subvisible and optically thin cirrus <span class="hlt">clouds</span> occurring near the tropopause that were detected only by the CPL. The mean upper tropospheric CTHs for the 9 days are 14.2 (+/- 2.1) km from the CPL and 10.7 (+/- 2.1), 12.1 (+/- 1.6), 9.7 (+/- 2.9), and 11.4 (+/- 2.8) km from the SCO2AT, MCO2AT, old VISST, and new VISST, respectively. Compared to the CPL, the MCO2AT CTHs had the smallest mean biases for semitransparent high <span class="hlt">clouds</span> in both single-layered and multilayered situations whereas the new VISST CTHs had the smallest mean biases when upper <span class="hlt">clouds</span> were opaque and optically thick. The biases for all techniques increased with increasing numbers of <span class="hlt">cloud</span> layers. The transparency of the upper layer <span class="hlt">clouds</span> tends to increase with the numbers of <span class="hlt">cloud</span> layers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20100002807','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20100002807"><span>Automated Detection of <span class="hlt">Clouds</span> in Satellite Imagery</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Jedlovec, Gary</p> <p>2010-01-01</p> <p>Many different approaches have been used to automatically detect <span class="hlt">clouds</span> in satellite imagery. Most approaches are deterministic and provide a binary <span class="hlt">cloud</span> - no <span class="hlt">cloud</span> product used in a variety of applications. Some of these applications require the identification of cloudy pixels for <span class="hlt">cloud</span> parameter retrieval, while others require only an ability to mask out <span class="hlt">clouds</span> for the retrieval of surface or atmospheric parameters in the absence of <span class="hlt">clouds</span>. A few approaches estimate a probability of the presence of a <span class="hlt">cloud</span> at each point in an image. These probabilities allow a user to select <span class="hlt">cloud</span> information based on the tolerance of the application to uncertainty in the estimate. Many automated <span class="hlt">cloud</span> detection techniques develop sophisticated tests using a combination of visible and infrared channels to determine the presence of <span class="hlt">clouds</span> in both day and night imagery. Visible channels are quite effective in detecting <span class="hlt">clouds</span> during the day, as long as test thresholds properly account for variations in surface features and atmospheric scattering. <span class="hlt">Cloud</span> detection at night is more challenging, since only courser resolution infrared measurements are available. A few schemes use just two infrared channels for day and night <span class="hlt">cloud</span> detection. The most influential factor in the success of a particular technique is the determination of the thresholds for each <span class="hlt">cloud</span> test. The techniques which perform the best usually have thresholds that are varied based on the geographic region, time of year, time of day and solar angle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AtmRe.195....1M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AtmRe.195....1M"><span>Effective <span class="hlt">cloud</span> optical depth and enhancement effects for broken liquid water <span class="hlt">clouds</span> in Valencia (Spain)</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Marín, M. J.; Serrano, D.; Utrillas, M. P.; Núñez, M.; Martínez-Lozano, J. A.</p> <p>2017-10-01</p> <p>Partly cloudy skies with liquid water <span class="hlt">clouds</span> have been analysed, founding that it is essential to distinguish data if the Sun is obstructed or not by <span class="hlt">clouds</span>. Both cases can be separated considering simultaneously the <span class="hlt">Cloud</span> Modification Factor (CMF) and the clearness index (kt). For partly cloudy skies and the Sun obstructed the effective <span class="hlt">cloud</span> optical depth (τ) has been obtained by the minimization method for overcast skies. This method was previously developed by the authors but, in this case, taking into account partial <span class="hlt">cloud</span> cover. This study has been conducted for the years 2011-2015 with the multiple scattering model SBDART and irradiance measurements for the UV Erythemal Radiation (UVER) and the broadband ranges. Afterwards a statistical analysis of τ has shown that the maximum value is much lower than for overcast skies and there is more discrepancy between the two spectral ranges regarding the results for overcast skies. In order to validate these results the effective <span class="hlt">cloud</span> optical depth has been correlated with several transmission factors, giving similar fit parameters to those obtained for overcast skies except for the clearness index in the UVER range. As our method is not applicable for partly cloudy skies with the visible Sun, the enhancement of radiation caused by <span class="hlt">clouds</span> when the Sun is visible has been studied. Results show that the average enhancement CMF values are the same for both ranges although enhancement is more frequent for low <span class="hlt">cloud</span> cover in the UVER and medium-high <span class="hlt">cloud</span> cover in the broadband range and it does not depend on the solar zenith angle.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A53G2347A','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A53G2347A"><span>Continuous All-Sky <span class="hlt">Cloud</span> Measurements: <span class="hlt">Cloud</span> Fraction Analysis Based on a Newly Developed Instrument</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Aebi, C.; Groebner, J.; Kaempfer, N.; Vuilleumier, L.</p> <p>2017-12-01</p> <p><span class="hlt">Clouds</span> play an important role in the climate system and are also a crucial parameter for the Earth's surface energy budget. Ground-based measurements of <span class="hlt">clouds</span> provide data in a high temporal resolution in order to quantify its influence on radiation. The newly developed all-sky <span class="hlt">cloud</span> camera at PMOD/WRC in Davos (Switzerland), the infrared <span class="hlt">cloud</span> camera (IRCCAM), is a microbolometer sensitive in the 8 - 14 μm wavelength range. To get all-sky information the camera is located on top of a frame looking downward on a spherical gold-plated mirror. The IRCCAM has been measuring continuously (day and nighttime) with a time resolution of one minute in Davos since September 2015. To assess the performance of the IRCCAM, two different visible all-sky cameras (Mobotix Q24M and Schreder VIS-J1006), which can only operate during daytime, are installed in Davos. All three camera systems have different software for calculating fractional <span class="hlt">cloud</span> coverage from images. Our study analyzes mainly the fractional <span class="hlt">cloud</span> coverage of the IRCCAM and compares it with the fractional <span class="hlt">cloud</span> coverage calculated from the two visible cameras. Preliminary results of the measurement accuracy of the IRCCAM compared to the visible camera indicate that 78 % of the data are within ± 1 octa and even 93 % within ± 2 octas. An uncertainty of 1-2 octas corresponds to the measurement uncertainty of human observers. Therefore, the IRCCAM shows similar performance in detection of <span class="hlt">cloud</span> coverage as the visible cameras and the human observers, with the advantage that continuous measurements with high temporal resolution are possible.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/24897343','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/24897343"><span><span class="hlt">Cloud</span>DOE: a user-friendly tool for deploying Hadoop <span class="hlt">clouds</span> and analyzing high-throughput sequencing data with MapReduce.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Chung, Wei-Chun; Chen, Chien-Chih; Ho, Jan-Ming; Lin, Chung-Yen; Hsu, Wen-Lian; Wang, Yu-Chun; Lee, D T; Lai, Feipei; Huang, Chih-Wei; Chang, Yu-Jung</p> <p>2014-01-01</p> <p>Explosive growth of next-generation sequencing data has resulted in ultra-large-scale data sets and ensuing computational problems. <span class="hlt">Cloud</span> computing provides an on-demand and scalable environment for large-scale data analysis. Using a MapReduce framework, data and workload can be distributed via a network to computers in the <span class="hlt">cloud</span> to substantially reduce computational latency. Hadoop/MapReduce has been successfully adopted in bioinformatics for genome assembly, mapping reads to genomes, and finding single nucleotide polymorphisms. Major <span class="hlt">cloud</span> providers offer Hadoop <span class="hlt">cloud</span> services to their users. However, it remains technically challenging to deploy a Hadoop <span class="hlt">cloud</span> for those who prefer to run MapReduce programs in a cluster without built-in Hadoop/MapReduce. We present <span class="hlt">Cloud</span>DOE, a platform-independent software package implemented in Java. <span class="hlt">Cloud</span>DOE encapsulates technical details behind a user-friendly graphical interface, thus liberating scientists from having to perform complicated operational procedures. Users are guided through the user interface to deploy a Hadoop <span class="hlt">cloud</span> within in-house computing environments and to run applications specifically targeted for bioinformatics, including <span class="hlt">Cloud</span>Burst, <span class="hlt">Cloud</span>Brush, and <span class="hlt">Cloud</span>RS. One may also use <span class="hlt">Cloud</span>DOE on top of a public <span class="hlt">cloud</span>. <span class="hlt">Cloud</span>DOE consists of three wizards, i.e., Deploy, Operate, and Extend wizards. Deploy wizard is designed to aid the system administrator to deploy a Hadoop <span class="hlt">cloud</span>. It installs Java runtime environment version 1.6 and Hadoop version 0.20.203, and initiates the service automatically. Operate wizard allows the user to run a MapReduce application on the dashboard list. To extend the dashboard list, the administrator may install a new MapReduce application using Extend wizard. <span class="hlt">Cloud</span>DOE is a user-friendly tool for deploying a Hadoop <span class="hlt">cloud</span>. Its smart wizards substantially reduce the complexity and costs of deployment, execution, enhancement, and management. Interested users may collaborate to improve the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4045712','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=4045712"><span><span class="hlt">Cloud</span>DOE: A User-Friendly Tool for Deploying Hadoop <span class="hlt">Clouds</span> and Analyzing High-Throughput Sequencing Data with MapReduce</span></a></p> <p><a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pmc">PubMed Central</a></p> <p>Chung, Wei-Chun; Chen, Chien-Chih; Ho, Jan-Ming; Lin, Chung-Yen; Hsu, Wen-Lian; Wang, Yu-Chun; Lee, D. T.; Lai, Feipei; Huang, Chih-Wei; Chang, Yu-Jung</p> <p>2014-01-01</p> <p>Background Explosive growth of next-generation sequencing data has resulted in ultra-large-scale data sets and ensuing computational problems. <span class="hlt">Cloud</span> computing provides an on-demand and scalable environment for large-scale data analysis. Using a MapReduce framework, data and workload can be distributed via a network to computers in the <span class="hlt">cloud</span> to substantially reduce computational latency. Hadoop/MapReduce has been successfully adopted in bioinformatics for genome assembly, mapping reads to genomes, and finding single nucleotide polymorphisms. Major <span class="hlt">cloud</span> providers offer Hadoop <span class="hlt">cloud</span> services to their users. However, it remains technically challenging to deploy a Hadoop <span class="hlt">cloud</span> for those who prefer to run MapReduce programs in a cluster without built-in Hadoop/MapReduce. Results We present <span class="hlt">Cloud</span>DOE, a platform-independent software package implemented in Java. <span class="hlt">Cloud</span>DOE encapsulates technical details behind a user-friendly graphical interface, thus liberating scientists from having to perform complicated operational procedures. Users are guided through the user interface to deploy a Hadoop <span class="hlt">cloud</span> within in-house computing environments and to run applications specifically targeted for bioinformatics, including <span class="hlt">Cloud</span>Burst, <span class="hlt">Cloud</span>Brush, and <span class="hlt">Cloud</span>RS. One may also use <span class="hlt">Cloud</span>DOE on top of a public <span class="hlt">cloud</span>. <span class="hlt">Cloud</span>DOE consists of three wizards, i.e., Deploy, Operate, and Extend wizards. Deploy wizard is designed to aid the system administrator to deploy a Hadoop <span class="hlt">cloud</span>. It installs Java runtime environment version 1.6 and Hadoop version 0.20.203, and initiates the service automatically. Operate wizard allows the user to run a MapReduce application on the dashboard list. To extend the dashboard list, the administrator may install a new MapReduce application using Extend wizard. Conclusions <span class="hlt">Cloud</span>DOE is a user-friendly tool for deploying a Hadoop <span class="hlt">cloud</span>. Its smart wizards substantially reduce the complexity and costs of deployment, execution, enhancement, and management. Interested users</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 identify 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> </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('http://adsabs.harvard.edu/abs/2012AGUFM.A31J..07H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012AGUFM.A31J..07H"><span>The CREW intercomparison of SEVIRI <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>Hamann, U.; Walther, A.; Bennartz, R.; Thoss, A.; Meirink, J. M.; Roebeling, R.</p> <p>2012-12-01</p> <p>About 70% of the earth's surface is covered with <span class="hlt">clouds</span>. They strongly influence the radiation balance and the water cycle of the earth. Hence the detailed monitoring of <span class="hlt">cloud</span> properties - such as <span class="hlt">cloud</span> fraction, <span class="hlt">cloud</span> top temperature, <span class="hlt">cloud</span> particle size, and <span class="hlt">cloud</span> water path - is important to understand the role of <span class="hlt">clouds</span> in the weather and the climate system. The remote sensing with passive sensors is an essential mean for the global observation of the <span class="hlt">cloud</span> parameters, but is nevertheless challenging. This presentation focuses on the inter-comparison and validation of <span class="hlt">cloud</span> physical properties retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard METEOSAT. For this study we use retrievals from 12 state-of-art algorithms (Eumetsat, KNMI, NASA Langley, NASA Goddard, University Madison/Wisconsin, DWD, DLR, Meteo-France, KMI, FU Berlin, UK MetOffice) that are made available through the common database of the CREW (<span class="hlt">Cloud</span> Retrieval Evaluation Working) group. <span class="hlt">Cloud</span> detection, <span class="hlt">cloud</span> top phase, height, and temperature, as well as optical properties and water path are validated with CLOUDSAT, CALIPSO, MISR, and AMSR-E measurements. Special emphasis is given to challenging retrieval conditions. Semi-transparent <span class="hlt">clouds</span> over the earth's surface or another <span class="hlt">cloud</span> layer modify the measured brightness temperature and increase the retrieval uncertainty. The consideration of the three-dimensional radiative effects is especially important for large viewing angles and broken <span class="hlt">cloud</span> fields. Aerosols might be misclassified as <span class="hlt">cloud</span> and may increase the retrieval uncertainty, too. Due to the availability of the high number of sophisticated retrieval datasets, the advantages of different retrieval approaches can be examined and suggestions for future retrieval developments can be made. We like to thank Eumetsat for sponsoring the CREW project including this work.nstitutes that participate in the CREW project.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170001667','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170001667"><span>First Transmitted Hyperspectral Light Measurements and <span class="hlt">Cloud</span> Properties from Recent Field Campaign Sampling <span class="hlt">Clouds</span> Under Biomass Burning Aerosol</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Leblanc, S.; Redemann, Jens; Shinozuka, Yohei; Flynn, Connor J.; Segal Rozenhaimer, Michal; Kacenelenbogen, Meloe Shenandoah; Pistone, Kristina Marie Myers; Schmidt, Sebastian; Cochrane, Sabrina</p> <p>2016-01-01</p> <p>We present a first view of data collected during a recent field campaign aimed at measuring biomass burning aerosol above <span class="hlt">clouds</span> from airborne platforms. The NASA ObseRvations of <span class="hlt">CLouds</span> above Aerosols and their intEractionS (ORACLES) field campaign recently concluded its first deployment sampling <span class="hlt">clouds</span> and overlying aerosol layer from the airborne platform NASA P3. We present results from the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR), in conjunction with the Solar Spectral Flux Radiometers (SSFR). During this deployment, 4STAR sampled transmitted solar light either via direct solar beam measurements and scattered light measurements, enabling the measurement of aerosol optical thickness and the retrieval of information on aerosol particles in addition to overlying <span class="hlt">cloud</span> properties. We focus on the zenith-viewing scattered light measurements, which are used to retrieve <span class="hlt">cloud</span> optical thickness, effective radius, and thermodynamic phase of <span class="hlt">clouds</span> under a biomass burning layer. The biomass burning aerosol layer present above the <span class="hlt">clouds</span> is the cause of potential bias in retrieved <span class="hlt">cloud</span> optical depth and effective radius from satellites. We contrast the typical reflection based approach used by satellites to the transmission based approach used by 4STAR during ORACLES for retrieving <span class="hlt">cloud</span> properties. It is suspected that these differing approaches will yield a change in retrieved properties since light transmitted through <span class="hlt">clouds</span> is sensitive to a different <span class="hlt">cloud</span> volume than reflected light at <span class="hlt">cloud</span> top. We offer a preliminary view of the implications of these differences in sampling volumes to the calculation of <span class="hlt">cloud</span> radiative effects (CRE).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1233295','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1233295"><span>Vertical microphysical profiles of convective <span class="hlt">clouds</span> as a tool for obtaining aerosol <span class="hlt">cloud</span>-mediated climate forcings</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>Rosenfeld, Daniel</p> <p></p> <p>Quantifying the aerosol/<span class="hlt">cloud</span>-mediated radiative effect at a global scale requires simultaneous satellite retrievals of <span class="hlt">cloud</span> condensation nuclei (CCN) concentrations and <span class="hlt">cloud</span> base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/<span class="hlt">cloud</span>-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective <span class="hlt">clouds</span> from an operational polar orbiting weather satellite. Our methodology uses such <span class="hlt">clouds</span> as an effective analog for CCN chambers. The <span class="hlt">cloud</span> base supersaturation (S) is determined by Wb and the satellite-retrieved <span class="hlt">cloud</span> base drop concentrations (Ndb), which ismore » the same as CCN(S). Developing and validating this methodology was possible thanks to the ASR/ARM measurements of CCN and vertical updraft profiles. Validation against ground-based CCN instruments at the ARM sites in Oklahoma, Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective <span class="hlt">clouds</span> of at least 1 km depth that are not obscured by upper layer <span class="hlt">clouds</span>, including semitransparent cirrus. The limitation for small solar backscattering angles of <25º restricts the satellite coverage to ~25% of the world area in a single day. This methodology will likely allow overcoming the challenge of quantifying the aerosol indirect effect and facilitate a substantial reduction of the uncertainty in anthropogenic climate forcing.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010ACPD...1010487M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010ACPD...1010487M"><span>Intercomparison of aerosol-<span class="hlt">cloud</span>-precipitation interactions in stratiform orographic mixed-phase <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>Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.</p> <p>2010-04-01</p> <p>Anthropogenic aerosols serve as a source of both <span class="hlt">cloud</span> condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of <span class="hlt">clouds</span>. Increasing aerosol number concentrations is hypothesized to retard the <span class="hlt">cloud</span> droplet collision/coalescence and the riming in mixed-phase <span class="hlt">clouds</span>, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-<span class="hlt">cloud</span>-precipitation interactions in stratiform orographic mixed-phase <span class="hlt">clouds</span>. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analyzed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as collision/coalescence, aggregation and riming to changes in the aerosol number concentrations are evaluated and compared. The participating models are the Consortium for Small-Scale Modeling's (COSMO) model with bulk-microphysics, the Weather Research and Forecasting (WRF) model with bin-microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice-habit prediction microphysics scheme. All models are operated on a <span class="hlt">cloud</span>-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the second indirect aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others which implies that a decrease in riming with increasing aerosol load is not a robust result</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011SPIE.7752E..04H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011SPIE.7752E..04H"><span>Analysis on the security 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>He, Zhonglin; He, Yuhua</p> <p>2011-02-01</p> <p><span class="hlt">Cloud</span> computing is a new technology, which is the fusion of computer technology and Internet development. It will lead the revolution of IT and information field. However, in <span class="hlt">cloud</span> computing data and application software is stored at large data centers, and the management of data and service is not completely trustable, resulting in safety problems, which is the difficult point to improve the quality of <span class="hlt">cloud</span> service. This paper briefly introduces the concept of <span class="hlt">cloud</span> computing. Considering the characteristics of <span class="hlt">cloud</span> computing, it constructs the security architecture of <span class="hlt">cloud</span> computing. At the same time, with an eye toward the security threats <span class="hlt">cloud</span> computing faces, several corresponding strategies are provided from the aspect of <span class="hlt">cloud</span> computing users and service providers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20040171157&hterms=coverage&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcoverage','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20040171157&hterms=coverage&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dcoverage"><span><span class="hlt">Cloud</span> Coverage and Height Distribution from the GLAS Polar Orbiting Lidar: Comparison to Passive <span class="hlt">Cloud</span> Retrievals</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Spinhime, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.</p> <p>2004-01-01</p> <p>The Geoscience Laser Altimeter System (GLAS) began full on orbit operations in September 2003. A main application of the two-wavelength GLAS lidar is highly accurate detection and profiling of global <span class="hlt">cloud</span> cover. Initial analysis indicates that <span class="hlt">cloud</span> and aerosol layers are consistently detected on a global basis to cross-sections down to 10(exp -6) per meter. Images of the lidar data dramatically and accurately show the vertical structure of <span class="hlt">cloud</span> and aerosol to the limit of signal attenuation. The GLAS lidar has made the most accurate measurement of global <span class="hlt">cloud</span> coverage and height to date. In addition to the calibrated lidar signal, GLAS data products include multi level boundaries and optical depth of all transmissive layers. Processing includes a multi-variable separation of <span class="hlt">cloud</span> and aerosol layers. An initial application of the data results is to compare monthly <span class="hlt">cloud</span> means from several months of GLAS observations in 2003 to existing <span class="hlt">cloud</span> climatologies from other satellite measurement. In some cases direct comparison to passive <span class="hlt">cloud</span> retrievals is possible. A limitation of the lidar measurements is nadir only sampling. However monthly means exhibit reasonably good global statistics and coverage results, at other than polar regions, compare well with other measurements but show significant differences in height distribution. For polar regions where passive <span class="hlt">cloud</span> retrievals are problematic and where orbit track density is greatest, the GLAS results are particularly an advance in <span class="hlt">cloud</span> cover information. Direct comparison to MODIS retrievals show a better than 90% agreement in <span class="hlt">cloud</span> detection for daytime, but less than 60% at night. Height retrievals are in much less agreement. GLAS is a part of the NASA EOS project and data products are thus openly available to the science community (see http://glo.gsfc.nasa.gov).</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' type 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/2017AGUFMIN51D0036Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFMIN51D0036Z"><span>Satellite-based estimation of <span class="hlt">cloud</span>-base updrafts for convective <span class="hlt">clouds</span> and stratocumulus</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zheng, Y.; Rosenfeld, D.; Li, Z.</p> <p>2017-12-01</p> <p>Updraft speeds of thermals have always been notoriously difficult to measure, despite significant roles they play in transporting pollutants and in <span class="hlt">cloud</span> formation and precipitation. To our knowledge, no attempt to date has been made to estimate updraft speed from satellite information. In this study, we introduce three methods of retrieving updraft speeds at <span class="hlt">cloud</span> base () for convective <span class="hlt">clouds</span> and marine stratocumulus with VIIRS onboard Suomi-NPP satellite. The first method uses ground-air temperature difference to characterize the surface sensible heat flux, which is found to be correlated with updraft speeds measured by the Doppler lidar over the Southern Great Plains (SGP). Based on the relationship, we use the satellite-retrieved surface skin temperature and reanalysis surface air temperature to estimate the updrafts. The second method is based on a good linear correlation between <span class="hlt">cloud</span> base height and updrafts, which was found over the SGP, the central Amazon, and on board a ship sailing between Honolulu and Los Angeles. We found a universal relationship for both land and ocean. The third method is for marine stratocumulus. A statistically significant relationship between Wb and <span class="hlt">cloud</span>-top radiative cooling rate (CTRC) is found from measurements over northeastern Pacific and Atlantic. Based on this relation, satellite- and reanalysis-derived CTRC is utilized to infer the Wb of stratocumulus <span class="hlt">clouds</span>. Evaluations against ground-based Doppler lidar measurements show estimation errors of 24%, 21% and 22% for the three methods, respectively.</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 type 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 type 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://adsabs.harvard.edu/abs/2017MS%26E..225a2184R','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MS%26E..225a2184R"><span>Bigdata Driven <span class="hlt">Cloud</span> Security: A Survey</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Raja, K.; Hanifa, Sabibullah Mohamed</p> <p>2017-08-01</p> <p><span class="hlt">Cloud</span> Computing (CC) is a fast-growing technology to perform massive-scale and complex computing. It eliminates the need to maintain expensive computing hardware, dedicated space, and software. Recently, it has been observed that massive growth in the scale of data or big data generated through <span class="hlt">cloud</span> computing. CC consists of a front-end, includes the users’ computers and software required to access the <span class="hlt">cloud</span> network, and back-end consists of various computers, servers and database systems that create the <span class="hlt">cloud</span>. In SaaS (Software as-a-Service - end users to utilize outsourced software), PaaS (Platform as-a-Service-platform is provided) and IaaS (Infrastructure as-a-Service-physical environment is outsourced), and DaaS (Database as-a-Service-data can be housed within a <span class="hlt">cloud</span>), where leading / traditional <span class="hlt">cloud</span> ecosystem delivers the <span class="hlt">cloud</span> services become a powerful and popular architecture. Many challenges and issues are in security or threats, most vital barrier for <span class="hlt">cloud</span> computing environment. The main barrier to the adoption of CC in health care relates to Data security. When placing and transmitting data using public networks, cyber attacks in any form are anticipated in CC. Hence, <span class="hlt">cloud</span> service users need to understand the risk of data breaches and adoption of service delivery model during deployment. This survey deeply covers the CC security issues (covering Data Security in Health care) so as to researchers can develop the robust security application models using Big Data (BD) on CC (can be created / deployed easily). Since, BD evaluation is driven by fast-growing <span class="hlt">cloud</span>-based applications developed using virtualized technologies. In this purview, MapReduce [12] is a good example of big data processing in a <span class="hlt">cloud</span> environment, and a model for <span class="hlt">Cloud</span> providers.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=Cloud+AND+computing+AND+accessibility&id=EJ935542','ERIC'); return false;" href="https://eric.ed.gov/?q=Cloud+AND+computing+AND+accessibility&id=EJ935542"><span>On <span class="hlt">Cloud</span> Nine</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>McCrea, Bridget; Weil, Marty</p> <p>2011-01-01</p> <p>Across the U.S., innovative collaboration practices are happening in the <span class="hlt">cloud</span>: Sixth-graders participate in literary salons. Fourth-graders mentor kindergarteners. And teachers use virtual Post-it notes to advise students as they create their own television shows. In other words, <span class="hlt">cloud</span> computing is no longer just used to manage administrative…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA09922&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=PIA09922&hterms=ammonia&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D40%26Ntt%3Dammonia"><span>Ammonia <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/> [figure removed for brevity, see original site] Click on the image for movie of Ammonia Ice <span class="hlt">Clouds</span> on Jupiter <p/> In this movie, put together from false-color images taken by the New Horizons Ralph instrument as the spacecraft flew past Jupiter in early 2007, show ammonia <span class="hlt">clouds</span> (appearing as bright blue areas) as they form and disperse over five successive Jupiter 'days.' Scientists noted how the larger <span class="hlt">cloud</span> travels along with a small, local deep hole.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19930044342&hterms=condensation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcondensation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19930044342&hterms=condensation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3Dcondensation"><span><span class="hlt">Cloud</span> condensation nuclei near marine cumulus</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hudson, James G.</p> <p>1993-01-01</p> <p>Extensive airborne measurements of <span class="hlt">cloud</span> condensation nucleus (CCN) spectra and condensation nuclei below, in, between, and above the cumulus <span class="hlt">clouds</span> near Hawaii point to important aerosol-<span class="hlt">cloud</span> interactions. Consistent particle concentrations of 200/cu cm were found above the marine boundary layer and within the noncloudy marine boundary layer. Lower and more variable CCN concentrations within the cloudy boundary layer, especially very close to the <span class="hlt">clouds</span>, appear to be a result of <span class="hlt">cloud</span> scavenging processes. Gravitational coagulation of <span class="hlt">cloud</span> droplets may be the principal cause of this difference in the vertical distribution of CCN. The results suggest a reservoir of CCN in the free troposphere which can act as a source for the marine boundary layer.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080044712','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080044712"><span><span class="hlt">Cloud</span> Effects on Meridional Atmospheric Energy Budget Estimated from <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES) Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kato, Seiji; Rose, Fred G.; Rutan, David A.; Charlock, Thomas P.</p> <p>2008-01-01</p> <p>The zonal mean atmospheric <span class="hlt">cloud</span> radiative effect, defined as the difference of the top-of-atmosphere (TOA) and surface <span class="hlt">cloud</span> radiative effects, is estimated from three years of <span class="hlt">Clouds</span> and the Earth's Radiant Energy System (CERES) data. The zonal mean shortwave effect is small, though it tends to be positive (warming). This indicates that <span class="hlt">clouds</span> increase shortwave absorption in the atmosphere, especially in midlatitudes. The zonal mean atmospheric <span class="hlt">cloud</span> radiative effect is, however, dominated by the longwave effect. The zonal mean longwave effect is positive in the tropics and decreases with latitude to negative values (cooling) in polar regions. The meridional gradient of <span class="hlt">cloud</span> effect between midlatitude and polar regions exists even when uncertainties in the <span class="hlt">cloud</span> effect on the surface enthalpy flux and in the modeled irradiances are taken into account. This indicates that <span class="hlt">clouds</span> increase the rate of generation of mean zonal available potential energy. Because the atmospheric cooling effect in polar regions is predominately caused by low level <span class="hlt">clouds</span>, which tend to be stationary, we postulate that the meridional and vertical gradients of <span class="hlt">cloud</span> effect increase the rate of meridional energy transport by dynamics in the atmosphere from midlatitude to polar region, especially in fall and winter. <span class="hlt">Clouds</span> then warm the surface in polar regions except in the Arctic in summer. <span class="hlt">Clouds</span>, therefore, contribute in increasing the rate of meridional energy transport from midlatitude to polar regions through the atmosphere.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014SPIE.9111E..0DC','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014SPIE.9111E..0DC"><span>Analysis of the VIIRS <span class="hlt">cloud</span> mask, comparison with the NAVOCEANO <span class="hlt">cloud</span> mask, and how they complement each other</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Cayula, Jean-François P.; May, Douglas A.; McKenzie, Bruce D.</p> <p>2014-05-01</p> <p>The Visible Infrared Imaging Radiometer Suite (VIIRS) <span class="hlt">Cloud</span> 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 <span class="hlt">cloud</span> contaminated observations. Unfortunately, VCM does not appear to perform as well as <span class="hlt">cloud</span> detection algorithms for SST. This may be due to similar but different goals of the two algorithms. VCM is concerned with detecting <span class="hlt">clouds</span> while SST is interested in identifying clear observations. The result is that in undetermined cases VCM defaults to "clear," while the SST <span class="hlt">cloud</span> detection defaults to "<span class="hlt">cloud</span>." This problem is further compounded because classic SST <span class="hlt">cloud</span> detection often flags as "<span class="hlt">cloud</span>" 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 <span class="hlt">cloud</span> detection from the NAVOCEANO <span class="hlt">Cloud</span> Mask (NCM), adapted from <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span>-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.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900031740&hterms=physical+chemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dphysical%2Bchemistry','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900031740&hterms=physical+chemistry&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dphysical%2Bchemistry"><span>Diffuse <span class="hlt">cloud</span> chemistry. [in interstellar matter</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Van Dishoeck, Ewine F.; Black, John H.</p> <p>1988-01-01</p> <p>The current status of models of diffuse interstellar <span class="hlt">clouds</span> is reviewed. A detailed comparison of recent gas-phase steady-state models shows that both the physical conditions and the molecular abundances in diffuse <span class="hlt">clouds</span> are still not fully understood. Alternative mechanisms are discussed and observational tests which may discriminate between the various models are suggested. Recent developments regarding the velocity structure of diffuse <span class="hlt">clouds</span> are mentioned. Similarities and differences between the chemistries in diffuse <span class="hlt">clouds</span> and those in translucent and high latitude <span class="hlt">clouds</span> are pointed out.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2012SPIE.8386E..0AL','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2012SPIE.8386E..0AL"><span>Transitioning ISR architecture into 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>Lash, Thomas D.</p> <p>2012-06-01</p> <p>Emerging <span class="hlt">cloud</span> computing platforms offer an ideal opportunity for Intelligence, Surveillance, and Reconnaissance (ISR) intelligence analysis. <span class="hlt">Cloud</span> computing platforms help overcome challenges and limitations of traditional ISR architectures. Modern ISR architectures can benefit from examining commercial <span class="hlt">cloud</span> applications, especially as they relate to user experience, usage profiling, and transformational business models. This paper outlines legacy ISR architectures and their limitations, presents an overview of <span class="hlt">cloud</span> technologies and their applications to the ISR intelligence mission, and presents an idealized ISR architecture implemented with <span class="hlt">cloud</span> computing.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20040086915','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20040086915"><span>Microphysics of Pyrocumulonimbus <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>Jensen, Eric; Ackerman, Andrew S.; Fridlind, Ann</p> <p>2004-01-01</p> <p>The intense heat from forest fires can generate explosive deep convective <span class="hlt">cloud</span> systems that inject pollutants to high altitudes. Both satellite and high-altitude aircraft measurements have documented cases in which these pyrocumulonimbus <span class="hlt">clouds</span> inject large amounts of smoke well into the stratosphere (Fromm and Servranckx 2003; Jost et al. 2004). This smoke can remain in the stratosphere, be transported large distances, and affect lower stratospheric chemistry. In addition recent in situ measurements in pyrocumulus updrafts have shown that the high concentrations of smoke particles have significant impacts on <span class="hlt">cloud</span> microphysical properties. Very high droplet number densities result in delayed precipitation and may enhance lightning (Andrew et al. 2004). Presumably, the smoke particles will also lead to changes in the properties of anvil cirrus produces by the deep convection, with resulting influences on <span class="hlt">cloud</span> radiative forcing. In situ sampling near the tops of mature pyrocumulonimbus is difficult due to the high altitude and violence of the storms. In this study, we use large eddy simulations (LES) with size-resolved microphysics to elucidate physical processes in pyrocumulonimbus <span class="hlt">clouds</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 identified 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> </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/2018A%26A...611A...5S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018A%26A...611A...5S"><span>Large Interstellar Polarisation Survey. II. UV/optical study of <span class="hlt">cloud-to-cloud</span> variations of dust in the diffuse ISM</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Siebenmorgen, R.; Voshchinnikov, N. V.; Bagnulo, S.; Cox, N. L. J.; Cami, J.; Peest, C.</p> <p>2018-03-01</p> <p>It is well known that the dust properties of the diffuse interstellar medium exhibit variations towards different sight-lines on a large scale. We have investigated the variability of the dust characteristics on a small scale, and from <span class="hlt">cloud-to-cloud</span>. We use low-resolution spectro-polarimetric data obtained in the context of the Large Interstellar Polarisation Survey (LIPS) towards 59 sight-lines in the Southern Hemisphere, and we fit these data using a dust model composed of silicate and carbon particles with sizes from the molecular to the sub-micrometre domain. Large (≥6 nm) silicates of prolate shape account for the observed polarisation. For 32 sight-lines we complement our data set with UVES archive high-resolution spectra, which enable us to establish the presence of single-<span class="hlt">cloud</span> or multiple-<span class="hlt">clouds</span> towards individual sight-lines. We find that the majority of these 35 sight-lines intersect two or more <span class="hlt">clouds</span>, while eight of them are dominated by a single absorbing <span class="hlt">cloud</span>. We confirm several correlations between extinction and parameters of the Serkowski law with dust parameters, but we also find previously undetected correlations between these parameters that are valid only in single-<span class="hlt">cloud</span> sight-lines. We find that interstellar polarisation from multiple-<span class="hlt">clouds</span> is smaller than from single-<span class="hlt">cloud</span> sight-lines, showing that the presence of a second or more <span class="hlt">clouds</span> depolarises the incoming radiation. We find large variations of the dust characteristics from <span class="hlt">cloud-to-cloud</span>. However, when we average a sufficiently large number of <span class="hlt">clouds</span> in single-<span class="hlt">cloud</span> or multiple-<span class="hlt">cloud</span> sight-lines, we always retrieve similar mean dust parameters. The typical dust abundances of the single-<span class="hlt">cloud</span> cases are [C]/[H] = 92 ppm and [Si]/[H] = 20 ppm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017ACP....17.9797S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017ACP....17.9797S"><span>Top-down and bottom-up aerosol-<span class="hlt">cloud</span> closure: towards understanding sources of uncertainty in deriving <span class="hlt">cloud</span> shortwave radiative flux</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sanchez, Kevin J.; Roberts, Gregory C.; Calmer, Radiance; Nicoll, Keri; Hashimshoni, Eyal; Rosenfeld, Daniel; Ovadnevaite, Jurgita; Preissler, Jana; Ceburnis, Darius; O'Dowd, Colin; Russell, Lynn M.</p> <p>2017-08-01</p> <p>Top-down and bottom-up aerosol-<span class="hlt">cloud</span> shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on <span class="hlt">Clouds</span> and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol-<span class="hlt">cloud</span> shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs)1 and satellite measurements of aerosols, <span class="hlt">clouds</span> and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and <span class="hlt">cloud</span> condensation nuclei (CCN) concentration were used to initiate a 1-D microphysical aerosol-<span class="hlt">cloud</span> parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a <span class="hlt">cloud</span> sensor to measure <span class="hlt">cloud</span> extinction or a five-hole probe for 3-D wind vectors. UAV <span class="hlt">cloud</span> measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ <span class="hlt">cloud</span> extinction measurements from UAVs to quantify closure in terms of <span class="hlt">cloud</span> shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the <span class="hlt">cloud</span>, which suggests that entrainment processes affect <span class="hlt">cloud</span> microphysical properties and lead to an overestimate of simulated <span class="hlt">cloud</span> shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved <span class="hlt">cloud</span>-top radiative closure. Entrainment reduced the difference between simulated and observation-derived <span class="hlt">cloud</span>-top shortwave radiative flux (δRF) by between 25 and 60 W m-2. After accounting for entrainment</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016AMT.....9..909F','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016AMT.....9..909F"><span>Synergy of stereo <span class="hlt">cloud</span> top height and ORAC optimal estimation <span class="hlt">cloud</span> retrieval: evaluation and application to AATSR</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Fisher, Daniel; Poulsen, Caroline A.; Thomas, Gareth E.; Muller, Jan-Peter</p> <p>2016-03-01</p> <p>In this paper we evaluate the impact on the <span class="hlt">cloud</span> parameter retrievals of the ORAC (Optimal Retrieval of Aerosol and <span class="hlt">Cloud</span>) algorithm following the inclusion of stereo-derived <span class="hlt">cloud</span> top heights as a priori information. This is performed in a mathematically rigorous way using the ORAC optimal estimation retrieval framework, which includes the facility to use such independent a priori information. Key to the use of a priori information is a characterisation of their associated uncertainty. This paper demonstrates the improvements that are possible using this approach and also considers their impact on the microphysical <span class="hlt">cloud</span> parameters retrieved. The Along-Track Scanning Radiometer (AATSR) instrument has two views and three thermal channels, so it is well placed to demonstrate the synergy of the two techniques. The stereo retrieval is able to improve the accuracy of the retrieved <span class="hlt">cloud</span> top height when compared to collocated <span class="hlt">Cloud</span>-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), particularly in the presence of boundary layer inversions and high <span class="hlt">clouds</span>. The impact of the stereo a priori information on the microphysical <span class="hlt">cloud</span> properties of <span class="hlt">cloud</span> optical thickness (COT) and effective radius (RE) was evaluated and generally found to be very small for single-layer <span class="hlt">clouds</span> conditions over open water (mean RE differences of 2.2 (±5.9) microns and mean COD differences of 0.5 (±1.8) for single-layer ice <span class="hlt">clouds</span> over open water at elevations of above 9 km, which are most strongly affected by the inclusion of the a priori).</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA02171&hterms=cloud+technology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dcloud%2Btechnology','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA02171&hterms=cloud+technology&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dcloud%2Btechnology"><span><span class="hlt">Cloud</span> Front</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>2006-01-01</p> <p><p/> [figure removed for brevity, see original site] Context image for PIA02171 <span class="hlt">Cloud</span> Front <p/> These <span class="hlt">clouds</span> formed in the south polar region. The faintness of the <span class="hlt">cloud</span> system likely indicates that these are mainly ice <span class="hlt">clouds</span>, with relatively little dust content. <p/> Image information: VIS instrument. Latitude -86.7N, Longitude 212.3E. 17 meter/pixel resolution. <p/> Note: this THEMIS visual image has not been radiometrically nor geometrically calibrated for this preliminary release. An empirical correction has been performed to remove instrumental effects. A linear shift has been applied in the cross-track and down-track direction to approximate spacecraft and planetary motion. Fully calibrated and geometrically projected images will be released through the Planetary Data System in accordance with Project policies at a later time. <p/> NASA's Jet Propulsion Laboratory manages the 2001 Mars Odyssey mission for NASA's Office of Space Science, Washington, D.C. The Thermal Emission Imaging System (THEMIS) was developed by Arizona State University, Tempe, in collaboration with Raytheon Santa Barbara Remote Sensing. The THEMIS investigation is led by Dr. Philip Christensen at Arizona State University. Lockheed Martin Astronautics, Denver, is the prime contractor for the Odyssey project, and developed and built the orbiter. Mission operations are conducted jointly from Lockheed Martin and from JPL, a division of the California Institute of Technology in Pasadena.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005GeoRL..3224819W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005GeoRL..3224819W"><span>Evaluation of AIRS <span class="hlt">cloud</span> properties using MPACE data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wu, Xuebao; Li, Jun; Menzel, W. Paul; Huang, Allen; Baggett, Kevin; Revercomb, Henry</p> <p>2005-12-01</p> <p>Retrieval of <span class="hlt">cloud</span> properties from the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite has been investigated. The <span class="hlt">cloud</span> products from the collocated MODerate resolution Imaging Spectroradiometer (MODIS) data are used to characterize the AIRS sub-pixel <span class="hlt">cloud</span> information such as <span class="hlt">cloud</span> phase, <span class="hlt">cloud</span> coverage, and <span class="hlt">cloud</span> layer information. A Minimum Residual (MR) approach is used to retrieve <span class="hlt">cloud</span> microphysical properties once the <span class="hlt">cloud</span> top pressure (CTP) and effective <span class="hlt">cloud</span> amount (ECA) are determined from AIRS CO2 absorption channels between 720 and 790 cm-1. The <span class="hlt">cloud</span> microphysical properties can be retrieved by minimizing the differences between the observations and the calculations using AIRS longwave window channels between 790 and 1130 cm-1. AIRS is used to derive <span class="hlt">cloud</span> properties during the Mixed Phase Arctic <span class="hlt">Cloud</span> Experiment (MPACE) field campaign. Comparison with measurements obtained from lidar data is made for a test day, showing that AIRS <span class="hlt">cloud</span> property retrievals agree with in situ lidar observations. Due to the large solar zenith angle, the MODIS operational retrieval approach is not able to provide <span class="hlt">cloud</span> microphysics north of Barrow, Alaska; however, AIRS provides <span class="hlt">cloud</span> microphysical properties with its high spectral resolution IR measurements.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016PPNL...13..609B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016PPNL...13..609B"><span>Optimization of over-provisioned <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>Balashov, N.; Baranov, A.; Korenkov, V.</p> <p>2016-09-01</p> <p>The functioning of modern applications in <span class="hlt">cloud</span>-centers is characterized by a huge variety of computational workloads generated. This causes uneven workload distribution and as a result leads to ineffective utilization of <span class="hlt">cloud</span>-centers' hardware. The proposed article addresses the possible ways to solve this issue and demonstrates that it is a matter of necessity to optimize <span class="hlt">cloud</span>-centers' hardware utilization. As one of the possible ways to solve the problem of the inefficient resource utilization in heterogeneous <span class="hlt">cloud</span>-environments an algorithm of dynamic re-allocation of virtual resources is suggested.</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 identify 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('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 identified 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://hdl.handle.net/2060/19830010449','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830010449"><span>Comparison of modern icing <span class="hlt">cloud</span> instruments</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Takeuchi, D. M.; Jahnsen, L. J.; Callander, S. M.; Humbert, M. C.</p> <p>1983-01-01</p> <p>Intercomparison tests with Particle Measuring Systems (PMS) were conducted. <span class="hlt">Cloud</span> liquid water content (LWC) measurements were also taken with a Johnson and Williams (JW) hot-wire device and an icing rate device (Leigh IDS). Tests include varying <span class="hlt">cloud</span> LWC (0.5 to 5 au gm), <span class="hlt">cloud</span> median volume diameter (MVD) (15 to 26 microns), temperature (-29 to 20 C), and air speeds (50 to 285 mph). Comparisons were based upon evaluating probe estimates of <span class="hlt">cloud</span> LWC and median volume diameter for given tunnel settings. Variations of plus or minus 10% and plus or minus 5% in LWC and MVD, respectively, were determined of spray <span class="hlt">clouds</span> between test made at given tunnel settings (fixed LWC, MVD, and air speed) indicating <span class="hlt">cloud</span> conditions were highly reproducible. Although LWC measurements from JW and Leigh devices were consistent with tunnel values, individual probe measurements either consistently over or underestimated tunnel values by factors ranging from about 0.2 to 2. Range amounted to a factor of 6 differences between LWC estimates of probes for given <span class="hlt">cloud</span> conditions. For given <span class="hlt">cloud</span> conditions, estimates of <span class="hlt">cloud</span> MVD between probes were within plus or minus 3 microns and 93% of the test cases. Measurements overestimated tunnel values in the range between 10 to 20 microns. The need for improving currently used calibration procedures was indicated. Establishment of test facility (or facilities) such as an icing tunnel where instruments can be calibrated against known <span class="hlt">cloud</span> standards would be a logical choice.</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 identify 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('https://images.nasa.gov/#/details-PIA12005.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA12005.html"><span>Titan South Polar <span class="hlt">Cloud</span> Burst</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2009-06-03</p> <p>This infrared image of Saturn's moon Titan shows a large burst of <span class="hlt">clouds</span> in the moon's south polar region. These <span class="hlt">clouds</span> form and move much like those on Earth, but in a much slower, more lingering fashion, new results from NASA's Cassini Spacecraft show. This image is a color composite, with red shown at a 5-micron wavelength, green at 2.7 microns, and blue at 2 microns. An infrared color mosaic is also used as a background image (red at 5 microns, green at 2 microns, blue at 1.3 microns). The images were taken by Cassini's visual and infrared mapping spectrometer during a flyby of Titan on March 26, 2007, known as T27. For a similar view see PIA12004. Titan's southern hemisphere still shows a very active meteorology (the <span class="hlt">cloud</span> appears in white-reddish tones) even in 2007. According to climate models, these <span class="hlt">clouds</span> should have faded out since 2005. Scientists have monitored Titan's atmosphere for three-and-a-half years, between July 2004 and December 2007, and observed more than 200 <span class="hlt">clouds</span>. The way these <span class="hlt">clouds</span> are distributed around Titan matches scientists' global circulation models. The only exception is timing—<span class="hlt">clouds</span> are still noticeable in the southern hemisphere while fall is approaching. http://photojournal.jpl.nasa.gov/catalog/PIA12005</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1294258','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1294258"><span>Determination of <span class="hlt">Cloud</span> Base Height, Wind Velocity, and Short-Range <span class="hlt">Cloud</span> Structure Using Multiple Sky Imagers Field Campaign Report</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>Huang, Dong; Schwartz, Stephen E.; Yu, Dantong</p> <p></p> <p><span class="hlt">Clouds</span> are a central focus of the U.S. Department of Energy (DOE)’s Atmospheric System Research (ASR) program and Atmospheric Radiation Measurement (ARM) Climate Research Facility, and more broadly are the subject of much investigation because of their important effects on atmospheric radiation and, through feedbacks, on climate sensitivity. Significant progress has been made by moving from a vertically pointing (“soda-straw”) to a three-dimensional (3D) view of <span class="hlt">clouds</span> by investing in scanning <span class="hlt">cloud</span> radars through the American Recovery and Reinvestment Act of 2009. Yet, because of the physical nature of radars, there are key gaps in ARM's <span class="hlt">cloud</span> observational capabilities. Formore » example, <span class="hlt">cloud</span> radars often fail to detect small shallow cumulus and thin cirrus <span class="hlt">clouds</span> that are nonetheless radiatively important. Furthermore, it takes five to twenty minutes for a <span class="hlt">cloud</span> radar to complete a 3D volume scan and <span class="hlt">clouds</span> can evolve substantially during this period. Ground-based stereo-imaging is a promising technique to complement existing ARM <span class="hlt">cloud</span> observation capabilities. It enables the estimation of <span class="hlt">cloud</span> coverage, height, horizontal motion, morphology, and spatial arrangement over an extended area of up to 30 by 30 km at refresh rates greater than 1 Hz (Peng et al. 2015). With fine spatial and temporal resolution of modern sky cameras, the stereo-imaging technique allows for the tracking of a small cumulus <span class="hlt">cloud</span> or a thin cirrus <span class="hlt">cloud</span> that cannot be detected by a <span class="hlt">cloud</span> radar. With support from the DOE SunShot Initiative, the Principal Investigator (PI)’s team at Brookhaven National Laboratory (BNL) has developed some initial capability for <span class="hlt">cloud</span> tracking using multiple distinctly located hemispheric cameras (Peng et al. 2015). To validate the ground-based <span class="hlt">cloud</span> stereo-imaging technique, the <span class="hlt">cloud</span> stereo-imaging field campaign was conducted at the ARM Facility’s Southern Great Plains (SGP) site in Oklahoma from July 15 to December 24. As shown in Figure 1</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19810017066','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19810017066"><span>Transport of infrared radiation in cuboidal <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>HARSHVARDHAN; Weinman, J. A.; Davies, R.</p> <p>1981-01-01</p> <p>The transport of infrared radiation in a single cuboidal <span class="hlt">cloud</span> using a vertical two steam approximation was modeled. The emittance of the top face of the model <span class="hlt">cloud</span> is always less than that for a plane parallel <span class="hlt">cloud</span> of the same optical depth. The hemisphere flux escaping from the <span class="hlt">cloud</span> top has a gradient from the center to the edges which brighten when the <span class="hlt">cloud</span> is over warmer ground. Cooling rate calculations in the 8 to 13.6 micrometer region show that there is cooling from the sides of the <span class="hlt">cloud</span> at all levels even when there is heating of the core from the ground below. The radiances exiting from model cuboidal <span class="hlt">clouds</span> were computed by path integration over the source function obtained with the two stream approximation. It is suggested that the brightness temperature measured from finite <span class="hlt">clouds</span> will overestimate the <span class="hlt">cloud</span> top temperature.</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 types 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('https://www.osti.gov/pages/biblio/1324260-ap-cloud-adaptive-particle-cloud-method-optimal-solutions-vlasovpoisson-equation','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1324260-ap-cloud-adaptive-particle-cloud-method-optimal-solutions-vlasovpoisson-equation"><span>AP-<span class="hlt">Cloud</span>: Adaptive particle-in-<span class="hlt">cloud</span> method for optimal solutions to Vlasov–Poisson equation</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; ...</p> <p>2016-04-19</p> <p>We propose a new adaptive Particle-in-<span class="hlt">Cloud</span> (AP-<span class="hlt">Cloud</span>) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-<span class="hlt">Cloud</span> adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-<span class="hlt">Cloud</span> is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-<span class="hlt">Cloud</span> theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-<span class="hlt">Cloud</span> method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/22572331-ap-cloud-adaptive-particle-cloud-method-optimal-solutions-vlasovpoisson-equation','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/22572331-ap-cloud-adaptive-particle-cloud-method-optimal-solutions-vlasovpoisson-equation"><span>AP-<span class="hlt">Cloud</span>: Adaptive Particle-in-<span class="hlt">Cloud</span> method for optimal solutions to Vlasov–Poisson equation</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>Wang, Xingyu; Samulyak, Roman, E-mail: roman.samulyak@stonybrook.edu; Computational Science Initiative, Brookhaven National Laboratory, Upton, NY 11973</p> <p></p> <p>We propose a new adaptive Particle-in-<span class="hlt">Cloud</span> (AP-<span class="hlt">Cloud</span>) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-<span class="hlt">Cloud</span> adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-<span class="hlt">Cloud</span> is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-<span class="hlt">Cloud</span> theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Simulation results show that the AP-<span class="hlt">Cloud</span> method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1324260','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1324260"><span>AP-<span class="hlt">Cloud</span>: Adaptive particle-in-<span class="hlt">cloud</span> method for optimal solutions to Vlasov–Poisson equation</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>Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin</p> <p></p> <p>We propose a new adaptive Particle-in-<span class="hlt">Cloud</span> (AP-<span class="hlt">Cloud</span>) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-<span class="hlt">Cloud</span> adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-<span class="hlt">Cloud</span> is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-<span class="hlt">Cloud</span> theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-<span class="hlt">Cloud</span> method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A43B2454J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A43B2454J"><span>Boundary Layer Thermodynamics and <span class="hlt">Cloud</span> Microphysics for a Mixed Stratocumulus and Cumulus <span class="hlt">Cloud</span> Field Observed during ACE-ENA</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jensen, M. P.; Miller, M. A.; Wang, J.</p> <p>2017-12-01</p> <p>The first Intensive Observation Period of the DOE Aerosol and <span class="hlt">Cloud</span> Experiments in the Eastern North Atlantic (ACE-ENA) took place from 21 June through 20 July 2017 involving the deployment of the ARM Gulfstream-159 (G-1) aircraft with a suite of in situ <span class="hlt">cloud</span> and aerosol instrumentation in the vicinity of the ARM Climate Research Facility Eastern North Atlantic (ENA) site on Graciosa Island, Azores. Here we present preliminary analysis of the thermodynamic characteristics of the marine boundary layer and the variability of <span class="hlt">cloud</span> properties for a mixed <span class="hlt">cloud</span> field including both stratiform <span class="hlt">cloud</span> layers and deeper cumulus elements. Analysis combines in situ atmospheric state observations from the G-1 with radiosonde profiles and surface meteorology from the ENA site in order to characterize the thermodynamic structure of the marine boundary layer including the coupling state and stability. <span class="hlt">Cloud</span>/drizzle droplet size distributions measured in situ are combined with remote sensing observations from a scanning <span class="hlt">cloud</span> radar, and vertically pointing <span class="hlt">cloud</span> radar and lidar provide quantification of the macrophysical and microphysical properties of the mixed <span class="hlt">cloud</span> field.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19900045348&hterms=1101&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3D%2526%25231101','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19900045348&hterms=1101&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3D%2526%25231101"><span>Physical conditions in molecular <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>Evans, Neal J., II</p> <p>1989-01-01</p> <p>Recent developments have complicated the picture of the physical conditions in molecular <span class="hlt">clouds</span>. The discoveries of widespread emission from high-J lines of CD and 12-micron IRAS emission have revealed the presence of considerably hotter gas and dust near the surfaces of molecular <span class="hlt">clouds</span>. These components can complicate interpretation of the bulk of the <span class="hlt">cloud</span> gas. Commonly assumed relations between column density or mean density and <span class="hlt">cloud</span> size are called into question by conflicting results and by consideration of selection effects. Analysis of density and density structure through molecular excitation has shown that very high densities exist in star formation regions, but unresolved structure and possible chemical effects complicate the interpretation. High resolution far-IR and submillimeter observations offer a complementary approach and are beginning to test theoretical predictions of density gradients in <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018ClDy...50.1209S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018ClDy...50.1209S"><span>Variability in modeled <span class="hlt">cloud</span> feedback tied to differences in the climatological spatial pattern of <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>Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.</p> <p>2018-02-01</p> <p>Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to <span class="hlt">clouds</span> (the shortwave <span class="hlt">cloud</span> feedback). Here, model differences in the shortwave <span class="hlt">cloud</span> feedback are found to be closely related to the spatial pattern of the <span class="hlt">cloud</span> contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global <span class="hlt">cloud</span> feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average <span class="hlt">cloud</span> feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global <span class="hlt">cloud</span> feedback may be substantially reduced by ensuring a realistic distribution of <span class="hlt">clouds</span> between regions of warm and cool SSTs in simulations of the current climate.</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('https://ntrs.nasa.gov/search.jsp?R=20080044857&hterms=thermodynamics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dthermodynamics','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080044857&hterms=thermodynamics&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3Dthermodynamics"><span>Comparison of the MODIS Multilayer <span class="hlt">Cloud</span> Detection and Thermodynamic Phase Products with CALIPSO and <span class="hlt">Cloud</span>Sat</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Platnick, Steven; King, Michael D.; Wind, Gala; Holz, Robert E.; Ackerman, Steven A.; Nagle, Fred W.</p> <p>2008-01-01</p> <p>CALIPSO and <span class="hlt">Cloud</span>Sat, launched in June 2006, provide global active remote sensing measurements of <span class="hlt">clouds</span> and aerosols that can be used for validation of a variety of passive imager retrievals derived from instruments flying on the Aqua spacecraft and other A-Train platforms. The most recent processing effort for the MODIS Atmosphere Team, referred to as the "Collection 5" stream, includes a research-level multilayer <span class="hlt">cloud</span> detection algorithm that uses both thermodynamic phase information derived from a combination of solar and thermal emission bands to discriminate layers of different phases, as well as true layer separation discrimination using a moderately absorbing water vapor band. The multilayer detection algorithm is designed to provide a means of assessing the applicability of 1D <span class="hlt">cloud</span> models used in the MODIS <span class="hlt">cloud</span> optical and microphysical product retrieval, which are generated at a 1 h resolution. Using pixel-level collocations of MODIS Aqua, CALIOP, and <span class="hlt">Cloud</span>Sat radar measurements, we investigate the global performance of the thermodynamic phase and multilayer <span class="hlt">cloud</span> detection algorithms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014GeoRL..41.1681L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014GeoRL..41.1681L"><span>Observed linkages between the northern annular mode/North Atlantic Oscillation, <span class="hlt">cloud</span> incidence, and <span class="hlt">cloud</span> radiative forcing</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Li, Ying; Thompson, David W. J.; Huang, Yi; Zhang, Minghong</p> <p>2014-03-01</p> <p>The signature of the northern annular mode/North Atlantic Oscillation (NAM/NAO) in the vertical and horizontal distribution of tropospheric cloudiness is investigated in <span class="hlt">Cloud</span>Sat and CALIPSO data from June 2006 to April 2011. During the Northern Hemisphere winter, the positive polarity of the NAM/NAO is marked by increases in zonally averaged <span class="hlt">cloud</span> incidence north of ~60°N, decreases between ~25 and 50°N, and increases in the subtropics. The tripolar-like anomalies in <span class="hlt">cloud</span> incidence associated with the NAM/NAO are largest over the North Atlantic Ocean basin/Middle East and are physically consistent with the NAM/NAO-related anomalies in vertical motion. Importantly, the NAM/NAO-related anomalies in tropospheric <span class="hlt">cloud</span> incidence lead to significant top of atmosphere <span class="hlt">cloud</span> radiative forcing anomalies that are comparable in amplitude to those associated with the NAM/NAO-related temperature anomalies. The results provide observational evidence that the most prominent pattern of Northern Hemisphere climate variability is significantly linked to variations in <span class="hlt">cloud</span> radiative forcing. Implications for two-way feedback between extratropical dynamics and <span class="hlt">cloud</span> radiative forcing are discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/1996SPIE.2961...12H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/1996SPIE.2961...12H"><span>Strategies for <span class="hlt">cloud</span>-top phase determination: differentiation between thin cirrus <span class="hlt">clouds</span> and snow in manual (ground truth) analyses</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.</p> <p>1996-12-01</p> <p>Quantitative assessments on the performance of automated <span class="hlt">cloud</span> analysis algorithms require the creation of highly accurate, manual <span class="hlt">cloud</span>, no <span class="hlt">cloud</span> (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of <span class="hlt">cloud</span> detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated <span class="hlt">cloud</span> classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice <span class="hlt">cloud</span> tops while ensuring that inaccuracies in automated <span class="hlt">cloud</span> detection are not propagated into the results of the <span class="hlt">cloud</span> classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a <span class="hlt">cloud</span> and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus <span class="hlt">clouds</span> and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus <span class="hlt">clouds</span> and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice <span class="hlt">clouds</span> and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19900018922','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900018922"><span>Spectral absorption of marine stratocumulus <span class="hlt">clouds</span> derived from in situ <span class="hlt">cloud</span> radiation measurements</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.; Radke, Lawrence F.; Hobbs, Peter V.</p> <p>1990-01-01</p> <p>A multiwavelength scanning radiometer was used to measure the angular distribution of scattered radiation deep within a <span class="hlt">cloud</span> layer at discrete wavelengths between 0.5 and 2.3 microns. The relative angular distribution of the intensity field at each wavelength is used to determine the similarity parameter, and hence single scattering albedo, of the <span class="hlt">cloud</span> at that wavelength using the diffusion domain method. In addition to the spectral similarity parameter, the analysis provides a good estimate of the optical thickness of the <span class="hlt">cloud</span> beneath the aircraft. In addition to the radiation measurements, microphysical and thermodynamic measurements were obtained from which the expected similarity parameter spectrum was calculated using accepted values of the refractive index of liquid water and the transmission function of water vapor. An analysis is presented for the results obtained for a 50 km section of clean marine stratocumulus <span class="hlt">clouds</span> on 10 July 1987. These observations were obtained off the coast of California from the University of Washington Convair C-131A aircraft as part of the First ISCCP Regional Experiment (FIRE). A comparison of the experimentally-derived similarity parameter spectrum with that expected theoretically from the <span class="hlt">cloud</span> droplet size distribution measured simultaneously from the aircraft is presented. The measurements and theory are in very close agreement for this case of clean maritime <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20170007806','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20170007806"><span>Validation of Quasi-Invariant Ice <span class="hlt">Cloud</span> Radiative Quantities with MODIS Satellite-Based <span class="hlt">Cloud</span> Property Retrievals</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ding, Jiachen; Yang, Ping; Kattawar, George W.; King, Michael D.; Platnick, Steven; Meyer, Kerry G.</p> <p>2017-01-01</p> <p>Similarity relations applied to ice <span class="hlt">cloud</span> radiance calculations are theoretically analyzed and numerically validated. If t(1v) and t(1vg) are conserved where t is optical thickness, v the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice <span class="hlt">cloud</span> optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection5 (C5) and Collection 6 (C6) <span class="hlt">cloud</span> property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice <span class="hlt">cloud</span> optical thickness values are multiplied by their respective (1wg)factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice <span class="hlt">cloud</span> effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice <span class="hlt">cloud</span> phase function ratios. The MODIS C5 and C6 values of ice <span class="hlt">cloud</span> similarity parameter, defined as [(1w)(1(exp. 1/2)wg)]12, also tend to be similar.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080039632&hterms=humidification&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhumidification','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080039632&hterms=humidification&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D10%26Ntt%3Dhumidification"><span>The Apparent Bluing of Aerosols Near <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>Marshak, Alexander</p> <p>2008-01-01</p> <p>Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing <span class="hlt">cloud</span> cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist <span class="hlt">cloud</span> environment, but part comes from 3D <span class="hlt">cloud</span>-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. I describe a simple model that quantifies the enhanced illumination of <span class="hlt">cloud</span>-free columns in the vicinity of <span class="hlt">clouds</span> that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the <span class="hlt">cloud</span>-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby <span class="hlt">clouds</span>. This assumption leads to a larger increase of AOT for shorter wavelengths, or to a "bluing" of aerosols near <span class="hlt">clouds</span>. Examples from the MODIS observations that illustrate the apparent bluing of aerosols near <span class="hlt">clouds</span> will be discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19950045732&hterms=coverage&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dcoverage','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19950045732&hterms=coverage&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dcoverage"><span>Analysis of <span class="hlt">cloud</span> top height and <span class="hlt">cloud</span> coverage from satellites using the O2 A and B bands</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Kuze, Akihiko; Chance, Kelly V.</p> <p>1994-01-01</p> <p><span class="hlt">Cloud</span> height and <span class="hlt">cloud</span> coverage detection are important for total ozone retrieval using ultraviolet and visible scattered light. Use of the O2 A and B bands, around 761 and 687 nm, by a satellite-borne instrument of moderately high spectral resolution viewing in the nadir makes it possible to detect <span class="hlt">cloud</span> top height and related parameters, including fractional coverage. The measured values of a satellite-borne spectrometer are convolutions of the instrument slit function and the atmospheric transmittance between <span class="hlt">cloud</span> top and satellite. Studies here determine the optical depth between a satellite orbit and the Earth or <span class="hlt">cloud</span> top height to high accuracy using FASCODE 3. <span class="hlt">Cloud</span> top height and a <span class="hlt">cloud</span> coverage parameter are determined by least squares fitting to calculated radiance ratios in the oxygen bands. A grid search method is used to search the parameter space of <span class="hlt">cloud</span> top height and the coverage parameter to minimize an appropriate sum of squares of deviations. For this search, nonlinearity of the atmospheric transmittance (i.e., leverage based on varying amounts of saturation in the absorption spectrum) is important for distinguishing between <span class="hlt">cloud</span> top height and fractional coverage. Using the above-mentioned method, an operational <span class="hlt">cloud</span> detection algorithm which uses minimal computation time can be implemented.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19860052995&hterms=nemesis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dnemesis','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19860052995&hterms=nemesis&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D20%26Ntt%3Dnemesis"><span>Dynamical evolution of the Oort <span class="hlt">cloud</span></span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Weissman, P. R.</p> <p>1985-01-01</p> <p>New studies of the dynamical evolution of cometary orbits in the Oort <span class="hlt">cloud</span> are made using a revised version of Weissman's (1982) Monte Carlo simulation model, which more accurately mimics the perturbation of comets by the giant planets. It is shown that perturbations by Saturn and Jupiter provide a substantial barrier to the diffusion of cometary perihelia into the inner solar system. Perturbations by Uranus and Neptune are rarely great enough to remove comets from the Oort <span class="hlt">cloud</span>, but do serve to scatter the comets in the <span class="hlt">cloud</span> in initial energy. The new model gives a population of 1.8 to 2.1 x 10 to the 12th comets for the present-day Oort <span class="hlt">cloud</span>, and a mass of 7 to 8 earth masses. Perturbation of the Oort <span class="hlt">cloud</span> by giant molecular <span class="hlt">clouds</span> in the galaxy is discussed, as is evidence for a massive 'inner Oort <span class="hlt">cloud</span>' internal to the observed one. The possibility of an unseen solar companion orbiting in the Oort <span class="hlt">cloud</span> and causing periodic comet showers is shown to be dynamically plausible but unlikely, based on the observed cratering rate on the earth and moon.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3481437','PMC'); return false;" href="https://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=3481437"><span>Atlas2 <span class="hlt">Cloud</span>: a framework for personal genome analysis in the <span class="hlt">cloud</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></p> <p>2012-01-01</p> <p>Background Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the <span class="hlt">cloud</span> computing and Software-as-a-Service (SaaS) technologies can help address these issues. Results We successfully enabled the Atlas2 <span class="hlt">Cloud</span> pipeline for personal genome analysis on two different <span class="hlt">cloud</span> service platforms: a community <span class="hlt">cloud</span> via the Genboree Workbench, and a commercial <span class="hlt">cloud</span> via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. Conclusions We find that providing a web interface and an optimized pipeline clearly facilitates usage of <span class="hlt">cloud</span> computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms. PMID:23134663</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/23134663','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/23134663"><span>Atlas2 <span class="hlt">Cloud</span>: a framework for personal genome analysis 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>Evani, Uday S; Challis, Danny; Yu, Jin; Jackson, Andrew R; Paithankar, Sameer; Bainbridge, Matthew N; Jakkamsetti, Adinarayana; Pham, Peter; Coarfa, Cristian; Milosavljevic, Aleksandar; Yu, Fuli</p> <p>2012-01-01</p> <p>Until recently, sequencing has primarily been carried out in large genome centers which have invested heavily in developing the computational infrastructure that enables genomic sequence analysis. The recent advancements in next generation sequencing (NGS) have led to a wide dissemination of sequencing technologies and data, to highly diverse research groups. It is expected that clinical sequencing will become part of diagnostic routines shortly. However, limited accessibility to computational infrastructure and high quality bioinformatic tools, and the demand for personnel skilled in data analysis and interpretation remains a serious bottleneck. To this end, the <span class="hlt">cloud</span> computing and Software-as-a-Service (SaaS) technologies can help address these issues. We successfully enabled the Atlas2 <span class="hlt">Cloud</span> pipeline for personal genome analysis on two different <span class="hlt">cloud</span> service platforms: a community <span class="hlt">cloud</span> via the Genboree Workbench, and a commercial <span class="hlt">cloud</span> via the Amazon Web Services using Software-as-a-Service model. We report a case study of personal genome analysis using our Atlas2 Genboree pipeline. We also outline a detailed cost structure for running Atlas2 Amazon on whole exome capture data, providing cost projections in terms of storage, compute and I/O when running Atlas2 Amazon on a large data set. We find that providing a web interface and an optimized pipeline clearly facilitates usage of <span class="hlt">cloud</span> computing for personal genome analysis, but for it to be routinely used for large scale projects there needs to be a paradigm shift in the way we develop tools, in standard operating procedures, and in funding mechanisms.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2014PhDT........39D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2014PhDT........39D"><span>Comparison of convective <span class="hlt">clouds</span> observed by spaceborne W-band radar and simulated by <span class="hlt">cloud</span>-resolving atmospheric models</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Dodson, Jason B.</p> <p></p> <p>Deep convective <span class="hlt">clouds</span> (DCCs) play an important role in regulating global climate through vertical mass flux, vertical water transport, and radiation. For general circulation models (GCMs) to simulate the global climate realistically, they must simulate DCCs realistically. GCMs have traditionally used cumulus parameterizations (CPs). Much recent research has shown that multiple persistent unrealistic behaviors in GCMs are related to limitations of CPs. Two alternatives to CPs exist: the global <span class="hlt">cloud</span>-resolving model (GCRM), and the multiscale modeling framework (MMF). Both can directly simulate the coarser features of DCCs because of their multi-kilometer horizontal resolutions, and can simulate large-scale meteorological processes more realistically than GCMs. However, the question of realistic behavior of simulated DCCs remains. How closely do simulated DCCs resemble observed DCCs? In this study I examine the behavior of DCCs in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and Superparameterized Community Atmospheric Model (SP-CAM), the latter with both single-moment and double-moment microphysics. I place particular emphasis on the relationship between <span class="hlt">cloud</span> vertical structure and convective environment. I also emphasize the transition between shallow <span class="hlt">clouds</span> and mature DCCs. The spatial domains used are the tropical oceans and the contiguous United States (CONUS), the latter of which produces frequent vigorous convection during the summer. <span class="hlt">Cloud</span>Sat is used to observe DCCs, and A-Train and reanalysis data are used to represent the large-scale environment in which the <span class="hlt">clouds</span> form. The <span class="hlt">Cloud</span>Sat <span class="hlt">cloud</span> mask and radar reflectivity profiles for CONUS cumuliform <span class="hlt">clouds</span> (defined as <span class="hlt">clouds</span> with a base within the planetary boundary layer) during boreal summer are first averaged and compared. Both NICAM and SP-CAM greatly underestimate the vertical growth of cumuliform <span class="hlt">clouds</span>. Then they are sorted by three large-scale environmental variables: total preciptable</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eosweb.larc.nasa.gov/project/airmspi/airmspi_oracles_l2_cloud_droplet_v1','SCIGOV-ASDC'); return false;" href="https://eosweb.larc.nasa.gov/project/airmspi/airmspi_oracles_l2_cloud_droplet_v1"><span>AirMSPI ORACLES <span class="hlt">Cloud</span> Droplet Data V001</span></a></p> <p><a target="_blank" href="http://eosweb.larc.nasa.gov/">Atmospheric Science Data Center </a></p> <p></p> <p>2018-05-05</p> <p>AirMSPI_ORACLES_<span class="hlt">Cloud_Droplet_Size_and_Cloud</span>_Optical_Depth L2 Derived Geophysical Parameters ... Order: Earthdata Search Parameters:  <span class="hlt">Cloud</span> Optical Depth <span class="hlt">Cloud</span> Droplet Effective Radius <span class="hlt">Cloud</span> Droplet ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=cloud+AND+computing&id=EJ977072','ERIC'); return false;" href="https://eric.ed.gov/?q=cloud+AND+computing&id=EJ977072"><span>The Basics of <span class="hlt">Cloud</span> Computing</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>Kaestner, Rich</p> <p>2012-01-01</p> <p>Most school business officials have heard the term "<span class="hlt">cloud</span> computing" bandied about and may have some idea of what the term means. In fact, they likely already leverage a <span class="hlt">cloud</span>-computing solution somewhere within their district. But what does <span class="hlt">cloud</span> computing really mean? This brief article puts a bit of definition behind the term and helps one…</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA00058.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA00058.html"><span>Neptune <span class="hlt">Clouds</span> Showing Vertical Relief</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>1996-01-29</p> <p>NASA's Voyager 2 high resolution color image, taken 2 hours before closest approach, provides obvious evidence of vertical relief in Neptune's bright <span class="hlt">cloud</span> streaks. These <span class="hlt">clouds</span> were observed at a latitude of 29 degrees north near Neptune's east terminator. The linear <span class="hlt">cloud</span> forms are stretched approximately along lines of constant latitude and the sun is toward the lower left. The bright sides of the <span class="hlt">clouds</span> which face the sun are brighter than the surrounding <span class="hlt">cloud</span> deck because they are more directly exposed to the sun. Shadows can be seen on the side opposite the sun. These shadows are less distinct at short wavelengths (violet filter) and more distinct at long wavelengths (orange filter). This can be understood if the underlying <span class="hlt">cloud</span> deck on which the shadow is cast is at a relatively great depth, in which case scattering by molecules in the overlying atmosphere will diffuse light into the shadow. Because molecules scatter blue light much more efficiently than red light, the shadows will be darkest at the longest (reddest) wavelengths, and will appear blue under white light illumination. The resolution of this image is 11 kilometers (6.8 miles per pixel) and the range is only 157,000 kilometers (98,000 miles). The width of the <span class="hlt">cloud</span> streaks range from 50 to 200 kilometers (31 to 124 miles), and their shadow widths range from 30 to 50 kilometers (18 to 31 miles). <span class="hlt">Cloud</span> heights appear to be of the order of 50 kilometers (31 miles). This corresponds to 2 scale heights. http://photojournal.jpl.nasa.gov/catalog/PIA00058</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19990094167&hterms=Influence+clouds+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DInfluence%2Bclouds%2Bclimate','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19990094167&hterms=Influence+clouds+climate&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D60%26Ntt%3DInfluence%2Bclouds%2Bclimate"><span>Mesoscale to Synoptic Scale <span class="hlt">Cloud</span> Variability</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Rossow, William B.</p> <p>1998-01-01</p> <p>The atmospheric circulation and its interaction with the oceanic circulation involve non-linear and non-local exchanges of energy and water over a very large range of space and time scales. These exchanges are revealed, in part, by the related variations of <span class="hlt">clouds</span>, which occur on a similar range of scales as the atmospheric motions that produce them. Collection of comprehensive measurements of the properties of the atmosphere, <span class="hlt">clouds</span> and surface allows for diagnosis of some of these exchanges. The use of a multi-satellite-network approach by the International Satellite <span class="hlt">Cloud</span> Climatology Project (ISCCP) comes closest to providing complete coverage of the relevant range space and time scales over which the <span class="hlt">clouds</span>, atmosphere and ocean vary. A nearly 15-yr dataset is now available that covers the range from 3 hr and 30 km to decade and planetary. This paper considers three topics: (1) <span class="hlt">cloud</span> variations at the smallest scales and how they may influence radiation-<span class="hlt">cloud</span> interactions, and (2) <span class="hlt">cloud</span> variations at "moderate" scales and how they may cause natural climate variability, and (3) <span class="hlt">cloud</span> variations at the largest scales and how they affect the climate. The emphasis in this discussion is on the more mature subject of <span class="hlt">cloud</span>-radiation interactions. There is now a need to begin similar detailed diagnostic studies of water exchange processes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20020014371&hterms=images+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dimages%2BMODIS','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20020014371&hterms=images+MODIS&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dimages%2BMODIS"><span>New 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; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas</p> <p>2001-01-01</p> <p>The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of <span class="hlt">cloud</span> properties using MODIS data, focusing primarily on the MODIS <span class="hlt">cloud</span> mask used to distinguish <span class="hlt">clouds</span>, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of <span class="hlt">cloud</span> optical properties, especially <span class="hlt">cloud</span> optical thickness and effective radius of water drops and ice crystals. Additional properties of <span class="hlt">clouds</span> derived from multispectral thermal infrared measurements, especially <span class="hlt">cloud</span> top pressure and emissivity, will also be described. Results will be presented of MODIS <span class="hlt">cloud</span> properties both over the land and over the ocean, showing the consistency in <span class="hlt">cloud</span> retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.</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 types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] 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 <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 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 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('https://www.osti.gov/biblio/22654383-fast-molecular-cloud-destruction-requires-fast-cloud-formation','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/22654383-fast-molecular-cloud-destruction-requires-fast-cloud-formation"><span>Fast Molecular <span class="hlt">Cloud</span> Destruction Requires Fast <span class="hlt">Cloud</span> Formation</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>Mac Low, Mordecai-Mark; Burkert, Andreas; Ibáñez-Mejía, Juan C., E-mail: mordecai@amnh.org, E-mail: burkert@usm.lmu.de, E-mail: ibanez@ph1.uni-koeln.de</p> <p></p> <p>A large fraction of the gas in the Galaxy is cold, dense, and molecular. If all this gas collapsed under the influence of gravity and formed stars in a local free-fall time, the star formation rate in the Galaxy would exceed that observed by more than an order of magnitude. Other star-forming galaxies behave similarly. Yet, observations and simulations both suggest that the molecular gas is indeed gravitationally collapsing, albeit hierarchically. Prompt stellar feedback offers a potential solution to the low observed star formation rate if it quickly disrupts star-forming <span class="hlt">clouds</span> during gravitational collapse. However, this requires that molecular cloudsmore » must be short-lived objects, raising the question of how so much gas can be observed in the molecular phase. This can occur only if molecular <span class="hlt">clouds</span> form as quickly as they are destroyed, maintaining a global equilibrium fraction of dense gas. We therefore examine <span class="hlt">cloud</span> formation timescales. We first demonstrate that supernova and superbubble sweeping cannot produce dense gas at the rate required to match the <span class="hlt">cloud</span> destruction rate. On the other hand, Toomre gravitational instability can reach the required production rate. We thus argue that, although dense, star-forming gas may last only around a single global free-fall time; the dense gas in star-forming galaxies can globally exist in a state of dynamic equilibrium between formation by gravitational instability and disruption by stellar feedback. At redshift z ≳ 2, the Toomre instability timescale decreases, resulting in a prediction of higher molecular gas fractions at early times, in agreement with the observations.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29358387','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29358387"><span>Precipitation formation from orographic <span class="hlt">cloud</span> seeding.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>French, Jeffrey R; Friedrich, Katja; Tessendorf, Sarah A; Rauber, Robert M; Geerts, Bart; Rasmussen, Roy M; Xue, Lulin; Kunkel, Melvin L; Blestrud, Derek R</p> <p>2018-02-06</p> <p>Throughout the western United States and other semiarid mountainous regions across the globe, water supplies are fed primarily through the melting of snowpack. Growing populations place higher demands on water, while warmer winters and earlier springs reduce its supply. Water managers are tantalized by the prospect of <span class="hlt">cloud</span> seeding as a way to increase winter snowfall, thereby shifting the balance between water supply and demand. Little direct scientific evidence exists that confirms even the basic physical hypothesis upon which <span class="hlt">cloud</span> seeding relies. The intent of glaciogenic seeding of orographic <span class="hlt">clouds</span> is to introduce aerosol into a <span class="hlt">cloud</span> to alter the natural development of <span class="hlt">cloud</span> particles and enhance wintertime precipitation in a targeted region. The hypothesized chain of events begins with the introduction of silver iodide aerosol into <span class="hlt">cloud</span> regions containing supercooled liquid water, leading to the nucleation of ice crystals, followed by ice particle growth to sizes sufficiently large such that snow falls to the ground. Despite numerous experiments spanning several decades, no direct observations of this process exist. Here, measurements from radars and aircraft-mounted <span class="hlt">cloud</span> physics probes are presented that together show the initiation, growth, and fallout to the mountain surface of ice crystals resulting from glaciogenic seeding. These data, by themselves, do not address the question of <span class="hlt">cloud</span> seeding efficacy, but rather form a critical set of observations necessary for such investigations. These observations are unambiguous and provide details of the physical chain of events following the introduction of glaciogenic <span class="hlt">cloud</span> seeding aerosol into supercooled liquid orographic <span class="hlt">clouds</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_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('https://images.nasa.gov/#/details-s44-77-074.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-s44-77-074.html"><span>Volcanic Plume from Mt. Unzen, Dust <span class="hlt">Cloud</span>, <span class="hlt">cloud</span> Vortices</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>1991-12-01</p> <p>Stable, south flowing air over the western Pacific Ocean (26.0N, 131.0E) is disturbed by islands south of Korea, resulting in sinuous <span class="hlt">clouds</span> known as von Karman vortices. The smoke plume from Japan's Mount Unzen Volcano on Kyushu, is visible just west of the large <span class="hlt">cloud</span> mass and extending southward. A very large, purple tinged dust pall, originating in Mongolia, can be seen on the Earth's Limb, covering eastern China and extending into the East China Sea.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AMT....10.2129B','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AMT....10.2129B"><span>Thin ice <span class="hlt">clouds</span> in the Arctic: <span class="hlt">cloud</span> optical depth and particle size retrieved from ground-based thermal infrared radiometry</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; Turner, David D.; Eloranta, Edwin W.</p> <p>2017-06-01</p> <p>Multiband downwelling thermal measurements of zenith sky radiance, along with <span class="hlt">cloud</span> boundary heights, were used in a retrieval algorithm to estimate <span class="hlt">cloud</span> optical depth and effective particle diameter of thin ice <span class="hlt">clouds</span> in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice <span class="hlt">clouds</span> cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several <span class="hlt">cloud</span> parameters including optical depth, effective particle diameter and shape, water vapor content, <span class="hlt">cloud</span> geometric thickness and <span class="hlt">cloud</span> base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, <span class="hlt">cloud</span> optical depth up to a maximum value of 2.6 and to separate thin ice <span class="hlt">clouds</span> into two classes: (1) TIC1 <span class="hlt">clouds</span> characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 <span class="hlt">clouds</span> characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave <span class="hlt">Cloud</span> Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R2 = 0.95) for <span class="hlt">cloud</span> optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 <span class="hlt">clouds</span>. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.</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> types, 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('http://adsabs.harvard.edu/abs/2017MS%26E..263d2060S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MS%26E..263d2060S"><span>Advanced <span class="hlt">cloud</span> fault tolerance system</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Sumangali, K.; Benny, Niketa</p> <p>2017-11-01</p> <p><span class="hlt">Cloud</span> computing has become a prevalent on-demand service on the internet to store, manage and process data. A pitfall that accompanies <span class="hlt">cloud</span> computing is the failures that can be encountered in the <span class="hlt">cloud</span>. To overcome these failures, we require a fault tolerance mechanism to abstract faults from users. We have proposed a fault tolerant architecture, which is a combination of proactive and reactive fault tolerance. This architecture essentially increases the reliability and the availability of the <span class="hlt">cloud</span>. In the future, we would like to compare evaluations of our proposed architecture with existing architectures and further improve it.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2016ACP....16.8643J','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2016ACP....16.8643J"><span>Aerosols, <span class="hlt">clouds</span>, and precipitation in the North Atlantic trades observed during the Barbados aerosol <span class="hlt">cloud</span> experiment - Part 1: Distributions and variability</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Jung, Eunsil; Albrecht, Bruce A.; Feingold, Graham; Jonsson, Haflidi H.; Chuang, Patrick; Donaher, Shaunna L.</p> <p>2016-07-01</p> <p>Shallow marine cumulus <span class="hlt">clouds</span> are by far the most frequently observed <span class="hlt">cloud</span> type over the Earth's oceans; but they are poorly understood and have not been investigated as extensively as stratocumulus <span class="hlt">clouds</span>. This study describes and discusses the properties and variations of aerosol, <span class="hlt">cloud</span>, and precipitation associated with shallow marine cumulus <span class="hlt">clouds</span> observed in the North Atlantic trades during a field campaign (Barbados Aerosol <span class="hlt">Cloud</span> Experiment- BACEX, March-April 2010), which took place off Barbados where African dust periodically affects the region. The principal observing platform was the Center for Interdisciplinary Remotely Piloted Aircraft Studies (CIRPAS) Twin Otter (TO) research aircraft, which was equipped with standard meteorological instruments, a zenith pointing <span class="hlt">cloud</span> radar and probes that measured aerosol, <span class="hlt">cloud</span>, and precipitation characteristics.The temporal variation and vertical distribution of aerosols observed from the 15 flights, which included the most intense African dust event during all of 2010 in Barbados, showed a wide range of aerosol conditions. During dusty periods, aerosol concentrations increased substantially in the size range between 0.5 and 10 µm (diameter), particles that are large enough to be effective giant <span class="hlt">cloud</span> condensation nuclei (CCN). The 10-day back trajectories showed three distinct air masses with distinct vertical structures associated with air masses originating in the Atlantic (typical maritime air mass with relatively low aerosol concentrations in the marine boundary layer), Africa (Saharan air layer), and mid-latitudes (continental pollution plumes). Despite the large differences in the total mass loading and the origin of the aerosols, the overall shapes of the aerosol particle size distributions were consistent, with the exception of the transition period.The TO was able to sample many <span class="hlt">clouds</span> at various phases of growth. Maximum <span class="hlt">cloud</span> depth observed was less than ˜ 3 km, while most <span class="hlt">clouds</span> were less than 1 km</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017nova.pres.3040K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017nova.pres.3040K"><span>Star-Forming <span class="hlt">Clouds</span> Feed, Churn, and Fall</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>2017-12-01</p> <p>Molecular <span class="hlt">clouds</span>, the birthplaces of stars in galaxies throughout the universe, are complicated and dynamic environments. A new series of simulations has explored how these <span class="hlt">clouds</span> form, grow, and collapse over their lifetimes.This composite image shows part of the Taurus Molecular <span class="hlt">Cloud</span>. [ESO/APEX (MPIfR/ESO/OSO)/A. Hacar et al./Digitized Sky Survey]Stellar BirthplacesMolecular <span class="hlt">clouds</span> form out of the matter in between stars, evolving through constant interactions with their turbulent environments. These interactions taking the form of accretion flows and surface forces, while gravity, turbulence, and magnetic fields interplay are thought to drive the properties and evolution of the <span class="hlt">clouds</span>.Our understanding of the details of this process, however, remains fuzzy. How does mass accretion affect these <span class="hlt">clouds</span> as they evolve? What happens when nearby supernova explosions blast the outsides of the <span class="hlt">clouds</span>? What makes the <span class="hlt">clouds</span> churn, producing the motion within them that prevents them from collapsing? The answers to these questions can tellus about the gas distributed throughout galaxies, revealing information about the environments in which stars form.A still from the simulation results showing the broader population of molecular <span class="hlt">clouds</span> that formed in the authors simulations, as well as zoom-in panels of three low-mass <span class="hlt">clouds</span> tracked in high resolution. [Ibez-Meja et al. 2017]Models of TurbulenceIn a new study led by Juan Ibez-Meja (MPI Garching and Universities of Heidelberg and Cologne in Germany, and American Museum of Natural History), scientists have now explored these questions using a series of three-dimensional simulations of a population of molecular <span class="hlt">clouds</span> forming and evolving in the turbulent interstellar medium.The simulations take into account a whole host of physics, including the effects of nearby supernova explosions, self-gravitation, magnetic fields, diffuse heating, and radiative cooling. After looking at the behavior of the broader population of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20080045463&hterms=Ackerman&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D40%26Ntt%3DAckerman','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20080045463&hterms=Ackerman&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAuthor-Name%26N%3D0%26No%3D40%26Ntt%3DAckerman"><span>Observing Ice in <span class="hlt">Clouds</span> from Space</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ackerman, S.; Star, D. O'C.; Skofronick-Jackson, G.; Evans, F.; Wang, J. R.; Norris, P.; daSilva, A.; Soden, B.</p> <p>2006-01-01</p> <p>There are many satellite observations of <span class="hlt">cloud</span> top properties and the liquid and rain content of <span class="hlt">clouds</span>, however, we do not yet quantitatively understand the processes that control the water budget of the upper troposphere where ice is the predominant phase, and how these processes are linked to precipitation processes and the radiative energy budget. The ice in <span class="hlt">clouds</span> in the upper troposphere either melts into rain or is detrained, and persists, as cirrus <span class="hlt">clouds</span> affecting the hydrological and energy cycle, respectively. Fully modeling the Earth's climate and improving weather and climate forecasts requires accurate satellite measurements of various <span class="hlt">cloud</span> properties at the temporal and spatial scales of <span class="hlt">cloud</span> processes. These properties include <span class="hlt">cloud</span> horizontal and vertical structure, <span class="hlt">cloud</span> water content and some measure of particle sizes and shapes. The uncertainty in knowledge of these ice characteristics is reflected in the large discrepancies in model simulations of the upper tropospheric water budget. Model simulations are sensitive to the partition of ice between precipitation and outflow processes, i.e., to the parameterization of ice <span class="hlt">clouds</span> and ice processes. One barrier to achieving accurate global ice <span class="hlt">cloud</span> properties is the lack of adequate observations at millimeter and submillimeter wavelengths (183-874 GHz). Recent advances in instrumentation have allowed for the development and implementation of an airborne submillimeter-wave radiometer. The brightness temperatures at these frequencies are especially sensitive to cirrus ice particle sizes (because they are comparable to the wavelength). This allows for more accurate ice water path estimates when multiple channels are used to probe into the <span class="hlt">cloud</span> layers. Further, submillimeter wavelengths offer simplicity in the retrieval algorithms because they do not probe into the liquid and near surface portions of <span class="hlt">clouds</span>, thus requiring only one term of the radiative transfer equation (ice scattering) to relate</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20050156910','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20050156910"><span>Apperception of <span class="hlt">Clouds</span> in AIRS Data</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Huang, Hung-Lung; Smith, William L.</p> <p>2005-01-01</p> <p>Our capacity to simulate the radiative characteristics of the Earth system has advanced greatly over the past decade. However, new space based measurements show that idealized simulations might not adequately represent the complexity of nature. For example, AIRS simulated multi-layer <span class="hlt">cloud</span> clearing research provides an excellent groundwork for early Atmospheric Infra-Red Sounder (AIRS) operational <span class="hlt">cloud</span> clearing and atmospheric profile retrieval. However, it doesn't reflect the complicated reality of <span class="hlt">clouds</span> over land and coastal areas. Thus far, operational AIRS/AMSU (Advanced Microwave Sounding Unit) <span class="hlt">cloud</span> clearing is not only of low yield but also of unsatisfying quality. This is not an argument for avoiding this challenging task, rather a powerful argument for exploring other synergistic approaches, and for adapting these strategies toward improving both indirect and direct use of cloudy infrared sounding data. Ample evidence is shown in this paper that the indirect use of cloudy sounding data by way of <span class="hlt">cloud</span> clearing is sub-optimal for data assimilation. Improvements are needed in quality control, retrieval yield, and overall <span class="hlt">cloud</span> clearing retrieval performance. For example, <span class="hlt">cloud</span> clearing over land, especially over the desert surface, has led to much degraded retrieval quality and often a very low yield of quality controlled <span class="hlt">cloud</span> cleared radiances. If these indirect <span class="hlt">cloud</span> cleared radiances are instead to be directly assimilated into NWP models, great caution must be used. Our limited and preliminary <span class="hlt">cloud</span> clearing results from AIRS/AMSU (with the use of MODIS data) and an AIRS/MODIS synergistic approach have, however, shown that higher spatial resolution multispectral imagery data can provide much needed quality control of the AIRS/AMSU <span class="hlt">cloud</span> clearing retrieval. When AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) are used synergistically, a higher spatial resolution over difficult terrain (especially desert areas) can be achieved and with a</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20010050107&hterms=condensation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dcondensation','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20010050107&hterms=condensation&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dcondensation"><span>Precipitating Condensation <span class="hlt">Clouds</span> in Substellar Atmospheres</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Ackerman, Andrew S.; Marley, Mark S.; Gore, Warren J. (Technical Monitor)</p> <p>2000-01-01</p> <p>We present a method to calculate vertical profiles of particle size distributions in condensation <span class="hlt">clouds</span> of giant planets and brown dwarfs. The method assumes a balance between turbulent diffusion and precipitation in horizontally uniform <span class="hlt">cloud</span> decks. Calculations for the Jovian ammonia <span class="hlt">cloud</span> are compared with previous methods. An adjustable parameter describing the efficiency of precipitation allows the new model to span the range of predictions from previous models. Calculations for the Jovian ammonia <span class="hlt">cloud</span> are found to be consistent with observational constraints. Example calculations are provided for water, silicate, and iron <span class="hlt">clouds</span> on brown dwarfs and on a cool extrasolar giant planet.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19910001215','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19910001215"><span>Measurements of the light-absorbing material inside <span class="hlt">cloud</span> droplets and its effect on <span class="hlt">cloud</span> albedo</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Twohy, C. H.; Clarke, A. D.; Warren, Stephen G.; Radke, L. F.; Charleson, R. J.</p> <p>1990-01-01</p> <p>Most of the measurements of light-absorbing aerosol particles made previously have been in non-cloudy air and therefore provide no insight into aerosol effects on <span class="hlt">cloud</span> properties. Here, researchers describe an experiment designed to measure light absorption exclusively due to substances inside <span class="hlt">cloud</span> droplets, compare the results to related light absorption measurements, and evaluate possible effects on the albedo of <span class="hlt">clouds</span>. The results of this study validate those of Twomey and Cocks and show that the measured levels of light-absorbing material are negligible for the radiative properties of realistic <span class="hlt">clouds</span>. For the measured <span class="hlt">clouds</span>, which appear to have been moderately polluted, the amount of elemental carbon (EC) present was insufficient to affect albedo. Much higher contaminant levels or much larger droplets than those measured would be necessary to significantly alter the radiative properties. The effect of the concentrations of EC actually measured on the albedo of snow, however, would be much more pronounced since, in contrast to <span class="hlt">clouds</span>, snowpacks are usually optically semi-infinite and have large particle sizes.</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 identify 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> <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 type 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 types 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('https://www.osti.gov/servlets/purl/1377405','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1377405"><span><span class="hlt">Cloud</span> Type Classification (cldtype) Value-Added Product</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>Flynn, Donna; Shi, Yan; Lim, K-S</p> <p></p> <p>The <span class="hlt">Cloud</span> Type (cldtype) value-added product (VAP) provides an automated <span class="hlt">cloud</span> type classification based on macrophysical quantities derived from vertically pointing lidar and radar. Up to 10 layers of <span class="hlt">clouds</span> are classified into seven <span class="hlt">cloud</span> types based on predetermined and site-specific thresholds of <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> boundaries obtained from the Active Remotely Sensed <span class="hlt">Cloud</span> Location (ARSCL) and Surface Meteorological Systems (MET) data. Rainmore » rates from MET are used to determine when radar signal attenuation precludes accurate <span class="hlt">cloud</span> 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 <span class="hlt">clouds</span>. 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 <span class="hlt">clouds</span> of interest for a variety of users.« less</p> </li> <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 types 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('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 type 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/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 identified</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015JGRD..120.5524M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015JGRD..120.5524M"><span>Simultaneously inferring above-<span class="hlt">cloud</span> absorbing aerosol optical thickness and underlying liquid phase <span class="hlt">cloud</span> optical and microphysical properties using MODIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Meyer, Kerry; Platnick, Steven; Zhang, Zhibo</p> <p>2015-06-01</p> <p>The regional haze over the southeast (SE) Atlantic Ocean induced by biomass burning in southern Africa can be problematic for passive imager-based retrievals of the underlying quasi-permanent marine boundary layer (MBL) <span class="hlt">clouds</span> and for estimates of top-of-atmosphere (TOA) aerosol direct radiative effect (DRE). Here an algorithm is introduced to simultaneously retrieve above-<span class="hlt">cloud</span> aerosol optical thickness (AOT), the <span class="hlt">cloud</span> optical thickness (COT), and <span class="hlt">cloud</span> effective particle radius (CER) of the underlying MBL <span class="hlt">clouds</span> while also providing pixel-level estimates of retrieval uncertainty. This approach utilizes reflectance measurements at six Moderate Resolution Imaging Spectroradiometer (MODIS) channels from the visible to the shortwave infrared. Retrievals are run under two aerosol model assumptions on 8 years (2006-2013) of June-October Aqua MODIS data over the SE Atlantic, from which a regional <span class="hlt">cloud</span> and above-<span class="hlt">cloud</span> aerosol climatology is produced. The <span class="hlt">cloud</span> retrieval methodology is shown to yield COT and CER consistent with those from the MODIS operational <span class="hlt">cloud</span> product (MOD06) when forcing AOT to zero, while the full COT-CER-AOT retrievals that account for the above-<span class="hlt">cloud</span> aerosol attenuation increase regional monthly mean COT and CER by up to 9% and 2%, respectively. Retrieved AOT is roughly 3 to 5 times larger than the collocated 532 nm <span class="hlt">Cloud</span>-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals, though closer agreement is observed with the CALIOP 1064 nm retrievals, a result consistent with previous case study analyses. Regional cloudy-sky above-<span class="hlt">cloud</span> aerosol DRE calculations are also performed that illustrate the importance of the aerosol model assumption and underlying <span class="hlt">cloud</span> retrievals.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1340540','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1340540"><span>Retrieval of Boundary Layer 3D <span class="hlt">Cloud</span> Properties Using Scanning <span class="hlt">Cloud</span> Radar and 3D Radiative Transfer</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>Marchand, Roger</p> <p></p> <p>Retrievals of <span class="hlt">cloud</span> optical and microphysical properties for boundary layer <span class="hlt">clouds</span>, including those widely used by ASR investigators, frequently assume that <span class="hlt">clouds</span> are sufficiently horizontally homogeneous that scattering and absorption (at all wavelengths) can be treated using one dimensional (1D) radiative transfer, and that differences in the field-of-view of different sensors are unimportant. Unfortunately, most boundary layer <span class="hlt">clouds</span> are far from horizontally homogeneous, and numerous theoretical and observational studies show that the assumption of horizontal homogeneity leads to significant errors. The introduction of scanning <span class="hlt">cloud</span> and precipitation radars at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) programmore » sites presents opportunities to move beyond the horizontally homogeneous assumption. The primary objective of this project was to develop a 3D retrieval for warm-phase (liquid only) boundary layer <span class="hlt">cloud</span> microphysical properties, and to assess errors in current 1D (non-scanning) approaches. Specific research activities also involved examination of the diurnal cycle of hydrometeors as viewed by ARM <span class="hlt">cloud</span> radar, and continued assessment of precipitation impacts on retrievals of <span class="hlt">cloud</span> liquid water path using passive microwaves.« less</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 types 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://hdl.handle.net/2060/19900010097','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19900010097"><span>Analytical optical scattering in <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>Phanord, Dieudonne D.</p> <p>1989-01-01</p> <p>An analytical optical model for scattering of light due to lightning by <span class="hlt">clouds</span> of different geometry is being developed. The self-consistent approach and the equivalent medium concept of Twersky was used to treat the case corresponding to outside illumination. Thus, the resulting multiple scattering problem is transformed with the knowledge of the bulk parameters, into scattering by a single obstacle in isolation. Based on the size parameter of a typical water droplet as compared to the incident wave length, the problem for the single scatterer equivalent to the distribution of <span class="hlt">cloud</span> particles can be solved either by Mie or Rayleigh scattering theory. The super computing code of Wiscombe can be used immediately to produce results that can be compared to the Monte Carlo computer simulation for outside incidence. A fairly reasonable inverse approach using the solution of the outside illumination case was proposed to model analytically the situation for point sources located inside the thick optical <span class="hlt">cloud</span>. Its mathematical details are still being investigated. When finished, it will provide scientists an enhanced capability to study more realistic <span class="hlt">clouds</span>. For testing purposes, the direct approach to the inside illumination of <span class="hlt">clouds</span> by lightning is under consideration. Presently, an analytical solution for the cubic <span class="hlt">cloud</span> will soon be obtained. For cylindrical or spherical <span class="hlt">clouds</span>, preliminary results are needed for scattering by bounded obstacles above or below a penetrable surface interface.</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://images.nasa.gov/#/details-PIA20516.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA20516.html"><span>Send in the <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>2017-01-02</p> <p>Floating high above the hydrocarbon lakes, wispy <span class="hlt">clouds</span> have finally started to return to Titan's northern latitudes <span class="hlt">Clouds</span> like these disappeared from Titan's (3,200 miles or 5,150 kilometers across) northern reaches for several years (from about 2010 to 2014). Now they have returned, but in far smaller numbers than expected. Since <span class="hlt">clouds</span> can quickly appear and disappear, Cassini scientists regularly monitor the large moon, in the hopes of observing <span class="hlt">cloud</span> activity. They are especially interested in comparing these observations to predictions of how <span class="hlt">cloud</span> cover should change with Saturn's seasons. Titan's clear skies are not what researchers expected. This view looks toward the Saturn-facing side of Titan. North on Titan is up and rotated 3 degrees to the left. The image was taken with the Cassini spacecraft narrow-angle camera on Oct. 29, 2016 using a spectral filter that preferentially admits wavelengths of near-infrared light centered at 938 nanometers. The view was obtained at a distance of approximately 545,000 miles (878,000 kilometers) from Titan. Image scale is 3 miles (5 kilometers) per pixel. http://photojournal.jpl.nasa.gov/catalog/PIA20516</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=20160005785&hterms=Ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DOcean','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20160005785&hterms=Ocean&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D90%26Ntt%3DOcean"><span>A <span class="hlt">Cloud</span>Sat-CALIPSO View of <span class="hlt">Cloud</span> and Precipitation Properties Across Cold Fronts over the Global Oceans</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Naud, Catherine M.; Posselt, Derek J.; van den Heever, Susan C.</p> <p>2015-01-01</p> <p>The distribution of <span class="hlt">cloud</span> and precipitation properties across oceanic extratropical cyclone cold fronts is examined using four years of combined <span class="hlt">Cloud</span>Sat radar and CALIPSO lidar retrievals. The global annual mean <span class="hlt">cloud</span> and precipitation distributions show that low-level <span class="hlt">clouds</span> are ubiquitous in the post frontal zone while higher-level <span class="hlt">cloud</span> frequency and precipitation peak in the warm sector along the surface front. Increases in temperature and moisture within the cold front region are associated with larger high-level but lower mid-/low level <span class="hlt">cloud</span> frequencies and precipitation decreases in the cold sector. This behavior seems to be related to a shift from stratiform to convective <span class="hlt">clouds</span> and precipitation. Stronger ascent in the warm conveyor belt tends to enhance cloudiness and precipitation across the cold front. A strong temperature contrast between the warm and cold sectors also encourages greater post-cold-frontal <span class="hlt">cloud</span> occurrence. While the seasonal contrasts in environmental temperature, moisture, and ascent strength are enough to explain most of the variations in <span class="hlt">cloud</span> and precipitation across cold fronts in both hemispheres, they do not fully explain the differences between Northern and Southern Hemisphere cold fronts. These differences are better explained when the impact of the contrast in temperature across the cold front is also considered. In addition, these large-scale parameters do not explain the relatively large frequency in springtime post frontal precipitation.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1351748','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1351748"><span>Effects of environment forcing on marine boundary layer <span class="hlt">cloud</span>-drizzle processes: MBL <span class="hlt">Cloud</span>-Drizzle Processes</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, Peng; Dong, Xiquan; Xi, Baike</p> <p></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 types of conditions. The type 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 type II <span class="hlt">clouds</span> 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 <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 type 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 type II cases suggest that boundary layer instability plays an important role in TKE production and <span class="hlt">cloud</span>-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</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1351748-effects-environment-forcing-marine-boundary-layer-cloud-drizzle-processes-mbl-cloud-drizzle-processes','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1351748-effects-environment-forcing-marine-boundary-layer-cloud-drizzle-processes-mbl-cloud-drizzle-processes"><span>Effects of environment forcing on marine boundary layer <span class="hlt">cloud</span>-drizzle processes: MBL <span class="hlt">Cloud</span>-Drizzle Processes</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Wu, Peng; Dong, Xiquan; Xi, Baike; ...</p> <p>2017-04-20</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 types of conditions. The type 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 type II <span class="hlt">clouds</span> 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 <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 type 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 type II cases suggest that boundary layer instability plays an important role in TKE production and <span class="hlt">cloud</span>-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</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/828460','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/828460"><span>The NSA/SHEBA <span class="hlt">Cloud</span> & Radiation Comparison Study</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>Janet M. Intrieri; Matthew D. Shupe</p> <p>2004-08-23</p> <p><span class="hlt">Cloud</span> and radiation data from two distinctly different Arctic areas are analyzed to study the differences between coastal Alaskan and open Arctic Ocean region <span class="hlt">clouds</span> and their respective influence on the surface radiation budget. The <span class="hlt">cloud</span> and radiation datasets were obtained from 1) the DOE North Slope of Alaska (NSA) facility in the coastal town of Barrow, Alaska, and 2) the SHEBA field program, which was conducted from an icebreaker frozen in, and drifting with, the sea-ice for one year in the Western Arctic Ocean. Radar, lidar, radiometer, and sounding measurements from both locations were used to produce annual cyclesmore » of <span class="hlt">cloud</span> occurrence and height, atmospheric temperature and humidity, surface longwave and shortwave broadband fluxes, surface albedo, and <span class="hlt">cloud</span> radiative forcing. In general, both regions revealed a similar annual trend of <span class="hlt">cloud</span> occurrence fraction with minimum values in winter (60-75%) and maximum values during spring, summer and fall (80-90%). However, the annual average <span class="hlt">cloud</span> occurrence fraction for SHEBA (76%) was lower than the 6-year average <span class="hlt">cloud</span> occurrence at NSA (92%). Both Arctic areas also showed similar annual cycle trends of <span class="hlt">cloud</span> forcing with <span class="hlt">clouds</span> warming the surface through most of the year and a period of surface cooling during the summer, when <span class="hlt">cloud</span> shading effects overwhelm <span class="hlt">cloud</span> greenhouse effects. The greatest difference between the two regions was observed in the magnitude of the <span class="hlt">cloud</span> cooling effect (i.e., shortwave <span class="hlt">cloud</span> forcing), which was significantly stronger at NSA and lasted for a longer period of time than at SHEBA. This is predominantly due to the longer and stronger melt season at NSA (i.e., albedo values that are much lower coupled with Sun angles that are somewhat higher) than the melt season observed over the ice pack at SHEBA. Longwave <span class="hlt">cloud</span> forcing values were comparable between the two sites indicating a general similarity in cloudiness and atmospheric temperature and humidity structure between the</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017nova.pres.2498K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017nova.pres.2498K"><span>Speeding <span class="hlt">Clouds</span> May Reveal Invisible Black Holes</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>2017-07-01</p> <p>Several small, speeding <span class="hlt">clouds</span> have been discovered at the center of our galaxy. A new study suggests that these unusual objects may reveal the lurking presence of inactive black holes.Peculiar Cloudsa) Velocity-integrated intensity map showing the location of the two high-velocity compact <span class="hlt">clouds</span>, HCN0.0090.044 and HCN0.0850.094, in the context of larger molecular <span class="hlt">clouds</span>. b) and c) Latitude-velocity and longitude-velocity maps for HCN0.0090.044 and HCN0.0850.094, respectively. d) and e) spectra for the two compacts <span class="hlt">clouds</span>, respectively. Click for a closer look. [Takekawa et al. 2017]Sgr A*, the supermassive black hole marking the center of our galaxy, is surrounded by a region roughly 650 light-years across known as the Central Molecular Zone. This area at the heart of our galaxy is filled with large amounts of warm, dense molecular gas that has a complex distribution and turbulent kinematics.Several peculiar gas <span class="hlt">clouds</span> have been discovered within the Central Molecular Zone within the past two decades. These <span class="hlt">clouds</span>, dubbed high-velocity compact <span class="hlt">clouds</span>, are characterized by their compact sizes and extremely broad velocity widths.What created this mysterious population of energetic <span class="hlt">clouds</span>? The recent discovery of two new high-velocity compact <span class="hlt">clouds</span>, reported on in a paper led by Shunya Takekawa (Keio University, Japan), may help us to answer this question.Two More to the CountUsing the James Clerk Maxwell Telescope in Hawaii, Takekawa and collaborators detected the small <span class="hlt">clouds</span> near the circumnuclear disk at the centermost part of our galaxy. These two <span class="hlt">clouds</span> have velocity spreads of -80 to -20 km/s and -80 to 0 km/s and compact sizes of just over 1 light-year. The <span class="hlt">clouds</span> similar appearances and physical properties suggest that they may both have been formed by the same process.Takekawa and collaborators explore and discard several possible origins for these <span class="hlt">clouds</span>, such as outflows from massive protostars (no massive, luminous stars have been detected affiliated</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2010AIPC.1324..184D','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2010AIPC.1324..184D"><span>An Overview of <span class="hlt">Cloud</span> Computing in Distributed Systems</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Divakarla, Usha; Kumari, Geetha</p> <p>2010-11-01</p> <p><span class="hlt">Cloud</span> computing is the emerging trend in the field of distributed computing. <span class="hlt">Cloud</span> computing evolved from grid computing and distributed computing. <span class="hlt">Cloud</span> plays an important role in huge organizations in maintaining huge data with limited resources. <span class="hlt">Cloud</span> also helps in resource sharing through some specific virtual machines provided by the <span class="hlt">cloud</span> service provider. This paper gives an overview of the <span class="hlt">cloud</span> organization and some of the basic security issues pertaining to the <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eosweb.larc.nasa.gov/project/dscovr/dscovr_epic_l2_cloud_01','SCIGOV-ASDC'); return false;" href="https://eosweb.larc.nasa.gov/project/dscovr/dscovr_epic_l2_cloud_01"><span>DSCOVR_EPIC_L2_<span class="hlt">CLOUD</span>_01</span></a></p> <p><a target="_blank" href="http://eosweb.larc.nasa.gov/">Atmospheric Science Data Center </a></p> <p></p> <p>2018-06-20</p> <p>... V1 Level:  L2 Platform:  DEEP SPACE CLIMATE OBSERVATORY Instrument:  Enhanced Polychromatic ... assuming ice phase <span class="hlt">Cloud</span> Optical Thickness – assuming liquid phase EPIC <span class="hlt">Cloud</span> Mask Oxygen A-band <span class="hlt">Cloud</span> Effective Height (in ...</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://eric.ed.gov/?q=cloud+AND+computing&pg=7&id=EJ878712','ERIC'); return false;" href="https://eric.ed.gov/?q=cloud+AND+computing&pg=7&id=EJ878712"><span>A View from 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>Chudnov, Daniel</p> <p>2010-01-01</p> <p><span class="hlt">Cloud</span> computing is definitely a thing now, but it's not new and it's not even novel. Back when people were first learning about the Internet in the 1990s, every diagram that one saw showing how the Internet worked had a big <span class="hlt">cloud</span> in the middle. That <span class="hlt">cloud</span> represented the diverse links, routers, gateways, and protocols that passed traffic around in…</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 type 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('http://www.dtic.mil/docs/citations/AD1010441','DTIC-ST'); return false;" href="http://www.dtic.mil/docs/citations/AD1010441"><span>Platform for High-Assurance <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>2016-06-01</p> <p>to create today’s standard <span class="hlt">cloud</span> computing applications and services. Additionally , our Super<span class="hlt">Cloud</span> (a related but distinct project under the same... Additionally , our Super<span class="hlt">Cloud</span> (a related but distinct project under the same MRC funding) reduces vendor lock-in and permits application to migrate, to follow...managing key- value storage with strong assurance properties. This first accomplishment allows us to climb the <span class="hlt">cloud</span> technical stack, by offering</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1020623-intercomparison-cloud-model-simulations-arctic-mixed-phase-boundary-layer-clouds-observed-during-sheba-fire-ace','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1020623-intercomparison-cloud-model-simulations-arctic-mixed-phase-boundary-layer-clouds-observed-during-sheba-fire-ace"><span>Intercomparison of <span class="hlt">cloud</span> model simulations of Arctic mixed-phase boundary layer <span class="hlt">clouds</span> observed during SHEBA/FIRE-ACE</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>Morrison, H.; Zuidema, Paquita; Ackerman, Andrew</p> <p>2011-06-16</p> <p>An intercomparison of six <span class="hlt">cloud</span>-resolving and large-eddy simulation models is presented. This case study is based on observations of a persistent mixed-phase boundary layer <span class="hlt">cloud</span> gathered on 7 May, 1998 from the Surface Heat Budget of Arctic Ocean (SHEBA) and First ISCCP Regional Experiment - Arctic <span class="hlt">Cloud</span> Experiment (FIRE-ACE). Ice nucleation is constrained in the simulations in a way that holds the ice crystal concentration approximately fixed, with two sets of sensitivity runs in addition to the baseline simulations utilizing different specified ice nucleus (IN) concentrations. All of the baseline and sensitivity simulations group into two distinct quasi-steady states associatedmore » with either persistent mixed-phase <span class="hlt">clouds</span> or all-ice <span class="hlt">clouds</span> after the first few hours of integration, implying the existence of multiple equilibria. These two states are associated with distinctly different microphysical, thermodynamic, and radiative characteristics. Most but not all of the models produce a persistent mixed-phase <span class="hlt">cloud</span> qualitatively similar to observations using the baseline IN/crystal concentration, while small increases in the IN/crystal concentration generally lead to rapid glaciation and conversion to the all-ice state. Budget analysis indicates that larger ice deposition rates associated with increased IN/crystal concentrations have a limited direct impact on dissipation of liquid in these simulations. However, the impact of increased ice deposition is greatly enhanced by several interaction pathways that lead to an increased surface precipitation flux, weaker <span class="hlt">cloud</span> top radiative cooling and <span class="hlt">cloud</span> dynamics, and reduced vertical mixing, promoting rapid glaciation of the mixed-phase <span class="hlt">cloud</span> for deposition rates in the <span class="hlt">cloud</span> layer greater than about 1-2x10-5 g kg-1 s-1. These results indicate the critical importance of precipitation-radiative-dynamical interactions in simulating <span class="hlt">cloud</span> phase, which have been neglected in previous fixed-dynamical parcel studies of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2015AGUFM.A34E..05K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2015AGUFM.A34E..05K"><span>Exploiting <span class="hlt">Cloud</span> Radar Doppler Spectra of Mixed-Phase <span class="hlt">Clouds</span> during ACCEPT Field Experiment to Identify Microphysical Processes</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kalesse, H.; Myagkov, A.; Seifert, P.; Buehl, J.</p> <p>2015-12-01</p> <p><span class="hlt">Cloud</span> radar Doppler spectra offer much information about <span class="hlt">cloud</span> processes. By analyzing millimeter radar Doppler spectra from <span class="hlt">cloud</span>-top to -base in mixed-phase <span class="hlt">clouds</span> 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 <span class="hlt">cloud</span>. 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. <span class="hlt">Cloud</span> 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 <span class="hlt">cloud</span> radar measurements, we try to identify <span class="hlt">cloud</span> phase in the <span class="hlt">cloud</span> 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 <span class="hlt">cloud</span> Doppler radar (METEK MIRA-35) in linear depolarization (LDR) mode is used. Data is from the deployment of the Leipzig Aerosol and <span class="hlt">Cloud</span> Remote Observations System (LACROS) during the Analysis of the Composition of</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1374609','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1374609"><span>Thin ice <span class="hlt">clouds</span> in the Arctic: <span class="hlt">cloud</span> optical depth and particle size retrieved from ground-based thermal infrared radiometry</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>Blanchard, Yann; Royer, Alain; O'Neill, Norman T.</p> <p></p> <p>Multiband downwelling thermal measurements of zenith sky radiance, along with <span class="hlt">cloud</span> boundary heights, were used in a retrieval algorithm to estimate <span class="hlt">cloud</span> optical depth and effective particle diameter of thin ice <span class="hlt">clouds</span> in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice <span class="hlt">clouds</span> cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several <span class="hlt">cloud</span> parameters including optical depth, effective particle diameter and shape, water vapor content, <span class="hlt">cloud</span> geometric thickness and <span class="hlt">cloud</span> base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, <span class="hlt">cloud</span> optical depth up to a maximum value of 2.6 and to separate thin ice <span class="hlt">clouds</span> into two classes: (1) TIC1 <span class="hlt">clouds</span> characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 <span class="hlt">clouds</span> characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave <span class="hlt">Cloud</span> Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for <span class="hlt">cloud</span> optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 <span class="hlt">clouds</span>. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1374609-thin-ice-clouds-arctic-cloud-optical-depth-particle-size-retrieved-from-ground-based-thermal-infrared-radiometry','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1374609-thin-ice-clouds-arctic-cloud-optical-depth-particle-size-retrieved-from-ground-based-thermal-infrared-radiometry"><span>Thin ice <span class="hlt">clouds</span> in the Arctic: <span class="hlt">cloud</span> optical depth and particle size retrieved from ground-based thermal infrared radiometry</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; ...</p> <p>2017-06-09</p> <p>Multiband downwelling thermal measurements of zenith sky radiance, along with <span class="hlt">cloud</span> boundary heights, were used in a retrieval algorithm to estimate <span class="hlt">cloud</span> optical depth and effective particle diameter of thin ice <span class="hlt">clouds</span> in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice <span class="hlt">clouds</span> cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several <span class="hlt">cloud</span> parameters including optical depth, effective particle diameter and shape, water vapor content, <span class="hlt">cloud</span> geometric thickness and <span class="hlt">cloud</span> base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, <span class="hlt">cloud</span> optical depth up to a maximum value of 2.6 and to separate thin ice <span class="hlt">clouds</span> into two classes: (1) TIC1 <span class="hlt">clouds</span> characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 <span class="hlt">clouds</span> characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave <span class="hlt">Cloud</span> Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for <span class="hlt">cloud</span> optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 <span class="hlt">clouds</span>. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011AGUFMGC32B..05L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011AGUFMGC32B..05L"><span><span class="hlt">Clouds</span>, Wind and the Biogeography of Central American <span class="hlt">Cloud</span> Forests: Remote Sensing, Atmospheric Modeling, and Walking in the Jungle</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Lawton, R.; Nair, U. S.</p> <p>2011-12-01</p> <p><span class="hlt">Cloud</span> forests stand at the core of the complex of montane ecosystems that provide the backbone to the multinational Mesoamerican Biological Corridor, which seeks to protect a biodiversity conservation "hotspot" of global significance in an area of rapidly changing land use. Although <span class="hlt">cloud</span> forests are generally defined by frequent and prolonged immersion in <span class="hlt">cloud</span>, workers differ in their feelings about "frequent" and "prolonged", and quantitative assessments are rare. Here we focus on the dry season, in which the <span class="hlt">cloud</span> and mist from orographic <span class="hlt">cloud</span> plays a critical role in forest water relations, and discuss remote sensing of orographic <span class="hlt">clouds</span>, and regional and atmospheric modeling at several scales to quantitatively examine the distribution of the atmospheric conditions that characterize <span class="hlt">cloud</span> forests. Remote sensing using data from GOES reveals diurnal and longer scale patterns in the distribution of dry season orographic <span class="hlt">clouds</span> in Central America at both regional and local scales. Data from MODIS, used to calculate the base height of orographic <span class="hlt">cloud</span> banks, reveals not only the geographic distributon of <span class="hlt">cloud</span> forest sites, but also striking regional variation in the frequency of montane immersion in orographic <span class="hlt">cloud</span>. At a more local scale, wind is known to have striking effects on forest structure and species distribution in tropical montane ecosystems, both as a general mechanical stress and as the major agent of ecological disturbance. High resolution regional atmospheric modeling using CSU RAMS in the Monteverde <span class="hlt">cloud</span> forests of Costa Rica provides quantitative information on the spatial distribution of canopy level winds, insight into the spatial structure and local dynamics of <span class="hlt">cloud</span> forest communities. This information will be useful in not only in local conservation planning and the design of the Mesoamerican Biological Corridor, but also in assessments of the sensitivity of <span class="hlt">cloud</span> forests to global and regional climate changes.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JGRD..122.2878H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.2878H"><span>Assessing the accuracy of MISR and MISR-simulated <span class="hlt">cloud</span> top heights using <span class="hlt">Cloud</span>Sat- and CALIPSO-retrieved hydrometeor profiles</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally</p> <p>2017-03-01</p> <p>Satellite retrievals of <span class="hlt">cloud</span> properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of <span class="hlt">Cloud</span>Sat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing <span class="hlt">cloud</span> top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped <span class="hlt">clouds</span> agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped <span class="hlt">cloud</span> cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped <span class="hlt">clouds</span> between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level <span class="hlt">clouds</span> between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator <span class="hlt">cloud</span> top height adjustment. This difference highlights the importance of sensor resolution and boundary layer <span class="hlt">cloud</span> spatial structure in determining low-altitude <span class="hlt">cloud</span> cover. The MISR-simulated and MISR-retrieved <span class="hlt">cloud</span> optical depth also show systematic differences, which are also likely due in part to <span class="hlt">cloud</span> spatial structure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19710000460','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19710000460"><span><span class="hlt">Cloud</span>-free resolution element statistics program</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Liley, B.; Martin, C. D.</p> <p>1971-01-01</p> <p>Computer program computes number of <span class="hlt">cloud</span>-free elements in field-of-view and percentage of total field-of-view occupied by <span class="hlt">clouds</span>. Human error is eliminated by using visual estimation to compute <span class="hlt">cloud</span> statistics from aerial photographs.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1343071','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1343071"><span>Evolution in <span class="hlt">Cloud</span> Population Statistics of the MJO: From AMIE Field Observations to Global-<span class="hlt">Cloud</span> Permitting Models Final Report</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>Kollias, Pavlos</p> <p></p> <p>This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global <span class="hlt">cloud</span>-permitting models, with emphases on <span class="hlt">cloud</span> population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value <span class="hlt">cloud</span> and precipitation products and derive <span class="hlt">cloud</span> statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic <span class="hlt">cloud</span> and precipitation <span class="hlt">cloud</span> classification that identify different <span class="hlt">cloud</span> (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 (<span class="hlt">cloud</span>) radar deployed at the ARM sites.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/servlets/purl/1357354','SCIGOV-STC'); return false;" href="https://www.osti.gov/servlets/purl/1357354"><span>Insights from a refined decomposition of <span class="hlt">cloud</span> feedbacks</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>Zelinka, Mark D.; Zhou, Chen; Klein, Stephen A.</p> <p></p> <p>Decomposing <span class="hlt">cloud</span> feedback into components due to changes in several gross <span class="hlt">cloud</span> properties provides valuable insights into its physical causes. Here we present a refined decomposition that separately considers changes in free tropospheric and low <span class="hlt">cloud</span> properties, better connecting feedbacks to individual governing processes and avoiding ambiguities present in a commonly used decomposition. It reveals that three net <span class="hlt">cloud</span> feedback components are robustly nonzero: positive feedbacks from increasing free tropospheric <span class="hlt">cloud</span> altitude and decreasing low <span class="hlt">cloud</span> cover and a negative feedback from increasing low <span class="hlt">cloud</span> optical depth. Low <span class="hlt">cloud</span> amount feedback is the dominant contributor to spread in net cloudmore » feedback but its anticorrelation with other components damps overall spread. Furthermore, the ensemble mean free tropospheric <span class="hlt">cloud</span> altitude feedback is roughly 60% as large as the standard <span class="hlt">cloud</span> altitude feedback because it avoids aliasing in low <span class="hlt">cloud</span> reductions. Implications for the “null hypothesis” climate sensitivity from well-understood and robustly simulated feedbacks are discussed.« less</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.osti.gov/pages/biblio/1357354-insights-from-refined-decomposition-cloud-feedbacks','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1357354-insights-from-refined-decomposition-cloud-feedbacks"><span>Insights from a refined decomposition of <span class="hlt">cloud</span> feedbacks</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Zelinka, Mark D.; Zhou, Chen; Klein, Stephen A.</p> <p>2016-09-05</p> <p>Decomposing <span class="hlt">cloud</span> feedback into components due to changes in several gross <span class="hlt">cloud</span> properties provides valuable insights into its physical causes. Here we present a refined decomposition that separately considers changes in free tropospheric and low <span class="hlt">cloud</span> properties, better connecting feedbacks to individual governing processes and avoiding ambiguities present in a commonly used decomposition. It reveals that three net <span class="hlt">cloud</span> feedback components are robustly nonzero: positive feedbacks from increasing free tropospheric <span class="hlt">cloud</span> altitude and decreasing low <span class="hlt">cloud</span> cover and a negative feedback from increasing low <span class="hlt">cloud</span> optical depth. Low <span class="hlt">cloud</span> amount feedback is the dominant contributor to spread in net cloudmore » feedback but its anticorrelation with other components damps overall spread. Furthermore, the ensemble mean free tropospheric <span class="hlt">cloud</span> altitude feedback is roughly 60% as large as the standard <span class="hlt">cloud</span> altitude feedback because it avoids aliasing in low <span class="hlt">cloud</span> reductions. Implications for the “null hypothesis” climate sensitivity from well-understood and robustly simulated feedbacks are discussed.« less</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017MmSAI..88..741K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017MmSAI..88..741K"><span>Time evolution of giant molecular <span class="hlt">cloud</span> mass functions with <span class="hlt">cloud-cloud</span> collisions and gas resurrection in various environments</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kobayashi, M. I. N.; Inutsuka, S.; Kobayashi, H.; Hasegawa, K.</p> <p></p> <p>We formulate the evolution equation for the giant molecular <span class="hlt">cloud</span> (GMC) mass functions including self-growth of GMCs through the thermal instability, self-dispersal due to massive stars born in GMCs, <span class="hlt">cloud-cloud</span> collisions (CCCs), and gas resurrection that replenishes the minimum-mass GMC population. The computed time evolutions obtained from this formulation suggest that the slope of GMC mass function in the mass range <105.5 Mȯ is governed by the ratio of GMC formation timescale to its dispersal timescale, and that the CCC process modifies only the massive end of the mass function. Our results also suggest that most of the dispersed gas contributes to the mass growth of pre-existing GMCs in arm regions whereas less than 60 per cent contributes in inter-arm regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=PIA00058&hterms=vertical+height&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dvertical%2Bheight','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=PIA00058&hterms=vertical+height&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D80%26Ntt%3Dvertical%2Bheight"><span>Neptune <span class="hlt">Clouds</span> Showing Vertical Relief</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>1989-01-01</p> <p>This Voyager 2 high resolution color image, taken 2 hours before closest approach, provides obvious evidence of vertical relief in Neptune's bright <span class="hlt">cloud</span> streaks. These <span class="hlt">clouds</span> were observed at a latitude of 29 degrees north near Neptune's east terminator. The linear <span class="hlt">cloud</span> forms are stretched approximately along lines of constant latitude and the sun is toward the lower left. The bright sides of the <span class="hlt">clouds</span> which face the sun are brighter than the surrounding <span class="hlt">cloud</span> deck because they are more directly exposed to the sun. Shadows can be seen on the side opposite the sun. These shadows are less distinct at short wavelengths (violet filter) and more distinct at long wavelengths (orange filter). This can be understood if the underlying <span class="hlt">cloud</span> deck on which the shadow is cast is at a relatively great depth, in which case scattering by molecules in the overlying atmosphere will diffuse light into the shadow. Because molecules scatter blue light much more efficiently than red light, the shadows will be darkest at the longest (reddest) wavelengths, and will appear blue under white light illumination. The resolution of this image is 11 kilometers (6.8 miles per pixel) and the range is only 157,000 kilometers (98,000 miles). The width of the <span class="hlt">cloud</span> streaks range from 50 to 200 kilometers (31 to 124 miles), and their shadow widths range from 30 to 50 kilometers (18 to 31 miles). <span class="hlt">Cloud</span> heights appear to be of the order of 50 kilometers (31 miles). This corresponds to 2 scale heights. The Voyager Mission is conducted by JPL for NASA's Office of Space Science and Applications.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JGRD..123.3724C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JGRD..123.3724C"><span>The <span class="hlt">Cloud</span> Top Distribution and Diurnal Variation of <span class="hlt">Clouds</span> Over East Asia: Preliminary Results From Advanced Himawari Imager</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Chen, Dandan; Guo, Jianping; Wang, Hongqing; Li, Jian; Min, Min; Zhao, Wenhui; Yao, Dan</p> <p>2018-04-01</p> <p><span class="hlt">Clouds</span>, as one of the most uncertain factors in climate system, have been intensively studied as satellites with advanced instruments emerged in recent years. However, few studies examine the vertical distributions of <span class="hlt">cloud</span> top and their temporal variations over East Asia based on geostationary satellite data. In this study, the vertical structures of <span class="hlt">cloud</span> top and its diurnal variations in summer of 2016 are analyzed using the Advanced Himawari Imager/Himawari-8 <span class="hlt">cloud</span> products. Results show that <span class="hlt">clouds</span> occur most frequently over the southern Tibetan Plateau and the Bay of Bengal. We find a steep gradient of <span class="hlt">cloud</span> occurrence frequency extending from southwest to northeast China and low-value centers over the eastern Pacific and the Inner Mongolia Plateau. The vertical structures of <span class="hlt">cloud</span> top are highly dependent on latitude, in addition to the nonnegligible roles of both terrain and land-sea thermal contrast. In terms of the diurnal cycle, <span class="hlt">clouds</span> tend to occur more often in the afternoon, peaking around 1700 local time over land and ocean. The amplitude of <span class="hlt">cloud</span> diurnal variation over ocean is much smaller than that over land, and complex terrain tends to be linked to larger amplitude. In vertical, the diurnal cycle of <span class="hlt">cloud</span> frequency exhibits bimodal pattern over both land and ocean. The high-level peaks occur at almost the same altitude over land and ocean. In contrast, the low-level peaks over ocean mainly reside in the boundary layer, much lower than those over land, which could be indicative of the frequent occurrence of marine boundary layer <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.H31G1596K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.H31G1596K"><span>DeepSAT's <span class="hlt">Cloud</span>CNN: A Deep Neural Network for Rapid <span class="hlt">Cloud</span> Detection from Geostationary Satellites</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.</p> <p>2017-12-01</p> <p><span class="hlt">Cloud</span> and <span class="hlt">cloud</span> shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate <span class="hlt">cloud</span>/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called <span class="hlt">Cloud</span>CNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's <span class="hlt">Cloud</span>CNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train <span class="hlt">Cloud</span>CNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time <span class="hlt">cloud</span> detection, cyclone detection, or extreme weather event predictions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2013AGUFMIN53A1552H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013AGUFMIN53A1552H"><span>BlueSky <span class="hlt">Cloud</span> - rapid infrastructure capacity using Amazon's <span class="hlt">Cloud</span> for wildfire emergency response</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Haderman, M.; Larkin, N. K.; Beach, M.; Cavallaro, A. M.; Stilley, J. C.; DeWinter, J. L.; Craig, K. J.; Raffuse, S. M.</p> <p>2013-12-01</p> <p>During peak fire season in the United States, many large wildfires often burn simultaneously across the country. Smoke from these fires can produce air quality emergencies. It is vital that incident commanders, air quality agencies, and public health officials have smoke impact information at their fingertips for evaluating where fires and smoke are and where the smoke will go next. To address the need for this kind of information, the U.S. Forest Service AirFire Team created the BlueSky Framework, a modeling system that predicts concentrations of particle pollution from wildfires. During emergency response, decision makers use BlueSky predictions to make public outreach and evacuation decisions. The models used in BlueSky predictions are computationally intensive, and the peak fire season requires significantly more computer resources than off-peak times. Purchasing enough hardware to run the number of BlueSky Framework runs that are needed during fire season is expensive and leaves idle servers running the majority of the year. The AirFire Team and STI developed BlueSky <span class="hlt">Cloud</span> to take advantage of Amazon's virtual servers hosted in the <span class="hlt">cloud</span>. With BlueSky <span class="hlt">Cloud</span>, as demand increases and decreases, servers can be easily spun up and spun down at a minimal cost. Moving standard BlueSky Framework runs into the Amazon <span class="hlt">Cloud</span> made it possible for the AirFire Team to rapidly increase the number of BlueSky Framework instances that could be run simultaneously without the costs associated with purchasing and managing servers. In this presentation, we provide an overview of the features of BlueSky <span class="hlt">Cloud</span>, describe how the system uses Amazon <span class="hlt">Cloud</span>, and discuss the costs and benefits of moving from privately hosted servers to a <span class="hlt">cloud</span>-based infrastructure.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20020076393','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20020076393"><span><span class="hlt">Cloud</span> Condensation Nuclei in FIRE III</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Hudson, James G.; Delnore, Victor E. (Technical Monitor)</p> <p>2002-01-01</p> <p>Yum and Hudson showed that the springtime Arctic aerosol is probably a result of long-range transport at high altitudes. Scavenging of particles by <span class="hlt">clouds</span> reduces the low level concentrations by a factor of 3. This produces a vertical gradient in particle concentrations when low-level <span class="hlt">clouds</span> are present. Concentrations are uniform with height when <span class="hlt">clouds</span> are not present. Low-level CCN (<span class="hlt">cloud</span> condensation nuclei) spectra are similar to those in other maritime areas as found by previous projects including FIRE 1 and ASTEX, which were also supported on earlier NASA-FIRE grants. Wylie and Hudson carried this work much further by comparing the CCN spectra observed during ACE with back trajectories of air masses and satellite photographs. This showed that <span class="hlt">cloud</span> scavenging reduces CCN concentrations at all altitudes over the springtime Arctic, with liquid <span class="hlt">clouds</span> being more efficient scavengers than frozen <span class="hlt">clouds</span>. The small size of the Arctic Ocean seems to make it more susceptible to continental and thus anthropogenic aerosol influences than any of the other larger oceans.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931..157L','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931..157L"><span>Identity-Based Authentication for <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>Li, Hongwei; Dai, Yuanshun; Tian, Ling; Yang, Haomiao</p> <p></p> <p><span class="hlt">Cloud</span> computing is a recently developed new technology for complex systems with massive-scale services sharing among numerous users. Therefore, authentication of both users and services is a significant issue for the trust and security of the <span class="hlt">cloud</span> computing. SSL Authentication Protocol (SAP), once applied in <span class="hlt">cloud</span> computing, will become so complicated that users will undergo a heavily loaded point both in computation and communication. This paper, based on the identity-based hierarchical model for <span class="hlt">cloud</span> computing (IBHMCC) and its corresponding encryption and signature schemes, presented a new identity-based authentication protocol for <span class="hlt">cloud</span> computing and services. Through simulation testing, it is shown that the authentication protocol is more lightweight and efficient than SAP, specially the more lightweight user side. Such merit of our model with great scalability is very suited to the massive-scale <span class="hlt">cloud</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018AtmRe.199..113W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018AtmRe.199..113W"><span>Comparison of <span class="hlt">cloud</span> top heights derived from FY-2 meteorological satellites with heights derived from ground-based millimeter wavelength <span class="hlt">cloud</span> radar</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wang, Zhe; Wang, Zhenhui; Cao, Xiaozhong; Tao, Fa</p> <p>2018-01-01</p> <p><span class="hlt">Clouds</span> are currently observed by both ground-based and satellite remote sensing techniques. Each technique has its own strengths and weaknesses depending on the observation method, instrument performance and the methods used for retrieval. It is important to study synergistic <span class="hlt">cloud</span> measurements to improve the reliability of the observations and to verify the different techniques. The FY-2 geostationary orbiting meteorological satellites continuously observe the sky over China. Their <span class="hlt">cloud</span> top temperature product can be processed to retrieve the <span class="hlt">cloud</span> top height (CTH). The ground-based millimeter wavelength <span class="hlt">cloud</span> radar can acquire information about the vertical structure of <span class="hlt">clouds</span>-such as the <span class="hlt">cloud</span> base height (CBH), CTH and the <span class="hlt">cloud</span> thickness-and can continuously monitor changes in the vertical profiles of <span class="hlt">clouds</span>. The CTHs were retrieved using both <span class="hlt">cloud</span> top temperature data from the FY-2 satellites and the <span class="hlt">cloud</span> radar reflectivity data for the same time period (June 2015 to May 2016) and the resulting datasets were compared in order to evaluate the accuracy of CTH retrievals using FY-2 satellites. The results show that the concordance rate of <span class="hlt">cloud</span> detection between the two datasets was 78.1%. Higher consistencies were obtained for thicker <span class="hlt">clouds</span> with larger echo intensity and for more continuous <span class="hlt">clouds</span>. The average difference in the CTH between the two techniques was 1.46 km. The difference in CTH between low- and mid-level <span class="hlt">clouds</span> was less than that for high-level <span class="hlt">clouds</span>. An attenuation threshold of the <span class="hlt">cloud</span> radar for rainfall was 0.2 mm/min; a rainfall intensity below this threshold had no effect on the CTH. The satellite CTH can be used to compensate for the attenuation error in the <span class="hlt">cloud</span> radar data.</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 type 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/2017JGRD..122.2351Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JGRD..122.2351Z"><span>Intercomparisons of marine boundary layer <span class="hlt">cloud</span> properties from the ARM CAP-MBL campaign and two MODIS <span class="hlt">cloud</span> products</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick</p> <p>2017-02-01</p> <p>From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) <span class="hlt">clouds</span> over the Azores region. In this paper, we present an intercomparison of the MBL <span class="hlt">cloud</span> properties, namely, <span class="hlt">cloud</span> liquid water path (LWP), <span class="hlt">cloud</span> optical thickness (COT), and <span class="hlt">cloud</span>-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) <span class="hlt">cloud</span> products (Goddard Space Flight Center (GSFC)-MODIS and <span class="hlt">Clouds</span> and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL <span class="hlt">cloud</span> cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS <span class="hlt">cloud</span> products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS <span class="hlt">cloud</span> product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL <span class="hlt">cloud</span> cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to <span class="hlt">cloud</span> top reduces the bias only by 0.5 µm.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/27792377','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/27792377"><span>Dispersion of Droplet <span class="hlt">Clouds</span> in Turbulence.</span></a></p> <p><a target="_blank" href="https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=pubmed">PubMed</a></p> <p>Bocanegra Evans, Humberto; Dam, Nico; Bertens, Guus; van der Voort, Dennis; van de Water, Willem</p> <p>2016-10-14</p> <p>We measure the absolute dispersion of <span class="hlt">clouds</span> of monodisperse, phosphorescent droplets in turbulent air by means of high-speed image-intensified video recordings. Laser excitation allows the initial preparation of well-defined, pencil-shaped luminous droplet <span class="hlt">clouds</span> in a completely nonintrusive way. We find that the dispersion of the <span class="hlt">clouds</span> is faster than the dispersion of fluid elements. We speculate that preferential concentration of inertial droplet <span class="hlt">clouds</span> is responsible for the enhanced dispersion.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2011PhDT........45K','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2011PhDT........45K"><span><span class="hlt">Cloud</span> Computing and Its Applications in GIS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Kang, Cao</p> <p>2011-12-01</p> <p><span class="hlt">Cloud</span> computing is a novel computing paradigm that offers highly scalable and highly available distributed computing services. The objectives of this research are to: 1. analyze and understand <span class="hlt">cloud</span> computing and its potential for GIS; 2. discover the feasibilities of migrating truly spatial GIS algorithms to distributed computing infrastructures; 3. explore a solution to host and serve large volumes of raster GIS data efficiently and speedily. These objectives thus form the basis for three professional articles. The first article is entitled "<span class="hlt">Cloud</span> Computing and Its Applications in GIS". This paper introduces the concept, structure, and features of <span class="hlt">cloud</span> computing. Features of <span class="hlt">cloud</span> computing such as scalability, parallelization, and high availability make it a very capable computing paradigm. Unlike High Performance Computing (HPC), <span class="hlt">cloud</span> computing uses inexpensive commodity computers. The uniform administration systems in <span class="hlt">cloud</span> computing make it easier to use than GRID computing. Potential advantages of <span class="hlt">cloud</span>-based GIS systems such as lower barrier to entry are consequently presented. Three <span class="hlt">cloud</span>-based GIS system architectures are proposed: public <span class="hlt">cloud</span>- based GIS systems, private <span class="hlt">cloud</span>-based GIS systems and hybrid <span class="hlt">cloud</span>-based GIS systems. Public <span class="hlt">cloud</span>-based GIS systems provide the lowest entry barriers for users among these three architectures, but their advantages are offset by data security and privacy related issues. Private <span class="hlt">cloud</span>-based GIS systems provide the best data protection, though they have the highest entry barriers. Hybrid <span class="hlt">cloud</span>-based GIS systems provide a compromise between these extremes. The second article is entitled "A <span class="hlt">cloud</span> computing algorithm for the calculation of Euclidian distance for raster GIS". Euclidean distance is a truly spatial GIS algorithm. Classical algorithms such as the pushbroom and growth ring techniques require computational propagation through the entire raster image, which makes it incompatible with the distributed nature</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017EGUGA..19.4094N','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017EGUGA..19.4094N"><span>Correlation between atmospheric electric fields and <span class="hlt">cloud</span> cover using a field mill and <span class="hlt">cloud</span> observation data</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Nakamori, Kota; Suzuki, Yasuki; Ohya, Hiroyo; Takano, Toshiaki; Kawamura, Yohei; Nakata, Hiroyuki; Yamashita, Kozo</p> <p>2017-04-01</p> <p>It is known that lightning and precipitations of rain droplets generated from thunderclouds are a generator of global atmospheric electric circuit. In the fair weather, the atmospheric electric fields (AEF) are downward (positive), while they are upward (negative) during lightning and precipitations. However, the correlations between the AEF, and the <span class="hlt">cloud</span> parameters such as <span class="hlt">cloud</span> cover, weather phenomenon, have been not revealed quantitatively yet. In this study, we investigate the correlations between the AEF and the <span class="hlt">cloud</span> parameters, weather phenomenon using a field mill, the 95 GHz-FALCON (FMCW Radar for <span class="hlt">Cloud</span> Observations)-I and all-sky camera observations. In this study, we installed a Boltek field mill on the roof of our building in Chiba University, Japan, (Geographic coordinate: 35.63 degree N, 140.10 degree E, the sea level: 55 m) on the first June, 2016. The sampling time of the AEF is 0.5 s. On the other hand, the FALCON-I has observed the <span class="hlt">cloud</span> parameters far from about 76 m of the field mill throughout 24 hours every day. The vertical <span class="hlt">cloud</span> profiles and the Doppler velocity of <span class="hlt">cloud</span> particles can be derived by the FALCON-I with high distance resolutions (48.8 m) (Takano et al., 2010). In addition, the images of the <span class="hlt">clouds</span> and precipitations are recorded with 30-s sampling by an all-sky camera using a CCD camera on the same roof during 05:00-22:00 LT every day. The distance between the field mill and the all-sky camera is 3.75 m. During 08:30 UT - 10:30 UT, on 4 July, 2016, we found the variation of the AEF due to the approach of thundercloud. The variation consisted of two patterns. One was slow variation due to the movement of thunderclouds, and the other was rapid variation associated with lightning discharges. As for the movement of thunderclouds, the AEF increased when the anvil was located over the field mill, which was opposite direction of the previous studies. This change might be due to the positive charges in the upper anvil more than 14 km</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> types 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://hdl.handle.net/2060/20120011942','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20120011942"><span><span class="hlt">Cloud</span> Macroscopic Organization: Order Emerging from Randomness</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Yuan, Tianle</p> <p>2011-01-01</p> <p><span class="hlt">Clouds</span> play a central role in many aspects of the climate system and their forms and shapes are remarkably diverse. Appropriate representation of <span class="hlt">clouds</span> in climate models is a major challenge because <span class="hlt">cloud</span> processes span at least eight orders of magnitude in spatial scales. Here we show that there exists order in <span class="hlt">cloud</span> size distribution of low-level <span class="hlt">clouds</span>, and that it follows a power-law distribution with exponent gamma close to 2. gamma is insensitive to yearly variations in environmental conditions, but has regional variations and land-ocean contrasts. More importantly, we demonstrate this self-organizing behavior of <span class="hlt">clouds</span> emerges naturally from a complex network model with simple, physical organizing principles: random clumping and merging. We also demonstrate symmetry between clear and cloudy skies in terms of macroscopic organization because of similar fundamental underlying organizing principles. The order in the apparently complex <span class="hlt">cloud</span>-clear field thus has its root in random local interactions. Studying <span class="hlt">cloud</span> organization with complex network models is an attractive new approach that has wide applications in climate science. We also propose a concept of <span class="hlt">cloud</span> statistic mechanics approach. This approach is fully complementary to deterministic models, and the two approaches provide a powerful framework to meet the challenge of representing <span class="hlt">clouds</span> in our climate models when working in tandem.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://ntrs.nasa.gov/search.jsp?R=19870018894&hterms=kernel&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dkernel','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=19870018894&hterms=kernel&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DAll%26N%3D0%26No%3D50%26Ntt%3Dkernel"><span>Kernel structures for <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>Spafford, Eugene H.; Mckendry, Martin S.</p> <p>1986-01-01</p> <p>An overview of the internal structure of the <span class="hlt">Clouds</span> kernel was presented. An indication of how these structures will interact in the prototype <span class="hlt">Clouds</span> implementation is given. Many specific details have yet to be determined and await experimentation with an actual working system.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20000025312','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20000025312"><span><span class="hlt">Cloud</span> Statistics for NASA Climate Change Studies</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Wylie, Donald P.</p> <p>1999-01-01</p> <p>The Principal Investigator participated in two field experiments and developed a global data set on cirrus <span class="hlt">cloud</span> frequency and optical depth to aid the development of numerical models of climate. Four papers were published under this grant. The accomplishments are summarized: (1) In SUCCESS (SUbsonic aircraft: Contrail & <span class="hlt">Cloud</span> Effects Special Study) the Principal Investigator aided weather forecasters in the start of the field program. A paper also was published on the <span class="hlt">clouds</span> studied in SUCCESS and the use of the satellite stereographic technique to distinguish <span class="hlt">cloud</span> forms and heights of <span class="hlt">clouds</span>. (2) In SHEBA (Surface Heat Budget in the Arctic) FIRE/ACE (Arctic <span class="hlt">Cloud</span> Experiment) the Principal Investigator provided daily weather and <span class="hlt">cloud</span> forecasts for four research aircraft crews, NASA's ER-2, UCAR's C-130, University of Washington's Convert 580, and the Canadian Atmospheric Environment Service's Convert 580. Approximately 105 forecasts were written. The Principal Investigator also made daily weather summaries with calculations of air trajectories for 54 flight days in the experiment. The trajectories show where the air sampled during the flights came from and will be used in future publications to discuss the origin and history of the air and <span class="hlt">clouds</span> sampled by the aircraft. A paper discussing how well the FIRE/ACE data represent normal climatic conditions in the arctic is being prepared. (3) The Principal Investigator's web page became the source of information for weather forecasting by the scientists on the SHEBA ship. (4) Global Cirrus frequency and optical depth is a continuing analysis of global <span class="hlt">cloud</span> cover and frequency distribution are being made from the NOAA polar orbiting weather satellites. This analysis is sensitive to cirrus <span class="hlt">clouds</span> because of the radiative channels used. During this grant three papers were published which describe <span class="hlt">cloud</span> frequencies, their optical properties and compare the Wisconsin FM <span class="hlt">Cloud</span> Analysis to other global <span class="hlt">cloud</span> data such as</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2005AGUFM.A23C0957Z','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2005AGUFM.A23C0957Z"><span>Derivation of <span class="hlt">Cloud</span> Heating Rate Profiles using observations of Mixed-Phase Arctic <span class="hlt">Clouds</span>: Impacts of Solar Zenith Angle</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Zhang, G.; McFarquhar, G.; Poellot, M.; Verlinde, J.; Heymsfield, A.; Kok, G.</p> <p>2005-12-01</p> <p>Arctic stratus <span class="hlt">clouds</span> play an important role in the energy balance of the Arctic region. Previous studies have suggested that Arctic stratus persist due to a balance among <span class="hlt">cloud</span> top radiation cooling, latent heating, ice crystal fall out and large scale forcing. In this study, radiative heating profiles through Arctic stratus are computed using <span class="hlt">cloud</span>, surface and thermodynamic observations obtained during the Mixed-Phase Arctic <span class="hlt">Cloud</span> Experiment (M-PACE) as input to the radiative transfer model STREAMER. In particular, microphysical and macrophycial <span class="hlt">cloud</span> properties such as phase, water content, effective particle size, particle shape, <span class="hlt">cloud</span> height and <span class="hlt">cloud</span> thickness were derived using data collected by in-situ sensors on the University of North Dakota (UND) Citation and ground-based remote sensors at Barrow and Oliktok Point. Temperature profiles were derived from radiosonde launches and a fresh snow surface was assumed. One series of sensitivity studies explored the dependence of the heating profile on the solar zenith angle. For smaller solar zenith angles, more incoming solar radiation is received at <span class="hlt">cloud</span> top acting to counterbalance infrared cooling. As solar zenith angle in the Arctic is large compared to low latitudes, a large solar zenith angle may contribute to the longevity of these <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.ncbi.nlm.nih.gov/pubmed/29029576','PUBMED'); return false;" href="https://www.ncbi.nlm.nih.gov/pubmed/29029576"><span>Marine Aerosols and <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>Brooks, Sarah D; Thornton, Daniel C O</p> <p>2018-01-03</p> <p>The role of marine bioaerosols in <span class="hlt">cloud</span> formation and climate is currently so uncertain that even the sign of the climate forcing is unclear. Marine aerosols form through direct emissions and through the conversion of gas-phase emissions to aerosols in the atmosphere. The composition and size of aerosols determine how effective they are in catalyzing the formation of water droplets and ice crystals in <span class="hlt">clouds</span> by acting as <span class="hlt">cloud</span> condensation nuclei and ice nucleating particles, respectively. Marine organic aerosols may be sourced both from recent regional phytoplankton blooms that add labile organic matter to the surface ocean and from long-term global processes, such as the upwelling of old refractory dissolved organic matter from the deep ocean. Understanding the formation of marine aerosols and their propensity to catalyze <span class="hlt">cloud</span> formation processes are challenges that must be addressed given the major uncertainties associated with aerosols in climate models.</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://hdl.handle.net/2060/19830011117','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19830011117"><span><span class="hlt">Cloud</span> cover estimation: Use of GOES imagery in development of <span class="hlt">cloud</span> cover data base for insolation assessment</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Huning, J. R.; Logan, T. L.; Smith, J. H.</p> <p>1982-01-01</p> <p>The potential of using digital satellite data to establish a <span class="hlt">cloud</span> cover data base for the United States, one that would provide detailed information on the temporal and spatial variability of <span class="hlt">cloud</span> development are studied. Key elements include: (1) interfacing GOES data from the University of Wisconsin Meteorological Data Facility with the Jet Propulsion Laboratory's VICAR image processing system and IBIS geographic information system; (2) creation of a registered multitemporal GOES data base; (3) development of a simple normalization model to compensate for sun angle; (4) creation of a variable size georeference grid that provides detailed <span class="hlt">cloud</span> information in selected areas and summarized information in other areas; and (5) development of a <span class="hlt">cloud</span>/shadow model which details the percentage of each grid cell that is <span class="hlt">cloud</span> and shadow covered, and the percentage of <span class="hlt">cloud</span> or shadow opacity. In addition, comparison of model calculations of insolation with measured values at selected test sites was accomplished, as well as development of preliminary requirements for a large scale data base of <span class="hlt">cloud</span> cover statistics.</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 identifying 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 identify 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/2003ApJ...590..895W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2003ApJ...590..895W"><span>Two Molecular <span class="hlt">Clouds</span> near M17</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wilson, T. L.; Hanson, M. M.; Muders, D.</p> <p>2003-06-01</p> <p>We present fully sampled images in the C18O J=2-1 line extending over 13'×23', made with the Heinrich Hertz Telescope (HHT) on Mount Graham, AZ. The HHT has a resolution of 35" at the line frequency. This region includes two molecular <span class="hlt">clouds</span>. <span class="hlt">Cloud</span> A, to the north, is more compact, while <span class="hlt">cloud</span> B is to the west of the H II region M17. <span class="hlt">Cloud</span> B contains the well-known source M17SW. In C18O we find 13 maxima in <span class="hlt">cloud</span> A and 39 in <span class="hlt">cloud</span> B. Sixteen sources in <span class="hlt">cloud</span> B are in M17SW, mapped previously with higher resolution. In <span class="hlt">cloud</span> B, sources outside M17SW have line widths comparable to those in M17SW. In comparison, <span class="hlt">cloud</span> A has lower C18O line intensities and smaller line widths but comparable densities and sizes. Maps of the cores of these <span class="hlt">clouds</span> were also obtained in the J=5-4 line of CS, which traces higher H2 densities. Our images of the cores of <span class="hlt">clouds</span> A and B show that for VLSR<=20 km s-1, the peaks of the CS emission are shifted closer to the H II region than the C18O maxima, so higher densities are found toward the H II region. Our CS data give additional support to the already strong evidence that M17SW and nearby regions are heated and compressed by the H II region. Our data show that <span class="hlt">cloud</span> A has a smaller interaction with the H II region. We surmise that M17SW was an initially denser region, and the turn-on of the H II region will make this the next region of massive star formation. Outside of M17SW, the only other obvious star formation region may be in <span class="hlt">cloud</span> A, since there is an intense millimeter dust continuum peak found by Henning et al. (1998) but no corresponding C18O maximum. If the CO/H2 ratio is constant, the dust must have a temperature of ~100 K or the H2 density is greater than 106 cm-3 or both to reconcile the C18O and dust data. Alternatively, if the CO/H2 ratio is low, perhaps much of the CO is depleted.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20080024183','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20080024183"><span>Evaluation and Applications of <span class="hlt">Cloud</span> Climatologies from CALIOP</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Winker, David; Getzewitch, Brian; Vaughan, Mark</p> <p>2008-01-01</p> <p><span class="hlt">Clouds</span> have a major impact on the Earth radiation budget and differences in the representation of <span class="hlt">clouds</span> in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing <span class="hlt">cloud</span> climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous <span class="hlt">cloud</span> and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average <span class="hlt">cloud</span> cover measured by CALIOP is about 75%, significantly higher than for existing <span class="hlt">cloud</span> climatologies due to the sensitivity of CALIOP to optically thin <span class="hlt">cloud</span>. Day/night biases in <span class="hlt">cloud</span> detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a <span class="hlt">cloud</span> climatology, characteristics of <span class="hlt">cloud</span> cover statistics derived from CALIOP data, and applications of those statistics.</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 identified 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://adsabs.harvard.edu/abs/2013APS..DFDM23007S','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2013APS..DFDM23007S"><span>Laboratory study of orographic <span class="hlt">cloud</span>-like flow</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Singh, Kanwar Nain; Sreenivas, K. R.</p> <p>2013-11-01</p> <p><span class="hlt">Clouds</span> are one of the major sources of uncertainty in climate prediction, listed in ``the most urgent scientific problems requiring attention'' IPCC. Also, convective <span class="hlt">clouds</span> are of utmost importance to study the dynamics of tropical meteorology and therefore, play a key role in understanding monsoons. The present work is to study the dynamics of orographic <span class="hlt">clouds</span>. Parameterization of these <span class="hlt">clouds</span> will help in forecasting the precipitation accurately. Also, one could validate laboratory results from our study by actually measuring <span class="hlt">cloud</span> development along a sloping terrain. In this context a planar buoyant turbulent wall jet is considered as an appropriate low order fluid-dynamical model for studying the turbulence and entrainment in orographic-<span class="hlt">clouds</span>. Flow is volumetrically heated to mimic the latent heat release due to condensation in an actual <span class="hlt">cloud</span>. This is the first step in studying the entrainment dynamics of the evolving orographic <span class="hlt">cloud</span>. We are going to present some results on the <span class="hlt">cloud</span> development using techniques that allows us to construct a 3-dimensional flow field at each instance and its development over the time. By combining velocity field from PIV and flow volume from PLIF at successive instances, we estimate the entrainment coefficient. Since the life-cycle of a <span class="hlt">cloud</span> is determined by the entrainment of ambient air, these results could be extremely helpful in understanding the dynamics of the <span class="hlt">clouds</span>. Detailed results will be presented at the conference.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/biblio/1252820-wind-speed-response-marine-non-precipitating-stratocumulus-clouds-over-diurnal-cycle-cloud-system-resolving-simulations','SCIGOV-STC'); return false;" href="https://www.osti.gov/biblio/1252820-wind-speed-response-marine-non-precipitating-stratocumulus-clouds-over-diurnal-cycle-cloud-system-resolving-simulations"><span>Wind speed response of marine non-precipitating stratocumulus <span class="hlt">clouds</span> over a diurnal cycle in <span class="hlt">cloud</span>-system resolving simulations</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>Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu</p> <p></p> <p>Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine stratocumulus <span class="hlt">clouds</span> and their radiative properties respond to changes in large-scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum and thereby acts on <span class="hlt">cloud</span> liquid water path (LWP) and <span class="hlt">cloud</span> radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus <span class="hlt">clouds</span> to different wind speeds over the course of a diurnal cycle, all else equal. In <span class="hlt">cloud</span>-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and strongermore » entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in <span class="hlt">cloud</span> updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning–afternoon contrast. The higher LWP at higher wind speed does not, however, enhance <span class="hlt">cloud</span> top cooling because in <span class="hlt">clouds</span> with LWP ≳50 gm –2, longwave emissions are insensitive to LWP. This leads to the general conclusion that in sufficiently thick stratocumulus <span class="hlt">clouds</span>, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in <span class="hlt">cloud</span> updrafts, rather than from enhanced longwave cooling. Here, we find that large-scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment and in part because shear from large-scale wind in the sub-<span class="hlt">cloud</span> layer hinders vertical moisture transport between the surface and <span class="hlt">cloud</span> base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large-scale wind takes over from</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://www.osti.gov/pages/biblio/1252820-wind-speed-response-marine-non-precipitating-stratocumulus-clouds-over-diurnal-cycle-cloud-system-resolving-simulations','SCIGOV-DOEP'); return false;" href="https://www.osti.gov/pages/biblio/1252820-wind-speed-response-marine-non-precipitating-stratocumulus-clouds-over-diurnal-cycle-cloud-system-resolving-simulations"><span>Wind speed response of marine non-precipitating stratocumulus <span class="hlt">clouds</span> over a diurnal cycle in <span class="hlt">cloud</span>-system resolving simulations</span></a></p> <p><a target="_blank" href="http://www.osti.gov/pages">DOE PAGES</a></p> <p>Kazil, Jan; Feingold, Graham; Yamaguchi, Takanobu</p> <p>2016-05-12</p> <p>Observed and projected trends in large-scale wind speed over the oceans prompt the question: how do marine stratocumulus <span class="hlt">clouds</span> and their radiative properties respond to changes in large-scale wind speed? Wind speed drives the surface fluxes of sensible heat, moisture, and momentum and thereby acts on <span class="hlt">cloud</span> liquid water path (LWP) and <span class="hlt">cloud</span> radiative properties. We present an investigation of the dynamical response of non-precipitating, overcast marine stratocumulus <span class="hlt">clouds</span> to different wind speeds over the course of a diurnal cycle, all else equal. In <span class="hlt">cloud</span>-system resolving simulations, we find that higher wind speed leads to faster boundary layer growth and strongermore » entrainment. The dynamical driver is enhanced buoyant production of turbulence kinetic energy (TKE) from latent heat release in <span class="hlt">cloud</span> updrafts. LWP is enhanced during the night and in the morning at higher wind speed, and more strongly suppressed later in the day. Wind speed hence accentuates the diurnal LWP cycle by expanding the morning–afternoon contrast. The higher LWP at higher wind speed does not, however, enhance <span class="hlt">cloud</span> top cooling because in <span class="hlt">clouds</span> with LWP ≳50 gm –2, longwave emissions are insensitive to LWP. This leads to the general conclusion that in sufficiently thick stratocumulus <span class="hlt">clouds</span>, additional boundary layer growth and entrainment due to a boundary layer moistening arises by stronger production of TKE from latent heat release in <span class="hlt">cloud</span> updrafts, rather than from enhanced longwave cooling. Here, we find that large-scale wind modulates boundary layer decoupling. At nighttime and at low wind speed during daytime, it enhances decoupling in part by faster boundary layer growth and stronger entrainment and in part because shear from large-scale wind in the sub-<span class="hlt">cloud</span> layer hinders vertical moisture transport between the surface and <span class="hlt">cloud</span> base. With increasing wind speed, however, in decoupled daytime conditions, shear-driven circulation due to large-scale wind takes over from</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2018JQSRT.214...39M','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2018JQSRT.214...39M"><span>Vertical profile of <span class="hlt">cloud</span> optical parameters derived from airborne measurements above, inside and below <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>Melnikova, Irina; Gatebe, Charles K.</p> <p>2018-07-01</p> <p>Past strategies for retrieving <span class="hlt">cloud</span> optical properties from remote sensing assumed significant limits for desired parameters such as semi-infinite optical thickness, single scattering albedo equaling unity (non-absorbing scattering), absence of spectral dependence of the optical thickness, etc., and only one optical parameter could be retrieved (either optical thickness or single scattering albedo). Here, we demonstrate a new method based on asymptotic theory for thick atmospheres, and the presence of a diffusion domain within the <span class="hlt">clouds</span> that does not put restrictions and makes it possible to get two or even three optical parameters (optical thickness, single scattering albedo and phase function asymmetry parameter) for every wavelength independently. We applied this method to measurements of angular distribution of solar radiation above, inside and below <span class="hlt">clouds</span>, obtained with NASA's <span class="hlt">Cloud</span> Absorption Radiometer (CAR) over two cases of marine stratocumulus <span class="hlt">clouds</span>; first case, offshore of Namibia and the second case, offshore of California. The observational and retrieval errors are accounted for by regularization, which allows stable and smooth solutions. Results show good potential for parameterization of the shortwave radiative properties (reflection, transmission, radiative divergence and heating rate) of water <span class="hlt">clouds</span>.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA21841.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA21841.html"><span><span class="hlt">Clouds</span> Sailing Overhead on Mars, Enhanced</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2017-08-09</p> <p>Wispy <span class="hlt">clouds</span> float across the Martian sky in this accelerated sequence of enhanced images from NASA's Curiosity Mars rover. The rover's Navigation Camera (Navcam) took these eight images over a span of four minutes early in the morning of the mission's 1,758th Martian day, or sol (July 17, 2017), aiming nearly straight overhead. They have been processed by first making a "flat field' adjustment for known differences in sensitivity among pixels and correcting for camera artifacts due to light reflecting within the camera, and then generating an "average" of all the frames and subtracting that average from each frame. This subtraction results in emphasizing any changes due to movement or lighting. The <span class="hlt">clouds</span> are also visible, though fainter, in a raw image sequence from these same observations. On the same Martian morning, Curiosity also observed <span class="hlt">clouds</span> near the southern horizon. The <span class="hlt">clouds</span> resemble Earth's cirrus <span class="hlt">clouds</span>, which are ice crystals at high altitudes. These Martian <span class="hlt">clouds</span> are likely composed of crystals of water ice that condense onto dust grains in the cold Martian atmosphere. Cirrus wisps appear as ice crystals fall and evaporate in patterns known as "fall streaks" or "mare's tails." Such patterns have been seen before at high latitudes on Mars, for instance by the Phoenix Mars Lander in 2008, and seasonally nearer the equator, for instance by the Opportunity rover. However, Curiosity has not previously observed such <span class="hlt">clouds</span> so clearly visible from the rover's study area about five degrees south of the equator. The Hubble Space Telescope and spacecraft orbiting Mars have observed a band of <span class="hlt">clouds</span> to appear near the Martian equator around the time of the Martian year when the planet is farthest from the Sun. With a more elliptical orbit than Earth's, Mars experiences more annual variation than Earth in its distance from the Sun. The most distant point in an orbit around the Sun is called the aphelion. The near-equatorial Martian <span class="hlt">cloud</span> pattern observed at</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017DPS....4930412C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017DPS....4930412C"><span>A Report of <span class="hlt">Clouds</span> on Titan</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Corlies, Paul; Hayes, Alexander; Adamkovics, Mate; Rodriguez, Sebastien; Kelland, John; Turtle, Elizabeth P.; Mitchell, Jonathan; Lora, Juan M.; Rojo, Patricio; Lunine, Jonathan I.</p> <p>2017-10-01</p> <p>We present in this work a detailed analysis of many of the <span class="hlt">clouds</span> in the Cassini Visual and Infrared Mapping Spectrometer (VIMS) dataset in order to understand their global and seasonal properties. <span class="hlt">Clouds</span> are one of the few direct observables in Titan’s atmosphere (Griffith et al 2009, Rodriguez et al 2009, Adamkovics et al 2010), and so determining their characteristics allows for a better understanding of surface atmosphere interactions, winds, transport of volatile material, and general circulation. We find the <span class="hlt">clouds</span> on Titan generally reside in at 5-15km altitude, which agrees with previous modelling efforts (Rafkin et al. 2015), as well as a power law distribution for <span class="hlt">cloud</span> optical depth. We assume an average <span class="hlt">cloud</span> droplet size of 100um. No seasonal dependence is observed with either <span class="hlt">cloud</span> altitude or optical depth, suggesting there is no preferred seasonal formation mechanisms. Combining these characteristics with <span class="hlt">cloud</span> size (Kelland et al 2017) can trace the transport of volatiles in Titan’s atmosphere, which can be compared against general circulation models (GCMs) (Lora et al 2015). We also present some specific analysis of interesting <span class="hlt">cloud</span> systems including hypothesized surface fogs (Brown et al 2009) and orographic <span class="hlt">cloud</span> formation (Barth et al 2010, Corlies et al 2017). In this analysis we use a correlation between Cassini VIMS and RADAR observations as well as an updated topographic map of Titan’s southern hemisphere to better understand the role that topography plays in influencing and driving atmospheric phenomena.Finally, with the end of the Cassini mission, ground based observing now acts as the only means with which to observe <span class="hlt">clouds</span> on Titan. We present an update of an ongoing <span class="hlt">cloud</span> campaign to search for <span class="hlt">clouds</span> on Titan and to understand their seasonal evolution.References:Adamkovics et al. 2010, Icarus 208:868Barth et al. 2010, Planet. Space Sci. 58:1740Corlies et al. 2017, 48th LPSC, 2870CGriffith et al. 2009, ApJ 702:L105Kelland et al</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/19940030885','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/19940030885"><span>The effects of <span class="hlt">cloud</span> inhomogeneities upon radiative fluxes, and the supply of a <span class="hlt">cloud</span> truth validation dataset</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p></p> <p>1994-01-01</p> <p>With the growing awareness and debate over the potential changes associated with global climate change, the polar regions are receiving increased attention. Global <span class="hlt">cloud</span> distributions can be expected to be altered by increased greenhouse forcing. Owing to the similarity of <span class="hlt">cloud</span> and snow-ice spectral signatures in both the visible and infrared wavelengths, it is difficult to distinguish <span class="hlt">clouds</span> from surface features in the polar regions. This work is directed towards the development of algorithms for the ASTER and HIRIS science/instrument teams. Special emphasis is placed on a wide variety of <span class="hlt">cloud</span> optical property retrievals, and especially retrievals of <span class="hlt">cloud</span> and surface properties in the polar regions.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('https://images.nasa.gov/#/details-PIA08599.html','SCIGOVIMAGE-NASA'); return false;" href="https://images.nasa.gov/#/details-PIA08599.html"><span><span class="hlt">Cloud</span>Sat Overflight of Hurricane Bud</span></a></p> <p><a target="_blank" href="https://images.nasa.gov/">NASA Image and Video Library</a></p> <p></p> <p>2006-07-13</p> <p>The image at the top of figure 1 is from a geostationary imager. The colors relate to the temperature of the <span class="hlt">clouds</span>. The higher the <span class="hlt">clouds</span>, the lower the temperature. The highest, coldest <span class="hlt">clouds</span> are located near the center of the hurricane.</p> </li> <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 identify 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('https://ntrs.nasa.gov/search.jsp?R=20140006229&hterms=Polarized&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D20%26Ntt%3DPolarized','NASA-TRS'); return false;" href="https://ntrs.nasa.gov/search.jsp?R=20140006229&hterms=Polarized&qs=Ntx%3Dmode%2Bmatchall%26Ntk%3DTitle%26N%3D0%26No%3D20%26Ntt%3DPolarized"><span>Detecting Super-Thin <span class="hlt">Clouds</span> With Polarized Light</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun, Wenbo; Videen, Gorden; Mishchenko, Michael I.</p> <p>2014-01-01</p> <p>We report a novel method for detecting <span class="hlt">cloud</span> particles in the atmosphere. Solar radiation backscattered from <span class="hlt">clouds</span> is studied with both satellite data and a radiative transfer model. A distinct feature is found in the angle of linear polarization of solar radiation that is backscattered from <span class="hlt">clouds</span>. The dominant backscattered electric field from the clear-sky Earth-atmosphere system is nearly parallel to the Earth surface. However, when <span class="hlt">clouds</span> are present, this electric field can rotate significantly away from the parallel direction. Model results demonstrate that this polarization feature can be used to detect super-thin cirrus <span class="hlt">clouds</span> having an optical depth of only 0.06 and super-thin liquid water <span class="hlt">clouds</span> having an optical depth of only 0.01. Such <span class="hlt">clouds</span> are too thin to be sensed using any current passive satellite instruments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://hdl.handle.net/2060/20150002153','NASA-TRS'); return false;" href="http://hdl.handle.net/2060/20150002153"><span>Detecting Super-Thin <span class="hlt">Clouds</span> with Polarized Sunlight</span></a></p> <p><a target="_blank" href="http://ntrs.nasa.gov/search.jsp">NASA Technical Reports Server (NTRS)</a></p> <p>Sun, Wenbo; Videen, Gorden; Mishchenko, Michael I.</p> <p>2014-01-01</p> <p>We report a novel method for detecting <span class="hlt">cloud</span> particles in the atmosphere. Solar radiation backscattered from <span class="hlt">clouds</span> is studied with both satellite data and a radiative transfer model. A distinct feature is found in the angle of linear polarization of solar radiation that is backscattered from <span class="hlt">clouds</span>. The dominant backscattered electric field from the clear-sky Earth-atmosphere system is nearly parallel to the Earth surface. However, when <span class="hlt">clouds</span> are present, this electric field can rotate significantly away from the parallel direction. Model results demonstrate that this polarization feature can be used to detect super-thin cirrus <span class="hlt">clouds</span> having an optical depth of only 0.06 and super-thin liquid water <span class="hlt">clouds</span> having an optical depth of only 0.01. Such <span class="hlt">clouds</span> are too thin to be sensed using any current passive satellite instruments.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017AGUFM.A52H..05C','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017AGUFM.A52H..05C"><span>The use of marine <span class="hlt">cloud</span> water samples as a diagnostic tool for aqueous chemistry, <span class="hlt">cloud</span> microphysical processes and dynamics</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Crosbie, E.; Ziemba, L. D.; Moore, R.; Shook, M.; Jordan, C.; Thornhill, K. L., II; Winstead, E.; Shingler, T.; Brown, M.; MacDonald, A. B.; Dadashazar, H.; Sorooshian, A.; Weiss-Penzias, P. S.; Anderson, B.</p> <p>2017-12-01</p> <p><span class="hlt">Clouds</span> play several roles in the Earth's climate system. In addition to their clear significance to the hydrological cycle, they strongly modulate the shortwave and longwave radiative balance of the atmosphere, with subsequent feedback on the atmospheric circulation. Furthermore, <span class="hlt">clouds</span> act as a conduit for the fate and emergence of important trace chemical species and are the predominant removal mechanism for atmospheric aerosols. Marine boundary layer <span class="hlt">clouds</span> cover large swaths of the global oceans. Because of their global significance, they have attracted significant attention into understanding how changes in aerosols are translated into changes in <span class="hlt">cloud</span> macro- and microphysical properties. The circular nature of the influence of <span class="hlt">clouds</span>-on-aerosols and aerosols-on-<span class="hlt">clouds</span> has been used to explain the chaotic patterns often seen in marine <span class="hlt">clouds</span>, however, this feedback also presents a substantial hurdle in resolving the uncertain role of anthropogenic aerosols on climate. Here we discuss ways in which the chemical constituents found in <span class="hlt">cloud</span> water can offer insight into the physical and chemical processes inherent in marine <span class="hlt">clouds</span>, through the use of aircraft measurements. We focus on observational data from <span class="hlt">cloud</span> water samples collected during flights conducted over the remote North Atlantic and along coastal California across multiple campaigns. We explore topics related to aqueous processing, wet scavenging and source apportionment.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2009LNCS.5931..460W','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2009LNCS.5931..460W"><span>Industrial <span class="hlt">Cloud</span>: Toward Inter-enterprise Integration</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Wlodarczyk, Tomasz Wiktor; Rong, Chunming; Thorsen, Kari Anne Haaland</p> <p></p> <p>Industrial <span class="hlt">cloud</span> is introduced as a new inter-enterprise integration concept in <span class="hlt">cloud</span> computing. The characteristics of an industrial <span class="hlt">cloud</span> are given by its definition and architecture and compared with other general <span class="hlt">cloud</span> concepts. The concept is then demonstrated by a practical use case, based on Integrated Operations (IO) in the Norwegian Continental Shelf (NCS), showing how industrial digital information integration platform gives competitive advantage to the companies involved. Further research and development challenges are also discussed.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2017JPhCS.898e2008T','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2017JPhCS.898e2008T"><span>Consolidation of <span class="hlt">cloud</span> computing in ATLAS</span></a></p> <p><a target="_blank" href="http://adsabs.harvard.edu/abstract_service.html">NASA Astrophysics Data System (ADS)</a></p> <p>Taylor, Ryan P.; Domingues Cordeiro, Cristovao Jose; Giordano, Domenico; Hover, John; Kouba, Tomas; Love, Peter; McNab, Andrew; Schovancova, Jaroslava; Sobie, Randall; ATLAS Collaboration</p> <p>2017-10-01</p> <p>Throughout the first half of LHC Run 2, ATLAS <span class="hlt">cloud</span> computing has undergone a period of consolidation, characterized by building upon previously established systems, with the aim of reducing operational effort, improving robustness, and reaching higher scale. This paper describes the current state of ATLAS <span class="hlt">cloud</span> computing. <span class="hlt">Cloud</span> activities are converging on a common contextualization approach for virtual machines, and <span class="hlt">cloud</span> resources are sharing monitoring and service discovery components. We describe the integration of Vacuum resources, streamlined usage of the Simulation at Point 1 <span class="hlt">cloud</span> for offline processing, extreme scaling on Amazon compute resources, and procurement of commercial <span class="hlt">cloud</span> capacity in Europe. Finally, building on the previously established monitoring infrastructure, we have deployed a real-time monitoring and alerting platform which coalesces data from multiple sources, provides flexible visualization via customizable dashboards, and issues alerts and carries out corrective actions in response to problems.</p> </li> <li> <p><a target="_blank" onclick="trackOutboundLink('http://adsabs.harvard.edu/abs/2007AstHe.100....8H','NASAADS'); return false;" href="http://adsabs.harvard.edu/abs/2007AstHe.100....8H"><span>Origin and Evolution of Comet <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>Higuchi, Arika</p> <p>2007-01-01</p> <p>The Oort <span class="hlt">cloud</span> (comet <span class="hlt">cloud</span>) is a spherical comet reservoir surrounding a planetary system. We have investigated the comet <span class="hlt">cloud</span> formation that consists of two dynamical stages of orbital evolution of planetesimals due to (1) planetary perturbation, and (2) the galactic tide. We investigated the first stage by using numerical calculations and obtained the probabilities of the fates of planetesimals as functions of the orbital parameters of the planets and planetesimals. We investigated the second stage by using the secular perturbation theory and showed the evolution of the structure of a comet <span class="hlt">cloud</span> from a planetesimal disk. We found that (1) massive planets effectively produce comet <span class="hlt">cloud</span> candidates by scattering and (2) many planetesimals with semimajor axes larger than 1,000 AU rise up their perihelion distances to the outside of the planetary region and become members of the Oort <span class="hlt">cloud</span> in 5 Gyr.</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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