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

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

Strategy for long-term 3D cloud-resolving simulations over the ARM SGP site and preliminary results

Science.gov (United States)

Lin, W.; Liu, Y.; Song, H.; Endo, S.

2011-12-01

Parametric representations of cloud/precipitation processes continue having to be adopted in climate simulations with increasingly higher spatial resolution or with emerging adaptive mesh framework; and it is only becoming more critical that such parameterizations have to be scale aware. Continuous cloud measurements at DOE's ARM sites have provided a strong observational basis for novel cloud parameterization research at various scales. Despite significant progress in our observational ability, there are important cloud-scale physical and dynamical quantities that are either not currently observable or insufficiently sampled. To complement the long-term ARM measurements, we have explored an optimal strategy to carry out long-term 3-D cloud-resolving simulations over the ARM SGP site using Weather Research and Forecasting (WRF) model with multi-domain nesting. The factors that are considered to have important influences on the simulated cloud fields include domain size, spatial resolution, model top, forcing data set, model physics and the growth of model errors. The hydrometeor advection that may play a significant role in hydrological process within the observational domain but is often lacking, and the limitations due to the constraint of domain-wide uniform forcing in conventional cloud system-resolving model simulations, are at least partly accounted for in our approach. Conventional and probabilistic verification approaches are employed first for selected cases to optimize the model's capability of faithfully reproducing the observed mean and statistical distributions of cloud-scale quantities. This then forms the basis of our setup for long-term cloud-resolving simulations over the ARM SGP site. The model results will facilitate parameterization research, as well as understanding and dissecting parameterization deficiencies in climate models.

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

Mechanisms of diurnal precipitation over the US Great Plains: a cloud resolving model perspective

Science.gov (United States)

Lee, Myong-In; Choi, Ildae; Tao, Wei-Kuo; Schubert, Siegfried D.; Kang, In-Sik

2010-02-01

The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program’s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer

Role of atmospheric aerosol concentration on deep convective precipitation: Cloud-resolving model simulations

Science.gov (United States)

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

2007-12-01

A two-dimensional cloud-resolving model with detailed spectral bin microphysics is used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: south Florida, Oklahoma, and the central Pacific. A pair of model simulations, one with an idealized low cloud condensation nuclei (CCN) (clean) and one with an idealized high CCN (dirty environment), is conducted for each case. In all three cases, rain reaches the ground earlier for the low-CCN case. Rain suppression is also evident in all three cases with high CCN. However, this suppression only occurs during the early stages of the simulations. During the mature stages of the simulations the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case to almost no effect in the Florida case to rain enhancement in the Pacific case. The model results suggest that evaporative cooling in the lower troposphere is a key process in determining whether high CCN reduces or enhances precipitation. Stronger evaporative cooling can produce a stronger cold pool and thus stronger low-level convergence through interactions with the low-level wind shear. Consequently, precipitation processes can be more vigorous. For example, the evaporative cooling is more than two times stronger in the lower troposphere with high CCN for the Pacific case. Sensitivity tests also suggest that ice processes are crucial for suppressing precipitation in the Oklahoma case with high CCN. A comparison and review of other modeling studies are also presented.

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.

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.

Time-resolved Shielded-Pickup Measurements and Modeling of Beam Conditioning Effects on Electron Cloud Buildup at CesrTA

CERN Document Server

Crittenden, J A; Liu, X; Palmer, M A; Santos, S; Sikora, J P; Kato, S; Calatroni, S; Rumolo, G

2012-01-01

The Cornell Electron Storage Ring Test Accelerator program includes investigations into electron cloud buildup in vacuum chambers with various coatings. Two 1.1-mlong sections located symmetrically in the east and west arc regions are equipped with BPM-like pickup detectors shielded against the direct beam-induced signal. They detect cloud electrons migrating through an 18-mm-diameter pattern of 0.76 mm-diameter holes in the top of the chamber. A digitizing oscilloscope is used to record the signals, providing time-resolved information on cloud development. We present new measurements of the effect of beam conditioning on a newly-installed amorphous carbon coated chamber, as well as on an extensively conditioned chamber with a diamond-like carbon coating. The ECLOUD modeling code is used to quantify the sensitivity of these measurements to model parameters, differentiating between photoelectron and secondary-electron production processes.

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.

A review of our understanding of the aerosol-cloud interaction from the perspective of a bin resolved cloud scale modelling

Science.gov (United States)

Flossmann, Andrea I.; Wobrock, Wolfram

2010-09-01

This review compiles the main results obtained using a mesoscale cloud model with bin resolved cloud micophysics and aerosol particle scavenging, as developed by our group over the years and applied to the simulation of shallow and deep convective clouds. The main features of the model are reviewed in different dynamical frameworks covering parcel model dynamics, as well as 1.5D, 2D and 3D dynamics. The main findings are summarized to yield a digested presentation which completes the general understanding of cloud-aerosol interaction, as currently available from textbook knowledge. Furthermore, it should provide support for general cloud model development, as it will suggest potentially minor processes that might be neglected with respect to more important ones and can support development of parameterizations for air quality, chemical transport and climate models. Our work has shown that in order to analyse dedicated campaign results, the supersaturation field and the complex dynamics of the specific clouds needs to be reproduced. Only 3D dynamics represents the variation of the supersaturation over the entire cloud, the continuous nucleation and deactivation of hydrometeors, and the dependence upon initial particle size distribution and solubility. However, general statements on certain processes can be obtained also by simpler dynamics. In particular, we found: Nucleation incorporates about 90% of the initial aerosol particle mass inside the cloud drops. Collision and coalescence redistributes the scavenged aerosol particle mass in such a way that the particle mass follows the main water mass. Small drops are more polluted than larger ones, as pollutant mass mixing ratio decreases with drops size. Collision and coalescence mixes the chemical composition of the generated drops. Their complete evaporation will release processed particles that are mostly larger and more hygroscopic than the initial particles. An interstitial aerosol is left unactivated between the

Mechanisms of Diurnal Precipitation over the United States Great Plains: A Cloud-Resolving Model Simulation

Science.gov (United States)

Lee, M.-I.; Choi, I.; Tao, W.-K.; Schubert, S. D.; Kang, I.-K.

2010-01-01

The mechanisms of summertime diurnal precipitation in the US Great Plains were examined with the two-dimensional (2D) Goddard Cumulus Ensemble (GCE) cloud-resolving model (CRM). The model was constrained by the observed large-scale background state and surface flux derived from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program s Intensive Observing Period (IOP) data at the Southern Great Plains (SGP). The model, when continuously-forced by realistic surface flux and large-scale advection, simulates reasonably well the temporal evolution of the observed rainfall episodes, particularly for the strongly forced precipitation events. However, the model exhibits a deficiency for the weakly forced events driven by diurnal convection. Additional tests were run with the GCE model in order to discriminate between the mechanisms that determine daytime and nighttime convection. In these tests, the model was constrained with the same repeating diurnal variation in the large-scale advection and/or surface flux. The results indicate that it is primarily the surface heat and moisture flux that is responsible for the development of deep convection in the afternoon, whereas the large-scale upward motion and associated moisture advection play an important role in preconditioning nocturnal convection. In the nighttime, high clouds are continuously built up through their interaction and feedback with long-wave radiation, eventually initiating deep convection from the boundary layer. Without these upper-level destabilization processes, the model tends to produce only daytime convection in response to boundary layer heating. This study suggests that the correct simulation of the diurnal variation in precipitation requires that the free-atmospheric destabilization mechanisms resolved in the CRM simulation must be adequately parameterized in current general circulation models (GCMs) many of which are overly sensitive to the parameterized boundary layer heating.

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)

A Power Efficient Exaflop Computer Design for Global Cloud System Resolving Climate Models.

Science.gov (United States)

Wehner, M. F.; Oliker, L.; Shalf, J.

2008-12-01

Exascale computers would allow routine ensemble modeling of the global climate system at the cloud system resolving scale. Power and cost requirements of traditional architecture systems are likely to delay such capability for many years. We present an alternative route to the exascale using embedded processor technology to design a system optimized for ultra high resolution climate modeling. These power efficient processors, used in consumer electronic devices such as mobile phones, portable music players, cameras, etc., can be tailored to the specific needs of scientific computing. We project that a system capable of integrating a kilometer scale climate model a thousand times faster than real time could be designed and built in a five year time scale for US$75M with a power consumption of 3MW. This is cheaper, more power efficient and sooner than any other existing technology.

Interface-Resolving Simulation of Collision Efficiency of Cloud Droplets

Science.gov (United States)

Wang, Lian-Ping; Peng, Cheng; Rosa, Bodgan; Onishi, Ryo

2017-11-01

Small-scale air turbulence could enhance the geometric collision rate of cloud droplets while large-scale air turbulence could augment the diffusional growth of cloud droplets. Air turbulence could also enhance the collision efficiency of cloud droplets. Accurate simulation of collision efficiency, however, requires capture of the multi-scale droplet-turbulence and droplet-droplet interactions, which has only been partially achieved in the recent past using the hybrid direct numerical simulation (HDNS) approach. % where Stokes disturbance flow is assumed. The HDNS approach has two major drawbacks: (1) the short-range droplet-droplet interaction is not treated rigorously; (2) the finite-Reynolds number correction to the collision efficiency is not included. In this talk, using two independent numerical methods, we will develop an interface-resolved simulation approach in which the disturbance flows are directly resolved numerically, combined with a rigorous lubrication correction model for near-field droplet-droplet interaction. This multi-scale approach is first used to study the effect of finite flow Reynolds numbers on the droplet collision efficiency in still air. Our simulation results show a significant finite-Re effect on collision efficiency when the droplets are of similar sizes. Preliminary results on integrating this approach in a turbulent flow laden with droplets will also be presented. This work is partially supported by the National Science Foundation.

Sensitivity of tropical convection in cloud-resolving WRF simulations to model physics and forcing procedures

Science.gov (United States)

Endo, S.; Lin, W.; Jackson, R. C.; Collis, S. M.; Vogelmann, A. M.; Wang, D.; Oue, M.; Kollias, P.

2017-12-01

Tropical convection is one of the main drivers of the climate system and recognized as a major source of uncertainty in climate models. High-resolution modeling is performed with a focus on the deep convection cases during the active monsoon period of the TWP-ICE field campaign to explore ways to improve the fidelity of convection permitting tropical simulations. Cloud resolving model (CRM) simulations are performed with WRF modified to apply flexible configurations for LES/CRM simulations. We have enhanced the capability of the forcing module to test different implementations of large-scale vertical advective forcing, including a function for optional use of large-scale thermodynamic profiles and a function for the condensate advection. The baseline 3D CRM configurations are, following Fridlind et al. (2012), driven by observationally-constrained ARM forcing and tested with diagnosed surface fluxes and fixed sea-surface temperature and prescribed aerosol size distributions. After the spin-up period, the simulations follow the observed precipitation peaks associated with the passages of precipitation systems. Preliminary analysis shows that the simulation is generally not sensitive to the treatment of the large-scale vertical advection of heat and moisture, while more noticeable changes in the peak precipitation rate are produced when thermodynamic profiles above the boundary layer were nudged to the reference profiles from the forcing dataset. The presentation will explore comparisons with observationally-based metrics associated with convective characteristics and examine the model performance with a focus on model physics, doubly-periodic vs. nested configurations, and different forcing procedures/sources. A radar simulator will be used to understand possible uncertainties in radar-based retrievals of convection properties. Fridlind, A. M., et al. (2012), A comparison of TWP-ICE observational data with cloud-resolving model results, J. Geophys. Res., 117, D05204

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.

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.

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.

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

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

Clausius-Clapeyron Scaling of Convective Available Potential Energy (CAPE) in Cloud-Resolving Simulations

Science.gov (United States)

Seeley, J.; Romps, D. M.

2015-12-01

Recent work by Singh and O'Gorman has produced a theory for convective available potential energy (CAPE) in radiative-convective equilibrium. In this model, the atmosphere deviates from a moist adiabat—and, therefore, has positive CAPE—because entrainment causes evaporative cooling in cloud updrafts, thereby steepening their lapse rate. This has led to the proposal that CAPE increases with global warming because the strength of evaporative cooling scales according to the Clausius-Clapeyron (CC) relation. However, CAPE could also change due to changes in cloud buoyancy and changes in the entrainment rate, both of which could vary with global warming. To test the relative importance of changes in CAPE due to CC scaling of evaporative cooling, changes in cloud buoyancy, and changes in the entrainment rate, we subject a cloud-resolving model to a suite of natural (and unnatural) forcings. We find that CAPE changes are primarily driven by changes in the strength of evaporative cooling; the effect of changes in the entrainment rate and cloud buoyancy are comparatively small. This builds support for CC scaling of CAPE.

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

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

Precipitation processes developed during TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999): 3D Cloud Resolving Model Simulation

Science.gov (United States)

Tao, W.-K.

2006-01-01

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research (NCAR), NOAA GFDL, the U.K. Met. Office, Colorado State University and NASA Goddard Space Flight Center. An improved 3D Goddard Cumulus Ensemble (GCE) model was recently used to simulate periods during TOGA COARE (December 19-27, 1992), GATE (september 1-7, 1974), SCSMEX (May 18-26, June 2-11, 1998) and KWAJEX (August 7-13, August 18-21, and August 29-September 12, 1999) using a 512 by 512 km domain and 41 vertical layers. The major objectives of this paper are: (1) to identify the differences and similarities in the simulated precipitation processes and their associated surface and water energy budgets in TOGA COARE, GATE, KWAJEX, and SCSMEX, and (2) to asses the impact of microphysics, radiation budget and surface fluxes on the organization of convection in tropics.

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.

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.

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.

A cloud chemistry module for the 3-D cloud-resolving mesoscale model Meso-NH with application to idealized cases

Directory of Open Access Journals (Sweden)

M. Leriche

2013-08-01

Full Text Available A complete chemical module has been developed for use in the Meso-NH three-dimensional cloud resolving mesoscale model. This module includes gaseous- and aqueous-phase chemical reactions that are analysed by a pre-processor generating the Fortran90 code automatically. The kinetic solver is based on a Rosenbrock algorithm, which is robust and accurate for integrating stiff systems and especially multiphase chemistry. The exchange of chemical species between the gas phase and cloud droplets and raindrops is computed kinetically by mass transfers considering non-equilibrium between the gas- and the condensed phases. Microphysical transfers of chemical species are considered for the various cloud microphysics schemes available, which are based on one-moment or two-moment schemes. The pH of the droplets and of the raindrops is diagnosed separately as the root of a high order polynomial equation. The chemical concentrations in the ice phase are modelled in a single phase encompassing the two categories of precipitating ice particles (snow and graupel of the microphysical scheme. The only process transferring chemical species in ice is retention during freezing or riming of liquid hydrometeors. Three idealized simulations are reported, which highlight the sensitivity of scavenging efficiency to the choice of the microphysical scheme and the retention coefficient in the ice phase. A two-dimensional warm, shallow convection case is used to compare the impact of the microphysical schemes on the temporal evolution and rates of acid precipitation. Acid wet deposition rates are shown to be overestimated when a one-moment microphysics scheme is used compared to a two-moment scheme. The difference is induced by a better prediction of raindrop radius and raindrop number concentration in the latter scheme. A two-dimensional mixed-phase squall line and a three-dimensional mixed-phase supercell were simulated to test the sensitivity of cloud vertical transport to

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

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.

Development of Spaceborne Radar Simulator by NICT and JAXA using JMA Cloud-resolving Model

Science.gov (United States)

Kubota, T.; Eito, H.; Aonashi, K.; Hashimoto, A.; Iguchi, T.; Hanado, H.; Shimizu, S.; Yoshida, N.; Oki, R.

2009-12-01

We are developing synthetic spaceborne radar data toward a simulation of the Dual-frequency Precipitation Radar (DPR) aboard the Global Precipitation Measurement (GPM) core-satellite. Our purposes are a production of test-bed data for higher level DPR algorithm developers, in addition to a diagnosis of a cloud resolving model (CRM). To make the synthetic data, we utilize the CRM by the Japan Meteorological Agency (JMA-NHM) (Ikawa and Saito 1991, Saito et al. 2006, 2007), and the spaceborne radar simulation algorithm by the National Institute of Information and Communications Technology (NICT) and the Japan Aerospace Exploration Agency (JAXA) named as the Integrated Satellite Observation Simulator for Radar (ISOSIM-Radar). The ISOSIM-Radar simulates received power data in a field of view of the spaceborne radar with consideration to a scan angle of the radar (Oouchi et al. 2002, Kubota et al. 2009). The received power data are computed with gaseous and hydrometeor attenuations taken into account. The backscattering and extinction coefficients are calculated assuming the Mie approximation for all species. The dielectric constants for solid particles are computed by the Maxwell-Garnett model (Bohren and Battan 1982). Drop size distributions are treated in accordance with those of the JMA-NHM. We assume a spherical sea surface, a Gaussian antenna pattern, and 49 antenna beam directions for scan angles from -17 to 17 deg. in the PR. In this study, we report the diagnosis of the JMA-NHM with reference to the TRMM Precipitation Radar (PR) and CloudSat Cloud Profiling Radar (CPR) using the ISOSIM-Radar from the view of comparisons in cloud microphysics schemes of the JMA-NHM. We tested three kinds of explicit bulk microphysics schemes based on Lin et al. (1983), that is, three-ice 1-moment scheme, three-ice 2-moment scheme (Eito and Aonashi 2009), and newly developed four-ice full 2-moment scheme (Hashimoto 2008). The hydrometeor species considered here are rain, graupel

Analysis of the environments of seven Mediterranean tropical-like storms using an axisymmetric, nonhydrostatic, cloud resolving model

Directory of Open Access Journals (Sweden)

L. Fita

2007-01-01

Full Text Available Tropical-like storms on the Mediterranean Sea are occasionally observed on satellite images, often with a clear eye surrounded by an axysimmetric cloud structure. These storms sometimes attain hurricane intensity and can severely affect coastal lands. A deep, cut-off, cold-core low is usually observed at mid-upper tropospheric levels in association with the development of these tropical-like systems. In this study we attempt to apply some tools previously used in studies of tropical hurricanes to characterise the environments in which seven known Mediterranean events developed. In particular, an axisymmetric, nonhydrostatic, cloud resolving model is applied to simulate the tropical-like storm genesis and evolution. Results are compared to surface observations when landfall occurred and with satellite microwave derived wind speed measurements over the sea. Finally, sensitivities of the numerical simulations to different factors (e.g. sea surface temperature, vertical humidity profile and size of the initial precursor of the storm are examined.

Physical feedbacks on stratus cloud amount resolve the Faint Young Sun Paradox

Science.gov (United States)

Goldblatt, C.; McCusker, K. E.; McDonald, V.

2017-12-01

Geological evidence suggests that Earth was mostly warm and not glaciated during the Archean, despite Earth receiving only around 80% of the present day amount of sunlight. 1-D models require higher abundances of greenhouse gases than geochemical proxies permit, whereas some 3-D models permit lower greenhouse gas inventories, but for reasons which are somewhat opaque. Here, we show that physically motivated changes to low cloud (stratus) amount likely played a large role in resolving the FYSP. The amount of stratus cloud is strongly linked to lower tropospheric stability [Slingo 1987; Woods and Bretherton 2006], with a stronger inversion at the planetary boundary layer trapping moisture and giving a higher stratus cloud fraction. By hypothesis, an Archean situation where the surface is heated less by sunlight and the atmosphere is heated more by absorption of thermal radiation with a stronger greenhouse, should feature a weaker inversion and less stable lower troposphere. Hence, with a weaker sun but stronger greenhouse, we expect less stratus clouds. To test this hypothesis, we run a set of carefully controlled General Circulation Model experiments using the Community Atmosphere Model. We change only the solar constant and CO2 mixing ratio, increasing CO2 and decreasing the solar constant so that the global mean surface temperature remains the same. We do not change anything else, so as to focus directly on a single hypothesis, and to keep the model as near to known conditions as possible. We find that at 80% of modern solar constant: (1) only 30,000 ppmv CO2 is required to maintain modern surface temperatures, versus the expectation of 80,000 ppmv from radiative forcing calculations. (2) The dominant change is to low cloud fraction, decreasing from 34% to 25%, with an associated reduction in short-wave cloud forcing of 20W/m/m. This can be set in the context of a 50W/m/m radiative deficit due to the weaker sun, so the cloud feedback contributes two-fifths of the

Precipitation Processes developed during ARM (1997), TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999), Consistent 2D, semi-3D and 3D Cloud Resolving Model Simulations

Science.gov (United States)

Tao, Wei-Kuo; Hou, A.; Atlas, R.; Starr, D.; Sud, Y.

2003-01-01

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. The major objectives of this paper are: (1) to assess the performance of the super-parameterization technique (i.e. is 2D or semi-3D CRM appropriate for the super-parameterization?); (2) calculate and examine the surface energy (especially radiation) and water budgets; (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

Extended-range prediction trials using the global cloud/cloud-system resolving model NICAM and its new ocean-coupled version NICOCO

Science.gov (United States)

Miyakawa, Tomoki

2017-04-01

The global cloud/cloud-system resolving model NICAM and its new fully-coupled version NICOCO is run on one of the worlds top-tier supercomputers, the K computer. NICOCO couples the full-3D ocean component COCO of the general circulation model MIROC using a general-purpose coupler Jcup. We carried out multiple MJO simulations using NICAM and the new ocean-coupled version NICOCO to examine their extended-range MJO prediction skills and the impact of ocean coupling. NICAM performs excellently in terms of MJO prediction, maintaining a valid skill up to 27 days after the model is initialized (Miyakawa et al 2014). As is the case in most global models, ocean coupling frees the model from being anchored by the observed SST and allows the model climate to drift away further from reality compared to the atmospheric version of the model. Thus, it is important to evaluate the model bias, and in an initial value problem such as the seasonal extended-range prediction, it is essential to be able to distinguish the actual signal from the early transition of the model from the observed state to its own climatology. Since NICAM is a highly resource-demanding model, evaluation and tuning of the model climatology (order of years) is challenging. Here we focus on the initial 100 days to estimate the early drift of the model, and subsequently evaluate MJO prediction skills of NICOCO. Results show that in the initial 100 days, NICOCO forms a La-Nina like SST bias compared to observation, with a warmer Maritime Continent warm pool and a cooler equatorial central Pacific. The enhanced convection over the Maritime Continent associated with this bias project on to the real-time multi-variate MJO indices (RMM, Wheeler and Hendon 2004), and contaminates the MJO skill score. However, the bias does not appear to demolish the MJO signal severely. The model maintains a valid MJO prediction skill up to nearly 4 weeks when evaluated after linearly removing the early drift component estimated from

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

Cloud computing models and their application in LTE based cellular systems

NARCIS (Netherlands)

Staring, A.J.; Karagiannis, Georgios

2013-01-01

As cloud computing emerges as the next novel concept in computer science, it becomes clear that the model applied in large data storage systems used to resolve issues coming forth from an increasing demand, could also be used to resolve the very high bandwidth requirements on access network, core

A new single-moment microphysics scheme for cloud-resolving models using observed dependence of ice concentration on temperature.

Science.gov (United States)

Khairoutdinov, M.

2015-12-01

The representation of microphysics, especially ice microphysics, remains one of the major uncertainties in cloud-resolving models (CRMs). Most of the cloud schemes use the so-called bulk microphysics approach, in which a few moments of such distributions are used as the prognostic variables. The System for Atmospheric Modeling (SAM) is the CRM that employs two such schemes. The single-moment scheme, which uses only mass for each of the water phases, and the two-moment scheme, which adds the particle concentration for each of the hydrometeor category. Of the two, the single-moment scheme is much more computationally efficient as it uses only two prognostic microphysics variables compared to ten variables used by the two-moment scheme. The efficiency comes from a rather considerable oversimplification of the microphysical processes. For instance, only a sum of the liquid and icy cloud water is predicted with the temperature used to diagnose the mixing ratios of different hydrometeors. The main motivation for using such simplified microphysics has been computational efficiency, especially in the applications of SAM as the super-parameterization in global climate models. Recently, we have extended the single-moment microphysics by adding only one additional prognostic variable, which has, nevertheless, allowed us to separate the cloud ice from liquid water. We made use of some of the recent observations of ice microphysics collected at various parts of the world to parameterize several aspects of ice microphysics that have not been explicitly represented before in our sing-moment scheme. For example, we use the observed broad dependence of ice concentration on temperature to diagnose the ice concentration in addition to prognostic mass. Also, there is no artificial separation between the pristine ice and snow, often used by bulk models. Instead we prescribed the ice size spectrum as the gamma distribution, with the distribution shape parameter controlled by the

Effects of Precipitation on Ocean Mixed-Layer Temperature and Salinity as Simulated in a 2-D Coupled Ocean-Cloud Resolving Atmosphere Model

Science.gov (United States)

Li, Xiaofan; Sui, C.-H.; Lau, K-M.; Adamec, D.

1999-01-01

A two-dimensional coupled ocean-cloud resolving atmosphere model is used to investigate possible roles of convective scale ocean disturbances induced by atmospheric precipitation on ocean mixed-layer heat and salt budgets. The model couples a cloud resolving model with an embedded mixed layer-ocean circulation model. Five experiment are performed under imposed large-scale atmospheric forcing in terms of vertical velocity derived from the TOGA COARE observations during a selected seven-day period. The dominant variability of mixed-layer temperature and salinity are simulated by the coupled model with imposed large-scale forcing. The mixed-layer temperatures in the coupled experiments with 1-D and 2-D ocean models show similar variations when salinity effects are not included. When salinity effects are included, however, differences in the domain-mean mixed-layer salinity and temperature between coupled experiments with 1-D and 2-D ocean models could be as large as 0.3 PSU and 0.4 C respectively. Without fresh water effects, the nocturnal heat loss over ocean surface causes deep mixed layers and weak cooling rates so that the nocturnal mixed-layer temperatures tend to be horizontally-uniform. The fresh water flux, however, causes shallow mixed layers over convective areas while the nocturnal heat loss causes deep mixed layer over convection-free areas so that the mixed-layer temperatures have large horizontal fluctuations. Furthermore, fresh water flux exhibits larger spatial fluctuations than surface heat flux because heavy rainfall occurs over convective areas embedded in broad non-convective or clear areas, whereas diurnal signals over whole model areas yield high spatial correlation of surface heat flux. As a result, mixed-layer salinities contribute more to the density differences than do mixed-layer temperatures.

Precipitation Processes developed during ARM (1997), TOGA COARE(1992), GATE(1 974), SCSMEX(1998) and KWAJEX(1999): Consistent 2D and 3D Cloud Resolving Model Simulations

Science.gov (United States)

Tao, W.-K.; Shie, C.-H.; Simpson, J.; Starr, D.; Johnson, D.; Sud, Y.

2003-01-01

Real clouds and clouds systems are inherently three dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud system with large horizontal domains at the National Center for Atmospheric Research. The results indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D simulations of these same cases. The reason for the strong similarity between the 2D and 3D CRM simulations is that the observed large-scale advective tendencies of potential temperature, water vapor mixing ratio, and horizontal momentum were used as the main forcing in both the 2D and 3D models. Interestingly, the 2D and 3D versions of the CRM used in CSU and U.K. Met Office showed significant differences in the rainfall and cloud statistics for three ARM cases. The major objectives of this project are to calculate and axamine: (1)the surface energy and water budgets, (2) the precipitation processes in the convective and stratiform regions, (3) the cloud upward and downward mass fluxes in the convective and stratiform regions; (4) cloud characteristics such as size, updraft intensity and lifetime, and (5) the entrainment and detrainment rates associated with clouds and cloud systems that developed in TOGA COARE, GATE, SCSMEX, ARM and KWAJEX. Of special note is that the analyzed (model generated) data sets are all produced by the same current version of the GCE model, i.e. consistent model physics and configurations. Trajectory analyse and inert tracer calculation will be conducted to identify the differences and similarities in the organization of convection between simulated 2D and 3D cloud systems.

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

Precipitation Processes Developed During ARM (1997), TOGA COARE (1992) GATE (1974), SCSMEX (1998), and KWAJEX (1999): Consistent 3D, Semi-3D and 3D Cloud Resolving Model Simulations

Science.gov (United States)

Tao, W.-K.; Hou, A.; Atlas, R.; Starr, D.; Sud, Y.

2003-01-01

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D) have been used to study the response of clouds to large-scale forcing. IN these 3D simulators, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical clouds systems with large horizontal domains at the National Center of Atmospheric Research (NCAR) and at NASA Goddard Space Center. At Goddard, a 3D cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE, GATE, SCSMEX, ARM, and KWAJEX using a 512 by 512 km domain (with 2-km resolution). The result indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D GCE model simulation. The major objective of this paper are: (1) to assess the performance of the super-parametrization technique, (2) calculate and examine the surface energy (especially radiation) and water budget, and (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

On the robustness of aerosol effects on an idealized supercell storm simulated with a cloud system-resolving model

Directory of Open Access Journals (Sweden)

H. Morrison

2012-08-01

Full Text Available A cloud system-resolving model (the Weather Research and Forecasting model with 1 km horizontal grid spacing is used to investigate the response of an idealized supercell storm to increased cloud droplet concentrations associated with polluted conditions. The primary focus is on exploring robustness of simulated aerosol effects in the face of complex process interactions and feedbacks between the cloud microphysics and dynamics. Simulations are run using sixteen different model configurations with various microphysical or thermodynamic processes modified or turned off. Robustness of the storm response to polluted conditions is also explored for each configuration by performing additional simulations with small perturbations to the initial conditions. Differences in the domain-mean accumulated surface precipitation and convective mass flux between polluted and pristine conditions are small for almost all model configurations, with relative differences in each quantity generally less than 15%. Configurations that produce a decrease (increase in cold pool strength in polluted conditions also tend to simulate a decrease (increase in surface precipitation and convective mass flux. Combined with an analysis of the dynamical and thermodynamic fields, these results indicate the importance of interactions between microphysics, cold pool evolution, and dynamics along outflow boundaries in explaining the system response. Several model configurations, including the baseline, produce an overall similar storm response (weakening in polluted conditions despite having different microphysical or thermodynamic processes turned off. With hail initiation turned off or the hail fallspeed-size relation set to that of snow, the model produces an invigoration instead of weakening of the storm in polluted conditions. These results highlight the difficulty of foreseeing impacts of changes to model parameterizations and isolating process interactions that drive the system

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

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)].

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

Evolution of Precipitation Structure During the November DYNAMO MJO Event: Cloud-Resolving Model Intercomparison and Cross Validation Using Radar Observations

Science.gov (United States)

Li, Xiaowen; Janiga, Matthew A.; Wang, Shuguang; Tao, Wei-Kuo; Rowe, Angela; Xu, Weixin; Liu, Chuntao; Matsui, Toshihisa; Zhang, Chidong

2018-04-01

Evolution of precipitation structures are simulated and compared with radar observations for the November Madden-Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground-based, ship-borne, and spaceborne precipitation radars and three cloud-resolving models (CRMs) driven by observed large-scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0-dBZ echo-top heights, and convective organization by contiguous 17-dBZ areas. The multi-radar and multi-model framework allows for more stringent model validations. The emphasis is on testing models' ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site-specific large-scale forcing can reproduce not only common features in cloud populations but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo-top heights for the strongest convection within large, organized precipitation features. Cross validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large-scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo-top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well-validated model simulations could be used to constrain uncertainties in observed echo-top heights when the low-resolution surveillance scanning strategy is used.

Cloud-resolving model intercomparison of an MC3E squall line case: Part I-Convective updrafts: CRM Intercomparison of a Squall Line

Energy Technology Data Exchange (ETDEWEB)

Fan, Jiwen [Pacific Northwest National Laboratory, Richland Washington USA; Han, Bin [Pacific Northwest National Laboratory, Richland Washington USA; School of Atmospheric Sciences, Nanjing University, Nanjing China; Varble, Adam [Department of Atmospheric Sciences, University of Utah, Salt Lake City Utah USA; Morrison, Hugh [National Center for Atmospheric Research, Boulder Colorado USA; North, Kirk [Department of Atmospheric and Oceanic Sciences, McGill University, Montreal Quebec USA; Kollias, Pavlos [Department of Atmospheric and Oceanic Sciences, McGill University, Montreal Quebec USA; School of Marine and Atmospheric Sciences, Stony Brook University, Stony Brook New York USA; Chen, Baojun [School of Atmospheric Sciences, Nanjing University, Nanjing China; Dong, Xiquan [Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson Arizona USA; Giangrande, Scott E. [Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton New York USA; Khain, Alexander [The Institute of the Earth Science, The Hebrew University of Jerusalem, Jerusalem Israel; Lin, Yun [Department of Atmospheric Sciences, Texas A& M University, College Station Texas USA; Mansell, Edward [NOAA/OAR/National Severe Storms Laboratory, Norman Oklahoma USA; Milbrandt, Jason A. [Meteorological Research Division, Environment and Climate Change Canada, Dorval Canada; Stenz, Ronald [Department of Atmospheric Sciences, University of North Dakota, Grand Forks North Dakota USA; Thompson, Gregory [National Center for Atmospheric Research, Boulder Colorado USA; Wang, Yuan [Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena California USA

2017-09-06

A constrained model intercomparison study of a mid-latitude mesoscale squall line is performed using the Weather Research & Forecasting (WRF) model at 1-km horizontal grid spacing with eight cloud microphysics schemes, to understand specific processes that lead to the large spread of simulated cloud and precipitation at cloud-resolving scales, with a focus of this paper on convective cores. Various observational data are employed to evaluate the baseline simulations. All simulations tend to produce a wider convective area than observed, but a much narrower stratiform area, with most bulk schemes overpredicting radar reflectivity. The magnitudes of the virtual potential temperature drop, pressure rise, and the peak wind speed associated with the passage of the gust front are significantly smaller compared with the observations, suggesting simulated cool pools are weaker. Simulations also overestimate the vertical velocity and Ze in convective cores as compared with observational retrievals. The modeled updraft velocity and precipitation have a significant spread across the eight schemes even in this strongly dynamically-driven system. The spread of updraft velocity is attributed to the combined effects of the low-level perturbation pressure gradient determined by cold pool intensity and buoyancy that is not necessarily well correlated to differences in latent heating among the simulations. Variability of updraft velocity between schemes is also related to differences in ice-related parameterizations, whereas precipitation variability increases in no-ice simulations because of scheme differences in collision-coalescence parameterizations.

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.

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

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...

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.

Improving representation of convective transport for scale-aware parameterization: 2. Analysis of cloud-resolving model simulations

Science.gov (United States)

Liu, Yi-Chin; Fan, Jiwen; Zhang, Guang J.; Xu, Kuan-Man; Ghan, Steven J.

2015-04-01

Following Part I, in which 3-D cloud-resolving model (CRM) simulations of a squall line and mesoscale convective complex in the midlatitude continental and the tropical regions are conducted and evaluated, we examine the scale dependence of eddy transport of water vapor, evaluate different eddy transport formulations, and improve the representation of convective transport across all scales by proposing a new formulation that more accurately represents the CRM-calculated eddy flux. CRM results show that there are strong grid-spacing dependencies of updraft and downdraft fractions regardless of altitudes, cloud life stage, and geographical location. As for the eddy transport of water vapor, updraft eddy flux is a major contributor to total eddy flux in the lower and middle troposphere. However, downdraft eddy transport can be as large as updraft eddy transport in the lower atmosphere especially at the mature stage of midlatitude continental convection. We show that the single-updraft approach significantly underestimates updraft eddy transport of water vapor because it fails to account for the large internal variability of updrafts, while a single downdraft represents the downdraft eddy transport of water vapor well. We find that using as few as three updrafts can account for the internal variability of updrafts well. Based on the evaluation with the CRM simulated data, we recommend a simplified eddy transport formulation that considers three updrafts and one downdraft. Such formulation is similar to the conventional one but much more accurately represents CRM-simulated eddy flux across all grid scales.

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)

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

Precipitation Processes Developed During ARM (1997), TOGA COARE (1992), GATE (1974), SCSMEX (1998), and KWAJEX (1999): Consistent 2D, Semi-3D and 3D Cloud Resolving Model Simulations

Science.gov (United States)

Tao, W-K.

2003-01-01

Real clouds and cloud systems are inherently three-dimensional (3D). Because of the limitations in computer resources, however, most cloud-resolving models (CRMs) today are still two-dimensional (2D). A few 3D CRMs have been used to study the response of clouds to large-scale forcing. In these 3D simulations, the model domain was small, and the integration time was 6 hours. Only recently have 3D experiments been performed for multi-day periods for tropical cloud systems with large horizontal domains at the National Center for Atmospheric Research (NACAR) and at NASA Goddard Space Flight Center . At Goddard, a 3D Goddard Cumulus Ensemble (GCE) model was used to simulate periods during TOGA COARE, SCSMEX and KWAJEX using 512 by 512 km domain (with 2 km resolution). The results indicate that surface precipitation and latent heating profiles are very similar between the 2D and 3D GCE model simulations. The reason for the strong similarity between the 2D and 3D CRM simulations is that the same observed large-scale advective tendencies of potential temperature, water vapor mixing ratio, and horizontal momentum were used as the main focusing in both the 2D and 3D models. Interestingly, the 2D and 3D versions of the CRM used at CSU showed significant differences in the rainfall and cloud statistics for three ARM cases. The major objectives of this paper are: (1) to assess the performance of the super-parameterization technique, (2) calculate and examine the surface energy (especially radiation) and water budgets, and (3) identify the differences and similarities in the organization and entrainment rates of convection between simulated 2D and 3D cloud systems.

Hardware/Software Co-design of Global Cloud System Resolving

Directory of Open Access Journals (Sweden)

Michael Wehner

2011-10-01

Full Text Available We present an analysis of the performance aspects of an atmospheric general circulation model at the ultra-high resolution required to resolve individual cloud systems and describe alternative technological paths to realize the integration of such a model in the relatively near future. Due to a superlinear scaling of the computational burden dictated by the Courant stability criterion, the solution of the equations of motion dominate the calculation at these ultra-high resolutions. From this extrapolation, it is estimated that a credible kilometer scale atmospheric model would require a sustained computational rate of at least 28 Petaflop/s to provide scientifically useful climate simulations. Our design study portends an alternate strategy for practical power-efficient implementations of next-generation ultra-scale systems. We demonstrate that hardware/software co-design of low-power embedded processor technology could be exploited to design a custom machine tailored to ultra-high resolution climate model specifications at relatively affordable cost and power considerations. A strawman machine design is presented consisting of in excess of 20 million processing elements that effectively exploits forthcoming many-core chips. The system pushes the limits of domain decomposition to increase explicit parallelism, and suggests that functional partitioning of sub-components of the climate code (much like the coarse-grained partitioning of computation between the atmospheric, ocean, land, and ice components of current coupled models may be necessary for future performance scaling.

Impact of Precipitating Ice Hydrometeors on Longwave Radiative Effect Estimated by a Global Cloud-System Resolving Model

Science.gov (United States)

Chen, Ying-Wen; Seiki, Tatsuya; Kodama, Chihiro; Satoh, Masaki; Noda, Akira T.

2018-02-01

Satellite observation and general circulation model (GCM) studies suggest that precipitating ice makes nonnegligible contributions to the radiation balance of the Earth. However, in most GCMs, precipitating ice is diagnosed and its radiative effects are not taken into account. Here we examine the longwave radiative impact of precipitating ice using a global nonhydrostatic atmospheric model with a double-moment cloud microphysics scheme. An off-line radiation model is employed to determine cloud radiative effects according to the amount and altitude of each type of ice hydrometeor. Results show that the snow radiative effect reaches 2 W m-2 in the tropics, which is about half the value estimated by previous studies. This effect is strongly dependent on the vertical separation of ice categories and is partially generated by differences in terminal velocities, which are not represented in GCMs with diagnostic precipitating ice. Results from sensitivity experiments that artificially change the categories and altitudes of precipitating ice show that the simulated longwave heating profile and longwave radiation field are sensitive to the treatment of precipitating ice in models. This study emphasizes the importance of incorporating appropriate treatments for the radiative effects of precipitating ice in cloud and radiation schemes in GCMs in order to capture the cloud radiative effects of upper level clouds.

Evaluating Lightning-generated NOx (LNOx) Parameterization based on Cloud Top Height at Resolutions with Partially-resolved Convection for Upper Tropospheric Chemistry Studies

Science.gov (United States)

Wong, J.; Barth, M. C.; Noone, D. C.

2012-12-01

Lightning-generated nitrogen oxides (LNOx) is an important precursor to tropospheric ozone production. With a meteorological time-scale variability similar to that of the ozone chemical lifetime, it can nonlinearly perturb tropospheric ozone concentration. Coupled with upper-air circulation patterns, LNOx can accumulate in significant amount in the upper troposphere with other precursors, thus enhancing ozone production (see attached figure). While LNOx emission has been included and tuned extensively in global climate models, its inclusions in regional chemistry models are seldom tested. Here we present a study that evaluates the frequently used Price and Rind parameterization based on cloud-top height at resolutions that partially resolve deep convection using the Weather Research and Forecasting model with Chemistry (WRF-Chem) over the contiguous United States. With minor modifications, the parameterization is shown to generate integrated flash counts close to those observed. However, the modeled frequency distribution of cloud-to-ground flashes do not represent well for storms with high flash rates, bringing into question the applicability of the intra-cloud/ground partitioning (IC:CG) formulation of Price and Rind in some studies. Resolution dependency also requires attention when sub-grid cloud-tops are used instead of the originally intended grid-averaged cloud-top. LNOx passive tracers being gathered by monsoonal upper tropospheric anticyclone.

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.

An improved lightning flash rate parameterization developed from Colorado DC3 thunderstorm data for use in cloud-resolving chemical transport models

Science.gov (United States)

Basarab, B. M.; Rutledge, S. A.; Fuchs, B. R.

2015-09-01

Accurate prediction of total lightning flash rate in thunderstorms is important to improve estimates of nitrogen oxides (NOx) produced by lightning (LNOx) from the storm scale to the global scale. In this study, flash rate parameterization schemes from the literature are evaluated against observed total flash rates for a sample of 11 Colorado thunderstorms, including nine storms from the Deep Convective Clouds and Chemistry (DC3) experiment in May-June 2012. Observed flash rates were determined using an automated algorithm that clusters very high frequency radiation sources emitted by electrical breakdown in clouds and detected by the northern Colorado lightning mapping array. Existing schemes were found to inadequately predict flash rates and were updated based on observed relationships between flash rate and simple storm parameters, yielding significant improvement. The most successful updated scheme predicts flash rate based on the radar-derived mixed-phase 35 dBZ echo volume. Parameterizations based on metrics for updraft intensity were also updated but were found to be less reliable predictors of flash rate for this sample of storms. The 35 dBZ volume scheme was tested on a data set containing radar reflectivity volume information for thousands of isolated convective cells in different regions of the U.S. This scheme predicted flash rates to within 5.8% of observed flash rates on average. These results encourage the application of this scheme to larger radar data sets and its possible implementation into cloud-resolving models.

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.

Impact of entrainment on cloud droplet spectra: theory, observations, and modeling

Science.gov (United States)

Grabowski, W.

2016-12-01

Understanding the impact of entrainment and mixing on microphysical properties of warm boundary layer clouds is an important aspect of the representation of such clouds in large-scale models of weather and climate. Entrainment leads to a reduction of the liquid water content in agreement with the fundamental thermodynamics, but its impact on the droplet spectrum is difficult to quantify in observations and modeling. For in-situ (e.g., aircraft) observations, it is impossible to follow air parcels and observe processes that lead to changes of the droplet spectrum in different regions of a cloud. For similar reasons traditional modeling methodologies (e.g., the Eulerian large eddy simulation) are not useful either. Moreover, both observations and modeling can resolve only relatively narrow range of spatial scales. Theory, typically focusing on differences between idealized concepts of homogeneous and inhomogeneous mixing, is also of a limited use for the multiscale turbulent mixing between a cloud and its environment. This presentation will illustrate the above points and argue that the Lagrangian large-eddy simulation with appropriate subgrid-scale scheme may provide key insights and eventually lead to novel parameterizations for large-scale models.

Evaluation of Cloud-Resolving and Limited Area Model Intercomparison Simulations Using TWP-ICE Observations. Part 2 ; Precipitation Microphysics

Science.gov (United States)

Varble, Adam; Zipser, Edward J.; Fridland, Ann M.; Zhu, Ping; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; Shipway, Ben; Williams, Christopher

2014-01-01

Ten 3-D cloud-resolving model (CRM) simulations and four 3-D limited area model (LAM) simulations of an intense mesoscale convective system observed on 23-24 January 2006 during the Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, colocated UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rainwater contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (mu) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes but lower RWCs. Two-moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and, thus, may have issues balancing raindrop formation, collision-coalescence, and raindrop breakup. Assuming a mu of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing mu to have values greater than 0 may improve excessive size sorting in two-moment schemes. Underpredicted stratiform rain rates are associated with underpredicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. A limited domain size also prevents a large, well-developed stratiform region like the one observed from developing in CRMs, although LAMs also fail to produce such a region.

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

Scale analysis of convective clouds

Directory of Open Access Journals (Sweden)

Micha Gryschka

2008-12-01

Full Text Available The size distribution of cumulus clouds due to shallow and deep convection is analyzed using satellite pictures, LES model results and data from the German rain radar network. The size distributions found can be described by simple power laws as has also been proposed for other cloud data in the literature. As the observed precipitation at ground stations is finally determined by cloud numbers in an area and individual sizes and rain rates of single clouds, the cloud size distributions might be used for developing empirical precipitation forecasts or for validating results from cloud resolving models being introduced to routine weather forecasts.

Cloud Feedbacks on Greenhouse Warming in a Multi-Scale Modeling Framework with a Higher-Order Turbulence Closure

Science.gov (United States)

Cheng, Anning; Xu, Kuan-Man

2015-01-01

Five-year simulation experiments with a multi-scale modeling Framework (MMF) with a advanced intermediately prognostic higher-order turbulence closure (IPHOC) in its cloud resolving model (CRM) component, also known as SPCAM-IPHOC (super parameterized Community Atmospheric Model), are performed to understand the fast tropical (30S-30N) cloud response to an instantaneous doubling of CO2 concentration with SST held fixed at present-day values. SPCAM-IPHOC has substantially improved the low-level representation compared with SPCAM. It is expected that the cloud responses to greenhouse warming in SPCAM-IPHOC is more realistic. The change of rising motion, surface precipitation, cloud cover, and shortwave and longwave cloud radiative forcing in SPCAM-IPHOC from the greenhouse warming will be presented in the presentation.

On the discrepancies between theoretical and measured below-cloud particle scavenging coefficients for rain – a numerical investigation using a detailed one-dimensional cloud microphysics model

Directory of Open Access Journals (Sweden)

X. Wang

2011-11-01

Full Text Available Existing theoretical formulations for the size-resolved scavenging coefficient Λ(d for atmospheric aerosol particles scavenged by rain predict values lower by one to two orders of magnitude than those estimated from field measurements of particle-concentration changes for particles smaller than 3 μm in diameter. Vertical turbulence is not accounted for in the theoretical formulations of Λ(d but does contribute to the field-derived estimates of Λ(d due to its influence on the overall concentration changes of aerosol particles in the layers undergoing impaction scavenging. A detailed one-dimensional cloud microphysics model has been used to simulate rain production and below-cloud particle scavenging, and to quantify the contribution of turbulent diffusion to the overall Λ(d values calculated from particle concentration changes. The relative contribution of vertical diffusion to below-cloud scavenging is found to be largest for submicron particles under weak precipitation conditions. The discrepancies between theoretical and field-derived Λ(d values can largely be explained by the contribution of vertical diffusion to below-cloud particle scavenging for all particles larger than 0.01 μm in diameter for which field data are available. The results presented here suggest that the current theoretical framework for Λ(d can provide a reasonable approximation of below-cloud aerosol particle scavenging by rain in size-resolved aerosol transport models if vertical diffusion is also considered by the models.

UCLALES-SALSA v1.0: a large-eddy model with interactive sectional microphysics for aerosol, clouds and precipitation

Science.gov (United States)

Tonttila, Juha; Maalick, Zubair; Raatikainen, Tomi; Kokkola, Harri; Kühn, Thomas; Romakkaniemi, Sami

2017-01-01

Challenges in understanding the aerosol-cloud interactions and their impacts on global climate highlight the need for improved knowledge of the underlying physical processes and feedbacks as well as their interactions with cloud and boundary layer dynamics. To pursue this goal, increasingly sophisticated cloud-scale models are needed to complement the limited supply of observations of the interactions between aerosols and clouds. For this purpose, a new large-eddy simulation (LES) model, coupled with an interactive sectional description for aerosols and clouds, is introduced. The new model builds and extends upon the well-characterized UCLA Large-Eddy Simulation Code (UCLALES) and the Sectional Aerosol module for Large-Scale Applications (SALSA), hereafter denoted as UCLALES-SALSA. Novel strategies for the aerosol, cloud and precipitation bin discretisation are presented. These enable tracking the effects of cloud processing and wet scavenging on the aerosol size distribution as accurately as possible, while keeping the computational cost of the model as low as possible. The model is tested with two different simulation set-ups: a marine stratocumulus case in the DYCOMS-II campaign and another case focusing on the formation and evolution of a nocturnal radiation fog. It is shown that, in both cases, the size-resolved interactions between aerosols and clouds have a critical influence on the dynamics of the boundary layer. The results demonstrate the importance of accurately representing the wet scavenging of aerosol in the model. Specifically, in a case with marine stratocumulus, precipitation and the subsequent removal of cloud activating particles lead to thinning of the cloud deck and the formation of a decoupled boundary layer structure. In radiation fog, the growth and sedimentation of droplets strongly affect their radiative properties, which in turn drive new droplet formation. The size-resolved diagnostics provided by the model enable investigations of these

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

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

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

Transforming the representation of the boundary layer and low clouds for high-resolution regional climate modeling: Final report

Energy Technology Data Exchange (ETDEWEB)

Hall, Alex [University of California, Los Angeles, CA (United States). Joint Institute for Regional Earth System Science and Engineering

2013-07-24

Stratocumulus and shallow cumulus clouds in subtropical oceanic regions (e.g., Southeast Pacific) cover thousands of square kilometers and play a key role in regulating global climate (e.g., Klein and Hartmann, 1993). Numerical modeling is an essential tool to study these clouds in regional and global systems, but the current generation of climate and weather models has difficulties in representing them in a realistic way (e.g., Siebesma et al., 2004; Stevens et al., 2007; Teixeira et al., 2011). While numerical models resolve the large-scale flow, subgrid-scale parameterizations are needed to estimate small-scale properties (e.g. boundary layer turbulence and convection, clouds, radiation), which have significant influence on the resolved scale due to the complex nonlinear nature of the atmosphere. To represent the contribution of these fine-scale processes to the resolved scale, climate models use various parameterizations, which are the main pieces in the model that contribute to the low clouds dynamics and therefore are the major sources of errors or approximations in their representation. In this project, we aim to 1) improve our understanding of the physical processes in thermal circulation and cloud formation, 2) examine the performance and sensitivity of various parameterizations in the regional weather model (Weather Research and Forecasting model; WRF), and 3) develop, implement, and evaluate the advanced boundary layer parameterization in the regional model to better represent stratocumulus, shallow cumulus, and their transition. Thus, this project includes three major corresponding studies. We find that the mean diurnal cycle is sensitive to model domain in ways that reveal the existence of different contributions originating from the Southeast Pacific land-masses. The experiments suggest that diurnal variations in circulations and thermal structures over this region are influenced by convection over the Peruvian sector of the Andes cordillera, while

Counting the clouds

International Nuclear Information System (INIS)

Randall, David A

2005-01-01

Cloud processes are very important for the global circulation of the atmosphere. It is now possible, though very expensive, to simulate the global circulation of the atmosphere using a model with resolution fine enough to explicitly represent the larger individual clouds. An impressive preliminary calculation of this type has already been performed by Japanese scientists, using the Earth Simulator. Within the next few years, such global cloud-resolving models (GCRMs) will be applied to weather prediction, and later they will be used in climatechange simulations. The tremendous advantage of GCRMs, relative to conventional lowerresolution global models, is that GCRMs can avoid many of the questionable 'parameterizations' used to represent cloud effects in lower-resolution global models. Although cloud microphysics, turbulence, and radiation must still be parameterized in GCRMs, the high resolution of a GCRM simplifies these problems considerably, relative to conventional models. The United States currently has no project to develop a GCRM, although we have both the computer power and the expertise to do it. A research program aimed at development and applications of GCRMs is outlined

Improving the Understanding and Model Representation of Processes that Couple Shallow Clouds, Aerosols, and Land-Ecosystems

Science.gov (United States)

Fast, J. D.; Berg, L. K.; Schmid, B.; Alexander, M. L. L.; Bell, D.; D'Ambro, E.; Hubbe, J. M.; Liu, J.; Mei, F.; Pekour, M. S.; Pinterich, T.; Schobesberger, S.; Shilling, J.; Springston, S. R.; Thornton, J. A.; Tomlinson, J. M.; Wang, J.; Zelenyuk, A.

2016-12-01

Cumulus convection is an important component in the atmospheric radiation budget and hydrologic cycle over the southern Great Plains and over many regions of the world, particularly during the summertime growing season when intense turbulence induced by surface radiation couples the land surface to clouds. Current convective cloud parameterizations, however, contain uncertainties resulting from insufficient coincident data that couples cloud macrophysical and microphysical properties to inhomogeneity in surface layer, boundary layer, and aerosol properties. We describe the measurement strategy and preliminary findings from the recent Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign conducted in May and September of 2016 in the vicinity of the DOE's Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site located in Oklahoma. The goal of the HI-SCALE campaign is to provide a detailed set of aircraft and surface measurements needed to obtain a more complete understanding and improved parameterizations of the lifecycle of shallow clouds. The sampling is done in two periods, one in the spring and the other in the late summer to take advantage of variations in the "greenness" for various types of vegetation, new particle formation, anthropogenic enhancement of biogenic secondary organic aerosol (SOA), and other aerosol properties. The aircraft measurements will be coupled with extensive routine ARM SGP measurements as well as Large Eddy Simulation (LES), cloud resolving, and cloud-system resolving models. Through these integrated analyses and modeling studies, the affects of inhomogeneity in land use, vegetation, soil moisture, convective eddies, and aerosol properties on the evolution of shallow clouds will be determined, including the feedbacks of cloud radiative effects.

Development and testing of an aerosol-stratus cloud parameterization scheme for middle and high latitudes

Energy Technology Data Exchange (ETDEWEB)

Olsson, P.Q.; Meyers, M.P.; Kreidenweis, S.; Cotton, W.R. [Colorado State Univ., Fort Collins, CO (United States)

1996-04-01

The aim of this new project is to develop an aerosol/cloud microphysics parameterization of mixed-phase stratus and boundary layer clouds. Our approach is to create, test, and implement a bulk-microphysics/aerosol model using data from Atmospheric Radiation Measurement (ARM) Cloud and Radiation Testbed (CART) sites and large-eddy simulation (LES) explicit bin-resolving aerosol/microphysics models. The primary objectives of this work are twofold. First, we need the prediction of number concentrations of activated aerosol which are transferred to the droplet spectrum, so that the aerosol population directly affects the cloud formation and microphysics. Second, we plan to couple the aerosol model to the gas and aqueous-chemistry module that will drive the aerosol formation and growth. We begin by exploring the feasibility of performing cloud-resolving simulations of Arctic stratus clouds over the North Slope CART site. These simulations using Colorado State University`s regional atmospheric modeling system (RAMS) will be useful in designing the structure of the cloud-resolving model and in interpreting data acquired at the North Slope site.

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

An Optical Lightning Simulator in an Electrified Cloud-Resolving Model to Prepare the Future Space Lightning Missions

Science.gov (United States)

Bovalo, Christophe; Defer, Eric; Pinty, Jean-Pierre

2016-04-01

The future decade will see the launch of several space missions designed to monitor the total lightning activity. Among these missions, the American (Geostationary Lightning Mapper - GLM) and European (Lightning Imager - LI) optical detectors will be onboard geostationary satellites (GOES-R and MTG, respectively). For the first time, the total lightning activity will be monitored over the full Earth disk and at a very high temporal resolution (2 and 1 ms, respectively). Missions like the French Tool for the Analysis of Radiation from lightNIng and Sprites (TARANIS) and ISS-LIS will bring complementary information in order to better understand the lightning physics and to improve the weather prediction (nowcasting and forecasting). Such missions will generate a huge volume of new and original observations for the scientific community and weather prediction centers that have to be prepared. Moreover, before the launch of these missions, fundamental questions regarding the interpretation of the optical signal property and its relation to cloud optical thickness and lightning discharge processes need to be further investigated. An innovative approach proposed here is to use the synergy existing in the French MesoNH Cloud-Resolving Model (CRM). Indeed, MesoNH is one of the only CRM able to simulate the lifecycle of electrical charges generated within clouds through non-inductive charging process (dependent of the 1-moment microphysical scheme). The lightning flash geometry is based on a fractal law while the electrical field is diagnosed thanks to the Gauss' law. The lightning optical simulator is linked to the electrical scheme as the lightning radiance at 777.4 nm is a function of the lightning current, approximated by the charges neutralized along the lightning path. Another important part is the scattering of this signal by the hydrometeors (mainly ice particles) that is taken into account. Simulations at 1-km resolution are done over the Langmuir Laboratory (New

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.

Why do general circulation models overestimate the aerosol cloud lifetime effect? A case study comparing CAM5 and a CRM

Science.gov (United States)

Zhou, Cheng; Penner, Joyce E.

2017-01-01

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 27 May 2011 at the southern Great Plains (SGP) measurement site established by the Department of Energy's (DOE) 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 the 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.

Classification of Clouds and Deep Convection from GEOS-5 Using Satellite Observations

Science.gov (United States)

Putman, William; Suarez, Max

2010-01-01

With the increased resolution of global atmospheric models and the push toward global cloud resolving models, the resemblance of model output to satellite observations has become strikingly similar. As we progress with our adaptation of the Goddard Earth Observing System Model, Version 5 (GEOS-5) as a high resolution cloud system resolving model, evaluation of cloud properties and deep convection require in-depth analysis beyond a visual comparison. Outgoing long-wave radiation (OLR) provides a sufficient comparison with infrared (IR) satellite imagery to isolate areas of deep convection. We have adopted a binning technique to generate a series of histograms for OLR which classify the presence and fraction of clear sky versus deep convection in the tropics that can be compared with a similar analyses of IR imagery from composite Geostationary Operational Environmental Satellite (GOES) observations. We will present initial results that have been used to evaluate the amount of deep convective parameterization required within the model as we move toward cloud system resolving resolutions of 10- to 1-km globally.

Evaluating Microphysics in Cloud-Resolving Models using TRMM and Ground-based Precipitation Radar Observations

Science.gov (United States)

Krueger, S. K.; Zulauf, M. A.; Li, Y.; Zipser, E. J.

2005-05-01

Global satellite datasets such as those produced by ISCCP, ERBE, and CERES provide strong observational constraints on cloud radiative properties. Such observations have been widely used for model evaluation, tuning, and improvement. Cloud radiative properties depend primarily on small, non-precipitating cloud droplets and ice crystals, yet the dynamical, microphysical and radiative processes which produce these small particles often involve large, precipitating hydrometeors. There now exists a global dataset of tropical cloud system precipitation feature (PF) properties, collected by TRMM and produced by Steve Nesbitt, that provides additional observational constraints on cloud system properties. We are using the TRMM PF dataset to evaluate the precipitation microphysics of two simulations of deep, precipitating, convective cloud systems: one is a 29-day summertime, continental case (ARM Summer 1997 SCM IOP, at the Southern Great Plains site); the second is a tropical maritime case: the Kwajalein MCS of 11-12 August 1999 (part of a 52-day simulation). Both simulations employed the same bulk, three-ice category microphysical parameterization (Krueger et al. 1995). The ARM simulation was executed using the UCLA/Utah 2D CRM, while the KWAJEX simulation was produced using the 3D CSU CRM (SAM). The KWAJEX simulation described above is compared with both the actual radar data and the TRMM statistics. For the Kwajalein MCS of 11 to 12 August 1999, there are research radar data available for the lifetime of the system. This particular MCS was large in size and rained heavily, but it was weak to average in measures of convective intensity, against the 5-year TRMM sample of 108. For the Kwajalein MCS simulation, the 20 dBZ contour is at 15.7 km and the 40 dBZ contour at 14.5 km! Of all 108 MCSs observed by TRMM, the highest value for the 40 dBZ contour is 8 km. Clearly, the high reflectivity cores are off scale compared with observed cloud systems in this area. A similar

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.

Effects of model resolution and parameterizations on the simulations of clouds, precipitation, and their interactions with aerosols

Science.gov (United States)

Lee, Seoung Soo; Li, Zhanqing; Zhang, Yuwei; Yoo, Hyelim; Kim, Seungbum; Kim, Byung-Gon; Choi, Yong-Sang; Mok, Jungbin; Um, Junshik; Ock Choi, Kyoung; Dong, Danhong

2018-01-01

This study investigates the roles played by model resolution and microphysics parameterizations in the well-known uncertainties or errors in simulations of clouds, precipitation, and their interactions with aerosols by the numerical weather prediction (NWP) models. For this investigation, we used cloud-system-resolving model (CSRM) simulations as benchmark simulations that adopt high-resolution and full-fledged microphysical processes. These simulations were evaluated against observations, and this evaluation demonstrated that the CSRM simulations can function as benchmark simulations. Comparisons between the CSRM simulations and the simulations at the coarse resolutions that are generally adopted by current NWP models indicate that the use of coarse resolutions as in the NWP models can lower not only updrafts and other cloud variables (e.g., cloud mass, condensation, deposition, and evaporation) but also their sensitivity to increasing aerosol concentration. The parameterization of the saturation process plays an important role in the sensitivity of cloud variables to aerosol concentrations. while the parameterization of the sedimentation process has a substantial impact on how cloud variables are distributed vertically. The variation in cloud variables with resolution is much greater than what happens with varying microphysics parameterizations, which suggests that the uncertainties in the NWP simulations are associated with resolution much more than microphysics parameterizations.

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.

Observations and Model Simulations of Orographic Mixed-Phase Clouds at Mountain Range Site

Science.gov (United States)

Lohmann, U.; Henneberg, O. C.; Henneberger, J.

2014-12-01

Aerosol-cloud interactions constitute the highest uncertainties in forcing estimation. Especially uncertainties due to mixed clouds (MPCs) have a large impact on the radiative balance and precipitation prediction. Due to Wegener-Bergeron-Findeisen-process (WBF) which describes glaciation of MPCs due to the lower saturation over ice than over water, MPCs are mostly expected as short lived clouds. In contrast to the theory of the WBF, in-situ measurements have shown that MPCs can persist over longer time. But only a small number of measurements of MPCs is available. In addition modeling studies about MPCs are difficult as their processes of the three-phase-system are on the micro scale and therefore not resolved in models. We present measurements obtained at the high-altitude research station Jungfraujoch (JFJ, 3580 m asl) in the Swiss Alps partly taken during the CLoud-Aerosol Interaction Experiments (CLACE). During the winter season, the JFJ has a high frequency of super-cooled clouds and is considered representative for being in the free troposphere. In-situ measurements of the microstructure of MPCs have been obtained with the digital imager HOLIMO, that delivers phase-resolved size distributions, concentrations, and water contents. The data set of MPCs at JFJ shows that for northerly wind cases partially-glaciated MPCs are more frequently observed than for southerly wind cases. The higher frequency of these intermediate states of MPCs suggests either higher updraft velocities, and therefore higher water-vapor supersaturations, or the absence of sufficiently high IN concentrations to quickly glaciate the MPC. Because of the limitation of in-situ information, i.e. point measurements and missing measurements of vertical velocities at JFJ, the mechanism of the long persistence of MPCs cannot be fully understood. Therefore, in addition to measurements we will investigate the JFJ region with a model study with the non-hydrostatic model COSMO-ART-M7. Combination of km

Jupiter's Deep Cloud Structure Revealed Using Keck Observations of Spectrally Resolved Line Shapes

Science.gov (United States)

Bjoraker, G. L.; Wong, M.H.; de Pater, I.; Adamkovics, M.

2015-01-01

Technique: We present a method to determine the pressure at which significant cloud opacity is present between 2 and 6 bars on Jupiter. We use: a) the strength of a Fraunhofer absorption line in a zone to determine the ratio of reflected sunlight to thermal emission, and b) pressure- broadened line profiles of deuterated methane (CH3D) at 4.66 meters to determine the location of clouds. We use radiative transfer models to constrain the altitude region of both the solar and thermal components of Jupiter's 5-meter spectrum. Results: For nearly all latitudes on Jupiter the thermal component is large enough to constrain the deep cloud structure even when upper clouds are present. We find that Hot Spots, belts, and high latitudes have broader line profiles than do zones. Radiative transfer models show that Hot Spots in the North and South Equatorial Belts (NEB, SEB) typically do not have opaque clouds at pressures greater than 2 bars. The South Tropical Zone (STZ) at 32 degrees South has an opaque cloud top between 4 and 5 bars. From thermochemical models this must be a water cloud. We measured the variation of the equivalent width of CH3D with latitude for comparison with Jupiter's belt-zone structure. We also constrained the vertical profile of H2O in an SEB Hot Spot and in the STZ. The Hot Spot is very dry for a probability less than 4.5 bars and then follows the H2O profile observed by the Galileo Probe. The STZ has a saturated H2O profile above its cloud top between 4 and 5 bars.

A systematic comparison of two-equation Reynolds-averaged Navier-Stokes turbulence models applied to shock-cloud interactions

Science.gov (United States)

Goodson, Matthew D.; Heitsch, Fabian; Eklund, Karl; Williams, Virginia A.

2017-07-01

Turbulence models attempt to account for unresolved dynamics and diffusion in hydrodynamical simulations. We develop a common framework for two-equation Reynolds-averaged Navier-Stokes turbulence models, and we implement six models in the athena code. We verify each implementation with the standard subsonic mixing layer, although the level of agreement depends on the definition of the mixing layer width. We then test the validity of each model into the supersonic regime, showing that compressibility corrections can improve agreement with experiment. For models with buoyancy effects, we also verify our implementation via the growth of the Rayleigh-Taylor instability in a stratified medium. The models are then applied to the ubiquitous astrophysical shock-cloud interaction in three dimensions. We focus on the mixing of shock and cloud material, comparing results from turbulence models to high-resolution simulations (up to 200 cells per cloud radius) and ensemble-averaged simulations. We find that the turbulence models lead to increased spreading and mixing of the cloud, although no two models predict the same result. Increased mixing is also observed in inviscid simulations at resolutions greater than 100 cells per radius, which suggests that the turbulent mixing begins to be resolved.

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.

Storm and cloud dynamics

CERN Document Server

Cotton, William R

1992-01-01

This book focuses on the dynamics of clouds and of precipitating mesoscale meteorological systems. Clouds and precipitating mesoscale systems represent some of the most important and scientifically exciting weather systems in the world. These are the systems that produce torrential rains, severe winds including downburst and tornadoes, hail, thunder and lightning, and major snow storms. Forecasting such storms represents a major challenge since they are too small to be adequately resolved by conventional observing networks and numerical prediction models.Key Features* Key Highlight

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...

Projection of the change in future extremes over Japan using a cloud-resolving model: (2) Precipitation Extremes and the results of the NHM-1km experiments

Science.gov (United States)

Kanada, S.; Nakano, M.; Nakamura, M.; Hayashi, S.; Kato, T.; Kurihara, K.; Sasaki, H.; Uchiyama, T.; Aranami, K.; Honda, Y.; Kitoh, A.

2008-12-01

In order to study changes in the regional climate in the vicinity of Japan during the summer rainy season due to global warming, experiments by a semi-cloud resolving non-hydrostatic model with a horizontal resolution of 5km (NHM-5km) have been conducted from June to October by nesting within the results of the 10-year time-integrated experiments using a hydrostatic atmospheric general circulation model with a horizontal grid of 20 km (AGCM-20km: TL959L60) for the present and future up to the year 2100. A non-hydrostatic model developed by the Japan Meteorological Agency (JMA) (JMA-NHM; Saito et al. 2001, 2006) was adopted. Detailed descriptions of the NHM-5km are shown by the poster of Nakano et al. Our results show that rainy days over most of the Japanese Islands will decrease in June and July and increase in August and September in the future climate. Especially, remarkable increases in intense precipitations such as larger than 150 - 300 mm/day are projected from the present to future climate. The 90th percentiles of regional largest values among maximum daily precipitations (R-MDPs) grow 156 to 207 mm/day in the present and future climates, respectively. It is well-known that the horizontal distribution of precipitation, especially the heavy rainfall in the vicinity of Japan, much depends on the topography. Therefore, higher resolution experiments by a cloud-resolving model with a horizontal resolution of 1km (NHM-1km) are one-way nested within the results of NHM-5km. The basic frame and design of the NHM-1km is the same as those of the NHM-5km, but the topography is finer and no cumulus parameterization is used in the NHM-1km experiments. The NHM-1km, which treats the convection and cloud microphysics explicitly, can represent not only horizontal distributions of rainfall in detail but also the 3-dimensional structures of meso-beta-scale convective systems (MCSs). Because of the limitation of computation resources, only heavy rainfall events that rank in top

Electron Cloud Buildup Characterization Using Shielded Pickup Measurements and Custom Modeling Code at CESRTA

CERN Document Server

Crittenden, James A

2013-01-01

The Cornell Electron Storage Ring Test Accelerator experimental program includes investigations into electron cloud buildup, applying various mitigation techniques in custom vacuum chambers. Among these are two 1.1-m-long sections located symmetrically in the east and west arc regions. These chambers are equipped with pickup detectors shielded against the direct beam-induced signal. They detect cloud electrons migrating through an 18-mm-diameter pattern of small holes in the top of the chamber. A digitizing oscilloscope is used to record the signals, providing time-resolved information on cloud development. Carbon-coated, TiN-coated and uncoated aluminum chambers have been tested. Electron and positron beams of 2.1, 4.0 and 5.3 GeV with a variety of bunch populations and spacings in steps of 4 and 14 ns have been used. Here we report on results from the ECLOUD modeling code which highlight the sensitivity of these measurements to the physical phenomena determining cloud buildup such as the photoelectron produ...

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

Science.gov (United States)

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

2017-07-01

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

Fast Cloud Adjustment to Increasing CO2 in a Superparameterized Climate Model

Directory of Open Access Journals (Sweden)

Marat Khairoutdinov

2012-05-01

Full Text Available Two-year simulation experiments with a superparameterized climate model, SP-CAM, are performed to understand the fast tropical (30S-30N cloud response to an instantaneous quadrupling of CO2 concentration with SST held fixed at present-day values.The greenhouse effect of the CO2 perturbation quickly warms the tropical land surfaces by an average of 0.5 K. This shifts rising motion, surface precipitation, and cloud cover at all levels from the ocean to the land, with only small net tropical-mean cloud changes. There is a widespread average reduction of about 80 m in the depth of the trade inversion capping the marine boundary layer (MBL over the cooler subtropical oceans.One apparent contributing factor is CO2-enhanced downwelling longwave radiation, which reduces boundary-layer radiative cooling, a primary driver of turbulent entrainment through the trade inversion. A second contributor is a slight CO2-induced heating of the free troposphere above the MBL, which strengthens the trade inversion and also inhibits entrainment. There is a corresponding downward displacement of MBL clouds with a very slight decrease in mean cloud cover and albedo.Two-dimensional cloud-resolving model (CRM simulations of this MBL response are run to steady state using composite SP-CAM simulated thermodynamic and wind profiles from a representative cool subtropical ocean regime, for the control and 4xCO2 cases. Simulations with a CRM grid resolution equal to that of SP-CAM are compared with much finer resolution simulations. The coarse-resolution simulations maintain a cloud fraction and albedo comparable to SP-CAM, but the fine-resolution simulations have a much smaller cloud fraction. Nevertheless, both CRM configurations simulate a reduction in inversion height comparable to SP-CAM. The changes in low cloud cover and albedo in the CRM simulations are small, but both simulations predict a slight reduction in low cloud albedo as in SP-CAM.

Cloud's Center of Gravity – a compact approach to analyze convective cloud development

Directory of Open Access Journals (Sweden)

I. Koren

2009-01-01

Full Text Available As cloud resolving models become more detailed, with higher resolution outputs, it is often complicated to isolate the physical processes that control the cloud attributes. Moreover, due to the high dimensionality and complexity of the model output, the analysis and interpretation of the results can be very complicated. Here we suggest a novel approach to convective cloud analysis that yields more insight into the physical and temporal evolution of clouds, and is compact and efficient. The different (3-D cloud attributes are weighted and projected onto a single point in space and in time, that has properties of, or similar to, the Center Of Gravity (COG. The location, magnitude and spread of this variable are followed in time. The implications of the COG approach are demonstrated for a study of aerosol effects on a warm convective cloud. We show that in addition to reducing dramatically the dimensionality of the output, such an approach often enhances the signal, adds more information, and makes the physical description of cloud evolution clearer, allowing unambiguous comparison of clouds evolving in different environmental conditions. This approach may also be useful for analysis of cloud data retrieved from surface or space-based cloud radars.

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...

A Numerical Study of Vortex and Precipitating Cloud Merging in Middle Latitudes

Institute of Scientific and Technical Information of China (English)

PING Fan; LUO Zhe-Xian; JU Jian-Hua

2006-01-01

@@ We mainly focus on the study of precipitating cloud merging associated with vortex merging. The vortex and precipitating cloud merging are simulated by the cloud resolving model from 0000 21 to 1800 23 July 2003. The results show that the model well simulates vortex circulation associated with precipitating clouds. It is also proven that the vortex merging follows the precipitating cloud merging although vortices show the spatial and temporal differences. The convection vorticity vector is introduced to describe the merging processes. Two merging cases are identified during the 42-h simulation and are studied.

Toward Quantitative Estimation of the Effect of Aerosol Particles in the Global Climate Model and Cloud Resolving Model

Science.gov (United States)

Eskes, H.; Boersma, F.; Dirksen, R.; van der A, R.; Veefkind, P.; Levelt, P.; Brinksma, E.; van Roozendael, M.; de Smedt, I.; Gleason, J.

2005-05-01

Based on measurements of GOME on ESA ERS-2, SCIAMACHY on ESA-ENVISAT, and Ozone Monitoring Instrument (OMI) on the NASA EOS-Aura satellite there is now a unique 11-year dataset of global tropospheric nitrogen dioxide measurements from space. The retrieval approach consists of two steps. The first step is an application of the DOAS (Differential Optical Absorption Spectroscopy) approach which delivers the total absorption optical thickness along the light path (the slant column). For GOME and SCIAMACHY this is based on the DOAS implementation developed by BIRA/IASB. For OMI the DOAS implementation was developed in a collaboration between KNMI and NASA. The second retrieval step, developed at KNMI, estimates the tropospheric vertical column of NO2 based on the slant column, cloud fraction and cloud top height retrieval, stratospheric column estimates derived from a data assimilation approach and vertical profile estimates from space-time collocated profiles from the TM chemistry-transport model. The second step was applied with only minor modifications to all three instruments to generate a uniform 11-year data set. In our talk we will address the following topics: - A short summary of the retrieval approach and results - Comparisons with other retrievals - Comparisons with global and regional-scale models - OMI-SCIAMACHY and SCIAMACHY-GOME comparisons - Validation with independent measurements - Trend studies of NO2 for the past 11 years

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

Low-level stratocumulus (Sc) clouds cover more of the Earth's surface than any other cloud type rendering them critical for Earth's energy balance, primarily via reflection of solar radiation, as well as their role in the global hydrological cycle. Stratocumuli are particularly sensitive to changes in aerosol loading on both microphysical and macrophysical scales, yet the complex feedbacks involved in aerosol-cloud-precipitation interactions remain poorly understood. Moreover, research on these clouds has largely been confined to marine environments, with far fewer studies over land where major sources of anthropogenic aerosols exist. The aerosol burden over Southeast Asia (SEA) in boreal spring, attributed to biomass burning (BB), exhibits highly consistent spatiotemporal distribution patterns, with major variability due to changes in aerosol loading mediated by processes ranging from large-scale climate factors to diurnal meteorological events. Downwind from source regions, the transported BB aerosols often overlap with low-level Sc cloud decks associated with the development of the region's pre-monsoon system, providing a unique, natural laboratory for further exploring their complex micro- and macro-scale relationships. Compared to other locations worldwide, studies of springtime biomass-burning aerosols and the predominately Sc cloud systems over SEA and their ensuing interactions are underrepresented in scientific literature. Measurements of aerosol and cloud properties, whether ground-based or from satellites, generally lack information on microphysical processes; thus cloud-resolving models are often employed to simulate the underlying physical processes in aerosol-cloud-precipitation interactions. The Goddard Cumulus Ensemble (GCE) cloud model has recently been enhanced with a triple-moment (3M) bulk microphysics scheme as well as the Regional Atmospheric Modeling System (RAMS) version 6 aerosol module. Because the aerosol burden not only affects cloud

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...

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

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?: NUDGING AND MODEL SENSITIVITIES

Energy Technology Data Exchange (ETDEWEB)

Lin, Guangxing [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Wan, Hui [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Zhang, Kai [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA; Ghan, Steven J. [Pacific Northwest National Laboratory, Atmospheric Science and Global Change Division, Richland Washington USA

2016-07-10

Efficient simulation strategies are crucial for the development and evaluation of high resolution climate models. This paper evaluates simulations with constrained meteorology for the quantification of parametric sensitivities in the Community Atmosphere Model version 5 (CAM5). Two parameters are perturbed as illustrating examples: the convection relaxation time scale (TAU), and the threshold relative humidity for the formation of low-level stratiform clouds (rhminl). Results suggest that the fidelity and computational efficiency of the constrained simulations depend strongly on 3 factors: the detailed implementation of nudging, the mechanism through which the perturbed parameter affects precipitation and cloud, and the magnitude of the parameter perturbation. In the case of a strong perturbation in convection, temperature and/or wind nudging with a 6-hour relaxation time scale leads to non-negligible side effects due to the distorted interactions between resolved dynamics and parameterized convection, while a 1-year free running simulation can satisfactorily capture the annual mean precipitation sensitivity in terms of both global average and geographical distribution. In the case of a relatively weak perturbation the large-scale condensation scheme, results from 1-year free-running simulations are strongly affected by noise associated with internal variability, while nudging winds effectively reduces the noise, and reasonably reproduces the response of precipitation and cloud forcing to parameter perturbation. These results indicate that caution is needed when using nudged simulations to assess precipitation and cloud forcing sensitivities to parameter changes in general circulation models. We also demonstrate that ensembles of short simulations are useful for understanding the evolution of model sensitivities.

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...

Evaluation of convection-resolving models using satellite data: The diurnal cycle of summer convection over the Alps

Directory of Open Access Journals (Sweden)

Michael Keller

2016-05-01

Full Text Available Diurnal moist convection is an important element of summer precipitation over Central Europe and the Alps. It is poorly represented in models using parameterized convection. In this study, we investigate the diurnal cycle of convection during 11 days in June 2007 using the COSMO model. The numerical simulations are compared with satellite measurements of GERB and SEVIRI, AVHRR satellite-based cloud properties and ground-based precipitation and temperature measurements. The simulations use horizontal resolutions of 12 km (convection-parameterizing model, CPM and 2 km (convection-resolving model, CRM and either a one-moment microphysics scheme (1M or a two-moment microphysics scheme (2M.They are conducted for a computational domain that covers an extended Alpine area from Northern Italy to Northern Germany. The CPM with 1M exhibits a significant overestimation of high cloud cover. This results in a compensation effect in the top of the atmosphere energy budget due to an underestimation of outgoing longwave radiation (OLR and an overestimation of reflected solar radiation (RSR. The CRM reduces high cloud cover and improves the OLR bias from a domain mean of −20.1 to −2.6 W/m2. When using 2M with ice sedimentation in the CRM, high cloud cover is further reduced. The stronger diurnal cycle of high cloud cover and associated convection over the Alps, compared to less mountainous regions, is well represented by the CRM but underestimated by the CPM. Despite substantial differences in high cloud cover, the use of a 2M has no significant impact on the diurnal cycle of precipitation. Furthermore, a negative mid-level cloud bias is found for all simulations.

Direct Scaling of Leaf-Resolving Biophysical Models from Leaves to Canopies

Science.gov (United States)

Bailey, B.; Mahaffee, W.; Hernandez Ochoa, M.

2017-12-01

Recent advances in the development of biophysical models and high-performance computing have enabled rapid increases in the level of detail that can be represented by simulations of plant systems. However, increasingly detailed models typically require increasingly detailed inputs, which can be a challenge to accurately specify. In this work, we explore the use of terrestrial LiDAR scanning data to accurately specify geometric inputs for high-resolution biophysical models that enables direct up-scaling of leaf-level biophysical processes. Terrestrial LiDAR scans generate "clouds" of millions of points that map out the geometric structure of the area of interest. However, points alone are often not particularly useful in generating geometric model inputs, as additional data processing techniques are required to provide necessary information regarding vegetation structure. A new method was developed that directly reconstructs as many leaves as possible that are in view of the LiDAR instrument, and uses a statistical backfilling technique to ensure that the overall leaf area and orientation distribution matches that of the actual vegetation being measured. This detailed structural data is used to provide inputs for leaf-resolving models of radiation, microclimate, evapotranspiration, and photosynthesis. Model complexity is afforded by utilizing graphics processing units (GPUs), which allows for simulations that resolve scales ranging from leaves to canopies. The model system was used to explore how heterogeneity in canopy architecture at various scales affects scaling of biophysical processes from leaves to canopies.

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.

Technical note: Fu-Liou-Gu and Corti-Peter model performance evaluation for radiative retrievals from cirrus clouds

Science.gov (United States)

Lolli, Simone; Campbell, James R.; Lewis, Jasper R.; Gu, Yu; Welton, Ellsworth J.

2017-06-01

We compare, for the first time, the performance of a simplified atmospheric radiative transfer algorithm package, the Corti-Peter (CP) model, versus the more complex Fu-Liou-Gu (FLG) model, for resolving top-of-the-atmosphere radiative forcing characteristics from single-layer cirrus clouds obtained from the NASA Micro-Pulse Lidar Network database in 2010 and 2011 at Singapore and in Greenbelt, Maryland, USA, in 2012. Specifically, CP simplifies calculation of both clear-sky longwave and shortwave radiation through regression analysis applied to radiative calculations, which contributes significantly to differences between the two. The results of the intercomparison show that differences in annual net top-of-the-atmosphere (TOA) cloud radiative forcing can reach 65 %. This is particularly true when land surface temperatures are warmer than 288 K, where the CP regression analysis becomes less accurate. CP proves useful for first-order estimates of TOA cirrus cloud forcing, but may not be suitable for quantitative accuracy, including the absolute sign of cirrus cloud daytime TOA forcing that can readily oscillate around zero globally.

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.

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.

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.

Intercomparison of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds

Science.gov (United States)

Muhlbauer, A.; Hashino, T.; Xue, L.; Teller, A.; Lohmann, U.; Rasmussen, R. M.; Geresdi, I.; Pan, Z.

2010-09-01

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analysed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as coalescence, aggregation, riming and diffusional growth to changes in the aerosol number concentrations are evaluated and compared. The participating numerical models are the model from the Consortium for Small-Scale Modeling (COSMO) with bulk microphysics, the Weather Research and Forecasting (WRF) model with bin microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others, which implies that a decrease in riming with increasing aerosol load is not a robust result

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.

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.

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.

The sensitivities of in cloud and cloud top phase distributions to primary ice formation in ICON-LEM

Science.gov (United States)

Beydoun, H.; Karrer, M.; Tonttila, J.; Hoose, C.

2017-12-01

Mixed phase clouds remain a leading source of uncertainty in our attempt to quantify cloud-climate and aerosol-cloud climate interactions. Nevertheless, recent advances in parametrizing the primary ice formation process, high resolution cloud modelling, and retrievals of cloud phase distributions from satellite data offer an excellent opportunity to conduct closure studies on the sensitivity of the cloud phase to microphysical and dynamical processes. Particularly, the reliability of satellite data to resolve the phase at the top of the cloud provides a promising benchmark to compare model output to. We run large eddy simulations with the new ICOsahedral Non-hydrostatic atmosphere model (ICON) to place bounds on the sensitivity of in cloud and cloud top phase to the primary ice formation process. State of the art primary ice formation parametrizations in the form of the cumulative ice active site density ns are implemented in idealized deep convective cloud simulations. We exploit the ability of ICON-LEM to switch between a two moment microphysics scheme and the newly developed Predicted Particle Properties (P3) scheme by running our simulations in both configurations for comparison. To quantify the sensitivity of cloud phase to primary ice formation, cloud ice content is evaluated against order of magnitude changes in ns at variable convective strengths. Furthermore, we assess differences between in cloud and cloud top phase distributions as well as the potential impact of updraft velocity on the suppression of the Wegener-Bergeron-Findeisen process. The study aims to evaluate our practical understanding of primary ice formation in the context of predicting the structure and evolution of mixed phase clouds.

Resolving both entrainment-mixing and number of activated CCN in deep convective clouds

Directory of Open Access Journals (Sweden)

E. Freud

2011-12-01

the cloud is pre-moistened by total evaporation of cloud droplets before it mixes deeper into the clouds where it can hardly change the droplet size distribution, hence R_e remains close to its adiabatic value at any given cloud depth. However, the tendency towards the extreme inhomogeneous mixing appeared to slightly decrease with altitude, possibly due to enhanced turbulence and larger cloud drops aloft.

Quantifying these effects, based on more examples from other projects and high resolution cloud models is essential for improving our understanding of the interactions between the cloud and its environment. These interactions may play an important role in cloud dynamics and microphysics, by affecting cloud depth and droplet size spectra, for example, and may therefore influence the cloud precipitation formation processes.

Particle backscatter and relative humidity measured across cirrus clouds and comparison with microphysical cirrus modelling

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M. Brabec

2012-10-01

Full Text Available Advanced measurement and modelling techniques are employed to estimate the partitioning of atmospheric water between the gas phase and the condensed phase in and around cirrus clouds, and thus to identify in-cloud and out-of-cloud supersaturations with respect to ice. In November 2008 the newly developed balloon-borne backscatter sonde COBALD (Compact Optical Backscatter and AerosoL Detector was flown 14 times together with a CFH (Cryogenic Frost point Hygrometer from Lindenberg, Germany (52° N, 14° E. The case discussed here in detail shows two cirrus layers with in-cloud relative humidities with respect to ice between 50% and 130%. Global operational analysis data of ECMWF (roughly 1° × 1° horizontal and 1 km vertical resolution, 6-hourly stored fields fail to represent ice water contents and relative humidities. Conversely, regional COSMO-7 forecasts (6.6 km × 6.6 km, 5-min stored fields capture the measured humidities and cloud positions remarkably well. The main difference between ECMWF and COSMO data is the resolution of small-scale vertical features responsible for cirrus formation. Nevertheless, ice water contents in COSMO-7 are still off by factors 2–10, likely reflecting limitations in COSMO's ice phase bulk scheme. Significant improvements can be achieved by comprehensive size-resolved microphysical and optical modelling along backward trajectories based on COSMO-7 wind and temperature fields, which allow accurate computation of humidities, homogeneous ice nucleation, resulting ice particle size distributions and backscatter ratios at the COBALD wavelengths. However, only by superimposing small-scale temperature fluctuations, which remain unresolved by the numerical weather prediction models, can we obtain a satisfying agreement with the observations and reconcile the measured in-cloud non-equilibrium humidities with conventional ice cloud microphysics. Conversely, the model-data comparison provides no evidence that additional

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.

Impact of Aerosol Processing on Orographic Clouds

Science.gov (United States)

Pousse-Nottelmann, Sara; Zubler, Elias M.; Lohmann, Ulrike

2010-05-01

. [6]. Our investigation regarding the influence of aerosol processing will focus on the regional scale using a cloud-system resolving model with a much higher resolution. Emphasis will be placed on orographic mixed-phase precipitation. Different two-dimensional simulations of idealized orographic clouds will be conducted to estimate the effect of aerosol processing on orographic cloud formation and precipitation. Here, cloud lifetime, location and extent as well as the cloud type will be of particular interest. In a supplementary study, the new parameterization will be compared to observations of total and interstitial aerosol concentrations and size distribution at the remote high alpine research station Jungfraujoch in Switzerland. In addition, our simulations will be compared to recent simulations of aerosol processing in warm, mixed-phase and cold clouds, which have been carried out at the location of Jungfraujoch station [5]. References: [1] Pruppacher & Jaenicke (1995), The processing of water vapor and aerosols by atmospheric clouds, a global estimate, Atmos. Res., 38, 283295. [2] Seifert & Beheng (2006), A two-moment microphysics parameterization for mixed-phase clouds. Part 1: Model description, Meteorol. Atmos. Phys., 92, 4566. [3] Vignati et al. (2004), An efficient size-resolved aerosol microphysics module for large-scale transport models, J. Geophys. Res., 109, D22202 [4] Muhlbauer & Lohmann (2008), Sensitivity studies of the role of aerosols in warm-phase orographic precipitation in different flow regimes, J. Atmos. Sci., 65, 25222542. [5] Hoose et al. (2008), Aerosol processing in mixed-phase clouds in ECHAM5HAM: Model description and comparison to observations, J. Geophys. Res., 113, D071210. [6] Hoose et al. (2008), Global simulations of aerosol processing in clouds, Atmos. Chem. Phys., 8, 69396963.

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

Subtropical Low Cloud Response to a Warmer Climate in an Superparameterized Climate Model: Part I. Regime Sorting and Physical Mechanisms

Directory of Open Access Journals (Sweden)

Peter N Blossey

2009-07-01

Full Text Available The subtropical low cloud response to a climate with SST uniformly warmed by 2 K is analyzed in the SP- CAM superparameterized climate model, in which each grid column is replaced by a two-dimensional cloud-resolving model (CRM. Intriguingly, SP-CAM shows substantial low cloud increases over the subtropical oceans in the warmer climate. The paper aims to understand the mechanism for these increases. The subtropical low cloud increase is analyzed by sorting grid-column months of the climate model into composite cloud regimes using percentile ranges of lower tropospheric stability (LTS. LTS is observed to be well correlated to subtropical low cloud amount and boundary layer vertical structure. The low cloud increase in SP-CAM is attributed to boundary-layer destabilization due to increased clear-sky radiative cooling in the warmer climate. This drives more shallow cumulus convection and a moister boundary layer, inducing cloud increases and further increasing the radiative cooling. The boundary layer depth does not change substantially, due to compensation between increased radiative cooling (which promotes more turbulent mixing and boundary-layer deepening and slight strengthening of the boundary-layer top inversion (which inhibits turbulent entrainment and promotes a shallower boundary layer. The widespread changes in low clouds do not appear to be driven by changes in mean subsidence.
In a companion paper we use column-mode CRM simulations based on LTS-composite profiles to further study the low cloud response mechanisms and to explore the sensitivity of low cloud response to grid resolution in SP-CAM.

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

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.

An examination of two pathways to tropical cyclogenesis occurring in idealized simulations with a cloud-resolving numerical model

Directory of Open Access Journals (Sweden)

M. E. Nicholls

2013-06-01

Full Text Available Simulations are conducted with a cloud-resolving numerical model to examine the transformation of a weak incipient mid-level cyclonic vortex into a tropical cyclone. Results demonstrate that two distinct pathways are possible and that development along a particular pathway is sensitive to model physics and initial conditions. One pathway involves a steady increase of the surface winds to tropical cyclone strength as the radius of maximum winds gradually decreases. A notable feature of this evolution is the creation of small-scale lower tropospheric cyclonic vorticity anomalies by deep convective towers and subsequent merger and convergence by the low-level secondary circulation. The second pathway also begins with a strengthening low-level circulation, but eventually a significantly stronger mid-level circulation develops. Cyclogenesis occurs subsequently when a small-scale surface concentrated vortex forms abruptly near the center of the larger-scale circulation. The small-scale vortex is warm core throughout the troposphere and results in a fall in local surface pressure of a few millibars. It usually develops rapidly, undergoing a modest growth to form a small tropical cyclone. Many of the simulated systems approach or reach tropical cyclone strength prior to development of a prominent mid-level vortex so that the subsequent formation of a strong small-scale surface concentrated vortex in these cases could be considered intensification rather than genesis. Experiments are performed to investigate the dependence on the inclusion of the ice phase, radiation, the size and strength of the incipient mid-level vortex, the amount of moisture present in the initial vortex, and the sea surface temperature. Notably, as the sea surface temperature is raised, the likelihood of development along the second pathway is increased. This appears to be related to an increased production of ice. The sensitivity of the pathway taken to model physics and initial

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

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.

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

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)

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.

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

Effects of Resolution on the Simulation of Boundary-layer Clouds and the Partition of Kinetic Energy to Subgrid Scales

Directory of Open Access Journals (Sweden)

Anning Cheng

2010-02-01

Full Text Available Seven boundary-layer cloud cases are simulated with UCLA-LES (The University of California, Los Angeles – large eddy simulation model with different horizontal and vertical gridspacing to investigate how the results depend on gridspacing. Some variables are more sensitive to horizontal gridspacing, while others are more sensitive to vertical gridspacing, and still others are sensitive to both horizontal and vertical gridspacings with similar or opposite trends. For cloud-related variables having the opposite dependence on horizontal and vertical gridspacings, changing the gridspacing proportionally in both directions gives the appearance of convergence. In this study, we mainly discuss the impact of subgrid-scale (SGS kinetic energy (KE on the simulations with coarsening of horizontal and vertical gridspacings. A running-mean operator is used to separate the KE of the high-resolution benchmark simulations into that of resolved scales of coarse-resolution simulations and that of SGSs. The diagnosed SGS KE is compared with that parameterized by the Smagorinsky-Lilly SGS scheme at various gridspacings. It is found that the parameterized SGS KE for the coarse-resolution simulations is usually underestimated but the resolved KE is unrealistically large, compared to benchmark simulations. However, the sum of resolved and SGS KEs is about the same for simulations with various gridspacings. The partitioning of SGS and resolved heat and moisture transports is consistent with that of SGS and resolved KE, which means that the parameterized transports are underestimated but resolved-scale transports are overestimated. On the whole, energy shifts to large-scales as the horizontal gridspacing becomes coarse, hence the size of clouds and the resolved circulation increase, the clouds become more stratiform-like with an increase in cloud fraction, cloud liquid-water path and surface precipitation; when coarse vertical gridspacing is used, cloud sizes do not

Evaluating the Performance of the Goddard Multi-Scale Modeling Framework against GPM, TRMM and CloudSat/CALIPSO Products

Science.gov (United States)

Chern, J. D.; Tao, W. K.; Lang, S. E.; Matsui, T.; Mohr, K. I.

2014-12-01

Four six-month (March-August 2014) experiments with the Goddard Multi-scale Modeling Framework (MMF) were performed to study the impacts of different Goddard one-moment bulk microphysical schemes and large-scale forcings on the performance of the MMF. Recently a new Goddard one-moment bulk microphysics with four-ice classes (cloud ice, snow, graupel, and frozen drops/hail) has been developed based on cloud-resolving model simulations with large-scale forcings from field campaign observations. The new scheme has been successfully implemented to the MMF and two MMF experiments were carried out with this new scheme and the old three-ice classes (cloud ice, snow graupel) scheme. The MMF has global coverage and can rigorously evaluate microphysics performance for different cloud regimes. The results show MMF with the new scheme outperformed the old one. The MMF simulations are also strongly affected by the interaction between large-scale and cloud-scale processes. Two MMF sensitivity experiments with and without nudging large-scale forcings to those of ERA-Interim reanalysis were carried out to study the impacts of large-scale forcings. The model simulated mean and variability of surface precipitation, cloud types, cloud properties such as cloud amount, hydrometeors vertical profiles, and cloud water contents, etc. in different geographic locations and climate regimes are evaluated against GPM, TRMM, CloudSat/CALIPSO satellite observations. The Goddard MMF has also been coupled with the Goddard Satellite Data Simulation Unit (G-SDSU), a system with multi-satellite, multi-sensor, and multi-spectrum satellite simulators. The statistics of MMF simulated radiances and backscattering can be directly compared with satellite observations to assess the strengths and/or deficiencies of MMF simulations and provide guidance on how to improve the MMF and microphysics.

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

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.

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...

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...

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.

Aerosol-cloud interactions from urban, regional to global scales

International Nuclear Information System (INIS)

Wang, Yuan

2015-01-01

The studies in this dissertation aim at advancing our scientific understandings about physical processes involved in the aerosol-cloud-precipitation interaction and quantitatively assessing the impacts of aerosols on the cloud systems with diverse scales over the globe on the basis of the observational data analysis and various modeling studies. As recognized in the Fifth Assessment Report by the Inter-government Panel on Climate Change, the magnitude of radiative forcing by atmospheric aerosols is highly uncertain, representing the largest uncertainty in projections of future climate by anthropogenic activities. By using a newly implemented cloud microphysical scheme in the cloud-resolving model, the thesis assesses aerosol-cloud interaction for distinct weather systems, ranging from individual cumulus to mesoscale convective systems. This thesis also introduces a novel hierarchical modeling approach that solves a long outstanding mismatch between simulations by regional weather models and global climate models in the climate modeling community. More importantly, the thesis provides key scientific solutions to several challenging questions in climate science, including the global impacts of the Asian pollution. As scientists wrestle with the complexities of climate change in response to varied anthropogenic forcing, perhaps no problem is more challenging than the understanding of the impacts of atmospheric aerosols from air pollution on clouds and the global circulation.

Aerosol-cloud interactions from urban, regional to global scales

Energy Technology Data Exchange (ETDEWEB)

Wang, Yuan [California Institute of Technology, Pasadena, CA (United States). Seismological Lab.

2015-10-01

The studies in this dissertation aim at advancing our scientific understandings about physical processes involved in the aerosol-cloud-precipitation interaction and quantitatively assessing the impacts of aerosols on the cloud systems with diverse scales over the globe on the basis of the observational data analysis and various modeling studies. As recognized in the Fifth Assessment Report by the Inter-government Panel on Climate Change, the magnitude of radiative forcing by atmospheric aerosols is highly uncertain, representing the largest uncertainty in projections of future climate by anthropogenic activities. By using a newly implemented cloud microphysical scheme in the cloud-resolving model, the thesis assesses aerosol-cloud interaction for distinct weather systems, ranging from individual cumulus to mesoscale convective systems. This thesis also introduces a novel hierarchical modeling approach that solves a long outstanding mismatch between simulations by regional weather models and global climate models in the climate modeling community. More importantly, the thesis provides key scientific solutions to several challenging questions in climate science, including the global impacts of the Asian pollution. As scientists wrestle with the complexities of climate change in response to varied anthropogenic forcing, perhaps no problem is more challenging than the understanding of the impacts of atmospheric aerosols from air pollution on clouds and the global circulation.

Supernova Driving. IV. The star-formation rate of molecular clouds

DEFF Research Database (Denmark)

Padoan, Paolo; Haugbølle, Troels; Nordlund, Åke

2017-01-01

We compute the star-formation rate (SFR) in molecular clouds (MCs) that originate ab initio in a new, higher-resolution simulation of supernova-driven turbulence. Because of the large number of well-resolved clouds with self-consistent boundary and initial conditions, we obtain a large range...... of cloud physical parameters with realistic statistical distributions, which is an unprecedented sample of star-forming regions to test SFR models and to interpret observational surveys. We confirm the dependence of the SFR per free-fall time, SFRff, on the virial parameter, αvir, found in previous...... MCs and in clouds near the Galactic center. Although not explicitly modeled by the theory, the scatter is consistent with the physical assumptions of our revised model and may also result in part from a lack of statistical equilibrium of the turbulence, due to the transient nature of MCs....

Radiative-dynamical and microphysical processes of thin cirrus clouds controlling humidity of air entering the stratosphere

Science.gov (United States)

Dinh, Tra; Fueglistaler, Stephan

2016-04-01

Thin cirrus clouds in the tropical tropopause layer (TTL) are of great interest due to their role in the control of water vapor and temperature in the TTL. Previous research on TTL cirrus clouds has focussed mainly on microphysical processes, specifically the ice nucleation mechanism and dehydration efficiency. Here, we use a cloud resolving model to analyse the sensitivity of TTL cirrus characteristics and impacts with respect to microphysical and radiative processes. A steady-state TTL cirrus cloud field is obtained in the model forced with dynamical conditions typical for the TTL (2-dimensional setup with a Kelvin-wave temperature perturbation). Our model results show that the dehydration efficiency (as given by the domain average relative humidity in the layer of cloud occurrence) is relatively insensitive to the ice nucleation mechanism, i.e. homogeneous versus heterogeneous nucleation. Rather, TTL cirrus affect the water vapor entering the stratosphere via an indirect effect associated with the cloud radiative heating and dynamics. Resolving the cloud radiative heating and the radiatively induced circulations approximately doubles the domain average ice mass. The cloud radiative heating is proportional to the domain average ice mass, and the observed increase in domain average ice mass induces a domain average temperature increase of a few Kelvin. The corresponding increase in water vapor entering the stratosphere is estimated to be about 30 to 40%.

The representation of low-level clouds during the West African monsoon in weather and climate models

Science.gov (United States)

Kniffka, Anke; Hannak, Lisa; Knippertz, Peter; Fink, Andreas

2016-04-01

The West African monsoon is one of the most important large-scale circulation features in the tropics and the associated seasonal rainfalls are crucial to rain-fed agriculture and water resources for hundreds of millions of people. However, numerical weather and climate models still struggle to realistically represent salient features of the monsoon across a wide range of scales. Recently it has been shown that substantial errors in radiation and clouds exist in the southern parts of West Africa (8°W-8°E, 5-10°N) during summer. This area is characterised by strong low-level jets associated with the formation of extensive ultra-low stratus clouds. Often persisting long after sunrise, these clouds have a substantial impact on the radiation budget at the surface and thus the diurnal evolution of the planetary boundary layer (PBL). Here we present some first results from a detailed analysis of the representation of these clouds and the associated PBL features across a range of weather and climate models. Recent climate model simulations for the period 1991-2010 run in the framework of the Year of Tropical Convection (YOTC) offer a great opportunity for this analysis. The models are those used for the latest Assessment Report of the Intergovernmental Panel on Climate Change, but for YOTC the model output has a much better temporal resolution, allowing to resolve the diurnal cycle, and includes diabatic terms, allowing to much better assess physical reasons for errors in low-level temperature, moisture and thus cloudiness. These more statistical climate model analyses are complemented by experiments using ICON (Icosahedral non-hydrostatic general circulation model), the new numerical weather prediction model of the German Weather Service and the Max Planck Institute for Meteorology. ICON allows testing sensitivities to model resolution and numerical schemes. These model simulations are validated against (re-)analysis data, satellite observations (e.g. CM SAF cloud and

Simulating moist convection with a quasi-elastic sigma coordinate model

CSIR Research Space (South Africa)

Bopape, Mary-Jane M

2012-10-01

Full Text Available : Corrected TOGA COARE Sounding Humidity Data: Impact on Diagnosed Properties of Convection and Climate over the Warm Pool. Journal of Climate, 12, 2370-2384. WW, X Wu and MW Moncrieff, 1996: Cloud-Resolving Modeling of Tropical Cloud Systems during Phase... during the suppressed phase of a Madden-Julian Oscillation: Comparing single-column models with cloud resolving models. Quarterly Journal of the Royal Meteorological Society, 1-22. Sun S and W Sun, 2002: A One-dimensional Time Dependent Cloud Model...

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

Cloud-Resolving Modeling Intercomparison Study of a Squall Line Case from MC3E - Properties of Convective Core

Science.gov (United States)

Fan, J.; Han, B.; Varble, A.; Morrison, H.; North, K.; Kollias, P.; Chen, B.; Dong, X.; Giangrande, S. E.; Khain, A.; Lin, Y.; Mansell, E.; Milbrandt, J.; Stenz, R.; Thompson, G.; Wang, Y.

2016-12-01

The large spread in CRM model simulations of deep convection and aerosol effects on deep convective clouds (DCCs) makes it difficult to (1) further our understanding of deep convection and (2) define "benchmarks" and then limit their use in parameterization developments. A constrained model intercomparsion study on a mid-latitude mesoscale squall line is performed using the Weather Research & Forecasting (WRF) model at 1-km horizontal grid spacing with eight cloud microphysics schemes to understand specific processes that lead to the large spreads of simulated convection and precipitation. Various observational data are employed to evaluate the baseline simulations. All simulations tend to produce a wider convective area but a much narrower stratiform area. The magnitudes of virtual potential temperature drop, pressure rise, and wind speed peak associated with the passage of the gust front are significantly smaller compared with the observations, suggesting simulated cool pools are weaker. Simulations generally overestimate the vertical velocity and radar reflectivity in convective cores compared with the retrievals. The modeled updraft velocity and precipitation have a significant spread across eight schemes. The spread of updraft velocity is the combination of both low-level pressure perturbation gradient (PPG) and buoyancy. Both PPG and thermal buoyancy are small for simulations of weak convection but both are large for those of strong convection. Ice-related parameterizations contribute majorly to the spread of updraft velocity, while they are not the reason for the large spread of precipitation. The understandings gained in this study can help to focus future observations and parameterization development.

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.

From Global to Cloud Resolving Scale: Experiments with a Scale- and Aerosol-Aware Physics Package and Impact on Tracer Transport

Science.gov (United States)

Grell, G. A.; Freitas, S. R.; Olson, J.; Bela, M.

2017-12-01

We will start by providing a summary of the latest cumulus parameterization modeling efforts at NOAA's Earth System Research Laboratory (ESRL) will be presented on both regional and global scales. The physics package includes a scale-aware parameterization of subgrid cloudiness feedback to radiation (coupled PBL, microphysics, radiation, shallow and congestus type convection), the stochastic Grell-Freitas (GF) scale- and aerosol-aware convective parameterization, and an aerosol aware microphysics package. GF is based on a stochastic approach originally implemented by Grell and Devenyi (2002) and described in more detail in Grell and Freitas (2014, ACP). It was expanded to include PDF's for vertical mass flux, as well as modifications to improve the diurnal cycle. This physics package will be used on different scales, spanning global to cloud resolving, to look at the impact on scalar transport and numerical weather prediction.

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.

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.

Minimum resolvable power contrast model

Science.gov (United States)

Qian, Shuai; Wang, Xia; Zhou, Jingjing

2018-01-01

Signal-to-noise ratio and MTF are important indexs to evaluate the performance of optical systems. However,whether they are used alone or joint assessment cannot intuitively describe the overall performance of the system. Therefore, an index is proposed to reflect the comprehensive system performance-Minimum Resolvable Radiation Performance Contrast (MRP) model. MRP is an evaluation model without human eyes. It starts from the radiance of the target and the background, transforms the target and background into the equivalent strips,and considers attenuation of the atmosphere, the optical imaging system, and the detector. Combining with the signal-to-noise ratio and the MTF, the Minimum Resolvable Radiation Performance Contrast is obtained. Finally the detection probability model of MRP is given.

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

A Virtual Machine Migration Strategy Based on Time Series Workload Prediction Using Cloud Model

Directory of Open Access Journals (Sweden)

Yanbing Liu

2014-01-01

Full Text Available Aimed at resolving the issues of the imbalance of resources and workloads at data centers and the overhead together with the high cost of virtual machine (VM migrations, this paper proposes a new VM migration strategy which is based on the cloud model time series workload prediction algorithm. By setting the upper and lower workload bounds for host machines, forecasting the tendency of their subsequent workloads by creating a workload time series using the cloud model, and stipulating a general VM migration criterion workload-aware migration (WAM, the proposed strategy selects a source host machine, a destination host machine, and a VM on the source host machine carrying out the task of the VM migration. Experimental results and analyses show, through comparison with other peer research works, that the proposed method can effectively avoid VM migrations caused by momentary peak workload values, significantly lower the number of VM migrations, and dynamically reach and maintain a resource and workload balance for virtual machines promoting an improved utilization of resources in the entire data center.

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.

A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes

Science.gov (United States)

Tao, W. K.

2017-12-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), and (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF). The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitation, processes and their sensitivity on model resolution and microphysics schemes will be presented. Also how to use of the multi-satellite simulator to improve precipitation processes will be discussed.

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.

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.

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.

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.

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.

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

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.

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...

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...

Atmospheric CO2 Concentration Measurements with Clouds from an Airborne Lidar

Science.gov (United States)

Mao, J.; Abshire, J. B.; Kawa, S. R.; Riris, H.; Allan, G. R.; Hasselbrack, W. E.; Numata, K.; Chen, J. R.; Sun, X.; DiGangi, J. P.; Choi, Y.

2017-12-01

Globally distributed atmospheric CO2 concentration measurements with high precision, low bias and full seasonal sampling are crucial to advance carbon cycle sciences. However, two thirds of the Earth's surface is typically covered by clouds, and passive remote sensing approaches from space are limited to cloud-free scenes. NASA Goddard is developing a pulsed, integrated-path differential absorption (IPDA) lidar approach to measure atmospheric column CO2 concentrations, XCO2, from space as a candidate for NASA's ASCENDS mission. Measurements of time-resolved laser backscatter profiles from the atmosphere also allow this technique to estimate XCO2 and range to cloud tops in addition to those to the ground with precise knowledge of the photon path-length. We demonstrate this measurement capability using airborne lidar measurements from summer 2017 ASCENDS airborne science campaign in Alaska. We show retrievals of XCO2 to ground and to a variety of cloud tops. We will also demonstrate how the partial column XCO2 to cloud tops and cloud slicing approach help resolving vertical and horizontal gradient of CO2 in cloudy conditions. The XCO2 retrievals from the lidar are validated against in situ measurements and compared to the Goddard Parameterized Chemistry Transport Model (PCTM) simulations. Adding this measurement capability to the future lidar mission for XCO2 will provide full global and seasonal data coverage and some information about vertical structure of CO2. This unique facility is expected to benefit atmospheric transport process studies, carbon data assimilation in models, and global and regional carbon flux estimation.

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.

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.

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)

Analysis of CCN activity of Remote and Combustion Aerosol over the South East Pacific during autumn 2008 and links to Sc cloud properties

Science.gov (United States)

Freitag, S.; Clarke, A. D.; Howell, S. G.; Twohy, C. H.; Snider, J. R.; Toohey, D. W.; Shank, L.; McNaughton, C. S.; Brekhovskikh, V.; Kapustin, V.

2013-12-01

The earth's most extensive Stratocumulus (Sc) deck, situated off the coast of Northern Chile and Southern Peru, strongly influences the radiation budget and climate over the South East Pacific (SEP) by enhancing solar reflection. This feature makes Sc clouds an important constituent for climate modeling, yet these clouds are poorly represented in models. A large uncertainty in understanding the variability in these low cloud fields arises from our deficit in understanding the role of aerosol. Hence, a major goal of the VOCALS (www.eol.ucar.edu/projects/vocals) campaign in 2008 was to further explore and assess interactions of natural and anthropogenic aerosol with Sc clouds in both the more polluted coastal environment and west of 80W where we encountered nearly pristine boundary layer clouds often exposed to cloud-top entrainment of pollution aerosol from the free troposphere. Extensive airborne measurements of size-resolved aerosol volatility and chemical composition collected aboard the NCAR C-130 were analyzed with an aerosol mass spectrometer (AMS) and a single particle soot photometer (SP2) to calculate aerosol hygroscopicity (κ) and predict cloud condensation nuclei (CCN) concentration for all observed air mass types above and below cloud utilizing estimated Sc cloud supersaturations deduced from cloud-processed aerosol size distribution information. The predicted CCN agree to within 10% to measured CCN. Results from this analysis are presented here and CCN variability observed along VOCALS flight tracks is discussed in conjunction with size-resolved cloud droplet information. This includes assessing the impact of aerosol perturbations on the shape of the cloud droplet size distribution parameterized in models and satellite algorithms such as cloud top effective radius retrievals. We will further discuss cloud droplet residual composition collected using a counterflow virtual impactor (CVI) and analyzed with the AMS and SP2. Size resolved variations in

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.

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).

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...

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.;

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.

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)

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.

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.

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.

Effective ASCII-HEX steganography for secure cloud

International Nuclear Information System (INIS)

Afghan, S.

2015-01-01

There are many reasons of cloud computing popularity some of the most important are; backup and rescue, cost effective, nearly limitless storage, automatic software amalgamation, easy access to information and many more. Pay-as-you-go model is followed to provide everything as a service. Data is secured by using standard security policies available at cloud end. In spite of its many benefits, as mentioned above, cloud computing has also some security issues. Provider as well as customer has to provide and collect data in a secure manner. Both of these issues plus efficient transmitting of data over cloud are very critical issues and needed to be resolved. There is need of security during the travel time of sensitive data over the network that can be processed or stored by the customer. Security to the customer's data at the provider end can be provided by using current security algorithms, which are not known by the customer. There is reliability problem due to existence of multiple boundaries in the cloud resource access. ASCII and HEX security with steganography is used to propose an algorithm that stores the encrypted data/cipher text in an image file which will be then sent to the cloud end. This is done by using CDM (Common Deployment Model). In future, an algorithm should be proposed and implemented for the security of virtual images in the cloud computing. (author)

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

Science.gov (United States)

Tao, Wei-Kuo; Chern, J.; Lamg, S.; Matsui, T.; Shen, B.; Zeng, X.; Shi, R.

2011-01-01

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to

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.

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.

Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915

Science.gov (United States)

Parodi, Antonio; Ferraris, Luca; Gallus, William; Maugeri, Maurizio; Molini, Luca; Siccardi, Franco; Boni, Giorgio

2017-05-01

Highly localized and persistent back-building mesoscale convective systems represent one of the most dangerous flash-flood-producing storms in the north-western Mediterranean area. Substantial warming of the Mediterranean Sea in recent decades raises concerns over possible increases in frequency or intensity of these types of events as increased atmospheric temperatures generally support increases in water vapour content. However, analyses of the historical record do not provide a univocal answer, but these are likely affected by a lack of detailed observations for older events. In the present study, 20th Century Reanalysis Project initial and boundary condition data in ensemble mode are used to address the feasibility of performing cloud-resolving simulations with 1 km horizontal grid spacing of a historic extreme event that occurred over Liguria: the San Fruttuoso case of 1915. The proposed approach focuses on the ensemble Weather Research and Forecasting (WRF) model runs that show strong convergence over the Ligurian Sea (17 out of 56 members) as these runs are the ones most likely to best simulate the event. It is found that these WRF runs generally do show wind and precipitation fields that are consistent with the occurrence of highly localized and persistent back-building mesoscale convective systems, although precipitation peak amounts are underestimated. Systematic small north-westward position errors with regard to the heaviest rain and strongest convergence areas imply that the reanalysis members may not be adequately representing the amount of cool air over the Po Plain outflowing into the Ligurian Sea through the Apennines gap. Regarding the role of historical data sources, this study shows that in addition to reanalysis products, unconventional data, such as historical meteorological bulletins, newspapers, and even photographs, can be very valuable sources of knowledge in the reconstruction of past extreme events.

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.

Evaluation of cumulus cloud – radiation interaction effects on air quality –relevant meteorological variables from WRF, from a regional climate perspective

Science.gov (United States)

Aware only of the resolved, grid-scale clouds, the Weather Research & Forecasting model (WRF) does not consider the interactions between subgrid-scale convective clouds and radiation. One consequence of this omission may be WRF’s overestimation of surface precipitation during sum...

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...

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.

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.

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

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.

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.

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.

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)

Shielded button electrodes for time-resolved measurements of electron cloud buildup

International Nuclear Information System (INIS)

Crittenden, J.A.; Billing, M.G.; Li, Y.; Palmer, M.A.; Sikora, J.P.

2014-01-01

We report on the design, deployment and signal analysis for shielded button electrodes sensitive to electron cloud buildup at the Cornell Electron Storage Ring. These simple detectors, derived from a beam-position monitor electrode design, have provided detailed information on the physical processes underlying the local production and the lifetime of electron densities in the storage ring. Digitizing oscilloscopes are used to record electron fluxes incident on the vacuum chamber wall in 1024 time steps of 100 ps or more. The fine time steps provide a detailed characterization of the cloud, allowing the independent estimation of processes contributing on differing time scales and providing sensitivity to the characteristic kinetic energies of the electrons making up the cloud. By varying the spacing and population of electron and positron beam bunches, we map the time development of the various cloud production and re-absorption processes. The excellent reproducibility of the measurements also permits the measurement of long-term conditioning of vacuum chamber surfaces

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...

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.

Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

Science.gov (United States)

Molthan, Andrew; Haynes, John M.; Jedlovec, Gary J.; Lapenta, William M.

2009-01-01

Steady increases in computing power have allowed for numerical weather prediction models to be initialized and run at high spatial resolution, permitting a transition from larger scale parameterizations of the effects of clouds and precipitation to the simulation of specific microphysical processes and hydrometeor size distributions. Although still relatively coarse in comparison to true cloud resolving models, these high resolution forecasts (on the order of 4 km or less) have demonstrated value in the prediction of severe storm mode and evolution and are being explored for use in winter weather events . Several single-moment bulk water microphysics schemes are available within the latest release of the Weather Research and Forecast (WRF) model suite, including the NASA Goddard Cumulus Ensemble, which incorporate some assumptions in the size distribution of a small number of hydrometeor classes in order to predict their evolution, advection and precipitation within the forecast domain. Although many of these schemes produce similar forecasts of events on the synoptic scale, there are often significant details regarding precipitation and cloud cover, as well as the distribution of water mass among the constituent hydrometeor classes. Unfortunately, validating data for cloud resolving model simulations are sparse. Field campaigns require in-cloud measurements of hydrometeors from aircraft in coordination with extensive and coincident ground based measurements. Radar remote sensing is utilized to detect the spatial coverage and structure of precipitation. Here, two radar systems characterize the structure of winter precipitation for comparison to equivalent features within a forecast model: a 3 GHz, Weather Surveillance Radar-1988 Doppler (WSR-88D) based in Omaha, Nebraska, and the 94 GHz NASA CloudSat Cloud Profiling Radar, a spaceborne instrument and member of the afternoon or "A-Train" of polar orbiting satellites tasked with cataloguing global cloud

Comparison of mean properties of simulated convection in a cloud-resolving model with those produced by cumulus parameterization

Energy Technology Data Exchange (ETDEWEB)

Dudhia, J.; Parsons, D.B. [National Center for Atmospheric Research, Boulder, CO (United States)

1996-04-01

An Intensive Observation Period (IOP) of the Atmospheric Radiation Measurement (ARM) Program took place at the Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site from June 16-26, 1993. The National Center for Atmospheric Research (NCAR)/Penn State Mesoscale Model (MM5) has been used to simulate this period on a 60-km domain with 20- and 6.67-km nests centered on Lamont, Oklahoma. Simulations are being run with data assimilation by the nudging technique to incorporate upper-air and surface data from a variety of platforms. The model maintains dynamical consistency between the fields, while the data correct for model biases that may occur during long-term simulations and provide boundary conditions. For the work reported here the Mesoscale Atmospheric Prediction System (MAPS) of the National Ocean and Atmospheric Administration (NOAA) 3-hourly analyses were used to drive the 60-km domain while the inner domains were unforced. A continuous 10-day period was simulated.

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

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

STAR FORMATION IN DISK GALAXIES. I. FORMATION AND EVOLUTION OF GIANT MOLECULAR CLOUDS VIA GRAVITATIONAL INSTABILITY AND CLOUD COLLISIONS

International Nuclear Information System (INIS)

Tasker, Elizabeth J.; Tan, Jonathan C.

2009-01-01

We investigate the formation and evolution of giant molecular clouds (GMCs) in a Milky-Way-like disk galaxy with a flat rotation curve. We perform a series of three-dimensional adaptive mesh refinement numerical simulations that follow both the global evolution on scales of ∼20 kpc and resolve down to scales ∼ H ≥ 100 cm -3 and track the evolution of individual clouds as they orbit through the galaxy from their birth to their eventual destruction via merger or via destructive collision with another cloud. After ∼140 Myr a large fraction of the gas in the disk has fragmented into clouds with masses ∼10 6 M sun and a mass spectrum similar to that of Galactic GMCs. The disk settles into a quasi-steady-state in which gravitational scattering of clouds keeps the disk near the threshold of global gravitational instability. The cloud collision time is found to be a small fraction, ∼1/5, of the orbital time, and this is an efficient mechanism to inject turbulence into the clouds. This helps to keep clouds only moderately gravitationally bound, with virial parameters of order unity. Many other observed GMC properties, such as mass surface density, angular momentum, velocity dispersion, and vertical distribution, can be accounted for in this simple model with no stellar feedback.

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.

Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM

Directory of Open Access Journals (Sweden)

U. Lohmann

2007-07-01

Full Text Available The double-moment cloud microphysics scheme from ECHAM4 that predicts both the mass mixing ratios and number concentrations of cloud droplets and ice crystals has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass, number concentrations and mixing state. The simulated liquid, ice and total water content and the cloud droplet and ice crystal number concentrations as a function of temperature in stratiform mixed-phase clouds between 0 and −35° C agree much better with aircraft observations in the ECHAM5 simulations. ECHAM5 performs better because more realistic aerosol concentrations are available for cloud droplet nucleation and because the Bergeron-Findeisen process is parameterized as being more efficient.

The total anthropogenic aerosol effect includes the direct, semi-direct and indirect effects and is defined as the difference in the top-of-the-atmosphere net radiation between present-day and pre-industrial times. It amounts to −1.9 W m⁻² in ECHAM5, when a relative humidity dependent cloud cover scheme and aerosol emissions representative for the years 1750 and 2000 from the AeroCom emission inventory are used. The contribution of the cloud albedo effect amounts to −0.7 W m⁻². The total anthropogenic aerosol effect is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed because the cloud lifetime effect increases.

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

Climate Model Evaluation using New Datasets from the Clouds and the Earth's Radiant Energy System (CERES)

Science.gov (United States)

Loeb, Norman G.; Wielicki, Bruce A.; Doelling, David R.

2008-01-01

. Diurnal cycles are explicitly resolved by merging geostationary satellite observations with CERES and MODIS. Atmospheric state data are provided from a frozen version of the Global Modeling and Assimilation Office- Data Assimilation System at the NASA Goddard Space Flight Center. In addition to improving the accuracy of top-of-atmosphere (TOA) radiative fluxes, CERES also produces radiative fluxes at the surface and at several levels in the atmosphere using radiative transfer modeling, constrained at the TOA by CERES (ERBE was limited to the TOA). In all, CERES uses 11 instruments on 7 spacecraft all integrated to obtain climate accuracy in TOA to surface fluxes. This presentation will provide an overview of several new CERES datasets of interest to the climate community (including a new adjusted TOA flux dataset constrained by estimates of heat storage in the Earth system), show direct comparisons between CERES ad ERBE, and provide a detailed error analysis of CERES fluxes at various time and space scales. We discuss how observations can be used to reduce uncertainties in cloud feedback and climate sensitivity and strongly argue why we should NOT "call off the quest".

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

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.

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.

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

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.

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.

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.

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

Spectral Longwave Cloud Radiative Forcing as Observed by AIRS

Science.gov (United States)

Blaisdell, John M.; Susskind, Joel; Lee, Jae N.; Iredell, Lena

2016-01-01

AIRS V6 products contain the spectral contributions to Outgoing Longwave Radiation (OLR), clear-sky OLR (OLR(sub CLR)), and Longwave Cloud Radiative Forcing (LWCRF) in 16 bands from 100 cm(exp -1) to 3260 cm(exp -1). We show climatologies of selected spectrally resolved AIRS V6 products over the period of September 2002 through August 2016. Spectrally resolved LWCRF can better describe the response of the Earth system to cloud and cloud feedback processes. The spectral LWCRF enables us to estimate the fraction of each contributing factor to cloud forcing, i.e.: surface temperature, mid to upper tropospheric water vapor, and tropospheric temperature. This presentation also compares the spatial characteristics of LWCRF from AIRS, CERES_EBAF Edition-2.8, and MERRA-2. AIRS and CERES LWCRF products show good agreement. The OLR bias between AIRS and CERES is very close to that of OLR(sub CLR). This implies that both AIRS and CERES OLR products accurately account for the effect of clouds on OLR.

Can Condensing Organic Aerosols Lead to Less Cloud Particles?

Science.gov (United States)

Gao, C. Y.; Tsigaridis, K.; Bauer, S.

2017-12-01

We examined the impact of condensing organic aerosols on activated cloud number concentration in a new aerosol microphysics box model, MATRIX-VBS. The model includes the volatility-basis set (VBS) framework in an aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state) that resolves aerosol mass and number concentrations and aerosol mixing state. Preliminary results show that by including the condensation of organic aerosols, the new model (MATRIX-VBS) has less activated particles compared to the original model (MATRIX), which treats organic aerosols as non-volatile. Parameters such as aerosol chemical composition, mass and number concentrations, and particle sizes which affect activated cloud number concentration are thoroughly evaluated via a suite of Monte-Carlo simulations. The Monte-Carlo simulations also provide information on which climate-relevant parameters play a critical role in the aerosol evolution in the atmosphere. This study also helps simplifying the newly developed box model which will soon be implemented in the global model GISS ModelE as a module.

[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

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.

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

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

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

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)

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.

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.

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.

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

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.

Fast cloud parameter retrievals of MIPAS/Envisat

Directory of Open Access Journals (Sweden)

R. Spang

2012-08-01

and tropospheric clouds similar to that of space- and ground-based lidars, with a tendency for higher cloud top heights and consequently higher sensitivity for some of the MIPAS detection methods. For the high cloud amount (HCA, pressure levels below 440 hPa on global scales the sensitivity of MIPAS is significantly greater than that of passive nadir viewers. This means that the high cloud fraction will be underestimated in the ISCCP dataset compared to the amount of high clouds deduced by MIPAS. Good correspondence in seasonal variability and geographical distribution of cloud occurrence and zonal means of cloud top height is found in a detailed comparison with a climatology for subvisible cirrus clouds from the Stratospheric Aerosol and Gas Experiment II (SAGE II limb sounder. Overall, validation with various sensors shows the need to consider differences in sensitivity, and especially the viewing geometries and field-of-view size, to make the datasets comparable (e.g. applying integration along the limb path through nadir cloud fields. The simulation of the limb path integration will be an important issue for comparisons with cloud-resolving global circulation or chemical transport models.

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.

Radiative-convective equilibrium model intercomparison project

Science.gov (United States)

Wing, Allison A.; Reed, Kevin A.; Satoh, Masaki; Stevens, Bjorn; Bony, Sandrine; Ohno, Tomoki

2018-03-01

RCEMIP, an intercomparison of multiple types of models configured in radiative-convective equilibrium (RCE), is proposed. RCE is an idealization of the climate system in which there is a balance between radiative cooling of the atmosphere and heating by convection. The scientific objectives of RCEMIP are three-fold. First, clouds and climate sensitivity will be investigated in the RCE setting. This includes determining how cloud fraction changes with warming and the role of self-aggregation of convection in climate sensitivity. Second, RCEMIP will quantify the dependence of the degree of convective aggregation and tropical circulation regimes on temperature. Finally, by providing a common baseline, RCEMIP will allow the robustness of the RCE state across the spectrum of models to be assessed, which is essential for interpreting the results found regarding clouds, climate sensitivity, and aggregation, and more generally, determining which features of tropical climate a RCE framework is useful for. A novel aspect and major advantage of RCEMIP is the accessibility of the RCE framework to a variety of models, including cloud-resolving models, general circulation models, global cloud-resolving models, single-column models, and large-eddy simulation models.

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

Cloud security - An approach with modern cryptographic solutions

OpenAIRE

Kostadinovska, Ivana

2016-01-01

The term “cloud computing” has been in the spotlights of IT specialists due to its potential of transforming computer industry. Unfortunately, there are still some challenges to be resolved and the security aspects in the cloud based computing environment remain at the core of interest. The goal of our work is to identify the main security issues of cloud computing and to present approaches to secure clouds. Our research also focuses on data and storage security layers. As a result, we f...

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.

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

Convergence behavior of idealized convection-resolving simulations of summertime deep moist convection over land

Science.gov (United States)

Panosetti, Davide; Schlemmer, Linda; Schär, Christoph

2018-05-01

Convection-resolving models (CRMs) can explicitly simulate deep convection and resolve interactions between convective updrafts. They are thus increasingly used in numerous weather and climate applications. However, the truncation of the continuous energy cascade at scales of O (1 km) poses a serious challenge, as in kilometer-scale simulations the size and properties of the simulated convective cells are often determined by the horizontal grid spacing (Δ x ).In this study, idealized simulations of deep moist convection over land are performed to assess the convergence behavior of a CRM at Δ x = 8, 4, 2, 1 km and 500 m. Two types of convergence estimates are investigated: bulk convergence addressing domain-averaged and integrated variables related to the water and energy budgets, and structural convergence addressing the statistics and scales of individual clouds and updrafts. Results show that bulk convergence generally begins at Δ x =4 km, while structural convergence is not yet fully achieved at the kilometer scale, despite some evidence that the resolution sensitivity of updraft velocities and convective mass fluxes decreases at finer resolution. In particular, at finer grid spacings the maximum updraft velocity generally increases, and the size of the smallest clouds is mostly determined by Δ x . A number of different experiments are conducted, and it is found that the presence of orography and environmental vertical wind shear yields more energetic structures at scales much larger than Δ x , sometimes reducing the resolution sensitivity. Overall the results lend support to the use of kilometer-scale resolutions in CRMs, despite the inability of these models to fully resolve the associated cloud field.

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

Towards an integrated multiscale simulation of turbulent clouds on PetaScale computers

International Nuclear Information System (INIS)

Wang Lianping; Ayala, Orlando; Parishani, Hossein; Gao, Guang R; Kambhamettu, Chandra; Li Xiaoming; Rossi, Louis; Orozco, Daniel; Torres, Claudio; Grabowski, Wojciech W; Wyszogrodzki, Andrzej A; Piotrowski, Zbigniew

2011-01-01

The development of precipitating warm clouds is affected by several effects of small-scale air turbulence including enhancement of droplet-droplet collision rate by turbulence, entrainment and mixing at the cloud edges, and coupling of mechanical and thermal energies at various scales. Large-scale computation is a viable research tool for quantifying these multiscale processes. Specifically, top-down large-eddy simulations (LES) of shallow convective clouds typically resolve scales of turbulent energy-containing eddies while the effects of turbulent cascade toward viscous dissipation are parameterized. Bottom-up hybrid direct numerical simulations (HDNS) of cloud microphysical processes resolve fully the dissipation-range flow scales but only partially the inertial subrange scales. it is desirable to systematically decrease the grid length in LES and increase the domain size in HDNS so that they can be better integrated to address the full range of scales and their coupling. In this paper, we discuss computational issues and physical modeling questions in expanding the ranges of scales realizable in LES and HDNS, and in bridging LES and HDNS. We review our on-going efforts in transforming our simulation codes towards PetaScale computing, in improving physical representations in LES and HDNS, and in developing better methods to analyze and interpret the simulation results.

On the Nature and Extent of Optically Thin Marine low Clouds

Science.gov (United States)

Leahy, L. V.; Wood, R.; Charlson, R. J.; Hostetler, C. A.; Rogers, R. R.; Vaughan, M. A.; Winker, D. M.

2012-01-01

Macrophysical properties of optically thin marine low clouds over the nonpolar oceans (60 deg S-60 deg N) are measured using 2 years of full-resolution nighttime data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Optically thin clouds, defined as the subset of marine low clouds that do not fully attenuate the lidar signal, comprise almost half of the low clouds over the marine domain. Regionally, the fraction of low clouds that are optically thin (f(sub thin,cld)) exhibits a strong inverse relationship with the low-cloud cover, with maxima in the tropical trades (f(sub thin,cld) greater than 0.8) and minima in regions of persistent marine stratocumulus and in midlatitudes (f(sub thin,cld) less than 0.3). Domain-wide, a power law fit describes the cloud length distribution, with exponent beta = 2.03 +/- 0.06 (+/-95% confidence interval). On average, the fraction of a cloud that is optically thin decreases from approximately 1 for clouds smaller than 2 km to less than 0.3 for clouds larger than 30 km. This relationship is found to be independent of region, so that geographical variations in the cloud length distribution explain three quarters of the variance in f(sub thin,cld). Comparing collocated trade cumulus observations from CALIOP and the airborne High Spectral Resolution Lidar reveals that clouds with lengths smaller than are resolvable with CALIOP contribute approximately half of the low clouds in the region sampled. A bounded cascade model is constructed to match the observations from the trades. The model shows that the observed optically thin cloud behavior is consistent with a power law scaling of cloud optical depth and suggests that most optically thin clouds only partially fill the CALIOP footprint.

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.)

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.

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

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

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.

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.

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.

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions: SCM SIMULATIONS OF CLOUD TRANSITIONS

Energy Technology Data Exchange (ETDEWEB)

Neggers, R. A. J. [Institute for Geophysics and Meteorology, Department of Geosciences, University of Cologne, Cologne Germany; Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Ackerman, A. S. [NASA Goddard Institute for Space Studies, New York NY USA; Angevine, W. M. [CIRES, University of Colorado, Boulder CO USA; NOAA Earth System Research Laboratory, Boulder CO USA; Bazile, E. [Météo France/CNRM, Toulouse France; Beau, I. [Météo France/ENM, Toulouse France; Blossey, P. N. [Department of Atmospheric Sciences, University of Washington, Seattle WA USA; Boutle, I. A. [Met Office, Exeter UK; de Bruijn, C. [Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Cheng, A. [NOAA Center for Weather and Climate Prediction, Environmental Modeling Center, College Park MD USA; van der Dussen, J. [Department of Geoscience and Remote Sensing, Delft University of Technology, Delft The Netherlands; Fletcher, J. [Department of Atmospheric Sciences, University of Washington, Seattle WA USA; University of Leeds, Leeds UK; Dal Gesso, S. [Institute for Geophysics and Meteorology, Department of Geosciences, University of Cologne, Cologne Germany; Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Jam, A. [Météo-France/CNRM & CNRS/IPSL/LMD, Toulouse France; Kawai, H. [Meteorological Research Institute, Climate Research Department, Japan Meteorological Agency, Tsukuba Japan; Cheedela, S. K. [Department of Atmosphere in the Earth System, Max-Planck Institut für Meteorologie, Hamburg Germany; Larson, V. E. [Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee WI USA; Lefebvre, M. -P. [Météo-France/CNRM & CNRS/IPSL/LMD, Toulouse France; Lock, A. P. [Met Office, Exeter UK; Meyer, N. R. [Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee WI USA; de Roode, S. R. [Department of Geoscience and Remote Sensing, Delft University of Technology, Delft The Netherlands; de Rooy, W. [Royal Netherlands Meteorological Institute, De Bilt The Netherlands; Sandu, I. [Section of Physical Aspects, European Centre for Medium-Range Weather Forecasts, Reading UK; Xiao, H. [University of California at Los Angeles, Los Angeles CA USA; Pacific Northwest National Laboratory, Richland WA USA; Xu, K. -M. [NASA Langley Research Centre, Hampton VI USA

2017-10-01

Results are presented of the GASS/EUCLIPSE single-column model inter-comparison 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 mod- els for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pa- cific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple met- rics to establish the model performance. Using this method some longstanding problems in low level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure and the associated impact on radia- tive transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median ex- hibits the well-known “too few too bright” problem. The boundary layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular the verti- cal structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid pa- rameterization.

Cloud Infrastructure & Applications - CloudIA

Science.gov (United States)

Sulistio, Anthony; Reich, Christoph; Doelitzscher, Frank

The idea behind Cloud Computing is to deliver Infrastructure-as-a-Services and Software-as-a-Service over the Internet on an easy pay-per-use business model. To harness the potentials of Cloud Computing for e-Learning and research purposes, and to small- and medium-sized enterprises, the Hochschule Furtwangen University establishes a new project, called Cloud Infrastructure & Applications (CloudIA). The CloudIA project is a market-oriented cloud infrastructure that leverages different virtualization technologies, by supporting Service-Level Agreements for various service offerings. This paper describes the CloudIA project in details and mentions our early experiences in building a private cloud using an existing infrastructure.

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

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.

Supernova Driving. IV. The Star-formation Rate of Molecular Clouds

Science.gov (United States)

Padoan, Paolo; Haugbølle, Troels; Nordlund, Åke; Frimann, Søren

2017-05-01

We compute the star-formation rate (SFR) in molecular clouds (MCs) that originate ab initio in a new, higher-resolution simulation of supernova-driven turbulence. Because of the large number of well-resolved clouds with self-consistent boundary and initial conditions, we obtain a large range of cloud physical parameters with realistic statistical distributions, which is an unprecedented sample of star-forming regions to test SFR models and to interpret observational surveys. We confirm the dependence of the SFR per free-fall time, SFRff, on the virial parameter, α vir, found in previous simulations, and compare a revised version of our turbulent fragmentation model with the numerical results. The dependences on Mach number, { M }, gas to magnetic pressure ratio, β, and compressive to solenoidal power ratio, χ at fixed α vir are not well constrained, because of random scatter due to time and cloud-to-cloud variations in SFRff. We find that SFRff in MCs can take any value in the range of 0 ≤ SFRff ≲ 0.2, and its probability distribution peaks at a value of SFRff ≈ 0.025, consistent with observations. The values of SFRff and the scatter in the SFRff-α vir relation are consistent with recent measurements in nearby MCs and in clouds near the Galactic center. Although not explicitly modeled by the theory, the scatter is consistent with the physical assumptions of our revised model and may also result in part from a lack of statistical equilibrium of the turbulence, due to the transient nature of MCs.

Absorbed dose from traversing spherically symmetric, Gaussian radioactive clouds

International Nuclear Information System (INIS)

Thompson, J.M.; Poston, J.W.

1999-01-01

If a large radioactive cloud is produced, sampling may require that an airplane traverse the cloud. A method to predict the absorbed dose to the aircrew from penetrating the radioactive cloud is needed. Dose rates throughout spherically symmetric Gaussian clouds of various sizes, and the absorbed doses from traversing the clouds, were calculated. Cloud size is a dominant parameter causing dose to vary by orders of magnitude for a given dose rate measured at some distance. A method to determine cloud size, based on dose rate readings at two or more distances from the cloud center, was developed. This method, however, failed to resolve the smallest cloud sizes from measurements made at 1,000 m to 2,000 m from the cloud center

EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

Science.gov (United States)

Bony, Sandrine; Stevens, Bjorn; Ament, Felix; Bigorre, Sebastien; Chazette, Patrick; Crewell, Susanne; Delanoë, Julien; Emanuel, Kerry; Farrell, David; Flamant, Cyrille; Gross, Silke; Hirsch, Lutz; Karstensen, Johannes; Mayer, Bernhard; Nuijens, Louise; Ruppert, James H.; Sandu, Irina; Siebesma, Pier; Speich, Sabrina; Szczap, Frédéric; Totems, Julien; Vogel, Raphaela; Wendisch, Manfred; Wirth, Martin

2017-11-01

Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.

EUREC4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation

Science.gov (United States)

Bony, Sandrine; Stevens, Bjorn; Ament, Felix; Bigorre, Sebastien; Chazette, Patrick; Crewell, Susanne; Delanoë, Julien; Emanuel, Kerry; Farrell, David; Flamant, Cyrille; Gross, Silke; Hirsch, Lutz; Karstensen, Johannes; Mayer, Bernhard; Nuijens, Louise; Ruppert, James H.; Sandu, Irina; Siebesma, Pier; Speich, Sabrina; Szczap, Frédéric; Totems, Julien; Vogel, Raphaela; Wendisch, Manfred; Wirth, Martin

Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of tradecumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of tradecumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.

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.

Statistical thermodynamics and the size distributions of tropical convective clouds.

Science.gov (United States)

Garrett, T. J.; Glenn, I. B.; Krueger, S. K.; Ferlay, N.

2017-12-01

Parameterizations for sub-grid cloud dynamics are commonly developed by using fine scale modeling or measurements to explicitly resolve the mechanistic details of clouds to the best extent possible, and then to formulating these behaviors cloud state for use within a coarser grid. A second is to invoke physical intuition and some very general theoretical principles from equilibrium statistical thermodynamics. This second approach is quite widely used elsewhere in the atmospheric sciences: for example to explain the heat capacity of air, blackbody radiation, or even the density profile or air in the atmosphere. Here we describe how entrainment and detrainment across cloud perimeters is limited by the amount of available air and the range of moist static energy in the atmosphere, and that constrains cloud perimeter distributions to a power law with a -1 exponent along isentropes and to a Boltzmann distribution across isentropes. Further, the total cloud perimeter density in a cloud field is directly tied to the buoyancy frequency of the column. These simple results are shown to be reproduced within a complex dynamic simulation of a tropical convective cloud field and in passive satellite observations of cloud 3D structures. The implication is that equilibrium tropical cloud structures can be inferred from the bulk thermodynamic structure of the atmosphere without having to analyze computationally expensive dynamic simulations.

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)

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.

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

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.

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.

Formation of Silicate and Titanium Clouds on Hot Jupiters

Science.gov (United States)

Powell, Diana; Zhang, Xi; Gao, Peter; Parmentier, Vivien

2018-06-01

We present the first application of a bin-scheme microphysical and vertical transport model to determine the size distribution of titanium and silicate cloud particles in the atmospheres of hot Jupiters. We predict particle size distributions from first principles for a grid of planets at four representative equatorial longitudes, and investigate how observed cloud properties depend on the atmospheric thermal structure and vertical mixing. The predicted size distributions are frequently bimodal and irregular in shape. There is a negative correlation between the total cloud mass and equilibrium temperature as well as a positive correlation between the total cloud mass and atmospheric mixing. The cloud properties on the east and west limbs show distinct differences that increase with increasing equilibrium temperature. Cloud opacities are roughly constant across a broad wavelength range, with the exception of features in the mid-infrared. Forward-scattering is found to be important across the same wavelength range. Using the fully resolved size distribution of cloud particles as opposed to a mean particle size has a distinct impact on the resultant cloud opacities. The particle size that contributes the most to the cloud opacity depends strongly on the cloud particle size distribution. We predict that it is unlikely that silicate or titanium clouds are responsible for the optical Rayleigh scattering slope seen in many hot Jupiters. We suggest that cloud opacities in emission may serve as sensitive tracers of the thermal state of a planet’s deep interior through the existence or lack of a cold trap in the deep atmosphere.

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,

Temporal evolution of stable water isotopologues in cloud droplets in a hill cap cloud in central Europe (HCCT-2010

Directory of Open Access Journals (Sweden)

J. K. Spiegel

2012-12-01

Full Text Available In this work, we present the first study resolving the temporal evolution of δ²H and δ¹⁸O values in cloud droplets during 13 different cloud events. The cloud events were probed on a 937 m high mountain chain in Germany in the framework of the Hill Cap Cloud Thuringia 2010 campaign (HCCT-2010 in September and October 2010. The δ values of cloud droplets ranged from −77‰ to −15‰ (δ²H and from −12.1‰ to −3.9‰ (δ¹⁸O over the whole campaign. The cloud water line of the measured δ values was δ²H=7.8×δ¹⁸O+13×10⁻³, which is of similar slope, but with higher deuterium excess than other Central European Meteoric Water Lines. Decreasing δ values in the course of the campaign agree with seasonal trends observed in rain in central Europe. The deuterium excess was higher in clouds developing after recent precipitation revealing episodes of regional moisture recycling. The variations in δ values during one cloud event could either result from changes in meteorological conditions during condensation or from variations in the δ values of the water vapor feeding the cloud. To test which of both aspects dominated during the investigated cloud events, we modeled the variation in δ values in cloud water using a closed box model. We could show that the variation in δ values of two cloud events was mainly due to changes in local temperature conditions. For the other eleven cloud events, the variation was most likely caused by changes in the isotopic composition of the advected and entrained vapor. Frontal passages during two of the latter cloud events led to the strongest temporal changes in both δ²H (≈ 6‰ per hour and δ¹⁸O (≈ 0.6‰ per hour. Moreover, a detailed trajectory analysis for the two longest cloud events revealed that variations in the entrained vapor were most likely related to rain out or changes in relative

Temporal evolution of stable water isotopologues in cloud droplets in a hill cap cloud in central Europe (HCCT-2010)

Science.gov (United States)

Spiegel, J.K.; Aemisegger, F.; Scholl, M.; Wienhold, F.G.; Collett, J.L.; Lee, T.; van Pinxteren, D.; Mertes, S.; Tilgner, A.; Herrmann, H.; Werner, Roland A.; Buchmann, N.; Eugster, W.

2012-01-01

In this work, we present the first study resolving the temporal evolution of δ2H and δ18O values in cloud droplets during 13 different cloud events. The cloud events were probed on a 937 m high mountain chain in Germany in the framework of the Hill Cap Cloud Thuringia 2010 campaign (HCCT-2010) in September and October 2010. The δ values of cloud droplets ranged from −77‰ to −15‰ (δ2H) and from −12.1‰ to −3.9‰ (δ18O) over the whole campaign. The cloud water line of the measured δ values was δ2H=7.8×δ18O+13×10−3, which is of similar slope, but with higher deuterium excess than other Central European Meteoric Water Lines. Decreasing δ values in the course of the campaign agree with seasonal trends observed in rain in central Europe. The deuterium excess was higher in clouds developing after recent precipitation revealing episodes of regional moisture recycling. The variations in δ values during one cloud event could either result from changes in meteorological conditions during condensation or from variations in the δ values of the water vapor feeding the cloud. To test which of both aspects dominated during the investigated cloud events, we modeled the variation in δ values in cloud water using a closed box model. We could show that the variation in δ values of two cloud events was mainly due to changes in local temperature conditions. For the other eleven cloud events, the variation was most likely caused by changes in the isotopic composition of the advected and entrained vapor. Frontal passages during two of the latter cloud events led to the strongest temporal changes in both δ2H (≈ 6‰ per hour) and δ18O (≈ 0.6‰ per hour). Moreover, a detailed trajectory analysis for the two longest cloud events revealed that variations in the entrained vapor were most likely related to rain out or changes in relative humidity and temperature at the moisture source region or both. This study illustrates the sensitivity of stable isotope

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.

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.

Impact of aerosol intrusions on sea-ice melting rates and the structure Arctic boundary layer clouds

Science.gov (United States)

Cotton, W.; Carrio, G.; Jiang, H.

2003-04-01

The Los Alamos National Laboratory sea-ice model (LANL CICE) was implemented into the real-time and research versions of the Colorado State University-Regional Atmospheric Modeling System (RAMS@CSU). The original version of CICE was modified in its structure to allow module communication in an interactive multigrid framework. In addition, some improvements have been made in the routines involved in the coupling, among them, the inclusion of iterative methods that consider variable roughness lengths for snow-covered ice thickness categories. This version of the model also includes more complex microphysics that considers the nucleation of cloud droplets, allowing the prediction of mixing ratios and number concentrations for all condensed water species. The real-time version of RAMS@CSU automatically processes the NASA Team SSMI F13 25km sea-ice coverage data; the data are objectively analyzed and mapped to the model grid configuration. We performed two types of cloud resolving simulations to assess the impact of the entrainment of aerosols from above the inversion on Arctic boundary layer clouds. The first series of numerical experiments corresponds to a case observed on May 4 1998 during the FIRE-ACE/SHEBA field experiment. Results indicate a significant impact on the microstructure of the simulated clouds. When assuming polluted initial profiles above the inversion, the liquid water fraction of the cloud monotonically decreases, the total condensate paths increases and downward IR tends to increase due to a significant increase in the ice water path. The second set of cloud resolving simulations focused on the evaluation of the potential effect of aerosol concentration above the inversion on melting rates during spring-summer period. For these multi-month simulations, the IFN and CCN profiles were also initialized assuming the 4 May profiles as benchmarks. Results suggest that increasing the aerosol concentrations above the boundary layer increases sea-ice melting

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

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.

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

Response to marine cloud brightening in a multi-model ensemble

Directory of Open Access Journals (Sweden)

C. W. Stjern

2018-01-01

Full Text Available Here we show results from Earth system model simulations from the marine cloud brightening experiment G4cdnc of the Geoengineering Model Intercomparison Project (GeoMIP. The nine contributing models prescribe a 50 % increase in the cloud droplet number concentration (CDNC of low clouds over the global oceans in an experiment dubbed G4cdnc, with the purpose of counteracting the radiative forcing due to anthropogenic greenhouse gases under the RCP4.5 scenario. The model ensemble median effective radiative forcing (ERF amounts to −1.9 W m−2, with a substantial inter-model spread of −0.6 to −2.5 W m−2. The large spread is partly related to the considerable differences in clouds and their representation between the models, with an underestimation of low clouds in several of the models. All models predict a statistically significant temperature decrease with a median of (for years 2020–2069 −0.96 [−0.17 to −1.21] K relative to the RCP4.5 scenario, with particularly strong cooling over low-latitude continents. Globally averaged there is a weak but significant precipitation decrease of −2.35 [−0.57 to −2.96] % due to a colder climate, but at low latitudes there is a 1.19 % increase over land. This increase is part of a circulation change where a strong negative top-of-atmosphere (TOA shortwave forcing over subtropical oceans, caused by increased albedo associated with the increasing CDNC, is compensated for by rising motion and positive TOA longwave signals over adjacent land regions.

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.

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...

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...

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.

Improvement of Systematic Bias of mean state and the intraseasonal variability of CFSv2 through superparameterization and revised cloud-convection-radiation parameterization

Science.gov (United States)

Mukhopadhyay, P.; Phani Murali Krishna, R.; Goswami, Bidyut B.; Abhik, S.; Ganai, Malay; Mahakur, M.; Khairoutdinov, Marat; Dudhia, Jimmy

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of

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...

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

Energy Technology Data Exchange (ETDEWEB)

Benincasa, Samantha M.; Pudritz, Ralph E.; Wadsley, James [Department of Physics and Astronomy, McMaster University, Hamilton, ON L8S 4M1 (Canada); Tasker, Elizabeth J. [Department of Physics, Faculty of Science, Hokkaido University, Kita-ku, Sapporo 060-0810 (Japan)

2013-10-10

We present the results of a study of simulated giant molecular clouds (GMCs) formed in a Milky Way-type galactic disk with a flat rotation curve. This simulation, which does not include star formation or feedback, produces clouds with masses ranging between 10{sup 4} M{sub ☉} and 10{sup 7} M{sub ☉}. We compare our simulated cloud population to two observational surveys: the Boston University-Five College Radio Astronomy Observatory Galactic Ring Survey and the BIMA All-Disk Survey of M33. An analysis of the global cloud properties as well as a comparison of Larson's scaling relations is carried out. We find that simulated cloud properties agree well with the observed cloud properties, with the closest agreement occurring between the clouds at comparable resolution in M33. Our clouds are highly filamentary—a property that derives both from their formation due to gravitational instability in the sheared galactic environment, as well as to cloud-cloud gravitational encounters. We also find that the rate at which potentially star-forming gas accumulates within dense regions—wherein n{sub thresh} ≥ 10{sup 4} cm{sup –3}—is 3% per 10 Myr, in clouds of roughly 10{sup 6} M{sub ☉}. This suggests that star formation rates in observed clouds are related to the rates at which gas can be accumulated into dense subregions within GMCs via filamentary flows. The most internally well-resolved clouds are chosen for listing in a catalog of simulated GMCs—the first of its kind. The cataloged clouds are available as an extracted data set from the global simulation.

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.

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.

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.

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.

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

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.

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

Cloud Computing Security in Openstack Architecture: General Overview

Directory of Open Access Journals (Sweden)

Gleb Igorevich Shakulo

2015-10-01

Full Text Available The subject of article is cloud computing security. Article begins with author analyzing cloud computing advantages and disadvantages, factors of growth, both positive and negative. Among latter, security is deemed one of the most prominent. Furthermore, author takes architecture of OpenStack project as an example for study: describes its essential components and their interconnection. As conclusion, author raises series of questions as possible areas of further research to resolve security concerns, thus making cloud computing more secure technology.

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.

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 ...

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.

Intercomparison between CMIP5 model and MODIS satellite-retrieved data of aerosol optical depth, cloud fraction, and cloud-aerosol interactions

Science.gov (United States)

Sockol, Alyssa; Small Griswold, Jennifer D.

2017-08-01

Aerosols are a critical component of the Earth's atmosphere and can affect the climate of the Earth through their interactions with solar radiation and clouds. Cloud fraction (CF) and aerosol optical depth (AOD) at 550 nm from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used with analogous cloud and aerosol properties from Historical Phase 5 of the Coupled Model Intercomparison Project (CMIP5) model runs that explicitly include anthropogenic aerosols and parameterized cloud-aerosol interactions. The models underestimate AOD by approximately 15% and underestimate CF by approximately 10% overall on a global scale. A regional analysis is then used to evaluate model performance in two regions with known biomass burning activity and absorbing aerosol (South America (SAM) and South Africa (SAF)). In SAM, the models overestimate AOD by 4.8% and underestimate CF by 14%. In SAF, the models underestimate AOD by 35% and overestimate CF by 13.4%. Average annual cycles show that the monthly timing of AOD peaks closely match satellite data in both SAM and SAF for all except the Community Atmosphere Model 5 and Geophysical Fluid Dynamics Laboratory (GFDL) models. Monthly timing of CF peaks closely match for all models (except GFDL) for SAM and SAF. Sorting monthly averaged 2° × 2.5° model or MODIS CF as a function of AOD does not result in the previously observed "boomerang"-shaped CF versus AOD relationship characteristic of regions with absorbing aerosols from biomass burning. Cloud-aerosol interactions, as observed using daily (or higher) temporal resolution data, are not reproducible at the spatial or temporal resolution provided by the CMIP5 models.

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.

Cloud Condensation Nuclei Activity of Aerosols during GoAmazon 2014/15 Field Campaign Report

Energy Technology Data Exchange (ETDEWEB)

Wang, J. [Brookhaven National Lab. (BNL), Upton, NY (United States); Martin, S. T. [Harvard Univ., Cambridge, MA (United States); Kleinman, L. [Brookhaven National Lab. (BNL), Upton, NY (United States); Thalman, R. M. [Brookhaven National Lab. (BNL), Upton, NY (United States)

2016-03-01

Aerosol indirect effects, which represent the impact of aerosols on climate through influencing the properties of clouds, remain one of the main uncertainties in climate predictions (Stocker et al. 2013). Reducing this large uncertainty requires both improved understanding and representation of aerosol properties and processes in climate models, including the cloud activation properties of aerosols. The Atmospheric System Research (ASR) science program plan of January 2010 states that: “A key requirement for simulating aerosol-cloud interactions is the ability to calculate cloud condensation nuclei and ice nuclei (CCN and IN, respectively) concentrations as a function of supersaturation from the chemical and microphysical properties of the aerosol.” The Observations and Modeling of the Green Ocean Amazon (GoAmazon 2014/15) study seeks to understand how aerosol and cloud life cycles are influenced by pollutant outflow from a tropical megacity (Manaus)—in particular, the differences in cloud-aerosol-precipitation interactions between polluted and pristine conditions. One key question of GoAmazon2014/5 is: “What is the influence of the Manaus pollution plume on the cloud condensation nuclei (CCN) activities of the aerosol particles and the secondary organic material in the particles?” To address this question, we measured size-resolved CCN spectra, a critical measurement for GoAmazon2014/5.

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.

Cloud Processing of Gases and Aerosols in Air Quality Modeling

Directory of Open Access Journals (Sweden)

Leiming Zhang

2011-10-01

Full Text Available The representations of cloud processing of gases and aerosols in some of the current state-of-the-art regional air quality models in North America and Europe are reviewed. Key processes reviewed include aerosol activation (or nucleation scavenging of aerosols, aqueous-phase chemistry, and wet deposition/removal of atmospheric tracers. It was found that models vary considerably in the parameterizations or algorithms used in representing these processes. As an emerging area of research, the current understanding of the uptake of water soluble organics by cloud droplets and the potential aqueous-phase reaction pathways leading to the atmospheric secondary organic aerosol (SOA formation is also reviewed. Sensitivity tests using the AURAMS model have been conducted in order to assess the impact on modeled regional particulate matter (PM from: (1 the different aerosol activation schemes, (2 the different below-cloud particle scavenging algorithms, and (3 the inclusion of cloud processing of water soluble organics as a potential pathway for the formation of atmospheric SOA. It was found that the modeled droplet number concentrations and ambient PM size distributions were strongly affected by the use of different aerosol activation schemes. The impact on the modeled average ambient PM mass concentration was found to be limited in terms of averaged PM2.5 concentration (~a few percents but more significant in terms of PM1.0 (up to 10 percents. The modeled ambient PM was found to be moderately sensitive to the below-cloud particle scavenging algorithms, with relative differences up to 10% and 20% in terms of PM2.5 and PM10, respectively, when using the two different algorithms for the scavenging coefficient (Λ corresponding to the lower and upper bounds in the parameterization for Λ. The model simulation with the additional cloud uptake and processing of water-soluble organic gases was shown to improve the evaluation statistics for modeled PM2.5 OA

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...

STAR FORMATION LAWS: THE EFFECTS OF GAS CLOUD SAMPLING

International Nuclear Information System (INIS)

Calzetti, D.; Liu, G.; Koda, J.

2012-01-01

Recent observational results indicate that the functional shape of the spatially resolved star formation-molecular gas density relation depends on the spatial scale considered. These results may indicate a fundamental role of sampling effects on scales that are typically only a few times larger than those of the largest molecular clouds. To investigate the impact of this effect, we construct simple models for the distribution of molecular clouds in a typical star-forming spiral galaxy and, assuming a power-law relation between star formation rate (SFR) and cloud mass, explore a range of input parameters. We confirm that the slope and the scatter of the simulated SFR-molecular gas surface density relation depend on the size of the sub-galactic region considered, due to stochastic sampling of the molecular cloud mass function, and the effect is larger for steeper relations between SFR and molecular gas. There is a general trend for all slope values to tend to ∼unity for region sizes larger than 1-2 kpc, irrespective of the input SFR-cloud relation. The region size of 1-2 kpc corresponds to the area where the cloud mass function becomes fully sampled. We quantify the effects of selection biases in data tracing the SFR, either as thresholds (i.e., clouds smaller than a given mass value do not form stars) or as backgrounds (e.g., diffuse emission unrelated to current star formation is counted toward the SFR). Apparently discordant observational results are brought into agreement via this simple model, and the comparison of our simulations with data for a few galaxies supports a steep (>1) power-law index between SFR and molecular gas.

Cloud detection for MIPAS using singular vector decomposition

Directory of Open Access Journals (Sweden)

J. Hurley

2009-09-01

Full Text Available Satellite-borne high-spectral-resolution limb sounders, such as the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS onboard ENVISAT, provide information on clouds, especially optically thin clouds, which have been difficult to observe in the past. The aim of this work is to develop, implement and test a reliable cloud detection method for infrared spectra measured by MIPAS.

Current MIPAS cloud detection methods used operationally have been developed to detect cloud effective filling more than 30% of the measurement field-of-view (FOV, under geometric and optical considerations – and hence are limited to detecting fairly thick cloud, or large physical extents of thin cloud. In order to resolve thin clouds, a new detection method using Singular Vector Decomposition (SVD is formulated and tested. This new SVD detection method has been applied to a year's worth of MIPAS data, and qualitatively appears to be more sensitive to thin cloud than the current operational method.

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.

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)

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

Directory of Open Access Journals (Sweden)

G. McFarquhar

2009-07-01

Full Text Available The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9–10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process

Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms

Science.gov (United States)

Sednev, I.; Menon, S.; McFarquhar, G.

2009-07-01

The importance of Arctic mixed-phase clouds on radiation and the Arctic climate is well known. However, the development of mixed-phase cloud parameterization for use in large scale models is limited by lack of both related observations and numerical studies using multidimensional models with advanced microphysics that provide the basis for understanding the relative importance of different microphysical processes that take place in mixed-phase clouds. To improve the representation of mixed-phase cloud processes in the GISS GCM we use the GISS single-column model coupled to a bin resolved microphysics (BRM) scheme that was specially designed to simulate mixed-phase clouds and aerosol-cloud interactions. Using this model with the microphysical measurements obtained from the DOE ARM Mixed-Phase Arctic Cloud Experiment (MPACE) campaign in October 2004 at the North Slope of Alaska, we investigate the effect of ice initiation processes and Bergeron-Findeisen process (BFP) on glaciation time and longevity of single-layer stratiform mixed-phase clouds. We focus on observations taken during 9-10 October, which indicated the presence of a single-layer mixed-phase clouds. We performed several sets of 12-h simulations to examine model sensitivity to different ice initiation mechanisms and evaluate model output (hydrometeors' concentrations, contents, effective radii, precipitation fluxes, and radar reflectivity) against measurements from the MPACE Intensive Observing Period. Overall, the model qualitatively simulates ice crystal concentration and hydrometeors content, but it fails to predict quantitatively the effective radii of ice particles and their vertical profiles. In particular, the ice effective radii are overestimated by at least 50%. However, using the same definition as used for observations, the effective radii simulated and that observed were more comparable. We find that for the single-layer stratiform mixed-phase clouds simulated, process of ice phase initiation

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.

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...

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.

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.

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.

Challenges of Future VANET and Cloud-Based Approaches

Directory of Open Access Journals (Sweden)

Rakesh Shrestha

2018-01-01

Full Text Available Vehicular ad hoc networks (VANETs have been studied intensively due to their wide variety of applications and services, such as passenger safety, enhanced traffic efficiency, and infotainment. With the evolution of technology and sudden growth in the number of smart vehicles, traditional VANETs face several technical challenges in deployment and management due to less flexibility, scalability, poor connectivity, and inadequate intelligence. Cloud computing is considered a way to satisfy these requirements in VANETs. However, next-generation VANETs will have special requirements of autonomous vehicles with high mobility, low latency, real-time applications, and connectivity, which may not be resolved by conventional cloud computing. Hence, merging of fog computing with the conventional cloud for VANETs is discussed as a potential solution for several issues in current and future VANETs. In addition, fog computing can be enhanced by integrating Software-Defined Network (SDN, which provides flexibility, programmability, and global knowledge of the network. We present two example scenarios for timely dissemination of safety messages in future VANETs based on fog and a combination of fog and SDN. We also explained the issues that need to be resolved for the deployment of three different cloud-based approaches.

A Decade-Long European-Scale Convection-Resolving Climate Simulation on GPUs

Science.gov (United States)

Leutwyler, D.; Fuhrer, O.; Ban, N.; Lapillonne, X.; Lüthi, D.; Schar, C.

2016-12-01

Convection-resolving models have proven to be very useful tools in numerical weather prediction and in climate research. However, due to their extremely demanding computational requirements, they have so far been limited to short simulations and/or small computational domains. Innovations in the supercomputing domain have led to new supercomputer designs that involve conventional multi-core CPUs and accelerators such as graphics processing units (GPUs). One of the first atmospheric models that has been fully ported to GPUs is the Consortium for Small-Scale Modeling weather and climate model COSMO. This new version allows us to expand the size of the simulation domain to areas spanning continents and the time period up to one decade. We present results from a decade-long, convection-resolving climate simulation over Europe using the GPU-enabled COSMO version on a computational domain with 1536x1536x60 gridpoints. The simulation is driven by the ERA-interim reanalysis. The results illustrate how the approach allows for the representation of interactions between synoptic-scale and meso-scale atmospheric circulations at scales ranging from 1000 to 10 km. We discuss some of the advantages and prospects from using GPUs, and focus on the performance of the convection-resolving modeling approach on the European scale. Specifically we investigate the organization of convective clouds and on validate hourly rainfall distributions with various high-resolution data sets.

Cloud Atlas: Rotational Modulations in the L/T Transition Brown Dwarf Companion HN Peg B

Science.gov (United States)

Zhou, Yifan; Apai, Dániel; Metchev, Stanimir; Lew, Ben W. P.; Schneider, Glenn; Marley, Mark S.; Karalidi, Theodora; Manjavacas, Elena; Bedin, Luigi R.; Cowan, Nicolas B.; Miles-Páez, Paulo A.; Lowrance, Patrick J.; Radigan, Jacqueline; Burgasser, Adam J.

2018-03-01

Time-resolved observations of brown dwarfs’ rotational modulations provide powerful insights into the properties of condensate clouds in ultra-cool atmospheres. Multi-wavelength light curves reveal cloud vertical structures, condensate particle sizes, and cloud morphology, which directly constrain condensate cloud and atmospheric circulation models. We report results from Hubble Space Telescope/Wide Field Camera 3 near-infrared G141 taken in six consecutive orbits observations of HN Peg B, an L/T transition brown dwarf companion to a G0V type star. The best-fit sine wave to the 1.1–1.7 μm broadband light curve has an amplitude of 1.206% ± 0.025% and period of 15.4 ± 0.5 hr. The modulation amplitude has no detectable wavelength dependence except in the 1.4 μm water absorption band, indicating that the characteristic condensate particle sizes are large (>1 μm). We detect significantly (4.4σ) lower modulation amplitude in the 1.4 μm water absorption band and find that HN Peg B’s spectral modulation resembles those of early T type brown dwarfs. We also describe a new empirical interpolation method to remove spectral contamination from the bright host star. This method may be applied in other high-contrast time-resolved observations with WFC3.