WorldWideScience

Sample records for sensing model cloud

  1. Clouds, Wind and the Biogeography of Central American Cloud Forests: Remote Sensing, Atmospheric Modeling, and Walking in the Jungle

    Science.gov (United States)

    Lawton, R.; Nair, U. S.

    2011-12-01

    Cloud 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 cloud forests are generally defined by frequent and prolonged immersion in cloud, workers differ in their feelings about "frequent" and "prolonged", and quantitative assessments are rare. Here we focus on the dry season, in which the cloud and mist from orographic cloud plays a critical role in forest water relations, and discuss remote sensing of orographic clouds, and regional and atmospheric modeling at several scales to quantitatively examine the distribution of the atmospheric conditions that characterize cloud forests. Remote sensing using data from GOES reveals diurnal and longer scale patterns in the distribution of dry season orographic clouds in Central America at both regional and local scales. Data from MODIS, used to calculate the base height of orographic cloud banks, reveals not only the geographic distributon of cloud forest sites, but also striking regional variation in the frequency of montane immersion in orographic cloud. 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 cloud forests of Costa Rica provides quantitative information on the spatial distribution of canopy level winds, insight into the spatial structure and local dynamics of cloud 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 cloud forests to global and regional climate changes.

  2. An Efficient Interactive Model for On-Demand Sensing-As-A-Servicesof Sensor-Cloud

    Directory of Open Access Journals (Sweden)

    Thanh Dinh

    2016-06-01

    Full Text Available This paper proposes an efficient interactive model for the sensor-cloud to enable the sensor-cloud to efficiently provide on-demand sensing services for multiple applications with different requirements at the same time. The interactive model is designed for both the cloud and sensor nodes to optimize the resource consumption of physical sensors, as well as the bandwidth consumption of sensing traffic. In the model, the sensor-cloud plays a key role in aggregating application requests to minimize the workloads required for constrained physical nodes while guaranteeing that the requirements of all applications are satisfied. Physical sensor nodes perform their sensing under the guidance of the sensor-cloud. Based on the interactions with the sensor-cloud, physical sensor nodes adapt their scheduling accordingly to minimize their energy consumption. Comprehensive experimental results show that our proposed system achieves a significant improvement in terms of the energy consumption of physical sensors, the bandwidth consumption from the sink node to the sensor-cloud, the packet delivery latency, reliability and scalability, compared to current approaches. Based on the obtained results, we discuss the economical benefits and how the proposed system enables a win-win model in the sensor-cloud.

  3. Satellite remote sensing and cloud modeling of St. Anthony, Minnesota storm clouds and dew point depression

    Science.gov (United States)

    Hung, R. J.; Tsao, Y. D.

    1988-01-01

    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 clouds, with overshooting cloud 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 cloud tops penetrating the tropopause. It is also found that there is less chance for clouds with a lower moisture content to be outgrown as a storm cloud than clouds with a higher moisture content.

  4. Ice formation in altocumulus clouds over Leipzig: Remote sensing measurements and detailed model simulations

    Science.gov (United States)

    Simmel, Martin; Bühl, Johannes; Ansmann, Albert; Tegen, Ina

    2014-05-01

    Over Leipzig, altocumulus clouds are frequently observed using a suite of remote sensing instruments. These observations cover a wide range of heights, temperatures, and microphysical properties of the clouds ranging from purely liquid to heavily frozen. For the current study, two cases were chosen to test the sensitivity of these clouds with respect to several microphysical and dynamical parameters such as aerosol properties (CCN, IN), ice particle shape as well as turbulence. The mixed-phase spectral microphysical model SPECS was coupled to a dynamical model of the Asai-Kasahara type resulting in the model system AK-SPECS. The relatively simple dynamics allows for a fine vertical resolution needed for the rather shallow cloud layers observed. Additionally, the proper description of hydrometeor sedimentation is important especially for the fast growing ice crystals to realistically capture their interaction with the vapour and liquid phase (Bergeron-Findeisen process). Since the focus is on the cloud microphysics, the dynamics in terms of vertical velocity profile is prescribed for the model runs and the feedback of the microphysics on dynamics by release or consumption of latent heat due to phase transfer is not taken into account. The microphysics focuses on (1) ice particle shape allowing hexagonal plates and columns with size-dependant axis ratios and (2) the ice nuclei (IN) budget realized with a prognostic temperature resolved field of potential IN allowing immersion freezing only when active IN and supercooled drops above a certain size threshold are present within a grid cell. Sensitivity studies show for both cases that ice particle shape seems to have the major influence on ice mass formation under otherwise identical conditions. This is due to the effect (1) on terminal fall velocity of the individual ice particle allowing for longer presence times in conditions supersaturated with respect to ice and (2) on water vapour deposition which is enhanced due

  5. Modeling of Cloud/Radiation Processes for Cirrus Cloud Formation

    National Research Council Canada - National Science Library

    Liou, K

    1997-01-01

    This technical report includes five reprints and pre-prints of papers associated with the modeling of cirrus cloud and radiation processes as well as remote sensing of cloud optical and microphysical...

  6. Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

    Science.gov (United States)

    Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

    2013-01-01

    In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

  7. Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

    Science.gov (United States)

    Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

    2017-04-01

    The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

  8. Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

    Science.gov (United States)

    Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

    2016-07-01

    The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to

  9. Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

    Science.gov (United States)

    Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

    2016-01-01

    The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to

  10. Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow

    Science.gov (United States)

    Simpson, James J.; Dettinger, M.D.; Gehrke, F.; McIntire, T.J.; Hufford, Gary L.

    2004-01-01

    Accurate prediction of available water supply from snowmelt is needed if the myriad of human, environmental, agricultural, and industrial demands for water are to be satisfied, especially given legislatively imposed conditions on its allocation. Robust retrievals of hydrologic basin model variables (e.g., insolation or areal extent of snow cover) provide several advantages over the current operational use of either point measurements or parameterizations to help to meet this requirement. Insolation can be provided at hourly time scales (or better if needed during rapid melt events associated with flooding) and at 1-km spatial resolution. These satellite-based retrievals incorporate the effects of highly variable (both in space and time) and unpredictable cloud cover on estimates of insolation. The insolation estimates are further adjusted for the effects of basin topography using a high-resolution digital elevation model prior to model input. Simulations of two Sierra Nevada rivers in the snowmelt seasons of 1998 and 1999 indicate that even the simplest improvements in modeled insolation can improve snowmelt simulations, with 10%-20% reductions in root-mean-square errors. Direct retrieval of the areal extent of snow cover may mitigate the need to rely entirely on internal calculations of this variable, a reliance that can yield large errors that are difficult to correct until long after the season is complete and that often leads to persistent underestimates or overestimates of the volumes of the water to operational reservoirs. Agencies responsible for accurately predicting available water resources from the melt of snowpack [e.g., both federal (the National Weather Service River Forecast Centers) and state (the California Department of Water Resources)] can benefit by incorporating concepts developed herein into their operational forecasting procedures. ?? 2004 American Meteorological Society.

  11. Insights on the Feasibility, Modeling and Field Testing of Cirrus Cloud Thinning from Satellite Remote Sensing

    Science.gov (United States)

    Mitchell, D. L.; Garnier, A.; Mejia, J.; Avery, M. A.; Erfani, E.

    2016-12-01

    To date, it is not clear whether the climate intervention method known as cirrus cloud thinning (CCT) can be viable since it requires cirrus clouds to form through homogeneous ice nucleation (henceforth hom) and some recent GCM studies predict cirrus are formed primarily through heterogeneous ice nucleation (henceforth het). A new CALIPSO infrared retrieval method has been developed for single-layer cirrus cloud that measures the temperature dependence of their layer-averaged number concentration N, effective diameter De and ice water content for optical depths (OD) between 0.3 and 3.0. Based on N, the prevailing ice nucleation mechanism (hom or het) can be estimated as a function of temperature, season, latitude and surface type. These satellite results indicate that seeding cirrus clouds at high latitudes during winter may produce significant global surface cooling. This is because hom often appears to dominate over land during winter north of 30°N latitude while the same appears true for most of the Southern Hemisphere (south of 30°S) during all seasons. Moreover, the sampled cirrus cloud frequency of occurrence in the Arctic is at least twice as large during winter relative to other seasons, while frequency of occurrence in the Antarctic peaks in the spring and is second-highest during winter. During Arctic winter, a combination of frequent hom cirrus, maximum cirrus coverage and an extreme or absent sun angle produces the maximum seasonal cirrus net radiative forcing (warming). Thus a reduction in OD and coverage (via CCT) for these cirrus clouds could yield a significant net cooling effect. From these CALIPSO retrievals, De-T relationships are generated as a function of season, latitude and surface type (land vs. ocean). These will be used in CAM5 to estimate De and the ice fall speed, from which the cirrus radiative forcing will be estimated during winter north of 30°latitude, where hom cirrus are common. Another CAM5 simulation will replace the hom

  12. Cloud Computing, Tieto Cloud Server Model

    OpenAIRE

    Suikkanen, Saara

    2013-01-01

    The purpose of this study is to find out what is cloud computing. To be able to make wise decisions when moving to cloud or considering it, companies need to understand what cloud is consists of. Which model suits best to they company, what should be taken into account before moving to cloud, what is the cloud broker role and also SWOT analysis of cloud? To be able to answer customer requirements and business demands, IT companies should develop and produce new service models. IT house T...

  13. Remote sensing image segmentation based on Hadoop cloud platform

    Science.gov (United States)

    Li, Jie; Zhu, Lingling; Cao, Fubin

    2018-01-01

    To solve the problem that the remote sensing image segmentation speed is slow and the real-time performance is poor, this paper studies the method of remote sensing image segmentation based on Hadoop platform. On the basis of analyzing the structural characteristics of Hadoop cloud platform and its component MapReduce programming, this paper proposes a method of image segmentation based on the combination of OpenCV and Hadoop cloud platform. Firstly, the MapReduce image processing model of Hadoop cloud platform is designed, the input and output of image are customized and the segmentation method of the data file is rewritten. Then the Mean Shift image segmentation algorithm is implemented. Finally, this paper makes a segmentation experiment on remote sensing image, and uses MATLAB to realize the Mean Shift image segmentation algorithm to compare the same image segmentation experiment. The experimental results show that under the premise of ensuring good effect, the segmentation rate of remote sensing image segmentation based on Hadoop cloud Platform has been greatly improved compared with the single MATLAB image segmentation, and there is a great improvement in the effectiveness of image segmentation.

  14. Retrieval of liquid water cloud properties from ground-based remote sensing observations

    NARCIS (Netherlands)

    Knist, C.L.

    2014-01-01

    Accurate ground-based remotely sensed microphysical and optical properties of liquid water clouds are essential references to validate satellite-observed cloud properties and to improve cloud parameterizations in weather and climate models. This requires the evaluation of algorithms for retrieval of

  15. Enterprise Cloud Adoption - Cloud Maturity Assessment Model

    OpenAIRE

    Conway, Gerry; Doherty, Eileen; Carcary, Marian; Crowley, Catherine

    2017-01-01

    The introduction and use of cloud computing by an organization has the promise of significant benefits that include reduced costs, improved services, and a pay-per-use model. Organizations that successfully harness these benefits will potentially have a distinct competitive edge, due to their increased agility and flexibility to rapidly respond to an ever changing and complex business environment. However, as cloud technology is a relatively new ph...

  16. Remote Sensing of Crystal Shapes in Ice Clouds

    Science.gov (United States)

    van Diedenhoven, Bastiaan

    2017-01-01

    Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally

  17. Toward the Characterization of Mixed-Phase Clouds Using Remote Sensing

    Science.gov (United States)

    Andronache, C.

    2015-12-01

    Mixed-phase clouds consist of a mixture of ice particles and liquid droplets at temperatures below 0 deg C. They are present in all seasons in many regions of the world, account for about 30% of the global cloud coverage, and are linked to cloud electrification and aircraft icing. The mix of ice particles, liquid droplets, and water vapor is unstable, and such clouds are thought to have a short lifetime. A characteristic parameter is the phase composition of mixed-phase clouds. It affects the cloud life cycle and the rate of precipitation. This parameter is important for cloud parameters retrievals by radar, lidar, and satellite and is relevant for climate modeling. The phase transformation includes the remarkable Wegener-Bergeron-Findeisen (WBF) process. The direction and the rate of the phase transformations depend on the local thermodynamic and microphysical properties. Cloud condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and the dynamic response of clouds to aerosols. The complexity of dynamics and microphysics involved in mixed-phase clouds requires a set of observational and modeling tools that continue to be refined. Among these techniques, the remote sensing methods provide an increasing number of parameters, covering large regions of the world. Thus, a series of studies were dedicated to stratiform mixed-phase clouds revealing longer lifetime than previously thought. Satellite data and aircraft in situ measurements in deep convective clouds suggest that highly supercooled water often occurs in vigorous continental convective storms. In this study, we use cases of convective clouds to discuss the feasibility of mixed-phase clouds characterization and potential advantages of remote sensing.

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

    Science.gov (United States)

    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.

  19. Cloud Robotics Model

    OpenAIRE

    Mester, Gyula

    2015-01-01

    Cloud Robotics was born from the merger of service robotics and cloud technologies. It allows robots to benefit from the powerful computational, storage, and communications resources of modern data centres. Cloud robotics allows robots to take advantage of the rapid increase in data transfer rates to offload tasks without hard real time requirements. Cloud Robotics has rapidly gained momentum with initiatives by companies such as Google, Willow Garage and Gostai as well as more than a dozen a...

  20. An Uneven Illumination Correction Algorithm for Optical Remote Sensing Images Covered with Thin Clouds

    Directory of Open Access Journals (Sweden)

    Xiaole Shen

    2015-09-01

    Full Text Available The uneven illumination phenomenon caused by thin clouds will reduce the quality of remote sensing images, and bring adverse effects to the image interpretation. To remove the effect of thin clouds on images, an uneven illumination correction can be applied. In this paper, an effective uneven illumination correction algorithm is proposed to remove the effect of thin clouds and to restore the ground information of the optical remote sensing image. The imaging model of remote sensing images covered by thin clouds is analyzed. Due to the transmission attenuation, reflection, and scattering, the thin cloud cover usually increases region brightness and reduces saturation and contrast of the image. As a result, a wavelet domain enhancement is performed for the image in Hue-Saturation-Value (HSV color space. We use images with thin clouds in Wuhan area captured by QuickBird and ZiYuan-3 (ZY-3 satellites for experiments. Three traditional uneven illumination correction algorithms, i.e., multi-scale Retinex (MSR algorithm, homomorphic filtering (HF-based algorithm, and wavelet transform-based MASK (WT-MASK algorithm are performed for comparison. Five indicators, i.e., mean value, standard deviation, information entropy, average gradient, and hue deviation index (HDI are used to analyze the effect of the algorithms. The experimental results show that the proposed algorithm can effectively eliminate the influences of thin clouds and restore the real color of ground objects under thin clouds.

  1. Satellite remote sensing of aerosol and cloud properties over Eurasia

    Science.gov (United States)

    Sogacheva, Larisa; Kolmonen, Pekka; Saponaro, Giulia; Virtanen, Timo; Rodriguez, Edith; Sundström, Anu-Maija; Atlaskina, Ksenia; de Leeuw, Gerrit

    2015-04-01

    Satellite remote sensing provides the spatial distribution of aerosol and cloud properties over a wide area. In our studies large data sets are used for statistical studies on aerosol and cloud interaction in an area over Fennoscandia, the Baltic Sea and adjacent regions over the European mainland. This area spans several regimes with different influences on aerosol cloud interaction such as a the transition from relative clean air over Fennoscandia to more anthropogenically polluted air further south, and the influence maritime air over the Baltic and oceanic air advected from the North Atlantic. Anthropogenic pollution occurs in several parts of the study area, and in particular near densely populated areas and megacities, but also in industrialized areas and areas with dense traffic. The aerosol in such areas is quite different from that produced over the boreal forest and has different effects on air quality and climate. Studies have been made on the effects of aerosols on air quality and on the radiation balance in China. The aim of the study is to study the effect of these different regimes on aerosol-cloud interaction using a large aerosol and cloud data set retrieved with the (Advanced) Along Track Scanning Radiometer (A)ATSR Dual View algorithm (ADV) further developed at Finnish Meteorological Institute and aerosol and cloud data provided by MODIS. Retrieval algorithms for aerosol and clouds have been developed for the (A)ATSR, consisting of a series of instruments of which we use the second and third one: ATSR-2 which flew on the ERS-2 satellite (1995-2003) and AATSR which flew on the ENVISAT satellite (2002-2012) (both from the European Space Agency, ESA). The ADV algorithm provides aerosol data on a global scale with a default resolution of 10x10km2 (L2) and an aggregate product on 1x1 degree (L3). Optional, a 1x1 km2 retrieval products is available over smaller areas for specific studies. Since for the retrieval of AOD no prior knowledge is needed on

  2. Business model elements impacting cloud computing adoption

    DEFF Research Database (Denmark)

    Bogataj, Kristina; Pucihar, Andreja; Sudzina, Frantisek

    The paper presents a proposed research framework for identification of business model elements impacting Cloud Computing Adoption. We provide a definition of main Cloud Computing characteristics, discuss previous findings on factors impacting Cloud Computing Adoption, and investigate technology a...

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Thanh Dinh

    2017-03-01

    Full Text Available 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.

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

    Science.gov (United States)

    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

  6. Introducing two Random Forest based methods for cloud detection in remote sensing images

    Science.gov (United States)

    Ghasemian, Nafiseh; Akhoondzadeh, Mehdi

    2018-07-01

    Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The

  7. Personal lifelong user model clouds

    DEFF Research Database (Denmark)

    Dolog, Peter; Kay, Judy; Kummerfeld, Bob

    This paper explores an architecture for very long term user modelling, based upon personal user model clouds. These ensure that the individual's applications can access their model whenever it is needed. At the same time, the user can control the use of their user model. So, they can ensure...... which combines both. Finally we discuss implications of our approach for consistency and freshness of the user model information....... it is accessed only when and where they wish, by applications that they wish. We consider the challenges of representing user models so that they can be reused by multiple applications. We indicate potential synergies between distributed and centralised user modelling architectures, proposing an architecture...

  8. Fuzzy AutoEncode Based Cloud Detection for Remote Sensing Imagery

    Directory of Open Access Journals (Sweden)

    Zhenfeng Shao

    2017-03-01

    Full Text Available Cloud detection of remote sensing imagery is quite challenging due to the influence of complicated underlying surfaces and the variety of cloud types. Currently, most of the methods mainly rely on prior knowledge to extract features artificially for cloud detection. However, these features may not be able to accurately represent the cloud characteristics under complex environment. In this paper, we adopt an innovative model named Fuzzy Autoencode Model (FAEM to integrate the feature learning ability of stacked autoencode networks and the detection ability of fuzzy function for highly accurate cloud detection on remote sensing imagery. Our proposed method begins by selecting and fusing spectral, texture, and structure information. Thereafter, the proposed technique established a FAEM to learn the deep discriminative features from a great deal of selected information. Finally, the learned features are mapped to the corresponding cloud density map with a fuzzy function. To demonstrate the effectiveness of the proposed method, 172 Landsat ETM+ images and 25 GF-1 images with different spatial resolutions are used in this paper. For the convenience of accuracy assessment, ground truth data are manually outlined. Results show that the average RER (ratio of right rate and error rate on Landsat images is greater than 29, while the average RER of Support Vector Machine (SVM is 21.8 and Random Forest (RF is 23. The results on GF-1 images exhibit similar performance as Landsat images with the average RER of 25.9, which is much higher than the results of SVM and RF. Compared to traditional methods, our technique has attained higher average cloud detection accuracy for either different spatial resolutions or various land surfaces.

  9. A Categorisation of Cloud Computing Business Models

    OpenAIRE

    Chang, Victor; Bacigalupo, David; Wills, Gary; De Roure, David

    2010-01-01

    This paper reviews current cloud computing business models and presents proposals on how organisations can achieve sustainability by adopting appropriate models. We classify cloud computing business models into eight types: (1) Service Provider and Service Orientation; (2) Support and Services Contracts; (3) In-House Private Clouds; (4) All-In-One Enterprise Cloud; (5) One-Stop Resources and Services; (6) Government funding; (7) Venture Capitals; and (8) Entertainment and Social Networking. U...

  10. Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

    Science.gov (United States)

    Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

    2010-01-01

    Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

  11. Examining the impact of overlying aerosols on the retrieval of cloud optical properties from passive remote sensing

    Science.gov (United States)

    Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

    2010-05-01

    Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space-based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below-aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol-induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 μm) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS-retrieved cloud optical thickness and effective radius can reach values of 10 and 10 μm, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

  12. Cloud forcing: A modeling perspective

    International Nuclear Information System (INIS)

    Potter, G.L.; Mobely, R.L.; Drach, R.S.; Corsetti, T.G.; Williams, D.N.; Slingo, J.M.

    1990-11-01

    Radiation fields from a perpetual July integration of a T106 version of the ECMWF operational model are used as surrogate observations of the radiation budget at the top of the atmosphere to illustrate various difficulties that modellers might face when trying to reconcile cloud radiation forcings derived from satellite observations with model-generated ones. Differences between the so-called Methods 1 and 2 of Cess and Potter (1987) and a variant Method 3 are addressed. Method 1 is shown to be the least robust of all methods, due to potential uncertainties related to persistent cloudiness, length of the period over which clear-sky conditions are looked for, biases in retrieved clear-sky quantities due to an insufficient sampling of the diurnal cycle. We advocate the use of Method 2 as the only unambiguous one to produce consistent radiative diagnostics for intercomparing model results. Impact of the three methods on the derived sensitivities and cloud feedbacks following an imposed change in sea surface temperature (used as a surrogate climate change) is discussed. 17 refs., 12 figs., 1 tab

  13. The application of time series models to cloud field morphology analysis

    Science.gov (United States)

    Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

    1987-01-01

    A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

  14. Modeling Incoherent Electron Cloud Effects

    International Nuclear Information System (INIS)

    Vay, Jean-Luc; Benedetto, E.; Fischer, W.; Franchetti, G.; Ohmi, K.; Schulte, D.; Sonnad, K.; Tomas, R.; Vay, J.-L.; Zimmermann, F.; Rumolo, G.; Pivi, M.; Raubenheimer, T.

    2007-01-01

    Incoherent electron effects could seriously limit the beam lifetime in proton or ion storage rings, such as LHC, SPS, or RHIC, or blow up the vertical emittance of positron beams, e.g., at the B factories or in linear-collider damping rings. Different approaches to modeling these effects each have their own merits and drawbacks. We describe several simulation codes which simplify the descriptions of the beam-electron interaction and of the accelerator structure in various different ways, and present results for a toy model of the SPS. In addition, we present evidence that for positron beams the interplay of incoherent electron-cloud effects and synchrotron radiation can lead to a significant increase in vertical equilibrium emittance. The magnitude of a few incoherent e+e- scattering processes is also estimated. Options for future code development are reviewed

  15. Seismic waveform modeling over cloud

    Science.gov (United States)

    Luo, Cong; Friederich, Wolfgang

    2016-04-01

    With the fast growing computational technologies, numerical simulation of seismic wave propagation achieved huge successes. Obtaining the synthetic waveforms through numerical simulation receives an increasing amount of attention from seismologists. However, computational seismology is a data-intensive research field, and the numerical packages usually come with a steep learning curve. Users are expected to master considerable amount of computer knowledge and data processing skills. Training users to use the numerical packages, correctly access and utilize the computational resources is a troubled task. In addition to that, accessing to HPC is also a common difficulty for many users. To solve these problems, a cloud based solution dedicated on shallow seismic waveform modeling has been developed with the state-of-the-art web technologies. It is a web platform integrating both software and hardware with multilayer architecture: a well designed SQL database serves as the data layer, HPC and dedicated pipeline for it is the business layer. Through this platform, users will no longer need to compile and manipulate various packages on the local machine within local network to perform a simulation. By providing users professional access to the computational code through its interfaces and delivering our computational resources to the users over cloud, users can customize the simulation at expert-level, submit and run the job through it.

  16. Security model for VM in cloud

    Science.gov (United States)

    Kanaparti, Venkataramana; Naveen K., R.; Rajani, S.; Padmvathamma, M.; Anitha, C.

    2013-03-01

    Cloud computing is a new approach emerged to meet ever-increasing demand for computing resources and to reduce operational costs and Capital Expenditure for IT services. As this new way of computation allows data and applications to be stored away from own corporate server, it brings more issues in security such as virtualization security, distributed computing, application security, identity management, access control and authentication. Even though Virtualization forms the basis for cloud computing it poses many threats in securing cloud. As most of Security threats lies at Virtualization layer in cloud we proposed this new Security Model for Virtual Machine in Cloud (SMVC) in which every process is authenticated by Trusted-Agent (TA) in Hypervisor as well as in VM. Our proposed model is designed to with-stand attacks by unauthorized process that pose threat to applications related to Data Mining, OLAP systems, Image processing which requires huge resources in cloud deployed on one or more VM's.

  17. Security Management Model in Cloud Computing Environment

    OpenAIRE

    Ahmadpanah, Seyed Hossein

    2016-01-01

    In the cloud computing environment, cloud virtual machine (VM) will be more and more the number of virtual machine security and management faced giant Challenge. In order to address security issues cloud computing virtualization environment, this paper presents a virtual machine based on efficient and dynamic deployment VM security management model state migration and scheduling, study of which virtual machine security architecture, based on AHP (Analytic Hierarchy Process) virtual machine de...

  18. MODEL FOR SEMANTICALLY RICH POINT CLOUD DATA

    Directory of Open Access Journals (Sweden)

    F. Poux

    2017-10-01

    Full Text Available This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  19. Model for Semantically Rich Point Cloud Data

    Science.gov (United States)

    Poux, F.; Neuville, R.; Hallot, P.; Billen, R.

    2017-10-01

    This paper proposes an interoperable model for managing high dimensional point clouds while integrating semantics. Point clouds from sensors are a direct source of information physically describing a 3D state of the recorded environment. As such, they are an exhaustive representation of the real world at every scale: 3D reality-based spatial data. Their generation is increasingly fast but processing routines and data models lack of knowledge to reason from information extraction rather than interpretation. The enhanced smart point cloud developed model allows to bring intelligence to point clouds via 3 connected meta-models while linking available knowledge and classification procedures that permits semantic injection. Interoperability drives the model adaptation to potentially many applications through specialized domain ontologies. A first prototype is implemented in Python and PostgreSQL database and allows to combine semantic and spatial concepts for basic hybrid queries on different point clouds.

  20. Optimizing cloud removal from satellite remotely sensed data for monitoring vegetation dynamics in humid tropical climate

    International Nuclear Information System (INIS)

    Hashim, M; Pour, A B; Onn, C H

    2014-01-01

    Remote sensing technology is an important tool to analyze vegetation dynamics, quantifying vegetation fraction of Earth's agricultural and natural vegetation. In optical remote sensing analysis removing atmospheric interferences, particularly distribution of cloud contaminations, are always a critical task in the tropical climate. This paper suggests a fast and alternative approach to remove cloud and shadow contaminations for Landsat Enhanced Thematic Mapper + (ETM + ) multi temporal datasets. Band 3 and Band 4 from all the Landsat ETM + dataset are two main spectral bands that are very crucial in this study for cloud removal technique. The Normalise difference vegetation index (NDVI) and the normalised difference soil index (NDSI) are two main derivatives derived from the datasets. Change vector analysis is used in this study to seek the vegetation dynamics. The approach developed in this study for cloud optimizing can be broadly applicable for optical remote sensing satellite data, which are seriously obscured with heavy cloud contamination in the tropical climate

  1. Remote Sensing of Clouds for Solar Forecasting Applications

    Science.gov (United States)

    Mejia, Felipe

    A method for retrieving cloud optical depth (tauc) using a UCSD developed ground- based Sky Imager (USI) is presented. The Radiance Red-Blue Ratio (RRBR) method is motivated from the analysis of simulated images of various tauc produced by a Radiative Transfer Model (RTM). From these images the basic parameters affecting the radiance and RBR of a pixel are identified as the solar zenith angle (SZA), tau c , solar pixel an- gle/scattering angle (SPA), and pixel zenith angle/view angle (PZA). The effects of these parameters are described and the functions for radiance, Ilambda (tau c ,SZA,SPA,PZA) , and the red-blue ratio, RBR(tauc ,SZA,SPA,PZA) , are retrieved from the RTM results. RBR, which is commonly used for cloud detection in sky images, provides non-unique solutions for tau c , where RBR increases with tauc up to about tauc = 1 (depending on other parameters) and then decreases. Therefore, the RRBR algorithm uses the measured Imeaslambda (SPA,PZA) , in addition to RBRmeas (SPA,PZA ) to obtain a unique solution for tauc . The RRBR method is applied to images of liquid water clouds taken by a USI at the Oklahoma Atmospheric Radiation Measurement program (ARM) site over the course of 220 days and compared against measurements from a microwave radiometer (MWR) and output from the Min [ MH96a ] method for overcast skies. tau c values ranged from 0-80 with values over 80 being capped and registered as 80. A tauc RMSE of 2.5 between the Min method [ MH96b ] and the USI are observed. The MWR and USI have an RMSE of 2.2 which is well within the uncertainty of the MWR. The procedure developed here provides a foundation to test and develop other cloud detection algorithms. Using the RRBR tauc estimate as an input we then explore the potential of using tomographic techniques for 3-D cloud reconstruction. The Algebraic Reconstruction Technique (ART) is applied to optical depth maps from sky images to reconstruct 3-D cloud extinction coefficients. Reconstruction accuracy

  2. Multi-scale Modeling of Arctic Clouds

    Science.gov (United States)

    Hillman, B. R.; Roesler, E. L.; Dexheimer, D.

    2017-12-01

    The presence and properties of clouds are critically important to the radiative budget in the Arctic, but clouds are notoriously difficult to represent in global climate models (GCMs). The challenge stems partly from a disconnect in the scales at which these models are formulated and the scale of the physical processes important to the formation of clouds (e.g., convection and turbulence). Because of this, these processes are parameterized in large-scale models. Over the past decades, new approaches have been explored in which a cloud system resolving model (CSRM), or in the extreme a large eddy simulation (LES), is embedded into each gridcell of a traditional GCM to replace the cloud and convective parameterizations to explicitly simulate more of these important processes. This approach is attractive in that it allows for more explicit simulation of small-scale processes while also allowing for interaction between the small and large-scale processes. The goal of this study is to quantify the performance of this framework in simulating Arctic clouds relative to a traditional global model, and to explore the limitations of such a framework using coordinated high-resolution (eddy-resolving) simulations. Simulations from the global model are compared with satellite retrievals of cloud fraction partioned by cloud phase from CALIPSO, and limited-area LES simulations are compared with ground-based and tethered-balloon measurements from the ARM Barrow and Oliktok Point measurement facilities.

  3. An efficient cloud detection method for high resolution remote sensing panchromatic imagery

    Science.gov (United States)

    Li, Chaowei; Lin, Zaiping; Deng, Xinpu

    2018-04-01

    In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

  4. Modeling microwave/electron-cloud interaction

    International Nuclear Information System (INIS)

    Mattes, M; Sorolla, E; Zimmermann, F

    2013-01-01

    Starting from the separate codes BI-RME and ECLOUD or PyECLOUD, we are developing a novel joint simulation tool, which models the combined effect of a charged particle beam and of microwaves on an electron cloud. Possible applications include the degradation of microwave transmission in telecommunication satellites by electron clouds; the microwave-transmission techniques being used in particle accelerators for the purpose of electroncloud diagnostics; the microwave emission by the electron cloud itself in the presence of a magnetic field; and the possible suppression of electron-cloud formation in an accelerator by injecting microwaves of suitable amplitude and frequency. A few early simulation results are presented. (author)

  5. An Interactive Web-Based Analysis Framework for Remote Sensing Cloud Computing

    Science.gov (United States)

    Wang, X. Z.; Zhang, H. M.; Zhao, J. H.; Lin, Q. H.; Zhou, Y. C.; Li, J. H.

    2015-07-01

    Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users' private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook. Users can write

  6. Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?

    Science.gov (United States)

    Grützun, V.; Quaas, J.; Morcrette, C. J.; Ament, F.

    2013-09-01

    Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the "perfect model approach." This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.

  7. Effects of ice crystal surface roughness and air bubble inclusions on cirrus cloud radiative properties from remote sensing perspective

    International Nuclear Information System (INIS)

    Tang, Guanglin; Panetta, R. Lee; Yang, Ping; Kattawar, George W.; Zhai, Peng-Wang

    2017-01-01

    We study the combined effects of surface roughness and inhomogeneity on the optical scattering properties of ice crystals and explore the consequent implications to remote sensing of cirrus cloud properties. Specifically, surface roughness and inhomogeneity are added to the Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (MC6) cirrus cloud particle habit model. Light scattering properties of the new habit model are simulated using a modified version of the Improved Geometric Optics Method (IGOM). Both inhomogeneity and surface roughness affect the single scattering properties significantly. In visible bands, inhomogeneity and surface roughness both tend to smooth the phase function and eliminate halos and the backscattering peak. The asymmetry parameter varies with the degree of surface roughness following a U shape - decreases and then increases - with a minimum at around 0.15, whereas it decreases monotonically with the air bubble volume fraction. Air bubble inclusions significantly increase phase matrix element -P_1_2 for scattering angles between 20°–120°, whereas surface roughness has a much weaker effect, increasing -P_1_2 slightly from 60°–120°. Radiative transfer simulations and cirrus cloud property retrievals are conducted by including both the factors. In terms of surface roughness and air bubble volume fraction, retrievals of cirrus cloud optical thickness or the asymmetry parameter using solar bands show similar patterns of variation. Polarimetric simulations using the MC6 cirrus cloud particle habit model are shown to be more consistent with observations when both surface roughness and inhomogeneity are simultaneously considered. - Highlights: • Surface roughness and air bubble inclusions affect optical properties of ice crystals significantly. • Including both factors improves simulations of ice cloud.• Cirrus cloud particle habit model of the MODIS collection 6 achieves better self-consistency and consistency with

  8. Remote sensing of contrails and aircraft altered cirrus clouds

    Energy Technology Data Exchange (ETDEWEB)

    Palikonda, R.; Nguyen, L.; Garber, D.P.; Smith, W.L. Jr [Analytical Services and Materials, Inc., Hampton, VA (United States); Minnis, P.; Young, D.F. [National Aeronautics and Space Administration, Hampton, VA (United States). Langley Research Center

    1997-12-31

    Analyses of satellite imagery are used to show that contrails can develop into fully extended cirrus cloud systems. Contrails can be advective on great distances, but would appear to observers as natural cirrus clouds. The conversion of simple contrails into cirrus may help explain the apparent increase of cloudiness over populated areas since the beginning of commercial jet air travel. Statistics describing the typical growth, advection, and lifetime of contrail cirrus is needed to evaluate their effects on climate. (author) 4 refs.

  9. Remote sensing of contrails and aircraft altered cirrus clouds

    Energy Technology Data Exchange (ETDEWEB)

    Palikonda, R; Nguyen, L; Garber, D P; Smith, Jr, W L [Analytical Services and Materials, Inc., Hampton, VA (United States); Minnis, P; Young, D F [National Aeronautics and Space Administration, Hampton, VA (United States). Langley Research Center

    1998-12-31

    Analyses of satellite imagery are used to show that contrails can develop into fully extended cirrus cloud systems. Contrails can be advective on great distances, but would appear to observers as natural cirrus clouds. The conversion of simple contrails into cirrus may help explain the apparent increase of cloudiness over populated areas since the beginning of commercial jet air travel. Statistics describing the typical growth, advection, and lifetime of contrail cirrus is needed to evaluate their effects on climate. (author) 4 refs.

  10. New photoionization models of intergalactic clouds

    Science.gov (United States)

    Donahue, Megan; Shull, J. M.

    1991-01-01

    New photoionization models of optically thin low-density intergalactic gas at constant pressure, photoionized by QSOs, are presented. All ion stages of H, He, C, N, O, Si, and Fe, plus H2 are modeled, and the column density ratios of clouds at specified values of the ionization parameter of n sub gamma/n sub H and cloud metallicity are predicted. If Ly-alpha clouds are much cooler than the previously assumed value, 30,000 K, the ionization parameter must be very low, even with the cooling contribution of a trace component of molecules. If the clouds cool below 6000 K, their final equilibrium must be below 3000 K, owing to the lack of a stable phase between 6000 and 3000 K. If it is assumed that the clouds are being irradiated by an EUV power-law continuum typical of WSOs, with J0 = 10 exp -21 ergs/s sq cm Hz, typical cloud thicknesses along the line of sight that are much smaller than would be expected from shocks, thermal instabilities, or gravitational collapse are derived.

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

    Science.gov (United States)

    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

  12. A Review of Cloud Business Models and Sustainability

    OpenAIRE

    Chang, Victor; Wills, Gary; De Roure, David

    2010-01-01

    This paper reviews current cloud computing business models and presents proposals on how organisations can achieve sustainability by adopting appropriate models. Using the Jericho Forum's Cloud Cube Model (CCM), we classify cloud computing business models into eight types: (1) Service Provider and Service Orientation; (2) Support and Services Contracts; (3) In-House Private Clouds; (4) All-In-One Enterprise Cloud; (5) One-Stop Resources and Services; (6) Government Funding; (7) Venture Capita...

  13. Cloud remote sensing from space in the era of the A-Train

    Science.gov (United States)

    Stephens, Graeme L.; Vane, Deborah G.

    2006-09-01

    The clouds of Earth are fundamental to most aspects of human life. Through production of precipitation, they are essential for delivering and sustaining the supplies of fresh water upon which human life depends. Clouds further exert a principal influence on the planet's energy balance. It is in clouds that latent heat is released through the process of condensation and the formation of precipitation affecting the development and evolution of the planet's storm systems. Clouds further exert a profound influence on the solar and infrared radiation that enters and leaves the atmosphere, further exerting profound effects on climate and on forces that affect climate change (Stephens, 2005). It is for these reasons, among others, that the need to observe the distribution and variability of the properties of clouds and precipitation has emerged as a priority in Earth observations. Most past and current observational programs are contructed in such a way that clouds and precipitation are treated as separate entities. Nature does not work this way and there is much to be gained scientifically in moving away from these artificial practices toward observing clouds and precipitation properties jointly. We are now embarking on a new age of remote sensing of clouds and precipitation using active sensors, starting with the tropical rainfall measurement mission (TRMM) and continuing on with the A-Train (described below). This new age provides us with the opportunity to move away from past and present artificial observing practices offering a more unified approach to observing clouds and precipitation properties jointly.

  14. Remote sensing the susceptibility of cloud albedo to changes in drop concentration

    International Nuclear Information System (INIS)

    Platnick, S.E.

    1991-01-01

    The role of clouds in reflecting solar radiation to space and thereby reducing surface heating is of critical importance to climate. Combustion processes that produce greenhouse gases also increase cloud condensation nuclei (CCN) concentrations which in turn increase cloud drop concentrations and thereby cloud albedo. A calculation of cloud susceptibility, defined in this work as the increase in albedo resulting from the addition of one cloud drop per cubic centimeter (as cloud liquid water content remains constant), is made through satellite remote sensing of cloud drop radius and optical thickness. The remote technique uses spectral channels of the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA polar orbiting satellites. Radiative transfer calculations of reflectance and effective surface and cloud emissivities are made for applicable sun and satellite viewing angles, including azimuth, at various radii and optical thicknesses for each AVHRR channel. Emission in channel 3 (at 3.75 microns) is removed to give the reflected solar component. These calculations are used to infer the radius and optical thickness giving the best match to the satellite measurements. The effect of the atmosphere on the signal received by the satellite is included in the analysis

  15. AN INTERACTIVE WEB-BASED ANALYSIS FRAMEWORK FOR REMOTE SENSING CLOUD COMPUTING

    Directory of Open Access Journals (Sweden)

    X. Z. Wang

    2015-07-01

    Full Text Available Spatiotemporal data, especially remote sensing data, are widely used in ecological, geographical, agriculture, and military research and applications. With the development of remote sensing technology, more and more remote sensing data are accumulated and stored in the cloud. An effective way for cloud users to access and analyse these massive spatiotemporal data in the web clients becomes an urgent issue. In this paper, we proposed a new scalable, interactive and web-based cloud computing solution for massive remote sensing data analysis. We build a spatiotemporal analysis platform to provide the end-user with a safe and convenient way to access massive remote sensing data stored in the cloud. The lightweight cloud storage system used to store public data and users’ private data is constructed based on open source distributed file system. In it, massive remote sensing data are stored as public data, while the intermediate and input data are stored as private data. The elastic, scalable, and flexible cloud computing environment is built using Docker, which is a technology of open-source lightweight cloud computing container in the Linux operating system. In the Docker container, open-source software such as IPython, NumPy, GDAL, and Grass GIS etc., are deployed. Users can write scripts in the IPython Notebook web page through the web browser to process data, and the scripts will be submitted to IPython kernel to be executed. By comparing the performance of remote sensing data analysis tasks executed in Docker container, KVM virtual machines and physical machines respectively, we can conclude that the cloud computing environment built by Docker makes the greatest use of the host system resources, and can handle more concurrent spatial-temporal computing tasks. Docker technology provides resource isolation mechanism in aspects of IO, CPU, and memory etc., which offers security guarantee when processing remote sensing data in the IPython Notebook

  16. Remote Sensing of Cloud Top Heights Using the Research Scanning Polarimeter

    Science.gov (United States)

    Sinclair, Kenneth; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej

    2015-01-01

    Clouds cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered clouds occur about half of the time and are predominantly two-layered. Changes in cloud top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at cloud altitude using a correlation function designed to identify the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the Cloud Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately identify cloud heights. Interestingly, the analysis reveals an ability for the approach to identify multiple cloud layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of identifying single and multiple cloud layers heights are explored. Special focus is given to sources of error in the method including optically thin clouds, physically thick clouds, multi

  17. Macroscopic modelization of the cloud elasticity*

    Directory of Open Access Journals (Sweden)

    Etancelin J.-M.

    2013-12-01

    Full Text Available In order to achieve its promise of providing information technologies (IT on demand, cloud computing needs to rely on a mathematical model capable of directing IT on and off according to a demand pattern to provide a true elasticity. This article provides a first method to reach this goal using a “fluid type” partial differential equations model. On the one hand it examines the question of service time optimization for the simultaneous satisfaction of the cloud consumer and provider. On the other hand it tries to model a way to deliver resources according to the real time capacity of the cloud that depends on parameters such as burst requests and application timeouts. All these questions are illustrated via an implicit finite volume scheme.

  18. Characterisation of the artificial neural network CiPS for cirrus cloud remote sensing with MSG/SEVIRI

    Directory of Open Access Journals (Sweden)

    J. Strandgren

    2017-11-01

    Full Text Available Cirrus clouds remain one of the key uncertainties in atmospheric research. To better understand the properties and physical processes of cirrus clouds, accurate large-scale observations from satellites are required. Artificial neural networks (ANNs have proved to be a useful tool for cirrus cloud remote sensing. Since physics is not modelled explicitly in ANNs, a thorough characterisation of the networks is necessary. In this paper the CiPS (Cirrus Properties from SEVIRI algorithm is characterised using the space-borne lidar CALIOP. CiPS is composed of a set of ANNs for the cirrus cloud detection, opacity identification and the corresponding cloud top height, ice optical thickness and ice water path retrieval from the imager SEVIRI aboard the geostationary Meteosat Second Generation satellites. First, the retrieval accuracy is characterised with respect to different land surface types. The retrieval works best over water and vegetated surfaces, whereas a surface covered by permanent snow and ice or barren reduces the cirrus detection ability and increases the retrieval errors for the ice optical thickness and ice water path if the cirrus cloud is thin (optical thickness less than approx. 0.3. Second, the retrieval accuracy is characterised with respect to the vertical arrangement of liquid, ice clouds and aerosol layers as derived from CALIOP lidar data. The CiPS retrievals show little interference from liquid water clouds and aerosol layers below an observed cirrus cloud. A liquid water cloud vertically close or adjacent to the cirrus clearly increases the average retrieval errors for the optical thickness and ice water path, respectively, only for thin cirrus clouds with an optical thickness below 0.3 or ice water path below 5.0 g m−2. For the cloud top height retrieval, only aerosol layers affect the retrieval error, with an increased positive bias when the cirrus is at low altitudes. Third, the CiPS retrieval error is

  19. Modelling cloud data for prototype manufacturing

    NARCIS (Netherlands)

    Liu, G.H.; Wong, Y.S.; Zhang, Y.F.; Loh, H.T.

    2003-01-01

    In this paper, the authors have developed a novel method to integrate reverse engineering (RE) and rapid prototyping (RP). Unorganised cloud data are directly sliced and modelled with two-dimensional (2D) cross-sections. Based on such a 2D CAD model, the data points are directly converted into RP

  20. Coupled fvGCM-GCE Modeling System, 3D Cloud-Resolving Model and Cloud Library

    Science.gov (United States)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-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 cloud 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 cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

  1. Macrophysical properties of continental cumulus clouds from active and passive remote sensing

    Energy Technology Data Exchange (ETDEWEB)

    Kassianov, Evgueni I.; Riley, Erin A.; Kleiss, Jessica; Long, Charles N.; Riihimaki, Laura D.; Flynn, Donna M.; Flynn, Connor J M.; Berg, Larry K.

    2017-10-06

    Cloud amount is an essential and extensively used macrophysical parameter of cumulus clouds. It is commonly defined as a cloud fraction (CF) from zenith-pointing ground-based active and passive remote sensing. However, conventional retrievals of CF from the remote sensing data with very narrow field-of-view (FOV) may not be representative of the surrounding area. Here we assess its representativeness using an integrated dataset collected at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site in Oklahoma, USA. For our assessment with focus on selected days with single-layer cumulus clouds (2005-2016), we include the narrow-FOV ARM Active Remotely Sensed Clouds Locations (ARSCL) and large-FOV Total Sky Imager (TSI) cloud products, the 915-MHz Radar Wind Profiler (RWP) measurements of wind speed and direction, and also high-resolution satellite images from Landsat and the Moderate Resolution Imaging Spectroradiometer (MODIS). We demonstrate that a root-mean-square difference (RMSD) between the 15-min averaged ARSCL cloud fraction (CF) and the 15-min averaged TSI fractional sky cover (FSC) is large (up to 0.3). We also discuss how the horizontal distribution of clouds can modify the obtained large RMSD using a new uniformity metric. The latter utilizes the spatial distribution of the FSC over the 100° FOV TSI images obtained with high temporal resolution (30 sec sampling). We demonstrate that cases with more uniform spatial distribution of FSC show better agreement between the narrow-FOV CF and large-FOV FSC, reducing the RMSD by up to a factor of 2.

  2. Chemical equilibrium models of interstellar gas clouds

    International Nuclear Information System (INIS)

    Freeman, A.

    1982-10-01

    This thesis contains work which helps towards our understanding of the chemical processes and astrophysical conditions in interstellar clouds, across the whole range of cloud types. The object of the exercise is to construct a mathematical model representing a large system of two-body chemical reactions in order to deduce astrophysical parameters and predict molecular abundances and chemical pathways. Comparison with observations shows that this type of model is valid but also indicates that our knowledge of some chemical reactions is incomplete. (author)

  3. Added Value of Far-Infrared Radiometry for Ice Cloud Remote Sensing

    Science.gov (United States)

    Libois, Q.; Blanchet, J. P.; Ivanescu, L.; S Pelletier, L.; Laurence, C.

    2017-12-01

    Several cloud retrieval algorithms based on satellite observations in the infrared have been developed in the last decades. However, most of these observations only cover the midinfrared (MIR, λ technology, though, now make it possible to consider spaceborne remote sensing in the FIR. Here we show that adding a few FIR channels with realistic radiometric performances to existing spaceborne narrowband radiometers would significantly improve their ability to retrieve ice cloud radiative properties. For clouds encountered in the polar regions and the upper troposphere, where the atmosphere above clouds is sufficiently transparent in the FIR, using FIR channels would reduce by more than 50% the uncertainties on retrieved values of optical thickness, effective particle diameter, and cloud top altitude. This would somehow extend the range of applicability of current infrared retrieval methods to the polar regions and to clouds with large optical thickness, where MIR algorithms perform poorly. The high performance of solar reflection-based algorithms would thus be reached in nighttime conditions. Using FIR observations is a promising venue for studying ice cloud microphysics and precipitation processes, which is highly relevant for cirrus clouds and convective towers, and for investigating the water cycle in the driest regions of the atmosphere.

  4. Determination of clouds in MSG data for the validation of clouds in a regional climate model

    OpenAIRE

    Huckle, Roger

    2009-01-01

    Regional climate models (e.g. CLM) can help to asses the influence of the antropogenic climate change on the different regions of the earth. Validation of these models is very important. Satellite data are of great benefit, as data on a global scale and high temporal resolution is available. In this thesis a cloud detection and object based cloud classification for Meteosat Second Generation (MSG) was developed and used to validate CLM clouds. Results show sometimes too many clouds in the CLM.

  5. Parameterization of clouds and radiation in climate models

    Energy Technology Data Exchange (ETDEWEB)

    Roeckner, E. [Max Planck Institute for Meterology, Hamburg (Germany)

    1995-09-01

    Clouds are a very important, yet poorly modeled element in the climate system. There are many potential cloud feedbacks, including those related to cloud cover, height, water content, phase change, and droplet concentration and size distribution. As a prerequisite to studying the cloud feedback issue, this research reports on the simulation and validation of cloud radiative forcing under present climate conditions using the ECHAM general circulation model and ERBE top-of-atmosphere radiative fluxes.

  6. Trust Model to Enhance Security and Interoperability of Cloud Environment

    Science.gov (United States)

    Li, Wenjuan; Ping, Lingdi

    Trust is one of the most important means to improve security and enable interoperability of current heterogeneous independent cloud platforms. This paper first analyzed several trust models used in large and distributed environment and then introduced a novel cloud trust model to solve security issues in cross-clouds environment in which cloud customer can choose different providers' services and resources in heterogeneous domains can cooperate. The model is domain-based. It divides one cloud provider's resource nodes into the same domain and sets trust agent. It distinguishes two different roles cloud customer and cloud server and designs different strategies for them. In our model, trust recommendation is treated as one type of cloud services just like computation or storage. The model achieves both identity authentication and behavior authentication. The results of emulation experiments show that the proposed model can efficiently and safely construct trust relationship in cross-clouds environment.

  7. Business Process as a Service Model Based Business and IT Cloud Alignment as a Cloud Offering

    OpenAIRE

    Robert Woitsch; Wilfrid Utz

    2015-01-01

    Cloud computing proved to offer flexible IT solutions. Although large enterprises may benefit from this technology, SMEs are falling behind in cloud usage due to missing ITcompetence and hence lose the ability to efficiently adapt their IT to their business needs. This paper introduces the project idea of the H2020 project CloudSocket, by elaborating the idea of Business Processes as a Service (BPaaS), where concept models and semantics are applied to align business processes with Cloud deplo...

  8. Equivalent Sensor Radiance Generation and Remote Sensing from Model Parameters. Part 1; Equivalent Sensor Radiance Formulation

    Science.gov (United States)

    Wind, Galina; DaSilva, Arlindo M.; Norris, Peter M.; Platnick, Steven E.

    2013-01-01

    In this paper we describe a general procedure for calculating equivalent sensor radiances from variables output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint the algorithm takes explicit account of the model subgrid variability, in particular its description of the probably density function of total water (vapor and cloud condensate.) The equivalent sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies. We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products.) We focus on clouds and cloud/aerosol interactions, because they are very important to model development and improvement.

  9. Observational Constraints for Modeling Diffuse Molecular Clouds

    Science.gov (United States)

    Federman, S. R.

    2014-02-01

    Ground-based and space-borne observations of diffuse molecular clouds suggest a number of areas where further improvements to modeling efforts is warranted. I will highlight those that have the widest applicability. The range in CO fractionation caused by selective isotope photodissociation, in particular the large 12C16O/13C16O ratios observed toward stars in Ophiuchus, is not reproduced well by current models. Our ongoing laboratory measurements of oscillator strengths and predissociation rates for Rydberg transitions in CO isotopologues may help clarify the situtation. The CH+ abundance continues to draw attention. Small scale structure seen toward ζ Per may provide additional constraints on the possible synthesis routes. The connection between results from optical transitions and those from radio and sub-millimeter wave transitions requires further effort. A study of OH+ and OH toward background stars reveals that these species favor different environments. This brings to focus the need to model each cloud along the line of sight separately, and to allow the physical conditions to vary within an individual cloud, in order to gain further insight into the chemistry. Now that an extensive set of data on molecular excitation is available, the models should seek to reproduce these data to place further constraints on the modeling results.

  10. Petri net modeling of encrypted information flow in federated cloud

    Science.gov (United States)

    Khushk, Abdul Rauf; Li, Xiaozhong

    2017-08-01

    Solutions proposed and developed for the cost-effective cloud systems suffer from a combination of secure private clouds and less secure public clouds. Need to locate applications within different clouds poses a security risk to the information flow of the entire system. This study addresses this by assigning security levels of a given lattice to the entities of a federated cloud system. A dynamic flow sensitive security model featuring Bell-LaPadula procedures is explored that tracks and authenticates the secure information flow in federated clouds. Additionally, a Petri net model is considered as a case study to represent the proposed system and further validate the performance of the said system.

  11. Remotely Sensed High-Resolution Global Cloud Dynamics for Predicting Ecosystem and Biodiversity Distributions.

    Directory of Open Access Journals (Sweden)

    Adam M Wilson

    2016-03-01

    Full Text Available Cloud cover can influence numerous important ecological processes, including reproduction, growth, survival, and behavior, yet our assessment of its importance at the appropriate spatial scales has remained remarkably limited. If captured over a large extent yet at sufficiently fine spatial grain, cloud cover dynamics may provide key information for delineating a variety of habitat types and predicting species distributions. Here, we develop new near-global, fine-grain (≈1 km monthly cloud frequencies from 15 y of twice-daily Moderate Resolution Imaging Spectroradiometer (MODIS satellite images that expose spatiotemporal cloud cover dynamics of previously undocumented global complexity. We demonstrate that cloud cover varies strongly in its geographic heterogeneity and that the direct, observation-based nature of cloud-derived metrics can improve predictions of habitats, ecosystem, and species distributions with reduced spatial autocorrelation compared to commonly used interpolated climate data. These findings support the fundamental role of remote sensing as an effective lens through which to understand and globally monitor the fine-grain spatial variability of key biodiversity and ecosystem properties.

  12. Shallow layer modelling of dense gas clouds

    Energy Technology Data Exchange (ETDEWEB)

    Ott, S.; Nielsen, M.

    1996-11-01

    The motivation for making shallow layer models is that they can deal with the dynamics of gravity driven flow in complex terrain at a modest computational cost compared to 3d codes. The main disadvantage is that the air-cloud interactions still have to be added `by hand`, where 3d models inherit the correct dynamics from the fundamental equations. The properties of the inviscid shallow water equations are discussed, focusing on existence and uniqueness of solutions. It is demonstrated that breaking waves and fronts pose severe problems, that can only be overcome if the hydrostatic approximation is given up and internal friction is added to the model. A set of layer integrated equations is derived starting from the Navier-Stokes equations. The various steps in the derivation are accompanied by plausibility arguments. These form the scientific basis of the model. The principle of least action is introduced as a means of generating consistent models, and as a tool for making discrete equations for numerical models, which automatically obey conservation laws. A numerical model called SLAM (Shallow LAyer Model) is presented. SLAM has some distinct features compared to other shallow layer models: A Lagrangian, moving grid; Explicit account for the turbulent kinetic energy budget; The entrainment rate is estimated on the basis of the local turbulent kinetic energy; Non-hydrostatic pressure; and Numerical methods respect conservation laws even for coarse grids. Thorney Island trial 8 is used as a reference case model tuning. The model reproduces the doughnut shape of the cloud and yield concentrations in reasonable agreement with observations, even when a small number of cells (e.g. 16) is used. It is concluded that lateral exchange of matter within the cloud caused by shear is important, and that the model should be improved on this point. (au) 16 ills., 38 refs.

  13. Remote Sensing of Clouds And Precipitation: Event-Based Characterization, Life Cycle Evolution, and Aerosol Influences

    Science.gov (United States)

    Esmaili, Rebekah Bradley

    Global climate models, numerical weather prediction, and flood models rely on accurate satellite precipitation products, which are the only datasets that are continuous in time and space across the globe. While there are more earth observing satellites than ever before, gaps in precipitation retrievals exist due to sensor and orbital limitations of low-earth (LEO) satellites, which are overcome by merging data from different sensors in satellite precipitation products (SPPs). Using cloud tracking at higher resolutions than the spatio-temporal scales of LEO satellites, this thesis examines how clouds typically form in the atmosphere, the rate that cloud size and temperature evolve over the life cycle, and the time of day that cloud development take place. This thesis found that cloud evolution was non-linear, which disagrees with the linear interpolation schemes used in SPPs. Longer lasting clouds tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lasting clouds. Over the ocean, longer lasting clouds were found to occur more frequently at night, while shorter lasting clouds were more common during the daytime. This thesis also examines whether large-scale Saharan dust outbreaks can impact the trajectories and intensity of cloud clusters in the tropical Atlantic, which is predicted by modeling studies. The presented results show that proximity to Saharan dust outbreaks shifts Atlantic cloud development northward and intense storms becoming more common, whereas on days with low dust loading small-scale, warmer clouds are more common. A simplified view of cloud evolution in merged rainfall retrievals is a possible source of errors, which can propagate into higher level analysis. This thesis investigates the difference in the intensity, duration, and frequency of precipitation in IMERG, a next-generation satellite precipitation product with ground radar observations over the

  14. Mesoscale meteorological model based on radioactive explosion cloud simulation

    International Nuclear Information System (INIS)

    Zheng Yi; Zhang Yan; Ying Chuntong

    2008-01-01

    In order to simulate nuclear explosion and dirty bomb radioactive cloud movement and concentration distribution, mesoscale meteorological model RAMS was used. Particles-size, size-active distribution and gravitational fallout in the cloud were considered. The results show that the model can simulate the 'mushroom' clouds of explosion. Three-dimension fluid field and radioactive concentration field were received. (authors)

  15. Modeling and Security in Cloud Ecosystems

    Directory of Open Access Journals (Sweden)

    Eduardo B. Fernandez

    2016-04-01

    Full Text Available Clouds do not work in isolation but interact with other clouds and with a variety of systems either developed by the same provider or by external entities with the purpose to interact with them; forming then an ecosystem. A software ecosystem is a collection of software systems that have been developed to coexist and evolve together. The stakeholders of such a system need a variety of models to give them a perspective of the possibilities of the system, to evaluate specific quality attributes, and to extend the system. A powerful representation when building or using software ecosystems is the use of architectural models, which describe the structural aspects of such a system. These models have value for security and compliance, are useful to build new systems, can be used to define service contracts, find where quality factors can be monitored, and to plan further expansion. We have described a cloud ecosystem in the form of a pattern diagram where its components are patterns and reference architectures. A pattern is an encapsulated solution to a recurrent problem. We have recently expanded these models to cover fog systems and containers. Fog Computing is a highly-virtualized platform that provides compute, storage, and networking services between end devices and Cloud Computing Data Centers; a Software Container provides an execution environment for applications sharing a host operating system, binaries, and libraries with other containers. We intend to use this architecture to answer a variety of questions about the security of this system as well as a reference to design interacting combinations of heterogeneous components. We defined a metamodel to relate security concepts which is being expanded.

  16. Cloud Shade by Dynamic Logistic Modeling

    Czech Academy of Sciences Publication Activity Database

    Brabec, Marek; Badescu, V.; Paulescu, M.

    2014-01-01

    Roč. 41, č. 6 (2014), s. 1174-1188 ISSN 0266-4763 R&D Projects: GA MŠk LD12009 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional support: RVO:67985807 Keywords : clouds * random process * sunshine number * Markovian logistic regression model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.417, year: 2014

  17. Remote Cloud Sensing Intensive Observation Period (RCS-IOP) millimeter-wave radar calibration and data intercomparison

    Energy Technology Data Exchange (ETDEWEB)

    Sekelsky, S.M.; Firda, J.M.; McIntosh, R.E. [Univ. of Massachusetts, Amherst, MA (United States)] [and others

    1996-04-01

    During April 1994, the University of Massachusetts (UMass) and the Pennsylvania State University (Penn State) fielded two millimeter-wave atmospheric radars in the Atmospheric Radiation Measurement Remote Cloud Sensing Intensive Operation Period (RCS-IOP) experiment. The UMass Cloud Profiling Radar System (CPRS) operates simultaneously at 33.12 GHz and 94.92 GHz through a single antenna. The Penn State radar operates at 93.95 GHz and has separate transmitting and receiving antennas. The two systems were separated by approximately 75 meters and simultaneously observed a variety of cloud types at verticle incidence over the course of the experiment. This abstract presents some initial results from our calibration efforts. An absolute calibration of the UMass radar was made from radar measurements of a trihedral corner reflector, which has a known radar cross-section. A relative calibration of between the Penn State and UMass radars is made from the statistical comparison of zenith pointing measurements of low altitude liquid clouds. Attenuation is removed with the aid of radiosonde data, and the difference in the calibration between the UMass and Penn State radars is determined by comparing the ratio of 94-GHz and 95-GHz reflectivity values to a model that accounts for parallax effects of the two antennas used in the Penn State system.

  18. Prediction of cloud droplet number in a general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Ghan, S.J.; Leung, L.R. [Pacific Northwest National Lab., Richland, WA (United States)

    1996-04-01

    We have applied the Colorado State University Regional Atmospheric Modeling System (RAMS) bulk cloud microphysics parameterization to the treatment of stratiform clouds in the National Center for Atmospheric Research Community Climate Model (CCM2). The RAMS predicts mass concentrations of cloud water, cloud ice, rain and snow, and number concnetration of ice. We have introduced the droplet number conservation equation to predict droplet number and it`s dependence on aerosols.

  19. Multiview 3D sensing and analysis for high quality point cloud reconstruction

    Science.gov (United States)

    Satnik, Andrej; Izquierdo, Ebroul; Orjesek, Richard

    2018-04-01

    Multiview 3D reconstruction techniques enable digital reconstruction of 3D objects from the real world by fusing different viewpoints of the same object into a single 3D representation. This process is by no means trivial and the acquisition of high quality point cloud representations of dynamic 3D objects is still an open problem. In this paper, an approach for high fidelity 3D point cloud generation using low cost 3D sensing hardware is presented. The proposed approach runs in an efficient low-cost hardware setting based on several Kinect v2 scanners connected to a single PC. It performs autocalibration and runs in real-time exploiting an efficient composition of several filtering methods including Radius Outlier Removal (ROR), Weighted Median filter (WM) and Weighted Inter-Frame Average filtering (WIFA). The performance of the proposed method has been demonstrated through efficient acquisition of dense 3D point clouds of moving objects.

  20. A stochastic cloud model for cloud and ozone retrievals from UV measurements

    International Nuclear Information System (INIS)

    Efremenko, Dmitry S.; Schüssler, Olena; Doicu, Adrian; Loyola, Diego

    2016-01-01

    The new generation of satellite instruments provides measurements in and around the Oxygen A-band on a global basis and with a relatively high spatial resolution. These data are commonly used for the determination of cloud properties. A stochastic model and radiative transfer model, previously developed by the authors, is used as the forward model component in retrievals of cloud parameters and ozone total and partial columns. The cloud retrieval algorithm combines local and global optimization routines, and yields a retrieval accuracy of about 1% and a fast computational time. Retrieved parameters are the cloud optical thickness and the cloud-top height. It was found that the use of the independent pixel approximation instead of the stochastic cloud model leads to large errors in the retrieved cloud parameters, as well as, in the retrieved ozone height resolved partial columns. The latter can be reduced by using the stochastic cloud model to compute the optimal value of the regularization parameter in the framework of Tikhonov regularization. - Highlights: • A stochastic radiative transfer model for retrieving clouds/ozone is designed. • Errors of independent pixel approximation (IPA) for O3 total column are small. • The error of IPA for ozone profile retrieval may become large. • The use of stochastic model reduces the error of ozone profile retrieval.

  1. Modeling Common-Sense Decisions

    Science.gov (United States)

    Zak, Michail

    This paper presents a methodology for efficient synthesis of dynamical model simulating a common-sense decision making process. The approach is based upon the extension of the physics' First Principles that includes behavior of living systems. The new architecture consists of motor dynamics simulating actual behavior of the object, and mental dynamics representing evolution of the corresponding knowledge-base and incorporating it in the form of information flows into the motor dynamics. The autonomy of the decision making process is achieved by a feedback from mental to motor dynamics. This feedback replaces unavailable external information by an internal knowledgebase stored in the mental model in the form of probability distributions.

  2. A Cloud Computing Workflow for Scalable Integration of Remote Sensing and Social Media Data in Urban Studies

    Science.gov (United States)

    Soliman, A.; Soltani, K.; Yin, J.; Subramaniam, B.; Liu, Y.; Padmanabhan, A.; Riteau, P.; Keahey, K.; Wang, S. W.

    2015-12-01

    Urban ecosystems are unique earth environments because both their physical and social components contribute to the overall dynamics of the system. Up-to-date, remote sensing data (e.g. optical and LiDAR) allowed researchers to monitor the development of impervious surfaces however, it was not adequate to detect associated social dynamics. Geo-located social media (e.g. Twitter) provides a data source to detect population dynamics and understand the interaction of people with their physical environment. Although, integrating social media with remote sensing data has been hindered by large volumes of data and the lack of models for integrating remote sensing products with unstructured social media data. In this research work, we leveraged the NSF chameleon cloud computing platform to provide virtual clusters and elastic auto-scaling of resources that are needed for the synthesis of landuse and geo-located Twitter data. In this context, data synthesis was used to address research questions related to population dynamics in major metropolitan areas. We provide an overview of a cloud computing workflow comprised of a set of coupled scalable synthesis modules for: a) preprocessing data, which includes storage and query of heterogeneous data streams, b) spatial data integration, which matches geo-located Twitter data with user defined landuse maps based on a conceptual model of human mobility and c) visualization of urban mobility patterns. Our results demonstrate the flexibility to connect data, synthesis methods and computing resources using cloud computing, which would be otherwise very difficult for untrained scientists to setup and control. Furthermore, we demonstrate the capabilities of CyberGIS-based workflow using the case study of comparing commuting distances across major US cities from 2013 through the present. We demonstrate how our workflow will support discoveries in urban ecological studies as well as linking human and physical dimensions in environmental

  3. Optical fibre multi-parameter sensing with secure cloud based signal capture and processing

    Science.gov (United States)

    Newe, Thomas; O'Connell, Eoin; Meere, Damien; Yuan, Hongwei; Leen, Gabriel; O'Keeffe, Sinead; Lewis, Elfed

    2016-05-01

    Recent advancements in cloud computing technologies in the context of optical and optical fibre based systems are reported. The proliferation of real time and multi-channel based sensor systems represents significant growth in data volume. This coupled with a growing need for security presents many challenges and presents a huge opportunity for an evolutionary step in the widespread application of these sensing technologies. A tiered infrastructural system approach is adopted that is designed to facilitate the delivery of Optical Fibre-based "SENsing as a Service- SENaaS". Within this infrastructure, novel optical sensing platforms, deployed within different environments, are interfaced with a Cloud-based backbone infrastructure which facilitates the secure collection, storage and analysis of real-time data. Feedback systems, which harness this data to affect a change within the monitored location/environment/condition, are also discussed. The cloud based system presented here can also be used with chemical and physical sensors that require real-time data analysis, processing and feedback.

  4. A stratiform cloud parameterization for general circulation models

    International Nuclear Information System (INIS)

    Ghan, S.J.; Leung, L.R.; Chuang, C.C.; Penner, J.E.; McCaa, J.

    1994-01-01

    The crude treatment of clouds in general circulation models (GCMs) is widely recognized as a major limitation in applying these models to predictions of global climate change. The purpose of this project is to develop in GCMs a stratiform cloud parameterization that expresses clouds in terms of bulk microphysical properties and their subgrid variability. Various clouds variables and their interactions are summarized. Precipitating cloud species are distinguished from non-precipitating species, and the liquid phase is distinguished from the ice phase. The size of the non-precipitating cloud particles (which influences both the cloud radiative properties and the conversion of non-precipitating cloud species to precipitating species) is determined by predicting both the mass and number concentrations of each species

  5. Security Issues Model on Cloud Computing: A Case of Malaysia

    OpenAIRE

    Komeil Raisian; Jamaiah Yahaya

    2015-01-01

    By developing the cloud computing, viewpoint of many people regarding the infrastructure architectures, software distribution and improvement model changed significantly. Cloud computing associates with the pioneering deployment architecture, which could be done through grid calculating, effectiveness calculating and autonomic calculating. The fast transition towards that, has increased the worries regarding a critical issue for the effective transition of cloud computing. From the security v...

  6. Variability in modeled cloud feedback tied to differences in the climatological spatial pattern of clouds

    Science.gov (United States)

    Siler, Nicholas; Po-Chedley, Stephen; Bretherton, Christopher S.

    2018-02-01

    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 clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud 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 cloud 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 cloud 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 cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

  7. FAST OCCLUSION AND SHADOW DETECTION FOR HIGH RESOLUTION REMOTE SENSING IMAGE COMBINED WITH LIDAR POINT CLOUD

    Directory of Open Access Journals (Sweden)

    X. Hu

    2012-08-01

    Full Text Available The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU is much more powerful than central processing unit (CPU. We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.

  8. Fast Occlusion and Shadow Detection for High Resolution Remote Sensing Image Combined with LIDAR Point Cloud

    Science.gov (United States)

    Hu, X.; Li, X.

    2012-08-01

    The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM) directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU) is much more powerful than central processing unit (CPU). We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.

  9. Treatment of cloud radiative effects in general circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Wang, W.C.; Dudek, M.P.; Liang, X.Z.; Ding, M. [State Univ. of New York, Albany, NY (United States)] [and others

    1996-04-01

    We participate in the Atmospheric Radiation Measurement (ARM) program with two objectives: (1) to improve the general circulation model (GCM) cloud/radiation treatment with a focus on cloud verticle overlapping and layer cloud optical properties, and (2) to study the effects of cloud/radiation-climate interaction on GCM climate simulations. This report summarizes the project progress since the Fourth ARM Science Team meeting February 28-March 4, 1994, in Charleston, South Carolina.

  10. Model of E-Cloud Instability in the Fermilab Recycler

    Energy Technology Data Exchange (ETDEWEB)

    Balbekov, V. [Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)

    2015-06-24

    Simple model of electron cloud is developed in the paper to explain e-cloud instability of bunched proton beam in the Fermilab Recycler. The cloud is presented as an immobile snake in strong vertical magnetic field. The instability is treated as an amplification of the bunch injection errors from the batch head to its tail. Nonlinearity of the e-cloud field is taken into account. Results of calculations are compared with experimental data demonstrating good correlation.

  11. Model Based Business and IT Cloud Alignment as a Cloud Offering

    OpenAIRE

    Robert Woitsch; Wilfrid Utz

    2015-01-01

    Cloud computing proved to offer flexible IT solutions. Although large enterprises may benefit from this technology by educating their IT departments, SMEs are dramatically falling behind in cloud usage and hence lose the ability to efficiently adapt their IT to their business needs. This paper introduces the project idea of the H2020 project CloudSocket, by elaborating the idea of Business Processes as a Service, where concept models and semantics are applied to align business pro...

  12. A modeling perspective on cloud radiative forcing

    International Nuclear Information System (INIS)

    Potter, G.L.; Corsetti, L.; Slingo, J.M.

    1993-02-01

    Radiation fields from a perpetual July integration of a T106 version of the ECM-WF operational model are used to identify the most appropriate way to diagnose cloud radiative forcing in a general circulation model, for the purposes of intercomparison between models. Differences between the Methods I and II of Cess and Potter (1987) and a variant method are addressed. Method I is shown to be the least robust of all methods, due to the potential uncertainties related to persistent cloudiness, length of the sampling period and biases in retrieved clear-sky quantities due to insufficient sampling of the diurnal cycle. Method II is proposed as an unambiguous way to produce consistent radiative diagnostics for intercomparing model results. The impact of the three methods on the derived sensitivities and cloud feedbacks following an imposed change in sea surface temperature is discussed. The sensitivity of the results to horizontal resolution is considered by using the diagnostics from parallel integrations with T21 version of the model

  13. A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors

    Science.gov (United States)

    Sedano, Fernando; Kempeneers, Pieter; Strobl, Peter; Kucera, Jan; Vogt, Peter; Seebach, Lucia; San-Miguel-Ayanz, Jesús

    2011-09-01

    This study presents a novel cloud masking approach for high resolution remote sensing images in the context of land cover mapping. As an advantage to traditional methods, the approach does not rely on thermal bands and it is applicable to images from most high resolution earth observation remote sensing sensors. The methodology couples pixel-based seed identification and object-based region growing. The seed identification stage relies on pixel value comparison between high resolution images and cloud free composites at lower spatial resolution from almost simultaneously acquired dates. The methodology was tested taking SPOT4-HRVIR, SPOT5-HRG and IRS-LISS III as high resolution images and cloud free MODIS composites as reference images. The selected scenes included a wide range of cloud types and surface features. The resulting cloud masks were evaluated through visual comparison. They were also compared with ad-hoc independently generated cloud masks and with the automatic cloud cover assessment algorithm (ACCA). In general the results showed an agreement in detected clouds higher than 95% for clouds larger than 50 ha. The approach produced consistent results identifying and mapping clouds of different type and size over various land surfaces including natural vegetation, agriculture land, built-up areas, water bodies and snow.

  14. A model of the microphysical evolution of a cloud

    International Nuclear Information System (INIS)

    Zinn, J.

    1994-01-01

    The earth's weather and climate are influenced strongly by phenomena associated with clouds. Therefore, a general circulation model (GCM) that models the evolution of weather and climate must include an accurate physical model of the clouds. This paper describes efforts to develop a suitable cloud model. It concentrates on the microphysical processes that determine the evolution of droplet and ice crystal size distributions, precipitation rates, total and condensed water content, and radiative extinction coefficients

  15. MODELING DUST IN THE MAGELLANIC CLOUDS

    Energy Technology Data Exchange (ETDEWEB)

    Zonca, Alberto; Casu, Silvia; Mulas, Giacomo; Aresu, Giambattista [INAF—Osservatorio Astronomico di Cagliari, Via della Scienza 5, I-09047 Selargius (Italy); Cecchi-Pestellini, Cesare, E-mail: azonca@oa-cagliari.inaf.it, E-mail: silvia@oa-cagliari.inaf.it, E-mail: gmulas@oa-cagliari.inaf.it, E-mail: garesu@oa-cagliari.inaf.it, E-mail: cecchi-pestellini@astropa.inaf.it [INAF—Osservatorio Astronomico di Palermo, P.za Parlamento 1, I-90134 Palermo (Italy)

    2015-09-01

    We model the extinction profiles observed in the Small and Large Magellanic clouds with a synthetic population of dust grains consisting of core-mantle particles and a collection of free-flying polycyclic aromatic hydrocarbons (PAHs). All different flavors of the extinction curves observed in the Magellanic Clouds (MCs) can be described by the present model, which has been previously (successfully) applied to a large sample of diffuse and translucent lines of sight in the Milky Way. We find that in the MCs the extinction produced by classical grains is generally larger than absorption by PAHs. Within this model, the nonlinear far-UV rise is accounted for by PAHs, whose presence in turn is always associated with a gap in the size distribution of classical particles. This hints either at a physical connection between (e.g., a common cause for) PAHs and the absence of middle-sized dust particles or the need for an additional component in the model that can account for the nonlinear far-UV rise without contributing to the UV bump at ∼217 nm such as, e.g., nanodiamonds.

  16. MODELING DUST IN THE MAGELLANIC CLOUDS

    International Nuclear Information System (INIS)

    Zonca, Alberto; Casu, Silvia; Mulas, Giacomo; Aresu, Giambattista; Cecchi-Pestellini, Cesare

    2015-01-01

    We model the extinction profiles observed in the Small and Large Magellanic clouds with a synthetic population of dust grains consisting of core-mantle particles and a collection of free-flying polycyclic aromatic hydrocarbons (PAHs). All different flavors of the extinction curves observed in the Magellanic Clouds (MCs) can be described by the present model, which has been previously (successfully) applied to a large sample of diffuse and translucent lines of sight in the Milky Way. We find that in the MCs the extinction produced by classical grains is generally larger than absorption by PAHs. Within this model, the nonlinear far-UV rise is accounted for by PAHs, whose presence in turn is always associated with a gap in the size distribution of classical particles. This hints either at a physical connection between (e.g., a common cause for) PAHs and the absence of middle-sized dust particles or the need for an additional component in the model that can account for the nonlinear far-UV rise without contributing to the UV bump at ∼217 nm such as, e.g., nanodiamonds

  17. Analysis of albedo versus cloud fraction relationships in liquid water clouds using heuristic models and large eddy simulation

    Science.gov (United States)

    Feingold, Graham; Balsells, Joseph; Glassmeier, Franziska; Yamaguchi, Takanobu; Kazil, Jan; McComiskey, Allison

    2017-07-01

    The relationship between the albedo of a cloudy scene A and cloud fraction fc is studied with the aid of heuristic models of stratocumulus and cumulus clouds. Existing work has shown that scene albedo increases monotonically with increasing cloud fraction but that the relationship varies from linear to superlinear. The reasons for these differences in functional dependence are traced to the relationship between cloud deepening and cloud widening. When clouds deepen with no significant increase in fc (e.g., in solid stratocumulus), the relationship between A and fc is linear. When clouds widen as they deepen, as in cumulus cloud fields, the relationship is superlinear. A simple heuristic model of a cumulus cloud field with a power law size distribution shows that the superlinear A-fc behavior is traced out either through random variation in cloud size distribution parameters or as the cloud field oscillates between a relative abundance of small clouds (steep slopes on a log-log plot) and a relative abundance of large clouds (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 cloud size distribution are highly correlated. Further analysis of the large eddy model-generated cloud fields suggests that cumulus clouds grow larger and deeper as their underlying plumes aggregate; this is followed by breakup of large plumes and a tendency to smaller clouds. The cloud and thermal size distributions oscillate back and forth approximately in unison.

  18. A Reputation-Based Identity Management Model for Cloud Computing

    Directory of Open Access Journals (Sweden)

    Lifa Wu

    2015-01-01

    Full Text Available In the field of cloud computing, most research on identity management has concentrated on protecting user data. However, users typically leave a trail when they access cloud services, and the resulting user traceability can potentially lead to the leakage of sensitive user information. Meanwhile, malicious users can do harm to cloud providers through the use of pseudonyms. To solve these problems, we introduce a reputation mechanism and design a reputation-based identity management model for cloud computing. In the model, pseudonyms are generated based on a reputation signature so as to guarantee the untraceability of pseudonyms, and a mechanism that calculates user reputation is proposed, which helps cloud service providers to identify malicious users. Analysis verifies that the model can ensure that users access cloud services anonymously and that cloud providers assess the credibility of users effectively without violating user privacy.

  19. A Model for Comparing Free Cloud Platforms

    Directory of Open Access Journals (Sweden)

    Radu LIXANDROIU

    2014-01-01

    Full Text Available VMware, VirtualBox, Virtual PC and other popular desktop virtualization applications are used only by a few users of IT techniques. This article attempts to make a comparison model for choosing the best cloud platform. Many virtualization applications such as VMware (VMware Player, Oracle VirtualBox and Microsoft Virtual PC are free for home users. The main goal of the virtualization software is that it allows users to run multiple operating systems simultane-ously on one virtual environment, using one computer desktop.

  20. Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

    Science.gov (United States)

    Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.; hide

    2014-01-01

    The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) - a crucial parameter to estimate the thermal cloud radiative forcing - can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 kilometers lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0

  1. Impact of cloud microphysics on cloud-radiation interactions in the CSU general circulation model

    Energy Technology Data Exchange (ETDEWEB)

    Fowler, L.D.; Randall, D.A.

    1995-04-01

    Our ability to study and quantify the impact of cloud-radiation interactions in studying global scale climate variations strongly relies upon the ability of general circulation models (GCMs) to simulate the coupling between the spatial and temporal variations of the model-generated cloudiness and atmospheric moisture budget components. In particular, the ability of GCMs to reproduce the geographical distribution of the sources and sinks of the planetary radiation balance depends upon their representation of the formation and dissipation of cloudiness in conjunction with cloud microphysics processes, and the fractional amount and optical characteristics of cloudiness in conjunction with the mass of condensate stored in the atmosphere. A cloud microphysics package which encompasses five prognostic variables for the mass of water vapor, cloud water, cloud ice, rain, and snow has been implemented in the Colorado State University General Circulation Model (CSU GCM) to simulate large-scale condensation processes. Convection interacts with the large-scale environment through the detrainment of cloud water and cloud ice at the top of cumulus towers. The cloud infrared emissivity and cloud optical depth of the model-generated cloudiness are interactive and depend upon the mass of cloud water and cloud ice suspended in the atmosphere. The global atmospheric moisture budget and planetary radiation budget of the CSU GCM obtained from a perpetual January simulation are discussed. Geographical distributions of the atmospheric moisture species are presented. Global maps of the top-of-atmosphere outgoing longwave radiation and planetary albedo are compared against Earth Radiation Budget Experiment (ERBE) satellite data.

  2. Deployment Models: Towards Eliminating Security Concerns From Cloud Computing

    OpenAIRE

    Zhao, Gansen; Chunming, Rong; Jaatun, Martin Gilje; Sandnes, Frode Eika

    2010-01-01

    Cloud computing has become a popular choice as an alternative to investing new IT systems. When making decisions on adopting cloud computing related solutions, security has always been a major concern. This article summarizes security concerns in cloud computing and proposes five service deployment models to ease these concerns. The proposed models provide different security related features to address different requirements and scenarios and can serve as reference models for deployment. D...

  3. Cloud Computing Adoption Business Model Factors: Does Enterprise Size Matter?

    OpenAIRE

    Bogataj Habjan, Kristina; Pucihar, Andreja

    2017-01-01

    This paper presents the results of research investigating the impact of business model factors on cloud computing adoption. The introduced research model consists of 40 cloud computing business model factors, grouped into eight factor groups. Their impact and importance for cloud computing adoption were investigated among enterpirses in Slovenia. Furthermore, differences in opinion according to enterprise size were investigated. Research results show no statistically significant impacts of in...

  4. A stratiform cloud parameterization for General Circulation Models

    International Nuclear Information System (INIS)

    Ghan, S.J.; Leung, L.R.; Chuang, C.C.; Penner, J.E.; McCaa, J.

    1994-01-01

    The crude treatment of clouds in General Circulation Models (GCMs) is widely recognized as a major limitation in the application of these models to predictions of global climate change. The purpose of this project is to develop a paxameterization for stratiform clouds in GCMs that expresses stratiform clouds in terms of bulk microphysical properties and their subgrid variability. In this parameterization, precipitating cloud species are distinguished from non-precipitating species, and the liquid phase is distinguished from the ice phase. The size of the non-precipitating cloud particles (which influences both the cloud radiative properties and the conversion of non-precipitating cloud species to precipitating species) is determined by predicting both the mass and number concentrations of each species

  5. Remote Sensing of Smoke, Land and Clouds from the NASA ER-2 during SAFARI 2000

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Moeller, Christopher C.; Revercomb, Henry E.; Chu, D. Allen

    2002-01-01

    The NASA ER-2 aircraft was deployed to southern Africa between August 17 and September 25, 2000 as part of the Southern Africa Regional Science Initiative (SAFARI) 2000. This aircraft carried a sophisticated array of multispectral scanners, multiangle spectroradiometers, a monostatic lidar, a gas correlation radiometer, upward and downward spectral flux radiometers, and two metric mapping cameras. These observations were obtained over a 3200 x 2800 km region of savanna, woody savanna, open shrubland, and grassland ecosystems throughout southern Africa, and were quite often coordinated with overflights by NASA's Terra and Landsat 7 satellites. The primary purpose of this sophisticated high altitude observing platform was to obtain independent observations of smoke, clouds, and land surfaces that could be used to check the validity of various remote sensing measurements derived by Earth-orbiting satellites. These include such things as the accuracy of the Moderate Resolution Imaging Spectro-radiometer (MODIS) cloud mask for distinguishing clouds and heavy aerosol from land and ocean surfaces, and Terra analyses of cloud optical and micro-physical properties, aerosol properties, leaf area index, vegetation index, fire occurrence, carbon monoxide, and surface radiation budget. In addition to coordination with Terra and Landsat 7 satellites, numerous flights were conducted over surface AERONET sites, flux towers in South Africa, Botswana, and Zambia, and in situ aircraft from the University of Washington, South Africa, and the United Kingdom.

  6. A Sparse Dictionary Learning-Based Adaptive Patch Inpainting Method for Thick Clouds Removal from High-Spatial Resolution Remote Sensing Imagery.

    Science.gov (United States)

    Meng, Fan; Yang, Xiaomei; Zhou, Chenghu; Li, Zhi

    2017-09-15

    Cloud cover is inevitable in optical remote sensing (RS) imagery on account of the influence of observation conditions, which limits the availability of RS data. Therefore, it is of great significance to be able to reconstruct the cloud-contaminated ground information. This paper presents a sparse dictionary learning-based image inpainting method for adaptively recovering the missing information corrupted by thick clouds patch-by-patch. A feature dictionary was learned from exemplars in the cloud-free regions, which was later utilized to infer the missing patches via sparse representation. To maintain the coherence of structures, structure sparsity was brought in to encourage first filling-in of missing patches on image structures. The optimization model of patch inpainting was formulated under the adaptive neighborhood-consistency constraint, which was solved by a modified orthogonal matching pursuit (OMP) algorithm. In light of these ideas, the thick-cloud removal scheme was designed and applied to images with simulated and true clouds. Comparisons and experiments show that our method can not only keep structures and textures consistent with the surrounding ground information, but also yield rare smoothing effect and block effect, which is more suitable for the removal of clouds from high-spatial resolution RS imagery with salient structures and abundant textured features.

  7. Remote Sensing of Tropical Ecosystems: Atmospheric Correction and Cloud Masking Matter

    Science.gov (United States)

    Hilker, Thomas; Lyapustin, Alexei I.; Tucker, Compton J.; Sellers, Piers J.; Hall, Forrest G.; Wang, Yujie

    2012-01-01

    Tropical rainforests are significant contributors to the global cycles of energy, water and carbon. As a result, monitoring of the vegetation status over regions such as Amazonia has been a long standing interest of Earth scientists trying to determine the effect of climate change and anthropogenic disturbance on the tropical ecosystems and its feedback on the Earth's climate. Satellite-based remote sensing is the only practical approach for observing the vegetation dynamics of regions like the Amazon over useful spatial and temporal scales, but recent years have seen much controversy over satellite-derived vegetation states in Amazônia, with studies predicting opposite feedbacks depending on data processing technique and interpretation. Recent results suggest that some of this uncertainty could stem from a lack of quality in atmospheric correction and cloud screening. In this paper, we assess these uncertainties by comparing the current standard surface reflectance products (MYD09, MYD09GA) and derived composites (MYD09A1, MCD43A4 and MYD13A2 - Vegetation Index) from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to results obtained from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. MAIAC uses a new cloud screening technique, and novel aerosol retrieval and atmospheric correction procedures which are based on time-series and spatial analyses. Our results show considerable improvements of MAIAC processed surface reflectance compared to MYD09/MYD13 with noise levels reduced by a factor of up to 10. Uncertainties in the current MODIS surface reflectance product were mainly due to residual cloud and aerosol contamination which affected the Normalized Difference Vegetation Index (NDVI): During the wet season, with cloud cover ranging between 90 percent and 99 percent, conventionally processed NDVI was significantly depressed due to undetected clouds. A smaller reduction in NDVI due to increased

  8. Route Assessment for Unmanned Aerial Vehicle Based on Cloud Model

    Directory of Open Access Journals (Sweden)

    Xixia Sun

    2014-01-01

    Full Text Available An integrated route assessment approach based on cloud model is proposed in this paper, where various sources of uncertainties are well kept and modeled by cloud theory. Firstly, a systemic criteria framework incorporating models for scoring subcriteria is developed. Then, the cloud model is introduced to represent linguistic variables, and survivability probability histogram of each route is converted into normal clouds by cloud transformation, enabling both randomness and fuzziness in the assessment environment to be managed simultaneously. Finally, a new way to measure the similarity between two normal clouds satisfying reflexivity, symmetry, transitivity, and overlapping is proposed. Experimental results demonstrate that the proposed route assessment approach outperforms fuzzy logic based assessment approach with regard to feasibility, reliability, and consistency with human thinking.

  9. Explicit prediction of ice clouds in general circulation models

    Science.gov (United States)

    Kohler, Martin

    1999-11-01

    Although clouds play extremely important roles in the radiation budget and hydrological cycle of the Earth, there are large quantitative uncertainties in our understanding of their generation, maintenance and decay mechanisms, representing major obstacles in the development of reliable prognostic cloud water schemes for General Circulation Models (GCMs). Recognizing their relative neglect in the past, both observationally and theoretically, this work places special focus on ice clouds. A recent version of the UCLA - University of Utah Cloud Resolving Model (CRM) that includes interactive radiation is used to perform idealized experiments to study ice cloud maintenance and decay mechanisms under various conditions in term of: (1) background static stability, (2) background relative humidity, (3) rate of cloud ice addition over a fixed initial time-period and (4) radiation: daytime, nighttime and no-radiation. Radiation is found to have major effects on the life-time of layer-clouds. Optically thick ice clouds decay significantly slower than expected from pure microphysical crystal fall-out (taucld = 0.9--1.4 h as opposed to no-motion taumicro = 0.5--0.7 h). This is explained by the upward turbulent fluxes of water induced by IR destabilization, which partially balance the downward transport of water by snowfall. Solar radiation further slows the ice-water decay by destruction of the inversion above cloud-top and the resulting upward transport of water. Optically thin ice clouds, on the other hand, may exhibit even longer life-times (>1 day) in the presence of radiational cooling. The resulting saturation mixing ratio reduction provides for a constant cloud ice source. These CRM results are used to develop a prognostic cloud water scheme for the UCLA-GCM. The framework is based on the bulk water phase model of Ose (1993). The model predicts cloud liquid water and cloud ice separately, and which is extended to split the ice phase into suspended cloud ice (predicted

  10. Architecting the cloud design decisions for cloud computing service models (SaaS, PaaS, and IaaS)

    CERN Document Server

    Kavis, Michael J

    2014-01-01

    An expert guide to selecting the right cloud service model for your business Cloud computing is all the rage, allowing for the delivery of computing and storage capacity to a diverse community of end-recipients. However, before you can decide on a cloud model, you need to determine what the ideal cloud service model is for your business. Helping you cut through all the haze, Architecting the Cloud is vendor neutral and guides you in making one of the most critical technology decisions that you will face: selecting the right cloud service model(s) based on a combination of both business and tec

  11. A fast infrared radiative transfer model for overlapping clouds

    International Nuclear Information System (INIS)

    Niu Jianguo; Yang Ping; Huang Hunglung; Davies, James E.; Li Jun; Baum, Bryan A.; Hu, Yong X.

    2007-01-01

    A fast infrared radiative transfer model (FIRTM2) appropriate for application to both single-layered and overlapping cloud situations is developed for simulating the outgoing infrared spectral radiance at the top of the atmosphere (TOA). In FIRTM2 a pre-computed library of cloud reflectance and transmittance values is employed to account for one or two cloud layers, whereas the background atmospheric optical thickness due to gaseous absorption can be computed from a clear-sky radiative transfer model. FIRTM2 is applicable to three atmospheric conditions: (1) clear-sky (2) single-layered ice or water cloud, and (3) two simultaneous cloud layers in a column (e.g., ice cloud overlying water cloud). Moreover, FIRTM2 outputs the derivatives (i.e., Jacobians) of the TOA brightness temperature with respect to cloud optical thickness and effective particle size. Sensitivity analyses have been carried out to assess the performance of FIRTM2 for two spectral regions, namely the longwave (LW) band (587.3-1179.5 cm -1 ) and the short-to-medium wave (SMW) band (1180.1-2228.9 cm -1 ). The assessment is carried out in terms of brightness temperature differences (BTD) between FIRTM2 and the well-known discrete ordinates radiative transfer model (DISORT), henceforth referred to as BTD (F-D). The BTD (F-D) values for single-layered clouds are generally less than 0.8 K. For the case of two cloud layers (specifically ice cloud over water cloud), the BTD (F-D) values are also generally less than 0.8 K except for the SMW band for the case of a very high altitude (>15 km) cloud comprised of small ice particles. Note that for clear-sky atmospheres, FIRTM2 reduces to the clear-sky radiative transfer model that is incorporated into FIRTM2, and the errors in this case are essentially those of the clear-sky radiative transfer model

  12. Implementation of a Novel Educational Modeling Approach for Cloud Computing

    Directory of Open Access Journals (Sweden)

    Sara Ouahabi

    2014-12-01

    Full Text Available The Cloud model is cost-effective because customers pay for their actual usage without upfront costs, and scalable because it can be used more or less depending on the customers’ needs. Due to its advantages, Cloud has been increasingly adopted in many areas, such as banking, e-commerce, retail industry, and academy. For education, cloud is used to manage the large volume of educational resources produced across many universities in the cloud. Keep interoperability between content in an inter-university Cloud is not always easy. Diffusion of pedagogical contents on the Cloud by different E-Learning institutions leads to heterogeneous content which influence the quality of teaching offered by university to teachers and learners. From this reason, comes the idea of using IMS-LD coupled with metadata in the cloud. This paper presents the implementation of our previous educational modeling by combining an application in J2EE with Reload editor that consists of modeling heterogeneous content in the cloud. The new approach that we followed focuses on keeping interoperability between Educational Cloud content for teachers and learners and facilitates the task of identification, reuse, sharing, adapting teaching and learning resources in the Cloud.

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

    Science.gov (United States)

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

    2008-01-01

    ]. Please see Tao et al. (2007) for more detailed description on aerosol impact on precipitation. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

  14. Dispersion modeling by kinematic simulation: Cloud dispersion model

    International Nuclear Information System (INIS)

    Fung, J C H; Perkins, R J

    2008-01-01

    A new technique has been developed to compute mean and fluctuating concentrations in complex turbulent flows (tidal current near a coast and deep ocean). An initial distribution of material is discretized into any small clouds which are advected by a combination of the mean flow and large scale turbulence. The turbulence can be simulated either by kinematic simulation (KS) or direct numerical simulation. The clouds also diffuse relative to their centroids; the statistics for this are obtained from a separate calculation of the growth of individual clouds in small scale turbulence, generated by KS. The ensemble of discrete clouds is periodically re-discretized, to limit the size of the small clouds and prevent overlapping. The model is illustrated with simulations of dispersion in uniform flow, and the results are compared with analytic, steady state solutions. The aim of this study is to understand how pollutants disperses in a turbulent flow through a numerical simulation of fluid particle motion in a random flow field generated by Fourier modes. Although this homogeneous turbulent is rather a 'simple' flow, it represents a building block toward understanding pollutant dispersion in more complex flow. The results presented here are preliminary in nature, but we expect that similar qualitative results should be observed in a genuine turbulent flow.

  15. A comparison of food crispness based on the cloud model.

    Science.gov (United States)

    Wang, Minghui; Sun, Yonghai; Hou, Jumin; Wang, Xia; Bai, Xue; Wu, Chunhui; Yu, Libo; Yang, Jie

    2018-02-01

    The cloud model is a typical model which transforms the qualitative concept into the quantitative description. The cloud model has been used less extensively in texture studies before. The purpose of this study was to apply the cloud model in food crispness comparison. The acoustic signals of carrots, white radishes, potatoes, Fuji apples, and crystal pears were recorded during compression. And three time-domain signal characteristics were extracted, including sound intensity, maximum short-time frame energy, and waveform index. The three signal characteristics and the cloud model were used to compare the crispness of the samples mentioned above. The crispness based on the Ex value of the cloud model, in a descending order, was carrot > potato > white radish > Fuji apple > crystal pear. To verify the results of the acoustic signals, mechanical measurement and sensory evaluation were conducted. The results of the two verification experiments confirmed the feasibility of the cloud model. The microstructures of the five samples were also analyzed. The microstructure parameters were negatively related with crispness (p cloud model method can be used for crispness comparison of different kinds of foods. The method is more accurate than the traditional methods such as mechanical measurement and sensory evaluation. The cloud model method can also be applied to other texture studies extensively. © 2017 Wiley Periodicals, Inc.

  16. Business process modeling in the cloud

    OpenAIRE

    Yarahmadi, Aziz

    2014-01-01

    In this study, I have defined the first steps of creating a methodological framework to implement a cloud business application. The term 'cloud' here refers to applying the processing power of a network of computing tools to business solutions in order to move on from legacy systems. I have introduced the hardware and software requirements of cloud computing in business and the procedure by which the business needs will be found, analyzed and recorded as a decision making system. But first we...

  17. Defining Generic Architecture for Cloud Infrastructure as a Service model

    NARCIS (Netherlands)

    Demchenko, Y.; de Laat, C.

    2011-01-01

    Infrastructure as a Service (IaaS) is one of the provisioning models for Clouds as defined in the NIST Clouds definition. Although widely used, current IaaS implementations and solutions doesn’t have common and well defined architecture model. The paper attempts to define a generic architecture for

  18. Defining generic architecture for Cloud IaaS provisioning model

    NARCIS (Netherlands)

    Demchenko, Y.; de Laat, C.; Mavrin, A.; Leymann, F.; Ivanov, I.; van Sinderen, M.; Shishkov, B.

    2011-01-01

    Infrastructure as a Service (IaaS) is one of the provisioning models for Clouds as defined in the NIST Clouds definition. Although widely used, current IaaS implementations and solutions doesn’t have common and well defined architecture model. The paper attempts to define a generic architecture for

  19. Establishing a Cloud Computing Success Model for Hospitals in Taiwan

    Science.gov (United States)

    Lian, Jiunn-Woei

    2017-01-01

    The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services. PMID:28112020

  20. Establishing a Cloud Computing Success Model for Hospitals in Taiwan.

    Science.gov (United States)

    Lian, Jiunn-Woei

    2017-01-01

    The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services.

  1. Establishing a Cloud Computing Success Model for Hospitals in Taiwan

    Directory of Open Access Journals (Sweden)

    Jiunn-Woei Lian PhD

    2017-01-01

    Full Text Available The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality and system quality directly affect cloud computing satisfaction, whereas service quality indirectly affects the satisfaction through trust. In other words, trust serves as the mediator between service quality and satisfaction. This cloud computing success model will help hospitals evaluate or achieve success after adopting private cloud computing health care services.

  2. Modeling of clouds and radiation for development of parameterizations for general circulation models

    International Nuclear Information System (INIS)

    Westphal, D.; Toon, B.; Jensen, E.; Kinne, S.; Ackerman, A.; Bergstrom, R.; Walker, A.

    1994-01-01

    Atmospheric Radiation Measurement (ARM) Program research at NASA Ames Research Center (ARC) includes radiative transfer modeling, cirrus cloud microphysics, and stratus cloud modeling. These efforts are designed to provide the basis for improving cloud and radiation parameterizations in our main effort: mesoscale cloud modeling. The range of non-convective cloud models used by the ARM modeling community can be crudely categorized based on the number of predicted hydrometers such as cloud water, ice water, rain, snow, graupel, etc. The simplest model has no predicted hydrometers and diagnoses the presence of clouds based on the predicted relative humidity. The vast majority of cloud models have two or more predictive bulk hydrometers and are termed either bulk water (BW) or size-resolving (SR) schemes. This study compares the various cloud models within the same dynamical framework, and compares results with observations rather than climate statistics

  3. Protecting Mobile Crowd Sensing against Sybil Attacks Using Cloud Based Trust Management System

    Directory of Open Access Journals (Sweden)

    Shih-Hao Chang

    2016-01-01

    Full Text Available Mobile crowd sensing (MCS arises as a new sensing paradigm, which leverages citizens for large-scale sensing by various mobile devices to efficiently collect and share local information. Unlike other MCS application challenges that consider user privacy and data trustworthiness, this study focuses on the network trustworthiness problem, namely, Sybil attacks in MCS network. The Sybil attack in computer security is a type of security attack, which illegally forges multiple identities in peer-to-peer networks, namely, Sybil identities. These Sybil identities will falsify multiple identities that negatively influence the effectiveness of sensing data in this MCS network or degrading entire network performance. To cope with this problem, a cloud based trust management scheme (CbTMS was proposed to detect Sybil attacks in the MCS network. The CbTMS was proffered for performing active and passive checking scheme, in addition to the mobile PCS trustworthiness management, and includes a decision tree algorithm, to verify the covered nodes in the MCS network. Simulation studies show that our CbTMS can efficiently detect the malicious Sybil nodes in the network and cause 6.87 Wh power reduction compared with other malicious Sybil node attack mode.

  4. Establishing a Cloud Computing Success Model for Hospitals in Taiwan

    OpenAIRE

    Lian, Jiunn-Woei

    2017-01-01

    The purpose of this study is to understand the critical quality-related factors that affect cloud computing success of hospitals in Taiwan. In this study, private cloud computing is the major research target. The chief information officers participated in a questionnaire survey. The results indicate that the integration of trust into the information systems success model will have acceptable explanatory power to understand cloud computing success in the hospital. Moreover, information quality...

  5. Determining Best Estimates and Uncertainties in Cloud Microphysical Parameters from ARM Field Data: Implications for Models, Retrieval Schemes and Aerosol-Cloud-Radiation Interactions

    Energy Technology Data Exchange (ETDEWEB)

    McFarquhar, Greg [Univ. of Illinois, Urbana, IL (United States)

    2015-12-28

    We proposed to analyze in-situ cloud data collected during ARM/ASR field campaigns to create databases of cloud microphysical properties and their uncertainties as needed for the development of improved cloud parameterizations for models and remote sensing retrievals, and for evaluation of model simulations and retrievals. In particular, we proposed to analyze data collected over the Southern Great Plains (SGP) during the Mid-latitude Continental Convective Clouds Experiment (MC3E), the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX), the Small Particles in Cirrus (SPARTICUS) Experiment and the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign, over the North Slope of Alaska during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE), and over the Tropical Western Pacific (TWP) during The Tropical Warm Pool International Cloud Experiment (TWP-ICE), to meet the following 3 objectives; derive statistical databases of single ice particle properties (aspect ratio AR, dominant habit, mass, projected area) and distributions of ice crystals (size distributions SDs, mass-dimension m-D, area-dimension A-D relations, mass-weighted fall speeds, single-scattering properties, total concentrations N, ice mass contents IWC), complete with uncertainty estimates; assess processes by which aerosols modulate cloud properties in arctic stratus and mid-latitude cumuli, and quantify aerosol’s influence in context of varying meteorological and surface conditions; and determine how ice cloud microphysical, single-scattering and fall-out properties and contributions of small ice crystals to such properties vary according to location, environment, surface, meteorological and aerosol conditions, and develop parameterizations of such effects.In this report we describe the accomplishments that we made on all 3 research objectives.

  6. A Review on Broker Based Cloud Service Model

    Directory of Open Access Journals (Sweden)

    Nagarajan Rajganesh

    2016-09-01

    Full Text Available Cloud computing emerged as a utility oriented computing that facilitates resource sharing under pay-as-you-go model. Nowadays, cloud offerings are not limited to range of services and anything can be shared as a service through the Internet. In this work, a detailed literature survey with respect to cloud service discovery and composition has been accounted. A proposed architecture with the inclusion of cloud broker is presented in our work. It focuses the importance of suitable service selection and its ranking towards fulfilling the customer’s service requirements. The proposed cloud broker advocates techniques such as reasoning and decision making capabilities for the improved cloud service selection and composition.

  7. Validation of Cloud Optical Parameters from Passive Remote Sensing in the Arctic by using the Aircraft Measurements

    Science.gov (United States)

    Chen, H.; Schmidt, S.; Coddington, O.; Wind, G.; Bucholtz, A.; Segal-Rosenhaimer, M.; LeBlanc, S. E.

    2017-12-01

    Cloud Optical Parameters (COPs: e.g., cloud optical thickness and cloud effective radius) and surface albedo are the most important inputs for determining the Cloud Radiative Effect (CRE) at the surface. In the Arctic, the COPs derived from passive remote sensing such as from the Moderate Resolution Imaging Spectroradiometer (MODIS) are difficult to obtain with adequate accuracy owing mainly to insufficient knowledge about the snow/ice surface, but also because of the low solar zenith angle. This study aims to validate COPs derived from passive remote sensing in the Arctic by using aircraft measurements collected during two field campaigns based in Fairbanks, Alaska. During both experiments, ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) and ARISE (Arctic Radiation-IceBridge Sea and Ice Experiment), the Solar Spectral Flux Radiometer (SSFR) measured upwelling and downwelling shortwave spectral irradiances, which can be used to derive surface and cloud albedo, as well as the irradiance transmitted by clouds. We assess the variability of the Arctic sea ice/snow surfaces albedo through these aircraft measurements and incorporate this variability into cloud retrievals for SSFR. We then compare COPs as derived from SSFR and MODIS for all suitable aircraft underpasses of the satellites. Finally, the sensitivities of the COPs to surface albedo and solar zenith angle are investigated.

  8. Cloud model construct for transaction-based cooperative systems ...

    African Journals Online (AJOL)

    Cloud model construct for transaction-based cooperative systems. ... procure cutting edge Information Technology infrastructure are some of the problems faced ... Results also reveal that credit cooperatives will benefit from the model by taking ...

  9. The emerging role of cloud computing in molecular modelling.

    Science.gov (United States)

    Ebejer, Jean-Paul; Fulle, Simone; Morris, Garrett M; Finn, Paul W

    2013-07-01

    There is a growing recognition of the importance of cloud computing for large-scale and data-intensive applications. The distinguishing features of cloud computing and their relationship to other distributed computing paradigms are described, as are the strengths and weaknesses of the approach. We review the use made to date of cloud computing for molecular modelling projects and the availability of front ends for molecular modelling applications. Although the use of cloud computing technologies for molecular modelling is still in its infancy, we demonstrate its potential by presenting several case studies. Rapid growth can be expected as more applications become available and costs continue to fall; cloud computing can make a major contribution not just in terms of the availability of on-demand computing power, but could also spur innovation in the development of novel approaches that utilize that capacity in more effective ways. Copyright © 2013 Elsevier Inc. All rights reserved.

  10. Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

    Science.gov (United States)

    Su, X.

    2017-12-01

    A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

  11. Evaluation of a stratiform cloud parameterization for general circulation models

    Energy Technology Data Exchange (ETDEWEB)

    Ghan, S.J.; Leung, L.R. [Pacific Northwest National Lab., Richland, WA (United States); McCaa, J. [Univ. of Washington, Seattle, WA (United States)

    1996-04-01

    To evaluate the relative importance of horizontal advection of cloud versus cloud formation within the grid cell of a single column model (SCM), we have performed a series of simulations with our SCM driven by a fixed vertical velocity and various rates of horizontal advection.

  12. Higher-fidelity yet efficient modeling of radiation energy transport through three-dimensional clouds

    International Nuclear Information System (INIS)

    Hall, M.L.; Davis, A.B.

    2005-01-01

    Accurate modeling of radiative energy transport through cloudy atmospheres is necessary for both climate modeling with GCMs (Global Climate Models) and remote sensing. Previous modeling efforts have taken advantage of extreme aspect ratios (cells that are very wide horizontally) by assuming a 1-D treatment vertically - the Independent Column Approximation (ICA). Recent attempts to resolve radiation transport through the clouds have drastically changed the aspect ratios of the cells, moving them closer to unity, such that the ICA model is no longer valid. We aim to provide a higher-fidelity atmospheric radiation transport model which increases accuracy while maintaining efficiency. To that end, this paper describes the development of an efficient 3-D-capable radiation code that can be easily integrated into cloud resolving models as an alternative to the resident 1-D model. Applications to test cases from the Intercomparison of 3-D Radiation Codes (I3RC) protocol are shown

  13. Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

    Science.gov (United States)

    Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

    2015-12-01

    Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in

  14. NASA 3D Models: CloudSat

    Data.gov (United States)

    National Aeronautics and Space Administration — Launched in April 2006, CloudSat monitors the state of the Earth’s atmosphere and weather with a sophisticated radar system. The instrument, jointly developed with...

  15. [Treatment of cloud radiative effects in general circulation models

    International Nuclear Information System (INIS)

    Wang, W.C.

    1993-01-01

    This is a renewal proposal for an on-going project of the Department of Energy (DOE)/Atmospheric Radiation Measurement (ARM) Program. The objective of the ARM Program is to improve the treatment of radiation-cloud in GCMs so that reliable predictions of the timing and magnitude of greenhouse gas-induced global warming and regional responses can be made. The ARM Program supports two research areas: (I) The modeling and analysis of data related to the parameterization of clouds and radiation in general circulation models (GCMs); and (II) the development of advanced instrumentation for both mapping the three-dimensional structure of the atmosphere and high accuracy/precision radiometric observations. The present project conducts research in area (I) and focuses on GCM treatment of cloud life cycle, optical properties, and vertical overlapping. The project has two tasks: (1) Development and Refinement of GCM Radiation-Cloud Treatment Using ARM Data; and (2) Validation of GCM Radiation-Cloud Treatment

  16. Icecube: Spaceflight Validation of an 874-GHz Submillimeter Wave Radiometer for Ice Cloud Remote Sensing

    Science.gov (United States)

    Wu, D. L.; Esper, J.; Ehsan, N.; Piepmeier, J. R.; Racette, P.

    2014-12-01

    Ice clouds play a key role in the Earth's radiation budget, mostly through their strong regulation of infrared radiation exchange. Submillimeter wave remote sensing offers a unique capability to improve cloud ice measurements from space. At 874 GHz cloud scattering produces a larger brightness temperature depression from cirrus than lower frequencies, which can be used to retrieve vertically-integrated cloud ice water path (IWP) and ice particle size. The objective of the IceCube project is to retire risks of 874-GHz receiver technology by raising its TRL from 5 to 7. The project will demonstrate, on a 3-U CubeSat in a low Earth orbit (LEO) environment, the 874-GHz receiver system with noise equivalent differential temperature (NEDT) of ~0.2 K for 1-second integration and calibration error of 2.0 K or less as measured from deep-space observations. The Goddard Space Flight Center (GSFC) is partnering with Virginia Diodes, Inc (VDI) to qualify commercially available 874-GHz receiver technology for spaceflight, and demonstrate the radiometer performance. The instrument (submm-wave cloud radiometer, or SCR), along with the CubeSat system developed and integrated by GSFC, will be ready for launch in two years. The instrument subsystem includes a reflector antenna, sub-millimeter wave mixer, frequency multipliers and stable local oscillator, an intermediate frequency (IF) circuit with noise injection, and data-power boards. The mixer and frequency multipliers are procured from VDI with GSFC insight into fabrication and testing processes to ensure scalability to spaceflight beyond TRL 7. The remaining components are a combination of GSFC-designed and commercial off-the-shelf (COTS) at TRLs of 5 or higher. The spacecraft system is specified by GSFC and comprises COTS components including three-axis stabilizer and sun sensor, GPS receiver, deployable solar arrays, UHF radio, and 2 GB of on-board storage. The spacecraft and instrument are integrated and flight qualified

  17. A cost modelling system for cloud computing

    OpenAIRE

    Ajeh, Daniel; Ellman, Jeremy; Keogh, Shelagh

    2014-01-01

    An advance in technology unlocks new opportunities for organizations to increase their productivity, efficiency and process automation while reducing the cost of doing business as well. The emergence of cloud computing addresses these prospects through the provision of agile systems that are scalable, flexible and reliable as well as cost effective. Cloud computing has made hosting and deployment of computing resources cheaper and easier with no up-front charges but pay per-use flexible payme...

  18. Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

    Science.gov (United States)

    Yang, Mengzhao; Song, Wei; Mei, Haibin

    2017-07-23

    The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

  19. Cloud Impacts on Pavement Temperature in Energy Balance Models

    Science.gov (United States)

    Walker, C. L.

    2013-12-01

    Forecast systems provide decision support for end-users ranging from the solar energy industry to municipalities concerned with road safety. Pavement temperature is an important variable when considering vehicle response to various weather conditions. A complex, yet direct relationship exists between tire and pavement temperatures. Literature has shown that as tire temperature increases, friction decreases which affects vehicle performance. Many forecast systems suffer from inaccurate radiation forecasts resulting in part from the inability to model different types of clouds and their influence on radiation. This research focused on forecast improvement by determining how cloud type impacts the amount of shortwave radiation reaching the surface and subsequent pavement temperatures. The study region was the Great Plains where surface solar radiation data were obtained from the High Plains Regional Climate Center's Automated Weather Data Network stations. Road pavement temperature data were obtained from the Meteorological Assimilation Data Ingest System. Cloud properties and radiative transfer quantities were obtained from the Clouds and Earth's Radiant Energy System mission via Aqua and Terra Moderate Resolution Imaging Spectroradiometer satellite products. An additional cloud data set was incorporated from the Naval Research Laboratory Cloud Classification algorithm. Statistical analyses using a modified nearest neighbor approach were first performed relating shortwave radiation variability with road pavement temperature fluctuations. Then statistical associations were determined between the shortwave radiation and cloud property data sets. Preliminary results suggest that substantial pavement forecasting improvement is possible with the inclusion of cloud-specific information. Future model sensitivity testing seeks to quantify the magnitude of forecast improvement.

  20. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1993-01-01

    Most of today's general circulation models (GCMS) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, there has arisen an urgent need for improvements in the treatment of clouds in GCMS, especially as the clouds relate to radiation. In the present paper, we investigate the effects of introducing pregnostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the long wave emissivity calculations. Results from several sensitivity simulations show that realistic cloud water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds become stronger, due to more realistic tropical convection

  1. Cloud Computing Adoption Model for Universities to Increase ICT Proficiency

    Directory of Open Access Journals (Sweden)

    Safiya Okai

    2014-08-01

    Full Text Available Universities around the world especially those in developing countries are faced with the problem of delivering the level of information and communications technology (ICT needed to facilitate teaching, learning, research, and development activities ideal in a typical university, which is needed to meet educational needs in-line with advancement in technology and the growing dependence on IT. This is mainly due to the high cost involved in providing and maintaining the needed hardware and software. A technology such as cloud computing that delivers on demand provisioning of IT resources on a pay per use basis can be used to address this problem. Cloud computing promises better delivery of IT services as well as availability whenever and wherever needed at reduced costs with users paying only as much as they consume through the services of cloud service providers. The cloud technology reduces complexity while increasing speed and quality of IT services provided; however, despite these benefits the challenges that come with its adoption have left many sectors especially the higher education skeptical in committing to this technology. This article identifies the reasons for the slow rate of adoption of cloud computing at university level, discusses the challenges faced and proposes a cloud computing adoption model that contains strategic guidelines to overcome the major challenges identified and a roadmap for the successful adoption of cloud computing by universities. The model was tested in one of the universities and found to be both useful and appropriate for adopting cloud computing at university level.

  2. Combined observational and modeling efforts of aerosol-cloud-precipitation interactions over Southeast Asia

    Science.gov (United States)

    Loftus, Adrian; Tsay, Si-Chee; Nguyen, Xuan Anh

    2016-04-01

    droplet size and number concentration, but also the spectral width of the cloud droplet size distribution, the 3M scheme is well suited to simulate aerosol-cloud-precipitation interactions within a three-dimensional regional cloud model. Moreover, the additional variability predicted on the hydrometeor distributions provides beneficial input for forward models to link the simulated microphysical processes with observations as well as to assess both ground-based and satellite retrieval methods. In this presentation, we provide an overview of the 7 South East Asian Studies / Biomass-burning Aerosols and Stratocumulus Environment: Lifecycles and Interactions Experiment (7-SEAS/BASELInE) operations during the spring of 2013. Preliminary analyses of pre-monsoon Sc system lifecycles observed during the first-ever deployment of a ground-based cloud radar to northern Vietnam will be also be presented. Initial results from GCE model simulations of these Sc using double-moment and the new 3M bulk microphysics schemes under various aerosol loadings will be used to showcase the 3M scheme as well as provide insight into how the impact of aerosols on cloud and precipitation processes in stratocumulus over land may manifest themselves in simulated remote-sensing signals. Applications and future work involving ongoing 7-SEAS campaigns aimed at improving our understanding of aerosol-cloud-precipitation interactions of will also be discussed.

  3. A Condensation–coalescence Cloud Model for Exoplanetary Atmospheres: Formulation and Test Applications to Terrestrial and Jovian Clouds

    Energy Technology Data Exchange (ETDEWEB)

    Ohno, Kazumasa; Okuzumi, Satoshi [Department of Earth and Planetary Sciences, Tokyo Institute of Technology, Meguro, Tokyo 152-8551 (Japan)

    2017-02-01

    A number of transiting exoplanets have featureless transmission spectra that might suggest the presence of clouds at high altitudes. A realistic cloud model is necessary to understand the atmospheric conditions under which such high-altitude clouds can form. In this study, we present a new cloud model that takes into account the microphysics of both condensation and coalescence. Our model provides the vertical profiles of the size and density of cloud and rain particles in an updraft for a given set of physical parameters, including the updraft velocity and the number density of cloud condensation nuclei (CCNs). We test our model by comparing with observations of trade-wind cumuli on Earth and ammonia ice clouds 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 cloud droplets by up to an order of magnitude. For Jovian ammonia clouds, the condensation–coalescence model simultaneously reproduces the effective particle radius, cloud optical thickness, and cloud 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 clouds but also in Jovian ice clouds. 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 clouds via cloud microphysics.

  4. A Condensation–coalescence Cloud Model for Exoplanetary Atmospheres: Formulation and Test Applications to Terrestrial and Jovian Clouds

    International Nuclear Information System (INIS)

    Ohno, Kazumasa; Okuzumi, Satoshi

    2017-01-01

    A number of transiting exoplanets have featureless transmission spectra that might suggest the presence of clouds at high altitudes. A realistic cloud model is necessary to understand the atmospheric conditions under which such high-altitude clouds can form. In this study, we present a new cloud model that takes into account the microphysics of both condensation and coalescence. Our model provides the vertical profiles of the size and density of cloud and rain particles in an updraft for a given set of physical parameters, including the updraft velocity and the number density of cloud condensation nuclei (CCNs). We test our model by comparing with observations of trade-wind cumuli on Earth and ammonia ice clouds 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 cloud droplets by up to an order of magnitude. For Jovian ammonia clouds, the condensation–coalescence model simultaneously reproduces the effective particle radius, cloud optical thickness, and cloud 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 clouds but also in Jovian ice clouds. 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 clouds via cloud microphysics.

  5. Scaling predictive modeling in drug development with cloud computing.

    Science.gov (United States)

    Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

    2015-01-26

    Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

  6. The accuracy of remotely-sensed IWC: An assessment from MLS, TRMM and CloudSat statistics

    Science.gov (United States)

    Wu, D. L.; Heymsfield, A. J.

    2006-12-01

    Understanding climate change requires accurate global cloud ice water content (IWC) measurements. Satellite remote sensing has been the major tool to provide such global observations, but the accuracy of deduced IWC depends on knowledge of cloud microphysics learned from in-situ samples. Because only limited number and type of ice clouds have been measured by in-situ sensors, the knowledge about cloud microphysics is incomplete, and the IWC accuracy from remote sensing can vary from 30% to 200% from case to case. Recent observations from MLS, TRMM and CloudSat allow us to evaluate consistency and accuracy of IWCs deduced from passive and active satellite techniques. In this study we conduct statistical analyses on the tropical and subtropical IWCs observed by MLS, TRMM and CloudSat. The probability density functions (PDFs) of IWC are found to depend on the volume size of averaging, and therefore data need to be averaged into the same volume in order for fair comparisons. Showing measurement noise, bias and sensitivity, the PDF is a better characterization than an average for evaluating IWC accuracy because an averaged IWC depends on cloud-detection threshold that can vary from sensor to sensor. Different thresholds will not only change the average value but also change cloud fraction and occurrence frequency. Our study shows that MLS and TRMM IWCs, despite large differences in sensitivity with little overlap, can still be compared under PDF. The two statistics are generally consistent within 50% at ~13 km, obeying an approximate lognormal distribution as suggested by some ground-based radar observations. MLS has sensitivity to IWC of 1-100 mg/m3 whereas TRMM can improve its sensitivity to IWC as low as 70 mg/m3 if the radar data are averaged properly for the equivalent volume of MLS samples. The proper statistical averaging requires full characteristics of IWC noise, which are not available for products normally derived from radar reflectivity, and therefore we

  7. The effects of aerosols on precipitation and dimensions of subtropical clouds: a sensitivity study using a numerical cloud model

    Directory of Open Access Journals (Sweden)

    A. Teller

    2006-01-01

    Full Text Available Numerical experiments were carried out using the Tel-Aviv University 2-D cloud model to investigate the effects of increased concentrations of Cloud Condensation Nuclei (CCN, giant CCN (GCCN and Ice Nuclei (IN on the development of precipitation and cloud structure in mixed-phase sub-tropical convective clouds. In order to differentiate between the contribution of the aerosols and the meteorology, all simulations were conducted with the same meteorological conditions. The results show that under the same meteorological conditions, polluted clouds (with high CCN concentrations produce less precipitation than clean clouds (with low CCN concentrations, the initiation of precipitation is delayed and the lifetimes of the clouds are longer. GCCN enhance the total precipitation on the ground in polluted clouds but they have no noticeable effect on cleaner clouds. The increased rainfall due to GCCN is mainly a result of the increased graupel mass in the cloud, but it only partially offsets the decrease in rainfall due to pollution (increased CCN. The addition of more effective IN, such as mineral dust particles, reduces the total amount of precipitation on the ground. This reduction is more pronounced in clean clouds than in polluted ones. Polluted clouds reach higher altitudes and are wider than clean clouds and both produce wider clouds (anvils when more IN are introduced. Since under the same vertical sounding the polluted clouds produce less rain, more water vapor is left aloft after the rain stops. In our simulations about 3.5 times more water evaporates after the rain stops from the polluted cloud as compared to the clean cloud. The implication is that much more water vapor is transported from lower levels to the mid troposphere under polluted conditions, something that should be considered in climate models.

  8. Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

    Science.gov (United States)

    Rind, David; Lonergan, P.; Shah, K.

    1999-01-01

    The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows

  9. Polar clouds and radiation in satellite observations, reanalyses, and climate models

    NARCIS (Netherlands)

    Lenaerts, JTM; Van Tricht, Kristof; Lhermitte, S.L.M.; L'Ecuyer, T.S.

    2017-01-01

    Clouds play a pivotal role in the surface energy budget of the polar regions. Here we use two largely independent data sets of cloud and surface downwelling radiation observations derived by satellite remote sensing (2007–2010) to evaluate simulated clouds and radiation over both polar ice sheets

  10. A Multilateral Negotiation Model for Cloud Service Market

    Science.gov (United States)

    Yoo, Dongjin; Sim, Kwang Mong

    Trading cloud services between consumers and providers is a complicated issue of cloud computing. Since a consumer can negotiate with multiple providers to acquire the same service and each provider can receive many requests from multiple consumers, to facilitate the trading of cloud services among multiple consumers and providers, a multilateral negotiation model for cloud market is necessary. The contribution of this work is the proposal of a business model supporting a multilateral price negotiation for trading cloud services. The design of proposed systems for cloud service market includes considering a many-to-many negotiation protocol, and price determining factor from service level feature. Two negotiation strategies are implemented: 1) MDA (Market Driven Agent); and 2) adaptive concession making responding to changes of bargaining position are proposed for cloud service market. Empirical results shows that MDA achieved better performance in some cases that the adaptive concession making strategy, it is noted that unlike the MDA, the adaptive concession making strategy does not assume that an agent has information of the number of competitors (e.g., a consumer agent adopting the adaptive concession making strategy need not know the number of consumer agents competing for the same service).

  11. Prognostic cloud water in the Los Alamos general circulation model

    International Nuclear Information System (INIS)

    Kristjansson, J.E.; Kao, C.Y.J.

    1994-01-01

    Most of today's general circulation models (GCMs) have a greatly simplified treatment of condensation and clouds. Recent observational studies of the earth's radiation budget have suggested cloud-related feedback mechanisms to be of tremendous importance for the issue of global change. Thus, an urgent need for improvements in the treatment of clouds in GCMs has arisen, especially as the clouds relate to radiation. In this paper, we investigate the effects of introducing prognostic cloud water into the Los Alamos GCM. The cloud water field, produced by both stratiform and convective condensation, is subject to 3-dimensional advection and vertical diffusion. The cloud water enters the radiation calculations through the longwave emissivity calculations. Results from several sensitivity simulations show that realistic water and precipitation fields can be obtained with the applied method. Comparisons with observations show that the most realistic results are obtained when more sophisticated schemes for moist convection are introduced at the same time. The model's cold bias is reduced and the zonal winds becomes stronger because of more realistic tropical convection

  12. Development and Testing of a Life Cycle Model and a Parameterization of Thin Mid-level Stratiform Clouds

    Energy Technology Data Exchange (ETDEWEB)

    Krueger, Steven K.

    2008-03-03

    We used a cloud-resolving model (a detailed computer model of cloud systems) to evaluate and improve the representation of clouds in global atmospheric models used for numerical weather prediction and climate modeling. We also used observations of the atmospheric state, including clouds, made at DOE's Atmospheric Radiation Measurement (ARM) Program's Climate Research Facility located in the Southern Great Plains (Kansas and Oklahoma) during Intensive Observation Periods to evaluate our detailed computer model as well as a single-column version of a global atmospheric model used for numerical weather prediction (the Global Forecast System of the NOAA National Centers for Environmental Prediction). This so-called Single-Column Modeling approach has proved to be a very effective method for testing the representation of clouds in global atmospheric models. The method relies on detailed observations of the atmospheric state, including clouds, in an atmospheric column comparable in size to a grid column used in a global atmospheric model. The required observations are made by a combination of in situ and remote sensing instruments. One of the greatest problems facing mankind at the present is climate change. Part of the problem is our limited ability to predict the regional patterns of climate change. In order to increase this ability, uncertainties in climate models must be reduced. One of the greatest of these uncertainties is the representation of clouds and cloud processes. This project, and ARM taken as a whole, has helped to improve the representation of clouds in global atmospheric models.

  13. Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part II: Multi-layered cloud

    Energy Technology Data Exchange (ETDEWEB)

    Morrison, H; McCoy, R B; Klein, S A; Xie, S; Luo, Y; Avramov, A; Chen, M; Cole, J; Falk, M; Foster, M; Genio, A D; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; McFarquhar, G; Poellot, M; Shipway, B; Shupe, M; Sud, Y; Turner, D; Veron, D; Walker, G; Wang, Z; Wolf, A; Xu, K; Yang, F; Zhang, G

    2008-02-27

    Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a deep, multi-layered, mixed-phase cloud system observed during the ARM Mixed-Phase Arctic Cloud Experiment. This cloud system was associated with strong surface turbulent sensible and latent heat fluxes as cold air flowed over the open Arctic Ocean, combined with a low pressure system that supplied moisture at mid-level. The simulations, performed by 13 single-column and 4 cloud-resolving models, generally overestimate the liquid water path and strongly underestimate the ice water path, although there is a large spread among the models. This finding is in contrast with results for the single-layer, low-level mixed-phase stratocumulus case in Part I of this study, as well as previous studies of shallow mixed-phase Arctic clouds, that showed an underprediction of liquid water path. The overestimate of liquid water path and underestimate of ice water path occur primarily when deeper mixed-phase clouds extending into the mid-troposphere were observed. These results suggest important differences in the ability of models to simulate Arctic mixed-phase clouds that are deep and multi-layered versus shallow and single-layered. In general, models with a more sophisticated, two-moment treatment of the cloud microphysics produce a somewhat smaller liquid water path that is closer to observations. The cloud-resolving models tend to produce a larger cloud fraction than the single-column models. The liquid water path and especially the cloud fraction have a large impact on the cloud radiative forcing at the surface, which is dominated by the longwave flux for this case.

  14. Integrating Cloud-Computing-Specific Model into Aircraft Design

    Science.gov (United States)

    Zhimin, Tian; Qi, Lin; Guangwen, Yang

    Cloud Computing is becoming increasingly relevant, as it will enable companies involved in spreading this technology to open the door to Web 3.0. In the paper, the new categories of services introduced will slowly replace many types of computational resources currently used. In this perspective, grid computing, the basic element for the large scale supply of cloud services, will play a fundamental role in defining how those services will be provided. The paper tries to integrate cloud computing specific model into aircraft design. This work has acquired good results in sharing licenses of large scale and expensive software, such as CFD (Computational Fluid Dynamics), UG, CATIA, and so on.

  15. Development of a cloud microphysical model and parameterizations to describe the effect of CCN on warm cloud

    Directory of Open Access Journals (Sweden)

    N. Kuba

    2006-01-01

    Full Text Available First, a hybrid cloud microphysical model was developed that incorporates both Lagrangian and Eulerian frameworks to study quantitatively the effect of cloud condensation nuclei (CCN on the precipitation of warm clouds. A parcel model and a grid model comprise the cloud model. The condensation growth of CCN in each parcel is estimated in a Lagrangian framework. Changes in cloud droplet size distribution arising from condensation and coalescence are calculated on grid points using a two-moment bin method in a semi-Lagrangian framework. Sedimentation and advection are estimated in the Eulerian framework between grid points. Results from the cloud model show that an increase in the number of CCN affects both the amount and the area of precipitation. Additionally, results from the hybrid microphysical model and Kessler's parameterization were compared. Second, new parameterizations were developed that estimate the number and size distribution of cloud droplets given the updraft velocity and the number of CCN. The parameterizations were derived from the results of numerous numerical experiments that used the cloud microphysical parcel model. The input information of CCN for these parameterizations is only several values of CCN spectrum (they are given by CCN counter for example. It is more convenient than conventional parameterizations those need values concerned with CCN spectrum, C and k in the equation of N=CSk, or, breadth, total number and median radius, for example. The new parameterizations' predictions of initial cloud droplet size distribution for the bin method were verified by using the aforesaid hybrid microphysical model. The newly developed parameterizations will save computing time, and can effectively approximate components of cloud microphysics in a non-hydrostatic cloud model. The parameterizations are useful not only in the bin method in the regional cloud-resolving model but also both for a two-moment bulk microphysical model and

  16. Numerical simulations of altocumulus with a cloud resolving model

    Energy Technology Data Exchange (ETDEWEB)

    Liu, S.; Krueger, S.K. [Univ. of Utah, Salt Lake City, UT (United States)

    1996-04-01

    Altocumulus and altostratus clouds together cover approximately 22% of the earth`s surface. They play an important role in the earth`s energy budget through their effect on solar and infrared radiation. However, there has been little altocumulus cloud investigation by either modelers or observational programs. Starr and Cox (SC) (1985a,b) simulated an altostratus case as part of the same study in which they modeled a thin layer of cirrus. Although this calculation was originally described as representing altostratus, it probably better represents altocumulus stratiformis. In this paper, we simulate altocumulus cloud with a cloud resolving model (CRM). We simply describe the CRM first. We calculate the same middle-level cloud case as SC to compare our results with theirs. We will look at the role of cloud-scale processes in response to large-scale forcing. We will also discuss radiative effects by simulating diurnal and nocturnal cases. Finally, we discuss the utility of a 1D model by comparing 1D simulations and 2D simulations.

  17. Intelligent Cloud Learning Model for Online Overseas Chinese Education

    Directory of Open Access Journals (Sweden)

    Yidong Chen

    2015-02-01

    Full Text Available With the development of Chinese economy, oversea Chinese education has been paid more and more attention. However, the overseas Chinese education resource is relatively lack because of historical reasons, which hindered further development . How to better share the Chinese education resources and provide intelligent personalized information service for overseas student is a key problem to be solved. In recent years, the rise of cloud computing provides us an opportunity to realize intelligent learning mode. Cloud computing offers some advantages by allowing users to use infrastructure, platforms and software . In this paper we proposed an intelligent cloud learning model based on cloud computing. The learning model can utilize network resources sufficiently to implement resource sharing according to the personal needs of students, and provide a good practicability for online overseas Chinese education.

  18. A PROFICIENT MODEL FOR HIGH END SECURITY IN CLOUD COMPUTING

    Directory of Open Access Journals (Sweden)

    R. Bala Chandar

    2014-01-01

    Full Text Available Cloud computing is an inspiring technology due to its abilities like ensuring scalable services, reducing the anxiety of local hardware and software management associated with computing while increasing flexibility and scalability. A key trait of the cloud services is remotely processing of data. Even though this technology had offered a lot of services, there are a few concerns such as misbehavior of server side stored data , out of control of data owner's data and cloud computing does not control the access of outsourced data desired by the data owner. To handle these issues, we propose a new model to ensure the data correctness for assurance of stored data, distributed accountability for authentication and efficient access control of outsourced data for authorization. This model strengthens the correctness of data and helps to achieve the cloud data integrity, supports data owner to have control on their own data through tracking and improves the access control of outsourced data.

  19. Aerosol effects on cloud water amounts were successfully simulated by a global cloud-system resolving model.

    Science.gov (United States)

    Sato, Yousuke; Goto, Daisuke; Michibata, Takuro; Suzuki, Kentaroh; Takemura, Toshihiko; Tomita, Hirofumi; Nakajima, Teruyuki

    2018-03-07

    Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol-cloud interactions. In most global climate models (GCMs), the aerosol-cloud interactions are represented by empirical parameterisations, in which the mass of cloud 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 cloud 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 cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

  20. Modelling ice microphysics of mixed-phase clouds

    Science.gov (United States)

    Ahola, J.; Raatikainen, T.; Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Korhonen, H.

    2017-12-01

    The low-level Arctic mixed-phase clouds have a significant role for the Arctic climate due to their ability to absorb and reflect radiation. Since the climate change is amplified in polar areas, it is vital to apprehend the mixed-phase cloud processes. From a modelling point of view, this requires a high spatiotemporal resolution to capture turbulence and the relevant microphysical processes, which has shown to be difficult.In order to solve this problem about modelling mixed-phase clouds, a new ice microphysics description has been developed. The recently published large-eddy simulation cloud model UCLALES-SALSA offers a good base for a feasible solution (Tonttila et al., Geosci. Mod. Dev., 10:169-188, 2017). The model includes aerosol-cloud interactions described with a sectional SALSA module (Kokkola et al., Atmos. Chem. Phys., 8, 2469-2483, 2008), which represents a good compromise between detail and computational expense.Newly, the SALSA module has been upgraded to include also ice microphysics. The dynamical part of the model is based on well-known UCLA-LES model (Stevens et al., J. Atmos. Sci., 56, 3963-3984, 1999) which can be used to study cloud dynamics on a fine grid.The microphysical description of ice is sectional and the included processes consist of formation, growth and removal of ice and snow particles. Ice cloud particles are formed by parameterized homo- or heterogeneous nucleation. The growth mechanisms of ice particles and snow include coagulation and condensation of water vapor. Autoconversion from cloud ice particles to snow is parameterized. The removal of ice particles and snow happens by sedimentation and melting.The implementation of ice microphysics is tested by initializing the cloud simulation with atmospheric observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC). The results are compared to the model results shown in the paper of Ovchinnikov et al. (J. Adv. Model. Earth Syst., 6, 223-248, 2014) and they show a good

  1. Green Functions For Multiple Scattering As Mathematical Tools For Dense Cloud Remote Sensing: Theory, With Passive And Active Applications

    International Nuclear Information System (INIS)

    Davis, A.B.; Marshak, A.; Cahalan, R.F.

    2001-01-01

    We survey radiative Green function theory (1) in linear transport theory where numerical procedures are required to obtain specific results and (2) in the photon diffusion limit (large optical depths) where it is analytically tractable, at least for homogeneous plane-parallel media. We then describe two recent applications of Green function theory to passive cloud remote sensing in the presence of strong three-dimensional transport effects. Finally, we describe recent instrumental breakthroughs in 'off-beam' cloud lidar which is based on direct measurements of radiative Green functions with special attention to the data collected during the Shuttle-based Lidar In-space Technology Experiment (LITE) mission.

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

    Science.gov (United States)

    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

  3. Cloud-to-Ground Lightning Estimates Derived from SSMI Microwave Remote Sensing and NLDN

    Science.gov (United States)

    Winesett, Thomas; Magi, Brian; Cecil, Daniel

    2015-01-01

    present in the cloud and electric charge separation occurs. These ice particles efficiently scatter the microwave radiation at the 85 and 37 GHz frequencies, thus leading to large brightness temperature depressions. Lightning flash rate is related to the total amount of ice passing through the convective updraft regions of thunderstorms. Confirmation of this relationship using TRMM LIS and TMI data, however, remains constrained to TRMM observational limits of the tropics and subtropics. Satellites from the Defense Meteorology Satellite Program (DMSP) have global coverage and are equipped with passive microwave imagers that, like TMI, observe brightness temperatures at 85 and 37 GHz. Unlike the TRMM satellite, however, DMSP satellites do not have a lightning sensor, and the DMSP microwave data has never been used to derive global lightning. In this presentation, a relationship between DMSP Special Sensor Microwave Imager (SSMI) data and ground-based cloud-to-ground (CG) lightning data from NLDN is investigated to derive a spatially complete time history of CG lightning for the USA study area. This relationship is analogous to the established using TRMM LIS and TMI data. NLDN has the most spatially and temporally complete CG lightning data for the USA, and therefore provides the best opportunity to find geospatially coincident observations with SSMI sensors. The strongest thunderstorms generally have minimum 85 GHz Polarized Corrected brightness Temperatures (PCT) less than 150 K. Archived radar data was used to resolve the spatial extent of the individual storms. NLDN data for that storm spatial extent defined by radar data was used to calculate the CG flash rate for the storm. Similar to results using TRMM sensors, a linear model best explained the relationship between storm-specific CG flash rates and minimum 85 GHz PCT. However, the results in this study apply only to CG lightning. To extend the results to weaker storms, the probability of CG lightning (instead of the

  4. Two Models of Magnetic Support for Photoevaporated Molecular Clouds

    International Nuclear Information System (INIS)

    Ryutov, D; Kane, J; Mizuta, A; Pound, M; Remington, B

    2004-01-01

    The thermal pressure inside molecular clouds is insufficient for maintaining the pressure balance at an ablation front at the cloud surface illuminated by nearby UV stars. Most probably, the required stiffness is provided by the magnetic pressure. After surveying existing models of this type, we concentrate on two of them: the model of a quasi-homogeneous magnetic field and the recently proposed model of a ''magnetostatic turbulence''. We discuss observational consequences of the two models, in particular, the structure and the strength of the magnetic field inside the cloud and in the ionized outflow. We comment on the possible role of reconnection events and their observational signatures. We mention laboratory experiments where the most significant features of the models can be tested

  5. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Science.gov (United States)

    Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

    2017-09-01

    The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff

  6. Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

    Directory of Open Access Journals (Sweden)

    A. Ehrlich

    2017-09-01

    Full Text Available The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow. Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C.In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S, λ2 = 1650 nm (sensitive to τ, and λ3 = 2100 nm (sensitive to reff, C are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012 were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice

  7. Modeling, Design, and Implementation of a Cloud Workflow Engine Based on Aneka

    OpenAIRE

    Zhou, Jiantao; Sun, Chaoxin; Fu, Weina; Liu, Jing; Jia, Lei; Tan, Hongyan

    2014-01-01

    This paper presents a Petri net-based model for cloud workflow which plays a key role in industry. Three kinds of parallelisms in cloud workflow are characterized and modeled. Based on the analysis of the modeling, a cloud workflow engine is designed and implemented in Aneka cloud environment. The experimental results validate the effectiveness of our approach of modeling, design, and implementation of cloud workflow.

  8. Above the cloud computing: applying cloud computing principles to create an orbital services model

    Science.gov (United States)

    Straub, Jeremy; Mohammad, Atif; Berk, Josh; Nervold, Anders K.

    2013-05-01

    Large satellites and exquisite planetary missions are generally self-contained. They have, onboard, all of the computational, communications and other capabilities required to perform their designated functions. Because of this, the satellite or spacecraft carries hardware that may be utilized only a fraction of the time; however, the full cost of development and launch are still bone by the program. Small satellites do not have this luxury. Due to mass and volume constraints, they cannot afford to carry numerous pieces of barely utilized equipment or large antennas. This paper proposes a cloud-computing model for exposing satellite services in an orbital environment. Under this approach, each satellite with available capabilities broadcasts a service description for each service that it can provide (e.g., general computing capacity, DSP capabilities, specialized sensing capabilities, transmission capabilities, etc.) and its orbital elements. Consumer spacecraft retain a cache of service providers and select one utilizing decision making heuristics (e.g., suitability of performance, opportunity to transmit instructions and receive results - based on the orbits of the two craft). The two craft negotiate service provisioning (e.g., when the service can be available and for how long) based on the operating rules prioritizing use of (and allowing access to) the service on the service provider craft, based on the credentials of the consumer. Service description, negotiation and sample service performance protocols are presented. The required components of each consumer or provider spacecraft are reviewed. These include fully autonomous control capabilities (for provider craft), a lightweight orbit determination routine (to determine when consumer and provider craft can see each other and, possibly, pointing requirements for craft with directional antennas) and an authentication and resource utilization priority-based access decision making subsystem (for provider craft

  9. Satellite remote sensing of dust aerosol indirect effects on ice cloud formation.

    Science.gov (United States)

    Ou, Steve Szu-Cheng; Liou, Kuo-Nan; Wang, Xingjuan; Hansell, Richard; Lefevre, Randy; Cocks, Stephen

    2009-01-20

    We undertook a new approach to investigate the aerosol indirect effect of the first kind on ice cloud formation by using available data products from the Moderate-Resolution Imaging Spectrometer (MODIS) and obtained physical understanding about the interaction between aerosols and ice clouds. Our analysis focused on the examination of the variability in the correlation between ice cloud parameters (optical depth, effective particle size, cloud water path, and cloud particle number concentration) and aerosol optical depth and number concentration that were inferred from available satellite cloud and aerosol data products. Correlation results for a number of selected scenes containing dust and ice clouds are presented, and dust aerosol indirect effects on ice clouds are directly demonstrated from satellite observations.

  10. A Developed Artificial Bee Colony Algorithm Based on Cloud Model

    Directory of Open Access Journals (Sweden)

    Ye Jin

    2018-04-01

    Full Text Available The Artificial Bee Colony (ABC algorithm is a bionic intelligent optimization method. The cloud model is a kind of uncertainty conversion model between a qualitative concept T ˜ that is presented by nature language and its quantitative expression, which integrates probability theory and the fuzzy mathematics. A developed ABC algorithm based on cloud model is proposed to enhance accuracy of the basic ABC algorithm and avoid getting trapped into local optima by introducing a new select mechanism, replacing the onlooker bees’ search formula and changing the scout bees’ updating formula. Experiments on CEC15 show that the new algorithm has a faster convergence speed and higher accuracy than the basic ABC and some cloud model based ABC variants.

  11. Aerosol and cloud sensing with the Lidar In-space Technology Experiment (LITE)

    Science.gov (United States)

    Winker, D. M.; McCormick, M. P.

    1994-01-01

    The Lidar In-space Technology Experiment (LITE) is a multi-wavelength backscatter lidar developed by NASA Langley Research Center to fly on the Space Shuttle. The LITE instrument is built around a three-wavelength ND:YAG laser and a 1-meter diameter telescope. The laser operates at 10 Hz and produces about 500 mJ per pulse at 1064 nm and 532 nm, and 150 mJ per pulse at 355 nm. The objective of the LITE program is to develop the engineering processes required for space lidar and to demonstrate applications of space-based lidar to remote sensing of the atmosphere. The LITE instrument was designed to study a wide range of cloud and aerosol phenomena. To this end, a comprehensive program of scientific investigations has been planned for the upcoming mission. Simulations of on-orbit performance show the instrument has sufficient sensitivity to detect even thin cirrus on a single-shot basis. Signal averaging provides the capability of measuring the height and structure of the planetary boundary layer, aerosols in the free troposphere, the stratospheric aerosol layer, and density profiles to an altitude of 40 km. The instrument has successfully completed a ground-test phase and is scheduled to fly on the Space Shuttle Discovery for a 9-day mission in September 1994.

  12. A fuzzy neural network model to forecast the percent cloud coverage and cloud top temperature maps

    Directory of Open Access Journals (Sweden)

    Y. Tulunay

    2008-12-01

    Full Text Available Atmospheric processes are highly nonlinear. A small group at the METU in Ankara has been working on a fuzzy data driven generic model of nonlinear processes. The model developed is called the Middle East Technical University Fuzzy Neural Network Model (METU-FNN-M. The METU-FNN-M consists of a Fuzzy Inference System (METU-FIS, a data driven Neural Network module (METU-FNN of one hidden layer and several neurons, and a mapping module, which employs the Bezier Surface Mapping technique. In this paper, the percent cloud coverage (%CC and cloud top temperatures (CTT are forecast one month ahead of time at 96 grid locations. The probable influence of cosmic rays and sunspot numbers on cloudiness is considered by using the METU-FNN-M.

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

    Science.gov (United States)

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

    2012-01-01

    Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and summertime convection over a mid-latitude continent with different concentrations of CCN: a low clean concentration and a high dirty concentration. The impact of atmospheric aerosol concentration on cloud and precipitation will be investigated.

  14. A Scalable Cloud Library Empowering Big Data Management, Diagnosis, and Visualization of Cloud-Resolving Models

    Science.gov (United States)

    Zhou, S.; Tao, W. K.; Li, X.; Matsui, T.; Sun, X. H.; Yang, X.

    2015-12-01

    A cloud-resolving model (CRM) is an atmospheric numerical model that can numerically resolve clouds and cloud systems at 0.25~5km horizontal grid spacings. The main advantage of the CRM is that it can allow explicit interactive processes between microphysics, radiation, turbulence, surface, and aerosols without subgrid cloud fraction, overlapping and convective parameterization. Because of their fine resolution and complex physical processes, it is challenging for the CRM community to i) visualize/inter-compare CRM simulations, ii) diagnose key processes for cloud-precipitation formation and intensity, and iii) evaluate against NASA's field campaign data and L1/L2 satellite data products due to large data volume (~10TB) and complexity of CRM's physical processes. We have been building the Super Cloud Library (SCL) upon a Hadoop framework, capable of CRM database management, distribution, visualization, subsetting, and evaluation in a scalable way. The current SCL capability includes (1) A SCL data model enables various CRM simulation outputs in NetCDF, including the NASA-Unified Weather Research and Forecasting (NU-WRF) and Goddard Cumulus Ensemble (GCE) model, to be accessed and processed by Hadoop, (2) A parallel NetCDF-to-CSV converter supports NU-WRF and GCE model outputs, (3) A technique visualizes Hadoop-resident data with IDL, (4) A technique subsets Hadoop-resident data, compliant to the SCL data model, with HIVE or Impala via HUE's Web interface, (5) A prototype enables a Hadoop MapReduce application to dynamically access and process data residing in a parallel file system, PVFS2 or CephFS, where high performance computing (HPC) simulation outputs such as NU-WRF's and GCE's are located. We are testing Apache Spark to speed up SCL data processing and analysis.With the SCL capabilities, SCL users can conduct large-domain on-demand tasks without downloading voluminous CRM datasets and various observations from NASA Field Campaigns and Satellite data to a

  15. IMAGE TO POINT CLOUD METHOD OF 3D-MODELING

    Directory of Open Access Journals (Sweden)

    A. G. Chibunichev

    2012-07-01

    Full Text Available This article describes the method of constructing 3D models of objects (buildings, monuments based on digital images and a point cloud obtained by terrestrial laser scanner. The first step is the automated determination of exterior orientation parameters of digital image. We have to find the corresponding points of the image and point cloud to provide this operation. Before the corresponding points searching quasi image of point cloud is generated. After that SIFT algorithm is applied to quasi image and real image. SIFT algorithm allows to find corresponding points. Exterior orientation parameters of image are calculated from corresponding points. The second step is construction of the vector object model. Vectorization is performed by operator of PC in an interactive mode using single image. Spatial coordinates of the model are calculated automatically by cloud points. In addition, there is automatic edge detection with interactive editing available. Edge detection is performed on point cloud and on image with subsequent identification of correct edges. Experimental studies of the method have demonstrated its efficiency in case of building facade modeling.

  16. The Route to Raindrop Formation in a Shallow Cumulus Cloud Simulated by a Lagrangian Cloud Model

    Science.gov (United States)

    Noh, Yign; Hoffmann, Fabian; Raasch, Siegfried

    2017-11-01

    The mechanism of raindrop formation in a shallow cumulus cloud is investigated using a Lagrangian cloud model (LCM). The analysis is focused on how and under which conditions a cloud droplet grows to a raindrop by tracking the history of individual Lagrangian droplets. It is found that the rapid collisional growth, leading to raindrop formation, is triggered when single droplets with a radius of 20 μm appear in the region near the cloud top, characterized by a large liquid water content, strong turbulence, large mean droplet size, a broad drop size distribution (DSD), and high supersaturations. Raindrop formation easily occurs when turbulence-induced collision enhancement(TICE) is considered, with or without any extra broadening of the DSD by another mechanism (such as entrainment and mixing). In contrast, when TICE is not considered, raindrop formation is severely delayed if no other broadening mechanism is active. The reason leading to the difference is clarified by the additional analysis of idealized box-simulations of the collisional growth process for different DSDs in varied turbulent environments. It is found that TICE does not accelerate the timing of the raindrop formation for individual droplets, but it enhances the collisional growth rate significantly afterward. KMA R & D Program (Korea), DFG (Germany).

  17. Longitudinal Control for Mengshi Autonomous Vehicle via Gauss Cloud Model

    Directory of Open Access Journals (Sweden)

    Hongbo Gao

    2017-12-01

    Full Text Available Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control technique of autonomous vehicle is basic theory and one key complex technique which must have the reliability and precision of vehicle controller. The longitudinal control technique is one of the foundations of the safety and stability of autonomous vehicle control. In our paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. The longitudinal control algorithm mainly uses cloud model generator to control the acceleration of the autonomous vehicle to achieve the goal that controls the speed of Mengshi autonomous vehicle. The proposed longitudinal control algorithm based on cloud model is verified by real experiments on Highway driving scene. The experiments results of the acceleration and speed show that the algorithm is validity and stability.

  18. Assessment of the accuracy of the conventional ray-tracing technique: Implications in remote sensing and radiative transfer involving ice clouds

    International Nuclear Information System (INIS)

    Bi, Lei; Yang, Ping; Liu, Chao; Yi, Bingqi; Baum, Bryan A.; Diedenhoven, Bastiaan van; Iwabuchi, Hironobu

    2014-01-01

    A fundamental problem in remote sensing and radiative transfer simulations involving ice clouds is the ability to compute accurate optical properties for individual ice particles. While relatively simple and intuitively appealing, the conventional geometric-optics method (CGOM) is used frequently for the solution of light scattering by ice crystals. Due to the approximations in the ray-tracing technique, the CGOM accuracy is not well quantified. The result is that the uncertainties are introduced that can impact many applications. Improvements in the Invariant Imbedding T-matrix method (II-TM) and the Improved Geometric-Optics Method (IGOM) provide a mechanism to assess the aforementioned uncertainties. The results computed by the II-TM+IGOM are considered as a benchmark because the II-TM solves Maxwell's equations from first principles and is applicable to particle size parameters ranging into the domain at which the IGOM has reasonable accuracy. To assess the uncertainties with the CGOM in remote sensing and radiative transfer simulations, two independent optical property datasets of hexagonal columns are developed for sensitivity studies by using the CGOM and the II-TM+IGOM, respectively. Ice cloud bulk optical properties obtained from the two datasets are compared and subsequently applied to retrieve the optical thickness and effective diameter from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. Additionally, the bulk optical properties are tested in broadband radiative transfer (RT) simulations using the general circulation model (GCM) version of the Rapid Radiative Transfer Model (RRTMG) that is adopted in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM, version 5.1). For MODIS retrievals, the mean bias of uncertainties of applying the CGOM in shortwave bands (0.86 and 2.13 μm) can be up to 5% in the optical thickness and as high as 20% in the effective diameter, depending on cloud optical

  19. Cloud-Scale Numerical Modeling of the Arctic Boundary Layer

    Science.gov (United States)

    Krueger, Steven K.

    1998-01-01

    The interactions between sea ice, open ocean, atmospheric radiation, and clouds over the Arctic Ocean exert a strong influence on global climate. Uncertainties in the formulation of interactive air-sea-ice processes in global climate models (GCMs) result in large differences between the Arctic, and global, climates simulated by different models. Arctic stratus clouds are not well-simulated by GCMs, yet exert a strong influence on the surface energy budget of the Arctic. Leads (channels of open water in sea ice) have significant impacts on the large-scale budgets during the Arctic winter, when they contribute about 50 percent of the surface fluxes over the Arctic Ocean, but cover only 1 to 2 percent of its area. Convective plumes generated by wide leads may penetrate the surface inversion and produce condensate that spreads up to 250 km downwind of the lead, and may significantly affect the longwave radiative fluxes at the surface and thereby the sea ice thickness. The effects of leads and boundary layer clouds must be accurately represented in climate models to allow possible feedbacks between them and the sea ice thickness. The FIRE III Arctic boundary layer clouds field program, in conjunction with the SHEBA ice camp and the ARM North Slope of Alaska and Adjacent Arctic Ocean site, will offer an unprecedented opportunity to greatly improve our ability to parameterize the important effects of leads and boundary layer clouds in GCMs.

  20. The ARM Cloud Radar Simulator for Global Climate Models: Bridging Field Data and Climate Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuying [Lawrence Livermore National Laboratory, Livermore, California; Xie, Shaocheng [Lawrence Livermore National Laboratory, Livermore, California; Klein, Stephen A. [Lawrence Livermore National Laboratory, Livermore, California; Marchand, Roger [University of Washington, Seattle, Washington; Kollias, Pavlos [Stony Brook University, Stony Brook, New York; Clothiaux, Eugene E. [The Pennsylvania State University, University Park, Pennsylvania; Lin, Wuyin [Brookhaven National Laboratory, Upton, New York; Johnson, Karen [Brookhaven National Laboratory, Upton, New York; Swales, Dustin [CIRES and NOAA/Earth System Research Laboratory, Boulder, Colorado; Bodas-Salcedo, Alejandro [Met Office Hadley Centre, Exeter, United Kingdom; Tang, Shuaiqi [Lawrence Livermore National Laboratory, Livermore, California; Haynes, John M. [Cooperative Institute for Research in the Atmosphere/Colorado State University, Fort Collins, Colorado; Collis, Scott [Argonne National Laboratory, Argonne, Illinois; Jensen, Michael [Brookhaven National Laboratory, Upton, New York; Bharadwaj, Nitin [Pacific Northwest National Laboratory, Richland, Washington; Hardin, Joseph [Pacific Northwest National Laboratory, Richland, Washington; Isom, Bradley [Pacific Northwest National Laboratory, Richland, Washington

    2018-01-01

    Clouds play an important role in Earth’s radiation budget and hydrological cycle. However, current global climate models (GCMs) have had difficulties in accurately simulating clouds and precipitation. To improve the representation of clouds in climate models, it is crucial to identify where simulated clouds differ from real world observations of them. This can be difficult, since significant differences exist between how a climate model represents clouds and what instruments observe, both in terms of spatial scale and the properties of the hydrometeors which are either modeled or observed. To address these issues and minimize impacts of instrument limitations, the concept of instrument “simulators”, which convert model variables into pseudo-instrument observations, has evolved with the goal to improve and to facilitate the comparison of modeled clouds with observations. Many simulators have (and continue to be developed) for a variety of instruments and purposes. A community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP; Bodas-Salcedo et al. 2011), contains several independent satellite simulators and is being widely used in the global climate modeling community to exploit satellite observations for model cloud evaluation (e.g., Klein et al. 2013; Zhang et al. 2010). This article introduces a ground-based cloud radar simulator developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program for comparing climate model clouds with ARM observations from its vertically pointing 35-GHz radars. As compared to CloudSat radar observations, ARM radar measurements occur with higher temporal resolution and finer vertical resolution. This enables users to investigate more fully the detailed vertical structures within clouds, resolve thin clouds, and quantify the diurnal variability of clouds. Particularly, ARM radars are sensitive to low-level clouds, which are

  1. Longitudinal Control for Mengshi Autonomous Vehicle via Cloud Model

    Science.gov (United States)

    Gao, H. B.; Zhang, X. Y.; Li, D. Y.; Liu, Y. C.

    2018-03-01

    Dynamic robustness and stability control is a requirement for self-driving of autonomous vehicle. Longitudinal control method of autonomous is a key technique which has drawn the attention of industry and academe. In this paper, we present a longitudinal control algorithm based on cloud model for Mengshi autonomous vehicle to ensure the dynamic stability and tracking performance of Mengshi autonomous vehicle. An experiments is applied to test the implementation of the longitudinal control algorithm. Empirical results show that if the longitudinal control algorithm based Gauss cloud model are applied to calculate the acceleration, and the vehicles drive at different speeds, a stable longitudinal control effect is achieved.

  2. Model Infrastruktur dan Manajemen Platform Server Berbasis Cloud Computing

    Directory of Open Access Journals (Sweden)

    Mulki Indana Zulfa

    2017-11-01

    Full Text Available Cloud computing is a new technology that is still very rapidly growing. This technology makes the Internet as the main media for the management of data and applications remotely. Cloud computing allows users to run an application without having to think about infrastructure and its platforms. Other technical aspects such as memory, storage, backup and restore, can be done very easily. This research is intended to modeling the infrastructure and management of computer platform in computer network of Faculty of Engineering, University of Jenderal Soedirman. The first stage in this research is literature study, by finding out the implementation model in previous research. Then the result will be combined with a new approach to existing resources and try to implement directly on the existing server network. The results showed that the implementation of cloud computing technology is able to replace the existing platform network.

  3. BUSINESS MODELLING AND DATABASE DESIGN IN CLOUD COMPUTING

    Directory of Open Access Journals (Sweden)

    Mihai-Constantin AVORNICULUI

    2015-04-01

    Full Text Available Electronic commerce is growing constantly from one year to another in the last decade, few are the areas that also register such a growth. It covers the exchanges of computerized data, but also electronic messaging, linear data banks and electronic transfer payment. Cloud computing, a relatively new concept and term, is a model of access services via the internet to distributed systems of configurable calculus resources at request which can be made available quickly with minimum management effort and intervention from the client and the provider. Behind an electronic commerce system in cloud there is a data base which contains the necessary information for the transactions in the system. Using business modelling, we get many benefits, which makes the design of the database used by electronic commerce systems in cloud considerably easier.

  4. Model-as-a-service (MaaS) using the cloud service innovation platform (CSIP)

    Science.gov (United States)

    Cloud infrastructures for modelling activities such as data processing, performing environmental simulations, or conducting model calibrations/optimizations provide a cost effective alternative to traditional high performance computing approaches. Cloud-based modelling examples emerged into the more...

  5. Testing remote sensing on artificial observations: impact of drizzle and 3-D cloud structure on effective radius retrievals

    Directory of Open Access Journals (Sweden)

    T. Zinner

    2010-10-01

    Full Text Available Remote sensing of cloud effective particle size with passive sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave and midwave infrared channels. In practice, retrieved effective radii from these combinations can be quite different. This difference is perhaps indicative of different penetration depths and path lengths for the spectral reflectances used. In addition, operational liquid water cloud retrievals are based on the assumption of a relatively narrow distribution of droplet sizes; the role of larger precipitation particles in these distributions is neglected. Therefore, possible explanations for the discrepancy in some MODIS spectral size retrievals could include 3-D radiative transport effects, including sub-pixel cloud inhomogeneity, and/or the impact of drizzle formation.

    For three cloud cases the possible factors of influence are isolated and investigated in detail by the use of simulated cloud scenes and synthetic satellite data: marine boundary layer cloud scenes from large eddy simulations (LES with detailed microphysics are combined with Monte Carlo radiative transfer calculations that explicitly account for the detailed droplet size distributions as well as 3-D radiative transfer to simulate MODIS observations. The operational MODIS optical thickness and effective radius retrieval algorithm is applied to these and the results are compared to the given LES microphysics.

    We investigate two types of marine cloud situations each with and without drizzle from LES simulations: (1 a typical daytime stratocumulus deck at two times in the diurnal cycle and (2 one scene with scattered cumulus. Only small impact of drizzle formation on the retrieved domain average and on the differences between the three

  6. VMware private cloud computing with vCloud director

    CERN Document Server

    Gallagher, Simon

    2013-01-01

    It's All About Delivering Service with vCloud Director Empowered by virtualization, companies are not just moving into the cloud, they're moving into private clouds for greater security, flexibility, and cost savings. However, this move involves more than just infrastructure. It also represents a different business model and a new way to provide services. In this detailed book, VMware vExpert Simon Gallagher makes sense of private cloud computing for IT administrators. From basic cloud theory and strategies for adoption to practical implementation, he covers all the issues. You'll lea

  7. Mesoscale Modeling, Forecasting and Remote Sensing Research.

    Science.gov (United States)

    remote sensing , cyclonic scale diagnostic studies and mesoscale numerical modeling and forecasting are summarized. Mechanisms involved in the release of potential instability are discussed and simulated quantitatively, giving particular attention to the convective formulation. The basic mesoscale model is documented including the equations, boundary condition, finite differences and initialization through an idealized frontal zone. Results of tests including a three dimensional test with real data, tests of convective/mesoscale interaction and tests with a detailed

  8. Traffic modelling for Big Data backed telecom cloud

    OpenAIRE

    Via Baraldés, Anna

    2016-01-01

    The objective of this project is to provide traffic models based on new services characteristics. Specifically, we focus on modelling the traffic between origin-destination node pairs (also known as OD pairs) in a telecom network. Two use cases are distinguished: i) traffic generation in the context of simulation, and ii) traffic modelling for prediction in the context of big-data backed telecom cloud systems. To this aim, several machine learning and statistical models and technics are studi...

  9. A Diagnostic PDF Cloud Scheme to Improve Subtropical Low Clouds in NCAR Community Atmosphere Model (CAM5)

    Science.gov (United States)

    Qin, Yi; Lin, Yanluan; Xu, Shiming; Ma, Hsi-Yen; Xie, Shaocheng

    2018-02-01

    Low clouds 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 cloud 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 cloud fraction and cloud condensate and thus alleviates the adjustment needed in the default relative humidity-based cloud fraction scheme. Short-term forecast simulations indicate that low cloud 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 cloud scheme, the new approach produced the mean climate reasonably well with improved shortwave cloud forcing (SWCF) due to more reasonable low cloud fraction and liquid water path over regions with predominant low clouds. Meanwhile, the SWCF bias over the tropical land regions is also alleviated. Furthermore, the simulated marine boundary layer clouds 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 cloud processes with other subgrid-scale physical processes is a promising approach to improve cloud simulations.

  10. DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING OF CLOUDS AND RADIATION USING ARM DATA, FINAL REPORT

    Energy Technology Data Exchange (ETDEWEB)

    Minnis, Patrick [NASA Langley Research Center, Hampton, VA

    2013-06-28

    During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products and raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.

  11. CloudLM: a Cloud-based Language Model for Machine Translation

    Directory of Open Access Journals (Sweden)

    Ferrández-Tordera Jorge

    2016-04-01

    Full Text Available Language models (LMs are an essential element in statistical approaches to natural language processing for tasks such as speech recognition and machine translation (MT. The advent of big data leads to the availability of massive amounts of data to build LMs, and in fact, for the most prominent languages, using current techniques and hardware, it is not feasible to train LMs with all the data available nowadays. At the same time, it has been shown that the more data is used for a LM the better the performance, e.g. for MT, without any indication yet of reaching a plateau. This paper presents CloudLM, an open-source cloud-based LM intended for MT, which allows to query distributed LMs. CloudLM relies on Apache Solr and provides the functionality of state-of-the-art language modelling (it builds upon KenLM, while allowing to query massive LMs (as the use of local memory is drastically reduced, at the expense of slower decoding speed.

  12. The ARM-GCSS Intercomparison Study of Single-Column Models and Cloud System Models

    International Nuclear Information System (INIS)

    Cederwall, R.T.; Rodriques, D.J.; Krueger, S.K.; Randall, D.A.

    1999-01-01

    The Single-Column Model (SCM) Working Group (WC) and the Cloud Working Group (CWG) in the Atmospheric Radiation Measurement (ARM) Program have begun a collaboration with the GEWEX Cloud System Study (GCSS) WGs. The forcing data sets derived from the special ARM radiosonde measurements made during the SCM Intensive Observation Periods (IOPs), the wealth of cloud and related data sets collected by the ARM Program, and the ARM infrastructure support of the SCM WG are of great value to GCSS. In return, GCSS brings the efforts of an international group of cloud system modelers to bear on ARM data sets and ARM-related scientific questions. The first major activity of the ARM-GCSS collaboration is a model intercomparison study involving SCMs and cloud system models (CSMs), also known as cloud-resolving or cloud-ensemble models. The SCM methodologies developed in the ARM Program have matured to the point where an intercomparison will help identify the strengths and weaknesses of various approaches. CSM simulations will bring much additional information about clouds to evaluate cloud parameterizations used in the SCMs. CSMs and SCMs have been compared successfully in previous GCSS intercomparison studies for tropical conditions. The ARM Southern Great Plains (SGP) site offers an opportunity for GCSS to test their models in continental, mid-latitude conditions. The Summer 1997 SCM IOP has been chosen since it provides a wide range of summertime weather events that will be a challenging test of these models

  13. Models of surface convection and dust clouds in brown dwarfs

    International Nuclear Information System (INIS)

    Freytag, B; Allard, F; Ludwig, H-G; Homeier, D; Steffen, M

    2008-01-01

    The influence of dust grains on the atmospheres of brown dwarfs is visible in observed spectra. To investigate what prevents the dust grains from falling down, or how fresh condensable material is mixed up in the atmosphere to allow new grains to form, we performed 2D radiation-hydrodynamics simulations with CO5BOLD of the upper part of the convection zone and the atmosphere containing the dust cloud layers. We find that unlike in models of Cepheids, the convective overshoot does not play a major role. Instead, the mixing in the dust clouds is controlled by gravity waves.

  14. Cloud Computing Platform for an Online Model Library System

    Directory of Open Access Journals (Sweden)

    Mingang Chen

    2013-01-01

    Full Text Available The rapid developing of digital content industry calls for online model libraries. For the efficiency, user experience, and reliability merits of the model library, this paper designs a Web 3D model library system based on a cloud computing platform. Taking into account complex models, which cause difficulties in real-time 3D interaction, we adopt the model simplification and size adaptive adjustment methods to make the system with more efficient interaction. Meanwhile, a cloud-based architecture is developed to ensure the reliability and scalability of the system. The 3D model library system is intended to be accessible by online users with good interactive experiences. The feasibility of the solution has been tested by experiments.

  15. Laboratory and modeling studies of chemistry in dense molecular clouds

    Science.gov (United States)

    Huntress, W. T., Jr.; Prasad, S. S.; Mitchell, G. F.

    1980-01-01

    A chemical evolutionary model with a large number of species and a large chemical library is used to examine the principal chemical processes in interstellar clouds. Simple chemical equilibrium arguments show the potential for synthesis of very complex organic species by ion-molecule radiative association reactions.

  16. Hypersonic: Model Analysis and Checking in the Cloud

    DEFF Research Database (Denmark)

    Acretoaie, Vlad; Störrle, Harald

    2014-01-01

    ”. Objective: In this paper we investigate the conceptual and technical feasibility of a new software architecture for modeling tools, where certain advanced features are factored out of the client and moved towards the Cloud. With this approach we plan to address the above mentioned drawbacks of existing...

  17. A new revenue maximization model using customized plans in cloud ...

    African Journals Online (AJOL)

    Cloud computing is emerging as a promising field offering a variety of computing services to end users. These services are offered at different prices using various pricing schemes and techniques. End users will favor the service provider offering the best quality with the lowest price. Therefore, applying a fair pricing model ...

  18. A security model for saas in cloud computing

    International Nuclear Information System (INIS)

    Abbas, R.; Farooq, A.

    2016-01-01

    Cloud computing is a type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. It has many service modes like Software as-a-Service (SaaS), Platform-as-a-Service (PaaS), Infrastructure-as-a-Service (IaaS). In SaaS model, service providers install and activate the applications in cloud and cloud customers access the software from cloud. So, the user does not have the need to purchase and install a particular software on his/her machine. While using SaaS model, there are multiple security issues and problems like Data security, Data breaches, Network security, Authentication and authorization, Data integrity, Availability, Web application security and Backup which are faced by users. Many researchers minimize these security problems by putting in hard work. A large work has been done to resolve these problems but there are a lot of issues that persist and need to overcome. In this research work, we have developed a security model that improves the security of data according to the desire of the End-user. The proposed model for different data security options can be helpful to increase the data security through which trade-off between functionalities can be optimized for private and public data. (author)

  19. Spectral cumulus parameterization based on cloud-resolving model

    Science.gov (United States)

    Baba, Yuya

    2018-02-01

    We have developed a spectral cumulus parameterization using a cloud-resolving model. This includes a new parameterization of the entrainment rate which was derived from analysis of the cloud properties obtained from the cloud-resolving model simulation and was valid for both shallow and deep convection. The new scheme was examined in a single-column model experiment and compared with the existing parameterization of Gregory (2001, Q J R Meteorol Soc 127:53-72) (GR scheme). The results showed that the GR scheme simulated more shallow and diluted convection than the new scheme. To further validate the physical performance of the parameterizations, Atmospheric Model Intercomparison Project (AMIP) experiments were performed, and the results were compared with reanalysis data. The new scheme performed better than the GR scheme in terms of mean state and variability of atmospheric circulation, i.e., the new scheme improved positive bias of precipitation in western Pacific region, and improved positive bias of outgoing shortwave radiation over the ocean. The new scheme also simulated better features of convectively coupled equatorial waves and Madden-Julian oscillation. These improvements were found to be derived from the modification of parameterization for the entrainment rate, i.e., the proposed parameterization suppressed excessive increase of entrainment, thus suppressing excessive increase of low-level clouds.

  20. Influence of seeing effects on cloud model inversions

    Czech Academy of Sciences Publication Activity Database

    Tziotziou, K.; Heinzel, Petr; Tsiropoula, G.

    2007-01-01

    Roč. 472, č. 1 (2007), s. 287-292 ISSN 0004-6361 Institutional research plan: CEZ:AV0Z10030501 Keywords : cloud model * inversions * seeing effects Subject RIV: BN - Astronomy, Celestial Mechanics, Astrophysics Impact factor: 4.259, year: 2007

  1. Cloud blueprint : A model-driven approach to configuring federated clouds

    NARCIS (Netherlands)

    Papazoglou, M.; Abello, A.; Bellatreche, L.; Benatallah, B.

    2012-01-01

    Current cloud solutions are fraught with problems. They introduce a monolithic cloud stack that imposes vendor lock-in and donot permit developers to mix and match services freely from diverse cloud service tiers and configure them dynamically to address application needs. Cloud blueprinting is a

  2. The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol-cloud interactions in multiscale modeling framework models: tracer transport results

    International Nuclear Information System (INIS)

    Jr, William I Gustafson; Berg, Larry K; Easter, Richard C; Ghan, Steven J

    2008-01-01

    All estimates of aerosol indirect effects on the global energy balance have either completely neglected the influence of aerosol on convective clouds or treated the influence in a highly parameterized manner. Embedding cloud-resolving models (CRMs) within each grid cell of a global model provides a multiscale modeling framework for treating both the influence of aerosols on convective as well as stratiform clouds and the influence of clouds on the aerosol, but treating the interactions explicitly by simulating all aerosol processes in the CRM is computationally prohibitive. An alternate approach is to use horizontal statistics (e.g., cloud mass flux, cloud fraction, and precipitation) from the CRM simulation to drive a single-column parameterization of cloud effects on the aerosol and then use the aerosol profile to simulate aerosol effects on clouds within the CRM. Here, we present results from the first component of the Explicit-Cloud Parameterized-Pollutant parameterization to be developed, which handles vertical transport of tracers by clouds. A CRM with explicit tracer transport serves as a benchmark. We show that this parameterization, driven by the CRM's cloud mass fluxes, reproduces the CRM tracer transport significantly better than a single-column model that uses a conventional convective cloud parameterization

  3. The Explicit-Cloud Parameterized-Pollutant hybrid approach for aerosol-cloud interactions in multiscale modeling framework models: tracer transport results

    Energy Technology Data Exchange (ETDEWEB)

    Jr, William I Gustafson; Berg, Larry K; Easter, Richard C; Ghan, Steven J [Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, PO Box 999, MSIN K9-30, Richland, WA (United States)], E-mail: William.Gustafson@pnl.gov

    2008-04-15

    All estimates of aerosol indirect effects on the global energy balance have either completely neglected the influence of aerosol on convective clouds or treated the influence in a highly parameterized manner. Embedding cloud-resolving models (CRMs) within each grid cell of a global model provides a multiscale modeling framework for treating both the influence of aerosols on convective as well as stratiform clouds and the influence of clouds on the aerosol, but treating the interactions explicitly by simulating all aerosol processes in the CRM is computationally prohibitive. An alternate approach is to use horizontal statistics (e.g., cloud mass flux, cloud fraction, and precipitation) from the CRM simulation to drive a single-column parameterization of cloud effects on the aerosol and then use the aerosol profile to simulate aerosol effects on clouds within the CRM. Here, we present results from the first component of the Explicit-Cloud Parameterized-Pollutant parameterization to be developed, which handles vertical transport of tracers by clouds. A CRM with explicit tracer transport serves as a benchmark. We show that this parameterization, driven by the CRM's cloud mass fluxes, reproduces the CRM tracer transport significantly better than a single-column model that uses a conventional convective cloud parameterization.

  4. The effects of the Boussinesq model to the rising of the explosion clouds

    International Nuclear Information System (INIS)

    Li Xiaoli; Zheng Yi

    2010-01-01

    It is to study the rising of the explosion clouds in the normal atmosphere using Boussinesq model and the Incompressible model, the numerical model is based on the assumption that effects the clouds are gravity and buoyancy. By comparing the evolvement of different density cloud, and gives the conclusion-the Boussinesq model and the Incompressible model is accord when the cloud's density is larger compared to the density of the environment. (authors)

  5. A MODELING METHOD OF FLUTTERING LEAVES BASED ON POINT CLOUD

    OpenAIRE

    J. Tang; Y. Wang; Y. Zhao; Y. Zhao; W. Hao; X. Ning; K. Lv; Z. Shi; M. Zhao

    2017-01-01

    Leaves falling gently or fluttering are common phenomenon in nature scenes. The authenticity of leaves falling plays an important part in the dynamic modeling of natural scenes. The leaves falling model has a widely applications in the field of animation and virtual reality. We propose a novel modeling method of fluttering leaves based on point cloud in this paper. According to the shape, the weight of leaves and the wind speed, three basic trajectories of leaves falling are defined, which ar...

  6. A cloud/particle model of the interstellar medium - Galactic spiral structure

    Science.gov (United States)

    Levinson, F. H.; Roberts, W. W., Jr.

    1981-01-01

    A cloud/particle model for gas flow in galaxies is developed that incorporates cloud-cloud collisions and supernovae as dominant local processes. Cloud-cloud collisions are the main means of dissipation. To counter this dissipation and maintain local dispersion, supernova explosions in the medium administer radial snowplow pushes to all nearby clouds. The causal link between these processes is that cloud-cloud collisions will form stars and that these stars will rapidly become supernovae. The cloud/particle model is tested and used to investigate the gas dynamics and spiral structures in galaxies where these assumptions may be reasonable. Particular attention is given to whether large-scale galactic shock waves, which are thought to underlie the regular well-delineated spiral structure in some galaxies, form and persist in a cloud-supernova dominated interstellar medium; this question is answered in the affirmative.

  7. TUNNEL POINT CLOUD FILTERING METHOD BASED ON ELLIPTIC CYLINDRICAL MODEL

    Directory of Open Access Journals (Sweden)

    N. Zhu

    2016-06-01

    Full Text Available The large number of bolts and screws that attached to the subway shield ring plates, along with the great amount of accessories of metal stents and electrical equipments mounted on the tunnel walls, make the laser point cloud data include lots of non-tunnel section points (hereinafter referred to as non-points, therefore affecting the accuracy for modeling and deformation monitoring. This paper proposed a filtering method for the point cloud based on the elliptic cylindrical model. The original laser point cloud data was firstly projected onto a horizontal plane, and a searching algorithm was given to extract the edging points of both sides, which were used further to fit the tunnel central axis. Along the axis the point cloud was segmented regionally, and then fitted as smooth elliptic cylindrical surface by means of iteration. This processing enabled the automatic filtering of those inner wall non-points. Experiments of two groups showed coincident results, that the elliptic cylindrical model based method could effectively filter out the non-points, and meet the accuracy requirements for subway deformation monitoring. The method provides a new mode for the periodic monitoring of tunnel sections all-around deformation in subways routine operation and maintenance.

  8. Cloud tolerance of remote sensing technologies to measure land surface temperature

    Science.gov (United States)

    Conventional means to estimate land surface temperature (LST) from space relies on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave (MW) obse...

  9. Cloud-Based Model Calibration Using OpenStudio: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Hale, E.; Lisell, L.; Goldwasser, D.; Macumber, D.; Dean, J.; Metzger, I.; Parker, A.; Long, N.; Ball, B.; Schott, M.; Weaver, E.; Brackney, L.

    2014-03-01

    OpenStudio is a free, open source Software Development Kit (SDK) and application suite for performing building energy modeling and analysis. The OpenStudio Parametric Analysis Tool has been extended to allow cloud-based simulation of multiple OpenStudio models parametrically related to a baseline model. This paper describes the new cloud-based simulation functionality and presents a model cali-bration case study. Calibration is initiated by entering actual monthly utility bill data into the baseline model. Multiple parameters are then varied over multiple iterations to reduce the difference between actual energy consumption and model simulation results, as calculated and visualized by billing period and by fuel type. Simulations are per-formed in parallel using the Amazon Elastic Cloud service. This paper highlights model parameterizations (measures) used for calibration, but the same multi-nodal computing architecture is available for other purposes, for example, recommending combinations of retrofit energy saving measures using the calibrated model as the new baseline.

  10. Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud

    Energy Technology Data Exchange (ETDEWEB)

    Klein, S A; McCoy, R B; Morrison, H; Ackerman, A; Avramov, A; deBoer, G; Chen, M; Cole, J; DelGenio, A; Golaz, J; Hashino, T; Harrington, J; Hoose, C; Khairoutdinov, M; Larson, V; Liu, X; Luo, Y; McFarquhar, G; Menon, S; Neggers, R; Park, S; Poellot, M; von Salzen, K; Schmidt, J; Sednev, I; Shipway, B; Shupe, M; Spangenberg, D; Sud, Y; Turner, D; Veron, D; Falk, M; Foster, M; Fridlind, A; Walker, G; Wang, Z; Wolf, A; Xie, S; Xu, K; Yang, F; Zhang, G

    2008-02-27

    Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics indicate that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is some evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics. This case study, which has been well observed from both aircraft and ground-based remote sensors, could be a benchmark for model simulations of mixed-phase clouds.

  11. Remote sensing approach to structural modelling

    International Nuclear Information System (INIS)

    El Ghawaby, M.A.

    1989-01-01

    Remote sensing techniques are quite dependable tools in investigating geologic problems, specially those related to structural aspects. The Landsat imagery provides discrimination between rock units, detection of large scale structures as folds and faults, as well as small scale fabric elements such as foliation and banding. In order to fulfill the aim of geologic application of remote sensing, some essential surveying maps might be done from images prior to the structural interpretation: land-use, land-form drainage pattern, lithological unit and structural lineament maps. Afterwards, the field verification should lead to interpretation of a comprehensive structural model of the study area to apply for the target problem. To deduce such a model, there are two ways of analysis the interpreter may go through: the direct and the indirect methods. The direct one is needed in cases where the resources or the targets are controlled by an obvious or exposed structural element or pattern. The indirect way is necessary for areas where the target is governed by a complicated structural pattern. Some case histories of structural modelling methods applied successfully for exploration of radioactive minerals, iron deposits and groundwater aquifers in Egypt are presented. The progress in imagery, enhancement and integration of remote sensing data with the other geophysical and geochemical data allow a geologic interpretation to be carried out which become better than that achieved with either of the individual data sets. 9 refs

  12. Space Science Cloud: a Virtual Space Science Research Platform Based on Cloud Model

    Science.gov (United States)

    Hu, Xiaoyan; Tong, Jizhou; Zou, Ziming

    Through independent and co-operational science missions, Strategic Pioneer Program (SPP) on Space Science, the new initiative of space science program in China which was approved by CAS and implemented by National Space Science Center (NSSC), dedicates to seek new discoveries and new breakthroughs in space science, thus deepen the understanding of universe and planet earth. In the framework of this program, in order to support the operations of space science missions and satisfy the demand of related research activities for e-Science, NSSC is developing a virtual space science research platform based on cloud model, namely the Space Science Cloud (SSC). In order to support mission demonstration, SSC integrates interactive satellite orbit design tool, satellite structure and payloads layout design tool, payload observation coverage analysis tool, etc., to help scientists analyze and verify space science mission designs. Another important function of SSC is supporting the mission operations, which runs through the space satellite data pipelines. Mission operators can acquire and process observation data, then distribute the data products to other systems or issue the data and archives with the services of SSC. In addition, SSC provides useful data, tools and models for space researchers. Several databases in the field of space science are integrated and an efficient retrieve system is developing. Common tools for data visualization, deep processing (e.g., smoothing and filtering tools), analysis (e.g., FFT analysis tool and minimum variance analysis tool) and mining (e.g., proton event correlation analysis tool) are also integrated to help the researchers to better utilize the data. The space weather models on SSC include magnetic storm forecast model, multi-station middle and upper atmospheric climate model, solar energetic particle propagation model and so on. All the services above-mentioned are based on the e-Science infrastructures of CAS e.g. cloud storage and

  13. Validation of the Two-Layer Model for Correcting Clear Sky Reflectance Near Clouds

    Science.gov (United States)

    Wen, Guoyong; Marshak, Alexander; Evans, K. Frank; Vamal, Tamas

    2014-01-01

    A two-layer model was developed in our earlier studies to estimate the clear sky reflectance enhancement near clouds. This simple model accounts for the radiative interaction between boundary layer clouds and molecular layer above, the major contribution to the reflectance enhancement near clouds for short wavelengths. We use LES/SHDOM simulated 3D radiation fields to valid the two-layer model for reflectance enhancement at 0.47 micrometer. We find: (a) The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; and (b) The magnitude of the 2-layer modeled enhancement agree reasonably well with the "truth" with some expected underestimation. We further extend our model to include cloud-surface interaction using the Poisson model for broken clouds. We found that including cloud-surface interaction improves the correction, though it can introduced some over corrections for large cloud albedo, large cloud optical depth, large cloud fraction, large cloud aspect ratio. This over correction can be reduced by excluding scenes (10 km x 10km) with large cloud fraction for which the Poisson model is not designed for. Further research is underway to account for the contribution of cloud-aerosol radiative interaction to the enhancement.

  14. Cloud condensation nuclei in Western Colorado: Observations and model predictions

    Science.gov (United States)

    Ward, Daniel Stewart

    Variations in the warm cloud-active portion of atmospheric aerosols, or cloud condensation nuclei (CCN), have been shown to impact cloud droplet number concentration and subsequently cloud and precipitation processes. This issue carries special significance in western Colorado where a significant portion of the region's water resources is supplied by precipitation from winter season, orographic clouds, which are particularly sensitive to variations in CCN. Temporal and spatial variations in CCN in western Colorado were investigated using a combination of observations and a new method for modeling CCN. As part of the Inhibition of Snowfall by Pollution Aerosols (ISPA-III) field campaign, total particle and CCN number concentration were measured for a 24-day period in Mesa Verde National Park, climatologically upwind of the San Juan Mountains. These data were combined with CCN observations from Storm Peak Lab (SPL) in northwestern Colorado and from the King Air platform, flying north to south along the Western Slope. Altogether, the sampled aerosols were characteristic of a rural continental environment and the cloud-active portion varied slowly in time, and little in space. Estimates of the is hygroscopicity parameter indicated consistently low aerosol hygroscopicity typical of organic aerosol species. The modeling approach included the addition of prognostic CCN to the Regional Atmospheric Modeling System (RAMS). The RAMS droplet activation scheme was altered using parcel model simulations to include variations in aerosol hygroscopicity, represented by K. Analysis of the parcel model output and a supplemental sensitivity study showed that model CCN will be sensitive to changes in aerosol hygroscopicity, but only for conditions of low supersaturation or small particle sizes. Aerosol number, size distribution median radius, and hygroscopicity (represented by the K parameter) in RAMS were constrained by nudging to forecasts of these quantities from the Weather

  15. Development of a Cloud Resolving Model for Heterogeneous Supercomputers

    Science.gov (United States)

    Sreepathi, S.; Norman, M. R.; Pal, A.; Hannah, W.; Ponder, C.

    2017-12-01

    A cloud resolving climate model is needed to reduce major systematic errors in climate simulations due to structural uncertainty in numerical treatments of convection - such as convective storm systems. This research describes the porting effort to enable SAM (System for Atmosphere Modeling) cloud resolving model on heterogeneous supercomputers using GPUs (Graphical Processing Units). We have isolated a standalone configuration of SAM that is targeted to be integrated into the DOE ACME (Accelerated Climate Modeling for Energy) Earth System model. We have identified key computational kernels from the model and offloaded them to a GPU using the OpenACC programming model. Furthermore, we are investigating various optimization strategies intended to enhance GPU utilization including loop fusion/fission, coalesced data access and loop refactoring to a higher abstraction level. We will present early performance results, lessons learned as well as optimization strategies. The computational platform used in this study is the Summitdev system, an early testbed that is one generation removed from Summit, the next leadership class supercomputer at Oak Ridge National Laboratory. The system contains 54 nodes wherein each node has 2 IBM POWER8 CPUs and 4 NVIDIA Tesla P100 GPUs. This work is part of a larger project, ACME-MMF component of the U.S. Department of Energy(DOE) Exascale Computing Project. The ACME-MMF approach addresses structural uncertainty in cloud processes by replacing traditional parameterizations with cloud resolving "superparameterization" within each grid cell of global climate model. Super-parameterization dramatically increases arithmetic intensity, making the MMF approach an ideal strategy to achieve good performance on emerging exascale computing architectures. The goal of the project is to integrate superparameterization into ACME, and explore its full potential to scientifically and computationally advance climate simulation and prediction.

  16. Synthetic quorum sensing in model microcapsule colonies

    Science.gov (United States)

    Shum, Henry; Balazs, Anna C.

    2017-08-01

    Biological quorum sensing refers to the ability of cells to gauge their population density and collectively initiate a new behavior once a critical density is reached. Designing synthetic materials systems that exhibit quorum sensing-like behavior could enable the fabrication of devices with both self-recognition and self-regulating functionality. Herein, we develop models for a colony of synthetic microcapsules that communicate by producing and releasing signaling molecules. Production of the chemicals is regulated by a biomimetic negative feedback loop, the “repressilator” network. Through theory and simulation, we show that the chemical behavior of such capsules is sensitive to both the density and number of capsules in the colony. For example, decreasing the spacing between a fixed number of capsules can trigger a transition in chemical activity from the steady, repressed state to large-amplitude oscillations in chemical production. Alternatively, for a fixed density, an increase in the number of capsules in the colony can also promote a transition into the oscillatory state. This configuration-dependent behavior of the capsule colony exemplifies quorum-sensing behavior. Using our theoretical model, we predict the transitions from the steady state to oscillatory behavior as a function of the colony size and capsule density.

  17. Added value of far-infrared radiometry for remote sensing of ice clouds

    Science.gov (United States)

    Libois, Quentin; Blanchet, Jean-Pierre

    2017-06-01

    Several cloud retrieval algorithms based on satellite observations in the infrared have been developed in the last decades. However, these observations only cover the midinfrared (MIR, λ transparent in the FIR, using FIR channels would reduce by more than 50% the uncertainties on retrieved values of optical thickness, effective particle diameter, and cloud top altitude. Notably, this would extend the range of applicability of current retrieval methods to the polar regions and to clouds with large optical thickness, where MIR algorithms perform poorly. The high performance of solar reflection-based algorithms would thus be reached in nighttime conditions. Since the sensitivity of ice cloud thermal emission to effective particle diameter is approximately 5 times larger in the FIR than in the MIR, using FIR observations is a promising venue for studying ice cloud microphysics and precipitation processes. This is highly relevant for cirrus clouds and convective towers. This is also essential to study precipitation in the driest regions of the atmosphere, where strong feedbacks are at play between clouds and water vapor. The deployment in the near future of a FIR spaceborne radiometer is technologically feasible and should be strongly supported.

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

    Science.gov (United States)

    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~influencer on the microphysical development of cloud droplets, can be potentially studied with polarimetric retrievals.

  19. Approximate models for broken clouds in stochastic radiative transfer theory

    International Nuclear Information System (INIS)

    Doicu, Adrian; Efremenko, Dmitry S.; Loyola, Diego; Trautmann, Thomas

    2014-01-01

    This paper presents approximate models in stochastic radiative transfer theory. The independent column approximation and its modified version with a solar source computed in a full three-dimensional atmosphere are formulated in a stochastic framework and for arbitrary cloud statistics. The nth-order stochastic models describing the independent column approximations are equivalent to the nth-order stochastic models for the original radiance fields in which the gradient vectors are neglected. Fast approximate models are further derived on the basis of zeroth-order stochastic models and the independent column approximation. The so-called “internal mixing” models assume a combination of the optical properties of the cloud and the clear sky, while the “external mixing” models assume a combination of the radiances corresponding to completely overcast and clear skies. A consistent treatment of internal and external mixing models is provided, and a new parameterization of the closure coefficient in the effective thickness approximation is given. An efficient computation of the closure coefficient for internal mixing models, using a previously derived vector stochastic model as a reference, is also presented. Equipped with appropriate look-up tables for the closure coefficient, these models can easily be integrated into operational trace gas retrieval systems that exploit absorption features in the near-IR solar spectrum. - Highlights: • Independent column approximation in a stochastic setting. • Fast internal and external mixing models for total and diffuse radiances. • Efficient optimization of internal mixing models to match reference models

  20. A simple dynamic rising nuclear cloud based model of ground radioactive fallout for atmospheric nuclear explosion

    International Nuclear Information System (INIS)

    Zheng Yi

    2008-01-01

    A simple dynamic rising nuclear cloud based model for atmospheric nuclear explosion radioactive prediction was presented. The deposition of particles and initial cloud radius changing with time before the cloud stabilization was considered. Large-scale relative diffusion theory was used after cloud stabilization. The model was considered reasonable and dependable in comparison with four U.S. nuclear test cases and DELFIC model results. (authors)

  1. Comparison of convective clouds observed by spaceborne W-band radar and simulated by cloud-resolving atmospheric models

    Science.gov (United States)

    Dodson, Jason B.

    Deep convective clouds (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 cloud-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 cloud vertical structure and convective environment. I also emphasize the transition between shallow clouds 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. CloudSat is used to observe DCCs, and A-Train and reanalysis data are used to represent the large-scale environment in which the clouds form. The CloudSat cloud mask and radar reflectivity profiles for CONUS cumuliform clouds (defined as clouds 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 clouds. Then they are sorted by three large-scale environmental variables: total preciptable

  2. Cloud Masking for Remotely Sensed Data Using Spectral and Principal Components Analysis

    Directory of Open Access Journals (Sweden)

    A. Ahmad

    2012-06-01

    Full Text Available Two methods of cloud masking tuned to tropical conditions have been developed, based on spectral analysis and Principal Components Analysis (PCA of Moderate Resolution Imaging Spectroradiometer (MODIS data. In the spectral approach, thresholds were applied to four reflective bands (1, 2, 3, and 4, three thermal bands (29, 31 and 32, the band 2/band 1 ratio, and the difference between band 29 and 31 in order to detect clouds. The PCA approach applied a threshold to the first principal component derived from the seven quantities used for spectral analysis. Cloud detections were compared with the standard MODIS cloud mask, and their accuracy was assessed using reference images and geographical information on the study area.

  3. Cloud Tolerance of Remote-Sensing Technologies to Measure Land Surface Temperature

    Science.gov (United States)

    Holmes, Thomas R. H.; Hain, Christopher R.; Anderson, Martha C.; Crow, Wade T.

    2016-01-01

    Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared(TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive microwave(MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product. This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

  4. Massive Cloud-Based Big Data Processing for Ocean Sensor Networks and Remote Sensing

    Science.gov (United States)

    Schwehr, K. D.

    2017-12-01

    Until recently, the work required to integrate and analyze data for global-scale environmental issues was prohibitive both in cost and availability. Traditional desktop processing systems are not able to effectively store and process all the data, and super computer solutions are financially out of the reach of most people. The availability of large-scale cloud computing has created tools that are usable by small groups and individuals regardless of financial resources or locally available computational resources. These systems give scientists and policymakers the ability to see how critical resources are being used across the globe with little or no barrier to entry. Google Earth Engine has the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra, MODIS Aqua, and Global Land Data Assimilation Systems (GLDAS) data catalogs available live online. Here we demonstrate these data to calculate the correlation between lagged chlorophyll and rainfall to identify areas of eutrophication, matching these events to ocean currents from datasets like HYbrid Coordinate Ocean Model (HYCOM) to check if there are constraints from oceanographic configurations. The system can provide addition ground truth with observations from sensor networks like the International Comprehensive Ocean-Atmosphere Data Set / Voluntary Observing Ship (ICOADS/VOS) and Argo floats. This presentation is intended to introduce users to the datasets, programming idioms, and functionality of Earth Engine for large-scale, data-driven oceanography.

  5. Intercomparison of model simulations of mixed-phase clouds observed during the ARM Mixed-Phase Arctic Cloud Experiment. Part I: Single layer cloud

    Energy Technology Data Exchange (ETDEWEB)

    Klein, Stephen A.; McCoy, Renata B.; Morrison, Hugh; Ackerman, Andrew S.; Avramov, Alexander; de Boer, Gijs; Chen, Mingxuan; Cole, Jason N.S.; Del Genio, Anthony D.; Falk, Michael; Foster, Michael J.; Fridlind, Ann; Golaz, Jean-Christophe; Hashino, Tempei; Harrington, Jerry Y.; Hoose, Corinna; Khairoutdinov, Marat F.; Larson, Vincent E.; Liu, Xiaohong; Luo, Yali; McFarquhar, Greg M.; Menon, Surabi; Neggers, Roel A. J.; Park, Sungsu; Poellot, Michael R.; Schmidt, Jerome M.; Sednev, Igor; Shipway, Ben J.; Shupe, Matthew D.; Spangenberg, Douglas A.; Sud, Yogesh C.; Turner, David D.; Veron, Dana E.; von Salzen, Knut; Walker, Gregory K.; Wang, Zhien; Wolf, Audrey B.; Xie, Shaocheng; Xu, Kuan-Man; Yang, Fanglin; Zhang, Gong

    2009-02-02

    Results are presented from an intercomparison of single-column and cloud-resolving model simulations of a cold-air outbreak mixed-phase stratocumulus cloud observed during the Atmospheric Radiation Measurement (ARM) program's Mixed-Phase Arctic Cloud Experiment. The observed cloud occurred in a well-mixed boundary layer with a cloud top temperature of -15 C. The observed average liquid water path of around 160 g m{sup -2} was about two-thirds of the adiabatic value and much greater than the average mass of ice crystal precipitation which when integrated from the surface to cloud top was around 15 g m{sup -2}. The simulations were performed by seventeen single-column models (SCMs) and nine cloud-resolving models (CRMs). While the simulated ice water path is generally consistent with the observed values, the median SCM and CRM liquid water path is a factor of three smaller than observed. Results from a sensitivity study in which models removed ice microphysics suggest that in many models the interaction between liquid and ice-phase microphysics is responsible for the large model underestimate of liquid water path. Despite this general underestimate, the simulated liquid and ice water paths of several models are consistent with the observed values. Furthermore, there is evidence that models with more sophisticated microphysics simulate liquid and ice water paths that are in better agreement with the observed values, although considerable scatter is also present. Although no single factor guarantees a good simulation, these results emphasize the need for improvement in the model representation of mixed-phase microphysics.

  6. Using a cloud to replenish parched groundwater modeling efforts.

    Science.gov (United States)

    Hunt, Randall J; Luchette, Joseph; Schreuder, Willem A; Rumbaugh, James O; Doherty, John; Tonkin, Matthew J; Rumbaugh, Douglas B

    2010-01-01

    Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate "virtual" computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.

  7. Using a cloud to replenish parched groundwater modeling efforts

    Science.gov (United States)

    Hunt, Randall J.; Luchette, Joseph; Schreuder, Willem A.; Rumbaugh, James O.; Doherty, John; Tonkin, Matthew J.; Rumbaugh, Douglas B.

    2010-01-01

    Groundwater models can be improved by introduction of additional parameter flexibility and simultaneous use of soft-knowledge. However, these sophisticated approaches have high computational requirements. Cloud computing provides unprecedented access to computing power via the Internet to facilitate the use of these techniques. A modeler can create, launch, and terminate “virtual” computers as needed, paying by the hour, and save machine images for future use. Such cost-effective and flexible computing power empowers groundwater modelers to routinely perform model calibration and uncertainty analysis in ways not previously possible.

  8. FINDING CUBOID-BASED BUILDING MODELS IN POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    W. Nguatem

    2012-07-01

    Full Text Available In this paper, we present an automatic approach for the derivation of 3D building models of level-of-detail 1 (LOD 1 from point clouds obtained from (dense image matching or, for comparison only, from LIDAR. Our approach makes use of the predominance of vertical structures and orthogonal intersections in architectural scenes. After robustly determining the scene's vertical direction based on the 3D points we use it as constraint for a RANSAC-based search for vertical planes in the point cloud. The planes are further analyzed to segment reliable outlines for rectangular surface within these planes, which are connected to construct cuboid-based building models. We demonstrate that our approach is robust and effective over a range of real-world input data sets with varying point density, amount of noise, and outliers.

  9. Comprehensive models of diffuse interstellar clouds : physical conditions and molecular abundances

    NARCIS (Netherlands)

    Dishoeck, van E.F.; Black, J.H.

    1986-01-01

    The limitations of steady state models of interstellar clouds are explored by means of comparison with observational data corresponding to clouds in front of Zeta Per, Zeta Oph, Chi Oph, and Omicron Per. The improved cloud models were constructed to reproduce the observed H and H2(J) column

  10. Towards a government public cloud model: The case of South Africa

    CSIR Research Space (South Africa)

    Mvelase, PS

    2013-06-01

    Full Text Available the government to benefit from other cloud computing advantages. However, modelling a multidimensional social problem as complex as the public cloud for a national government requires time, knowledge and experience from a wide range of specialization disciplines...

  11. Generalized Additive Models for Nowcasting Cloud Shading

    Czech Academy of Sciences Publication Activity Database

    Brabec, Marek; Paulescu, M.; Badescu, V.

    2014-01-01

    Roč. 101, March (2014), s. 272-282 ISSN 0038-092X R&D Projects: GA MŠk LD12009 Grant - others:European Cooperation in Science and Technology(XE) COST ES1002 Institutional support: RVO:67985807 Keywords : sunshine number * nowcasting * generalized additive model * Markov chain Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 3.469, year: 2014

  12. Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

    Directory of Open Access Journals (Sweden)

    Milan Vukićević

    2014-01-01

    Full Text Available Rapid growth and storage of biomedical data enabled many opportunities for predictive modeling and improvement of healthcare processes. On the other side analysis of such large amounts of data is a difficult and computationally intensive task for most existing data mining algorithms. This problem is addressed by proposing a cloud based system that integrates metalearning framework for ranking and selection of best predictive algorithms for data at hand and open source big data technologies for analysis of biomedical data.

  13. Evaluation of NCMRWF unified model vertical cloud structure with CloudSat over the Indian summer monsoon region

    Science.gov (United States)

    Jayakumar, A.; Mamgain, Ashu; Jisesh, A. S.; Mohandas, Saji; Rakhi, R.; Rajagopal, E. N.

    2016-05-01

    Representation of rainfall distribution and monsoon circulation in the high resolution versions of NCMRWF Unified model (NCUM-REG) for the short-range forecasting of extreme rainfall event is vastly dependent on the key factors such as vertical cloud distribution, convection and convection/cloud relationship in the model. Hence it is highly relevant to evaluate the vertical structure of cloud and precipitation of the model over the monsoon environment. In this regard, we utilized the synergy of the capabilities of CloudSat data for long observational period, by conditioning it for the synoptic situation of the model simulation period. Simulations were run at 4-km grid length with the convective parameterization effectively switched off and on. Since the sample of CloudSat overpasses through the monsoon domain is small, the aforementioned methodology may qualitatively evaluate the vertical cloud structure for the model simulation period. It is envisaged that the present study will open up the possibility of further improvement in the high resolution version of NCUM in the tropics for the Indian summer monsoon associated rainfall events.

  14. Cloud data centers and cost modeling a complete guide to planning, designing and building a cloud data center

    CERN Document Server

    Wu, Caesar

    2015-01-01

    Cloud Data Centers and Cost Modeling establishes a framework for strategic decision-makers to facilitate the development of cloud data centers. Just as building a house requires a clear understanding of the blueprints, architecture, and costs of the project; building a cloud-based data center requires similar knowledge. The authors take a theoretical and practical approach, starting with the key questions to help uncover needs and clarify project scope. They then demonstrate probability tools to test and support decisions, and provide processes that resolve key issues. After laying a foundati

  15. Differential Equations Models to Study Quorum Sensing.

    Science.gov (United States)

    Pérez-Velázquez, Judith; Hense, Burkhard A

    2018-01-01

    Mathematical models to study quorum sensing (QS) have become an important tool to explore all aspects of this type of bacterial communication. A wide spectrum of mathematical tools and methods such as dynamical systems, stochastics, and spatial models can be employed. In this chapter, we focus on giving an overview of models consisting of differential equations (DE), which can be used to describe changing quantities, for example, the dynamics of one or more signaling molecule in time and space, often in conjunction with bacterial growth dynamics. The chapter is divided into two sections: ordinary differential equations (ODE) and partial differential equations (PDE) models of QS. Rates of change are represented mathematically by derivatives, i.e., in terms of DE. ODE models allow describing changes in one independent variable, for example, time. PDE models can be used to follow changes in more than one independent variable, for example, time and space. Both types of models often consist of systems (i.e., more than one equation) of equations, such as equations for bacterial growth and autoinducer concentration dynamics. Almost from the onset, mathematical modeling of QS using differential equations has been an interdisciplinary endeavor and many of the works we revised here will be placed into their biological context.

  16. Modelling the Intention to Adopt Cloud Computing Services: A Transaction Cost Theory Perspective

    Directory of Open Access Journals (Sweden)

    Ogan Yigitbasioglu

    2014-11-01

    Full Text Available This paper uses transaction cost theory to study cloud computing adoption. A model is developed and tested with data from an Australian survey. According to the results, perceived vendor opportunism and perceived legislative uncertainty around cloud computing were significantly associated with perceived cloud computing security risk. There was also a significant negative relationship between perceived cloud computing security risk and the intention to adopt cloud services. This study also reports on adoption rates of cloud computing in terms of applications, as well as the types of services used.

  17. A New Method of Cloud Detection Based on Cascaded AdaBoost

    International Nuclear Information System (INIS)

    Ma, C; Chen, F; Liu, J; Duan, J

    2014-01-01

    Cloud detection of remote sensing image is a critical step in the processing of the remote sensing images. How to quickly, accurately and effectively detect cloud on remote sensing images, is still a challenging issue in this area. In order to avoid disadvantages of the current algorithms, the cascaded AdaBoost classifier algorithm is successfully applied to the cloud detection. A new algorithm combined cascaded AdaBoost classifier and multi-features, is proposed in this paper. First, multi-features based on the color, texture and spectral features are extracted from the remote sensing image. Second, the automatic cloud detection model is obtained based on the cascaded AdaBoost algorithm. In this paper, the results show that the new algorithm can determine cloud detection model and threshold values adaptively for different resolution remote sensing training data. The accuracy of cloud detection is improved. So it is a new effective algorithm for the cloud detection of remote sensing images

  18. Remote sensing inputs to water demand modeling

    Science.gov (United States)

    Estes, J. E.; Jensen, J. R.; Tinney, L. R.; Rector, M.

    1975-01-01

    In an attempt to determine the ability of remote sensing techniques to economically generate data required by water demand models, the Geography Remote Sensing Unit, in conjunction with the Kern County Water Agency of California, developed an analysis model. As a result it was determined that agricultural cropland inventories utilizing both high altitude photography and LANDSAT imagery can be conducted cost effectively. In addition, by using average irrigation application rates in conjunction with cropland data, estimates of agricultural water demand can be generated. However, more accurate estimates are possible if crop type, acreage, and crop specific application rates are employed. An analysis of the effect of saline-alkali soils on water demand in the study area is also examined. Finally, reference is made to the detection and delineation of water tables that are perched near the surface by semi-permeable clay layers. Soil salinity prediction, automated crop identification on a by-field basis, and a potential input to the determination of zones of equal benefit taxation are briefly touched upon.

  19. Cloud-based crowd sensing: a framework for location-based crowd analyzer and advisor

    Science.gov (United States)

    Aishwarya, K. C.; Nambi, A.; Hudson, S.; Nadesh, R. K.

    2017-11-01

    Cloud computing is an emerging field of computer science to integrate and explore large and powerful computing systems and storages for personal and also for enterprise requirements. Mobile Cloud Computing is the inheritance of this concept towards mobile hand-held devices. Crowdsensing, or to be precise, Mobile Crowdsensing is the process of sharing resources from an available group of mobile handheld devices that support sharing of different resources such as data, memory and bandwidth to perform a single task for collective reasons. In this paper, we propose a framework to use Crowdsensing and perform a crowd analyzer and advisor whether the user can go to the place or not. This is an ongoing research and is a new concept to which the direction of cloud computing has shifted and is viable for more expansion in the near future.

  20. Remote Sensing of Aerosols from Satellites: Why Has It Been Do Difficult to Quantify Aerosol-Cloud Interactions for Climate Assessment, and How Can We Make Progress?

    Science.gov (United States)

    Kahn, Ralph A.

    2015-01-01

    The organizers of the National Academy of Sciences Arthur M. Sackler Colloquia Series on Improving Our Fundamental Understanding of the Role of Aerosol-Cloud Interactions in the Climate System would like to post Ralph Kahn's presentation entitled Remote Sensing of Aerosols from Satellites: Why has it been so difficult to quantify aerosol-cloud interactions for climate assessment, and how can we make progress? to their public website.

  1. Laser Remote Sensing from ISS: CATS Cloud and Aerosol Level 2 Data Products (Heritage Edition)

    Science.gov (United States)

    Rodier, Sharon; Palm, Steve; Vaughan, Mark; Yorks, John; McGill, Matt; Jensen, Mike; Murray, Tim; Trepte, Chip

    2016-01-01

    With the recent launch of the Cloud-Aerosol Transport System (CATS) we have the opportunity to acquire a continuous record of space based lidar measurements spanning from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) era to the start of the EarthCARE mission. Utilizing existing well-validated science algorithms from the CALIPSO mission, we will ingest the CATS data stream and deliver high-quality lidar data sets to the user community at the earliest possible opportunity. In this paper we present an overview of procedures necessary to generate CALIPSO-like lidar level 2 data products from the CATS level 1 data products.

  2. Model to Implement Virtual Computing Labs via Cloud Computing Services

    Directory of Open Access Journals (Sweden)

    Washington Luna Encalada

    2017-07-01

    Full Text Available In recent years, we have seen a significant number of new technological ideas appearing in literature discussing the future of education. For example, E-learning, cloud computing, social networking, virtual laboratories, virtual realities, virtual worlds, massive open online courses (MOOCs, and bring your own device (BYOD are all new concepts of immersive and global education that have emerged in educational literature. One of the greatest challenges presented to e-learning solutions is the reproduction of the benefits of an educational institution’s physical laboratory. For a university without a computing lab, to obtain hands-on IT training with software, operating systems, networks, servers, storage, and cloud computing similar to that which could be received on a university campus computing lab, it is necessary to use a combination of technological tools. Such teaching tools must promote the transmission of knowledge, encourage interaction and collaboration, and ensure students obtain valuable hands-on experience. That, in turn, allows the universities to focus more on teaching and research activities than on the implementation and configuration of complex physical systems. In this article, we present a model for implementing ecosystems which allow universities to teach practical Information Technology (IT skills. The model utilizes what is called a “social cloud”, which utilizes all cloud computing services, such as Software as a Service (SaaS, Platform as a Service (PaaS, and Infrastructure as a Service (IaaS. Additionally, it integrates the cloud learning aspects of a MOOC and several aspects of social networking and support. Social clouds have striking benefits such as centrality, ease of use, scalability, and ubiquity, providing a superior learning environment when compared to that of a simple physical lab. The proposed model allows students to foster all the educational pillars such as learning to know, learning to be, learning

  3. SPATIAL MOTION OF THE MAGELLANIC CLOUDS: TIDAL MODELS RULED OUT?

    International Nuclear Information System (INIS)

    Ruzicka, Adam; Palous, Jan; Theis, Christian

    2009-01-01

    Recently, Kallivayalil et al. derived new values of the proper motion for the Large and Small Magellanic Clouds (LMC and SMC, respectively). The spatial velocities of both Clouds are unexpectedly higher than their previous values resulting from agreement between the available theoretical models of the Magellanic System and the observations of neutral hydrogen (H I) associated with the LMC and the SMC. Such proper motion estimates are likely to be at odds with the scenarios for creation of the large-scale structures in the Magellanic System suggested so far. We investigated this hypothesis for the pure tidal models, as they were the first ones devised to explain the evolution of the Magellanic System, and the tidal stripping is intrinsically involved in every model assuming the gravitational interaction. The parameter space for the Milky Way (MW)-LMC-SMC interaction was analyzed by a robust search algorithm (genetic algorithm) combined with a fast, restricted N-body model of the interaction. Our method extended the known variety of evolutionary scenarios satisfying the observed kinematics and morphology of the Magellanic large-scale structures. Nevertheless, assuming the tidal interaction, no satisfactory reproduction of the H I data available for the Magellanic Clouds was achieved with the new proper motions. We conclude that for the proper motion data by Kallivayalil et al., within their 1σ errors, the dynamical evolution of the Magellanic System with the currently accepted total mass of the MW cannot be explained in the framework of pure tidal models. The optimal value for the western component of the LMC proper motion was found to be μ W lmc ∼> -1.3 mas yr -1 in case of tidal models. It corresponds to the reduction of the Kallivayalil et al. value for μ W lmc by ∼ 40% in its magnitude.

  4. Final Technical Report for "High-resolution global modeling of the effects of subgrid-scale clouds and turbulence on precipitating cloud systems"

    Energy Technology Data Exchange (ETDEWEB)

    Larson, Vincent [Univ. of Wisconsin, Milwaukee, WI (United States)

    2016-11-25

    The Multiscale Modeling Framework (MMF) embeds a cloud-resolving model in each grid column of a General Circulation Model (GCM). A MMF model does not need to use a deep convective parameterization, and thereby dispenses with the uncertainties in such parameterizations. However, MMF models grossly under-resolve shallow boundary-layer clouds, and hence those clouds may still benefit from parameterization. In this grant, we successfully created a climate model that embeds a cloud parameterization (“CLUBB”) within a MMF model. This involved interfacing CLUBB’s clouds with microphysics and reducing computational cost. We have evaluated the resulting simulated clouds and precipitation with satellite observations. The chief benefit of the project is to provide a MMF model that has an improved representation of clouds and that provides improved simulations of precipitation.

  5. The cloud-phase feedback in the Super-parameterized Community Earth System Model

    Science.gov (United States)

    Burt, M. A.; Randall, D. A.

    2016-12-01

    Recent comparisons of observations and climate model simulations by I. Tan and colleagues have suggested that the Wegener-Bergeron-Findeisen (WBF) process tends to be too active in climate models, making too much cloud ice, and resulting in an exaggerated negative cloud-phase feedback on climate change. We explore the WBF process and its effect on shortwave cloud forcing in present-day and future climate simulations with the Community Earth System Model, and its super-parameterized counterpart. Results show that SP-CESM has much less cloud ice and a weaker cloud-phase feedback than CESM.

  6. Abs: a high-level modeling language for cloud-aware programming

    NARCIS (Netherlands)

    N. Bezirgiannis (Nikolaos); F.S. de Boer (Frank)

    2016-01-01

    textabstractCloud technology has become an invaluable tool to the IT business, because of its attractive economic model. Yet, from the programmers’ perspective, the development of cloud applications remains a major challenge. In this paper we introduce a programming language that allows Cloud

  7. Geographical point cloud modelling with the 3D medial axis transform

    NARCIS (Netherlands)

    Peters, R.Y.

    2018-01-01

    A geographical point cloud is a detailed three-dimensional representation of the geometry of our geographic environment.
    Using geographical point cloud modelling, we are able to extract valuable information from geographical point clouds that can be used for applications in asset management,

  8. An Economic Model for Self-tuned Cloud Caching

    OpenAIRE

    Dash, Debabrata; Kantere, Verena; Ailamaki, Anastasia

    2009-01-01

    Cloud computing, the new trend for service infrastructures requires user multi-tenancy as well as minimal capital expenditure. In a cloud that services large amounts of data that are massively collected and queried, such as scientific data, users typically pay for query services. The cloud supports caching of data in order to provide quality query services. User payments cover query execution costs and maintenance of cloud infrastructure, and incur cloud profit. The challenge resides in provi...

  9. Cloud radiative effects and changes simulated by the Coupled Model Intercomparison Project Phase 5 models

    Science.gov (United States)

    Shin, Sun-Hee; Kim, Ok-Yeon; Kim, Dongmin; Lee, Myong-In

    2017-07-01

    Using 32 CMIP5 (Coupled Model Intercomparison Project Phase 5) models, this study examines the veracity in the simulation of cloud amount and their radiative effects (CREs) in the historical run driven by observed external radiative forcing for 1850-2005, and their future changes in the RCP (Representative Concentration Pathway) 4.5 scenario runs for 2006-2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics, four models—ACCESS1.0, ACCESS1.3, HadGEM2-CC, and HadGEM2-ES—are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average. All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about -0.99% K-1 and net radiative warming of 0.46 W m-2 K-1, suggesting a role of positive feedback to global warming.

  10. Evolution in Cloud Population Statistics of the MJO: From AMIE Field Observations to Global Cloud-Permiting Models

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Chidong [Univ. of Miami, Coral Gables, FL (United States)

    2016-08-14

    Motivated by the success of the AMIE/DYNAMO field campaign, which collected unprecedented observations of cloud and precipitation from the tropical Indian Ocean in Octber 2011 – March 2012, this project explored how such observations can be applied to assist the development of global cloud-permitting models through evaluating and correcting model biases in cloud statistics. The main accomplishment of this project were made in four categories: generating observational products for model evaluation, using AMIE/DYNAMO observations to validate global model simulations, using AMIE/DYNAMO observations in numerical studies of cloud-permitting models, and providing leadership in the field. Results from this project provide valuable information for building a seamless bridge between DOE ASR program’s component on process level understanding of cloud processes in the tropics and RGCM focus on global variability and regional extremes. In particular, experience gained from this project would be directly applicable to evaluation and improvements of ACME, especially as it transitions to a non-hydrostatic variable resolution model.

  11. Modeling the Cloud to Enhance Capabilities for Crises and Catastrophe Management

    Science.gov (United States)

    2016-11-16

    through support by a prior DOD grant, and in this project, we focused on how to effectively adapt this for the cloud catastrophe environment. The...the effects of varying cloud resources and the cloud architecture on L, o, and g values, we will be able to formulate realistic analytical models of...variation in computing and communication costs of test problems due to varying loads in the cloud environment. We used the parallel matrix multiplication

  12. Southeast Atlantic Cloud Properties in a Multivariate Statistical Model - How Relevant is Air Mass History for Local Cloud Properties?

    Science.gov (United States)

    Fuchs, Julia; Cermak, Jan; Andersen, Hendrik

    2017-04-01

    This study aims at untangling the impacts of external dynamics and local conditions on cloud properties in the Southeast Atlantic (SEA) by combining satellite and reanalysis data using multivariate statistics. The understanding of clouds and their determinants at different scales is important for constraining the Earth's radiative budget, and thus prominent in climate-system research. In this study, SEA stratocumulus cloud properties are observed not only as the result of local environmental conditions but also as affected by external dynamics and spatial origins of air masses entering the study area. In order to assess to what extent cloud properties are impacted by aerosol concentration, air mass history, and meteorology, a multivariate approach is conducted using satellite observations of aerosol and cloud properties (MODIS, SEVIRI), information on aerosol species composition (MACC) and meteorological context (ERA-Interim reanalysis). To account for the often-neglected but important role of air mass origin, information on air mass history based on HYSPLIT modeling is included in the statistical model. This multivariate approach is intended to lead to a better understanding of the physical processes behind observed stratocumulus cloud properties in the SEA.

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

    Science.gov (United States)

    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.

  14. Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

    Science.gov (United States)

    Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

    2013-12-01

    Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it

  15. Study of tropical clouds feedback to a climate warming as simulated by climate models

    International Nuclear Information System (INIS)

    Brient, Florent

    2012-01-01

    The last IPCC report affirms the predominant role of low cloud-radiative feedbacks in the inter-model spread of climate sensitivity. Understanding the mechanisms that control the behavior of low-level clouds is thus crucial. However, the complexity of coupled ocean-atmosphere models and the large number of processes potentially involved make the analysis of this response difficult. To simplify the analysis and to identify the most critical controls of cloud feedbacks, we analyze the cloud response to climate change simulated by the IPSL-CM5A model in a hierarchy of configurations. A comparison between three model configurations (coupled, atmospheric and aqua-planet) using the same physical parametrizations shows that the cloud response to global warming is dominated by a decrease of low clouds in regimes of moderate subsidence. Using a Single Column Model, forced by weak subsidence large-scale forcing, allows us to reproduce the vertical cloud profile predicted in the 3D model, as well as its response to climate change (if a stochastic forcing is added on vertical velocity). We analyze the sensitivity of this low-cloud response to external forcing and also to uncertain parameters of physical parameterizations involved on the atmospheric model. Through a moist static energy (MSE) budget, we highlight several mechanisms: (1) Robust: Over weak subsidence regimes, the Clausius-Clapeyron relationship predicts that a warmer atmosphere leads to a increase of the vertical MSE gradient, resulting on a strengthening of the import of low-MSE from the free atmosphere into the cloudy boundary layer. The MSE budget links changes of vertical advection and cloud radiative effects. (2) Physics Model Dependent: The coupling between shallow convection, turbulence and cloud schemes allows the intensification of low-MSE transport so that cloud radiative cooling becomes 'less necessary' to balance the energy budget (Robust positive low cloud-radiative feedback for the model). The

  16. Constraining the models' response of tropical low clouds to SST forcings using CALIPSO observations

    Science.gov (United States)

    Cesana, G.; Del Genio, A. D.; Ackerman, A. S.; Brient, F.; Fridlind, A. M.; Kelley, M.; Elsaesser, G.

    2017-12-01

    Low-cloud response to a warmer climate is still pointed out as being the largest source of uncertainty in the last generation of climate models. To date there is no consensus among the models on whether the tropical low cloudiness would increase or decrease in a warmer climate. In addition, it has been shown that - depending on their climate sensitivity - the models either predict deeper or shallower low clouds. Recently, several relationships between inter-model characteristics of the present-day climate and future climate changes have been highlighted. These so-called emergent constraints aim to target relevant model improvements and to constrain models' projections based on current climate observations. Here we propose to use - for the first time - 10 years of CALIPSO cloud statistics to assess the ability of the models to represent the vertical structure of tropical low clouds for abnormally warm SST. We use a simulator approach to compare observations and simulations and focus on the low-layered clouds (i.e. z fraction. Vertically, the clouds deepen namely by decreasing the cloud fraction in the lowest levels and increasing it around the top of the boundary-layer. This feature is coincident with an increase of the high-level cloud fraction (z > 6.5km). Although the models' spread is large, the multi-model mean captures the observed variations but with a smaller amplitude. We then employ the GISS model to investigate how changes in cloud parameterizations affect the response of low clouds to warmer SSTs on the one hand; and how they affect the variations of the model's cloud profiles with respect to environmental parameters on the other hand. Finally, we use CALIPSO observations to constrain the model by determining i) what set of parameters allows reproducing the observed relationships and ii) what are the consequences on the cloud feedbacks. These results point toward process-oriented constraints of low-cloud responses to surface warming and environmental

  17. Process-model simulations of cloud albedo enhancement by aerosols in the Arctic

    Science.gov (United States)

    Kravitz, Ben; Wang, Hailong; Rasch, Philip J.; Morrison, Hugh; Solomon, Amy B.

    2014-01-01

    A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN), either through geoengineering or other increased sources of Arctic aerosols. An updated cloud microphysical scheme is employed, with prognostic CCN and cloud particle numbers in both liquid and mixed-phase marine low clouds. Injection of CCN into the marine boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. Albedo increases are stronger for pure liquid clouds than mixed-phase clouds. Liquid precipitation can be suppressed by CCN injection, whereas ice precipitation (snow) is affected less; thus, the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. CCN injection into a clean regime results in a greater albedo increase than injection into a polluted regime, consistent with current knowledge about aerosol–cloud interactions. Unlike previous studies investigating warm clouds, dynamical changes in circulation owing to precipitation changes are small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering is unlikely to be effective as the sole means of altering the global radiation budget but could have substantial local radiative effects. PMID:25404677

  18. EDITORIAL: Aerosol cloud interactions—a challenge for measurements and modeling at the cutting edge of cloud climate interactions

    Science.gov (United States)

    Spichtinger, Peter; Cziczo, Daniel J.

    2008-04-01

    Research in aerosol properties and cloud characteristics have historically been considered two separate disciplines within the field of atmospheric science. As such, it has been uncommon for a single researcher, or even research group, to have considerable expertise in both subject areas. The recent attention paid to global climate change has shown that clouds can have a considerable effect on the Earth's climate and that one of the most uncertain aspects in their formation, persistence, and ultimate dissipation is the role played by aerosols. This highlights the need for researchers in both disciplines to interact more closely than they have in the past. This is the vision behind this focus issue of Environmental Research Letters. Certain interactions between aerosols and clouds are relatively well studied and understood. For example, it is known that an increase in the aerosol concentration will increase the number of droplets in warm clouds, decrease their average size, reduce the rate of precipitation, and extend the lifetime. Other effects are not as well known. For example, persistent ice super-saturated conditions are observed in the upper troposphere that appear to exceed our understanding of the conditions required for cirrus cloud formation. Further, the interplay of dynamics versus effects purely attributed to aerosols remains highly uncertain. The purpose of this focus issue is to consider the current state of knowledge of aerosol/cloud interactions, to define the contemporary uncertainties, and to outline research foci as we strive to better understand the Earth's climate system. This focus issue brings together laboratory experiments, field data, and model studies. The authors address issues associated with warm liquid water, cold ice, and intermediate temperature mixed-phase clouds. The topics include the uncertainty associated with the effect of black carbon and organics, aerosol types of anthropogenic interest, on droplet and ice formation. Phases

  19. Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

    Science.gov (United States)

    Ben-David, Avishai; Davidson, Charles E

    2012-04-23

    A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

  20. Combining observations and models to reduce uncertainty in the cloud response to global warming

    Science.gov (United States)

    Norris, J. R.; Myers, T.; Chellappan, S.

    2017-12-01

    Currently there is large uncertainty on how subtropical low-level clouds will respond to global warming and whether they will act as a positive feedback or negative feedback. Global climate models substantially agree on what changes in atmospheric structure and circulation will occur with global warming but greatly disagree over how clouds will respond to these changes in structure and circulation. An examination of models with the most realistic simulations of low-level cloudiness indicates that the model cloud response to atmospheric changes associated with global warming is quantitatively similar to the model cloud response to atmospheric changes at interannual time scales. For these models, the cloud response to global warming predicted by multilinear regression using coefficients derived from interannual time scales is quantitatively similar to the cloud response to global warming directly simulated by the model. Since there is a large spread among cloud response coefficients even among models with the most realistic cloud simulations, substitution of coefficients derived from satellite observations reduces the uncertainty range of the low-level cloud feedback. Increased sea surface temperature associated with global warming acts to reduce low-level cloudiness, which is partially offset by increased lower tropospheric stratification that acts to enhance low-level cloudiness. Changes in free-tropospheric relative humidity, subsidence, and horizontal advection have only a small impact on low-level cloud. The net reduction in subtropical low-level cloudiness increases absorption of solar radiation by the climate system, thus resulting in a weak positive feedback.

  1. FIRST PRISMATIC BUILDING MODEL RECONSTRUCTION FROM TOMOSAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    Y. Sun

    2016-06-01

    Full Text Available This paper demonstrates for the first time the potential of explicitly modelling the individual roof surfaces to reconstruct 3-D prismatic building models using spaceborne tomographic synthetic aperture radar (TomoSAR point clouds. The proposed approach is modular and works as follows: it first extracts the buildings via DSM generation and cutting-off the ground terrain. The DSM is smoothed using BM3D denoising method proposed in (Dabov et al., 2007 and a gradient map of the smoothed DSM is generated based on height jumps. Watershed segmentation is then adopted to oversegment the DSM into different regions. Subsequently, height and polygon complexity constrained merging is employed to refine (i.e., to reduce the retrieved number of roof segments. Coarse outline of each roof segment is then reconstructed and later refined using quadtree based regularization plus zig-zag line simplification scheme. Finally, height is associated to each refined roof segment to obtain the 3-D prismatic model of the building. The proposed approach is illustrated and validated over a large building (convention center in the city of Las Vegas using TomoSAR point clouds generated from a stack of 25 images using Tomo-GENESIS software developed at DLR.

  2. High-Resolution Global Modeling of the Effects of Subgrid-Scale Clouds and Turbulence on Precipitating Cloud Systems

    Energy Technology Data Exchange (ETDEWEB)

    Bogenschutz, Peter [National Center for Atmospheric Research, Boulder, CO (United States); Moeng, Chin-Hoh [National Center for Atmospheric Research, Boulder, CO (United States)

    2015-10-13

    The PI’s at the National Center for Atmospheric Research (NCAR), Chin-Hoh Moeng and Peter Bogenschutz, have primarily focused their time on the implementation of the Simplified-Higher Order Turbulence Closure (SHOC; Bogenschutz and Krueger 2013) to the Multi-scale Modeling Framework (MMF) global model and testing of SHOC on deep convective cloud regimes.

  3. A Coupled fcGCM-GCE Modeling System: A 3D Cloud Resolving Model and a Regional Scale Model

    Science.gov (United States)

    Tao, Wei-Kuo

    2005-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-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 ore sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (21CE, several 31CE), Goddard radiation (including explicity calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generation regional scale model, WRF. In this talk, I will present: (1) A Brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), (3) A discussion on the Goddard WRF version (its developments and applications), and (4) The characteristics of the four-dimensional cloud data

  4. Mobile-cloud assisted video summarization framework for efficient management of remote sensing data generated by wireless capsule sensors.

    Science.gov (United States)

    Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

    2014-09-15

    Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

  5. Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

    Directory of Open Access Journals (Sweden)

    Irfan Mehmood

    2014-09-01

    Full Text Available Wireless capsule endoscopy (WCE has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data.

  6. Mobile-Cloud Assisted Video Summarization Framework for Efficient Management of Remote Sensing Data Generated by Wireless Capsule Sensors

    Science.gov (United States)

    Mehmood, Irfan; Sajjad, Muhammad; Baik, Sung Wook

    2014-01-01

    Wireless capsule endoscopy (WCE) has great advantages over traditional endoscopy because it is portable and easy to use, especially in remote monitoring health-services. However, during the WCE process, the large amount of captured video data demands a significant deal of computation to analyze and retrieve informative video frames. In order to facilitate efficient WCE data collection and browsing task, we present a resource- and bandwidth-aware WCE video summarization framework that extracts the representative keyframes of the WCE video contents by removing redundant and non-informative frames. For redundancy elimination, we use Jeffrey-divergence between color histograms and inter-frame Boolean series-based correlation of color channels. To remove non-informative frames, multi-fractal texture features are extracted to assist the classification using an ensemble-based classifier. Owing to the limited WCE resources, it is impossible for the WCE system to perform computationally intensive video summarization tasks. To resolve computational challenges, mobile-cloud architecture is incorporated, which provides resizable computing capacities by adaptively offloading video summarization tasks between the client and the cloud server. The qualitative and quantitative results are encouraging and show that the proposed framework saves information transmission cost and bandwidth, as well as the valuable time of data analysts in browsing remote sensing data. PMID:25225874

  7. Remote sensing, hydrological modeling and in situ observations in snow cover research: A review

    Science.gov (United States)

    Dong, Chunyu

    2018-06-01

    Snow is an important component of the hydrological cycle. As a major part of the cryosphere, snow cover also represents a valuable terrestrial water resource. In the context of climate change, the dynamics of snow cover play a crucial role in rebalancing the global energy and water budgets. Remote sensing, hydrological modeling and in situ observations are three techniques frequently utilized for snow cover investigations. However, the uncertainties caused by systematic errors, scale gaps, and complicated snow physics, among other factors, limit the usability of these three approaches in snow studies. In this paper, an overview of the advantages, limitations and recent progress of the three methods is presented, and more effective ways to estimate snow cover properties are evaluated. The possibility of improving remotely sensed snow information using ground-based observations is discussed. As a rapidly growing source of volunteered geographic information (VGI), web-based geotagged photos have great potential to provide ground truth data for remotely sensed products and hydrological models and thus contribute to procedures for cloud removal, correction, validation, forcing and assimilation. Finally, this review proposes a synergistic framework for the future of snow cover research. This framework highlights the cross-scale integration of in situ and remotely sensed snow measurements and the assimilation of improved remote sensing data into hydrological models.

  8. Investigation of Arctic mixed-phase clouds by combining airborne remote sensing and in situ observations during VERDI, RACEPAC and ACLOUD

    Science.gov (United States)

    Ehrlich, André; Bierwirth, Eike; Borrmann, Stephan; Crewell, Susanne; Herber, Andreas; Hoor, Peter; Jourdan, Olivier; Krämer, Martina; Lüpkes, Christof; Mertes, Stephan; Neuber, Roland; Petzold, Andreas; Schnaiter, Martin; Schneider, Johannes; Weigel, Ralf; Weinzierl, Bernadett; Wendisch, Manfred

    2016-04-01

    To improve our understanding of Arctic mixed-phase clouds a series of airborne research campaigns has been initiated by a collaboration of German research institutes. Clouds in areas dominated by a close sea-ice cover were observed during the research campaign Vertical distribution of ice in Arctic mixed-phase clouds (VERDI, April/May 2012) and the Radiation-Aerosol-Cloud Experiment in the Arctic Circle (RACEPAC, April/May 2014) which both were based in Inuvik, Canada. The aircraft (Polar 5 & 6, Basler BT-67) operated by the Alfred Wegener Institute for Polar and Marine Research, Germany did cover a wide area above the Canadian Beaufort with in total 149 flight hours (62h during VERDI, 87h during RACEPAC). For May/June 2017 a third campaign ACLOUD (Arctic Clouds - Characterization of Ice, aerosol Particles and Energy fluxes) with base in Svalbard is planned within the Transregional Collaborative Research Centre TR 172 ArctiC Amplification: Climate Relevant Atmospheric and SurfaCe Processes, and Feedback Mechanisms (AC)3 to investigate Arctic clouds in the transition zone between open ocean and sea ice. The aim of all campaigns is to combine remote sensing and in-situ cloud, aerosol and trace gas measurements to investigate interactions between radiation, cloud and aerosol particles. While during VERDI remote sensing and in-situ measurements were performed by one aircraft subsequently, for RACEPAC and ACLOUD two identical aircraft are coordinated at different altitudes to horizontally collocate both remote sensing and in-situ measurements. The campaign showed that in this way radiative and microphysical processes in the clouds can by studied more reliably and remote sensing methods can be validated efficiently. Here we will illustrate the scientific strategy of the projects including the progress in instrumentation. Differences in the general synoptic and sea ice situation and related changes in cloud properties at the different locations and seasons will be

  9. Raman lidar measurements of water vapor and aerosols during the atmospheric radiation measurement (ARM) remote clouds sensing (RCS) intensive observation period (IOP)

    Energy Technology Data Exchange (ETDEWEB)

    Melfi, S.H.; Starr, D.O`C.; Whiteman, D. [NASA Goddard Space Flight Center, Greenbelt, MD (United States)] [and others

    1996-04-01

    The first Atmospheric Radiation Measurement (ARM) remote Cloud Study (RCS) Intensive Operations Period (IOP) was held during April 1994 at the Southern Great Plains (SGP) site. This experiment was conducted to evaluate and calibrate state-of-the-art, ground based remote sensing instruments and to use the data acquired by these instruments to validate retrieval algorithms developed under the ARM program.

  10. Microphysical variability of vigorous Amazonian deep convection observed by CloudSat, and relevance for cloud-resolving model

    Science.gov (United States)

    Dodson, J. B.; Taylor, P. C.

    2017-12-01

    The number and varieties of both satellite cloud observations and cloud simulations are increasing rapidly. This create a challenge in identifying the best methods for quantifying the physical processes associated with deep convection, and then comparing convective observations with simulations. The use of satellite simulators in conjunction with model output is an increasingly popular method of comparison studies. However, the complexity of deep convective systems renders simplistic comparison metrics hazardous, possibly resulting is misleading or even contradicting conclusions. To investigate this, CloudSat observations of Amazonian deep convective cores (DCCs) and associated anvils are compared and contrasted with output from cloud resolving models in a manner that both highlights microphysical proprties of observed convection, and displays the effects of microphysical parameterizations on allowing robust comparisons. First, contoured frequency by altitude diagrams (CFAD) are calculated from the reflectivity fields of DCCs observed by CloudSat. This reveals two distinct modes of hydrometeor variability in the high level cloud region, with one dominated by snow and aggregates, and the other by large graupel and hail. Second, output from the superparameterized Community Atmospheric Model (SP-CAM) data are processed with the Quickbeam radar simulator to produce CFADs which can be compared with the observed CFADs. Two versions of SP-CAM are used, with one (version 4) having single-moment microphysics which excludes graupel/hail, and the other (version 5) a double-moment scheme with graupel. The change from version 4 to 5 improves the reflectivity CFAD, even without corresponding changes to non-hydrometeor fields such as vertical velocity. However, it does not produce a realistic double hydrometeor mode. Finally, the influences of microphysics are further tested in the System for Atmospheric Modeling (SAM), which allows for higher control over model parameters than

  11. A sustainability model based on cloud infrastructures for core and downstream Copernicus services

    Science.gov (United States)

    Manunta, Michele; Calò, Fabiana; De Luca, Claudio; Elefante, Stefano; Farres, Jordi; Guzzetti, Fausto; Imperatore, Pasquale; Lanari, Riccardo; Lengert, Wolfgang; Zinno, Ivana; Casu, Francesco

    2014-05-01

    SAR products generation and exploitation. In particular, CNR is porting the multi-temporal DInSAR technique referred to as Small Baseline Subset (SBAS) into the ESA G-POD (Grid Processing On Demand) and CIOP (Cloud Computing Operational Pilot) platforms (Elefante et al., 2013) within the SuperSites Exploitation Platform (SSEP) project, which aim is contributing to the development of an ecosystem for big geo-data processing and dissemination. This work focuses on presenting the main results that have been achieved by the DORIS project concerning the use of advanced DInSAR products for supporting CPA during the risk management cycle. Furthermore, based on the DORIS experience, a sustainability model for Core and Downstream Copernicus services based on the effective exploitation of cloud platforms is proposed. In this framework, remote sensing community, both service providers and users, can significantly benefit from the Helix Nebula-The Science Cloud initiative, created by European scientific institutions, agencies, SMEs and enterprises to pave the way for the development and exploitation of a cloud computing infrastructure for science. REFERENCES Elefante, S., Imperatore, P. , Zinno, I., M. Manunta, E. Mathot, F. Brito, J. Farres, W. Lengert, R. Lanari, F. Casu, 2013, "SBAS-DINSAR Time series generation on cloud computing platforms". IEEE IGARSS Conference, Melbourne (AU), July 2013.

  12. The collision of a strong shock with a gas cloud: a model for Cassiopeia A

    International Nuclear Information System (INIS)

    Sgro, A.G.

    1975-01-01

    The result of the collision of the shock with the cloud is a shock traveling around the cloud, a shock transmitted into the cloud, and a shock reflected from the cloud. By equating the cooling time of the posttransmitted shock gas to the time required for the transmitted shock to travel the length of the cloud, a critical cloud density n/subc/ /sup prime/ is defined. For clouds with density greater than n/subc/ /sup prime/, the posttransmitted shock gas cools rapidly and then emits the lines of the lower ionization stages of its constituent elements. The structure of such and its expected appearance to an observer are discussed and compared with the quasi-stationary condensations of Cas A. Conversely, clouds with density less than n/subc//sup prime/ remain hot for several thousand years, and are sources of X-radiation whose temperatures are much less than that of the intercloud gas. After the transmitted shock passes, the cloud pressure is greater than the pressure in the surrounding gas, causing the cloud to expand and the emission to decrease from its value just after the collision. A model in which the soft X-radiation of Cas A is due to a collection of such clouds is discussed. The faint emission patches to the north of Cas A are interpreted as preshocked clouds which will probably become quasi-stationary condensations after being hit by the shock

  13. a Modeling Method of Fluttering Leaves Based on Point Cloud

    Science.gov (United States)

    Tang, J.; Wang, Y.; Zhao, Y.; Hao, W.; Ning, X.; Lv, K.; Shi, Z.; Zhao, M.

    2017-09-01

    Leaves falling gently or fluttering are common phenomenon in nature scenes. The authenticity of leaves falling plays an important part in the dynamic modeling of natural scenes. The leaves falling model has a widely applications in the field of animation and virtual reality. We propose a novel modeling method of fluttering leaves based on point cloud in this paper. According to the shape, the weight of leaves and the wind speed, three basic trajectories of leaves falling are defined, which are the rotation falling, the roll falling and the screw roll falling. At the same time, a parallel algorithm based on OpenMP is implemented to satisfy the needs of real-time in practical applications. Experimental results demonstrate that the proposed method is amenable to the incorporation of a variety of desirable effects.

  14. A MODELING METHOD OF FLUTTERING LEAVES BASED ON POINT CLOUD

    Directory of Open Access Journals (Sweden)

    J. Tang

    2017-09-01

    Full Text Available Leaves falling gently or fluttering are common phenomenon in nature scenes. The authenticity of leaves falling plays an important part in the dynamic modeling of natural scenes. The leaves falling model has a widely applications in the field of animation and virtual reality. We propose a novel modeling method of fluttering leaves based on point cloud in this paper. According to the shape, the weight of leaves and the wind speed, three basic trajectories of leaves falling are defined, which are the rotation falling, the roll falling and the screw roll falling. At the same time, a parallel algorithm based on OpenMP is implemented to satisfy the needs of real-time in practical applications. Experimental results demonstrate that the proposed method is amenable to the incorporation of a variety of desirable effects.

  15. Lifetime-Aware Cloud Data Centers: Models and Performance Evaluation

    Directory of Open Access Journals (Sweden)

    Luca Chiaraviglio

    2016-06-01

    Full Text Available We present a model to evaluate the server lifetime in cloud data centers (DCs. In particular, when the server power level is decreased, the failure rate tends to be reduced as a consequence of the limited number of components powered on. However, the variation between the different power states triggers a failure rate increase. We therefore consider these two effects in a server lifetime model, subject to an energy-aware management policy. We then evaluate our model in a realistic case study. Our results show that the impact on the server lifetime is far from negligible. As a consequence, we argue that a lifetime-aware approach should be pursued to decide how and when to apply a power state change to a server.

  16. A comparative analysis of pricing models for enterprise cloud platforms

    CSIR Research Space (South Africa)

    Mvelase, P

    2013-09-01

    Full Text Available on the realization that it is not economically viable for SMMEs to acquire their own private cloud infrastructure or even subscribe to public cloud services as a single entity. In our VE-enabled cloud enterprise architecture for SMMEs, temporary co...

  17. Security Certification Challenges in a Cloud Computing Delivery Model

    Science.gov (United States)

    2010-04-27

    Relevant Security Standards, Certifications, and Guidance  NIST SP 800 series  ISO /IEC 27001 framework  Cloud Security Alliance  Statement of...CSA Domains / Cloud Features ISO 27001 Cloud Service Provider Responsibility Government Agency Responsibility Analyze Security gaps Compensating

  18. ARTISTIC VISUALIZATION OF TRAJECTORY DATA USING CLOUD MODEL

    Directory of Open Access Journals (Sweden)

    T. Wu

    2017-09-01

    Full Text Available Rapid advance of location acquisition technologies boosts the generation of trajectory data, which track the traces of moving objects. A trajectory is typically represented by a sequence of timestamped geographical locations. Data visualization is an efficient means to represent distributions and structures of datasets and reveal hidden patterns in the data. In this paper, we explore a cloud model-based method for the generation of stylized renderings of trajectory data. The artistic visualizations of the proposed method do not have the goal to allow for data mining tasks or others but instead show the aesthetic effect of the traces of moving objects in a distorted manner. The techniques used to create the images of traces of moving objects include the uncertain line using extended cloud model, stroke-based rendering of geolocation in varying styles, and stylistic shading with aesthetic effects for print or electronic displays, as well as various parameters to be further personalized. The influence of different parameters on the aesthetic qualities of various painted images is investigated, including step size, types of strokes, colour modes, and quantitative comparisons using four aesthetic measures are also involved into the experiment. The experimental results suggest that the proposed method is with advantages of uncertainty, simplicity and effectiveness, and it would inspire professional graphic designers and amateur users who may be interested in playful and creative exploration of artistic visualization of trajectory data.

  19. Artistic Visualization of Trajectory Data Using Cloud Model

    Science.gov (United States)

    Wu, T.; Zhou, Y.; Zhang, L.

    2017-09-01

    Rapid advance of location acquisition technologies boosts the generation of trajectory data, which track the traces of moving objects. A trajectory is typically represented by a sequence of timestamped geographical locations. Data visualization is an efficient means to represent distributions and structures of datasets and reveal hidden patterns in the data. In this paper, we explore a cloud model-based method for the generation of stylized renderings of trajectory data. The artistic visualizations of the proposed method do not have the goal to allow for data mining tasks or others but instead show the aesthetic effect of the traces of moving objects in a distorted manner. The techniques used to create the images of traces of moving objects include the uncertain line using extended cloud model, stroke-based rendering of geolocation in varying styles, and stylistic shading with aesthetic effects for print or electronic displays, as well as various parameters to be further personalized. The influence of different parameters on the aesthetic qualities of various painted images is investigated, including step size, types of strokes, colour modes, and quantitative comparisons using four aesthetic measures are also involved into the experiment. The experimental results suggest that the proposed method is with advantages of uncertainty, simplicity and effectiveness, and it would inspire professional graphic designers and amateur users who may be interested in playful and creative exploration of artistic visualization of trajectory data.

  20. Remote-Sensing Data Distribution and Processing in the Cloud at the ASF DAAC

    Science.gov (United States)

    Stoner, C.; Arko, S. A.; Nicoll, J. B.; Labelle-Hamer, A. L.

    2016-12-01

    The Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC) has been tasked to archive and distribute data from both SENTINEL-1 satellites and from the NASA-ISRO Synthetic Aperture Radar (NISAR) satellite in a cost effective manner. In order to best support processing and distribution of these large data sets for users, the ASF DAAC enhanced our data system in a number of ways that will be detailed in this presentation.The SENTINEL-1 mission comprises a constellation of two polar-orbiting satellites, operating day and night performing C-band Synthetic Aperture Radar (SAR) imaging, enabling them to acquire imagery regardless of the weather. SENTINEL-1A was launched by the European Space Agency (ESA) in April 2014. SENTINEL-1B is scheduled to launch in April 2016.The NISAR satellite is designed to observe and take measurements of some of the planet's most complex processes, including ecosystem disturbances, ice-sheet collapse, and natural hazards such as earthquakes, tsunamis, volcanoes and landslides. NISAR will employ radar imaging, polarimetry, and interferometry techniques using the SweepSAR technology employed for full-resolution wide-swath imaging. NISAR data files are large, making storage and processing a challenge for conventional store and download systems.To effectively process, store, and distribute petabytes of data in a High-performance computing environment, ASF took a long view with regard to technology choices and picked a path of most flexibility and Software re-use. To that end, this Software tools and services presentation will cover Web Object Storage (WOS) and the ability to seamlessly move from local sunk cost hardware to public cloud, such as Amazon Web Services (AWS). A prototype of SENTINEL-1A system that is in AWS, as well as a local hardware solution, will be examined to explain the pros and cons of each. In preparation for NISAR files which will be even larger than SENTINEL-1A, ASF has embarked on a number of cloud

  1. Cloud Computing Impelementation Using Model Roadmap for Cloud Computing Adoption (ROCCA on IT Consultant Industry

    Directory of Open Access Journals (Sweden)

    Panji Arief Perdana

    2017-09-01

    increase the performance PT Matrica Consulting Service based on the characteristics of the cloud which is flexible and secure to be accessed as long as it is connected to the Internet and maintained properly.

  2. Quantifying uncertainties in radar forward models through a comparison between CloudSat and SPartICus reflectivity factors

    Science.gov (United States)

    Mascio, Jeana; Mace, Gerald G.

    2017-02-01

    Interpretations of remote sensing measurements collected in sample volumes containing ice-phase hydrometeors are very sensitive to assumptions regarding the distributions of mass with ice crystal dimension, otherwise known as mass-dimensional or m-D relationships. How these microphysical characteristics vary in nature is highly uncertain, resulting in significant uncertainty in algorithms that attempt to derive bulk microphysical properties from remote sensing measurements. This uncertainty extends to radar reflectivity factors forward calculated from model output because the statistics of the actual m-D in nature is not known. To investigate the variability in m-D relationships in cirrus clouds, reflectivity factors measured by CloudSat are combined with particle size distributions (PSDs) collected by coincident in situ aircraft by using an optimal estimation-based (OE) retrieval of the m-D power law. The PSDs were collected by 12 flights of the Stratton Park Engineering Company Learjet during the Small Particles in Cirrus campaign. We find that no specific habit emerges as preferred, and instead, we find that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum-defying simple categorization. With the uncertainties derived from the OE algorithm, the uncertainties in forward-modeled backscatter cross section and, in turn, radar reflectivity is calculated by using a bootstrapping technique, allowing us to infer the uncertainties in forward-modeled radar reflectivity that would be appropriately applied to remote sensing simulator algorithms.

  3. Value creation in the cloud: understanding business model factors affecting value of cloud computing

    OpenAIRE

    Morgan, Lorraine; Conboy, Kieran

    2013-01-01

    peer-reviewed Despite the rapid emergence of cloud technology, its prevalence and accessibility to all types of organizations and its potential to predominantly shift competitive landscapes by providing a new platform for creating and delivering business value, empirical research on the business value of cloud computing, and in particular how service providers create value for their customers, is quite limited. Of what little research exists to date, most focuses on technical issu...

  4. Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

    Science.gov (United States)

    Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

    2017-12-01

    Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

  5. The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

    Science.gov (United States)

    Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Helene; Douville, Herve; Good, Peter; Kay, Jennifer E.; hide

    2017-01-01

    The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions 'How does the Earth system respond to forcing?' and 'What are the origins and consequences of systematic model biases?' and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity. A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation

  6. SenseMyHeart: A cloud service and API for wearable heart monitors.

    Science.gov (United States)

    Pinto Silva, P M; Silva Cunha, J P

    2015-01-01

    In the era of ubiquitous computing, the growing adoption of wearable systems and body sensor networks is trailing the path for new research and software for cardiovascular intensity, energy expenditure and stress and fatigue detection through cardiovascular monitoring. Several systems have received clinical-certification and provide huge amounts of reliable heart-related data in a continuous basis. PhysioNet provides equally reliable open-source software tools for ECG processing and analysis that can be combined with these devices. However, this software remains difficult to use in a mobile environment and for researchers unfamiliar with Linux-based systems. In the present paper we present an approach that aims at tackling these limitations by developing a cloud service that provides an API for a PhysioNet-based pipeline for ECG processing and Heart Rate Variability measurement. We describe the proposed solution, along with its advantages and tradeoffs. We also present some client tools (windows and Android) and several projects where the developed cloud service has been used successfully as a standard for Heart Rate and Heart Rate Variability studies in different scenarios.

  7. A multilayer model to simulate rocket exhaust clouds

    Directory of Open Access Journals (Sweden)

    Davidson Martins Moreira

    2011-01-01

    Full Text Available This paper presents the MSDEF (Modelo Simulador da Dispersão de Efluentes de Foguetes, in Portuguese model, which represents the solution for time-dependent advection-diffusion equation applying the Laplace transform considering the Atmospheric Boundary Layer as a multilayer system. This solution allows a time evolution description of the concentration field emitted from a source during a release lasting time tr , and it takes into account deposition velocity, first-order chemical reaction, gravitational settling, precipitation scavenging, and plume rise effect. This solution is suitable for describing critical events relative to accidental release of toxic, flammable, or explosive substances. A qualitative evaluation of the model to simulate rocket exhaust clouds is showed.

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

    Science.gov (United States)

    Fu, Donglai; Liu, Yanhua

    2017-01-01

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

  9. Modelling operations and security of cloud systems using Z-notation and Chinese Wall security policy

    Science.gov (United States)

    Basu, Srijita; Sengupta, Anirban; Mazumdar, Chandan

    2016-11-01

    Enterprises are increasingly using cloud computing for hosting their applications. Availability of fast Internet and cheap bandwidth are causing greater number of people to use cloud-based services. This has the advantage of lower cost and minimum maintenance. However, ensuring security of user data and proper management of cloud infrastructure remain major areas of concern. Existing techniques are either too complex, or fail to properly represent the actual cloud scenario. This article presents a formal cloud model using the constructs of Z-notation. Principles of the Chinese Wall security policy have been applied to design secure cloud-specific operations. The proposed methodology will enable users to safely host their services, as well as process sensitive data, on cloud.

  10. Potential transformation of trace species including aircraft exhaust in a cloud environment. The `Chedrom model`

    Energy Technology Data Exchange (ETDEWEB)

    Ozolin, Y.E.; Karol, I.L. [Main Geophysical Observatory, St. Petersburg (Russian Federation); Ramaroson, R. [Office National d`Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

    1997-12-31

    Box model for coupled gaseous and aqueous phases is used for sensitivity study of potential transformation of trace gases in a cloud environment. The rate of this transformation decreases with decreasing of pH in droplets, with decreasing of photodissociation rates inside the cloud and with increasing of the droplet size. Model calculations show the potential formation of H{sub 2}O{sub 2} in aqueous phase and transformation of gaseous HNO{sub 3} into NO{sub x} in a cloud. This model is applied for exploration of aircraft exhausts evolution in plume inside a cloud. (author) 10 refs.

  11. Potential transformation of trace species including aircraft exhaust in a cloud environment. The `Chedrom model`

    Energy Technology Data Exchange (ETDEWEB)

    Ozolin, Y E; Karol, I L [Main Geophysical Observatory, St. Petersburg (Russian Federation); Ramaroson, R [Office National d` Etudes et de Recherches Aerospatiales (ONERA), 92 - Chatillon (France)

    1998-12-31

    Box model for coupled gaseous and aqueous phases is used for sensitivity study of potential transformation of trace gases in a cloud environment. The rate of this transformation decreases with decreasing of pH in droplets, with decreasing of photodissociation rates inside the cloud and with increasing of the droplet size. Model calculations show the potential formation of H{sub 2}O{sub 2} in aqueous phase and transformation of gaseous HNO{sub 3} into NO{sub x} in a cloud. This model is applied for exploration of aircraft exhausts evolution in plume inside a cloud. (author) 10 refs.

  12. Modeling ion sensing in molecular electronics

    International Nuclear Information System (INIS)

    Chen, Caroline J.; Smeu, Manuel; Ratner, Mark A.

    2014-01-01

    We examine the ability of molecules to sense ions by measuring the change in molecular conductance in the presence of such charged species. The detection of protons (H + ), alkali metal cations (M + ), calcium ions (Ca 2+ ), and hydronium ions (H 3 O + ) is considered. Density functional theory (DFT) is used within the Keldysh non-equilibrium Green's function framework (NEGF) to model electron transport properties of quinolinedithiol (QDT, C 9 H 7 NS 2 ), bridging Al electrodes. The geometry of the transport region is relaxed with DFT. The transport properties of the device are modeled with NEGF-DFT to determine if this device can distinguish among the M + + QDT species containing monovalent cations, where M + = H + , Li + , Na + , or K + . Because of the asymmetry of QDT in between the two electrodes, both positive and negative biases are considered. The electron transmission function and conductance properties are simulated for electrode biases in the range from −0.5 V to 0.5 V at increments of 0.1 V. Scattering state analysis is used to determine the molecular orbitals that are the main contributors to the peaks in the transmission function near the Fermi level of the electrodes, and current-voltage relationships are obtained. The results show that QDT can be used as a proton detector by measuring transport through it and can conceivably act as a pH sensor in solutions. In addition, QDT may be able to distinguish among different monovalent species. This work suggests an approach to design modern molecular electronic conductance sensors with high sensitivity and specificity using well-established quantum chemistry

  13. Cloud-turbulence interactions: Sensitivity of a general circulation model to closure assumptions

    International Nuclear Information System (INIS)

    Brinkop, S.; Roeckner, E.

    1993-01-01

    Several approaches to parameterize the turbulent transport of momentum, heat, water vapour and cloud water for use in a general circulation model (GCM) have been tested in one-dimensional and three-dimensional model simulations. The schemes differ with respect to their closure assumptions (conventional eddy diffusivity model versus turbulent kinetic energy closure) and also regarding their treatment of cloud-turbulence interactions. The basis properties of these parameterizations are discussed first in column simulations of a stratocumulus-topped atmospheric boundary layer (ABL) under a strong subsidence inversion during the KONTROL experiment in the North Sea. It is found that the K-models tend to decouple the cloud layer from the adjacent layers because the turbulent activity is calculated from local variables. The higher-order scheme performs better in this respect because internally generated turbulence can be transported up and down through the action of turbulent diffusion. Thus, the TKE-scheme provides not only a better link between the cloud and the sub-cloud layer but also between the cloud and the inversion as a result of cloud-top entrainment. In the stratocumulus case study, where the cloud is confined by a pronounced subsidence inversion, increased entrainment favours cloud dilution through enhanced evaporation of cloud droplets. In the GCM study, however, additional cloud-top entrainment supports cloud formation because indirect cloud generating processes are promoted through efficient ventilation of the ABL, such as the enhanced moisture supply by surface evaporation and the increased depth of the ABL. As a result, tropical convection is more vigorous, the hydrological cycle is intensified, the whole troposphere becomes warmer and moister in general and the cloudiness in the upper part of the ABL is increased. (orig.)

  14. Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

    Science.gov (United States)

    Putman, William M.

    2010-01-01

    NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

  15. Measurement and modeling of shortwave irradiance components in cloud-free atmospheres

    Energy Technology Data Exchange (ETDEWEB)

    Halthore, R.N.

    1999-08-04

    Atmosphere scatters and absorbs incident solar radiation modifying its spectral content and decreasing its intensity at the surface. It is very useful to classify the earth-atmospheric solar radiation into several components--direct solar surface irradiance (E{sub direct}), diffuse-sky downward surface irradiance (E{sub diffuse}), total surface irradiance, and upwelling flux at the surface and at the top-of-the atmosphere. E{sub direct} depends only on the extinction properties of the atmosphere without regard to details of extinction, namely scattering or absorption; furthermore it can be accurately measured to high accuracy (0.3%) with the aid of an active cavity radiometer (ACR). E{sub diffuse} has relatively larger uncertainties both in its measurement using shaded pyranometers and in model estimates, owing to the difficulty in accurately characterizing pyranometers and in measuring model inputs such as surface reflectance, aerosol single scattering albedo, and phase function. Radiative transfer model simulations of the above surface radiation components in cloud-free skies using measured atmospheric properties show that while E{sub direct} estimates are closer to measurements, E{sub diffuse} is overestimated by an amount larger than the combined uncertainties in model inputs and measurements, illustrating a fundamental gap in the understanding of the magnitude of atmospheric absorption in cloud-free skies. The excess continuum type absorption required to reduce the E{sub diffuse} model overestimate ({approximately}3--8% absorptance) would significantly impact climate prediction and remote sensing. It is not clear at present what the source for this continuum absorption is. Here issues related to measurements and modeling of the surface irradiance components are discussed.

  16. Improving Mixed-phase Cloud Parameterization in Climate Model with the ACRF Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Zhien [Univ. of Wyoming, Laramie, WY (United States)

    2016-12-13

    Mixed-phase cloud microphysical and dynamical processes are still poorly understood, and their representation in GCMs is a major source of uncertainties in overall cloud feedback in GCMs. Thus improving mixed-phase cloud parameterizations in climate models is critical to reducing the climate forecast uncertainties. This study aims at providing improved knowledge of mixed-phase cloud properties from the long-term ACRF observations and improving mixed-phase clouds simulations in the NCAR Community Atmosphere Model version 5 (CAM5). The key accomplishments are: 1) An improved retrieval algorithm was developed to provide liquid droplet concentration for drizzling or mixed-phase stratiform clouds. 2) A new ice concentration retrieval algorithm for stratiform mixed-phase clouds was developed. 3) A strong seasonal aerosol impact on ice generation in Arctic mixed-phase clouds was identified, which is mainly attributed to the high dust occurrence during the spring season. 4) A suite of multi-senor algorithms was applied to long-term ARM observations at the Barrow site to provide a complete dataset (LWC and effective radius profile for liquid phase, and IWC, Dge profiles and ice concentration for ice phase) to characterize Arctic stratiform mixed-phase clouds. This multi-year stratiform mixed-phase cloud dataset provides necessary information to study related processes, evaluate model stratiform mixed-phase cloud simulations, and improve model stratiform mixed-phase cloud parameterization. 5). A new in situ data analysis method was developed to quantify liquid mass partition in convective mixed-phase clouds. For the first time, we reliably compared liquid mass partitions in stratiform and convective mixed-phase clouds. Due to the different dynamics in stratiform and convective mixed-phase clouds, the temperature dependencies of liquid mass partitions are significantly different due to much higher ice concentrations in convective mixed phase clouds. 6) Systematic evaluations

  17. Forecasting Lightning Threat using Cloud-resolving Model Simulations

    Science.gov (United States)

    McCaul, E. W., Jr.; Goodman, S. J.; LaCasse, K. M.; Cecil, D. J.

    2009-01-01

    As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\\dgc\\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating

  18. ARM Cloud Radar Simulator Package for Global Climate Models Value-Added Product

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yuying [North Carolina State Univ., Raleigh, NC (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-05-01

    It has been challenging to directly compare U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility ground-based cloud radar measurements with climate model output because of limitations or features of the observing processes and the spatial gap between model and the single-point measurements. To facilitate the use of ARM radar data in numerical models, an ARM cloud radar simulator was developed to converts model data into pseudo-ARM cloud radar observations that mimic the instrument view of a narrow atmospheric column (as compared to a large global climate model [GCM] grid-cell), thus allowing meaningful comparison between model output and ARM cloud observations. The ARM cloud radar simulator value-added product (VAP) was developed based on the CloudSat simulator contained in the community satellite simulator package, the Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulator Package (COSP) (Bodas-Salcedo et al., 2011), which has been widely used in climate model evaluation with satellite data (Klein et al., 2013, Zhang et al., 2010). The essential part of the CloudSat simulator is the QuickBeam radar simulator that is used to produce CloudSat-like radar reflectivity, but is capable of simulating reflectivity for other radars (Marchand et al., 2009; Haynes et al., 2007). Adapting QuickBeam to the ARM cloud radar simulator within COSP required two primary changes: one was to set the frequency to 35 GHz for the ARM Ka-band cloud radar, as opposed to 94 GHz used for the CloudSat W-band radar, and the second was to invert the view from the ground to space so as to attenuate the beam correctly. In addition, the ARM cloud radar simulator uses a finer vertical resolution (100 m compared to 500 m for CloudSat) to resolve the more detailed structure of clouds captured by the ARM radars. The ARM simulator has been developed following the COSP workflow (Figure 1) and using the capabilities available in COSP

  19. Model simulations of aerosol effects on clouds and precipitation in comparison with ARM data

    Energy Technology Data Exchange (ETDEWEB)

    Penner, Joyce E. [Univ. of Michigan, Ann Arbor, MI (United States); Zhou, Cheng [Univ. of Michigan, Ann Arbor, MI (United States)

    2017-01-12

    Observation-based studies have shown that the aerosol cloud lifetime effect or the increase of cloud liquid water path (LWP) with increased aerosol loading may have been overestimated in climate models. Here, we simulate shallow warm clouds on 05/27/2011 at the Southern Great Plains (SGP) measurement site established by Department of Energy's Atmospheric Radiation Measurement (ARM) Program using a single column version of a global climate model (Community Atmosphere Model or CAM) and a cloud resolving model (CRM). The LWP simulated by CAM increases substantially with aerosol loading while that in the CRM does not. The increase of LWP in CAM is caused by a large decrease of the autoconversion rate when cloud droplet number increases. In the CRM, the autoconversion rate is also reduced, but this is offset or even outweighed by the increased evaporation of cloud droplets near cloud top, resulting in an overall decrease in LWP. Our results suggest that climate models need to include the dependence of cloud top growth and the evaporation/condensation process on cloud droplet number concentrations.

  20. A Dynamic Model for Load Balancing in Cloud Infrastructure

    Directory of Open Access Journals (Sweden)

    Jitendra Bhagwandas Bhatia

    2015-08-01

    Full Text Available This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform-independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, a prediction model is employed to maintain high availability and a power-aware algorithm is applied for choosing a suitable physical node for a virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.For anyone building a private, public or hybrid IaaS cloud infrastructure, load balancing of virtual hosts on a limited number of physical nodes, becomes a crucial aspect. This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, prediction model is employed to maintain high availability and power aware algorithm is applied for choosing a suitable physical node for virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.

  1. Aerosol activation and cloud processing in the global aerosol-climate model ECHAM5-HAM

    Directory of Open Access Journals (Sweden)

    G. J. Roelofs

    2006-01-01

    Full Text Available A parameterization for cloud processing is presented that calculates activation of aerosol particles to cloud drops, cloud drop size, and pH-dependent aqueous phase sulfur chemistry. The parameterization is implemented in the global aerosol-climate model ECHAM5-HAM. The cloud processing parameterization uses updraft speed, temperature, and aerosol size and chemical parameters simulated by ECHAM5-HAM to estimate the maximum supersaturation at the cloud base, and subsequently the cloud drop number concentration (CDNC due to activation. In-cloud sulfate production occurs through oxidation of dissolved SO2 by ozone and hydrogen peroxide. The model simulates realistic distributions for annually averaged CDNC although it is underestimated especially in remote marine regions. On average, CDNC is dominated by cloud droplets growing on particles from the accumulation mode, with smaller contributions from the Aitken and coarse modes. The simulations indicate that in-cloud sulfate production is a potentially important source of accumulation mode sized cloud condensation nuclei, due to chemical growth of activated Aitken particles and to enhanced coalescence of processed particles. The strength of this source depends on the distribution of produced sulfate over the activated modes. This distribution is affected by uncertainties in many parameters that play a direct role in particle activation, such as the updraft velocity, the aerosol chemical composition and the organic solubility, and the simulated CDNC is found to be relatively sensitive to these uncertainties.

  2. Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

    Science.gov (United States)

    Platnick, Steven E.

    2011-01-01

    The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

  3. RACLOUDS - Model for Clouds Risk Analysis in the Information Assets Context

    Directory of Open Access Journals (Sweden)

    SILVA, P. F.

    2016-06-01

    Full Text Available Cloud computing offers benefits in terms of availability and cost, but transfers the responsibility of information security management for the cloud service provider. Thus the consumer loses control over the security of their information and services. This factor has prevented the migration to cloud computing in many businesses. This paper proposes a model where the cloud consumer can perform risk analysis on providers before and after contracting the service. The proposed model establishes the responsibilities of three actors: Consumer, Provider and Security Labs. The inclusion of actor Security Labs provides more credibility to risk analysis making the results more consistent for the consumer.

  4. Baryon magnetic moments in the quark model and pion cloud contributions

    International Nuclear Information System (INIS)

    Sato, Toshiro; Sawada, Shoji

    1981-01-01

    Baryon magnetic moment is studied paying attention to the effects of pion cloud which is surrounding the 'bare' baryon whose magnetic moment is given by the quark model with broken SU(6) symmetry. The precisely measured nucleon magnetic moments are reproduced by the pion cloud contributions from the distance larger than 1.4 fm. The effects of pion cloud on the hyperon magnetic moments are also discussed. It is shown that the pion cloud contributions largely reduce the discrepancies between the quark model predictions and the recent accurate experimental data on the hyperon magnetic moments. (author)

  5. Experimental and Modeling Studies of Interactions of Marine Aerosols and Clouds

    National Research Council Canada - National Science Library

    Kreidenweis, Sonia

    1995-01-01

    The specific objectives of the modeling component are to develop models of the marine boundary layer, including models that predict cloud formation and evolution and the effects of such processes on the marine aerosol (and vice versa...

  6. Probing Clouds in Planets with a Simple Radiative Transfer Model: The Jupiter Case

    Science.gov (United States)

    Mendikoa, Inigo; Perez-Hoyos, Santiago; Sanchez-Lavega, Agustin

    2012-01-01

    Remote sensing of planets evokes using expensive on-orbit satellites and gathering complex data from space. However, the basic properties of clouds in planetary atmospheres can be successfully estimated with small telescopes even from an urban environment using currently available and affordable technology. This makes the process accessible for…

  7. Blueprint model and language for engineering cloud applications

    OpenAIRE

    Nguyen, D.K.

    2013-01-01

    The research presented in this thesis is positioned within the domain of engineering CSBAs. Its contribution is twofold: (1) a uniform specification language, called the Blueprint Specification Language (BSL), for specifying cloud services across several cloud vendors and (2) a set of associated techniques, called the Blueprint Manipulation Techniques (BMTs), for publishing, querying, and composing cloud service specifications with aim to support the flexible design and configuration of an CSBA.

  8. The virtual machine (VM) scaler: an infrastructure manager supporting environmental modeling on IaaS clouds

    Science.gov (United States)

    Infrastructure-as-a-service (IaaS) clouds provide a new medium for deployment of environmental modeling applications. Harnessing advancements in virtualization, IaaS clouds can provide dynamic scalable infrastructure to better support scientific modeling computational demands. Providing scientific m...

  9. A business model for a South African government public cloud platform

    CSIR Research Space (South Africa)

    Mvelase, P

    2014-05-01

    Full Text Available of public services is conducted. This paper designs a cloud business model that suits South Africa’s perspective. The idea is to model a government public cloud which does not interfere with the secured business functions of the government but find a...

  10. The Kimball Free-Cloud Model: A Failed Innovation in Chemical Education?

    Science.gov (United States)

    Jensen, William B.

    2014-01-01

    This historical review traces the origins of the Kimball free-cloud model of the chemical bond, otherwise known as the charge-cloud or tangent-sphere model, and the central role it played in attempts to reform the introductory chemical curriculum at both the high school and college levels in the 1960s. It also critically evaluates the limitations…

  11. The Radiative Properties of Small Clouds: Multi-Scale Observations and Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Feingold, Graham [NOAA ESRL; McComiskey, Allison [CIRES, University of Colorado

    2013-09-25

    Warm, liquid clouds and their representation in climate models continue to represent one of the most significant unknowns in climate sensitivity and climate change. Our project combines ARM observations, LES modeling, and satellite imagery to characterize shallow clouds and the role of aerosol in modifying their radiative effects.

  12. Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions

    NARCIS (Netherlands)

    Neggers, R.A.J.; Ackerman, Andrew S.; Angevine, W. M.; Bazile, Eric; Beau, I.; Blossey, P. N.; Boutle, I. A.; de Bruijn, C.; cheng, A; van der Dussen, J.J.; Fletcher, J.; Dal Gesso, S.; Jam, A.; Kawai, H; Cheedela, S. K.; Larson, V. E.; Lefebvre, Marie Pierre; Lock, A. P.; Meyer, N. R.; de Roode, S.R.; de Rooy, WC; Sandu, I; Xiao, H; Xu, K. M.

    2017-01-01

    Results are presented of the GASS/EUCLIPSE single-column model intercomparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate models for this cloud regime, using

  13. Final Report for 'Modeling Electron Cloud Diagnostics for High-Intensity Proton Accelerators'

    International Nuclear Information System (INIS)

    Veitzer, Seth A.

    2009-01-01

    Electron clouds in accelerators such as the ILC degrade beam quality and limit operating efficiency. The need to mitigate electron clouds has a direct impact on the design and operation of these accelerators, translating into increased cost and reduced performance. Diagnostic techniques for measuring electron clouds in accelerating cavities are needed to provide an assessment of electron cloud evolution and mitigation. Accurate numerical modeling of these diagnostics is needed to validate the experimental techniques. In this Phase I, we developed detailed numerical models of microwave propagation through electron clouds in accelerating cavities with geometries relevant to existing and future high-intensity proton accelerators such as Project X and the ILC. Our numerical techniques and simulation results from the Phase I showed that there was a high probability of success in measuring both the evolution of electron clouds and the effects of non-uniform electron density distributions in Phase II.

  14. The Importance of Business Model Factors for Cloud Computing Adoption: Role of Previous Experiences

    Directory of Open Access Journals (Sweden)

    Bogataj Habjan Kristina

    2017-08-01

    Full Text Available Background and Purpose: Bringing several opportunities for more effective and efficient IT governance and service exploitation, cloud computing is expected to impact the European and global economies significantly. Market data show that despite many advantages and promised benefits the adoption of cloud computing is not as fast and widespread as foreseen. This situation shows the need for further exploration of the potentials of cloud computing and its implementation on the market. The purpose of this research was to identify individual business model factors with the highest impact on cloud computing adoption. In addition, the aim was to identify the differences in opinion regarding the importance of business model factors on cloud computing adoption according to companies’ previous experiences with cloud computing services.

  15. Making sense of the Sense Model: translation priming with Japanese-English bilinguals

    OpenAIRE

    Allen, David; Conklin, Kathy; Van Heuven, Walter J.B.

    2015-01-01

    Many studies have reported that first language (L1) translation primes speed responses to second language (L2) targets, whereas L2 translation primes generally do not speed up responses to L1 targets in lexical decision. According to the Sense Model (Finkbeiner, Forster, Nicol & Nakamura, 2004) this asymmetry is due to the proportion of senses activated by the prime. Because L2 primes activate only a subset of the L1 translations senses, priming is not observed. In this study we test the pred...

  16. Forecasting Lightning Threat using Cloud-Resolving Model Simulations

    Science.gov (United States)

    McCaul, Eugene W., Jr.; Goodman, Steven J.; LaCasse, Katherine M.; Cecil, Daniel J.

    2008-01-01

    Two new approaches are proposed and developed for making time and space dependent, quantitative short-term forecasts of lightning threat, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the WRF model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed phase region at the-15 C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash rate proxy fields against domain-wide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. Our blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Exploratory tests for selected North Alabama cases show that, because WRF can distinguish the general character of most convective events, our methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single

  17. Above the cloud computing orbital services distributed data model

    Science.gov (United States)

    Straub, Jeremy

    2014-05-01

    Technology miniaturization and system architecture advancements have created an opportunity to significantly lower the cost of many types of space missions by sharing capabilities between multiple spacecraft. Historically, most spacecraft have been atomic entities that (aside from their communications with and tasking by ground controllers) operate in isolation. Several notable example exist; however, these are purpose-designed systems that collaborate to perform a single goal. The above the cloud computing (ATCC) concept aims to create ad-hoc collaboration between service provider and consumer craft. Consumer craft can procure processing, data transmission, storage, imaging and other capabilities from provider craft. Because of onboard storage limitations, communications link capability limitations and limited windows of communication, data relevant to or required for various operations may span multiple craft. This paper presents a model for the identification, storage and accessing of this data. This model includes appropriate identification features for this highly distributed environment. It also deals with business model constraints such as data ownership, retention and the rights of the storing craft to access, resell, transmit or discard the data in its possession. The model ensures data integrity and confidentiality (to the extent applicable to a given data item), deals with unique constraints of the orbital environment and tags data with business model (contractual) obligation data.

  18. The simplest model of a dust cloud in a plasma

    International Nuclear Information System (INIS)

    Ignatov, A.M.

    1998-01-01

    A cloud consisting of a finite number of dust grains in a plasma is considered. It is shown that the absorption of the plasma by the dust grains gives rise to the formation of a plasma flow toward to the cloud. The drag force produced by this flow acts upon the dust grains and counterbalances the electrostatic repulsing force. The distribution of the grain density inside the cloud is determined. The characteristic size of the cloud is estimated as r D 3/2 /a 1/2 , where r D is the plasma Debye radius, and a is the size of the dust grains

  19. Estimation of convective entrainment properties from a cloud-resolving model simulation during TWP-ICE

    Science.gov (United States)

    Zhang, Guang J.; Wu, Xiaoqing; Zeng, Xiping; Mitovski, Toni

    2016-10-01

    The fractional entrainment rate in convective clouds is an important parameter in current convective parameterization schemes of climate models. In this paper, it is estimated using a 1-km-resolution cloud-resolving model (CRM) simulation of convective clouds from TWP-ICE (the Tropical Warm Pool-International Cloud Experiment). The clouds are divided into different types, characterized by cloud-top heights. The entrainment rates and moist static energy that is entrained or detrained are determined by analyzing the budget of moist static energy for each cloud type. Results show that the entrained air is a mixture of approximately equal amount of cloud air and environmental air, and the detrained air is a mixture of ~80 % of cloud air and 20 % of the air with saturation moist static energy at the environmental temperature. After taking into account the difference in moist static energy between the entrained air and the mean environment, the estimated fractional entrainment rate is much larger than those used in current convective parameterization schemes. High-resolution (100 m) large-eddy simulation of TWP-ICE convection was also analyzed to support the CRM results. It is shown that the characteristics of entrainment rates estimated using both the high-resolution data and CRM-resolution coarse-grained data are similar. For each cloud category, the entrainment rate is high near cloud base and top, but low in the middle of clouds. The entrainment rates are best fitted to the inverse of in-cloud vertical velocity by a second order polynomial.

  20. Provide a model to improve the performance of intrusion detection systems in the cloud

    OpenAIRE

    Foroogh Sedighi

    2016-01-01

    High availability of tools and service providers in cloud computing and the fact that cloud computing services are provided by internet and deal with public, have caused important challenges for new computing model. Cloud computing faces problems and challenges such as user privacy, data security, data ownership, availability of services, and recovery after breaking down, performance, scalability, programmability. So far, many different methods are presented for detection of intrusion in clou...

  1. A novel cost based model for energy consumption in cloud computing.

    Science.gov (United States)

    Horri, A; Dastghaibyfard, Gh

    2015-01-01

    Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment.

  2. Clouds and the extratropical circulation response to global warming in a hierarchy of global atmosphere models

    Science.gov (United States)

    Voigt, A.

    2017-12-01

    Climate models project that global warming will lead to substantial changes in extratropical jet streams. Yet, many quantitative aspects of warming-induced jet stream changes remain uncertain, and recent work has indicated an important role of clouds and their radiative interactions. Here, I will investigate how cloud-radiative changes impact the zonal-mean extratropical circulation response under global warming using a hierarchy of global atmosphere models. I will first focus on aquaplanet setups with prescribed sea-surface temperatures (SSTs), which reproduce the model spread found in realistic simulations with interactive SSTs. Simulations with two CMIP5 models MPI-ESM and IPSL-CM5A and prescribed clouds show that half of the circulation response can be attributed to cloud changes. The rise of tropical high-level clouds and the upward and poleward movement of midlatitude high-level clouds lead to poleward jet shifts. High-latitude low-level cloud changes shift the jet poleward in one model but not in the other. The impact of clouds on the jet operates via the atmospheric radiative forcing that is created by the cloud changes and is qualitatively reproduced in a dry Held-Suarez model, although the latter is too sensitive because of its simplified treatment of diabatic processes. I will then show that the aquaplanet results also hold when the models are used in a realistic setup that includes continents and seasonality. I will further juxtapose these prescribed-SST simulations with interactive-SST simulations and show that atmospheric and surface cloud-radiative interactions impact the jet poleward jet shifts in about equal measure. Finally, I will discuss the cloud impact on regional and seasonal circulation changes.

  3. Global vertical mass transport by clouds - A two-dimensional model study

    International Nuclear Information System (INIS)

    Olofsson, Mats

    1988-05-01

    A two-dimensional global dispersion model, where vertical transport in the troposphere carried out by convective as well as by frontal cloud systems is explicitly treated, is developed from an existing diffusion model. A parameterization scheme for the cloud transport, based on global cloud statistics, is presented. The model has been tested by using Kr-85, Rn-222 and SO 2 as tracers. Comparisons have been made with observed distributions of these tracers, but also with model results without the cloud transport, using eddy diffusion as the primary means of vertical transport. The model results indicate that for trace species with a turnover time of days to weeks, the introduction of cloud-transport gives much more realistic simulations of their vertical distribution. Layers of increased mixing ratio with height, which can be found in real atmosphere, are reproduced in our cloud-transport model profiles, but can never be simulated with a pure eddy diffusion model. The horizontal transport in the model, by advection and eddy diffusion, gives a realistic distribution between the hemispheres of the more long-lived tracers (Kr-85). A combination of vertical transport by convective and frontal cloud systems is shown to improve the model simulations, compared to limiting it to convective transport only. The importance of including cumulus clouds in the convective transport scheme, in addition to the efficient transport by cumulonimbus clouds, is discussed. The model results are shown to be more sensitive to the vertical detrainment distribution profile than to the absolute magnitude of the vertical mass transport. The scavenging processes for SO 2 are parameterized without the introduction of detailed chemistry. An enhanced removal, due to the increased contact with droplets in the in-cloud lifting process, is introduced in the model. (author)

  4. COLLISIONAL GROOMING MODELS OF THE KUIPER BELT DUST CLOUD

    International Nuclear Information System (INIS)

    Kuchner, Marc J.; Stark, Christopher C.

    2010-01-01

    We modeled the three-dimensional structure of the Kuiper Belt (KB) dust cloud at four different dust production rates, incorporating both planet-dust interactions and grain-grain collisions using the collisional grooming algorithm. Simulated images of a model with a face-on optical depth of ∼10 -4 primarily show an azimuthally symmetric ring at 40-47 AU in submillimeter and infrared wavelengths; this ring is associated with the cold classical KB. For models with lower optical depths (10 -6 and 10 -7 ), synthetic infrared images show that the ring widens and a gap opens in the ring at the location of Neptune; this feature is caused by trapping of dust grains in Neptune's mean motion resonances. At low optical depths, a secondary ring also appears associated with the hole cleared in the center of the disk by Saturn. Our simulations, which incorporate 25 different grain sizes, illustrate that grain-grain collisions are important in sculpting today's KB dust, and probably other aspects of the solar system dust complex; collisions erase all signs of azimuthal asymmetry from the submillimeter image of the disk at every dust level we considered. The model images switch from being dominated by resonantly trapped small grains ('transport dominated') to being dominated by the birth ring ('collision dominated') when the optical depth reaches a critical value of τ ∼ v/c, where v is the local Keplerian speed.

  5. Collisional Grooming Models of the Kuiper Belt Dust Cloud

    Science.gov (United States)

    Kuchner, Marc J.; Stark, Christopher C.

    2010-01-01

    We modeled the three-dimensional structure of the Kuiper Belt (KB) dust cloud at four different dust production rates, incorporating both planet-dust interactions and grain-grain collisions using the collisional grooming algorithm. Simulated images of a model with a face-on optical depth of approximately 10 (exp -4) primarily show an azimuthally- symmetric ring at 40-47 AU in submillimeter and infrared wavelengths; this ring is associated with the cold classical KB. For models with lower optical depths (10 (exp -6) and 10 (exp-7)), synthetic infrared images show that the ring widens and a gap opens in the ring at the location of Neptune; this feature is caused by trapping of dust grains in Neptune's mean motion resonances. At low optical depths, a secondary ring also appears associated with the hole cleared in the center of the disk by Saturn. Our simulations, which incorporate 25 different grain sizes, illustrate that grain-grain collisions are important in sculpting today's KB dust, and probably other aspects of the solar system dust complex; collisions erase all signs of azimuthal asymmetry from the submillimeter image of the disk at every dust level we considered. The model images switch from being dominated by resonantly trapped small grains ("transport dominated") to being dominated by the birth ring ("collision dominated") when the optical depth reaches a critical value of r approximately v/c, where v is the local Keplerian speed.

  6. Blueprint model and language for engineering cloud applications

    NARCIS (Netherlands)

    Nguyen, D.K.

    2013-01-01

    The research presented in this thesis is positioned within the domain of engineering CSBAs. Its contribution is twofold: (1) a uniform specification language, called the Blueprint Specification Language (BSL), for specifying cloud services across several cloud vendors and (2) a set of associated

  7. User Utility Oriented Queuing Model for Resource Allocation in Cloud Environment

    Directory of Open Access Journals (Sweden)

    Zhe Zhang

    2015-01-01

    Full Text Available Resource allocation is one of the most important research topics in servers. In the cloud environment, there are massive hardware resources of different kinds, and many kinds of services are usually run on virtual machines of the cloud server. In addition, cloud environment is commercialized, and economical factor should also be considered. In order to deal with commercialization and virtualization of cloud environment, we proposed a user utility oriented queuing model for task scheduling. Firstly, we modeled task scheduling in cloud environment as an M/M/1 queuing system. Secondly, we classified the utility into time utility and cost utility and built a linear programming model to maximize total utility for both of them. Finally, we proposed a utility oriented algorithm to maximize the total utility. Massive experiments validate the effectiveness of our proposed model.

  8. Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework

    Energy Technology Data Exchange (ETDEWEB)

    Ackerman, Thomas P. [Univ. of Washington, Seattle, WA (United States)

    2015-03-01

    The research performed under this grant was intended to improve the embedded cloud model in the Multi-scale Modeling Framework (MMF) for convective clouds by using a 2-moment microphysics scheme rather than the single moment scheme used in all the MMF runs to date. The technical report and associated documents describe the results of testing the cloud resolving model with fixed boundary conditions and evaluation of model results with data. The overarching conclusion is that such model evaluations are problematic because errors in the forcing fields control the results so strongly that variations in parameterization values cannot be usefully constrained

  9. Representation of Arctic mixed-phase clouds and the Wegener-Bergeron-Findeisen process in climate models: Perspectives from a cloud-resolving study

    Science.gov (United States)

    Fan, Jiwen; Ghan, Steven; Ovchinnikov, Mikhail; Liu, Xiaohong; Rasch, Philip J.; Korolev, Alexei

    2011-01-01

    Two types of Arctic mixed-phase clouds observed during the ISDAC and M-PACE field campaigns are simulated using a 3-dimensional cloud-resolving model (CRM) with size-resolved cloud microphysics. The modeled cloud properties agree reasonably well with aircraft measurements and surface-based retrievals. Cloud properties such as the probability density function (PDF) of vertical velocity (w), cloud liquid and ice, regimes of cloud particle growth, including the Wegener-Bergeron-Findeisen (WBF) process, and the relationships among properties/processes in mixed-phase clouds are examined to gain insights for improving their representation in General Circulation Models (GCMs). The PDF of the simulated w is well represented by a Gaussian function, validating, at least for arctic clouds, the subgrid treatment used in GCMs. The PDFs of liquid and ice water contents can be approximated by Gamma functions, and a Gaussian function can describe the total water distribution, but a fixed variance assumption should be avoided in both cases. The CRM results support the assumption frequently used in GCMs that mixed phase clouds maintain water vapor near liquid saturation. Thus, ice continues to grow throughout the stratiform cloud but the WBF process occurs in about 50% of cloud volume where liquid and ice co-exist, predominantly in downdrafts. In updrafts, liquid and ice particles grow simultaneously. The relationship between the ice depositional growth rate and cloud ice strongly depends on the capacitance of ice particles. The simplified size-independent capacitance of ice particles used in GCMs could lead to large deviations in ice depositional growth.

  10. A study of cloud microphysics and precipitation over the Tibetan Plateau by radar observations and cloud-resolving model simulations: Cloud Microphysics over Tibetan Plateau

    Energy Technology Data Exchange (ETDEWEB)

    Gao, Wenhua [State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China; Pacific Northwest National Laboratory, Richland Washington USA; Sui, Chung-Hsiung [Department of Atmospheric Sciences, National Taiwan University, Taipei Taiwan; Fan, Jiwen [Pacific Northwest National Laboratory, Richland Washington USA; Hu, Zhiqun [State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China; Zhong, Lingzhi [State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing China

    2016-11-27

    Cloud microphysical properties and precipitation over the Tibetan Plateau (TP) are unique because of the high terrains, clean atmosphere, and sufficient water vapor. With dual-polarization precipitation radar and cloud radar measurements during the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III), the simulated microphysics and precipitation by the Weather Research and Forecasting model (WRF) with the Chinese Academy of Meteorological Sciences (CAMS) microphysics and other microphysical schemes are investigated through a typical plateau rainfall event on 22 July 2014. Results show that the WRF-CAMS simulation reasonably reproduces the spatial distribution of 24-h accumulated precipitation, but has limitations in simulating time evolution of precipitation rates. The model-calculated polarimetric radar variables have biases as well, suggesting bias in modeled hydrometeor types. The raindrop sizes in convective region are larger than those in stratiform region indicated by the small intercept of raindrop size distribution in the former. The sensitivity experiments show that precipitation processes are sensitive to the changes of warm rain processes in condensation and nucleated droplet size (but less sensitive to evaporation process). Increasing droplet condensation produces the best area-averaged rain rate during weak convection period compared with the observation, suggesting a considerable bias in thermodynamics in the baseline simulation. Increasing the initial cloud droplet size causes the rain rate reduced by half, an opposite effect to that of increasing droplet condensation.

  11. Cloud vector mapping using MODIS 09 Climate Modeling Grid (CMG) for the year 2010 and 2011

    International Nuclear Information System (INIS)

    Jah, Asjad Asif; Farrukh, Yousaf Bin; Ali, Rao Muhammad Saeed

    2013-01-01

    An alternate use for MODIS images was sought by mapping cloud movement directions and dissipation time during the 2010 and 2011 floods. MODIS Level-02 daily CMG (Climate Modelling Grid) land-cover images were downloaded and subsequently rectified and clipped to the study area. These images were then put together to observe the direction of cloud movement and vectorize the observed paths. Initial findings suggest that usually cloud does not have a prolonged coverage period over the northern humid region of the country and dissipates within less than 24-hours. Additionally, this led to the development of a robust methodology for cloud motion analysis using FOSS and market leading GIS utilities

  12. A GLOBAL MAGNETIC TOPOLOGY MODEL FOR MAGNETIC CLOUDS. II

    Energy Technology Data Exchange (ETDEWEB)

    Hidalgo, M. A., E-mail: miguel.hidalgo@uah.es [Departamento de Fisica, Universidad de Alcala, Apartado 20, E-28871 Alcala de Henares, Madrid (Spain)

    2013-04-01

    In the present work, we extensively used our analytical approach to the global magnetic field topology of magnetic clouds (MCs), introduced in a previous paper, in order to show its potential and to study its physical consistency. The model assumes toroidal topology with a non-uniform (variable maximum radius) cross-section along them. Moreover, it has a non-force-free character and also includes the expansion of its cross-section. As is shown, the model allows us, first, to analyze MC magnetic structures-determining their physical parameters-with a variety of magnetic field shapes, and second, to reconstruct their relative orientation in the interplanetary medium from the observations obtained by several spacecraft. Therefore, multipoint spacecraft observations give the opportunity to infer the structure of this large-scale magnetic flux rope structure in the solar wind. For these tasks, we use data from Helios (A and B), STEREO (A and B), and Advanced Composition Explorer. We show that the proposed analytical model can explain quite well the topology of several MCs in the interplanetary medium and is a good starting point for understanding the physical mechanisms under these phenomena.

  13. Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review

    Science.gov (United States)

    Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela

    2017-11-01

    Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using

  14. Mechanisms and Model Diversity of Trade-Wind Shallow Cumulus Cloud Feedbacks: A Review

    Science.gov (United States)

    Vial, Jessica; Bony, Sandrine; Stevens, Bjorn; Vogel, Raphaela

    Shallow cumulus clouds in the trade-wind regions are at the heart of the long standing uncertainty in climate sensitivity estimates. In current climate models, cloud feedbacks are strongly influenced by cloud-base cloud amount in the trades. Therefore, understanding the key factors controlling cloudiness near cloud-base in shallow convective regimes has emerged as an important topic of investigation. We review physical understanding of these key controlling factors and discuss the value of the different approaches that have been developed so far, based on global and high-resolution model experimentations and process-oriented analyses across a range of models and for observations. The trade-wind cloud feedbacks appear to depend on two important aspects: (1) how cloudiness near cloud-base is controlled by the local interplay between turbulent, convective and radiative processes; (2) how these processes interact with their surrounding environment and are influenced by mesoscale organization. Our synthesis of studies that have explored these aspects suggests that the large diversity of model responses is related to fundamental differences in how the processes controlling trade cumulus operate in models, notably, whether they are parameterized or resolved. In models with parameterized convection, cloudiness near cloud-base is very sensitive to the vigor of convective mixing in response to changes in environmental conditions. This is in contrast with results from high-resolution models, which suggest that cloudiness near cloud-base is nearly invariant with warming and independent of large-scale environmental changes. Uncertainties are difficult to narrow using current observations, as the trade cumulus variability and its relation to large-scale environmental factors strongly depend on the time and/or spatial scales at which the mechanisms are evaluated. New opportunities for testing physical understanding of the factors controlling shallow cumulus cloud responses using

  15. Building an Elastic Parallel OGC Web Processing Service on a Cloud-Based Cluster: A Case Study of Remote Sensing Data Processing Service

    Directory of Open Access Journals (Sweden)

    Xicheng Tan

    2015-10-01

    Full Text Available Since the Open Geospatial Consortium (OGC proposed the geospatial Web Processing Service (WPS, standard OGC Web Service (OWS-based geospatial processing has become the major type of distributed geospatial application. However, improving the performance and sustainability of the distributed geospatial applications has become the dominant challenge for OWSs. This paper presents the construction of an elastic parallel OGC WPS service on a cloud-based cluster and the designs of a high-performance, cloud-based WPS service architecture, the scalability scheme of the cloud, and the algorithm of the elastic parallel geoprocessing. Experiments of the remote sensing data processing service demonstrate that our proposed method can provide a higher-performance WPS service that uses less computing resources. Our proposed method can also help institutions reduce hardware costs, raise the rate of hardware usage, and conserve energy, which is important in building green and sustainable geospatial services or applications.

  16. Observations of Co-variation in Cloud Properties and their Relationships with Atmospheric State

    Science.gov (United States)

    Sinclair, K.; van Diedenhoven, B.; Fridlind, A. M.; Arnold, T. G.; Yorks, J. E.; Heymsfield, G. M.; McFarquhar, G. M.; Um, J.

    2017-12-01

    Radiative properties of upper tropospheric ice clouds are generally not well represented in global and cloud models. Cloud top height, cloud thermodynamic phase, cloud optical thickness, cloud water path, particle size and ice crystal shape all serve as observational targets for models to constrain cloud properties. Trends or biases in these cloud properties could have profound effects on the climate since they affect cloud radiative properties. Better understanding of co-variation between these cloud properties and linkages with atmospheric state variables can lead to better representation of clouds in models by reducing biases in their micro- and macro-physical properties as well as their radiative properties. This will also enhance our general understanding of cloud processes. In this analysis we look at remote sensing, in situ and reanalysis data from the MODIS Airborne Simulator (MAS), Cloud Physics Lidar (CPL), Cloud Radar System (CRS), GEOS-5 reanalysis data and GOES imagery obtained during the Tropical Composition, Cloud and Climate Coupling (TC4) airborne campaign. The MAS, CPL and CRS were mounted on the ER-2 high-altitude aircraft during this campaign. In situ observations of ice size and shape were made aboard the DC8 and WB57 aircrafts. We explore how thermodynamic phase, ice effective radius, particle shape and radar reflectivity vary with altitude and also investigate how these observed cloud properties vary with cloud type, cloud top temperature, relative humidity and wind profiles. Observed systematic relationships are supported by physical interpretations of cloud processes and any unexpected differences are examined.

  17. Analytic Closed-Form Solution of a Mixed Layer Model for Stratocumulus Clouds

    Science.gov (United States)

    Akyurek, Bengu Ozge

    Stratocumulus clouds play an important role in climate cooling and are hard to predict using global climate and weather forecast models. Thus, previous studies in the literature use observations and numerical simulation tools, such as large-eddy simulation (LES), to solve the governing equations for the evolution of stratocumulus clouds. In contrast to the previous works, this work provides an analytic closed-form solution to the cloud thickness evolution of stratocumulus clouds in a mixed-layer model framework. With a focus on application over coastal lands, the diurnal cycle of cloud thickness and whether or not clouds dissipate are of particular interest. An analytic solution enables the sensitivity analysis of implicitly interdependent variables and extrema analysis of cloud variables that are hard to achieve using numerical solutions. In this work, the sensitivity of inversion height, cloud-base height, and cloud thickness with respect to initial and boundary conditions, such as Bowen ratio, subsidence, surface temperature, and initial inversion height, are studied. A critical initial cloud thickness value that can be dissipated pre- and post-sunrise is provided. Furthermore, an extrema analysis is provided to obtain the minima and maxima of the inversion height and cloud thickness within 24 h. The proposed solution is validated against LES results under the same initial and boundary conditions. Then, the proposed analytic framework is extended to incorporate multiple vertical columns that are coupled by advection through wind flow. This enables a bridge between the micro-scale and the mesoscale relations. The effect of advection on cloud evolution is studied and a sensitivity analysis is provided.

  18. Investigation of drought-vulnerable regions in North Korea using remote sensing and cloud computing climate data.

    Science.gov (United States)

    Yu, Jinhang; Lim, Joongbin; Lee, Kyoo-Seock

    2018-02-08

    Drought is one of the most severe natural disasters in the world and leads to serious challenges that affect both the natural environment and human societies. North Korea (NK) has frequently suffered from severe and prolonged droughts since the second half of the twentieth century. These droughts affect the growing conditions of agricultural crops, which have led to food shortages in NK. However, it is not easy to obtain ground data because NK is one of the most closed-off societies in the world. In this situation, remote sensing (RS) techniques and cloud computing climate data (CCCD) can be used for drought monitoring in NK. RS-derived drought indices and CCCD were used to determine the drought-vulnerable regions in the spring season in NK. After the results were compared and discussed, the following conclusions were derived: (1) 10.0% of the total area of NK is estimated to be a drought-vulnerable region. The most susceptible regions to drought appear in the eastern and western coastal regions, far from BaekDu-DaeGan (BDDG), while fewer drought regions are found near BDDG and the Nahngrim Mountains. The drought-vulnerable regions are the coastal regions of South Hamgyong Province, North Hamgyong Province, South Pyongan Province, and South Hwanghae Province. The latter region is the food basket of NK. (2) In terms of land cover, the drought-vulnerable regions mainly consisted of croplands and mixed forest.

  19. Integrated Model to Assess Cloud Deployment Effectiveness When Developing an IT-strategy

    Science.gov (United States)

    Razumnikov, S.; Prankevich, D.

    2016-04-01

    Developing an IT-strategy of cloud deployment is a complex issue since even the stage of its formation necessitates revealing what applications will be the best possible to meet the requirements of a company business-strategy, evaluate reliability and safety of cloud providers and analyze staff satisfaction. A system of criteria, as well an integrated model to assess cloud deployment effectiveness is offered. The model makes it possible to identify what applications being at the disposal of a company, as well as new tools to be deployed are reliable and safe enough for implementation in the cloud environment. The data on practical use of the procedure to assess cloud deployment effectiveness by a provider of telecommunication services is presented. The model was used to calculate values of integral indexes of services to be assessed, then, ones, meeting the criteria and answering the business-strategy of a company, were selected.

  20. The role of aerosols in cloud drop parameterizations and its applications in global climate models

    Energy Technology Data Exchange (ETDEWEB)

    Chuang, C.C.; Penner, J.E. [Lawrence Livermore National Lab., CA (United States)

    1996-04-01

    The characteristics of the cloud drop size distribution near cloud base are initially determined by aerosols that serve as cloud condensation nuclei and the updraft velocity. We have developed parameterizations relating cloud drop number concentration to aerosol number and sulfate mass concentrations and used them in a coupled global aerosol/general circulation model (GCM) to estimate the indirect aerosol forcing. The global aerosol model made use of our detailed emissions inventories for the amount of particulate matter from biomass burning sources and from fossil fuel sources as well as emissions inventories of the gas-phase anthropogenic SO{sub 2}. This work is aimed at validating the coupled model with the Atmospheric Radiation Measurement (ARM) Program measurements and assessing the possible magnitude of the aerosol-induced cloud effects on climate.

  1. Inverse modeling of cloud-aerosol interactions -- Part 1: Detailed response surface analysis

    NARCIS (Netherlands)

    Partridge, D.G.; Vrugt, J.A.; Tunved, P.; Ekman, A.M.L.; Gorea, D.; Sooroshian, A.

    2011-01-01

    New methodologies are required to probe the sensitivity of parameters describing cloud droplet activation. This paper presents an inverse modeling-based method for exploring cloud-aerosol interactions via response surfaces. The objective function, containing the difference between the measured and

  2. Simulation modeling of cloud computing for smart grid using CloudSim

    Directory of Open Access Journals (Sweden)

    Sandeep Mehmi

    2017-05-01

    Full Text Available In this paper a smart grid cloud has been simulated using CloudSim. Various parameters like number of virtual machines (VM, VM Image size, VM RAM, VM bandwidth, cloudlet length, and their effect on cost and cloudlet completion time in time-shared and space-shared resource allocation policy have been studied. As the number of cloudlets increased from 68 to 178, greater number of cloudlets completed their execution with high cloudlet completion time in time-shared allocation policy as compared to space-shared allocation policy. Similar trend has been observed when VM bandwidth is increased from 1 Gbps to 10 Gbps and VM RAM is increased from 512 MB to 5120 MB. The cost of processing increased linearly with respect to increase in number of VMs, VM Image size and cloudlet length.

  3. A Hybrid Verifiable and Delegated Cryptographic Model in Cloud Computing

    Directory of Open Access Journals (Sweden)

    Jaber Ibrahim Naser

    2018-02-01

    Full Text Available Access control is very important in cloud data sharing. Especially in the domains like healthcare, it is essential to have access control mechanisms in place for confidentiality and secure data access. Attribute based encryption has been around for many years to secure data and provide controlled access. In this paper, we proposed a framework that supports circuit and attributes based encryption mechanism that involves multiple parties. They are data owner, data user, cloud server and attribute authority. An important feature of the proposed system is the verifiable delegation of the decryption process to cloud server. Data owner encrypts data and delegates decryption process to cloud. Cloud server performs partial decryption and then the final decrypted data are shared for users as per the privileges. Data owner  thus reduces computational complexity by delegating decryption process cloud server. We built a prototype application using the Microsoft.NET platform for proof of the concept. The empirical results revealed that there is controlled access with multiple user roles and access control rights for secure and confidential data access in cloud computing.

  4. Development of Presentation Model with Cloud Based Infrastructure

    Directory of Open Access Journals (Sweden)

    Magdalena Widiantari Maria

    2018-01-01

    Full Text Available Computer mediated communication are the communication activities using technology which have rapidly in progress. Communication interactive activities nowadays has no longer only involving person to person but mediated by technology, and have been done in many fields including in education and teaching activity. In this study, presentation media based on cloud's infrastructure designed to replace face to face or in class lectures. In addition, the presentation will allow media data storage indefinitely, and accessible wherever and anytime. This is in line with the concept of student center learning where students were encouraged to more active in the lecture activities. The purpose of this research is making or designing a presentation model based on cloud‘s infrastructure. This research is using research and development method which is consists of four stages, where the first phase is composing the concept of media presentation design. The second phase are choosing the subject that will be designed as the subject of presentation. The third stage is designing presentation model. And the fourth phase is collecting materials of the subject that will be presented by each lecturer.

  5. Economic model of a cloud provider operating in a federated cloud

    OpenAIRE

    Goiri Presa, Íñigo; Guitart Fernández, Jordi; Torres Viñals, Jordi

    2012-01-01

    Resource provisioning in Cloud providers is a challenge because of the high variability of load over time. On the one hand, the providers can serve most of the requests owning only a restricted amount of resources, but this forces to reject customers during peak hours. On the other hand, valley hours incur in under-utilization of the resources, which forces the providers to increase their prices to be profitable. Federation overcomes these limitations and allows pro...

  6. A Unified Model of Cloud-to-Ground Lightning Stroke

    Science.gov (United States)

    Nag, A.; Rakov, V. A.

    2014-12-01

    The first stroke in a cloud-to-ground lightning discharge is thought to follow (or be initiated by) the preliminary breakdown process which often produces a train of relatively large microsecond-scale electric field pulses. This process is poorly understood and rarely modeled. Each lightning stroke is composed of a downward leader process and an upward return-stroke process, which are usually modeled separately. We present a unified engineering model for computing the electric field produced by a sequence of preliminary breakdown, stepped leader, and return stroke processes, serving to transport negative charge to ground. We assume that a negatively-charged channel extends downward in a stepped fashion through the relatively-high-field region between the main negative and lower positive charge centers and then through the relatively-low-field region below the lower positive charge center. A relatively-high-field region is also assumed to exist near ground. The preliminary breakdown pulse train is assumed to be generated when the negatively-charged channel interacts with the lower positive charge region. At each step, an equivalent current source is activated at the lower extremity of the channel, resulting in a step current wave that propagates upward along the channel. The leader deposits net negative charge onto the channel. Once the stepped leader attaches to ground (upward connecting leader is presently neglected), an upward-propagating return stroke is initiated, which neutralizes the charge deposited by the leader along the channel. We examine the effect of various model parameters, such as step length and current propagation speed, on model-predicted electric fields. We also compare the computed fields with pertinent measurements available in the literature.

  7. Aerosol-cloud interactions in a multi-scale modeling framework

    Science.gov (United States)

    Lin, G.; Ghan, S. J.

    2017-12-01

    Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the

  8. Collaborative Cloud Manufacturing: Design of Business Model Innovations Enabled by Cyberphysical Systems in Distributed Manufacturing Systems

    Directory of Open Access Journals (Sweden)

    Erwin Rauch

    2016-01-01

    Full Text Available Collaborative cloud manufacturing, as a concept of distributed manufacturing, allows different opportunities for changing the logic of generating and capturing value. Cyberphysical systems and the technologies behind them are the enablers for new business models which have the potential to be disruptive. This paper introduces the topics of distributed manufacturing as well as cyberphysical systems. Furthermore, the main business model clusters of distributed manufacturing systems are described, including collaborative cloud manufacturing. The paper aims to provide support for developing business model innovations based on collaborative cloud manufacturing. Therefore, three business model architecture types of a differentiated business logic are discussed, taking into consideration the parameters which have an influence and the design of the business model and its architecture. As a result, new business models can be developed systematically and new ideas can be generated to boost the concept of collaborative cloud manufacturing within all sustainable business models.

  9. Coupling spectral-bin cloud microphysics with the MOSAIC aerosol model in WRF-Chem: Methodology and results for marine stratocumulus clouds

    Science.gov (United States)

    Gao, Wenhua; Fan, Jiwen; Easter, R. C.; Yang, Qing; Zhao, Chun; Ghan, Steven J.

    2016-09-01

    Aerosol-cloud interaction processes can be represented more physically with bin cloud microphysics relative to bulk microphysical parameterizations. However, due to computational power limitations in the past, bin cloud microphysics was often run with very simple aerosol treatments. The purpose of this study is to represent better aerosol-cloud interaction processes in the Chemistry version of Weather Research and Forecast model (WRF-Chem) at convection-permitting scales by coupling spectral-bin cloud microphysics (SBM) with the MOSAIC sectional aerosol model. A flexible interface is built that exchanges cloud and aerosol information between them. The interface contains a new bin aerosol activation approach, which replaces the treatments in the original SBM. It also includes the modified aerosol resuspension and in-cloud wet removal processes with the droplet loss tendencies and precipitation fluxes from SBM. The newly coupled system is evaluated for two marine stratocumulus cases over the Southeast Pacific Ocean with either a simplified aerosol setup or full-chemistry. We compare the aerosol activation process in the newly coupled SBM-MOSAIC against the SBM simulation without chemistry using a simplified aerosol setup, and the results show consistent activation rates. A longer time simulation reinforces that aerosol resuspension through cloud drop evaporation plays an important role in replenishing aerosols and impacts cloud and precipitation in marine stratocumulus clouds. Evaluation of the coupled SBM-MOSAIC with full-chemistry using aircraft measurements suggests that the new model works realistically for the marine stratocumulus clouds, and improves the simulation of cloud microphysical properties compared to a simulation using MOSAIC coupled with the Morrison two-moment microphysics.

  10. Microphysical Modeling of Mineral Clouds in GJ1214 b and GJ436 b: Predicting Upper Limits on the Cloud-top Height

    Science.gov (United States)

    Ohno, Kazumasa; Okuzumi, Satoshi

    2018-05-01

    The ubiquity of clouds in the atmospheres of exoplanets, especially of super-Earths, is one of the outstanding issues for the transmission spectra survey. Understanding the formation process of clouds in super-Earths is necessary to interpret the observed spectra correctly. In this study, we investigate the vertical distributions of particle size and mass density of mineral clouds in super-Earths using a microphysical model that takes into account the vertical transport and growth of cloud particles in a self-consistent manner. We demonstrate that the vertical profiles of mineral clouds significantly vary with the concentration of cloud condensation nuclei and atmospheric metallicity. We find that the height of the cloud top increases with increasing metallicity as long as the metallicity is lower than the threshold. If the metallicity is larger than the threshold, the cloud-top height no longer increases appreciably with metallicity because coalescence yields larger particles of higher settling velocities. We apply our cloud model to GJ1214 b and GJ436 b, for which recent transmission observations suggest the presence of high-altitude opaque clouds. For GJ436 b, we show that KCl particles can ascend high enough to explain the observation. For GJ1214 b, by contrast, the height of KCl clouds predicted from our model is too low to explain its flat transmission spectrum. Clouds made of highly porous KCl particles could explain the observations if the atmosphere is highly metal-rich, and hence the particle microstructure might be a key to interpret the flat spectrum of GJ1214 b.

  11. Remote Sensing of Radiative and Microphysical Properties of Clouds During TC (sup 4): Results from MAS, MASTER, MODIS, and MISR

    Science.gov (United States)

    King, Michael D.; Platnick, Steven; Wind, Galina; Arnold, G. Thomas; Dominguez, Roseanne T.

    2010-01-01

    The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

  12. Reconstruction of Consistent 3d CAD Models from Point Cloud Data Using a Priori CAD Models

    Science.gov (United States)

    Bey, A.; Chaine, R.; Marc, R.; Thibault, G.; Akkouche, S.

    2011-09-01

    We address the reconstruction of 3D CAD models from point cloud data acquired in industrial environments, using a pre-existing 3D model as an initial estimate of the scene to be processed. Indeed, this prior knowledge can be used to drive the reconstruction so as to generate an accurate 3D model matching the point cloud. We more particularly focus our work on the cylindrical parts of the 3D models. We propose to state the problem in a probabilistic framework: we have to search for the 3D model which maximizes some probability taking several constraints into account, such as the relevancy with respect to the point cloud and the a priori 3D model, and the consistency of the reconstructed model. The resulting optimization problem can then be handled using a stochastic exploration of the solution space, based on the random insertion of elements in the configuration under construction, coupled with a greedy management of the conflicts which efficiently improves the configuration at each step. We show that this approach provides reliable reconstructed 3D models by presenting some results on industrial data sets.

  13. Evaluation and Improvement of Cloud and Convective Parameterizations from Analyses of ARM Observations and Models

    Energy Technology Data Exchange (ETDEWEB)

    Del Genio, Anthony D. [NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)

    2016-03-11

    Over this period the PI and his performed a broad range of data analysis, model evaluation, and model improvement studies using ARM data. These included cloud regimes in the TWP and their evolution over the MJO; M-PACE IOP SCM-CRM intercomparisons; simulations of convective updraft strength and depth during TWP-ICE; evaluation of convective entrainment parameterizations using TWP-ICE simulations; evaluation of GISS GCM cloud behavior vs. long-term SGP cloud statistics; classification of aerosol semi-direct effects on cloud cover; depolarization lidar constraints on cloud phase; preferred states of the winter Arctic atmosphere, surface, and sub-surface; sensitivity of convection to tropospheric humidity; constraints on the parameterization of mesoscale organization from TWP-ICE WRF simulations; updraft and downdraft properties in TWP-ICE simulated convection; insights from long-term ARM records at Manus and Nauru.

  14. Reconciliation of the cloud computing model with US federal electronic health record regulations.

    Science.gov (United States)

    Schweitzer, Eugene J

    2012-01-01

    Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing.

  15. Reconciliation of the cloud computing model with US federal electronic health record regulations

    Science.gov (United States)

    2011-01-01

    Cloud computing refers to subscription-based, fee-for-service utilization of computer hardware and software over the Internet. The model is gaining acceptance for business information technology (IT) applications because it allows capacity and functionality to increase on the fly without major investment in infrastructure, personnel or licensing fees. Large IT investments can be converted to a series of smaller operating expenses. Cloud architectures could potentially be superior to traditional electronic health record (EHR) designs in terms of economy, efficiency and utility. A central issue for EHR developers in the US is that these systems are constrained by federal regulatory legislation and oversight. These laws focus on security and privacy, which are well-recognized challenges for cloud computing systems in general. EHRs built with the cloud computing model can achieve acceptable privacy and security through business associate contracts with cloud providers that specify compliance requirements, performance metrics and liability sharing. PMID:21727204

  16. Biomimicry of quorum sensing using bacterial lifecycle model.

    Science.gov (United States)

    Niu, Ben; Wang, Hong; Duan, Qiqi; Li, Li

    2013-01-01

    Recent microbiologic studies have shown that quorum sensing mechanisms, which serve as one of the fundamental requirements for bacterial survival, exist widely in bacterial intra- and inter-species cell-cell communication. Many simulation models, inspired by the social behavior of natural organisms, are presented to provide new approaches for solving realistic optimization problems. Most of these simulation models follow population-based modelling approaches, where all the individuals are updated according to the same rules. Therefore, it is difficult to maintain the diversity of the population. In this paper, we present a computational model termed LCM-QS, which simulates the bacterial quorum-sensing (QS) mechanism using an individual-based modelling approach under the framework of Agent-Environment-Rule (AER) scheme, i.e. bacterial lifecycle model (LCM). LCM-QS model can be classified into three main sub-models: chemotaxis with QS sub-model, reproduction and elimination sub-model and migration sub-model. The proposed model is used to not only imitate the bacterial evolution process at the single-cell level, but also concentrate on the study of bacterial macroscopic behaviour. Comparative experiments under four different scenarios have been conducted in an artificial 3-D environment with nutrients and noxious distribution. Detailed study on bacterial chemotatic processes with quorum sensing and without quorum sensing are compared. By using quorum sensing mechanisms, artificial bacteria working together can find the nutrient concentration (or global optimum) quickly in the artificial environment. Biomimicry of quorum sensing mechanisms using the lifecycle model allows the artificial bacteria endowed with the communication abilities, which are essential to obtain more valuable information to guide their search cooperatively towards the preferred nutrient concentrations. It can also provide an inspiration for designing new swarm intelligence optimization algorithms

  17. An Incremental Model for Cloud Adoption: Based on a Study of Regional Organizations

    Directory of Open Access Journals (Sweden)

    Emre Erturk

    2017-11-01

    Full Text Available Many organizations that use cloud computing services intend to increase this commitment. A survey was distributed to organizations in Hawke’s Bay, New Zealand to understand their adoption of cloud solutions, in comparison with global trends and practices. The survey also included questions on the benefits and challenges, and which delivery model(s they have adopted and are planning to adopt. One aim is to contribute to the cloud computing literature and build on the existing adoption models. This study also highlights additional aspects applicable to various organizations (small, medium, large and regional. Finally, recommendations are provided for related future research projects.

  18. Using satellites and global models to investigate aerosol-cloud interactions

    Science.gov (United States)

    Gryspeerdt, E.; Quaas, J.; Goren, T.; Sourdeval, O.; Mülmenstädt, J.

    2017-12-01

    Aerosols are known to impact liquid cloud properties, through both microphysical and radiative processes. Increasing the number concentration of aerosol particles can increase the cloud droplet number concentration (CDNC). Through impacts on precipitation processes, this increase in CDNC may also be able to impact the cloud fraction (CF) and the cloud liquid water path (LWP). Several studies have looked into the effect of aerosols on the CDNC, but as the albedo of a cloudy scene depends much more strongly on LWP and CF, an aerosol influence on these properties could generate a significant radiative forcing. While the impact of aerosols on cloud properties can be seen in case studies involving shiptracks and volcanoes, producing a global estimate of these effects remains challenging due to the confounding effect of local meteorology. For example, relative humidity significantly impacts the aerosol optical depth (AOD), a common satellite proxy for CCN, as well as being a strong control on cloud properties. This can generate relationships between AOD and cloud properties, even when there is no impact of aerosol-cloud interactions. In this work, we look at how aerosol-cloud interactions can be distinguished from the effect of local meteorology in satellite studies. With a combination global climate models and multiple sources of satellite data, we show that the choice of appropriate mediating variables and case studies can be used to develop constraints on the aerosol impact on CF and LWP. This will lead to improved representations of clouds in global climate models and help to reduce the uncertainty in the global impact of anthropogenic aerosols on cloud properties.

  19. Global model comparison of heterogeneous ice nucleation parameterizations in mixed phase clouds

    Science.gov (United States)

    Yun, Yuxing; Penner, Joyce E.

    2012-04-01

    A new aerosol-dependent mixed phase cloud parameterization for deposition/condensation/immersion (DCI) ice nucleation and one for contact freezing are compared to the original formulations in a coupled general circulation model and aerosol transport model. The present-day cloud liquid and ice water fields and cloud radiative forcing are analyzed and compared to observations. The new DCI freezing parameterization changes the spatial distribution of the cloud water field. Significant changes are found in the cloud ice water fraction and in the middle cloud fractions. The new DCI freezing parameterization predicts less ice water path (IWP) than the original formulation, especially in the Southern Hemisphere. The smaller IWP leads to a less efficient Bergeron-Findeisen process resulting in a larger liquid water path, shortwave cloud forcing, and longwave cloud forcing. It is found that contact freezing parameterizations have a greater impact on the cloud water field and radiative forcing than the two DCI freezing parameterizations that we compared. The net solar flux at top of atmosphere and net longwave flux at the top of the atmosphere change by up to 8.73 and 3.52 W m-2, respectively, due to the use of different DCI and contact freezing parameterizations in mixed phase clouds. The total climate forcing from anthropogenic black carbon/organic matter in mixed phase clouds is estimated to be 0.16-0.93 W m-2using the aerosol-dependent parameterizations. A sensitivity test with contact ice nuclei concentration in the original parameterization fit to that recommended by Young (1974) gives results that are closer to the new contact freezing parameterization.

  20. Cloud ice: A climate model challenge with signs and expectations of progress

    Science.gov (United States)

    Waliser, Duane E.; Li, Jui-Lin F.; Woods, Christopher P.; Austin, Richard T.; Bacmeister, Julio; Chern, Jiundar; Del Genio, Anthony; Jiang, Jonathan H.; Kuang, Zhiming; Meng, Huan; Minnis, Patrick; Platnick, Steve; Rossow, William B.; Stephens, Graeme L.; Sun-Mack, Szedung; Tao, Wei-Kuo; Tompkins, Adrian M.; Vane, Deborah G.; Walker, Christopher; Wu, Dong

    2009-04-01

    Present-day shortcomings in the representation of upper tropospheric ice clouds in general circulation models (GCMs) lead to errors in weather and climate forecasts as well as account for a source of uncertainty in climate change projections. An ongoing challenge in rectifying these shortcomings has been the availability of adequate, high-quality, global observations targeting ice clouds and related precipitating hydrometeors. In addition, the inadequacy of the modeled physics and the often disjointed nature between model representation and the characteristics of the retrieved/observed values have hampered GCM development and validation efforts from making effective use of the measurements that have been available. Thus, even though parameterizations in GCMs accounting for cloud ice processes have, in some cases, become more sophisticated in recent years, this development has largely occurred independently of the global-scale measurements. With the relatively recent addition of satellite-derived products from Aura/Microwave Limb Sounder (MLS) and CloudSat, there are now considerably more resources with new and unique capabilities to evaluate GCMs. In this article, we illustrate the shortcomings evident in model representations of cloud ice through a comparison of the simulations assessed in the Intergovernmental Panel on Climate Change Fourth Assessment Report, briefly discuss the range of global observational resources that are available, and describe the essential components of the model parameterizations that characterize their "cloud" ice and related fields. Using this information as background, we (1) discuss some of the main considerations and cautions that must be taken into account in making model-data comparisons related to cloud ice, (2) illustrate present progress and uncertainties in applying satellite cloud ice (namely from MLS and CloudSat) to model diagnosis, (3) show some indications of model improvements, and finally (4) discuss a number of

  1. Photoionization modeling of Magellanic Cloud planetary nebulae. I

    Science.gov (United States)

    Dopita, M. A.; Meatheringham, S. J.

    1991-01-01

    The results of self-consistent photoionization modeling of 38 Magellanic Cloud PNe are presented and used to construct an H-R diagram for the central stars and to obtain both the nebular chemical abundances and the physical parameters of the nebulae. T(eff)s derived from nebular excitation analysis are in agreement with temperatures derived by the classical Zanstra method. There is a linear correlation between log T(eff) and the excitation class. The majority of the central stars in the sample with optically thick nebulae have masses between 0.55 and 0.7 solar mass and are observed during their hydrogen-burning excursion toward high temperatures. Optically thin objects are found scattered throughout the H-R diagram, but tend to have a somewhat smaller mean mass. Type I PN are found to have high core masses and to lie on the descending branch of the evolutionary tracks. The nebular mass of the optically thick objects is closely related to the nebular radius, and PN with nebular masses over one solar are observed.

  2. Design Thinking and Cloud Manufacturing: A Study of Cloud Model Sharing Platform Based on Separated Data Log

    Directory of Open Access Journals (Sweden)

    Zhe Wei

    2013-01-01

    Full Text Available To solve the product data consistency problem which is caused by the portable system that cannot conduct real-time update of product data in mobile environment under the mass customization production mode, a new product data optimistic replication method based on log is presented. This paper focuses on the design thinking provider, probing into a manufacturing resource design thinking cloud platform based on manufacturing resource-locating technologies, and also discuss several application scenarios of cloud locating technologies in the manufacturing environment. The actual demand of manufacturing creates a new mode which is service-oriented and has high efficiency and low consumption. Finally, they are different from the crowd-sourcing application model of Local-Motors. The sharing platform operator is responsible for a master plan for the platform, proposing a open interface standard and establishing a service operation mode.

  3. A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

    Science.gov (United States)

    Hagos, Samson; Feng, Zhe; Plant, Robert S.; Houze, Robert A.; Xiao, Heng

    2018-02-01

    A stochastic prognostic framework for modeling the population dynamics of convective clouds and representing them in climate models is proposed. The framework follows the nonequilibrium statistical mechanical approach to constructing a master equation for representing the evolution of the number of convective cells of a specific size and their associated cloud-base mass flux, given a large-scale forcing. In this framework, referred to as STOchastic framework for Modeling Population dynamics of convective clouds (STOMP), the evolution of convective cell size is predicted from three key characteristics of convective cells: (i) the probability of growth, (ii) the probability of decay, and (iii) the cloud-base mass flux. STOMP models are constructed and evaluated against CPOL radar observations at Darwin and convection permitting model (CPM) simulations. Multiple models are constructed under various assumptions regarding these three key parameters and the realisms of these models are evaluated. It is shown that in a model where convective plumes prefer to aggregate spatially and the cloud-base mass flux is a nonlinear function of convective cell area, the mass flux manifests a recharge-discharge behavior under steady forcing. Such a model also produces observed behavior of convective cell populations and CPM simulated cloud-base mass flux variability under diurnally varying forcing. In addition to its use in developing understanding of convection processes and the controls on convective cell size distributions, this modeling framework is also designed to serve as a nonequilibrium closure formulations for spectral mass flux parameterizations.

  4. Analysis and Research on Spatial Data Storage Model Based on Cloud Computing Platform

    Science.gov (United States)

    Hu, Yong

    2017-12-01

    In this paper, the data processing and storage characteristics of cloud computing are analyzed and studied. On this basis, a cloud computing data storage model based on BP neural network is proposed. In this data storage model, it can carry out the choice of server cluster according to the different attributes of the data, so as to complete the spatial data storage model with load balancing function, and have certain feasibility and application advantages.

  5. flexCloud: Deployment of the FLEXPART Atmospheric Transport Model as a Cloud SaaS Environment

    Science.gov (United States)

    Morton, Don; Arnold, Dèlia

    2014-05-01

    FLEXPART (FLEXible PARTicle dispersion model) is a Lagrangian transport and dispersion model used by a growing international community. We have used it to simulate and forecast the atmospheric transport of wildfire smoke, volcanic ash and radionuclides. Additionally, FLEXPART may be run in backwards mode to provide information for the determination of emission sources such as nuclear emissions and greenhouse gases. This open source software is distributed in source code form, and has several compiler and library dependencies that users need to address. Although well-documented, getting it compiled, set up, running, and post-processed is often tedious, making it difficult for the inexperienced user. Our interest is in moving scientific modeling and simulation activities from site-specific clusters and supercomputers to a cloud model as a service paradigm. Choosing FLEXPART for our prototyping, our vision is to construct customised IaaS images containing fully-compiled and configured FLEXPART codes, including pre-processing, execution and postprocessing components. In addition, with the inclusion of a small web server in the image, we introduce a web-accessible graphical user interface that drives the system. A further initiative being pursued is the deployment of multiple, simultaneous FLEXPART ensembles in the cloud. A single front-end web interface is used to define the ensemble members, and separate cloud instances are launched, on-demand, to run the individual models and to conglomerate the outputs into a unified display. The outcome of this work is a Software as a Service (Saas) deployment whereby the details of the underlying modeling systems are hidden, allowing modelers to perform their science activities without the burden of considering implementation details.

  6. Tropical Oceanic Precipitation Processes Over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

    Science.gov (United States)

    Tao, W.-K.; Johnson, D.; Simpson, J.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.

  7. Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

    Science.gov (United States)

    Pan, Yuchen; Ding, Shuai; Fan, Wenjuan; Li, Jing; Yang, Shanlin

    2015-01-01

    Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard's Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments.

  8. A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation

    Science.gov (United States)

    Gleason, Colin J.; Wada, Yoshihide; Wang, Jida

    2018-01-01

    Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modeling are frequently cited as potential solutions, but these techniques largely rely on these same in-decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at-many-stations hydraulic geometry (AMHG) and the PCR-GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984-2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modeled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978-1984) yields an RMSE of 439 m3/s (40.8%). By contrast, the original simulation had an order-of-magnitude flow error. This improvement is substantial but not perfect: tuned flows have a 1-2 month wet season lag and a negative base flow bias. Accounting for this 2 month lag yields a hydrograph RMSE of 270 m3/s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modeling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water.

  9. Cloud processing of gases and aerosols in the Community Multiscale Air Quality (CMAQ) model: Impacts of extended chemistry

    Science.gov (United States)

    Clouds and fogs can significantly impact the concentration and distribution of atmospheric gases and aerosols through chemistry, scavenging, and transport. This presentation summarizes the representation of cloud processes in the Community Multiscale Air Quality (CMAQ) modeling ...

  10. Removal of clouds, dust and shadow pixels from hyperspectral imagery using a non-separable and stationary spatio-temporal covariance model

    KAUST Repository

    Angel, Yoseline

    2016-10-25

    Hyperspectral remote sensing images are usually affected by atmospheric conditions such as clouds and their shadows, which represents a contamination of reflectance data and complicates the extraction of biophysical variables to monitor phenological cycles of crops. This paper explores a cloud removal approach based on reflectance prediction using multitemporal data and spatio-Temporal statistical models. In particular, a covariance model that captures the behavior of spatial and temporal components in data simultaneously (i.e. non-separable) is considered. Eight weekly images collected from the Hyperion hyper-spectrometer instrument over an agricultural region of Saudi Arabia were used to reconstruct a scene with the presence of cloudy affected pixels over a center-pivot crop. A subset of reflectance values of cloud-free pixels from 50 bands in the spectral range from 426.82 to 884.7 nm at each date, were used as input to fit a parametric family of non-separable and stationary spatio-Temporal covariance functions. Applying simple kriging as an interpolator, cloud affected pixels were replaced by cloud-free predicted values per band, obtaining their respective predicted spectral profiles at the same time. An exercise of reconstructing simulated cloudy pixels in a different swath was conducted to assess the model accuracy, achieving root mean square error (RMSE) values per band less than or equal to 3%. The spatial coherence of the results was also checked through absolute error distribution maps demonstrating their consistency.

  11. Removal of clouds, dust and shadow pixels from hyperspectral imagery using a non-separable and stationary spatio-temporal covariance model

    KAUST Repository

    Angel, Yoseline; Houborg, Rasmus; McCabe, Matthew

    2016-01-01

    Hyperspectral remote sensing images are usually affected by atmospheric conditions such as clouds and their shadows, which represents a contamination of reflectance data and complicates the extraction of biophysical variables to monitor phenological cycles of crops. This paper explores a cloud removal approach based on reflectance prediction using multi-temporal data and spatio-temporal statistical models. In particular, a covariance model that captures the behavior of spatial and temporal components in data simultaneously (i.e. non-separable) is considered. Eight weekly images collected from the Hyperion hyper-spectrometer instrument over an agricultural region of Saudi Arabia were used to reconstruct a scene with the presence of cloudy affected pixels over a center-pivot crop. A subset of reflectance values of cloud-free pixels from 50 bands in the spectral range from 426.82 to 884.7 nm at each date, were used as input to fit a parametric family of non-separable and stationary spatio-temporal covariance functions. Applying simple kriging as an interpolator, cloud affected pixels were replaced by cloud-free predicted values per band, obtaining their respective predicted spectral profiles at the same time. An exercise of reconstructing simulated cloudy pixels in a different swath was conducted to assess the model accuracy, achieving root mean square error (RMSE) values per band less than or equal to 3%. The spatial coherence of the results was also checked through absolute error distribution maps demonstrating their consistency.

  12. Removal of clouds, dust and shadow pixels from hyperspectral imagery using a non-separable and stationary spatio-temporal covariance model

    Science.gov (United States)

    Angel, Yoseline; Houborg, Rasmus; McCabe, Matthew F.

    2016-10-01

    Hyperspectral remote sensing images are usually affected by atmospheric conditions such as clouds and their shadows, which represents a contamination of reflectance data and complicates the extraction of biophysical variables to monitor phenological cycles of crops. This paper explores a cloud removal approach based on reflectance prediction using multitemporal data and spatio-temporal statistical models. In particular, a covariance model that captures the behavior of spatial and temporal components in data simultaneously (i.e. non-separable) is considered. Eight weekly images collected from the Hyperion hyper-spectrometer instrument over an agricultural region of Saudi Arabia were used to reconstruct a scene with the presence of cloudy affected pixels over a center-pivot crop. A subset of reflectance values of cloud-free pixels from 50 bands in the spectral range from 426.82 to 884.7 nm at each date, were used as input to fit a parametric family of non-separable and stationary spatio-temporal covariance functions. Applying simple kriging as an interpolator, cloud affected pixels were replaced by cloud-free predicted values per band, obtaining their respective predicted spectral profiles at the same time. An exercise of reconstructing simulated cloudy pixels in a different swath was conducted to assess the model accuracy, achieving root mean square error (RMSE) values per band less than or equal to 3%. The spatial coherence of the results was also checked through absolute error distribution maps demonstrating their consistency.

  13. Removal of clouds, dust and shadow pixels from hyperspectral imagery using a non-separable and stationary spatio-temporal covariance model

    KAUST Repository

    Angel, Yoseline

    2016-09-26

    Hyperspectral remote sensing images are usually affected by atmospheric conditions such as clouds and their shadows, which represents a contamination of reflectance data and complicates the extraction of biophysical variables to monitor phenological cycles of crops. This paper explores a cloud removal approach based on reflectance prediction using multi-temporal data and spatio-temporal statistical models. In particular, a covariance model that captures the behavior of spatial and temporal components in data simultaneously (i.e. non-separable) is considered. Eight weekly images collected from the Hyperion hyper-spectrometer instrument over an agricultural region of Saudi Arabia were used to reconstruct a scene with the presence of cloudy affected pixels over a center-pivot crop. A subset of reflectance values of cloud-free pixels from 50 bands in the spectral range from 426.82 to 884.7 nm at each date, were used as input to fit a parametric family of non-separable and stationary spatio-temporal covariance functions. Applying simple kriging as an interpolator, cloud affected pixels were replaced by cloud-free predicted values per band, obtaining their respective predicted spectral profiles at the same time. An exercise of reconstructing simulated cloudy pixels in a different swath was conducted to assess the model accuracy, achieving root mean square error (RMSE) values per band less than or equal to 3%. The spatial coherence of the results was also checked through absolute error distribution maps demonstrating their consistency.

  14. A FAST METHOD FOR MEASURING THE SIMILARITY BETWEEN 3D MODEL AND 3D POINT CLOUD

    Directory of Open Access Journals (Sweden)

    Z. Zhang

    2016-06-01

    Full Text Available This paper proposes a fast method for measuring the partial Similarity between 3D Model and 3D point Cloud (SimMC. It is crucial to measure SimMC for many point cloud-related applications such as 3D object retrieval and inverse procedural modelling. In our proposed method, the surface area of model and the Distance from Model to point Cloud (DistMC are exploited as measurements to calculate SimMC. Here, DistMC is defined as the weighted distance of the distances between points sampled from model and point cloud. Similarly, Distance from point Cloud to Model (DistCM is defined as the average distance of the distances between points in point cloud and model. In order to reduce huge computational burdens brought by calculation of DistCM in some traditional methods, we define SimMC as the ratio of weighted surface area of model to DistMC. Compared to those traditional SimMC measuring methods that are only able to measure global similarity, our method is capable of measuring partial similarity by employing distance-weighted strategy. Moreover, our method is able to be faster than other partial similarity assessment methods. We demonstrate the superiority of our method both on synthetic data and laser scanning data.

  15. Clouds-radiation interactions in a general circulation model - Impact upon the planetary radiation balance

    Science.gov (United States)

    Smith, Laura D.; Vonder Haar, Thomas H.

    1991-01-01

    Simultaneously conducted observations of the earth radiation budget and the cloud amount estimates, taken during the June 1979 - May 1980 Nimbus 7 mission were used to show interactions between the cloud amount and raidation and to verify a long-term climate simulation obtained with the latest version of the NCAR Community Climate Model (CCM). The parameterization of the radiative, dynamic, and thermodynamic processes produced the mean radiation and cloud quantities that were in reasonable agreement with satellite observations, but at the expense of simulating their short-term fluctuations. The results support the assumption that the inclusion of the cloud liquid water (ice) variable would be the best mean to reduce the blinking of clouds in NCAR CCM.

  16. Applications integration in a hybrid cloud computing environment: modelling and platform

    Science.gov (United States)

    Li, Qing; Wang, Ze-yuan; Li, Wei-hua; Li, Jun; Wang, Cheng; Du, Rui-yang

    2013-08-01

    With the development of application services providers and cloud computing, more and more small- and medium-sized business enterprises use software services and even infrastructure services provided by professional information service companies to replace all or part of their information systems (ISs). These information service companies provide applications, such as data storage, computing processes, document sharing and even management information system services as public resources to support the business process management of their customers. However, no cloud computing service vendor can satisfy the full functional IS requirements of an enterprise. As a result, enterprises often have to simultaneously use systems distributed in different clouds and their intra enterprise ISs. Thus, this article presents a framework to integrate applications deployed in public clouds and intra ISs. A run-time platform is developed and a cross-computing environment process modelling technique is also developed to improve the feasibility of ISs under hybrid cloud computing environments.

  17. Reliability Evaluation for the Surface to Air Missile Weapon Based on Cloud Model

    Directory of Open Access Journals (Sweden)

    Deng Jianjun

    2015-01-01

    Full Text Available The fuzziness and randomness is integrated by using digital characteristics, such as Expected value, Entropy and Hyper entropy. The cloud model adapted to reliability evaluation is put forward based on the concept of the surface to air missile weapon. The cloud scale of the qualitative evaluation is constructed, and the quantitative variable and the qualitative variable in the system reliability evaluation are corresponded. The practical calculation result shows that it is more effective to analyze the reliability of the surface to air missile weapon by this way. The practical calculation result also reflects the model expressed by cloud theory is more consistent with the human thinking style of uncertainty.

  18. Evaluating Cloud and Precipitation Processes in Numerical Models using Current and Potential Future Satellite Missions

    Science.gov (United States)

    van den Heever, S. C.; Tao, W. K.; Skofronick Jackson, G.; Tanelli, S.; L'Ecuyer, T. S.; Petersen, W. A.; Kummerow, C. D.

    2015-12-01

    Cloud, aerosol and precipitation processes play a fundamental role in the water and energy cycle. It is critical to accurately represent these microphysical processes in numerical models if we are to better predict cloud and precipitation properties on weather through climate timescales. Much has been learned about cloud properties and precipitation characteristics from NASA satellite missions such as TRMM, CloudSat, and more recently GPM. Furthermore, data from these missions have been successfully utilized in evaluating the microphysical schemes in cloud-resolving models (CRMs) and global models. However, there are still many uncertainties associated with these microphysics schemes. These uncertainties can be attributed, at least in part, to the fact that microphysical processes cannot be directly observed or measured, but instead have to be inferred from those cloud properties that can be measured. Evaluation of microphysical parameterizations are becoming increasingly important as enhanced computational capabilities are facilitating the use of more sophisticated schemes in CRMs, and as future global models are being run on what has traditionally been regarded as cloud-resolving scales using CRM microphysical schemes. In this talk we will demonstrate how TRMM, CloudSat and GPM data have been used to evaluate different aspects of current CRM microphysical schemes, providing examples of where these approaches have been successful. We will also highlight CRM microphysical processes that have not been well evaluated and suggest approaches for addressing such issues. Finally, we will introduce a potential NASA satellite mission, the Cloud and Precipitation Processes Mission (CAPPM), which would facilitate the development and evaluation of different microphysical-dynamical feedbacks in numerical models.

  19. Introducing Subrid-scale Cloud Feedbacks to Radiation for Regional Meteorological and Cllimate Modeling

    Science.gov (United States)

    Convection systems and associated cloudiness directly influence regional and local radiation budgets, and dynamics and thermodynamics through feedbacks. However, most subgrid-scale convective parameterizations in regional weather and climate models do not consider cumulus cloud ...

  20. Validating firn compaction model with remote sensing data

    DEFF Research Database (Denmark)

    Simonsen, S. B.; Stenseng, Lars; Sørensen, Louise Sandberg

    A comprehensive understanding of firn processes is of outmost importance, when estimating present and future changes of the Greenland Ice Sheet. Especially, when remote sensing altimetry is used to assess the state of ice sheets and their contribution to global sea level rise, firn compaction...... models have been shown to be a key component. Now, remote sensing data can also be used to validate the firn models. Radar penetrating the upper part of the firn column in the interior part of Greenland shows a clear layering. The observed layers from the radar data can be used as an in-situ validation...... correction relative to the changes in the elevation of the surface observed with remote sensing altimetry? What model time resolution is necessary to resolved the observed layering? What model refinements are necessary to give better estimates of the surface mass balance of the Greenland ice sheet from...

  1. PREVENTIVE SIGNATURE MODEL FOR SECURE CLOUD DEPLOYMENT THROUGH FUZZY DATA ARRAY COMPUTATION

    Directory of Open Access Journals (Sweden)

    R. Poorvadevi

    2017-01-01

    Full Text Available Cloud computing is a resource pool which offers boundless services by the form of resources to its end users whoever heavily depends on cloud service providers. Cloud is providing the service access across the geographic locations in an efficient way. However it is offering numerous services, client end system is not having adequate methods, security policies and other protocols for using the cloud customer secret level transactions and other privacy related information. So, this proposed model brings the solution for securing the cloud user confidential data, Application deployment and also identifying the genuineness of the user by applying the scheme which is referred as fuzzy data array computation. Fuzzy data array computation provides an effective system is called signature retrieval and evaluation system through which customer’s data can be safeguarded along with their application. This signature system can be implemented on the cloud environment using the cloud sim 3.0 simulator tools. It facilitates the security operation over the data centre and cloud vendor locations in an effective manner.

  2. Advancing cloud lifecycle representation in numerical models using innovative analysis methods that bridge arm observations over a breadth of scales

    Energy Technology Data Exchange (ETDEWEB)

    Tselioudis, George [Columbia Univ., New York, NY (United States)

    2016-03-04

    From its location on the subtropics-midlatitude boundary, the Azores is influenced by both the subtropical high pressure and the midlatitude baroclinic storm regimes, and therefore experiences a wide range of cloud structures, from fair-weather scenes to stratocumulus sheets to deep convective systems. This project combined three types of data sets to study cloud variability in the Azores: a satellite analysis of cloud regimes, a reanalysis characterization of storminess, and a 19-month field campaign that occurred on Graciosa Island. Combined analysis of the three data sets provides a detailed picture of cloud variability and the respective dynamic influences, with emphasis on low clouds that constitute a major uncertainty source in climate model simulations. The satellite cloud regime analysis shows that the Azores cloud distribution is similar to the mean global distribution and can therefore be used to evaluate cloud simulation in global models. Regime analysis of low clouds shows that stratocumulus decks occur under the influence of the Azores high-pressure system, while shallow cumulus clouds are sustained by cold-air outbreaks, as revealed by their preference for post-frontal environments and northwesterly flows. An evaluation of CMIP5 climate model cloud regimes over the Azores shows that all models severely underpredict shallow cumulus clouds, while most models also underpredict the occurrence of stratocumulus cloud decks. It is demonstrated that carefully selected case studies can be related through regime analysis to climatological cloud distributions, and a methodology is suggested utilizing process-resolving model simulations of individual cases to better understand cloud-dynamics interactions and attempt to explain and correct climate model cloud deficiencies.

  3. Clouds in ECMWF's 30 KM Resolution Global Atmospheric Forecast Model (TL639)

    Science.gov (United States)

    Cahalan, R. F.; Morcrette, J. J.

    1999-01-01

    Global models of the general circulation of the atmosphere resolve a wide range of length scales, and in particular cloud structures extend from planetary scales to the smallest scales resolvable, now down to 30 km in state-of-the-art models. Even the highest resolution models do not resolve small-scale cloud phenomena seen, for example, in Landsat and other high-resolution satellite images of clouds. Unresolved small-scale disturbances often grow into larger ones through non-linear processes that transfer energy upscale. Understanding upscale cascades is of crucial importance in predicting current weather, and in parameterizing cloud-radiative processes that control long term climate. Several movie animations provide examples of the temporal and spatial variation of cloud fields produced in 4-day runs of the forecast model at the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, England, at particular times and locations of simultaneous measurement field campaigns. model resolution is approximately 30 km horizontally (triangular truncation TL639) with 31 vertical levels from surface to stratosphere. Timestep of the model is about 10 minutes, but animation frames are 3 hours apart, at timesteps when the radiation is computed. The animations were prepared from an archive of several 4-day runs at the highest available model resolution, and archived at ECMWF. Cloud, wind and temperature fields in an approximately 1000 km X 1000 km box were retrieved from the archive, then approximately 60 Mb Vis5d files were prepared with the help of Graeme Kelly of ECMWF, and were compressed into MPEG files each less than 3 Mb. We discuss the interaction of clouds and radiation in the model, and compare the variability of cloud liquid as a function of scale to that seen in cloud observations made in intensive field campaigns. Comparison of high-resolution global runs to cloud-resolving models, and to lower resolution climate models is leading to better

  4. Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

    Science.gov (United States)

    Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan

    2018-05-01

    A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.

  5. A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes

    Science.gov (United States)

    Tao, Wei-Kuo

    2012-01-01

    During the past decade, numerical weather and global non-hydrostatic models have started using more complex microphysical schemes originally developed for high resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. These microphysical schemes affect the dynamic through the release of latent heat (buoyancy loading and pressure gradient) the radiation through the cloud coverage (vertical distribution of cloud species), and surface processes through rainfall (both amount and intensity). Recently, several major improvements of ice microphysical processes (or schemes) have been developed for cloud-resolving model (Goddard Cumulus Ensemble, GCE, model) and regional scale (Weather Research and Forecast, WRF) model. These improvements include an improved 3-ICE (cloud ice, snow and graupel) scheme (Lang et al. 2010); a 4-ICE (cloud ice, snow, graupel and hail) scheme and a spectral bin microphysics scheme and two different two-moment microphysics schemes. The performance of these schemes has been evaluated by using observational data from TRMM and other major field campaigns. In this talk, we will present the high-resolution (1 km) GeE and WRF model simulations and compared the simulated model results with observation from recent field campaigns [i.e., midlatitude continental spring season (MC3E; 2010), high latitude cold-season (C3VP, 2007; GCPEx, 2012), and tropical oceanic (TWP-ICE, 2006)].

  6. Research on Methods for Discovering and Selecting Cloud Infrastructure Services Based on Feature Modeling

    Directory of Open Access Journals (Sweden)

    Huamin Zhu

    2016-01-01

    Full Text Available Nowadays more and more cloud infrastructure service providers are providing large numbers of service instances which are a combination of diversified resources, such as computing, storage, and network. However, for cloud infrastructure services, the lack of a description standard and the inadequate research of systematic discovery and selection methods have exposed difficulties in discovering and choosing services for users. First, considering the highly configurable properties of a cloud infrastructure service, the feature model method is used to describe such a service. Second, based on the description of the cloud infrastructure service, a systematic discovery and selection method for cloud infrastructure services are proposed. The automatic analysis techniques of the feature model are introduced to verify the model’s validity and to perform the matching of the service and demand models. Finally, we determine the critical decision metrics and their corresponding measurement methods for cloud infrastructure services, where the subjective and objective weighting results are combined to determine the weights of the decision metrics. The best matching instances from various providers are then ranked by their comprehensive evaluations. Experimental results show that the proposed methods can effectively improve the accuracy and efficiency of cloud infrastructure service discovery and selection.

  7. Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking

    Directory of Open Access Journals (Sweden)

    Alireza Taravat

    2015-02-01

    Full Text Available A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data. It consists of a multi-layer perceptron with one hidden sigmoid layer, trained with the error back-propagation algorithm. The model is fed by six bands of MSG data (0.6, 0.8, 1.6, 3.9, 6.2 and 10.8 μm with 10 hidden nodes. The multiple-layer perceptrons lead to a cloud detection accuracy of 88.96%, when trained to map two predefined values that classify cloud and clear sky. The network was further evaluated using sixty MSG images taken at different dates. The network detected not only bright thick clouds but also thin or less bright clouds. The analysis demonstrated the feasibility of using machine learning models of cloud detection in MSG SEVIRI imagery.

  8. Providing a New Model for Discovering Cloud Services Based on Ontology

    Directory of Open Access Journals (Sweden)

    B. Heydari

    2017-12-01

    Full Text Available Due to its efficient, flexible, and dynamic substructure in information technology and service quality parameters estimation, cloud computing has become one of the most important issues in computer world. Discovering cloud services has been posed as a fundamental issue in reaching out high efficiency. In order to do one’s own operations in cloud space, any user needs to request several various services either simultaneously or according to a working routine. These services can be presented by different cloud producers or different decision-making policies. Therefore, service management is one of the important and challenging issues in cloud computing. With the advent of semantic web and practical services accordingly in cloud computing space, access to different kinds of applications has become possible. Ontology is the core of semantic web and can be used to ease the process of discovering services. A new model based on ontology has been proposed in this paper. The results indicate that the proposed model has explored cloud services based on user search results in lesser time compared to other models.

  9. Dynamical Model for the Zodiacal Cloud and Sporadic Meteors

    Science.gov (United States)

    Nesvorný, David; Janches, Diego; Vokrouhlický, David; Pokorný, Petr; Bottke, William F.; Jenniskens, Peter

    2011-12-01

    The solar system is dusty, and would become dustier over time as asteroids collide and comets disintegrate, except that small debris particles in interplanetary space do not last long. They can be ejected from the solar system by Jupiter, thermally destroyed near the Sun, or physically disrupted by collisions. Also, some are swept by the Earth (and other planets), producing meteors. Here we develop a dynamical model for the solar system meteoroids and use it to explain meteor radar observations. We find that the Jupiter Family Comets (JFCs) are the main source of the prominent concentrations of meteors arriving at the Earth from the helion and antihelion directions. To match the radiant and orbit distributions, as measured by the Canadian Meteor Orbit Radar (CMOR) and Advanced Meteor Orbit Radar (AMOR), our model implies that comets, and JFCs in particular, must frequently disintegrate when reaching orbits with low perihelion distance. Also, the collisional lifetimes of millimeter particles may be longer (gsim 105 yr at 1 AU) than postulated in the standard collisional models (~104 yr at 1 AU), perhaps because these chondrule-sized meteoroids are stronger than thought before. Using observations of the Infrared Astronomical Satellite to calibrate the model, we find that the total cross section and mass of small meteoroids in the inner solar system are (1.7-3.5) × 1011 km2 and ~4 × 1019 g, respectively, in a good agreement with previous studies. The mass input required to keep the zodiacal cloud in a steady state is estimated to be ~104-105 kg s-1. The input is up to ~10 times larger than found previously, mainly because particles released closer to the Sun have shorter collisional lifetimes and need to be supplied at a faster rate. The total mass accreted by the Earth in particles between diameters D = 5 μm and 1 cm is found to be ~15,000 tons yr-1 (factor of two uncertainty), which is a large share of the accretion flux measured by the Long Term Duration

  10. DYNAMICAL MODEL FOR THE ZODIACAL CLOUD AND SPORADIC METEORS

    International Nuclear Information System (INIS)

    Nesvorný, David; Vokrouhlický, David; Pokorný, Petr; Bottke, William F.; Janches, Diego; Jenniskens, Peter

    2011-01-01

    The solar system is dusty, and would become dustier over time as asteroids collide and comets disintegrate, except that small debris particles in interplanetary space do not last long. They can be ejected from the solar system by Jupiter, thermally destroyed near the Sun, or physically disrupted by collisions. Also, some are swept by the Earth (and other planets), producing meteors. Here we develop a dynamical model for the solar system meteoroids and use it to explain meteor radar observations. We find that the Jupiter Family Comets (JFCs) are the main source of the prominent concentrations of meteors arriving at the Earth from the helion and antihelion directions. To match the radiant and orbit distributions, as measured by the Canadian Meteor Orbit Radar (CMOR) and Advanced Meteor Orbit Radar (AMOR), our model implies that comets, and JFCs in particular, must frequently disintegrate when reaching orbits with low perihelion distance. Also, the collisional lifetimes of millimeter particles may be longer (∼> 10 5 yr at 1 AU) than postulated in the standard collisional models (∼10 4 yr at 1 AU), perhaps because these chondrule-sized meteoroids are stronger than thought before. Using observations of the Infrared Astronomical Satellite to calibrate the model, we find that the total cross section and mass of small meteoroids in the inner solar system are (1.7-3.5) × 10 11 km 2 and ∼4 × 10 19 g, respectively, in a good agreement with previous studies. The mass input required to keep the zodiacal cloud in a steady state is estimated to be ∼10 4 -10 5 kg s –1 . The input is up to ∼10 times larger than found previously, mainly because particles released closer to the Sun have shorter collisional lifetimes and need to be supplied at a faster rate. The total mass accreted by the Earth in particles between diameters D = 5 μm and 1 cm is found to be ∼15,000 tons yr –1 (factor of two uncertainty), which is a large share of the accretion flux measured by the

  11. Evaluation of stratocumulus cloud prediction in the Met Office forecast model during VOCALS-REx

    Directory of Open Access Journals (Sweden)

    S. J. Abel

    2010-11-01

    Full Text Available Observations in the subtropical southeast Pacific obtained during the VOCALS-REx field experiment are used to evaluate the representation of stratocumulus cloud in the Met Office forecast model and to identify key areas where model biases exist. Marked variations in the large scale structure of the cloud field were observed during the experiment on both day-to-day and on diurnal timescales. In the remote maritime region the model is shown to have a good representation of synoptically induced variability in both cloud cover and marine boundary layer depth. Satellite observations show a strong diurnal cycle in cloud fraction and liquid water path in the stratocumulus with enhanced clearances of the cloud deck along the Chilean and Peruvian coasts on certain days. The model accurately simulates the phase of the diurnal cycle but is unable to capture the coastal clearing of cloud. Observations along the 20° S latitude line show a gradual increase in the depth of the boundary layer away from the coast. This trend is well captured by the model (typical low bias of 200 m although significant errors exist at the coast where the model marine boundary layer is too shallow and moist. Drizzle in the model responds to changes in liquid water path in a manner that is consistent with previous ship-borne observations in the region although the intensity of this drizzle is likely to be too high, particularly in the more polluted coastal region where higher cloud droplet number concentrations are typical. Another mode of variability in the cloud field that the model is unable to capture are regions of pockets of open cellular convection embedded in the overcast stratocumulus deck and an example of such a feature that was sampled during VOCALS-REx is shown.

  12. Modeling study of cloud droplet nucleation and in-cloud sulfate production during the Sanitation of the Atmosphere (SANA) 2 campaign

    Science.gov (United States)

    Liu, Xiaohong; Seidl, Winfried

    1998-01-01

    Based upon the measurements of vertical profiles of gaseous SO2, H2O2, O3, and meteorological parameters from aircraft and of the aerosol chemical composition and gaseous NH3, HNO3, and SO2 at the surface in southeastern Germany (Melpitz) during the Sanitation of the Atmosphere (SANA) 2 campaign, realistic modeling of cloud droplet nucleation and in-cloud sulfate production was performed with an explicit microphysical cloud model with size-resolved chemistry and cloud top entrainment. For the fair weather cumulus observed during the measurements, the calculated cloud droplet number concentrations could be as high as 2000 cm-3 (and precloud aerosol sulfate up to 9.1 μg m-3), indicating strong sulfur pollution at Melpitz during the campaign. The in-cloud sulfate production is within 1.5-5.0 μg m-3, depending on the initial gaseous NH3 concentration in the parcel. This result shows the necessity of gaseous NH3 vertical profile measurements. Entrainment can reduce the cloud droplet number concentration and cause the distribution of in-cloud produced sulfate to shift toward larger particle sizes. Under the cases we studied, we do not find a significant effect of cloud top gaseous H2O2 entrainment on the in-cloud sulfate production. For the adiabatic cases the departure of bulk water H2O2 from the Henry's law equilibrium is very small. When entrainment included, however, bulk water H2O2 concentrations could be clearly less than the equilibrium values, and the deficiencies are higher (>20%) for droplets larger than 10 μm radius. Our results suggest that entrainment could be one of the important factors to account for the measured H2O2 deficiency in cloud water.

  13. Supervised Gaussian mixture model based remote sensing image ...

    African Journals Online (AJOL)

    Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test the Gaussian mixture model algorithm. For the purpose of validating the experiment, the resulting classified satellite image is compared with the ground truth data. For the simulated modelling, ...

  14. Cloud Forecasting and 3-D Radiative Transfer Model Validation using Citizen-Sourced Imagery

    Science.gov (United States)

    Gasiewski, A. J.; Heymsfield, A.; Newman Frey, K.; Davis, R.; Rapp, J.; Bansemer, A.; Coon, T.; Folsom, R.; Pfeufer, N.; Kalloor, J.

    2017-12-01

    Cloud radiative feedback mechanisms are one of the largest sources of uncertainty in global climate models. Variations in local 3D cloud structure impact the interpretation of NASA CERES and MODIS data for top-of-atmosphere radiation studies over clouds. Much of this uncertainty results from lack of knowledge of cloud vertical and horizontal structure. Surface-based data on 3-D cloud structure from a multi-sensor array of low-latency ground-based cameras can be used to intercompare radiative transfer models based on MODIS and other satellite data with CERES data to improve the 3-D cloud parameterizations. Closely related, forecasting of solar insolation and associated cloud cover on time scales out to 1 hour and with spatial resolution of 100 meters is valuable for stabilizing power grids with high solar photovoltaic penetrations. Data for cloud-advection based solar insolation forecasting with requisite spatial resolution and latency needed to predict high ramp rate events obtained from a bottom-up perspective is strongly correlated with cloud-induced fluctuations. The development of grid management practices for improved integration of renewable solar energy thus also benefits from a multi-sensor camera array. The data needs for both 3D cloud radiation modelling and solar forecasting are being addressed using a network of low-cost upward-looking visible light CCD sky cameras positioned at 2 km spacing over an area of 30-60 km in size acquiring imagery on 30 second intervals. Such cameras can be manufactured in quantity and deployed by citizen volunteers at a marginal cost of 200-400 and operated unattended using existing communications infrastructure. A trial phase to understand the potential utility of up-looking multi-sensor visible imagery is underway within this NASA Citizen Science project. To develop the initial data sets necessary to optimally design a multi-sensor cloud camera array a team of 100 citizen scientists using self-owned PDA cameras is being

  15. A model of the magnetosheath magnetic field during magnetic clouds

    Directory of Open Access Journals (Sweden)

    L. Turc

    2014-02-01

    Full Text Available Magnetic clouds (MCs are huge interplanetary structures which originate from the Sun and have a paramount importance in driving magnetospheric storms. Before reaching the magnetosphere, MCs interact with the Earth's bow shock. This may alter their structure and therefore modify their expected geoeffectivity. We develop a simple 3-D model of the magnetosheath adapted to MCs conditions. This model is the first to describe the interaction of MCs with the bow shock and their propagation inside the magnetosheath. We find that when the MC encounters the Earth centrally and with its axis perpendicular to the Sun–Earth line, the MC's magnetic structure remains mostly unchanged from the solar wind to the magnetosheath. In this case, the entire dayside magnetosheath is located downstream of a quasi-perpendicular bow shock. When the MC is encountered far from its centre, or when its axis has a large tilt towards the ecliptic plane, the MC's structure downstream of the bow shock differs significantly from that upstream. Moreover, the MC's structure also differs from one region of the magnetosheath to another and these differences vary with time and space as the MC passes by. In these cases, the bow shock configuration is mainly quasi-parallel. Strong magnetic field asymmetries arise in the magnetosheath; the sign of the magnetic field north–south component may change from the solar wind to some parts of the magnetosheath. We stress the importance of the Bx component. We estimate the regions where the magnetosheath and magnetospheric magnetic fields are anti-parallel at the magnetopause (i.e. favourable to reconnection. We find that the location of anti-parallel fields varies with time as the MCs move past Earth's environment, and that they may be situated near the subsolar region even for an initially northward magnetic field upstream of the bow shock. Our results point out the major role played by the bow shock configuration in modifying or keeping the

  16. Extraction and representation of common feature from uncertain facial expressions with cloud model.

    Science.gov (United States)

    Wang, Shuliang; Chi, Hehua; Yuan, Hanning; Geng, Jing

    2017-12-01

    Human facial expressions are key ingredient to convert an individual's innate emotion in communication. However, the variation of facial expressions affects the reliable identification of human emotions. In this paper, we present a cloud model to extract facial features for representing human emotion. First, the uncertainties in facial expression are analyzed in the context of cloud model. The feature extraction and representation algorithm is established under cloud generators. With forward cloud generator, facial expression images can be re-generated as many as we like for visually representing the extracted three features, and each feature shows different roles. The effectiveness of the computing model is tested on Japanese Female Facial Expression database. Three common features are extracted from seven facial expression images. Finally, the paper is concluded and remarked.

  17. A Comparison of Competing Models for Understanding Industrial Organization’s Acceptance of Cloud Services

    Directory of Open Access Journals (Sweden)

    Shui-Lien Chen

    2018-03-01

    Full Text Available Cloud computing is the next generation in computing, and the next natural step in the evolution of on-demand information technology services and products. However, only a few studies have addressed the adoption of cloud computing from an organizational perspective, which have not proven whether the research model is the best-fitting model. The purpose of this paper is to construct research competing models (RCMs and determine the best-fitting model for understanding industrial organization’s acceptance of cloud services. This research integrated the technology acceptance model and the principle of model parsimony to develop four cloud service adoption RCMs with enterprise usage intention being used as a proxy for actual behavior, and then compared the RCMs using structural equation modeling (SEM. Data derived from a questionnaire-based survey of 227 firms in Taiwan were tested against the relationships through SEM. Based on the empirical study, the results indicated that, although all four RCMs had a high goodness of fit, in both nested and non-nested structure comparisons, research competing model A (Model A demonstrated superior performance and was the best-fitting model. This study introduced a model development strategy that can most accurately explain and predict the behavioral intention of organizations to adopt cloud services.

  18. Assessing 1D Atmospheric Solar Radiative Transfer Models: Interpretation and Handling of Unresolved Clouds.

    Science.gov (United States)

    Barker, H. W.; Stephens, G. L.; Partain, P. T.; Bergman, J. W.; Bonnel, B.; Campana, K.; Clothiaux, E. E.; Clough, S.; Cusack, S.; Delamere, J.; Edwards, J.; Evans, K. F.; Fouquart, Y.; Freidenreich, S.; Galin, V.; Hou, Y.; Kato, S.; Li, J.;  Mlawer, E.;  Morcrette, J.-J.;  O'Hirok, W.;  Räisänen, P.;  Ramaswamy, V.;  Ritter, B.;  Rozanov, E.;  Schlesinger, M.;  Shibata, K.;  Sporyshev, P.;  Sun, Z.;  Wendisch, M.;  Wood, N.;  Yang, F.

    2003-08-01

    The primary purpose of this study is to assess the performance of 1D solar radiative transfer codes that are used currently both for research and in weather and climate models. Emphasis is on interpretation and handling of unresolved clouds. Answers are sought to the following questions: (i) How well do 1D solar codes interpret and handle columns of information pertaining to partly cloudy atmospheres? (ii) Regardless of the adequacy of their assumptions about unresolved clouds, do 1D solar codes perform as intended?One clear-sky and two plane-parallel, homogeneous (PPH) overcast cloud cases serve to elucidate 1D model differences due to varying treatments of gaseous transmittances, cloud optical properties, and basic radiative transfer. The remaining four cases involve 3D distributions of cloud water and water vapor as simulated by cloud-resolving models. Results for 25 1D codes, which included two line-by-line (LBL) models (clear and overcast only) and four 3D Monte Carlo (MC) photon transport algorithms, were submitted by 22 groups. Benchmark, domain-averaged irradiance profiles were computed by the MC codes. For the clear and overcast cases, all MC estimates of top-of-atmosphere albedo, atmospheric absorptance, and surface absorptance agree with one of the LBL codes to within ±2%. Most 1D codes underestimate atmospheric absorptance by typically 15-25 W m-2 at overhead sun for the standard tropical atmosphere regardless of clouds.Depending on assumptions about unresolved clouds, the 1D codes were partitioned into four genres: (i) horizontal variability, (ii) exact overlap of PPH clouds, (iii) maximum/random overlap of PPH clouds, and (iv) random overlap of PPH clouds. A single MC code was used to establish conditional benchmarks applicable to each genre, and all MC codes were used to establish the full 3D benchmarks. There is a tendency for 1D codes to cluster near their respective conditional benchmarks, though intragenre variances typically exceed those for

  19. Can CFMIP2 models reproduce the leading modes of cloud vertical structure in the CALIPSO-GOCCP observations?

    Science.gov (United States)

    Wang, Fang; Yang, Song

    2018-02-01

    Using principal component (PC) analysis, three leading modes of cloud vertical structure (CVS) are revealed by the GCM-Oriented CALIPSO Cloud Product (GOCCP), i.e. tropical high, subtropical anticyclonic and extratropical cyclonic cloud modes (THCM, SACM and ECCM, respectively). THCM mainly reflect the contrast between tropical high clouds and clouds in middle/high latitudes. SACM is closely associated with middle-high clouds in tropical convective cores, few-cloud regimes in subtropical anticyclonic clouds and stratocumulus over subtropical eastern oceans. ECCM mainly corresponds to clouds along extratropical cyclonic regions. Models of phase 2 of Cloud Feedback Model Intercomparison Project (CFMIP2) well reproduce the THCM, but SACM and ECCM are generally poorly simulated compared to GOCCP. Standardized PCs corresponding to CVS modes are generally captured, whereas original PCs (OPCs) are consistently underestimated (overestimated) for THCM (SACM and ECCM) by CFMIP2 models. The effects of CVS modes on relative cloud radiative forcing (RSCRF/RLCRF) (RSCRF being calculated at the surface while RLCRF at the top of atmosphere) are studied in terms of principal component regression method. Results show that CFMIP2 models tend to overestimate (underestimated or simulate the opposite sign) RSCRF/RLCRF radiative effects (REs) of ECCM (THCM and SACM) in unit global mean OPC compared to observations. These RE biases may be attributed to two factors, one of which is underestimation (overestimation) of low/middle clouds (high clouds) (also known as stronger (weaker) REs in unit low/middle (high) clouds) in simulated global mean cloud profiles, the other is eigenvector biases in CVS modes (especially for SACM and ECCM). It is suggested that much more attention should be paid on improvement of CVS, especially cloud parameterization associated with particular physical processes (e.g. downwelling regimes with the Hadley circulation, extratropical storm tracks and others), which

  20. Cloud diagnosis impact on deposition modelling applied to the Fukushima accident

    Science.gov (United States)

    Quérel, Arnaud; Quélo, Denis; Roustan, Yelva; Mathieu, Anne

    2017-04-01

    The accident at the Fukushima Daiichi Nuclear Power Plant in Japan in March 2011 resulted in the release of several hundred PBq of activity into the environment. Most of the radioactivity was released in a time period of about 40 days. Radioactivity was dispersed in the atmosphere and the ocean and subsequently traces of radionuclides were detected all over Japan. At the Fukushima airport for instance, a deposit as large as 36 kBq/m2 of Cs-137 was measured resulting of an atmospheric deposition of the plume. Both dry and wet deposition were probably involved since a raining event occurred on the 15th of March when the plume was passing nearby. The accident scenario have given rise to a number of scientific investigations. Atmospheric deposition, for example, was studied by utilizing atmospheric transport models. In atmospheric transport models, some parameters, such as cloud diagnosis, are derived from meteorological data. This cloud diagnosis is a key issue for wet deposition modelling since it allows to distinguish between two processes: in-cloud scavenging which corresponds to the collection of radioactive particles into the cloud and below-cloud scavenging consequent to the removal of radioactive material due to the falling drops. Several parametrizations of cloud diagnosis exist in the literature, using different input data: relative humidity, liquid water content, also. All these diagnosis return a large range of cloud base heights and cloud top heights. In this study, computed cloud diagnostics are compared to the observations at the Fukushima airport. Atmospheric dispersion simulations at Japan scale are then performed utilizing the most reliable ones. Impact on results are discussed.

  1. Cloud service performance evaluation: status, challenges, and opportunities – a survey from the system modeling perspective

    Directory of Open Access Journals (Sweden)

    Qiang Duan

    2017-05-01

    Full Text Available With rapid advancement of Cloud computing and networking technologies, a wide spectrum of Cloud services have been developed by various providers and utilized by numerous organizations as indispensable ingredients of their information systems. Cloud service performance has a significant impact on performance of the future information infrastructure. Thorough evaluation on Cloud service performance is crucial and beneficial to both service providers and consumers; thus forming an active research area. Some key technologies for Cloud computing, such as virtualization and the Service-Oriented Architecture (SOA, bring in special challenges to service performance evaluation. A tremendous amount of effort has been put by the research community to address these challenges and exciting progress has been made. Among the work on Cloud performance analysis, evaluation approaches developed with a system modeling perspective play an important role. However, related works have been reported in different sections of the literature; thus lacking a big picture that shows the latest status of this area. The objectives of this article is to present a survey that reflects the state of the art of Cloud service performance evaluation from the system modeling perspective. This articles also examines open issues and challenges to the surveyed evaluation approaches and identifies possible opportunities for future research in this important field.

  2. Automatic 3D Building Detection and Modeling from Airborne LiDAR Point Clouds

    Science.gov (United States)

    Sun, Shaohui

    Urban reconstruction, with an emphasis on man-made structure modeling, is an active research area with broad impact on several potential applications. Urban reconstruction combines photogrammetry, remote sensing, computer vision, and computer graphics. Even though there is a huge volume of work that has been done, many problems still remain unsolved. Automation is one of the key focus areas in this research. In this work, a fast, completely automated method to create 3D watertight building models from airborne LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and produces multi-layer rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts algorithm is used to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the properties of the local implicit surface patch. The ground terrain and building rooftop footprints are then extracted, utilizing the developed strategy, a two-step hierarchical Euclidean clustering. The method presented here adopts a "divide-and-conquer" scheme. Once the building footprints are segmented from the terrain and vegetative areas, the whole scene is divided into individual pendent processing units which represent potential points on the rooftop. For each individual building region, significant features on the rooftop are further detected using a specifically designed region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop feature is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected

  3. Retrieval of effective cloud field parameters from radiometric data

    Science.gov (United States)

    Paulescu, Marius; Badescu, Viorel; Brabec, Marek

    2017-06-01

    Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.

  4. STRUCTURAL AND FUNCTIONAL MODEL OF CLOUD ORIENTED LEARNING ENVIRONMENT FOR BACHELORS OF INFORMATICS TRAINING

    Directory of Open Access Journals (Sweden)

    Tetiana A. Vakaliuk

    2017-06-01

    Full Text Available The article summarizes the essence of the category "model". There are presented the main types of models used in educational research: structural, functional, structural and functional model as well as basic requirements for building these types of models. The national experience in building models and designing cloud-based learning environment of educational institutions (both higher and secondary is analyzed. It is presented structural and functional model of cloud-based learning environment for Bachelor of Informatics. Also we describe each component of cloud-based learning environment model for bachelors of informatics training: target, managerial, organizational, content and methodical, communication, technological and productive. It is summarized, that COLE should solve all major tasks that relate to higher education institutions.

  5. Cloud fluid models of gas dynamics and star formation in galaxies

    Science.gov (United States)

    Struck-Marcell, Curtis; Scalo, John M.; Appleton, P. N.

    1987-01-01

    The large dynamic range of star formation in galaxies, and the apparently complex environmental influences involved in triggering or suppressing star formation, challenges the understanding. The key to this understanding may be the detailed study of simple physical models for the dominant nonlinear interactions in interstellar cloud systems. One such model is described, a generalized Oort model cloud fluid, and two simple applications of it are explored. The first of these is the relaxation of an isolated volume of cloud fluid following a disturbance. Though very idealized, this closed box study suggests a physical mechanism for starbursts, which is based on the approximate commensurability of massive cloud lifetimes and cloud collisional growth times. The second application is to the modeling of colliding ring galaxies. In this case, the driving processes operating on a dynamical timescale interact with the local cloud processes operating on the above timescale. The results is a variety of interesting nonequilibrium behaviors, including spatial variations of star formation that do not depend monotonically on gas density.

  6. Reference Models of Information Systems Constructed with the use of Technologies of Cloud Calculations

    Directory of Open Access Journals (Sweden)

    Darya Sergeevna Simonenkova

    2013-09-01

    Full Text Available The subject of the research is analysis of various models of the information system constructed with the use of technologies of cloud calculations. Analysis of models is required for constructing a new reference model which will be used for develop a security threats model.

  7. Airborne Spectral BRDF of Various Surface Types (Ocean, Vegetation, Snow, Desert, Wetlands, Cloud Decks, Smoke Layers) for Remote Sensing Applications

    Science.gov (United States)

    Gatebe, Charles K.; King, Michael D.

    2016-01-01

    In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

  8. How Models Simulate the Radiative Effect in the Transition Zone of the Aerosol-Cloud Continuum

    Science.gov (United States)

    Calbo Angrill, J.; González, J. A.; Long, C. N.; McComiskey, A. C.

    2017-12-01

    Several studies have pointed towards dealing with clouds and aerosols as two manifestations of what is essentially the same physical phenomenon: a suspension of tiny particles in the air. Although the two extreme cases (i.e., pure aerosol and well-defined cloud) are easily distinguished, and obviously produce different radiative effects, there are many situations in the transition (or "twilight") zone. In a recent paper [Calbó et al., Atmos. Res. 2017, j.atmosres.2017.06.010], the authors of the current communication estimated that about 10% of time there might be a suspension of particles in the air that is difficult to distinguish as either cloud or aerosol. Radiative transfer models, however, simulate the effect of clouds and aerosols with different modules, routines, or parameterizations. In this study, we apply a sensitivity analysis approach to assess the ability of two radiative transfer models (SBDART and RRTM) in simulating the radiative effect of a suspension of particles with characteristics in the boundary between cloud and aerosol. We simulate this kind of suspension either in "cloud mode" or in "aerosol mode" and setting different values of optical depth, droplet size, water path, aerosol type, cloud height, etc. Irradiances both for solar and infrared bands are studied, both at ground level and at the top of the atmosphere, and all analyses are repeated for different solar zenith angles. We obtain that (a) water clouds and ice clouds have similar radiative effects if they have the same optical depth; (b) the spread of effects regarding different aerosol type/aerosol characteristics is remarkable; (c) radiative effects of an aerosol layer and of a cloud layer are different, even if they have similar optical depth; (d) for a given effect on the diffuse component, the effect on the direct component is usually greater (more extinction of direct beam) by aerosols than by clouds; (e) radiative transfer models are somewhat limited when simulating the

  9. A Coupled GCM-Cloud Resolving Modeling System, and a Regional Scale Model to Study Precipitation Processes

    Science.gov (United States)

    Tao, Wei-Kuo

    2007-01-01

    Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a superparameterization 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 cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. The Goddard MMF is based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM), and it has started production runs with two years results (1998 and 1999). Also, at Goddard, we have implemented several Goddard microphysical schemes (2ICE, several 31CE), Goddard radiation (including explicitly calculated cloud optical properties), and Goddard Land Information (LIS, that includes the CLM and NOAH land surface models) into a next generatio11 regional scale model, WRF. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes (microphysical and land processes), (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), and preliminary results (the comparison with traditional GCMs), and (3) A discussion on the Goddard WRF version (its developments and applications).

  10. Evaluation of the Cloud Fields in the UK Met Office HadGEM3-UKCA Model Using the CCCM Satellite Data Product to Advance Our Understanding of the Influence of Clouds on Tropospheric Composition and Chemistry

    Science.gov (United States)

    Varma, Sunil; Voulgarakis, Apostolos; Liu, Hongyu; Crawford, James H.; White, James

    2016-01-01

    To determine the role of clouds in driving inter-annual and inter-seasonal variability of trace gases in the troposphere and lower stratosphere with a particular focus on the importance of cloud modification of photolysis. To evaluate the cloud fields and their vertical distribution in the HadGEM3 model utilizing CCCM, a unique 3-D cloud data product merged from multiple A-Train satellites (CERES, CloudSat, CALIPSO, and MODIS) developed at the NASA Langley Research Center.

  11. A scheme for parameterizing ice cloud water content in general circulation models

    Science.gov (United States)

    Heymsfield, Andrew J.; Donner, Leo J.

    1989-01-01

    A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.

  12. Framework of cloud parameterization including ice for 3-D mesoscale models

    Energy Technology Data Exchange (ETDEWEB)

    Levkov, L; Jacob, D; Eppel, D; Grassl, H

    1989-01-01

    A parameterization scheme for the simulation of ice in clouds incorporated into the hydrostatic version of the GKSS three-dimensional mesoscale model. Numerical simulations of precipitation are performed: over the Northe Sea, the Hawaiian trade wind area and in the region of the intertropical convergence zone. Not only some major features of convective structures in all three areas but also cloud-aerosol interactions have successfully been simulated. (orig.) With 19 figs., 2 tabs.

  13. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Science.gov (United States)

    Zhou, C.; Zhang, X.; Gong, S.; Wang, Y.; Xue, M.

    2016-01-01

    A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under a China Meteorological Administration (CMA) chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme - WDM6) and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  14. From On-Premise Software to Cloud Services: The Impact of Cloud Computing on Enterprise Software Vendors' Business Models

    OpenAIRE

    Boillat, Thomas; Legner, Christine

    2013-01-01

    Cloud computing is an emerging paradigm that allows users to conveniently access computing resources as pay-per-use services. Whereas cloud offerings such as Amazon's Elastic Compute Cloud and Google Apps are rapidly gaining a large user base, enterprise software's migration towards the cloud is still in its infancy. For software vendors the move towardscloud solutions implies profound changes in their value-creation logic. Not only are they forced to deliver fully web-enabled solutions and t...

  15. Cloud Security in 21st Century: Current Key Issues in Service Models on Cloud Computing and how to overcome them

    OpenAIRE

    Sharma, Supern

    2011-01-01

    Cloud computing is a disruptive innovation which offers new ways to increase capacity and capabilities of the organization’s IT infrastructure. In last few years cloud computing has taken computing industry by storm and many organizations are using cloud computing services to increase the efficiency, decrease their IT budgets and play an important role in defining the IT strategy of their business. Cloud computing offers various benefits such as scalability, elasticity, reducing IT expenditur...

  16. DYNAMICAL MODEL FOR THE ZODIACAL CLOUD AND SPORADIC METEORS

    Energy Technology Data Exchange (ETDEWEB)

    Nesvorny, David; Vokrouhlicky, David; Pokorny, Petr; Bottke, William F. [Department of Space Studies, Southwest Research Institute, 1050 Walnut St., Suite 300, Boulder, CO 80302 (United States); Janches, Diego [Space Weather Laboratory, Code 674, GSFC/NASA, Greenbelt, MD 20771 (United States); Jenniskens, Peter [Carl Sagan Center, SETI Institute, 515 N. Whisman Road, Mountain View, CA 94043 (United States)

    2011-12-20

    The solar system is dusty, and would become dustier over time as asteroids collide and comets disintegrate, except that small debris particles in interplanetary space do not last long. They can be ejected from the solar system by Jupiter, thermally destroyed near the Sun, or physically disrupted by collisions. Also, some are swept by the Earth (and other planets), producing meteors. Here we develop a dynamical model for the solar system meteoroids and use it to explain meteor radar observations. We find that the Jupiter Family Comets (JFCs) are the main source of the prominent concentrations of meteors arriving at the Earth from the helion and antihelion directions. To match the radiant and orbit distributions, as measured by the Canadian Meteor Orbit Radar (CMOR) and Advanced Meteor Orbit Radar (AMOR), our model implies that comets, and JFCs in particular, must frequently disintegrate when reaching orbits with low perihelion distance. Also, the collisional lifetimes of millimeter particles may be longer ({approx}> 10{sup 5} yr at 1 AU) than postulated in the standard collisional models ({approx}10{sup 4} yr at 1 AU), perhaps because these chondrule-sized meteoroids are stronger than thought before. Using observations of the Infrared Astronomical Satellite to calibrate the model, we find that the total cross section and mass of small meteoroids in the inner solar system are (1.7-3.5) Multiplication-Sign 10{sup 11} km{sup 2} and {approx}4 Multiplication-Sign 10{sup 19} g, respectively, in a good agreement with previous studies. The mass input required to keep the zodiacal cloud in a steady state is estimated to be {approx}10{sup 4}-10{sup 5} kg s{sup -1}. The input is up to {approx}10 times larger than found previously, mainly because particles released closer to the Sun have shorter collisional lifetimes and need to be supplied at a faster rate. The total mass accreted by the Earth in particles between diameters D = 5 {mu}m and 1 cm is found to be {approx}15

  17. Traffic Flow Prediction Model for Large-Scale Road Network Based on Cloud Computing

    Directory of Open Access Journals (Sweden)

    Zhaosheng Yang

    2014-01-01

    Full Text Available To increase the efficiency and precision of large-scale road network traffic flow prediction, a genetic algorithm-support vector machine (GA-SVM model based on cloud computing is proposed in this paper, which is based on the analysis of the characteristics and defects of genetic algorithm and support vector machine. In cloud computing environment, firstly, SVM parameters are optimized by the parallel genetic algorithm, and then this optimized parallel SVM model is used to predict traffic flow. On the basis of the traffic flow data of Haizhu District in Guangzhou City, the proposed model was verified and compared with the serial GA-SVM model and parallel GA-SVM model based on MPI (message passing interface. The results demonstrate that the parallel GA-SVM model based on cloud computing has higher prediction accuracy, shorter running time, and higher speedup.

  18. New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data

    Science.gov (United States)

    Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.

    2016-05-01

    Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.

  19. Sensitivity study of cloud/radiation interaction using a second order turbulence radiative-convective model

    International Nuclear Information System (INIS)

    Kao, C.Y.J.; Smith, W.S.

    1993-01-01

    A high resolution one-dimensional version of a second order turbulence convective/radiative model, developed at the Los Alamos National Laboratory, was used to conduct a sensitivity study of a stratocumulus cloud deck, based on data taken at San Nicolas Island during the intensive field observation marine stratocumulus phase of the First International Satellite Cloud Climatology Program (ISCCP) Regional Experiment (FIRE IFO), conducted during July, 1987. Initial profiles for liquid water potential temperature, and total water mixing ratio were abstracted from the FIRE data. The dependence of the diurnal behavior in liquid water content, cloud top height, and cloud base height were examined for variations in subsidence rate, sea surface temperature, and initial inversion strength. The modelled diurnal variation in the column integrated liquid water agrees quite well with the observed data, for the case of low subsidence. The modelled diurnal behavior for the height of the cloud top and base show qualitative agreement with the FIRE data, although the overall height of the cloud layer is about 200 meters too high

  20. Modeling the partitioning of organic chemical species in cloud phases with CLEPS (1.1)

    Science.gov (United States)

    Rose, Clémence; Chaumerliac, Nadine; Deguillaume, Laurent; Perroux, Hélène; Mouchel-Vallon, Camille; Leriche, Maud; Patryl, Luc; Armand, Patrick

    2018-02-01

    The new detailed aqueous-phase mechanism Cloud Explicit Physico-chemical Scheme (CLEPS 1.0), which describes the oxidation of isoprene-derived water-soluble organic compounds, is coupled with a warm microphysical module simulating the activation of aerosol particles into cloud droplets. CLEPS 1.0 was then extended to CLEPS 1.1 to include the chemistry of the newly added dicarboxylic acids dissolved from the particulate phase. The resulting coupled model allows the prediction of the aqueous-phase concentrations of chemical compounds originating from particle scavenging, mass transfer from the gas-phase and in-cloud aqueous chemical reactivity. The aim of the present study was more particularly to investigate the effect of particle scavenging on cloud chemistry. Several simulations were performed to assess the influence of various parameters on model predictions and to interpret long-term measurements conducted at the top of Puy de Dôme (PUY, France) in marine air masses. Specific attention was paid to carboxylic acids, whose predicted concentrations are on average in the lower range of the observations, with the exception of formic acid, which is rather overestimated in the model. The different sensitivity runs highlight the fact that formic and acetic acids mainly originate from the gas phase and have highly variable aqueous-phase reactivity depending on the cloud acidity, whereas C3-C4 carboxylic acids mainly originate from the particulate phase and are supersaturated in the cloud.

  1. Remote Sensing and In-Situ Observations of Arctic Mixed-Phase and Cirrus Clouds Acquired During Mixed-Phase Arctic Cloud Experiment: Atmospheric Radiation Measurement Uninhabited Aerospace Vehicle Participation

    International Nuclear Information System (INIS)

    McFarquhar, G.M.; Freer, M.; Um, J.; McCoy, R.; Bolton, W.

    2005-01-01

    The Atmospheric Radiation Monitor (ARM) uninhabited aerospace vehicle (UAV) program aims to develop measurement techniques and instruments suitable for a new class of high altitude, long endurance UAVs while supporting the climate community with valuable data sets. Using the Scaled Composites Proteus aircraft, ARM UAV participated in Mixed-Phase Arctic Cloud Experiment (M-PACE), obtaining unique data to help understand the interaction of clouds with solar and infrared radiation. Many measurements obtained using the Proteus were coincident with in-situ observations made by the UND Citation. Data from M-PACE are needed to understand interactions between clouds, the atmosphere and ocean in the Arctic, critical interactions given large-scale models suggest enhanced warming compared to lower latitudes is occurring

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

    Science.gov (United States)

    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.

  3. Remote sensing estimates of impervious surfaces for pluvial flood modelling

    DEFF Research Database (Denmark)

    Kaspersen, Per Skougaard; Drews, Martin

    This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...

  4. Model to Implement Virtual Computing Labs via Cloud Computing Services

    OpenAIRE

    Washington Luna Encalada; José Luis Castillo Sequera

    2017-01-01

    In recent years, we have seen a significant number of new technological ideas appearing in literature discussing the future of education. For example, E-learning, cloud computing, social networking, virtual laboratories, virtual realities, virtual worlds, massive open online courses (MOOCs), and bring your own device (BYOD) are all new concepts of immersive and global education that have emerged in educational literature. One of the greatest challenges presented to e-learning solutions is the...

  5. Modelling dust polarization observations of molecular clouds through MHD simulations

    Science.gov (United States)

    King, Patrick K.; Fissel, Laura M.; Chen, Che-Yu; Li, Zhi-Yun

    2018-03-01

    The BLASTPol observations of Vela C have provided the most detailed characterization of the polarization fraction p and dispersion in polarization angles S for a molecular cloud. We compare the observed distributions of p and S with those obtained in synthetic observations of simulations of molecular clouds, assuming homogeneous grain alignment. We find that the orientation of the mean magnetic field relative to the observer has a significant effect on the p and S distributions. These distributions for Vela C are most consistent with synthetic observations where the mean magnetic field is close to the line of sight. Our results point to apparent magnetic disorder in the Vela C molecular cloud, although it can be due to either an inclination effect (i.e. observing close to the mean field direction) or significant field tangling from strong turbulence/low magnetization. The joint correlations of p with column density and of S with column density for the synthetic observations generally agree poorly with the Vela C joint correlations, suggesting that understanding these correlations requires a more sophisticated treatment of grain alignment physics.

  6. Effects of sea surface temperature, cloud radiative and microphysical processes, and diurnal variations on rainfall in equilibrium cloud-resolving model simulations

    International Nuclear Information System (INIS)

    Jiang Zhe; Li Xiao-Fan; Zhou Yu-Shu; Gao Shou-Ting

    2012-01-01

    The effects of sea surface temperature (SST), cloud radiative and microphysical processes, and diurnal variations on rainfall statistics are documented with grid data from the two-dimensional equilibrium cloud-resolving model simulations. For a rain rate of higher than 3 mm·h −1 , water vapor convergence prevails. The rainfall amount decreases with the decrease of SST from 29 °C to 27 °C, the inclusion of diurnal variation of SST, or the exclusion of microphysical effects of ice clouds and radiative effects of water clouds, which are primarily associated with the decreases in water vapor convergence. However, the amount of rainfall increases with the increase of SST from 29 °C to 31 °C, the exclusion of diurnal variation of solar zenith angle, and the exclusion of the radiative effects of ice clouds, which are primarily related to increases in water vapor convergence. For a rain rate of less than 3 mm·h −1 , water vapor divergence prevails. Unlike rainfall statistics for rain rates of higher than 3 mm·h −1 , the decrease of SST from 29 °C to 27 °C and the exclusion of radiative effects of water clouds in the presence of radiative effects of ice clouds increase the rainfall amount, which corresponds to the suppression in water vapor divergence. The exclusion of microphysical effects of ice clouds decreases the amount of rainfall, which corresponds to the enhancement in water vapor divergence. The amount of rainfall is less sensitive to the increase of SST from 29 °C to 31 °C and to the radiative effects of water clouds in the absence of the radiative effects of ice clouds. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

  7. Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

    Science.gov (United States)

    Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.

    2017-12-01

    Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.

  8. MaMR: High-performance MapReduce programming model for material cloud applications

    Science.gov (United States)

    Jing, Weipeng; Tong, Danyu; Wang, Yangang; Wang, Jingyuan; Liu, Yaqiu; Zhao, Peng

    2017-02-01

    With the increasing data size in materials science, existing programming models no longer satisfy the application requirements. MapReduce is a programming model that enables the easy development of scalable parallel applications to process big data on cloud computing systems. However, this model does not directly support the processing of multiple related data, and the processing performance does not reflect the advantages of cloud computing. To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR. An optimized data sharing strategy to supply the shared data to the different Map and Reduce stages was also designed. We added a new merge phase to MapReduce that can efficiently merge data from the map and reduce modules. Experiments showed that the model and framework present effective performance improvements compared to previous work.

  9. Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

    Science.gov (United States)

    Luo, Yali; Krueger, Steven K.; Xu, Kuan-Man

    2005-01-01

    This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

  10. Application of a Snow Growth Model to Radar Remote Sensing

    Science.gov (United States)

    Erfani, E.; Mitchell, D. L.

    2014-12-01

    Microphysical growth processes of diffusion, aggregation and riming are incorporated analytically in a steady-state snow growth model (SGM) to solve the zeroth- and second- moment conservation equations with respect to mass. The SGM is initiated by radar reflectivity (Zw), supersaturation, temperature, and a vertical profile of the liquid water content (LWC), and it uses a gamma size distribution (SD) to predict the vertical evolution of size spectra. Aggregation seems to play an important role in the evolution of snowfall rates and the snowfall rates produced by aggregation, diffusion and riming are considerably greater than those produced by diffusion and riming alone, demonstrating the strong interaction between aggregation and riming. The impact of ice particle shape on particle growth rates and fall speeds is represented in the SGM in terms of ice particle mass-dimension (m-D) power laws (m = αDβ). These growth rates are qualitatively consistent with empirical growth rates, with slower (faster) growth rates predicted for higher (lower) β values. In most models, β is treated constant for a given ice particle habit, but it is well known that β is larger for the smaller crystals. Our recent work quantitatively calculates β and α for cirrus clouds as a function of D where the m-D expression is a second-order polynomial in log-log space. By adapting this method to the SGM, the ice particle growth rates and fall speeds are predicted more accurately. Moreover, the size spectra predicted by the SGM are in good agreement with those from aircraft measurements during Lagrangian spiral descents through frontal clouds, indicating the successful modeling of microphysical processes. Since the lowest Zw over complex topography is often significantly above cloud base, the precipitation is often underestimated by radar quantitative precipitation estimates (QPE). Our SGM is capable of being initialized with Zw at the lowest reliable radar echo and consequently improves

  11. An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment

    Directory of Open Access Journals (Sweden)

    Vinothkumar Muthurajan

    2016-01-01

    Full Text Available Cloud computing requires the security upgrade in data transmission approaches. In general, key-based encryption/decryption (symmetric and asymmetric mechanisms ensure the secure data transfer between the devices. The symmetric key mechanisms (pseudorandom function provide minimum protection level compared to asymmetric key (RSA, AES, and ECC schemes. The presence of expired content and the irrelevant resources cause unauthorized data access adversely. This paper investigates how the integrity and secure data transfer are improved based on the Elliptic Curve based Schnorr scheme. This paper proposes a virtual machine based cloud model with Hybrid Cloud Security Algorithm (HCSA to remove the expired content. The HCSA-based auditing improves the malicious activity prediction during the data transfer. The duplication in the cloud server degrades the performance of EC-Schnorr based encryption schemes. This paper utilizes the blooming filter concept to avoid the cloud server duplication. The combination of EC-Schnorr and blooming filter efficiently improves the security performance. The comparative analysis between proposed HCSA and the existing Distributed Hash Table (DHT regarding execution time, computational overhead, and auditing time with auditing requests and servers confirms the effectiveness of HCSA in the cloud security model creation.

  12. An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment.

    Science.gov (United States)

    Muthurajan, Vinothkumar; Narayanasamy, Balaji

    2016-01-01

    Cloud computing requires the security upgrade in data transmission approaches. In general, key-based encryption/decryption (symmetric and asymmetric) mechanisms ensure the secure data transfer between the devices. The symmetric key mechanisms (pseudorandom function) provide minimum protection level compared to asymmetric key (RSA, AES, and ECC) schemes. The presence of expired content and the irrelevant resources cause unauthorized data access adversely. This paper investigates how the integrity and secure data transfer are improved based on the Elliptic Curve based Schnorr scheme. This paper proposes a virtual machine based cloud model with Hybrid Cloud Security Algorithm (HCSA) to remove the expired content. The HCSA-based auditing improves the malicious activity prediction during the data transfer. The duplication in the cloud server degrades the performance of EC-Schnorr based encryption schemes. This paper utilizes the blooming filter concept to avoid the cloud server duplication. The combination of EC-Schnorr and blooming filter efficiently improves the security performance. The comparative analysis between proposed HCSA and the existing Distributed Hash Table (DHT) regarding execution time, computational overhead, and auditing time with auditing requests and servers confirms the effectiveness of HCSA in the cloud security model creation.

  13. The highs and lows of cloud radiative feedback: Comparing observational data and CMIP5 models

    Science.gov (United States)

    Jenney, A.; Randall, D. A.

    2014-12-01

    Clouds play a complex role in the climate system, and remain one of the more difficult aspects of the future climate to predict. Over subtropical eastern ocean basins, particularly next to California, Peru, and Southwest Africa, low marine stratocumulus clouds (MSC) help to reduce the amount of solar radiation that reaches the surface by reflecting incident sunlight. The climate feedback associated with these clouds is thought to be positive. This project looks at CMIP5 models and compares them to observational data from CERES and ERA-Interim to try and find observational evidence and model agreement for low, marine stratocumulus cloud feedback. Although current evidence suggests that the low cloud feedback is positive (IPCC, 2014), an analysis of the simulated relationship between July lower tropospheric stability (LTS) and shortwave cloud forcing in MSC regions suggests that this feedback is not due to changes in LTS. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp.

  14. Detecting Super-Thin Clouds With Polarized Light

    Science.gov (United States)

    Sun, Wenbo; Videen, Gorden; Mishchenko, Michael I.

    2014-01-01

    We report a novel method for detecting cloud particles in the atmosphere. Solar radiation backscattered from clouds 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 clouds. The dominant backscattered electric field from the clear-sky Earth-atmosphere system is nearly parallel to the Earth surface. However, when clouds 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 clouds having an optical depth of only 0.06 and super-thin liquid water clouds having an optical depth of only 0.01. Such clouds are too thin to be sensed using any current passive satellite instruments.

  15. Challenges for Cloud Modeling in the Context of Aerosol–Cloud–Precipitation Interactions

    Energy Technology Data Exchange (ETDEWEB)

    Lebo, Zachary J. [Department of Atmospheric Science, University of Wyoming, Laramie, Wyoming; Shipway, Ben J. [Met Office, Exeter, United Kingdom; Fan, Jiwen [Pacific Northwest National Laboratory, Richland, Washington; Geresdi, Istvan [Faculty of Science, University of Pécs, Pécs, Hungary; Hill, Adrian [Met Office, Exeter, United Kingdom; Miltenberger, Annette [School of Earth and Environment, University of Leeds, Leeds, United Kingdom; Morrison, Hugh [Mesoscale and Microscale Meteorology Laboratory, National Center for Atmospheric Research, Boulder, Colorado; Rosenberg, Phil [School of Earth and Environment, University of Leeds, Leeds, United Kingdom; Varble, Adam [Department of Atmospheric Sciences, University of Utah, Salt Lake City, Utah; Xue, Lulin [Research Applications Laboratory, National Center for Atmospheric Research, Boulder, Colorado

    2017-08-01

    The International Cloud Modeling Workshop (CMW) has been a longstanding tradition in the cloud microphysics modeling community and is typically held the week prior to the International Conference on Clouds and Precipitation (ICCP). For the Ninth CMW, more than 40 participants from 10 countries convened at the Met Office in Exeter, United Kingdom. The workshop included 4 detailed case studies (described in more detail below) rooted in recent field campaigns. The overarching objective of these cases was to utilize new observations to better understand inter-model differences and model deficiencies, explore new modeling techniques, and gain physical insight into the behavior of clouds. As was the case at the Eighth CMW, there was a general theme of understanding the role of aerosol impacts in the context of cloud-precipitation interactions. However, an additional objective was the focal point of several cases at the most recent workshop: microphysical-dynamical interactions. Many of the cases focused less on idealized small-domain simulations (as was the general focus of previous workshops) and more on large-scale nested configurations examining effects at various scales.

  16. Numerical modeling and experimental research on the movement of the explosion clouds

    International Nuclear Information System (INIS)

    Li Xiaoli; Zheng Yi; Liu Wei; Wu Guansheng

    2011-01-01

    It presents the experimental research and numerical modeling on the movement of explosion clouds. The experiment was performed under two kinds of recorder, one is high speed CCD recorder which was mainly used to record the process of the fireball when the TNT was detonated, and the other is SONY vidicon that was mainly used to record the movement of the clouds. Based on the assumption that the effects on the clouds were gravity and buoyancy, the numerical model on the thermal was established. The initial condition of the thermal that was to say the initial cloud dimension was gained through the results of the recording of the highly CCD recorder. Followed this, the results of the numerical simulation were presented. And the computational results of the rising cloud are reasonable compared to that of the experiment. Thus, it can be seen that the numerical modeling and experimental research methods presented in this paper are reasonable and it can be serve as a reference to related person. Finally, the problems about the experiment and the model are pointed to establish a more accurate model. (authors)

  17. A Model for the Acceptance of Cloud Computing Technology Using DEMATEL Technique and System Dynamics Approach

    Directory of Open Access Journals (Sweden)

    seyyed mohammad zargar

    2018-03-01

    Full Text Available Cloud computing is a new method to provide computing resources and increase computing power in organizations. Despite the many benefits this method shares, it has not been universally used because of some obstacles including security issues and has become a concern for IT managers in organization. In this paper, the general definition of cloud computing is presented. In addition, having reviewed previous studies, the researchers identified effective variables on technology acceptance and, especially, cloud computing technology. Then, using DEMATEL technique, the effectiveness and permeability of the variable were determined. The researchers also designed a model to show the existing dynamics in cloud computing technology using system dynamics approach. The validity of the model was confirmed through evaluation methods in dynamics model by using VENSIM software. Finally, based on different conditions of the proposed model, a variety of scenarios were designed. Then, the implementation of these scenarios was simulated within the proposed model. The results showed that any increase in data security, government support and user training can lead to the increase in the adoption and use of cloud computing technology.

  18. Instantaneous Linkages between Clouds and Large-Scale Meteorology over the Southern Ocean in Observations and a Climate Model

    Energy Technology Data Exchange (ETDEWEB)

    Wall, Casey J. [Department of Atmospheric Sciences, University of Washington, Seattle, Washington; Hartmann, Dennis L. [Department of Atmospheric Sciences, University of Washington, Seattle, Washington; Ma, Po-Lun [Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington

    2017-12-01

    Instantaneous, coincident, footprint-level satellite observations of cloud properties and radiation taken during austral summer over the Southern Ocean are used to study relationships between clouds and large-scale meteorology. Cloud properties are very sensitive to the strength of vertical motion in the middle-troposphere, and low-cloud properties are sensitive to estimated inversion strength, low-level temperature advection, and sea surface temperature. These relationships are quantified. An index for the meteorological anomalies associated with midlatitude cyclones is presented, and it is used to reveal the sensitivity of clouds to the meteorology within the warm- and cold-sector of cyclones. The observed relationships between clouds and meteorology are compared to those in the Community Atmosphere Model version 5 (CAM5) using satellite simulators. Low-clouds simulated by CAM5 are too few, too bright, and contain too much ice, and low-clouds located in the cold-sector of cyclones are too sensitive to variations in the meteorology. The latter two biases are dramatically reduced when CAM5 is coupled with an updated boundary layer parameterization know as Cloud Layers Unified by Binormals (CLUBB). More generally, this study demonstrates that examining the instantaneous timescale is a powerful approach to understanding the physical processes that control clouds and how they are represented in climate models. Such an evaluation goes beyond the cloud climatology and exposes model bias under various meteorological conditions.

  19. Volcano and ship tracks indicate excessive aerosol-induced cloud water increases in a climate model.

    Science.gov (United States)

    Toll, Velle; Christensen, Matthew; Gassó, Santiago; Bellouin, Nicolas

    2017-12-28

    Aerosol-cloud interaction is the most uncertain mechanism of anthropogenic radiative forcing of Earth's climate, and aerosol-induced cloud water changes are particularly poorly constrained in climate models. By combining satellite retrievals of volcano and ship tracks in stratocumulus clouds, we compile a unique observational dataset and confirm that liquid water path (LWP) responses to aerosols are bidirectional, and on average the increases in LWP are closely compensated by the decreases. Moreover, the meteorological parameters controlling the LWP responses are strikingly similar between the volcano and ship tracks. In stark contrast to observations, there are substantial unidirectional increases in LWP in the Hadley Centre climate model, because the model accounts only for the decreased precipitation efficiency and not for the enhanced entrainment drying. If the LWP increases in the model were compensated by the decreases as the observations suggest, its indirect aerosol radiative forcing in stratocumulus regions would decrease by 45%.

  20. Cloud Response to Arctic Sea Ice Loss and Implications for Feedbacks in the CESM1 Climate Model

    Science.gov (United States)

    Morrison, A.; Kay, J. E.; Chepfer, H.; Guzman, R.; Bonazzola, M.

    2017-12-01

    Clouds have the potential to accelerate or slow the rate of Arctic sea ice loss through their radiative influence on the surface. Cloud feedbacks can therefore play into Arctic warming as clouds respond to changes in sea ice cover. As the Arctic moves toward an ice-free state, understanding how cloud - sea ice relationships change in response to sea ice loss is critical for predicting the future climate trajectory. From satellite observations we know the effect of present-day sea ice cover on clouds, but how will clouds respond to sea ice loss as the Arctic transitions to a seasonally open water state? In this study we use a lidar simulator to first evaluate cloud - sea ice relationships in the Community Earth System Model (CESM1) against present-day observations (2006-2015). In the current climate, the cloud response to sea ice is well-represented in CESM1: we see no summer cloud response to changes in sea ice cover, but more fall clouds over open water than over sea ice. Since CESM1 is credible for the current Arctic climate, we next assess if our process-based understanding of Arctic cloud feedbacks related to sea ice loss is relevant for understanding future Arctic clouds. In the future Arctic, summer cloud structure continues to be insensitive to surface conditions. As the Arctic warms in the fall, however, the boundary layer deepens and cloud fraction increases over open ocean during each consecutive decade from 2020 - 2100. This study will also explore seasonal changes in cloud properties such as opacity and liquid water path. Results thus far suggest that a positive fall cloud - sea ice feedback exists in the present-day and future Arctic climate.

  1. Comparison of Land Skin Temperature from a Land Model, Remote Sensing, and In-situ Measurement

    Science.gov (United States)

    Wang, Aihui; Barlage, Michael; Zeng, Xubin; Draper, Clara Sophie

    2014-01-01

    Land skin temperature (Ts) is an important parameter in the energy exchange between the land surface and atmosphere. Here hourly Ts from the Community Land Model Version 4.0, MODIS satellite observations, and in-situ observations in 2003 were compared. Compared with the in-situ observations over four semi-arid stations, both MODIS and modeled Ts show negative biases, but MODIS shows an overall better performance. Global distribution of differences between MODIS and modeled Ts shows diurnal, seasonal, and spatial variations. Over sparsely vegetated areas, the model Ts is generally lower than the MODIS observed Ts during the daytime, while the situation is opposite at nighttime. The revision of roughness length for heat and the constraint of minimum friction velocity from Zeng et al. [2012] bring the modeled Ts closer to MODIS during the day, and have little effect on Ts at night. Five factors contributing to the Ts differences between the model and MODIS are identified, including the difficulty in properly accounting for cloud cover information at the appropriate temporal and spatial resolutions, and uncertainties in surface energy balance computation, atmospheric forcing data, surface emissivity, and MODIS Ts data. These findings have implications for the cross-evaluation of modeled and remotely sensed Ts, as well as the data assimilation of Ts observations into Earth system models.

  2. SUNYA Regional Climate Model Simulations of East Asia Summer Monsoon: Effects of Cloud Vertical Structure on the Surface Energy Balance

    Directory of Open Access Journals (Sweden)

    Wei Gong and Wei-Chyung Wang

    2007-01-01

    Full Text Available We used the State University of New York at Albany (SUNYA regional climate model to study the effect of cloud vertical distribution in affecting the surface energy balance of the East Asia summer monsoon (EASM. Simulations were conducted for the summers of 1988 and 1989, during which large contrast in the intra-seasonal cloud radiative forcing (CRF was observed at the top of the atmosphere. The model results indicate that both the high and low clouds are persistent throughout the summer months in both years. Because of large cloud water, low clouds significantly reduce the solar radiation flux reaching the surface, which nevertheless still dominate the surface energy balance, accounting for more than 50% of the surface heating. The low clouds also contribute significantly the downward longwave radiation to the surface with values strongly dependent on the cloud base temperature. The presence of low clouds effectively decreases the temperature and moisture gradients near surface, resulting in a substantial decrease in the sensible and latent heat fluxes from surface, which partially compensate the decrease of the net radiative cooling of the surface. For example, in the two days, May 8 and July 11 of 1988, the total cloud cover of 80% is simulated, but the respective low cloud cover (water was 63% (114 gm-2 and 22% (21 gm-2. As a result, the downward solar radiation is smaller by 161 Wm-2 in May 8. On the other hand, the cloud temperature was _ lower, yielding 56 Wm-2 smaller downward longwave radiation. The near surface temperature and gradient is more than _ smaller (and moisture gradient, leading to 21 and 81 Wm-2 smaller sensible heat and latent heat fluxes. It is also demonstrated that the model is capable to reproduce the intraseasonal variation of shortwave CRF, and catches the relationship between total cloud cover and SW CRF. The model results show the dominance of high cloud on the regional mean longwave CRF and low cloud on the intra

  3. Improving aerosol interaction with clouds and precipitation in a regional chemical weather modeling system

    Directory of Open Access Journals (Sweden)

    C. Zhou

    2016-01-01

    Full Text Available A comprehensive aerosol–cloud–precipitation interaction (ACI scheme has been developed under a China Meteorological Administration (CMA chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme – WDM6 and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.

  4. Isotopic modeling of the sub-cloud evaporation effect in precipitation

    Energy Technology Data Exchange (ETDEWEB)

    Salamalikis, V., E-mail: vsalamalik@upatras.gr [Laboratory of Atmospheric Physics, Department of Physics, University of Patras, GR 26500 Patras (Greece); Argiriou, A.A. [Laboratory of Atmospheric Physics, Department of Physics, University of Patras, GR 26500 Patras (Greece); Dotsika, E. [Stable Isotope Unit, Institute of Nanoscience and Nanotechnology, National Center of Scientific Research ‘Demokritos’, Ag. Paraskevi Attikis, 15310 Athens (Greece)

    2016-02-15

    In dry and warm environments sub-cloud evaporation influences the falling raindrops modifying their final stable isotopic content. During their descent from the cloud base towards the ground surface, through the unsaturated atmosphere, hydrometeors are subjected to evaporation whereas the kinetic fractionation results to less depleted or enriched isotopic signatures compared to the initial isotopic composition of the raindrops at cloud base. Nowadays the development of Generalized Climate Models (GCMs) that include isotopic content calculation modules are of great interest for the isotopic tracing of the global hydrological cycle. Therefore the accurate description of the underlying processes affecting stable isotopic content can improve the performance of iso-GCMs. The aim of this study is to model the sub-cloud evaporation effect using a) mixing and b) numerical isotope evaporation models. The isotope-mixing evaporation model simulates the isotopic enrichment (difference between the ground and the cloud base isotopic composition of raindrops) in terms of raindrop size, ambient temperature and relative humidity (RH) at ground level. The isotopic enrichment (Δδ) varies linearly with the evaporated raindrops mass fraction of the raindrop resulting to higher values at drier atmospheres and for smaller raindrops. The relationship between Δδ and RH is described by a ‘heat capacity’ model providing high correlation coefficients for both isotopes (R{sup 2} > 80%) indicating that RH is an ideal indicator of the sub-cloud evaporation effect. Vertical distribution of stable isotopes in falling raindrops is also investigated using a numerical isotope-evaporation model. Temperature and humidity dependence of the vertical isotopic variation is clearly described by the numerical isotopic model showing an increase in the isotopic values with increasing temperature and decreasing RH. At an almost saturated atmosphere (RH = 95%) sub-cloud evaporation is negligible and the

  5. Isotopic modeling of the sub-cloud evaporation effect in precipitation

    International Nuclear Information System (INIS)

    Salamalikis, V.; Argiriou, A.A.; Dotsika, E.

    2016-01-01

    In dry and warm environments sub-cloud evaporation influences the falling raindrops modifying their final stable isotopic content. During their descent from the cloud base towards the ground surface, through the unsaturated atmosphere, hydrometeors are subjected to evaporation whereas the kinetic fractionation results to less depleted or enriched isotopic signatures compared to the initial isotopic composition of the raindrops at cloud base. Nowadays the development of Generalized Climate Models (GCMs) that include isotopic content calculation modules are of great interest for the isotopic tracing of the global hydrological cycle. Therefore the accurate description of the underlying processes affecting stable isotopic content can improve the performance of iso-GCMs. The aim of this study is to model the sub-cloud evaporation effect using a) mixing and b) numerical isotope evaporation models. The isotope-mixing evaporation model simulates the isotopic enrichment (difference between the ground and the cloud base isotopic composition of raindrops) in terms of raindrop size, ambient temperature and relative humidity (RH) at ground level. The isotopic enrichment (Δδ) varies linearly with the evaporated raindrops mass fraction of the raindrop resulting to higher values at drier atmospheres and for smaller raindrops. The relationship between Δδ and RH is described by a ‘heat capacity’ model providing high correlation coefficients for both isotopes (R"2 > 80%) indicating that RH is an ideal indicator of the sub-cloud evaporation effect. Vertical distribution of stable isotopes in falling raindrops is also investigated using a numerical isotope-evaporation model. Temperature and humidity dependence of the vertical isotopic variation is clearly described by the numerical isotopic model showing an increase in the isotopic values with increasing temperature and decreasing RH. At an almost saturated atmosphere (RH = 95%) sub-cloud evaporation is negligible and the

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

    Science.gov (United States)

    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.

  7. Lidar Cloud Detection with Fully Convolutional Networks

    Science.gov (United States)

    Cromwell, E.; Flynn, D.

    2017-12-01

    The vertical distribution of clouds from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of clouds can be expressed as a binary cloud mask and is a primary input for climate modeling efforts and cloud formation studies. Current cloud detection algorithms producing these masks do not accurately identify the cloud boundaries and tend to oversample or over-represent the cloud. This translates as uncertainty for assessing the radiative impact of clouds and tracking changes in cloud 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 cloud 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 cloud 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 cloud mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current cloud mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a cloud mask accuracy of 90% and a precision of 80%.

  8. AUTOMATED CALIBRATION OF FEM MODELS USING LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    B. Riveiro

    2018-05-01

    Full Text Available In present work it is pretended to estimate elastic parameters of beams through the combined use of precision geomatic techniques (laser scanning and structural behaviour simulation tools. The study has two aims, on the one hand, to develop an algorithm able to interpret automatically point clouds acquired by laser scanning systems of beams subjected to different load situations on experimental tests; and on the other hand, to minimize differences between deformation values given by simulation tools and those measured by laser scanning. In this way we will proceed to identify elastic parameters and boundary conditions of structural element so that surface stresses can be estimated more easily.

  9. Cloud albedo changes in response to anthropogenic sulfate and non-sulfate aerosol forcings in CMIP5 models

    Directory of Open Access Journals (Sweden)

    L. Frey

    2017-07-01

    Full Text Available The effects of different aerosol types on cloud albedo are analysed using the linear relation between total albedo and cloud fraction found on a monthly mean scale in regions of subtropical marine stratocumulus clouds and the influence of simulated aerosol variations on this relation. Model experiments from the Coupled Model Intercomparison Project phase 5 (CMIP5 are used to separately study the responses to increases in sulfate, non-sulfate and all anthropogenic aerosols. A cloud brightening on the month-to-month scale due to variability in the background aerosol is found to dominate even in the cases where anthropogenic aerosols are added. The aerosol composition is of importance for this cloud brightening, that is thereby region dependent. There is indication that absorbing aerosols to some extent counteract the cloud brightening but scene darkening with increasing aerosol burden is generally not supported, even in regions where absorbing aerosols dominate. Month-to-month cloud albedo variability also confirms the importance of liquid water content for cloud albedo. Regional, monthly mean cloud albedo is found to increase with the addition of anthropogenic aerosols and more so with sulfate than non-sulfate. Changes in cloud albedo between experiments are related to changes in cloud water content as well as droplet size distribution changes, so that models with large increases in liquid water path and/or cloud droplet number show large cloud albedo increases with increasing aerosol. However, no clear relation between model sensitivities to aerosol variations on the month-to-month scale and changes in cloud albedo due to changed aerosol burden is found.

  10. Combination of Tls Point Clouds and 3d Data from Kinect v2 Sensor to Complete Indoor Models

    Science.gov (United States)

    Lachat, E.; Landes, T.; Grussenmeyer, P.

    2016-06-01

    The combination of data coming from multiple sensors is more and more applied for remote sensing issues (multi-sensor imagery) but also in cultural heritage or robotics, since it often results in increased robustness and accuracy of the final data. In this paper, the reconstruction of building elements such as window frames or door jambs scanned thanks to a low cost 3D sensor (Kinect v2) is presented. Their combination within a global point cloud of an indoor scene acquired with a terrestrial laser scanner (TLS) is considered. If the added elements acquired with the Kinect sensor enable to reach a better level of detail of the final model, an adapted acquisition protocol may also provide several benefits as for example time gain. The paper aims at analyzing whether the two measurement techniques can be complementary in this context. The limitations encountered during the acquisition and reconstruction steps are also investigated.

  11. COMBINATION OF TLS POINT CLOUDS AND 3D DATA FROM KINECT V2 SENSOR TO COMPLETE INDOOR MODELS

    Directory of Open Access Journals (Sweden)

    E. Lachat

    2016-06-01

    Full Text Available The combination of data coming from multiple sensors is more and more applied for remote sensing issues (multi-sensor imagery but also in cultural heritage or robotics, since it often results in increased robustness and accuracy of the final data. In this paper, the reconstruction of building elements such as window frames or door jambs scanned thanks to a low cost 3D sensor (Kinect v2 is presented. Their combination within a global point cloud of an indoor scene acquired with a terrestrial laser scanner (TLS is considered. If the added elements acquired with the Kinect sensor enable to reach a better level of detail of the final model, an adapted acquisition protocol may also provide several benefits as for example time gain. The paper aims at analyzing whether the two measurement techniques can be complementary in this context. The limitations encountered during the acquisition and reconstruction steps are also investigated.

  12. Cloud Cover

    Science.gov (United States)

    Schaffhauser, Dian

    2012-01-01

    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 cloud computing. Edgecombe County Public Schools in Tarboro, North Carolina, intends to exploit a major cloud initiative being refined in the state and involving every…

  13. Simulation of cloud/radiation interaction using a second-order turbulence radiative-convective model

    International Nuclear Information System (INIS)

    Kao, C.Y.; Smith, W.S.

    1994-01-01

    Extended sheets of low-level stratus and stratocumulus clouds are a persistent feature over the eastern parts of the major ocean basins associated with the quasi-permanent subtropical high-pressure systems. These clouds exert a strong influence on climate through their high albedo, compared with the underlying surface, and their low altitude. The former leads to a reduction of the net shortwave flux entering the atmosphere, and the latter leads to an infrared loss in a way essentially the same as the cloud-free conditions. This paper is a modeling study with the current understanding of the important physical processes associated with a cloud-capped boundary layer. The numerical model is a high-resolution one-dimensional version of the second-order turbulence convective/radiative model developed at the Los Alamos National Laboratory. Future work includes sensitivity tests to ascertain the model validity as well as to systematically include all the possible ambient atmospheric and surface conditions. Detailed budget analyses are also useful in categorizing the cloud-capped boundary layers into a few classes

  14. Clumpy molecular clouds: A dynamic model self-consistently regulated by T Tauri star formation

    International Nuclear Information System (INIS)

    Norman, C.; Silk, J.

    1980-01-01

    A new model is proposed which can account for the longevity, energetics, and dynamical structure of dark molecular clouds. It seems clear that the kinetic and gravitational energy in macroscopic cloud motions cannot account for the energetic of many molecular clouds. A stellar energy source must evidently be tapped, and infrared observations indicate that one cannot utilize massive stars in dark clouds. Recent observations of a high space density of T Tauri stars in some dark clouds provide the basis for our assertion that high-velocity winds from these low-mass pre--main-sequence stars provide a continuous dynamic input into molecular clouds. The T Tauri winds sweep up shells of gas, the intersections or collisions of which form dense clumps embedded in a more rarefied interclump medium. Observations constrain the clumps to be ram-pressure confined, but at the relatively low Mach numbers, continuous leakage occurs. This mass input into the interclump medium leads to the existence of two phases; a dense, cold phase (clumps of density approx.10 4 --10 5 cm -3 and temperature approx.10 K) and a warm, more diffuse, interclump medium (ICM, of density approx.10 3 --10 4 cm -3 and temperature approx.30 K). Clump collisions lead to coalescence, and the evolution of the mass spectrum of clumps is studied

  15. Business models and business model innovation in a “Secure and Distributed Cloud Clustering (DISC) Society”

    DEFF Research Database (Denmark)

    Lindgren, Peter; Taran, Yariv

    2011-01-01

    of secure business models and how business models can be operated and innovated in a secure context have intensified tremendously. The development of new mobile and wireless security technologies gives hopes to really realize a secure cloud clustering society where business models can act and be innovated......The development and innovation of business models to a secure distributed cloud clustering society (DISC)—is indeed still a complex venture and has not been widely researched yet. Numerous types of security technologies are in these years proposed and in the “slip stream” of these the study...... secure—but we still have some steps to go before we reach the final destination. The paper gives a conceptual futuristic outlook on behalf of the input from SW2010 and state of the art business model research to what we can expect of business Model and business model innovation in a future secure cloud...

  16. The Role of Aerosols on Precipitation Processes: Cloud Resolving Model Simulations

    Science.gov (United States)

    Tao, Wei-Kuo; Li, X.; Matsui, T.

    2012-01-01

    Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region, the sub-tropics (Florida) and midlatitudes using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CeN case but has less cloud 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 category, a detailed analysis of the instantaneous size spectrum can be obtained for these cases. It is shown that since the low (CN case produces fewer droplets, larger sizes develop due to greater condensational and collection growth, leading to a broader size spectrum in comparison to the high CCN case. Sensitivity tests were performed to

  17. A QoS aware services mashup model for cloud computing applications

    Directory of Open Access Journals (Sweden)

    Yee Ming Chen

    2012-12-01

    Full Text Available Purpose: With the popularity of cloud computing, cloud services have become to be application programming platform where users can create new applications mashup(composing the functionality offered byothers.By composing of distributed, cloud services dynamicallyto provide more complex tasks, services mashup provides an attractive way for building large-scale Internetapplications.Oneof the challenging issues of cloud services mashup is how to find service paths to route the service instances provider through whilemeeting the applications’ resource requirements so that the QoS constraints are satisfied. However, QoS aware service routing problem istypically NP-hard.The purpose of this paper is to propose a QoS Aware Services Mashup(QASM model to solve this problem more effectively.Design/methodology/approach: In this paper, we focus on the QoS aware services selection problem in cloud services mashup, for example, given the user service composition requirements and their QoS constraint descriptions, how to select the required serviceinstances and route the data flows through these instances so that the QoS requirements are satisfied. We design a heuristic algorithm to find service paths to route the data flows through whilemeeting the applications’ resource requirements and specific QoS constraints.Findings: This study propose a QoS Aware Services Mashup(QASM model to solve this problem more effectively. Simulations show that QASM can achieve desired QoS assurances as well as load balancing in cloud services environment.Originality/value: This paperpresent a QASM model for providing high performance distributedapplications in the cloud computing systems.

  18. A Cloud Computing Model for Optimization of Transport Logistics Process

    Directory of Open Access Journals (Sweden)

    Benotmane Zineb

    2017-09-01

    Full Text Available In any increasing competitive environment and even in companies; we must adopt a good logistic chain management policy which is the main objective to increase the overall gain by maximizing profits and minimizing costs, including manufacturing costs such as: transaction, transport, storage, etc. In this paper, we propose a cloud platform of this chain logistic for decision support; in fact, this decision must be made to adopt new strategy for cost optimization, besides, the decision-maker must have knowledge on the consequences of this new strategy. Our proposed cloud computing platform has a multilayer structure; this later is contained from a set of web services to provide a link between applications using different technologies; to enable sending; and receiving data through protocols, which should be understandable by everyone. The chain logistic is a process-oriented business; it’s used to evaluate logistics process costs, to propose optimal solutions and to evaluate these solutions before their application. As a scenario, we have formulated the problem for the delivery process, and we have proposed a modified Bin-packing algorithm to improve vehicles loading.

  19. A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model.

    Science.gov (United States)

    Miura, Hiroaki; Satoh, Masaki; Nasuno, Tomoe; Noda, Akira T; Oouchi, Kazuyoshi

    2007-12-14

    A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

  20. Prototype methodology for obtaining cloud seeding guidance from HRRR model data

    Science.gov (United States)

    Dawson, N.; Blestrud, D.; Kunkel, M. L.; Waller, B.; Ceratto, J.

    2017-12-01

    Weather model data, along with real time observations, are critical to determine whether atmospheric conditions are prime for super-cooled liquid water during cloud seeding operations. Cloud seeding groups can either use operational forecast models, or run their own model on a computer cluster. A custom weather model provides the most flexibility, but is also expensive. For programs with smaller budgets, openly-available operational forecasting models are the de facto method for obtaining forecast data. The new High-Resolution Rapid Refresh (HRRR) model (3 x 3 km grid size), developed by the Earth System Research Laboratory (ESRL), provides hourly model runs with 18 forecast hours per run. While the model cannot be fine-tuned for a specific area or edited to provide cloud-seeding-specific output, model output is openly available on a near-real-time basis. This presentation focuses on a prototype methodology for using HRRR model data to create maps which aid in near-real-time cloud seeding decision making. The R programming language is utilized to run a script on a Windows® desktop/laptop computer either on a schedule (such as every half hour) or manually. The latest HRRR model run is downloaded from NOAA's Operational Model Archive and Distribution System (NOMADS). A GRIB-filter service, provided by NOMADS, is used to obtain surface and mandatory pressure level data for a subset domain which greatly cuts down on the amount of data transfer. Then, a set of criteria, identified by the Idaho Power Atmospheric Science Group, is used to create guidance maps. These criteria include atmospheric stability (lapse rates), dew point depression, air temperature, and wet bulb temperature. The maps highlight potential areas where super-cooled liquid water may exist, reasons as to why cloud seeding should not be attempted, and wind speed at flight level.

  1. Modelling cloud effects on ozone on a regional scale : A case study

    NARCIS (Netherlands)

    Matthijsen, J.; Builtjes, P.J.H.; Meijer, E.W.; Boersen, G.

    1997-01-01

    We have investigated the influence of clouds on ozone on a regional scale (Europe) with a regional scale photochemical dispersion model (LOTOS). The LOTOS-model calculates ozone and other photo-oxidant concentrations in the lowest three km of the troposphere, using actual meteorologic data and

  2. Wavefront Sensing for WFIRST with a Linear Optical Model

    Science.gov (United States)

    Jurling, Alden S.; Content, David A.

    2012-01-01

    In this paper we develop methods to use a linear optical model to capture the field dependence of wavefront aberrations in a nonlinear optimization-based phase retrieval algorithm for image-based wavefront sensing. The linear optical model is generated from a ray trace model of the system and allows the system state to be described in terms of mechanical alignment parameters rather than wavefront coefficients. This approach allows joint optimization over images taken at different field points and does not require separate convergence of phase retrieval at individual field points. Because the algorithm exploits field diversity, multiple defocused images per field point are not required for robustness. Furthermore, because it is possible to simultaneously fit images of many stars over the field, it is not necessary to use a fixed defocus to achieve adequate signal-to-noise ratio despite having images with high dynamic range. This allows high performance wavefront sensing using in-focus science data. We applied this technique in a simulation model based on the Wide Field Infrared Survey Telescope (WFIRST) Intermediate Design Reference Mission (IDRM) imager using a linear optical model with 25 field points. We demonstrate sub-thousandth-wave wavefront sensing accuracy in the presence of noise and moderate undersampling for both monochromatic and polychromatic images using 25 high-SNR target stars. Using these high-quality wavefront sensing results, we are able to generate upsampled point-spread functions (PSFs) and use them to determine PSF ellipticity to high accuracy in order to reduce the systematic impact of aberrations on the accuracy of galactic ellipticity determination for weak-lensing science.

  3. Assessment of the Effects of Entrainment and Wind Shear on Nuclear Cloud Rise Modeling

    Science.gov (United States)

    Zalewski, Daniel; Jodoin, Vincent

    2001-04-01

    Accurate modeling of nuclear cloud rise is critical in hazard prediction following a nuclear detonation. This thesis recommends improvements to the model currently used by DOD. It considers a single-term versus a three-term entrainment equation, the value of the entrainment and eddy viscous drag parameters, as well as the effect of wind shear in the cloud rise following a nuclear detonation. It examines departures from the 1979 version of the Department of Defense Land Fallout Interpretive Code (DELFIC) with the current code used in the Hazard Prediction and Assessment Capability (HPAC) code version 3.2. The recommendation for a single-term entrainment equation, with constant value parameters, without wind sh