NASA Astrophysics Data System (ADS)
Zhang, Junhua; Lohmann, Ulrike
2003-08-01
The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.
Evaluating statistical cloud schemes: What can we gain from ground-based remote sensing?
NASA Astrophysics Data System (ADS)
Grützun, V.; Quaas, J.; Morcrette, C. J.; Ament, F.
2013-09-01
Statistical cloud schemes with prognostic probability distribution functions have become more important in atmospheric modeling, especially since they are in principle scale adaptive and capture cloud physics in more detail. While in theory the schemes have a great potential, their accuracy is still questionable. High-resolution three-dimensional observational data of water vapor and cloud water, which could be used for testing them, are missing. We explore the potential of ground-based remote sensing such as lidar, microwave, and radar to evaluate prognostic distribution moments using the "perfect model approach." This means that we employ a high-resolution weather model as virtual reality and retrieve full three-dimensional atmospheric quantities and virtual ground-based observations. We then use statistics from the virtual observation to validate the modeled 3-D statistics. Since the data are entirely consistent, any discrepancy occurring is due to the method. Focusing on total water mixing ratio, we find that the mean ratio can be evaluated decently but that it strongly depends on the meteorological conditions as to whether the variance and skewness are reliable. Using some simple schematic description of different synoptic conditions, we show how statistics obtained from point or line measurements can be poor at representing the full three-dimensional distribution of water in the atmosphere. We argue that a careful analysis of measurement data and detailed knowledge of the meteorological situation is necessary to judge whether we can use the data for an evaluation of higher moments of the humidity distribution used by a statistical cloud scheme.
Studies in the use of cloud type statistics in mission simulation
NASA Technical Reports Server (NTRS)
Fowler, M. G.; Willand, J. H.; Chang, D. T.; Cogan, J. L.
1974-01-01
A study to further improve NASA's global cloud statistics for mission simulation is reported. Regional homogeneity in cloud types was examined; most of the original region boundaries defined for cloud cover amount in previous studies were supported by the statistics on cloud types and the number of cloud layers. Conditionality in cloud statistics was also examined with special emphasis on temporal and spatial dependencies, and cloud type interdependence. Temporal conditionality was found up to 12 hours, and spatial conditionality up to 200 miles; the diurnal cycle in convective cloudiness was clearly evident. As expected, the joint occurrence of different cloud types reflected the dynamic processes which form the clouds. Other phases of the study improved the cloud type statistics for several region and proposed a mission simulation scheme combining the 4-dimensional atmospheric model, sponsored by MSFC, with the global cloud model.
Further developments in cloud statistics for computer simulations
NASA Technical Reports Server (NTRS)
Chang, D. T.; Willand, J. H.
1972-01-01
This study is a part of NASA's continued program to provide global statistics of cloud parameters for computer simulation. The primary emphasis was on the development of the data bank of the global statistical distributions of cloud types and cloud layers and their applications in the simulation of the vertical distributions of in-cloud parameters such as liquid water content. These statistics were compiled from actual surface observations as recorded in Standard WBAN forms. Data for a total of 19 stations were obtained and reduced. These stations were selected to be representative of the 19 primary cloud climatological regions defined in previous studies of cloud statistics. Using the data compiled in this study, a limited study was conducted of the hemogeneity of cloud regions, the latitudinal dependence of cloud-type distributions, the dependence of these statistics on sample size, and other factors in the statistics which are of significance to the problem of simulation. The application of the statistics in cloud simulation was investigated. In particular, the inclusion of the new statistics in an expanded multi-step Monte Carlo simulation scheme is suggested and briefly outlined.
NASA Astrophysics Data System (ADS)
Posselt, D.; L'Ecuyer, T.; Matsui, T.
2009-05-01
Cloud resolving models are typically used to examine the characteristics of clouds and precipitation and their relationship to radiation and the large-scale circulation. As such, they are not required to reproduce the exact location of each observed convective system, much less each individual cloud. Some of the most relevant information about clouds and precipitation is provided by instruments located on polar-orbiting satellite platforms, but these observations are intermittent "snapshots" in time, making assessment of model performance challenging. In contrast to direct comparison, model results can be evaluated statistically. This avoids the requirement for the model to reproduce the observed systems, while returning valuable information on the performance of the model in a climate-relevant sense. The focus of this talk is a model evaluation study, in which updates to the microphysics scheme used in a three-dimensional version of the Goddard Cumulus Ensemble (GCE) model are evaluated using statistics of observed clouds, precipitation, and radiation. We present the results of multiday (non-equilibrium) simulations of organized deep convection using single- and double-moment versions of a the model's cloud microphysical scheme. Statistics of TRMM multi-sensor derived clouds, precipitation, and radiative fluxes are used to evaluate the GCE results, as are simulated TRMM measurements obtained using a sophisticated instrument simulator suite. We present advantages and disadvantages of performing model comparisons in retrieval and measurement space and conclude by motivating the use of data assimilation techniques for analyzing and improving model parameterizations.
NASA Technical Reports Server (NTRS)
Xiang, Xuwu; Smith, Eric A.; Tripoli, Gregory J.
1992-01-01
A hybrid statistical-physical retrieval scheme is explored which combines a statistical approach with an approach based on the development of cloud-radiation models designed to simulate precipitating atmospheres. The algorithm employs the detailed microphysical information from a cloud model as input to a radiative transfer model which generates a cloud-radiation model database. Statistical procedures are then invoked to objectively generate an initial guess composite profile data set from the database. The retrieval algorithm has been tested for a tropical typhoon case using Special Sensor Microwave/Imager (SSM/I) data and has shown satisfactory results.
Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM
NASA Astrophysics Data System (ADS)
Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Kloster, S.; Roeckner, E.; Zhang, J.
2007-07-01
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.
Validation of Microphysical Schemes in a CRM Using TRMM Satellite
NASA Astrophysics Data System (ADS)
Li, X.; Tao, W.; Matsui, T.; Liu, C.; Masunaga, H.
2007-12-01
The microphysical scheme in the Goddard Cumulus Ensemble (GCE) model has been the most heavily developed component in the past decade. The cloud-resolving model now has microphysical schemes ranging from the original Lin type bulk scheme, to improved bulk schemes, to a two-moment scheme, to a detailed bin spectral scheme. Even with the most sophisticated bin scheme, many uncertainties still exist, especially in ice phase microphysics. In this study, we take advantages of the long-term TRMM observations, especially the cloud profiles observed by the precipitation radar (PR), to validate microphysical schemes in the simulations of Mesoscale Convective Systems (MCSs). Two contrasting cases, a midlatitude summertime continental MCS with leading convection and trailing stratiform region, and an oceanic MCS in tropical western Pacific are studied. The simulated cloud structures and particle sizes are fed into a forward radiative transfer model to simulate the TRMM satellite sensors, i.e., the PR, the TRMM microwave imager (TMI) and the visible and infrared scanner (VIRS). MCS cases that match the structure and strength of the simulated systems over the 10-year period are used to construct statistics of different sensors. These statistics are then compared with the synthetic satellite data obtained from the forward radiative transfer calculations. It is found that the GCE model simulates the contrasts between the continental and oceanic case reasonably well, with less ice scattering in the oceanic case comparing with the continental case. However, the simulated ice scattering signals for both PR and TMI are generally stronger than the observations, especially for the bulk scheme and at the upper levels in the stratiform region. This indicates larger, denser snow/graupel particles at these levels. Adjusting microphysical schemes in the GCE model according the observations, especially the 3D cloud structure observed by TRMM PR, result in a much better agreement.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Sud, Y. C.; Walker, G. K.
1999-09-01
A prognostic cloud scheme named McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme) has been designed and developed with the aim of improving moist processes, microphysics of clouds, and cloud-radiation interactions in GCMs. McRAS distinguishes three types of clouds: convective, stratiform, and boundary layer. The convective clouds transform and merge into stratiform clouds on an hourly timescale, while the boundary layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the autoconversion equations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud microphysics throughout the life cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry.An evaluation of McRAS in a single-column model (SCM) with the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE) Phase III data has shown that, together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. The time history and time mean in-cloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvils and towers, and the convective updraft and downdraft velocities and mass fluxes all simulate a realistic behavior. Some of these diagnostics are not verifiable with data on hand. These SCM sensitivity tests show that (i) without clouds the simulated GATE-SCM atmosphere is cooler than observed; (ii) the model's convective scheme, RAS, is an important subparameterization of McRAS; and (iii) advection of cloud water substance is helpful in simulating better cloud distribution and cloud-radiation interaction. An evaluation of the performance of McRAS in the Goddard Earth Observing System II GCM is given in a companion paper (Part II).
Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes
NASA Astrophysics Data System (ADS)
van Lier-Walqui, M.; Morrison, H.; Kumjian, M. R.; Prat, O. P.; Martinkus, C.
2017-12-01
Atmospheric model parameterization schemes employ approximations to represent the effects of unresolved processes. These approximations are a source of error in forecasts, caused in part by considerable uncertainty about the optimal value of parameters within each scheme -- parameteric uncertainty. Furthermore, there is uncertainty regarding the best choice of the overarching structure of the parameterization scheme -- structrual uncertainty. Parameter estimation can constrain the first, but may struggle with the second because structural choices are typically discrete. We address this problem in the context of cloud microphysics parameterization schemes by creating a flexible framework wherein structural and parametric uncertainties can be simultaneously constrained. Our scheme makes no assuptions about drop size distribution shape or the functional form of parametrized process rate terms. Instead, these uncertainties are constrained by observations using a Markov Chain Monte Carlo sampler within a Bayesian inference framework. Our scheme, the Bayesian Observationally-constrained Statistical-physical Scheme (BOSS), has flexibility to predict various sets of prognostic drop size distribution moments as well as varying complexity of process rate formulations. We compare idealized probabilistic forecasts from versions of BOSS with varying levels of structural complexity. This work has applications in ensemble forecasts with model physics uncertainty, data assimilation, and cloud microphysics process studies.
Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM
NASA Astrophysics Data System (ADS)
Lohmann, U.; Stier, P.; Hoose, C.; Ferrachat, S.; Roeckner, E.; Zhang, J.
2007-03-01
The double-moment cloud microphysics scheme from ECHAM4 has been coupled to the size-resolved aerosol scheme ECHAM5-HAM. ECHAM5-HAM predicts the aerosol mass and number concentrations and the aerosol mixing state. This results in a much better agreement with observed vertical profiles of the black carbon and aerosol mass mixing ratios than with the previous version ECHAM4, where only the different aerosol mass mixing ratios were predicted. Also, 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 -1.8 W m-2 in ECHAM5, when a relative humidity dependent cloud cover scheme and present-day aerosol emissions representative for the year 2000 are used. It is larger when either a statistical cloud cover scheme or a different aerosol emission inventory are employed.
NASA Astrophysics Data System (ADS)
Chen, Y. H.; Kuo, C. P.; Huang, X.; Yang, P.
2017-12-01
Clouds play an important role in the Earth's radiation budget, and thus realistic and comprehensive treatments of cloud optical properties and cloud-sky radiative transfer are crucial for simulating weather and climate. However, most GCMs neglect LW scattering effects by clouds and tend to use inconsistent cloud SW and LW optical parameterizations. Recently, co-authors of this study have developed a new LW optical properties parameterization for ice clouds, which is based on ice cloud particle statistics from MODIS measurements and state-of-the-art scattering calculation. A two-stream multiple-scattering scheme has also been implemented into the RRTMG_LW, a widely used longwave radiation scheme by climate modeling centers. This study is to integrate both the new LW cloud-radiation scheme for ice clouds and the modified RRTMG_LW with scattering capability into the NCAR CESM to improve the cloud longwave radiation treatment. A number of single column model (SCM) simulations using the observation from the ARM SGP site on July 18 to August 4 in 1995 are carried out to assess the impact of new LW optical properties of clouds and scattering-enabled radiation scheme on simulated radiation budget and cloud radiative effect (CRE). The SCM simulation allows interaction between cloud and radiation schemes with other parameterizations, but the large-scale forcing is prescribed or nudged. Comparing to the results from the SCM of the standard CESM, the new ice cloud optical properties alone leads to an increase of LW CRE by 26.85 W m-2 in average, as well as an increase of the downward LW flux at surface by 6.48 W m-2. Enabling LW cloud scattering further increases the LW CRE by another 3.57 W m-2 and the downward LW flux at the surface by 0.2 W m-2. The change of LW CRE is mainly due to an increase of cloud top height, which enhances the LW CRE. A long-term simulation of CESM will be carried out to further understand the impact of such changes on simulated climates.
NASA Astrophysics Data System (ADS)
Kuang, Zhiming; Bretherton, Christopher S.
2006-07-01
In this paper, an idealized, high-resolution simulation of a gradually forced transition from shallow, nonprecipitating to deep, precipitating cumulus convection is described; how the cloud and transport statistics evolve as the convection deepens is explored; and the collected statistics are used to evaluate assumptions in current cumulus schemes. The statistical analysis methodologies that are used do not require tracing the history of individual clouds or air parcels; instead they rely on probing the ensemble characteristics of cumulus convection in the large model dataset. They appear to be an attractive way for analyzing outputs from cloud-resolving numerical experiments. Throughout the simulation, it is found that 1) the initial thermodynamic properties of the updrafts at the cloud base have rather tight distributions; 2) contrary to the assumption made in many cumulus schemes, nearly undiluted air parcels are too infrequent to be relevant to any stage of the simulated convection; and 3) a simple model with a spectrum of entraining plumes appears to reproduce most features of the cloudy updrafts, but significantly overpredicts the mass flux as the updrafts approach their levels of zero buoyancy. A buoyancy-sorting model was suggested as a potential remedy. The organized circulations of cold pools seem to create clouds with larger-sized bases and may correspondingly contribute to their smaller lateral entrainment rates. Our results do not support a mass-flux closure based solely on convective available potential energy (CAPE), and are in general agreement with a convective inhibition (CIN)-based closure. The general similarity in the ensemble characteristics of shallow and deep convection and the continuous evolution of the thermodynamic structure during the transition provide justification for developing a single unified cumulus parameterization that encompasses both shallow and deep convection.
Design and Performance of McRas in SCMs and GEOS I/II GCMs
NASA Technical Reports Server (NTRS)
Sud, Yogesh C.; Einaudi, Franco (Technical Monitor)
2000-01-01
The design of a prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) for general circulation models (GCMs) will be discussed. McRAS distinguishes three types of clouds: (1) convective, (2) stratiform, and (3) boundary-layer types. The convective clouds transform and merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds merge into the stratiform clouds instantly. The cloud condensate converts into precipitation following the auto-conversion equations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, as well as diffuse both horizontally and vertically with a fully interactive cloud-microphysics throughout the life-cycle of the cloud, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III and 5-ARN CART datasets has shown that together with the rest of the model physics, McRAS can simulate the observed temperature, humidity, and precipitation without many systematic errors. The time history and time mean incloud water and ice distribution, fractional cloudiness, cloud optical thickness, origin of precipitation in the convective anvil and towers, and the convective updraft and downdraft velocities and mass fluxes all show a realistic behavior. Performance of McRAS in GEOS 11 GCM shows several satisfactory features but some of the remaining deficiencies suggest need for additional research involving convective triggers and inhibitors, provision for continuously detraining updraft, a realistic scheme for cumulus gravity wave drag, and refinements to physical conditions for ascertaining cloud detrainment level.
How Well Can Infrared Sounders Observe the Atmosphere and Surface Through Clouds?
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, L. Larrabee; Yang, Ping
2010-01-01
Infrared sounders, such as the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared sounder (CrIS), have a cloud-impenetrable disadvantage in observing the atmosphere and surface under opaque cloudy conditions. However, recent studies indicate that hyperspectral, infrared sounders have the ability to detect cloud effective-optical and microphysical properties and to penetrate optically thin clouds in observing the atmosphere and surface to a certain degree. We have developed a retrieval scheme dealing with atmospheric conditions with cloud presence. This scheme can be used to analyze the retrieval accuracy of atmospheric and surface parameters under clear and cloudy conditions. In this paper, we present the surface emissivity results derived from IASI global measurements under both clear and cloudy conditions. The accuracy of surface emissivity derived under cloudy conditions is statistically estimated in comparison with those derived under clear sky conditions. The retrieval error caused by the clouds is shown as a function of cloud optical depth, which helps us to understand how well infrared sounders can observe the atmosphere and surface through clouds.
NASA Astrophysics Data System (ADS)
Tan, Z.; Schneider, T.; Teixeira, J.; Lam, R.; Pressel, K. G.
2014-12-01
Sub-grid scale (SGS) closures in current climate models are usually decomposed into several largely independent parameterization schemes for different cloud and convective processes, such as boundary layer turbulence, shallow convection, and deep convection. These separate parameterizations usually do not converge as the resolution is increased or as physical limits are taken. This makes it difficult to represent the interactions and smooth transition among different cloud and convective regimes. Here we present an eddy-diffusivity mass-flux (EDMF) closure that represents all sub-grid scale turbulent, convective, and cloud processes in a unified parameterization scheme. The buoyant updrafts and precipitative downdrafts are parameterized with a prognostic multiple-plume mass-flux (MF) scheme. The prognostic term for the mass flux is kept so that the life cycles of convective plumes are better represented. The interaction between updrafts and downdrafts are parameterized with the buoyancy-sorting model. The turbulent mixing outside plumes is represented by eddy diffusion, in which eddy diffusivity (ED) is determined from a turbulent kinetic energy (TKE) calculated from a TKE balance that couples the environment with updrafts and downdrafts. Similarly, tracer variances are decomposed consistently between updrafts, downdrafts and the environment. The closure is internally coupled with a probabilistic cloud scheme and a simple precipitation scheme. We have also developed a relatively simple two-stream radiative scheme that includes the longwave (LW) and shortwave (SW) effects of clouds, and the LW effect of water vapor. We have tested this closure in a single-column model for various regimes spanning stratocumulus, shallow cumulus, and deep convection. The model is also run towards statistical equilibrium with climatologically relevant large-scale forcings. These model tests are validated against large-eddy simulation (LES) with the same forcings. The comparison of results verifies the capacity of this closure to realistically represent different cloud and convective processes. Implementation of the closure in an idealized GCM allows us to study cloud feedbacks to climate change and to study the interactions between clouds, convections, and the large-scale circulation.
NASA Astrophysics Data System (ADS)
Storelvmo, T.
2015-12-01
Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.
The Incorporation and Initialization of Cloud Water/ice in AN Operational Forecast Model
NASA Astrophysics Data System (ADS)
Zhao, Qingyun
Quantitative precipitation forecasts have been one of the weakest aspects of numerical weather prediction models. Theoretical studies show that the errors in precipitation calculation can arise from three sources: errors in the large-scale forecasts of primary variables, errors in the crude treatment of condensation/evaporation and precipitation processes, and errors in the model initial conditions. A new precipitation parameterization scheme has been developed to investigate the forecast value of improved precipitation physics via the introduction of cloud water and cloud ice into a numerical prediction model. The main feature of this scheme is the explicit calculation of cloud water and cloud ice in both the convective and stratiform precipitation parameterization. This scheme has been applied to the eta model at the National Meteorological Center. Four extensive tests have been performed. The statistical results showed a significant improvement in the model precipitation forecasts. Diagnostic studies suggest that the inclusion of cloud ice is important in transferring water vapor to precipitation and in the enhancement of latent heat release; the latter subsequently affects the vertical motion field significantly. Since three-dimensional cloud data is absent from the analysis/assimilation system for most numerical models, a method has been proposed to incorporate observed precipitation and nephanalysis data into the data assimilation system to obtain the initial cloud field for the eta model. In this scheme, the initial moisture and vertical motion fields are also improved at the same time as cloud initialization. The physical initialization is performed in a dynamical initialization framework that uses the Newtonian dynamical relaxation method to nudge the model's wind and mass fields toward analyses during a 12-hour data assimilation period. Results from a case study showed that a realistic cloud field was produced by this method at the end of the data assimilation period. Precipitation forecasts have been significantly improved as a result of the improved initial cloud, moisture and vertical motion fields.
Aerosol Complexity and Implications for Predictability and Short-Term Forecasting
NASA Technical Reports Server (NTRS)
Colarco, Peter
2016-01-01
There are clear NWP and climate impacts from including aerosol radiative and cloud interactions. Changes in dynamics and cloud fields affect aerosol lifecycle, plume height, long-range transport, overall forcing of the climate system, etc. Inclusion of aerosols in NWP systems has benefit to surface field biases (e.g., T2m, U10m). Including aerosol affects has impact on analysis increments and can have statistically significant impacts on, e.g., tropical cyclogenesis. Above points are made especially with respect to aerosol radiative interactions, but aerosol-cloud interaction is a bigger signal on the global system. Many of these impacts are realized even in models with relatively simple (bulk) aerosol schemes (approx.10 -20 tracers). Simple schemes though imply simple representation of aerosol absorption and importantly for aerosol-cloud interaction particle-size distribution. Even so, more complex schemes exhibit a lot of diversity between different models, with issues such as size selection both for emitted particles and for modes. Prospects for complex sectional schemes to tune modal (and even bulk) schemes toward better selection of size representation. I think this is a ripe topic for more research -Systematic documentation of benefits of no vs. climatological vs. interactive (direct and then direct+indirect) aerosols. Document aerosol impact on analysis increments, inclusion in NWP data assimilation operator -Further refinement of baseline assumptions in model design (e.g., absorption, particle size distribution). Did not get into model resolution and interplay of other physical processes with aerosols (e.g., moist physics, obviously important), chemistry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Han, Ji-Young; Hong, Song-You; Sunny Lim, Kyo-Sun
The sensitivity of a cumulus parameterization scheme (CPS) to a representation of precipitation production is examined. To do this, the parameter that determines the fraction of cloud condensate converted to precipitation in the simplified Arakawa–Schubert (SAS) convection scheme is modified following the results from a cloud-resolving simulation. While the original conversion parameter is assumed to be constant, the revised parameter includes a temperature dependency above the freezing level, whichleadstolessproductionoffrozenprecipitating condensate with height. The revised CPS has been evaluated for a heavy rainfall event over Korea as well as medium-range forecasts using the Global/Regional Integrated Model system (GRIMs). The inefficient conversionmore » of cloud condensate to convective precipitation at colder temperatures generally leads to a decrease in pre-cipitation, especially in the category of heavy rainfall. The resultant increase of detrained moisture induces moistening and cooling at the top of clouds. A statistical evaluation of the medium-range forecasts with the revised precipitation conversion parameter shows an overall improvement of the forecast skill in precipitation and large-scale fields, indicating importance of more realistic representation of microphysical processes in CPSs.« less
NASA Technical Reports Server (NTRS)
Sud, Y. C.; Walker, G. K.
1998-01-01
A prognostic cloud scheme named McRAS (Microphysics of clouds with Relaxed Arakawa-Schubert Scheme) was developed with the aim of improving cloud-microphysics, and cloud-radiation interactions in GCMs. McRAS distinguishes convective, stratiform, and boundary-layer clouds. The convective clouds merge into stratiform clouds on an hourly time-scale, while the boundary-layer clouds do so instantly. The cloud condensate transforms into precipitation following the auto-conversion relations of Sundqvist that contain a parametric adaptation for the Bergeron-Findeisen process of ice crystal growth and collection of cloud condensate by precipitation. All clouds convect, advect, and diffuse both horizontally and vertically with a fully active cloud-microphysics throughout its life-cycle, while the optical properties of clouds are derived from the statistical distribution of hydrometeors and idealized cloud geometry. An evaluation of McRAS in a single column model (SCM) with the GATE Phase III data has shown that McRAS can simulate the observed temperature, humidity, and precipitation without discernible systematic errors. An evaluation with the ARM-CART SCM data in a cloud model intercomparison exercise shows reasonable but not an outstanding accurate simulation. Such a discrepancy is common to almost all models and is related, in part, to the input data quality. McRAS was implemented in the GEOS II GCM. A 50 month integration that was initialized with the ECMWF analysis of observations for January 1, 1987 and forced with the observed sea-surface temperatures and sea-ice distribution and vegetation properties (biomes, and soils), with prognostic soil moisture, snow-cover, and hydrology showed a very realistic simulation of cloud process, incloud water and ice, and cloud-radiative forcing (CRF). The simulated ITCZ showed a realistic time-mean structure and seasonal cycle, while the simulated CRF showed sensitivity to vertical distribution of cloud water which can be easily altered by the choice of time constant and incloud critical cloud water amount regulators for auto-conversion. The CRF and its feedbacks also have a profound effect on the ITCZ. Even though somewhat weaker than observed, the McRAS-GCM simulation produces robust 30-60 day oscillations in the 200 hPa velocity potential. Two ensembles of 4-summer (July, August, September) simulations, one each for 1987 and 1988 show that the McRAS-GCM simulates realistic and statistically significant precipitation differences over India, Central America, and tropical Africa. Several seasonal simulations were performed with McRAS-GEOS II GCM for the summer (June-July- August) and winter (December-January-February) periods to determine how the simulated clouds and CRFs would be affected by: i) advection of clouds; ii) cloud top entrainment instability, iii) cloud water inhomogeneity correction, and (iv) cloud production and dissipation in different cloud-processes. The results show that each of these processes contributes to the simulated cloud-fraction and CRF.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Somerville, Richard
2013-08-22
The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been a collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen).« less
NASA Technical Reports Server (NTRS)
Bacmeister, Julio; Rienecker, Michele; Suarez, Max; Norris, Peter
2007-01-01
The GEOS-5 atmospheric model is being developed as a weather-and-climate capable model. It must perform well in assimilation mode as well as in weather and climate simulations and forecasts and in coupled chemistry-climate simulations. In developing GEOS-5, attention has focused on the representation of moist processes. The moist physics package uses a single phase prognostic condensate and a prognostic cloud fraction. Two separate cloud types are distinguished by their source: "anvil" cloud originates in detraining convection, and large-scale cloud originates in a PDF-based condensation calculation. Ice and liquid phases for each cloud type are considered. Once created, condensate and fraction from the anvil and statistical cloud types experience the same loss processes: evaporation of condensate and fraction, auto-conversion of liquid or mixed phase condensate, sedimentation of frozen condensate, and accretion of condensate by falling precipitation. The convective parameterization scheme is the Relaxed Arakawa-Schubert, or RAS, scheme. Satellite data are used to evaluate the performance of the moist physics packages and help in their tuning. In addition, analysis of and comparisons to cloud-resolving models such as the Goddard Cumulus Ensemble model are used to help improve the PDFs used in the moist physics. The presentation will show some of our evaluations including precipitation diagnostics.
Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses
NASA Technical Reports Server (NTRS)
Molnar, Gyula I.; Susskind, Joel
2005-01-01
The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.
A Linearized Prognostic Cloud Scheme in NASAs Goddard Earth Observing System Data Assimilation Tools
NASA Technical Reports Server (NTRS)
Holdaway, Daniel; Errico, Ronald M.; Gelaro, Ronald; Kim, Jong G.; Mahajan, Rahul
2015-01-01
A linearized prognostic cloud scheme has been developed to accompany the linearized convection scheme recently implemented in NASA's Goddard Earth Observing System data assimilation tools. The linearization, developed from the nonlinear cloud scheme, treats cloud variables prognostically so they are subject to linearized advection, diffusion, generation, and evaporation. Four linearized cloud variables are modeled, the ice and water phases of clouds generated by large-scale condensation and, separately, by detraining convection. For each species the scheme models their sources, sublimation, evaporation, and autoconversion. Large-scale, anvil and convective species of precipitation are modeled and evaporated. The cloud scheme exhibits linearity and realistic perturbation growth, except around the generation of clouds through large-scale condensation. Discontinuities and steep gradients are widely used here and severe problems occur in the calculation of cloud fraction. For data assimilation applications this poor behavior is controlled by replacing this part of the scheme with a perturbation model. For observation impacts, where efficiency is less of a concern, a filtering is developed that examines the Jacobian. The replacement scheme is only invoked if Jacobian elements or eigenvalues violate a series of tuned constants. The linearized prognostic cloud scheme is tested by comparing the linear and nonlinear perturbation trajectories for 6-, 12-, and 24-h forecast times. The tangent linear model performs well and perturbations of clouds are well captured for the lead times of interest.
How to assess the impact of a physical parameterization in simulations of moist convection?
NASA Astrophysics Data System (ADS)
Grabowski, Wojciech
2017-04-01
A numerical model capable in simulating moist convection (e.g., cloud-resolving model or large-eddy simulation model) consists of a fluid flow solver combined with required representations (i.e., parameterizations) of physical processes. The later typically include cloud microphysics, radiative transfer, and unresolved turbulent transport. Traditional approaches to investigate impacts of such parameterizations on convective dynamics involve parallel simulations with different parameterization schemes or with different scheme parameters. Such methodologies are not reliable because of the natural variability of a cloud field that is affected by the feedback between the physics and dynamics. For instance, changing the cloud microphysics typically leads to a different realization of the cloud-scale flow, and separating dynamical and microphysical impacts is difficult. This presentation will present a novel modeling methodology, the piggybacking, that allows studying the impact of a physical parameterization on cloud dynamics with confidence. The focus will be on the impact of cloud microphysics parameterization. Specific examples of the piggybacking approach will include simulations concerning the hypothesized deep convection invigoration in polluted environments, the validity of the saturation adjustment in modeling condensation in moist convection, and separation of physical impacts from statistical uncertainty in simulations applying particle-based Lagrangian microphysics, the super-droplet method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hagos, Samson M.; Feng, Zhe; Burleyson, Casey D.
Regional cloud permitting model simulations of cloud populations observed during the 2011 ARM Madden Julian Oscillation Investigation Experiment/ Dynamics of Madden-Julian Experiment (AMIE/DYNAMO) field campaign are evaluated against radar and ship-based measurements. Sensitivity of model simulated surface rain rate statistics to parameters and parameterization of hydrometeor sizes in five commonly used WRF microphysics schemes are examined. It is shown that at 2 km grid spacing, the model generally overestimates rain rate from large and deep convective cores. Sensitivity runs involving variation of parameters that affect rain drop or ice particle size distribution (more aggressive break-up process etc) generally reduce themore » bias in rain-rate and boundary layer temperature statistics as the smaller particles become more vulnerable to evaporation. Furthermore significant improvement in the convective rain-rate statistics is observed when the horizontal grid-spacing is reduced to 1 km and 0.5 km, while it is worsened when run at 4 km grid spacing as increased turbulence enhances evaporation. The results suggest modulation of evaporation processes, through parameterization of turbulent mixing and break-up of hydrometeors may provide a potential avenue for correcting cloud statistics and associated boundary layer temperature biases in regional and global cloud permitting model simulations.« less
Private genome analysis through homomorphic encryption
2015-01-01
Background The rapid development of genome sequencing technology allows researchers to access large genome datasets. However, outsourcing the data processing o the cloud poses high risks for personal privacy. The aim of this paper is to give a practical solution for this problem using homomorphic encryption. In our approach, all the computations can be performed in an untrusted cloud without requiring the decryption key or any interaction with the data owner, which preserves the privacy of genome data. Methods We present evaluation algorithms for secure computation of the minor allele frequencies and χ2 statistic in a genome-wide association studies setting. We also describe how to privately compute the Hamming distance and approximate Edit distance between encrypted DNA sequences. Finally, we compare performance details of using two practical homomorphic encryption schemes - the BGV scheme by Gentry, Halevi and Smart and the YASHE scheme by Bos, Lauter, Loftus and Naehrig. Results The approach with the YASHE scheme analyzes data from 400 people within about 2 seconds and picks a variant associated with disease from 311 spots. For another task, using the BGV scheme, it took about 65 seconds to securely compute the approximate Edit distance for DNA sequences of size 5K and figure out the differences between them. Conclusions The performance numbers for BGV are better than YASHE when homomorphically evaluating deep circuits (like the Hamming distance algorithm or approximate Edit distance algorithm). On the other hand, it is more efficient to use the YASHE scheme for a low-degree computation, such as minor allele frequencies or χ2 test statistic in a case-control study. PMID:26733152
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berg, Larry K.; Kassianov, Evgueni I.; Long, Charles N.
2006-03-30
In previous work, Berg and Stull (2005) developed a new parameterization for Fair-Weather Cumuli (FWC). Preliminary testing of the new scheme used data collected during a field experiment conducted during the summer of 1996. This campaign included a few research flights conducted over three locations within the Atmospheric Radiation Measurement (ARM) Climate Research Facility (ACRF) Southern Great Plains (SGP) site. A more comprehensive verification of the new scheme requires a detailed climatology of FWC. Several cloud climatologies have been completed for the ACRF SGP, but these efforts have focused on either broad categories of clouds grouped by height and seasonmore » (e.g., Lazarus et al. 1999) or height and time of day (e.g., Dong et al. 2005). In these two examples, the low clouds were not separated by the type of cloud, either stratiform or cumuliform, nor were the horizontal chord length (the length of the cloud slice that passed directly overhead) or cloud aspect ratio (defined as the ratio of the cloud thickness to the cloud chord length) reported. Lane et al. (2002) presented distributions of cloud chord length, but only for one year. The work presented here addresses these shortcomings by looking explicitly at cases with FWC over five summers. Specifically, we will address the following questions: •Does the cloud fraction (CF), cloud-base height (CBH), and cloud-top height (CTH) of FWC change with the time of day or the year? •What is the distribution of FWC chord lengths? •Is there a relationship between the cloud chord length and the cloud thickness?« less
Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes
NASA Technical Reports Server (NTRS)
Chern, Jiun-Dar; Tao, Wei-Kuo; Lang, Stephen E.; Matsui, Toshihisa; Li, J.-L.; Mohr, Karen I.; Skofronick-Jackson, Gail M.; Peters-Lidard, Christa D.
2016-01-01
The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.
Excursion set mass functions for hierarchical Gaussian fluctuations
NASA Technical Reports Server (NTRS)
Bond, J. R.; Kaiser, N.; Cole, S.; Efstathiou, G.
1991-01-01
It is pointed out that most schemes for determining the mass function of virialized objects from the statistics of the initial density perturbation field suffer from the cloud-in-cloud problem of miscounting the number of low-mass clumps, many of which would have been subsumed into larger objects. The paper proposes a solution based on the theory of the excursion sets of F(r, R sub f), the four-dimensional initial density perturbation field smoothed with a continuous hierarchy of filters of radii R sub f.
Implementing a warm cloud microphysics parameterization for convective clouds in NCAR CESM
NASA Astrophysics Data System (ADS)
Shiu, C.; Chen, Y.; Chen, W.; Li, J. F.; Tsai, I.; Chen, J.; Hsu, H.
2013-12-01
Most of cumulus convection schemes use simple empirical approaches to convert cloud liquid mass to rain water or cloud ice to snow e.g. using a constant autoconversion rate and dividing cloud liquid mass into cloud water and ice as function of air temperature (e.g. Zhang and McFarlane scheme in NCAR CAM model). There are few studies trying to use cloud microphysical schemes to better simulate such precipitation processes in the convective schemes of global models (e.g. Lohmann [2008] and Song, Zhang, and Li [2012]). A two-moment warm cloud parameterization (i.e. Chen and Liu [2004]) is implemented into the deep convection scheme of CAM5.2 of CESM model for treatment of conversion of cloud liquid water to rain water. Short-term AMIP type global simulations are conducted to evaluate the possible impacts from the modification of this physical parameterization. Simulated results are further compared to observational results from AMWG diagnostic package and CloudSAT data sets. Several sensitivity tests regarding to changes in cloud top droplet concentration (here as a rough testing for aerosol indirect effects) and changes in detrained cloud size of convective cloud ice are also carried out to understand their possible impacts on the cloud and precipitation simulations.
PRECISE:PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare
Chen, Feng; Wang, Shuang; Mohammed, Noman; Cheng, Samuel; Jiang, Xiaoqian
2015-01-01
Quality improvement (QI) requires systematic and continuous efforts to enhance healthcare services. A healthcare provider might wish to compare local statistics with those from other institutions in order to identify problems and develop intervention to improve the quality of care. However, the sharing of institution information may be deterred by institutional privacy as publicizing such statistics could lead to embarrassment and even financial damage. In this article, we propose a PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare (PRECISE), which aims at enabling cross-institution comparison of healthcare statistics while protecting privacy. The proposed framework relies on a set of state-of-the-art cryptographic protocols including homomorphic encryption and Yao’s garbled circuit schemes. By securely pooling data from different institutions, PRECISE can rank the encrypted statistics to facilitate QI among participating institutes. We conducted experiments using MIMIC II database and demonstrated the feasibility of the proposed PRECISE framework. PMID:26146645
PRECISE:PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare.
Chen, Feng; Wang, Shuang; Mohammed, Noman; Cheng, Samuel; Jiang, Xiaoqian
2014-10-01
Quality improvement (QI) requires systematic and continuous efforts to enhance healthcare services. A healthcare provider might wish to compare local statistics with those from other institutions in order to identify problems and develop intervention to improve the quality of care. However, the sharing of institution information may be deterred by institutional privacy as publicizing such statistics could lead to embarrassment and even financial damage. In this article, we propose a PRivacy-prEserving Cloud-assisted quality Improvement Service in hEalthcare (PRECISE), which aims at enabling cross-institution comparison of healthcare statistics while protecting privacy. The proposed framework relies on a set of state-of-the-art cryptographic protocols including homomorphic encryption and Yao's garbled circuit schemes. By securely pooling data from different institutions, PRECISE can rank the encrypted statistics to facilitate QI among participating institutes. We conducted experiments using MIMIC II database and demonstrated the feasibility of the proposed PRECISE framework.
NASA Astrophysics Data System (ADS)
Zhao, Wenjie; Peng, Yiran; Wang, Bin; Yi, Bingqi; Lin, Yanluan; Li, Jiangnan
2018-05-01
A newly implemented Baum-Yang scheme for simulating ice cloud optical properties is compared with existing schemes (Mitchell and Fu schemes) in a standalone radiative transfer model and in the global climate model (GCM) Community Atmospheric Model Version 5 (CAM5). This study systematically analyzes the effect of different ice cloud optical schemes on global radiation and climate by a series of simulations with a simplified standalone radiative transfer model, atmospheric GCM CAM5, and a comprehensive coupled climate model. Results from the standalone radiative model show that Baum-Yang scheme yields generally weaker effects of ice cloud on temperature profiles both in shortwave and longwave spectrum. CAM5 simulations indicate that Baum-Yang scheme in place of Mitchell/Fu scheme tends to cool the upper atmosphere and strengthen the thermodynamic instability in low- and mid-latitudes, which could intensify the Hadley circulation and dehydrate the subtropics. When CAM5 is coupled with a slab ocean model to include simplified air-sea interaction, reduced downward longwave flux to surface in Baum-Yang scheme mitigates ice-albedo feedback in the Arctic as well as water vapor and cloud feedbacks in low- and mid-latitudes, resulting in an overall temperature decrease by 3.0/1.4 °C globally compared with Mitchell/Fu schemes. Radiative effect and climate feedback of the three ice cloud optical schemes documented in this study can be referred for future improvements on ice cloud simulation in CAM5.
A keyword searchable attribute-based encryption scheme with attribute update for cloud storage.
Wang, Shangping; Ye, Jian; Zhang, Yaling
2018-01-01
Ciphertext-policy attribute-based encryption (CP-ABE) scheme is a new type of data encryption primitive, which is very suitable for data cloud storage for its fine-grained access control. Keyword-based searchable encryption scheme enables users to quickly find interesting data stored in the cloud server without revealing any information of the searched keywords. In this work, we provide a keyword searchable attribute-based encryption scheme with attribute update for cloud storage, which is a combination of attribute-based encryption scheme and keyword searchable encryption scheme. The new scheme supports the user's attribute update, especially in our new scheme when a user's attribute need to be updated, only the user's secret key related with the attribute need to be updated, while other user's secret key and the ciphertexts related with this attribute need not to be updated with the help of the cloud server. In addition, we outsource the operation with high computation cost to cloud server to reduce the user's computational burden. Moreover, our scheme is proven to be semantic security against chosen ciphertext-policy and chosen plaintext attack in the general bilinear group model. And our scheme is also proven to be semantic security against chosen keyword attack under bilinear Diffie-Hellman (BDH) assumption.
A keyword searchable attribute-based encryption scheme with attribute update for cloud storage
Wang, Shangping; Zhang, Yaling
2018-01-01
Ciphertext-policy attribute-based encryption (CP-ABE) scheme is a new type of data encryption primitive, which is very suitable for data cloud storage for its fine-grained access control. Keyword-based searchable encryption scheme enables users to quickly find interesting data stored in the cloud server without revealing any information of the searched keywords. In this work, we provide a keyword searchable attribute-based encryption scheme with attribute update for cloud storage, which is a combination of attribute-based encryption scheme and keyword searchable encryption scheme. The new scheme supports the user's attribute update, especially in our new scheme when a user's attribute need to be updated, only the user's secret key related with the attribute need to be updated, while other user's secret key and the ciphertexts related with this attribute need not to be updated with the help of the cloud server. In addition, we outsource the operation with high computation cost to cloud server to reduce the user's computational burden. Moreover, our scheme is proven to be semantic security against chosen ciphertext-policy and chosen plaintext attack in the general bilinear group model. And our scheme is also proven to be semantic security against chosen keyword attack under bilinear Diffie-Hellman (BDH) assumption. PMID:29795577
A Robust Multi-Scale Modeling System for the Study of Cloud and Precipitation Processes
NASA Technical Reports Server (NTRS)
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)].
NASA Astrophysics Data System (ADS)
Dzambo, Andrew M.; Turner, David D.
2016-10-01
Midlatitude cirrus cloud macrophysical and microphysical properties have been shown in previous studies to vary seasonally and in various large-scale dynamical regimes, but relative humidity with respect to ice (RHI) within cirrus clouds has not been studied extensively in this context. Using a combination of radiosonde and millimeter-wavelength cloud radar data, we identify 1076 cirrus clouds spanning a 7 year period from 2004 to 2011. These data are separated into five classes using a previously published algorithm that is based largely on synoptic conditions. Using these data and classification scheme, we find that RHI in cirrus clouds varies seasonally. Variations in cirrus cloud RHI exist within the prescribed classifications; however, most of the variations are within the measurement uncertainty. Additionally, with the exception of nonsummer class cirrus, these variations are not statistically significant. We also find that cirrus cloud occurrence is not necessarily correlated with higher observed values of RHI. The structure of RHI in cirrus clouds varies more in thicker clouds, which follows previous studies showing that macrophysical and microphysical variability increases in thicker cirrus clouds.
NASA Astrophysics Data System (ADS)
Salzmann, M.; Ming, Y.; Golaz, J.-C.; Ginoux, P. A.; Morrison, H.; Gettelman, A.; Krämer, M.; Donner, L. J.
2010-08-01
A new stratiform cloud scheme including a two-moment bulk microphysics module, a cloud cover parameterization allowing ice supersaturation, and an ice nucleation parameterization has been implemented into the recently developed GFDL AM3 general circulation model (GCM) as part of an effort to treat aerosol-cloud-radiation interactions more realistically. Unlike the original scheme, the new scheme facilitates the study of cloud-ice-aerosol interactions via influences of dust and sulfate on ice nucleation. While liquid and cloud ice water path associated with stratiform clouds are similar for the new and the original scheme, column integrated droplet numbers and global frequency distributions (PDFs) of droplet effective radii differ significantly. This difference is in part due to a difference in the implementation of the Wegener-Bergeron-Findeisen (WBF) mechanism, which leads to a larger contribution from super-cooled droplets in the original scheme. Clouds are more likely to be either completely glaciated or liquid due to the WBF mechanism in the new scheme. Super-saturations over ice simulated with the new scheme are in qualitative agreement with observations, and PDFs of ice numbers and effective radii appear reasonable in the light of observations. Especially, the temperature dependence of ice numbers qualitatively agrees with in-situ observations. The global average long-wave cloud forcing decreases in comparison to the original scheme as expected when super-saturation over ice is allowed. Anthropogenic aerosols lead to a larger decrease in short-wave absorption (SWABS) in the new model setup, but outgoing long-wave radiation (OLR) decreases as well, so that the net effect of including anthropogenic aerosols on the net radiation at the top of the atmosphere (netradTOA = SWABS-OLR) is of similar magnitude for the new and the original scheme.
NASA Astrophysics Data System (ADS)
Salzmann, M.; Ming, Y.; Golaz, J.-C.; Ginoux, P. A.; Morrison, H.; Gettelman, A.; Krämer, M.; Donner, L. J.
2010-03-01
A new stratiform cloud scheme including a two-moment bulk microphysics module, a cloud cover parameterization allowing ice supersaturation, and an ice nucleation parameterization has been implemented into the recently developed GFDL AM3 general circulation model (GCM) as part of an effort to treat aerosol-cloud-radiation interactions more realistically. Unlike the original scheme, the new scheme facilitates the study of cloud-ice-aerosol interactions via influences of dust and sulfate on ice nucleation. While liquid and cloud ice water path associated with stratiform clouds are similar for the new and the original scheme, column integrated droplet numbers and global frequency distributions (PDFs) of droplet effective radii differ significantly. This difference is in part due to a difference in the implementation of the Wegener-Bergeron-Findeisen (WBF) mechanism, which leads to a larger contribution from super-cooled droplets in the original scheme. Clouds are more likely to be either completely glaciated or liquid due to the WBF mechanism in the new scheme. Super-saturations over ice simulated with the new scheme are in qualitative agreement with observations, and PDFs of ice numbers and effective radii appear reasonable in the light of observations. Especially, the temperature dependence of ice numbers qualitatively agrees with in-situ observations. The global average long-wave cloud forcing decreases in comparison to the original scheme as expected when super-saturation over ice is allowed. Anthropogenic aerosols lead to a larger decrease in short-wave absorption (SWABS) in the new model setup, but outgoing long-wave radiation (OLR) decreases as well, so that the net effect of including anthropogenic aerosols on the net radiation at the top of the atmosphere (netradTOA = SWABS-OLR) is of similar magnitude for the new and the original scheme.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shen, Samuel S. P.
2013-09-01
The long-range goal of several past and current projects in our DOE-supported research has been the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data, and the implementation and testing of these parameterizations in global models. The main objective of the present project being reported on here has been to develop and apply advanced statistical techniques, including Bayesian posterior estimates, to diagnose and evaluate features of both observed and simulated clouds. The research carried out under this project has been novel in two important ways. The first is that it is a key stepmore » in the development of practical stochastic cloud-radiation parameterizations, a new category of parameterizations that offers great promise for overcoming many shortcomings of conventional schemes. The second is that this work has brought powerful new tools to bear on the problem, because it has been an interdisciplinary collaboration between a meteorologist with long experience in ARM research (Somerville) and a mathematician who is an expert on a class of advanced statistical techniques that are well-suited for diagnosing model cloud simulations using ARM observations (Shen). The motivation and long-term goal underlying this work is the utilization of stochastic radiative transfer theory (Lane-Veron and Somerville, 2004; Lane et al., 2002) to develop a new class of parametric representations of cloud-radiation interactions and closely related processes for atmospheric models. The theoretical advantage of the stochastic approach is that it can accurately calculate the radiative heating rates through a broken cloud layer without requiring an exact description of the cloud geometry.« less
NASA Astrophysics Data System (ADS)
Alapaty, K.; Zhang, G. J.; Song, X.; Kain, J. S.; Herwehe, J. A.
2012-12-01
Short lived pollutants such as aerosols play an important role in modulating not only the radiative balance but also cloud microphysical properties and precipitation rates. In the past, to understand the interactions of aerosols with clouds, several cloud-resolving modeling studies were conducted. These studies indicated that in the presence of anthropogenic aerosols, single-phase deep convection precipitation is reduced or suppressed. On the other hand, anthropogenic aerosol pollution led to enhanced precipitation for mixed-phase deep convective clouds. To date, there have not been many efforts to incorporate such aerosol indirect effects (AIE) in mesoscale models or global models that use parameterization schemes for deep convection. Thus, the objective of this work is to implement a diagnostic cloud microphysical scheme directly into a deep convection parameterization facilitating aerosol indirect effects in the WRF-CMAQ integrated modeling systems. Major research issues addressed in this study are: What is the sensitivity of a deep convection scheme to cloud microphysical processes represented by a bulk double-moment scheme? How close are the simulated cloud water paths as compared to observations? Does increased aerosol pollution lead to increased precipitation for mixed-phase clouds? These research questions are addressed by performing several WRF simulations using the Kain-Fritsch convection parameterization and a diagnostic cloud microphysical scheme. In the first set of simulations (control simulations) the WRF model is used to simulate two scenarios of deep convection over the continental U.S. during two summer periods at 36 km grid resolution. In the second set, these simulations are repeated after incorporating a diagnostic cloud microphysical scheme to study the impacts of inclusion of cloud microphysical processes. Finally, in the third set, aerosol concentrations simulated by the CMAQ modeling system are supplied to the embedded cloud microphysical scheme to study impacts of aerosol concentrations on precipitation and radiation fields. Observations available from the ARM microbase data, the SURFRAD network, GOES imagery, and other reanalysis and measurements will be used to analyze the impacts of a cloud microphysical scheme and aerosol concentrations on parameterized convection.
Allowing for Horizontally Heterogeneous Clouds and Generalized Overlap in an Atmospheric GCM
NASA Technical Reports Server (NTRS)
Lee, D.; Oreopoulos, L.; Suarez, M.
2011-01-01
While fully accounting for 3D effects in Global Climate Models (GCMs) appears not realistic at the present time for a variety of reasons such as computational cost and unavailability of 3D cloud structure in the models, incorporation in radiation schemes of subgrid cloud variability described by one-point statistics is now considered feasible and is being actively pursued. This development has gained momentum once it was demonstrated that CPU-intensive spectrally explicit Independent Column Approximation (lCA) can be substituted by stochastic Monte Carlo ICA (McICA) calculations where spectral integration is accomplished in a manner that produces relatively benign random noise. The McICA approach has been implemented in Goddard's GEOS-5 atmospheric GCM as part of the implementation of the RRTMG radiation package. GEOS-5 with McICA and RRTMG can handle horizontally variable clouds which can be set via a cloud generator to arbitrarily overlap within the full spectrum of maximum and random both in terms of cloud fraction and layer condensate distributions. In our presentation we will show radiative and other impacts of the combined horizontal and vertical cloud variability on multi-year simulations of an otherwise untuned GEOS-5 with fixed SSTs. Introducing cloud horizontal heterogeneity without changing the mean amounts of condensate reduces reflected solar and increases thermal radiation to space, but disproportionate changes may increase the radiative imbalance at TOA. The net radiation at TOA can be modulated by allowing the parameters of the generalized overlap and heterogeneity scheme to vary, a dependence whose behavior we will discuss. The sensitivity of the cloud radiative forcing to the parameters of cloud horizontal heterogeneity and comparisons of CERES-derived forcing will be shown.
2013-06-21
potential temperature (Tripoli and Cotton , 1981), total wa- ter mixing ratio and cloud microphysics. The microphysics scheme has categories for cloud droplets...components, with diurnal variation, are both activated when the radiation scheme is included. A simpler scheme developed by Chen and Cotton (1987) is an...radiation. Additionally, one more simula- tion, Experiment 17, was conducted using the Chen– Cotton radiation scheme instead of the Harrington scheme
Searchable attribute-based encryption scheme with attribute revocation in cloud storage.
Wang, Shangping; Zhao, Duqiao; Zhang, Yaling
2017-01-01
Attribute based encryption (ABE) is a good way to achieve flexible and secure access control to data, and attribute revocation is the extension of the attribute-based encryption, and the keyword search is an indispensable part for cloud storage. The combination of both has an important application in the cloud storage. In this paper, we construct a searchable attribute-based encryption scheme with attribute revocation in cloud storage, the keyword search in our scheme is attribute based with access control, when the search succeeds, the cloud server returns the corresponding cipher text to user and the user can decrypt the cipher text definitely. Besides, our scheme supports multiple keywords search, which makes the scheme more practical. Under the assumption of decisional bilinear Diffie-Hellman exponent (q-BDHE) and decisional Diffie-Hellman (DDH) in the selective security model, we prove that our scheme is secure.
Wang, Weiguo; Liu, Xiaohong; Xie, Shaocheng; ...
2009-07-23
Here, cloud properties have been simulated with a new double-moment microphysics scheme under the framework of the single-column version of NCAR Community Atmospheric Model version 3 (CAM3). For comparison, the same simulation was made with the standard single-moment microphysics scheme of CAM3. Results from both simulations compared favorably with observations during the Tropical Warm Pool–International Cloud Experiment by the U.S. Department of Energy Atmospheric Radiation Measurement Program in terms of the temporal variation and vertical distribution of cloud fraction and cloud condensate. Major differences between the two simulations are in the magnitude and distribution of ice water content within themore » mixed-phase cloud during the monsoon period, though the total frozen water (snow plus ice) contents are similar. The ice mass content in the mixed-phase cloud from the new scheme is larger than that from the standard scheme, and ice water content extends 2 km further downward, which is in better agreement with observations. The dependence of the frozen water mass fraction on temperature from the new scheme is also in better agreement with available observations. Outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from the simulation with the new scheme is, in general, larger than that with the standard scheme, while the surface downward longwave radiation is similar. Sensitivity tests suggest that different treatments of the ice crystal effective radius contribute significantly to the difference in the calculations of TOA OLR, in addition to cloud water path. Numerical experiments show that cloud properties in the new scheme can respond reasonably to changes in the concentration of aerosols and emphasize the importance of correctly simulating aerosol effects in climate models for aerosol-cloud interactions. Further evaluation, especially for ice cloud properties based on in-situ data, is needed.« less
New, Improved Goddard Bulk-Microphysical Schemes for Studying Precipitation Processes in WRF
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2007-01-01
An improved bulk microphysical parameterization is implemented into the Weather Research and Forecasting ()VRF) model. This bulk microphysical scheme has three different options, 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atlantic hurricane). The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The Goddard 3ICE scheme with a cloud ice-snow-hail configuration agreed better with observations in terms of rainfall intensity and a narrow convective line than did simulations with a cloud ice-snow-graupel or cloud ice-snow (i.e., 2ICE) configuration. This is because the 3ICE-hail scheme includes dense ice precipitating (hail) particle with very fast fall speed (over 10 in For an Atlantic hurricane case, the Goddard microphysical schemes had no significant impact on the track forecast but did affect the intensity slightly. The improved Goddard schemes are also compared with WRF's three other 3ICE bulk microphysical schemes: WSM6, Purdue-Lin and Thompson. For the summer midlatitude convective line system, all of the schemes resulted in simulated precipitation events that were elongated in the southwest-northeast direction in qualitative agreement with the observed feature. However, the Goddard 3ICE scheme with the hail option and the Thompson scheme agree better with observations in terms of rainfall intensity, expect that the Goddard scheme simulated more heavy rainfall (over 48 mm/h). For the Atlantic hurricane case, none of the schemes had a significant impact on the track forecast; however, the simulated intensity using the Purdue-Lin scheme was much stronger than the other schemes. The vertical distributions of model simulated cloud species (i.e., snow) are quite sensitive to microphysical schemes, which is an important issue for future verification against satellite retrievals. Both the Purdue-Lin and WSM6 schemes simulated very little snow compared to the other schemes for both the midlatitude convective line and hurricane cases. Sensitivity tests are performed for these two WRF schemes to identify that snow productions could be increased by increasing the snow intercept, turning off the auto-conversion from snow to graupel and reducing the transfer processes from cloud-sized particles to precipitation-sized ice.
NASA Astrophysics Data System (ADS)
Kao, C.-Y. J.; Smith, W. S.
1999-05-01
A physically based cloud parameterization package, which includes the Arakawa-Schubert (AS) scheme for subgrid-scale convective clouds and the Sundqvist (SUN) scheme for nonconvective grid-scale layered clouds (hereafter referred to as the SUNAS cloud package), is incorporated into the National Center for Atmospheric Research (NCAR) Community Climate Model, Version 2 (CCM2). The AS scheme is used for a more reasonable heating distribution due to convective clouds and their associated precipitation. The SUN scheme allows for the prognostic computation of cloud water so that the cloud optical properties are more physically determined for shortwave and longwave radiation calculations. In addition, the formation of anvil-like clouds from deep convective systems is able to be simulated with the SUNAS package. A 10-year simulation spanning the period from 1980 to 1989 is conducted, and the effect of the cloud package on the January climate is assessed by comparing it with various available data sets and the National Center for Environmental Protection/NCAR reanalysis. Strengths and deficiencies of both the SUN and AS methods are identified and discussed. The AS scheme improves some aspects of the model dynamics and precipitation, especially with respect to the Pacific North America (PNA) pattern. CCM2's tendency to produce a westward bias of the 500 mbar stationary wave (time-averaged zonal anomalies) in the PNA sector is remedied apparently because of a less "locked-in" heating pattern in the tropics. The additional degree of freedom added by the prognostic calculation of cloud water in the SUN scheme produces interesting results in the modeled cloud and radiation fields compared with data. In general, too little cloud water forms in the tropics, while excessive cloud cover and cloud liquid water are simulated in midlatitudes. This results in a somewhat degraded simulation of the radiation budget. The overall simulated precipitation by the SUNAS package is, however, substantially improved over the original CCM2.
Cloud Radiation Forcings and Feedbacks: General Circulation Model Tests and Observational Validation
NASA Technical Reports Server (NTRS)
Lee,Wan-Ho; Iacobellis, Sam F.; Somerville, Richard C. J.
1997-01-01
Using an atmospheric general circulation model (the National Center for Atmospheric Research Community Climate Model: CCM2), the effects on climate sensitivity of several different cloud radiation parameterizations have been investigated. In addition to the original cloud radiation scheme of CCM2, four parameterizations incorporating prognostic cloud water were tested: one version with prescribed cloud radiative properties and three other versions with interactive cloud radiative properties. The authors' numerical experiments employ perpetual July integrations driven by globally constant sea surface temperature forcings of two degrees, both positive and negative. A diagnostic radiation calculation has been applied to investigate the partial contributions of high, middle, and low cloud to the total cloud radiative forcing, as well as the contributions of water vapor, temperature, and cloud to the net climate feedback. The high cloud net radiative forcing is positive, and the middle and low cloud net radiative forcings are negative. The total net cloud forcing is negative in all of the model versions. The effect of interactive cloud radiative properties on global climate sensitivity is significant. The net cloud radiative feedbacks consist of quite different shortwave and longwave components between the schemes with interactive cloud radiative properties and the schemes with specified properties. The increase in cloud water content in the warmer climate leads to optically thicker middle- and low-level clouds and in turn to negative shortwave feedbacks for the interactive radiative schemes, while the decrease in cloud amount simply produces a positive shortwave feedback for the schemes with a specified cloud water path. For the longwave feedbacks, the decrease in high effective cloudiness for the schemes without interactive radiative properties leads to a negative feedback, while for the other cases, the longwave feedback is positive. These cloud radiation parameterizations are empirically validated by using a single-column diagnostic model. together with measurements from the Atmospheric Radiation Measurement program and from the Tropical Ocean Global Atmosphere Combined Ocean-Atmosphere Response Experiment. The inclusion of prognostic cloud water produces a notable improvement in the realism of the parameterizations, as judged by these observations. Furthermore, the observational evidence suggests that deriving cloud radiative properties from cloud water content and microphysical characteristics is a promising route to further improvement.
NASA Technical Reports Server (NTRS)
Tao, W.K.; Shi, J.J.; Braun, S.; Simpson, J.; Chen, S.S.; Lang, S.; Hong, S.Y.; Thompson, G.; Peters-Lidard, C.
2009-01-01
A Goddard bulk microphysical parameterization is implemented into the Weather Research and Forecasting (WRF) model. This bulk microphysical scheme has three different options, 2ICE (cloud ice & snow), 3ICE-graupel (cloud ice, snow & graupel) and 3ICE-hail (cloud ice, snow & hail). High-resolution model simulations are conducted to examine the impact of microphysical schemes on different weather events: a midlatitude linear convective system and an Atlantic hurricane. The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The Goddard 3ICE scheme with the cloud ice-snow-hail configuration agreed better with observations ill of rainfall intensity and having a narrow convective line than did simulations with the cloud ice-snow-graupel and cloud ice-snow (i.e., 2ICE) configurations. This is because the Goddard 3ICE-hail configuration has denser precipitating ice particles (hail) with very fast fall speeds (over 10 m/s) For an Atlantic hurricane case, the Goddard microphysical scheme (with 3ICE-hail, 3ICE-graupel and 2ICE configurations) had no significant impact on the track forecast but did affect the intensity slightly. The Goddard scheme is also compared with WRF's three other 3ICE bulk microphysical schemes: WSM6, Purdue-Lin and Thompson. For the summer midlatitude convective line system, all of the schemes resulted in simulated precipitation events that were elongated in southwest-northeast direction in qualitative agreement with the observed feature. However, the Goddard 3ICE-hail and Thompson schemes were closest to the observed rainfall intensities although the Goddard scheme simulated more heavy rainfall (over 48 mm/h). For the Atlantic hurricane case, none of the schemes had a significant impact on the track forecast; however, the simulated intensity using the Purdue-Lin scheme was much stronger than the other schemes. The vertical distributions of model-simulated cloud species (e.g., snow) are quite sensitive to the microphysical schemes, which is an issue for future verification against satellite retrievals. Both the Purdue-Lin and WSM6 schemes simulated very little snow compared to the other schemes for both the midlatitude convective line and hurricane case. Sensitivity tests with these two schemes showed that increasing the snow intercept, turning off the auto-conversion from snow to graupel, eliminating dry growth, and reducing the transfer processes from cloud-sized particles to precipitation-sized ice collectively resulted in a net increase in those schemes' snow amounts.
NASA Astrophysics Data System (ADS)
Yu, Tianxu; Rose, William I.; Prata, A. J.
2002-08-01
Volcanic ash in volcanic clouds can be mapped in two dimensions using two-band thermal infrared data available from meteorological satellites. Wen and Rose [1994] developed an algorithm that allows retrieval of the effective particle size, the optical depth of the volcanic cloud, and the mass of fine ash in the cloud. Both the mapping and the retrieval scheme are less accurate in the humid tropical atmosphere. In this study we devised and tested a scheme for atmospheric correction of volcanic ash mapping and retrievals. The scheme utilizes infrared (IR) brightness temperature (BT) information in two infrared channels (both between 10 and 12.5 μm) and the brightness temperature differences (BTD) to estimate the amount of BTD shift caused by lower tropospheric water vapor. It is supported by the moderate resolution transmission (MODTRAN) analysis. The discrimination of volcanic clouds in the new scheme also uses both BT and BTD data but corrects for the effects of the water vapor. The new scheme is demonstrated and compared with the old scheme using two well-documented examples: (1) the 18 August 1992 volcanic cloud of Crater Peak, Mount Spurr, Alaska, and (2) the 26 December 1997 volcanic cloud from Soufriere Hills, Montserrat. The Spurr example represents a relatively ``dry'' subarctic atmospheric condition. The new scheme sees a volcanic cloud that is about 50% larger than the old. The mean optical depth and effective radii of cloud particles are lower by 22% and 9%, and the fine ash mass in the cloud is 14% higher. The Montserrat cloud is much smaller than Spurr and is more sensitive to atmospheric moisture. It also was located in a moist tropical atmosphere. For the Montserrat example the new scheme shows larger differences, with the area of the volcanic cloud being about 5.5 times larger, the optical depth and effective radii of particles lower by 56% and 28%, and the total fine particle mass in the cloud increased by 53%. The new scheme can be automated and can contribute to more accurate remote volcanic ash detection. More tests are needed to find the best way to estimate the water vapor effects in real time.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Xue; Klein, S. A.; Ma, H. -Y.
To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less
Zheng, Xue; Klein, S. A.; Ma, H. -Y.; ...
2016-07-19
To assess marine boundary layer (MBL) cloud simulations in three versions of the Community Atmosphere Model (CAM), three sets of short-term global hindcasts are performed and compared to Atmospheric Radiation Measurement Program (ARM) observations on Graciosa Island in the Azores from June 2009 to December 2010. Here, the three versions consist of CAM5.3 with default schemes (CAM5.3), CAM5.3 with Cloud Layers Unified By Binormals (CLUBB-MG1), and CAM5.3 with CLUBB and updated microphysics scheme (CLUBB-MG2). Our results show that relative to CAM5.3 default schemes, simulations with CLUBB better represent MBL cloud base height, the height of the major cloud layer, andmore » the daily cloud cover variability. CLUBB also better simulates the relationship of cloud fraction to cloud liquid water path (LWP) most likely due to CLUBB's consistent treatment of these variables through a probability distribution function (PDF) approach. Subcloud evaporation of precipitation is substantially enhanced in simulations with CLUBB-MG2 and is more realistic based on the limited observational estimate. Despite these improvements, all model versions underestimate MBL cloud cover. CLUBB-MG2 reduces biases in in-cloud LWP (clouds are not too bright) but there are still too few of MBL clouds due to an underestimate in the frequency of overcast scenes. Thus, combining CLUBB with MG2 scheme better simulates MBL cloud processes, but because biases remain in MBL cloud cover CLUBB-MG2 does not improve the simulation of the surface shortwave cloud radiative effect (CRE SW).« less
Double-moment cloud microphysics scheme for the deep convection parameterization in the GFDL AM3
NASA Astrophysics Data System (ADS)
Belochitski, A.; Donner, L.
2014-12-01
A double-moment cloud microphysical scheme originally developed by Morrision and Gettelman (2008) for the stratiform clouds and later adopted for the deep convection by Song and Zhang (2011) has been implemented in to the Geophysical Fluid Dynamics Laboratory's atmospheric general circulation model AM3. The scheme treats cloud drop, cloud ice, rain, and snow number concentrations and mixing ratios as diagnostic variables and incorporates processes of autoconversion, self-collection, collection between hydrometeor species, sedimentation, ice nucleation, drop activation, homogeneous and heterogeneous freezing, and the Bergeron-Findeisen process. Such detailed representation of microphysical processes makes the scheme suitable for studying the interactions between aerosols and convection, as well as aerosols' indirect effects on clouds and their roles in climate change. The scheme is first tested in the single column version of the GFDL AM3 using forcing data obtained at the U.S. Department of Energy Atmospheric Radiation Measurment project's Southern Great Planes site. Scheme's impact on SCM simulations is discussed. As the next step, runs of the full atmospheric GCM incorporating the new parameterization are compared to the unmodified version of GFDL AM3. Global climatological fields and their variability are contrasted with those of the original version of the GCM. Impact on cloud radiative forcing and climate sensitivity is investigated.
Double-moment Cloud Microphysics Scheme for the Deep Convection Parameterization in the GFDL AM3
NASA Astrophysics Data System (ADS)
Belochitski, A.; Donner, L.
2013-12-01
A double-moment cloud microphysical scheme originally developed by Morrision and Gettelman (2008) for the stratiform clouds and later adopted for the deep convection by Song and Zhang (2011) is being implemented in to the deep convection parameterization of Geophysical Fluid Dynamics Laboratory's atmospheric general circulation model AM3. The scheme treats cloud drop, cloud ice, rain, and snow number concentrations and mixing ratios as diagnostic variables and incorporates processes of autoconversion, self-collection, collection between hydrometeor species, sedimentation, ice nucleation, drop activation, homogeneous and heterogeneous freezing, and the Bergeron-Findeisen process. Detailed representation of microphysical processes makes the scheme suitable for studying the interactions between aerosols and convection, as well as aerosols' indirect effects on clouds and the roles of these effects in climate change. The scheme is implemented into the single column version of the GFDL AM3 and evaluated using large scale forcing data obtained at the U.S. Department of Energy Atmospheric Radiation Measurment project's Southern Great Planes and Tropical West Pacific sites. Sensitivity of the scheme to formulations for autoconversion of cloud water and its accretion by rain, self-collection of rain and self-collection of snow, as well as the formulation for heterogenous ice nucleation is investigated. In the future, tests with the full atmospheric GCM will be conducted.
Jiang, Lide; Wang, Menghua
2013-09-20
A new flag/masking scheme has been developed for identifying stray light and cloud shadow pixels that significantly impact the quality of satellite-derived ocean color products. Various case studies have been carried out to evaluate the performance of the new cloud contamination flag/masking scheme on ocean color products derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi National Polar-orbiting Partnership (SNPP). These include direct visual assessments, detailed quantitative case studies, objective statistic analyses, and global image examinations and comparisons. The National Oceanic and Atmospheric Administration (NOAA) Multisensor Level-1 to Level-2 (NOAA-MSL12) ocean color data processing system has been used in the study. The new stray light and cloud shadow identification method has been shown to outperform the current stray light flag in both valid data coverage and data quality of satellite-derived ocean color products. In addition, some cloud-related flags from the official VIIRS-SNPP data processing software, i.e., the Interface Data Processing System (IDPS), have been assessed. Although the data quality with the IDPS flags is comparable to that of the new flag implemented in the NOAA-MSL12 ocean color data processing system, the valid data coverage from the IDPS is significantly less than that from the NOAA-MSL12 using the new stray light and cloud shadow flag method. Thus, the IDPS flag/masking algorithms need to be refined and modified to reduce the pixel loss, e.g., the proposed new cloud contamination flag/masking can be implemented in IDPS VIIRS ocean color data processing.
Role of Microphysical Parameterizations with Droplet Relative Dispersion in IAP AGCM 4.1
Xie, Xiaoning; Zhang, He; Liu, Xiaodong; ...
2018-01-10
In previous studies we see that accurate descriptions of the cloud droplet effective radius (Re) and the autoconversion process of cloud droplets to raindrops (Au) can effectively improve simulated clouds and surface precipitation, and reduce the uncertainty of aerosol indirect effects in global climate models (GCMs). In this paper, we implement cloud microphysical schemes including two-moment Au and R e considering relative dispersion of the cloud droplet size distribution into version 4.1 of the Institute of Atmospheric Physics atmospheric GCM (IAP AGCM 4.1), which is the atmospheric component of the Chinese Academy of Sciences-Earth System model (CAS-ESM 1.0). An analysismore » of the effects of different schemes shows that the newly implemented schemes can improve both the simulated shortwave (SWCF) and longwave cloud radiative forcings (LWCF) as compared to the standard scheme in IAP AGCM 4.1. The new schemes also effectively enhance the large-scale precipitation, especially over low latitudes, although the influences of total precipitation are insignificant for different schemes. Further studies show that similar results can be found with the Community Atmosphere Model 5.1 (CAM5.1).« less
Role of Microphysical Parameterizations with Droplet Relative Dispersion in IAP AGCM 4.1
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xie, Xiaoning; Zhang, He; Liu, Xiaodong
In previous studies we see that accurate descriptions of the cloud droplet effective radius (Re) and the autoconversion process of cloud droplets to raindrops (Au) can effectively improve simulated clouds and surface precipitation, and reduce the uncertainty of aerosol indirect effects in global climate models (GCMs). In this paper, we implement cloud microphysical schemes including two-moment Au and R e considering relative dispersion of the cloud droplet size distribution into version 4.1 of the Institute of Atmospheric Physics atmospheric GCM (IAP AGCM 4.1), which is the atmospheric component of the Chinese Academy of Sciences-Earth System model (CAS-ESM 1.0). An analysismore » of the effects of different schemes shows that the newly implemented schemes can improve both the simulated shortwave (SWCF) and longwave cloud radiative forcings (LWCF) as compared to the standard scheme in IAP AGCM 4.1. The new schemes also effectively enhance the large-scale precipitation, especially over low latitudes, although the influences of total precipitation are insignificant for different schemes. Further studies show that similar results can be found with the Community Atmosphere Model 5.1 (CAM5.1).« less
Surface radiant flux densities inferred from LAC and GAC AVHRR data
NASA Astrophysics Data System (ADS)
Berger, F.; Klaes, D.
To infer surface radiant flux densities from current (NOAA-AVHRR, ERS-1/2 ATSR) and future meteorological (Envisat AATSR, MSG, METOP) satellite data, the complex, modular analysis scheme SESAT (Strahlungs- und Energieflüsse aus Satellitendaten) could be developed (Berger, 2001). This scheme allows the determination of cloud types, optical and microphysical cloud properties as well as surface and TOA radiant flux densities. After testing of SESAT in Central Europe and the Baltic Sea catchment (more than 400scenes U including a detailed validation with various surface measurements) it could be applied to a large number of NOAA-16 AVHRR overpasses covering the globe.For the analysis, two different spatial resolutions U local area coverage (LAC) andwere considered. Therefore, all inferred results, like global area coverage (GAC) U cloud cover, cloud properties and radiant properties, could be intercompared. Specific emphasis could be made to the surface radiant flux densities (all radiative balance compoments), where results for different regions, like Southern America, Southern Africa, Northern America, Europe, and Indonesia, will be presented. Applying SESAT, energy flux densities, like latent and sensible heat flux densities could also be determined additionally. A statistical analysis of all results including a detailed discussion for the two spatial resolutions will close this study.
Privacy-Preserving Location-Based Service Scheme for Mobile Sensing Data.
Xie, Qingqing; Wang, Liangmin
2016-11-25
With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP) can provide location-based service (LBS) for users. However, the mobile cloud is untrustworthy. The privacy concerns force the sensitive locations to be stored on the mobile cloud in an encrypted form. However, this brings a great challenge to utilize these data to provide efficient LBS. To solve this problem, we propose a privacy-preserving LBS scheme for mobile sensing data, based on the RSA (for Rivest, Shamir and Adleman) algorithm and ciphertext policy attribute-based encryption (CP-ABE) scheme. The mobile cloud can perform location distance computing and comparison efficiently for authorized users, without location privacy leakage. In the end, theoretical security analysis and experimental evaluation demonstrate that our scheme is secure against the chosen plaintext attack (CPA) and efficient enough for practical applications in terms of user side computation overhead.
Privacy-Preserving Location-Based Service Scheme for Mobile Sensing Data †
Xie, Qingqing; Wang, Liangmin
2016-01-01
With the wide use of mobile sensing application, more and more location-embedded data are collected and stored in mobile clouds, such as iCloud, Samsung cloud, etc. Using these data, the cloud service provider (CSP) can provide location-based service (LBS) for users. However, the mobile cloud is untrustworthy. The privacy concerns force the sensitive locations to be stored on the mobile cloud in an encrypted form. However, this brings a great challenge to utilize these data to provide efficient LBS. To solve this problem, we propose a privacy-preserving LBS scheme for mobile sensing data, based on the RSA (for Rivest, Shamir and Adleman) algorithm and ciphertext policy attribute-based encryption (CP-ABE) scheme. The mobile cloud can perform location distance computing and comparison efficiently for authorized users, without location privacy leakage. In the end, theoretical security analysis and experimental evaluation demonstrate that our scheme is secure against the chosen plaintext attack (CPA) and efficient enough for practical applications in terms of user side computation overhead. PMID:27897984
Cloud microphysics modification with an online coupled COSMO-MUSCAT regional model
NASA Astrophysics Data System (ADS)
Sudhakar, D.; Quaas, J.; Wolke, R.; Stoll, J.; Muehlbauer, A. D.; Tegen, I.
2015-12-01
Abstract: The quantification of clouds, aerosols, and aerosol-cloud interactions in models, continues to be a challenge (IPCC, 2013). In this scenario two-moment bulk microphysical scheme is used to understand the aerosol-cloud interactions in the regional model COSMO (Consortium for Small Scale Modeling). The two-moment scheme in COSMO has been especially designed to represent aerosol effects on the microphysics of mixed-phase clouds (Seifert et al., 2006). To improve the model predictability, the radiation scheme has been coupled with two-moment microphysical scheme. Further, the cloud microphysics parameterization has been modified via coupling COSMO with MUSCAT (MultiScale Chemistry Aerosol Transport model, Wolke et al., 2004). In this study, we will be discussing the initial result from the online-coupled COSMO-MUSCAT model system with modified two-moment parameterization scheme along with COSP (CFMIP Observational Simulator Package) satellite simulator. This online coupled model system aims to improve the sub-grid scale process in the regional weather prediction scenario. The constant aerosol concentration used in the Seifert and Beheng, (2006) parameterizations in COSMO model has been replaced by aerosol concentration derived from MUSCAT model. The cloud microphysical process from the modified two-moment scheme is compared with stand-alone COSMO model. To validate the robustness of the model simulation, the coupled model system is integrated with COSP satellite simulator (Muhlbauer et al., 2012). Further, the simulations are compared with MODIS (Moderate Resolution Imaging Spectroradiometer) and ISCCP (International Satellite Cloud Climatology Project) satellite products.
Research on multi-user encrypted search scheme in cloud environment
NASA Astrophysics Data System (ADS)
Yu, Zonghua; Lin, Sui
2017-05-01
Aiming at the existing problems of multi-user encrypted search scheme in cloud computing environment, a basic multi-user encrypted scheme is proposed firstly, and then the basic scheme is extended to an anonymous hierarchical management authority. Compared with most of the existing schemes, the scheme not only to achieve the protection of keyword information, but also to achieve the protection of user identity privacy; the same time, data owners can directly control the user query permissions, rather than the cloud server. In addition, through the use of a special query key generation rules, to achieve the hierarchical management of the user's query permissions. The safety analysis shows that the scheme is safe and that the performance analysis and experimental data show that the scheme is practicable.
Lagrangian Particle Tracking Simulation for Warm-Rain Processes in Quasi-One-Dimensional Domain
NASA Astrophysics Data System (ADS)
Kunishima, Y.; Onishi, R.
2017-12-01
Conventional cloud simulations are based on the Euler method and compute each microphysics process in a stochastic way assuming infinite numbers of particles within each numerical grid. They therefore cannot provide the Lagrangian statistics of individual particles in cloud microphysics (i.e., aerosol particles, cloud particles, and rain drops) nor discuss the statistical fluctuations due to finite number of particles. We here simulate the entire precipitation process of warm-rain, with tracking individual particles. We use the Lagrangian Cloud Simulator (LCS), which is based on the Euler-Lagrangian framework. In that framework, flow motion and scalar transportation are computed with the Euler method, and particle motion with the Lagrangian one. The LCS tracks particle motions and collision events individually with considering the hydrodynamic interaction between approaching particles with a superposition method, that is, it can directly represent the collisional growth of cloud particles. It is essential for trustworthy collision detection to take account of the hydrodynamic interaction. In this study, we newly developed a stochastic model based on the Twomey cloud condensation nuclei (CCN) activation for the Lagrangian tracking simulation and integrated it into the LCS. Coupling with the Euler computation for water vapour and temperature fields, the initiation and condensational growth of water droplets were computed in the Lagrangian way. We applied the integrated LCS for a kinematic simulation of warm-rain processes in a vertically-elongated domain of, at largest, 0.03×0.03×3000 (m3) with horizontal periodicity. Aerosol particles with a realistic number density, 5×107 (m3), were evenly distributed over the domain at the initial state. Prescribed updraft at the early stage initiated development of a precipitating cloud. We have confirmed that the obtained bulk statistics fairly agree with those from a conventional spectral-bin scheme for a vertical column domain. The centre of the discussion will be the Lagrangian statistics which is collected from the individual behaviour of the tracked particles.
NASA Astrophysics Data System (ADS)
Meinke, I.
2003-04-01
A new method is presented to validate cloud parametrization schemes in numerical atmospheric models with satellite data of scanning radiometers. This method is applied to the regional atmospheric model HRM (High Resolution Regional Model) using satellite data from ISCCP (International Satellite Cloud Climatology Project). Due to the limited reliability of former validations there has been a need for developing a new validation method: Up to now differences between simulated and measured cloud properties are mostly declared as deficiencies of the cloud parametrization scheme without further investigation. Other uncertainties connected with the model or with the measurements have not been taken into account. Therefore changes in the cloud parametrization scheme based on such kind of validations might not be realistic. The new method estimates uncertainties of the model and the measurements. Criteria for comparisons of simulated and measured data are derived to localize deficiencies in the model. For a better specification of these deficiencies simulated clouds are classified regarding their parametrization. With this classification the localized model deficiencies are allocated to a certain parametrization scheme. Applying this method to the regional model HRM the quality of forecasting cloud properties is estimated in detail. The overestimation of simulated clouds in low emissivity heights especially during the night is localized as model deficiency. This is caused by subscale cloudiness. As the simulation of subscale clouds in the regional model HRM is described by a relative humidity parametrization these deficiencies are connected with this parameterization.
NASA Astrophysics Data System (ADS)
Schulz, Hans Martin; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg
2016-03-01
The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.
Spectral cumulus parameterization based on cloud-resolving model
NASA Astrophysics Data System (ADS)
Baba, Yuya
2018-02-01
We have developed a spectral cumulus parameterization using a cloud-resolving model. This includes a new parameterization of the entrainment rate which was derived from analysis of the cloud properties obtained from the cloud-resolving model simulation and was valid for both shallow and deep convection. The new scheme was examined in a single-column model experiment and compared with the existing parameterization of Gregory (2001, Q J R Meteorol Soc 127:53-72) (GR scheme). The results showed that the GR scheme simulated more shallow and diluted convection than the new scheme. To further validate the physical performance of the parameterizations, Atmospheric Model Intercomparison Project (AMIP) experiments were performed, and the results were compared with reanalysis data. The new scheme performed better than the GR scheme in terms of mean state and variability of atmospheric circulation, i.e., the new scheme improved positive bias of precipitation in western Pacific region, and improved positive bias of outgoing shortwave radiation over the ocean. The new scheme also simulated better features of convectively coupled equatorial waves and Madden-Julian oscillation. These improvements were found to be derived from the modification of parameterization for the entrainment rate, i.e., the proposed parameterization suppressed excessive increase of entrainment, thus suppressing excessive increase of low-level clouds.
A cloud detection scheme for the Chinese Carbon Dioxide Observation Satellite (TANSAT)
NASA Astrophysics Data System (ADS)
Wang, Xi; Guo, Zheng; Huang, Yipeng; Fan, Hongjie; Li, Wanbiao
2017-01-01
Cloud detection is an essential preprocessing step for retrieving carbon dioxide from satellite observations of reflected sunlight. During the pre-launch study of the Chinese Carbon Dioxide Observation Satellite (TANSAT), a cloud-screening scheme was presented for the Cloud and Aerosol Polarization Imager (CAPI), which only performs measurements in five channels located in the visible to near-infrared regions of the spectrum. The scheme for CAPI, based on previous cloudscreening algorithms, defines a method to regroup individual threshold tests for each pixel in a scene according to the derived clear confidence level. This scheme is proven to be more effective for sensors with few channels. The work relies upon the radiance data from the Visible and Infrared Radiometer (VIRR) onboard the Chinese FengYun-3A Polar-orbiting Meteorological Satellite (FY-3A), which uses four wavebands similar to that of CAPI and can serve as a proxy for its measurements. The scheme has been applied to a number of the VIRR scenes over four target areas (desert, snow, ocean, forest) for all seasons. To assess the screening results, comparisons against the cloud-screening product from MODIS are made. The evaluation suggests that the proposed scheme inherits the advantages of schemes described in previous publications and shows improved cloud-screening results. A seasonal analysis reveals that this scheme provides better performance during warmer seasons, except for observations over oceans, where results are much better in colder seasons.
APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels
NASA Astrophysics Data System (ADS)
Klüser, L.; Killius, N.; Gesell, G.
2015-10-01
The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.
Determination of precipitation profiles from airborne passive microwave radiometric measurements
NASA Technical Reports Server (NTRS)
Kummerow, Christian; Hakkarinen, Ida M.; Pierce, Harold F.; Weinman, James A.
1991-01-01
This study presents the first quantitative retrievals of vertical profiles of precipitation derived from multispectral passive microwave radiometry. Measurements of microwave brightness temperature (Tb) obtained by a NASA high-altitude research aircraft are related to profiles of rainfall rate through a multichannel piecewise-linear statistical regression procedure. Statistics for Tb are obtained from a set of cloud radiative models representing a wide variety of convective, stratiform, and anvil structures. The retrieval scheme itself determines which cloud model best fits the observed meteorological conditions. Retrieved rainfall rate profiles are converted to equivalent radar reflectivity for comparison with observed reflectivities from a ground-based research radar. Results for two case studies, a stratiform rain situation and an intense convective thunderstorm, show that the radiometrically derived profiles capture the major features of the observed vertical structure of hydrometer density.
NASA Astrophysics Data System (ADS)
He, Y.; Dickinson, R.
2005-12-01
The seasonal variation of marine stratus and stratocumulus (MSC) plays a significant role in ocean- atmosphere-land interaction during the seasonal transition of basic climate in the Eastern Pacific. A key factor in parameterization of MSC cloud cover is atmospheric stability. In this study, we examine the importance of lower troposphere stability for Marine Stratus and Stratocumulus (MSC) cloud cover variations over subtropical oceans on monthly and seasonal timescales. Our approach is to consider a two-layer conceptual model with moist denser boundary layer air topped by dry lighter free air beneath a trade wind inversion at around 700 mb.The vertical integrated dry static energy is of central importance in the lower troposphere. The variation of dry static energy transport and latent heat release leads to the variation of cloud top radiative forcing, which is a function of low cloud cover. A diagnostic cloud cover scheme derived from the model is a nonlinear function of lower troposphere stability and large-scale subsidence. Use ERA-40 and ISCCP-FD data as input, the scheme reproduces well the seasonal variation of low cloud cover in four MSC regions near the western coast of continents. NCAR CAM linear empirical cloud cover scheme could explain 16% of the observed ISCCP monthly covariance in the southeast subtropical Pacific during 1990 to 2000 period; while the new cloud cover scheme could explain 50% of the total covariance. When implementing new scheme into NCAR CAM3.1, it is found that the seasonal phase of MSC is better simulated near the Peruvian region, but the seasonal amplitudes of MSC cloud cover in four MSC regions using both schemes have systematic problems. Possible causes for model cloud biases are investigated through numerical experiments. The importance of MSC cloud cover in the eastern Pacific on local mean climate is also discussed.
Incorporation of a Cumulus Fraction Scheme in the GRAPES_Meso and Evaluation of Its Performance
NASA Astrophysics Data System (ADS)
Zheng, X.
2016-12-01
Accurate simulation of cloud cover fraction is a key and difficult issue in numerical modeling studies. Preliminary evaluations have indicated that cloud fraction is generally underestimated in GRAPES_Meso simulations, while the cloud fraction scheme (CFS) of ECMWF can provide more realistic results. Therefore, the ECMWF cumulus fraction scheme is introduced into GRAPES_Meso to replace the original CFS, and the model performance with the new CFS is evaluated based on simulated three-dimensional cloud fractions and surface temperature. Results indicate that the simulated cloud fractions increase and become more accurate with the new CFS; the simulation for vertical cloud structure has improved too; errors in surface temperature simulation have decreased. The above analysis and results suggest that the new CFS has a positive impact on cloud fraction and surface temperature simulation.
NASA Astrophysics Data System (ADS)
Zhang, Lei; Dong, Xiquan; Kennedy, Aaron; Xi, Baike; Li, Zhanqing
2017-03-01
The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies (GISS) Model E2 atmospheric general circulation model (GCM; post-CMIP5, hereafter P5). In this study, single column model (SCM P5) simulated cloud fractions (CFs), cloud liquid water paths (LWPs) and precipitation were compared with Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) groundbased observations made during the period 2002-08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase (10%-20%) but precipitation increased significantly (56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.
Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission
NASA Technical Reports Server (NTRS)
Wilson, Michael J.; Oreopoulos, Lazarous
2011-01-01
The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.
Towards a true aerosol-and-cloud retrieval scheme
NASA Astrophysics Data System (ADS)
Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don
2014-05-01
The Optimal Retrieval of Aerosol and Cloud (ORAC) - formally the Oxford-RAL Aerosol and Cloud retrieval - offers a framework that can provide consistent and well characterised properties of both aerosols and clouds from a range of imaging satellite instruments. Several practical issues stand in the way of achieving the potential of this combined scheme however; in particular the sometimes conflicting priorities and requirements of aerosol and cloud retrieval problems, and the question of the unambiguous identification of aerosol and cloud pixels. This presentation will present recent developments made to the ORAC scheme for both aerosol and cloud, and detail how these are being integrated into a single retrieval framework. The implementation of a probabilistic method for pixel identification will also be presented, for both cloud detection and aerosol/cloud type selection. The method is based on Bayesian methods applied the optimal estimation retrieval output of ORAC and is particularly aimed at providing additional information in the so-called "twilight zone", where pixels can't be unambiguously identified as either aerosol or cloud and traditional cloud or aerosol products do not provide results.
Predictive Control of Networked Multiagent Systems via Cloud Computing.
Liu, Guo-Ping
2017-01-18
This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.
Eulerian and Lagrangian approaches to multidimensional condensation and collection
NASA Astrophysics Data System (ADS)
Li, Xiang-Yu; Brandenburg, A.; Haugen, N. E. L.; Svensson, G.
2017-06-01
Turbulence is argued to play a crucial role in cloud droplet growth. The combined problem of turbulence and cloud droplet growth is numerically challenging. Here an Eulerian scheme based on the Smoluchowski equation is compared with two Lagrangian superparticle (or superdroplet) schemes in the presence of condensation and collection. The growth processes are studied either separately or in combination using either two-dimensional turbulence, a steady flow or just gravitational acceleration without gas flow. Good agreement between the different schemes for the time evolution of the size spectra is observed in the presence of gravity or turbulence. The Lagrangian superparticle schemes are found to be superior over the Eulerian one in terms of computational performance. However, it is shown that the use of interpolation schemes such as the cloud-in-cell algorithm is detrimental in connection with superparticle or superdroplet approaches. Furthermore, the use of symmetric over asymmetric collection schemes is shown to reduce the amount of scatter in the results. For the Eulerian scheme, gravitational collection is rather sensitive to the mass bin resolution, but not so in the case with turbulence.
Sensitivity of CAM5-simulated Arctic clouds and radiation to ice nucleation parameterization
Xie, Shaocheng; Liu, Xiaohong; Zhao, Chuanfeng; ...
2013-08-06
Sensitivity of Arctic clouds and radiation in the Community Atmospheric Model, version 5, to the ice nucleation process is examined by testing a new physically based ice nucleation scheme that links the variation of ice nuclei (IN) number concentration to aerosol properties. The default scheme parameterizes the IN concentration simply as a function of ice supersaturation. The new scheme leads to a significant reduction in simulated IN concentration at all latitudes while changes in cloud amounts and properties are mainly seen at high- and midlatitude storm tracks. In the Arctic, there is a considerable increase in midlevel clouds and amore » decrease in low-level clouds, which result from the complex interaction among the cloud macrophysics, microphysics, and large-scale environment. The smaller IN concentrations result in an increase in liquid water path and a decrease in ice water path caused by the slowdown of the Bergeron–Findeisen process in mixed-phase clouds. Overall, there is an increase in the optical depth of Arctic clouds, which leads to a stronger cloud radiative forcing (net cooling) at the top of the atmosphere. The comparison with satellite data shows that the new scheme slightly improves low-level cloud simulations over most of the Arctic but produces too many midlevel clouds. Considerable improvements are seen in the simulated low-level clouds and their properties when compared with Arctic ground-based measurements. As a result, issues with the observations and the model–observation comparison in the Arctic region are discussed.« less
Winter QPF Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations
NASA Technical Reports Server (NTRS)
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 characteristics. Each system provides a unique perspective. The WSR-88D operates in a surveillance mode, sampling cloud volumes of Rayleigh scatterers where reflectivity is proportional to the sixth moment of the size distribution of equivalent spheres. The CloudSat radar provides enhanced sensitivity to smaller cloud ice crystals aloft, as well as consistent vertical profiles along each orbit. However, CloudSat reflectivity signatures are complicated somewhat by resonant Mie scattering effects and significant attenuation in the presence of cloud or rain water. Here, both radar systems are applied to a case of light to moderate snowfall within the warm frontal zone of a cold season, synoptic scale storm. Radars allow for an evaluation of the accuracy of a single-moment scheme in replicating precipitation structures, based on the bulk statistical properties of precipitation as suggested by reflectivity signatures.
Modeling the Influences of Aerosols on Pre-Monsoon Circulation and Rainfall over Southeast Asia
NASA Technical Reports Server (NTRS)
Lee, D.; Sud, Y. C.; Oreopoulos, L.; Kim, K.-M.; Lau, W. K.; Kang, I.-S.
2014-01-01
We conduct several sets of simulations with a version of NASA's Goddard Earth Observing System, version 5, (GEOS-5) Atmospheric Global Climate Model (AGCM) equipped with a two-moment cloud microphysical scheme to understand the role of biomass burning aerosol (BBA) emissions in Southeast Asia (SEA) in the pre-monsoon period of February-May. Our experiments are designed so that both direct and indirect aerosol effects can be evaluated. For climatologically prescribed monthly sea surface temperatures, we conduct sets of model integrations with and without biomass burning emissions in the area of peak burning activity, and with direct aerosol radiative effects either active or inactive. Taking appropriate differences between AGCM experiment sets, we find that BBA affects liquid clouds in statistically significantly ways, increasing cloud droplet number concentrations, decreasing droplet effective radii (i.e., a classic aerosol indirect effect), and locally suppressing precipitation due to a deceleration of the autoconversion process, with the latter effect apparently also leading to cloud condensate increases. Geographical re-arrangements of precipitation patterns, with precipitation increases downwind of aerosol sources are also seen, most likely because of advection of weakly precipitating cloud fields. Somewhat unexpectedly, the change in cloud radiative effect (cloud forcing) at surface is in the direction of lesser cooling because of decreases in cloud fraction. Overall, however, because of direct radiative effect contributions, aerosols exert a net negative forcing at both the top of the atmosphere and, perhaps most importantly, the surface, where decreased evaporation triggers feedbacks that further reduce precipitation. Invoking the approximation that direct and indirect aerosol effects are additive, we estimate that the overall precipitation reduction is about 40% due to the direct effects of absorbing aerosols, which stabilize the atmosphere and reduce surface latent heat fluxes via cooler land surface temperatures. Further refinements of our two-moment cloud microphysics scheme are needed for a more complete examination of the role of aerosol-convection interactions in the seasonal development of the SEA monsoon.
NASA Technical Reports Server (NTRS)
Wang, Shuguang; Sobel, Adam H.; Fridlind, Ann; Feng, Zhe; Comstock, Jennifer M.; Minnis, Patrick; Nordeen, Michele L.
2015-01-01
The recently completed CINDY/DYNAMO field campaign observed two Madden-Julian oscillation (MJO) events in the equatorial Indian Ocean from October to December 2011. Prior work has indicated that the moist static energy anomalies in these events grew and were sustained to a significant extent by radiative feedbacks. We present here a study of radiative fluxes and clouds in a set of cloud-resolving simulations of these MJO events. The simulations are driven by the large-scale forcing data set derived from the DYNAMO northern sounding array observations, and carried out in a doubly periodic domain using the Weather Research and Forecasting (WRF) model. Simulated cloud properties and radiative fluxes are compared to those derived from the S-PolKa radar and satellite observations. To accommodate the uncertainty in simulated cloud microphysics, a number of single-moment (1M) and double-moment (2M) microphysical schemes in the WRF model are tested. The 1M schemes tend to underestimate radiative flux anomalies in the active phases of the MJO events, while the 2M schemes perform better, but can overestimate radiative flux anomalies. All the tested microphysics schemes exhibit biases in the shapes of the histograms of radiative fluxes and radar reflectivity. Histograms of radiative fluxes and brightness temperature indicate that radiative biases are not evenly distributed; the most significant bias occurs in rainy areas with OLR less than 150 W/ cu sq in the 2M schemes. Analysis of simulated radar reflectivities indicates that this radiative flux uncertainty is closely related to the simulated stratiform cloud coverage. Single-moment schemes underestimate stratiform cloudiness by a factor of 2, whereas 2M schemes simulate much more stratiform cloud.
A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models
NASA Astrophysics Data System (ADS)
Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.
2016-12-01
Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.
Re-formulation and Validation of Cloud Microphysics Schemes
NASA Astrophysics Data System (ADS)
Wang, J.; Georgakakos, K. P.
2007-12-01
The research focuses on improving quantitative precipitation forecasts by removing significant uncertainties in current cloud microphysics schemes embedded in models such as WRF and MM5 and cloud-resolving models such as GCE. Reformulation of several production terms in these microphysics schemes was found necessary. When estimating four graupel production terms involved in the accretion between rain, snow and graupel, current microphysics schemes assumes that all raindrops and snow particles are falling at their appropriate mass-weighted mean terminal velocities and thus analytic solutions are able to be found for these production terms. Initial analysis and tests showed that these approximate analytic solutions give significant and systematic overestimates of these terms, and, thus, become one of major error sources of the graupel overproduction and associated extreme radar reflectivity in simulations. These results are corroborated by several reports. For example, the analytic solution overestimates the graupel production by collisions between raindrops and snow by up to 230%. The structure of "pure" snow (not rimed) and "pure graupel" (completely rimed) in current microphysics schemes excludes intermediate forms between "pure" snow and "pure" graupel and thus becomes a significant reason of graupel overproduction in hydrometeor simulations. In addition, the generation of the same density graupel by both the freezing of supercooled water and the riming of snow may cause underestimation of graupel production by freezing. A parameterization scheme of the riming degree of snow is proposed and then a dynamic fallspeed-diameter relationship and density- diameter relationship of rimed snow is assigned to graupel based on the diagnosed riming degree. To test if these new treatments can improve quantitative precipitation forecast, the Hurricane Katrina and a severe winter snowfall event in the Sierra Nevada Range are selected as case studies. A series of control simulation and sensitivity tests was conducted for these two cases. Two statistical methods are used to compare simulated radar reflectivity by the model with that detected by ground-based and airborne radar at different height levels. It was found that the changes made in current microphysical schemes improve QPF and microphysics simulation significantly.
ED(MF)n: Humidity-Convection Feedbacks in a Mass Flux Scheme Based on Resolved Size Densities
NASA Astrophysics Data System (ADS)
Neggers, R.
2014-12-01
Cumulus cloud populations remain at least partially unresolved in present-day numerical simulations of global weather and climate, and accordingly their impact on the larger-scale flow has to be represented through parameterization. Various methods have been developed over the years, ranging in complexity from the early bulk models relying on a single plume to more recent approaches that attempt to reconstruct the underlying probability density functions, such as statistical schemes and multiple plume approaches. Most of these "classic" methods capture key aspects of cumulus cloud populations, and have been successfully implemented in operational weather and climate models. However, the ever finer discretizations of operational circulation models, driven by advances in the computational efficiency of supercomputers, is creating new problems for existing sub-grid schemes. Ideally, a sub-grid scheme should automatically adapt its impact on the resolved scales to the dimension of the grid-box within which it is supposed to act. It can be argued that this is only possible when i) the scheme is aware of the range of scales of the processes it represents, and ii) it can distinguish between contributions as a function of size. How to conceptually represent this knowledge of scale in existing parameterization schemes remains an open question that is actively researched. This study considers a relatively new class of models for sub-grid transport in which ideas from the field of population dynamics are merged with the concept of multi plume modelling. More precisely, a multiple mass flux framework for moist convective transport is formulated in which the ensemble of plumes is created in "size-space". It is argued that thus resolving the underlying size-densities creates opportunities for introducing scale-awareness and scale-adaptivity in the scheme. The behavior of an implementation of this framework in the Eddy Diffusivity Mass Flux (EDMF) model, named ED(MF)n, is examined for a standard case of subtropical marine shallow cumulus. We ask if a system of multiple independently resolved plumes is able to automatically create the vertical profile of bulk (mass) flux at which the sub-grid scale transport balances the imposed larger-scale forcings in the cloud layer.
Cloud Statistics and Discrimination in the Polar Regions
NASA Astrophysics Data System (ADS)
Chan, M.; Comiso, J. C.
2012-12-01
Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.
Radiative Impacts of Cloud Heterogeneity and Overlap in an Atmospheric General Circulation Model
NASA Technical Reports Server (NTRS)
Oreopoulos, L.; Lee, D.; Sud, Y. C.; Suarez, M. J.
2012-01-01
The radiative impacts of introducing horizontal heterogeneity of layer cloud condensate, and vertical overlap of condensate and cloud fraction are examined with the aid of a new radiation package operating in the GEOS-5 Atmospheric General Circulation Model. The impacts are examined in terms of diagnostic top-of-the-atmosphere shortwave (SW) and longwave (LW) cloud radiative effect (CRE) calculations for a range of assumptions and parameter specifications about the overlap. The investigation is conducted for two distinct cloud schemes, the one that comes with the standard GEOS-5 distribution, and another which has been recently used experimentally for its enhanced GEOS-5 distribution, and another which has been recently used experimentally for its enhanced cloud microphysical capabilities; both are coupled to a cloud generator allowing arbitrary cloud overlap specification. We find that cloud overlap radiative impacts are significantly stronger for the operational cloud scheme for which a change of cloud fraction overlap from maximum-random to generalized results to global changes of SW and LW CRE of approximately 4 Watts per square meter, and zonal changes of up to approximately 10 Watts per square meter. This is because of fewer occurrences compared to the other scheme of large layer cloud fractions and of multi-layer situations with large numbers of atmospheric being simultaneously cloudy, conditions that make overlap details more important. The impact on CRE of the details of condensate distribution overlap is much weaker. Once generalized overlap is adopted, both cloud schemes are only modestly sensitive to the exact values of the overlap parameters. We also find that if one of the CRE components is overestimated and the other underestimated, both cannot be driven towards observed values by adjustments to cloud condensate heterogeneity and overlap alone.
NASA Astrophysics Data System (ADS)
Luo, S.
2016-12-01
Radiation field and cloud properties over the Southern Ocean area generated by the Australian Community Climate and Earth System Simulator (ACCESS) are evaluated using multiple-satellite products from the Fast Longwave And Shortwave radiative Fluxes (FLASHFlux) project and NASA/GEWEX surface radiation budget (SRB) data. The cloud properties are also evaluated using the observational simulator package COSP, a synthetic brightness temperature model (SBTM) and cloud liquid-water path data (UWisc) from the University of Wisconsin satellite retrievals. All of these evaluations are focused on the Southern Ocean area in an effort to understand the reasons behind the short-wave radiation biases at the surface. It is found that the model overestimates the high-level cloud fraction and frequency of occurrence of small ice-water content and underestimates the middle and low-level cloud fraction and water content. In order to improve the modelled radiation fields over the Southern Ocean area, two main modifications have been made to the physical schemes in the ACCESS model. Firstly the autoconversion rate at which the cloud water is converted into rain and the accretion rate in the warm rain scheme have been modified, which increases the cloud liquid-water content in warm cloud layers. Secondly, the scheme which determines the fraction of supercooled liquid water in mixed-phase clouds in the parametrization of cloud optical properties has been changed to use one derived from CALIPSO data which provides larger liquid cloud fractions and thus higher optical depths than the default scheme. Sensitivity tests of these two schemes in ACCESS climate runs have shown that applying either can lead to a reduction of the solar radiation reaching the surface and reduce the short-wave radiation biases.
The Arctic clouds from model simulations and long-term observations at Barrow, Alaska
NASA Astrophysics Data System (ADS)
Zhao, Ming
The Arctic is a region that is very sensitive to global climate change while also experiencing significant changes in its surface air temperature, sea-ice cover, atmospheric circulation, precipitation, snowfall, biogeochemical cycling, and land surface. Although previous studies have shown that the arctic clouds play an important role in the arctic climate changes, the arctic clouds are poorly understood and simulated in climate model due to limited observations. Furthermore, most of the studies were based on short-term experiments and typically only cover the warm seasons, which do not provide a full understanding of the seasonal cycle of arctic clouds. To address the above concerns and to improve our understanding of arctic clouds, six years of observational and retrieval data from 1999 to 2004 at the Atmospheric Radiation Management (ARM) Climate Research Facility (ACRF) North Slope of Alaska (NSA) Barrow site are used to understand the arctic clouds and related radiative processes. In particular, we focus on the liquid-ice mass partition in the mixed-phase cloud layer. Statistical results show that aerosol type and concentration are important factors that impact the mixed-phase stratus (MPS) cloud microphysical properties: liquid water path (LWP) and liquid water fraction (LWF) decrease with the increase of cloud condensation nuclei (CCN) number concentration; the high dust loading and dust occurrence in the spring are possible reasons for the much lower LWF than the other seasons. The importance of liquid-ice mass partition on surface radiation budgets was analyzed by comparing cloud longwave radiative forcings under the same LWP but different ice water path (IWP) ranges. Results show the ice phase enhance the surface cloud longwave (LW) forcing by 8˜9 W m-2 in the moderately thin MPS. This result provides an observational evidence on the aerosol glaciation effect in the moderately thin MPS, which is largely unknown so far. The above new insights are important to guide the model parameterizations of liquid-ice mass partition in arctic mixed-phase clouds, and are served as a test bed to cloud models and cloud microphysical schemes. The observational data between 1999 and 2007 are used to assess the performance of the European Center for Medium-Range Weather Forecasts (ECMWF) model in the Arctic region. The ECMWF model-simulated near-surface humidity had seasonal dependent biases as large as 20%, while also experiencing difficulty representing boundary layer (BL) temperature inversion height and strength during the transition seasons. Although the ECMWF model captured the seasonal variation of surface heat fluxes, it had sensible heat flux biases over 20 W m-2 in most of the cold months. Furthermore, even though the model captured the general seasonal variations of low-level cloud fraction (LCF) and LWP, it still overestimated the LCF by 20% or more and underestimated the LWP over 50% in the cold season. On average, the ECMWF model underestimated LWP by ˜30 g m-2 but more accurately predicted ice water path for BL clouds. For BL mixed-phase clouds, the model predicted water-ice mass partition was significantly lower than the observations, largely due to the temperature dependence of water-ice mass partition used in the model. The new cloud and BL schemes of the ECMWF model that were implemented after 2003 only resulted in minor improvements in BL cloud simulations in summer. These results indicate that significant improvements in cold season BL and mixed-phase cloud processes in the model are needed. In this study, single-layer MPS clouds were simulated by the Weather Research and Forecasting (WRF) model under different microphysical schemes and different ice nuclei (IN) number concentrations. Results show that by using proper IN concentration, the WRF model incorporated with Morrison microphysical scheme can reasonably capture the observed seasonal differences in temperature dependent liquid-ice mass partition. However, WRF simulations underestimate both LWP and IWP indicating its deficiency in capturing the radiative impacts of arctic MPS clouds.
NASA Astrophysics Data System (ADS)
Markowitz, Alex; Krumpe, Mirko; Nikutta, R.
2016-06-01
In two papers (Markowitz, Krumpe, & Nikutta 2014, and Nikutta et al., in prep.), we derive the first X-ray statistical constraints for clumpy-torus models in Seyfert AGN by quantifying multi-timescale variability in line of-sight X-ray absorbing gas as a function of optical classification.We systematically search for discrete absorption events in the vast archive of RXTE monitoring of 55 nearby type Is and Compton-thin type IIs. We are sensitive to discrete absorption events due to clouds of full-covering, neutral/mildly ionized gas transiting the line of sight. Our results apply to both dusty and non-dusty clumpy media, and probe model parameter space complementary to that for eclipses observed with XMM-Newton, Suzaku, and Chandra.We detect twelve eclipse events in eight Seyferts, roughly tripling the number previously published from this archive. Event durations span hours to years. Most of our detected clouds are Compton-thin, and most clouds' distances from the black hole are inferred to be commensurate with the outer portions of the BLR or the inner regions of infrared-emitting dusty tori.We present the density profiles of the highest-quality eclipse events; the column density profile for an eclipsing cloud in NGC 3783 is doubly spiked, possibly indicating a cloud that is being tidallysheared. We discuss implications for cloud distributions in the context of clumpy-torus models. We calculate eclipse probabilities for orientation-dependent Type I/II unification schemes.We present constraints on cloud sizes, stability, and radial distribution. We infer that clouds' small angular sizes as seen from the SMBH imply 107 clouds required across the BLR + torus. Cloud size is roughly proportional to distance from the black hole, hinting at the formation processes (e.g., disk fragmentation). All observed clouds are sub-critical with respect to tidal disruption; self-gravity alone cannot contain them. External forces, such as magnetic fields or ambient pressure, are needed to contain them; otherwise, clouds must be short-lived.
Three-moment representation of rain in a cloud microphysics model
NASA Astrophysics Data System (ADS)
Paukert, M.; Fan, J.; Rasch, P. J.; Morrison, H.; Milbrandt, J.; Khain, A.; Shpund, J.
2017-12-01
Two-moment microphysics schemes have been commonly used for cloud simulation in models across different scales - from large-eddy simulations to global climate models. These schemes have yielded valuable insights into cloud and precipitation processes, however the size distributions are limited to two degrees of freedom, and thus the shape parameter is typically fixed or diagnosed. We have developed a three-moment approach for the rain category in order to provide an additional degree of freedom to the size distribution and thereby improve the cloud microphysics representations for more accurate weather and climate simulations. The approach is applied to the Predicted Particle Properties (P3) scheme. In addition to the rain number and mass mixing ratios predicted in the two-moment P3, we now include prognostic equations for the sixth moment of the size distribution (radar reflectivity), thus allowing the shape parameter to evolve freely. We employ the spectral bin microphysics (SBM) model to formulate the three-moment process rates in P3 for drop collisions and breakup. We first test the three-moment scheme with a maritime stratocumulus case from the VOCALS field campaign, and compare the model results with respect to cloud and precipitation properties from the new P3 scheme, original two-moment P3 scheme, SBM, and in-situ aircraft measurements. The improved simulation results by the new P3 scheme will be discussed and physically explained.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gettelman, A.; Liu, Xiaohong; Ghan, Steven J.
2010-09-28
A process-based treatment of ice supersaturation and ice-nucleation is implemented in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model (CAM). The new scheme is designed to allow (1) supersaturation with respect to ice, (2) ice nucleation by aerosol particles and (3) ice cloud cover consistent with ice microphysics. The scheme is implemented with a 4-class 2 moment microphysics code and is used to evaluate ice cloud nucleation mechanisms and supersaturation in CAM. The new model is able to reproduce field observations of ice mass and mixed phase cloud occurrence better than previous versions of the model. Simulations indicatemore » heterogeneous freezing and contact nucleation on dust are both potentially important over remote areas of the Arctic. Cloud forcing and hence climate is sensitive to different formulations of the ice microphysics. Arctic radiative fluxes are sensitive to the parameterization of ice clouds. These results indicate that ice clouds are potentially an important part of understanding cloud forcing and potential cloud feedbacks, particularly in the Arctic.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liou, Kuo-Nan; Ou, S. C.; Gu, Y.
During the report period, we have made the following research accomplishments. First, we performed analysis for a number of MODIS scenes comprising of heavy dust events and ice clouds, covering regions of frequent dust outbreaks in East Asia, Middle East, and West Africa, as well as areas associated with long-range dust transports over the Equatorial Tropical Atlantic Ocean. These scenes contain both dust/aerosols and clouds. We collected suitable aerosol/ice-cloud data, correlated ice cloud and aerosol parameters by means of statistical analysis, and interpreted resulting correlation trends based on the physical principles governing cloud microphysics. Aerosol and cloud optical depths andmore » cloud effective particle size inferred from MODIS for selected domains were analyzed from which the parameters including dust aerosol number concentration, ice cloud water path, and ice particle number concentration were subsequently derived. We illustrated that the Twomey (solar albedo) effect can be statistically quantified based on the slope of best-fit straight lines in the correlation study. Analysis of aerosol and cloud retrieval products revealed that for all cases, the region with a larger dust aerosol optical depth is always characterized by a smaller cloud particle size, consistent with the Twomey hypothesis for aerosol-cloud interactions. Second, we developed mean correlation curves with uncertainties associated with small ice-crystal concentration observations for the mean effective ice crystal size (De) and ice water content (IWC) by dividing the atmosphere into three characteristic regions: Tropics cirrus, Midlatitude cirrus, including a temperature classification to improve correlation, and Arctic ice clouds. We illustrated that De has a high correlation with IWC based on theoretical consideration and analysis of thousands of observed ice crystal data obtained from a number of ARM-DOE field campaigns and other experiments. The correlation has the form: ln(De) = a + b ln(IWC) + c ((ln(IWC))2, where a, b, and c are fitting coefficients and are functions of three regions. We demonstrated that this correlation can be effectively incorporated in GCMs and climate models that predict IWC - a significant advance in ice microphysics parameterization for interactive cloud-radiation analysis and feedback. Substantial July mean differences are shown in the OLR (W/m2) and precipitation (mm/day) patterns between UCLA GCM simulations based on Des determined from the De-IWC correlations and the control run using a fixed ice crystal size. Third, in order to improve the computation of spectral radiative transfer processes in the WRF model, we developed a consistent and efficient radiation scheme that can better resolve the spectral bands, determine the cloud optical properties, and provide more reliable and accurate radiative heating fields. In the newly developed radiation module, we have implemented in WRF a modified and improved version referred to as the Fu-Liou-Gu scheme, which includes a combination of delta-four-stream and delta-two-stream approximations for solar and IR flux calculations, respectively. This combination has been proven to be computationally efficient and at the same time to produce a high degree of accuracy. The incorporation of nongray gaseous absorption in multiple scattering atmospheres was based on the correlated k-distribution method. The solar and IR spectra are divided into 6 and 12 bands, respectively, according to the location of absorption bands of H2O, CO2, O3, CH4, N2O, and CFCs. We further included absorption by the water vapor continuum and a number of minor absorbers in the solar spectrum leading to an additional absorption of solar flux in a clear atmosphere on the order of 1-3 W/m2. Additionally, we incorporated the ice microphysics parameterization that includes an interactive mean effective ice crystal size in association with radiation parameterizations. The Fu-Liou-Gu scheme is an ideal tool for the simulation of radiative transfer and ice microphysics within the domain of WRF. It is particularly useful for studying direct and indirect aerosol radiative effects associated with ice cloud formation. The newly implemented radiation module has been demonstrated to work well in WRF and can be effectively used for studies related to cirrus cloud formation and evolution as well as aerosol-cloud-radiation interactions. With the newly implemented radiation scheme, the simulations of cloud cover and ice water path have been improved for cirrus clouds, with a more consistent comparison with the corresponding MODIS observations, especially for optically thin cirrus with an improvement of about 20% in the simulated mean ice water path.« less
NASA Astrophysics Data System (ADS)
Ishida, H.; Ota, Y.; Sekiguchi, M.; Sato, Y.
2016-12-01
A three-dimensional (3D) radiative transfer calculation scheme is developed to estimate horizontal transport of radiation energy in a very high resolution (with the order of 10 m in spatial grid) simulation of cloud evolution, especially for horizontally inhomogeneous clouds such as shallow cumulus and stratocumulus. Horizontal radiative transfer due to inhomogeneous clouds seems to cause local heating/cooling in an atmosphere with a fine spatial scale. It is, however, usually difficult to estimate the 3D effects, because the 3D radiative transfer often needs a large resource for computation compared to a plane-parallel approximation. This study attempts to incorporate a solution scheme that explicitly solves the 3D radiative transfer equation into a numerical simulation, because this scheme has an advantage in calculation for a sequence of time evolution (i.e., the scene at a time is little different from that at the previous time step). This scheme is also appropriate to calculation of radiation with strong absorption, such as the infrared regions. For efficient computation, this scheme utilizes several techniques, e.g., the multigrid method for iteration solution, and a correlated-k distribution method refined for efficient approximation of the wavelength integration. For a case study, the scheme is applied to an infrared broadband radiation calculation in a broken cloud field generated with a large eddy simulation model. The horizontal transport of infrared radiation, which cannot be estimated by the plane-parallel approximation, and its variation in time can be retrieved. The calculation result elucidates that the horizontal divergences and convergences of infrared radiation flux are not negligible, especially at the boundaries of clouds and within optically thin clouds, and the radiative cooling at lateral boundaries of clouds may reduce infrared radiative heating in clouds. In a future work, the 3D effects on radiative heating/cooling will be able to be included into atmospheric numerical models.
NASA Astrophysics Data System (ADS)
Storelvmo, Trude; Sagoo, Navjit; Tan, Ivy
2016-04-01
Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has not focused on improving the ability of GCMs to accurately simulate phase partitioning in mixed-phase clouds. Getting the relative proportion of liquid droplets and ice crystals in clouds right in GCMs is critical for the representation of cloud radiative forcings and cloud-climate feedbacks. Here, we first present satellite observations of cloud phase obtained by NASA's CALIOP instrument, and report on robust statistical relationships between cloud phase and several aerosols species that have been demonstrated to act as ice nuclei (IN) in laboratory studies. We then report on results from model intercomparison projects that reveal that GCMs generally underestimate the amount of supercooled liquid in clouds. For a selected GCM (NCAR 's CAM5), we thereafter show that the underestimate can be attributed to two main factors: i) the presence of IN in the mixed-phase temperature range, and ii) the Wegener-Bergeron-Findeisen process, which converts liquid to ice once ice crystals have formed. Finally, we show that adjusting these two processes such that the GCM's cloud phase is in agreement with the observed has a substantial impact on the simulated radiative forcing due to IN perturbations, as well as on the cloud-climate feedbacks and ultimately climate sensitivity simulated by the GCM.
NASA Astrophysics Data System (ADS)
Havemann, S.; Aumann, H. H.; Desouza-Machado, S. G.
2017-12-01
The HT-FRTC uses principal components which cover the spectrum at a very high spectral resolution allowing very fast line-by-line-like, hyperspectral and broadband simulations for satellite-based, airborne and ground-based sensors. Using data from IASI and from the Airborne Research Interferometer Evaluation System (ARIES) on board the FAAM BAE 146 aircraft, variational retrievals in principal component space with HT-FRTC as forward model have demonstrated that valuable information on temperature and humidity profiles and on the cirrus cloud properties can be obtained simultaneously. The NASA/JPL/UMBC cloudy RTM inter-comparison project has been working on a global dataset consisting of 7377 AIRS spectra. Initial simulations with HT-FRTC for this dataset have been promising. A next step taken here is to investigate how sensitive the results are with respect to different assumptions in the cloud modelling. One aspect of this is to study how assumptions about the microphysical and related optical properties of liquid/ice clouds impact the statistics of the agreement between model and observations. The other aspect is about the cloud overlap scheme. Different schemes have been tested (maximum, random, maximum random). As the computational cost increases linearly with the number of cloud columns, it will be investigated if there is an optimal number of columns beyond which there is little additional benefit to be gained. During daytime the high wave number channels of AIRS are affected by solar radiation. With full scattering calculations using a monochromatic version of the Edwards-Slingo radiation code the HT-FRTC can model solar radiation reasonably well, but full scattering calculations are relatively expensive. Pure Chou scaling on the other hand can not properly describe scattering of solar radiation by clouds and requires additional refinements.
Proof of cipher text ownership based on convergence encryption
NASA Astrophysics Data System (ADS)
Zhong, Weiwei; Liu, Zhusong
2017-08-01
Cloud storage systems save disk space and bandwidth through deduplication technology, but with the use of this technology has been targeted security attacks: the attacker can get the original file just use hash value to deceive the server to obtain the file ownership. In order to solve the above security problems and the different security requirements of cloud storage system files, an efficient information theory security proof of ownership scheme is proposed. This scheme protects the data through the convergence encryption method, and uses the improved block-level proof of ownership scheme, and can carry out block-level client deduplication to achieve efficient and secure cloud storage deduplication scheme.
NASA Astrophysics Data System (ADS)
Cayula, Jean-François P.; May, Douglas A.; McKenzie, Bruce D.
2014-05-01
The Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask (VCM) Intermediate Product (IP) has been developed for use with Suomi National Polar-orbiting Partnership (NPP) VIIRS Environmental Data Record (EDR) products. In particular, the VIIRS Sea Surface Temperature (SST) EDR relies on VCM to identify cloud contaminated observations. Unfortunately, VCM does not appear to perform as well as cloud detection algorithms for SST. This may be due to similar but different goals of the two algorithms. VCM is concerned with detecting clouds while SST is interested in identifying clear observations. The result is that in undetermined cases VCM defaults to "clear," while the SST cloud detection defaults to "cloud." This problem is further compounded because classic SST cloud detection often flags as "cloud" all types of corrupted data, thus making a comparison with VCM difficult. The Naval Oceanographic Office (NAVOCEANO), which operationally produces a VIIRS SST product, relies on cloud detection from the NAVOCEANO Cloud Mask (NCM), adapted from cloud detection schemes designed for SST processing. To analyze VCM, the NAVOCEANO SST process was modified to attach the VCM flags to all SST retrievals. Global statistics are computed for both day and night data. The cases where NCM and/or VCM tag data as cloud-contaminated or clear can then be investigated. By analyzing the VCM individual test flags in conjunction with the status of NCM, areas where VCM can complement NCM are identified.
Wang, Shangping; Zhang, Xiaoxue; Zhang, Yaling
2016-01-01
Cipher-policy attribute-based encryption (CP-ABE) focus on the problem of access control, and keyword-based searchable encryption scheme focus on the problem of finding the files that the user interested in the cloud storage quickly. To design a searchable and attribute-based encryption scheme is a new challenge. In this paper, we propose an efficiently multi-user searchable attribute-based encryption scheme with attribute revocation and grant for cloud storage. In the new scheme the attribute revocation and grant processes of users are delegated to proxy server. Our scheme supports multi attribute are revoked and granted simultaneously. Moreover, the keyword searchable function is achieved in our proposed scheme. The security of our proposed scheme is reduced to the bilinear Diffie-Hellman (BDH) assumption. Furthermore, the scheme is proven to be secure under the security model of indistinguishability against selective ciphertext-policy and chosen plaintext attack (IND-sCP-CPA). And our scheme is also of semantic security under indistinguishability against chosen keyword attack (IND-CKA) in the random oracle model. PMID:27898703
Wang, Shangping; Zhang, Xiaoxue; Zhang, Yaling
2016-01-01
Cipher-policy attribute-based encryption (CP-ABE) focus on the problem of access control, and keyword-based searchable encryption scheme focus on the problem of finding the files that the user interested in the cloud storage quickly. To design a searchable and attribute-based encryption scheme is a new challenge. In this paper, we propose an efficiently multi-user searchable attribute-based encryption scheme with attribute revocation and grant for cloud storage. In the new scheme the attribute revocation and grant processes of users are delegated to proxy server. Our scheme supports multi attribute are revoked and granted simultaneously. Moreover, the keyword searchable function is achieved in our proposed scheme. The security of our proposed scheme is reduced to the bilinear Diffie-Hellman (BDH) assumption. Furthermore, the scheme is proven to be secure under the security model of indistinguishability against selective ciphertext-policy and chosen plaintext attack (IND-sCP-CPA). And our scheme is also of semantic security under indistinguishability against chosen keyword attack (IND-CKA) in the random oracle model.
76 FR 17158 - Assumption Buster Workshop: Distributed Data Schemes Provide Security
Federal Register 2010, 2011, 2012, 2013, 2014
2011-03-28
... Schemes Provide Security''. Distributed data architectures, such as cloud computing, offer very attractive... locating your data in the cloud, and by breaking it up and replicating different segments throughout the...
Parameterization of bulk condensation in numerical cloud models
NASA Technical Reports Server (NTRS)
Kogan, Yefim L.; Martin, William J.
1994-01-01
The accuracy of the moist saturation adjustment scheme has been evaluated using a three-dimensional explicit microphysical cloud model. It was found that the error in saturation adjustment depends strongly on the Cloud Condensation Nucleii (CCN) concentration in the ambient atmosphere. The scheme provides rather accurate results in the case where a sufficiently large number of CCN (on the order of several hundred per cubic centimeter) is available. However, under conditions typical of marine stratocumulus cloud layers with low CCN concentration, the error in the amounts of condensed water vapor and released latent heat may be as large as 40%-50%. A revision of the saturation adjustment scheme is devised that employs the CCN concentration, dynamical supersaturation, and cloud water content as additional variables in the calculation of the condensation rate. The revised condensation model reduced the error in maximum updraft and cloud water content in the climatically significant case of marine stratocumulus cloud layers by an order of magnitude.
APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels
NASA Astrophysics Data System (ADS)
Klüser, L.; Killius, N.; Gesell, G.
2015-04-01
The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.
Evaluation of Surface Flux Parameterizations with Long-Term ARM Observations
Liu, Gang; Liu, Yangang; Endo, Satoshi
2013-02-01
Surface momentum, sensible heat, and latent heat fluxes are critical for atmospheric processes such as clouds and precipitation, and are parameterized in a variety of models ranging from cloud-resolving models to large-scale weather and climate models. However, direct evaluation of the parameterization schemes for these surface fluxes is rare due to limited observations. This study takes advantage of the long-term observations of surface fluxes collected at the Southern Great Plains site by the Department of Energy Atmospheric Radiation Measurement program to evaluate the six surface flux parameterization schemes commonly used in the Weather Research and Forecasting (WRF) model and threemore » U.S. general circulation models (GCMs). The unprecedented 7-yr-long measurements by the eddy correlation (EC) and energy balance Bowen ratio (EBBR) methods permit statistical evaluation of all six parameterizations under a variety of stability conditions, diurnal cycles, and seasonal variations. The statistical analyses show that the momentum flux parameterization agrees best with the EC observations, followed by latent heat flux, sensible heat flux, and evaporation ratio/Bowen ratio. The overall performance of the parameterizations depends on atmospheric stability, being best under neutral stratification and deteriorating toward both more stable and more unstable conditions. Further diagnostic analysis reveals that in addition to the parameterization schemes themselves, the discrepancies between observed and parameterized sensible and latent heat fluxes may stem from inadequate use of input variables such as surface temperature, moisture availability, and roughness length. The results demonstrate the need for improving the land surface models and measurements of surface properties, which would permit the evaluation of full land surface models.« less
NASA Technical Reports Server (NTRS)
Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; Fridlind, Ann; Endo, Satoshi; Song, Hua; Feng, Sha; Toto, Tami; Li, Zhijin; Zhang, Minghua
2015-01-01
Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.
Lin, Wuyin; Liu, Yangang; Vogelmann, Andrew M.; ...
2015-06-19
Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) project has constructed case studies from the Atmospheric Radiation Measurement (ARM) Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only amore » relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.
Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculatedmore » from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.« less
Secure Dynamic access control scheme of PHR in cloud computing.
Chen, Tzer-Shyong; Liu, Chia-Hui; Chen, Tzer-Long; Chen, Chin-Sheng; Bau, Jian-Guo; Lin, Tzu-Ching
2012-12-01
With the development of information technology and medical technology, medical information has been developed from traditional paper records into electronic medical records, which have now been widely applied. The new-style medical information exchange system "personal health records (PHR)" is gradually developed. PHR is a kind of health records maintained and recorded by individuals. An ideal personal health record could integrate personal medical information from different sources and provide complete and correct personal health and medical summary through the Internet or portable media under the requirements of security and privacy. A lot of personal health records are being utilized. The patient-centered PHR information exchange system allows the public autonomously maintain and manage personal health records. Such management is convenient for storing, accessing, and sharing personal medical records. With the emergence of Cloud computing, PHR service has been transferred to storing data into Cloud servers that the resources could be flexibly utilized and the operation cost can be reduced. Nevertheless, patients would face privacy problem when storing PHR data into Cloud. Besides, it requires a secure protection scheme to encrypt the medical records of each patient for storing PHR into Cloud server. In the encryption process, it would be a challenge to achieve accurately accessing to medical records and corresponding to flexibility and efficiency. A new PHR access control scheme under Cloud computing environments is proposed in this study. With Lagrange interpolation polynomial to establish a secure and effective PHR information access scheme, it allows to accurately access to PHR with security and is suitable for enormous multi-users. Moreover, this scheme also dynamically supports multi-users in Cloud computing environments with personal privacy and offers legal authorities to access to PHR. From security and effectiveness analyses, the proposed PHR access scheme in Cloud computing environments is proven flexible and secure and could effectively correspond to real-time appending and deleting user access authorization and appending and revising PHR records.
NASA Astrophysics Data System (ADS)
Dietlicher, Remo; Neubauer, David; Lohmann, Ulrike
2018-04-01
A new scheme for stratiform cloud microphysics has been implemented in the ECHAM6-HAM2 general circulation model. It features a widely used description of cloud water with two categories for cloud droplets and raindrops. The unique aspect of the new scheme is the break with the traditional approach to describe cloud ice analogously. Here we parameterize cloud ice by a single category that predicts bulk particle properties (P3). This method has already been applied in a regional model and most recently also in the Community Atmosphere Model 5 (CAM5). A single cloud ice category does not rely on heuristic conversion rates from one category to another. Therefore, it is conceptually easier and closer to first principles. This work shows that a single category is a viable approach to describe cloud ice in climate models. Prognostic representation of sedimentation is achieved by a nested approach for sub-stepping the cloud microphysics scheme. This yields good results in terms of accuracy and performance as compared to simulations with high temporal resolution. Furthermore, the new scheme allows for a competition between various cloud processes and is thus able to unbiasedly represent the ice formation pathway from nucleation to growth by vapor deposition and collisions to sedimentation. Specific aspects of the P3 method are evaluated. We could not produce a purely stratiform cloud where rime growth dominates growth by vapor deposition and conclude that the lack of appropriate conditions renders the prognostic parameters associated with the rime properties unnecessary. Limitations inherent in a single category are examined.
NASA Astrophysics Data System (ADS)
Wang, Kai; Zhang, Yang; Zhang, Xin; Fan, Jiwen; Leung, L. Ruby; Zheng, Bo; Zhang, Qiang; He, Kebin
2018-03-01
An advanced online-coupled meteorology and chemistry model WRF-CAM5 has been applied to East Asia using triple-nested domains at different grid resolutions (i.e., 36-, 12-, and 4-km) to simulate a severe dust storm period in spring 2010. Analyses are performed to evaluate the model performance and investigate model sensitivity to different horizontal grid sizes and aerosol activation parameterizations and to examine aerosol-cloud interactions and their impacts on the air quality. A comprehensive model evaluation of the baseline simulations using the default Abdul-Razzak and Ghan (AG) aerosol activation scheme shows that the model can well predict major meteorological variables such as 2-m temperature (T2), water vapor mixing ratio (Q2), 10-m wind speed (WS10) and wind direction (WD10), and shortwave and longwave radiation across different resolutions with domain-average normalized mean biases typically within ±15%. The baseline simulations also show moderate biases for precipitation and moderate-to-large underpredictions for other major variables associated with aerosol-cloud interactions such as cloud droplet number concentration (CDNC), cloud optical thickness (COT), and cloud liquid water path (LWP) due to uncertainties or limitations in the aerosol-cloud treatments. The model performance is sensitive to grid resolutions, especially for surface meteorological variables such as T2, Q2, WS10, and WD10, with the performance generally improving at finer grid resolutions for those variables. Comparison of the sensitivity simulations with an alternative (i.e., the Fountoukis and Nenes (FN) series scheme) and the default (i.e., AG scheme) aerosol activation scheme shows that the former predicts larger values for cloud variables such as CDNC and COT across all grid resolutions and improves the overall domain-average model performance for many cloud/radiation variables and precipitation. Sensitivity simulations using the FN series scheme also have large impacts on radiations, T2, precipitation, and air quality (e.g., decreasing O3) through complex aerosol-radiation-cloud-chemistry feedbacks. The inclusion of adsorptive activation of dust particles in the FN series scheme has similar impacts on the meteorology and air quality but to lesser extent as compared to differences between the FN series and AG schemes. Compared to the overall differences between the FN series and AG schemes, impacts of adsorptive activation of dust particles can contribute significantly to the increase of total CDNC (∼45%) during dust storm events and indicate their importance in modulating regional climate over East Asia.
Bayesian cloud detection for MERIS, AATSR, and their combination
NASA Astrophysics Data System (ADS)
Hollstein, A.; Fischer, J.; Carbajal Henken, C.; Preusker, R.
2015-04-01
A broad range of different of Bayesian cloud detection schemes is applied to measurements from the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The cloud detection schemes were designed to be numerically efficient and suited for the processing of large numbers of data. Results from the classical and naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as well as for their combination. A sensitivity study on the resolution of multidimensional histograms, which were post-processed by Gaussian smoothing, shows how theoretically insufficient numbers of truth data can be used to set up accurate classical Bayesian cloud masks. Sets of exploited features from single and derived channels are numerically optimized and results for naive and classical Bayesian cloud masks are presented. The application of the Bayesian approach is discussed in terms of reproducing existing algorithms, enhancing existing algorithms, increasing the robustness of existing algorithms, and on setting up new classification schemes based on manually classified scenes.
A privacy authentication scheme based on cloud for medical environment.
Chen, Chin-Ling; Yang, Tsai-Tung; Chiang, Mao-Lun; Shih, Tzay-Farn
2014-11-01
With the rapid development of the information technology, the health care technologies already became matured. Such as electronic medical records that can be easily stored. However, how to get medical resources more convenient is currently concerning issue. In spite of many literatures discussed about medical systems, these literatures should face many security challenges. The most important issue is patients' privacy. Therefore, we propose a privacy authentication scheme based on cloud environment. In our scheme, we use mobile device's characteristics, allowing peoples to use medical resources on the cloud environment to find medical advice conveniently. The digital signature is used to ensure the security of the medical information that is certified by the medical department in our proposed scheme.
NASA Technical Reports Server (NTRS)
Molthan, A. L.; Haynes, J. A.; Jedlovec, G. L.; Lapenta, W. M.
2009-01-01
As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.
NASA Astrophysics Data System (ADS)
Zhou, C.; Zhang, X.; Gong, S.; Wang, Y.; Xue, M.
2016-01-01
A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under a China Meteorological Administration (CMA) chemical weather modeling system, GRAPES/CUACE (Global/Regional Assimilation and PrEdiction System, CMA Unified Atmospheric Chemistry Environment). Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) are interactively fed online into a two-moment cloud scheme (WRF Double-Moment 6-class scheme - WDM6) and a convective parameterization to drive cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred.
The results show that aerosols that interact with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content, and cloud droplet number concentrations, while decreasing the mean diameters of cloud droplets with varying magnitudes of the changes in each case and region. These interactive microphysical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24 to 48 % enhancements of threat score for 6 h precipitation in almost all regions. The aerosols that interact with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3 °C.
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man; Luo, Yali; Morrison, Hugh; Mcfarquhar, G.M.
2008-01-01
Single-layer mixed-phase stratiform (MPS) Arctic clouds, which formed under conditions of large surface heat flux combined with general subsidence during a subperiod of the Atmospheric Radiation Measurement (ARM) Program Mixed-Phase Arctic Cloud Experiment (M-PACE), are simulated with a cloud resolving model (CRM). The CRM is implemented with either an advanced two-moment (M05) or a commonly used one-moment (L83) bulk microphysics scheme and a state-of-the-art radiative transfer scheme. The CONTROL simulation, that uses the M05 scheme and observed aerosol size distribution and ice nulei (IN) number concentration, reproduces the magnitudes and vertical structures of cloud liquid water content (LWC), total ice water content (IWC), number concentration and effective radius of cloud droplets as suggested by the M-PACE observations. It underestimates ice crystal number concentrations by an order of magnitude and overestimates effective radius of ice crystals by a factor of 2-3. The OneM experiment, that uses the L83 scheme, produces values of liquid water path (LWP) and ice plus snow water path (ISWP) that were about 30% and 4 times, respectively, of those produced by the CONTROL. Its vertical profile of IWC exhibits a bimodal distribution in contrast to the constant distribution of IWC produced in the CONTROL and observations.
Roesler, Erika L.; Posselt, Derek J.; Rood, Richard B.
2017-04-06
Three-dimensional large eddy simulations (LES) are used to analyze a springtime Arctic mixed-phase stratocumulus observed on 26 April 2008 during the Indirect and Semi-Direct Aerosol Campaign. Two subgrid-scale turbulence parameterizations are compared. The first scheme is a 1.5-order turbulent kinetic energy (1.5-TKE) parameterization that has been previously applied to boundary layer cloud simulations. The second scheme, Cloud Layers Unified By Binormals (CLUBB), provides higher-order turbulent closure with scale awareness. The simulations, in comparisons with observations, show that both schemes produce the liquid profiles within measurement variability but underpredict ice water mass and overpredict ice number concentration. The simulation using CLUBBmore » underpredicted liquid water path more than the simulation using the 1.5-TKE scheme, so the turbulent length scale and horizontal grid box size were increased to increase liquid water path and reduce dissipative energy. The LES simulations show this stratocumulus cloud to maintain a closed cellular structure, similar to observations. The updraft and downdraft cores self-organize into a larger meso-γ-scale convective pattern with the 1.5-TKE scheme, but the cores remain more isotropic with the CLUBB scheme. Additionally, the cores are often composed of liquid and ice instead of exclusively containing one or the other. Furthermore, these results provide insight into traditionally unresolved and unmeasurable aspects of an Arctic mixed-phase cloud. From analysis, this cloud's updraft and downdraft cores appear smaller than other closed-cell stratocumulus such as midlatitude stratocumulus and Arctic autumnal mixed-phase stratocumulus due to the weaker downdrafts and lower precipitation rates.« less
Simulations of arctic mixed-phase clouds in forecasts with CAM3 and AM2 for M-PACE
Xie, Shaocheng; Boyle, James; Klein, Stephen A.; ...
2008-02-27
[1] Simulations of mixed-phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed-phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of themore » boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener-Bergeron-Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. Furthermore, this paper shows that the Wegener-Bergeron-Findeisen process is important for these models to correctly simulate the observed features of mixed-phase clouds.« less
Simulations of Arctic mixed-phase clouds in forecasts with CAM3 and AM2 for M-PACE
NASA Astrophysics Data System (ADS)
Xie, Shaocheng; Boyle, James; Klein, Stephen A.; Liu, Xiaohong; Ghan, Steven
2008-02-01
Simulations of mixed-phase clouds in forecasts with the NCAR Atmosphere Model version 3 (CAM3) and the GFDL Atmospheric Model version 2 (AM2) for the Mixed-Phase Arctic Cloud Experiment (M-PACE) are performed using analysis data from numerical weather prediction centers. CAM3 significantly underestimates the observed boundary layer mixed-phase cloud fraction and cannot realistically simulate the variations of liquid water fraction with temperature and cloud height due to its oversimplified cloud microphysical scheme. In contrast, AM2 reasonably reproduces the observed boundary layer cloud fraction while its clouds contain much less cloud condensate than CAM3 and the observations. The simulation of the boundary layer mixed-phase clouds and their microphysical properties is considerably improved in CAM3 when a new physically based cloud microphysical scheme is used (CAM3LIU). The new scheme also leads to an improved simulation of the surface and top of the atmosphere longwave radiative fluxes. Sensitivity tests show that these results are not sensitive to the analysis data used for model initialization. Increasing model horizontal resolution helps capture the subgrid-scale features in Arctic frontal clouds but does not help improve the simulation of the single-layer boundary layer clouds. AM2 simulated cloud fraction and LWP are sensitive to the change in cloud ice number concentrations used in the Wegener-Bergeron-Findeisen process while CAM3LIU only shows moderate sensitivity in its cloud fields to this change. This paper shows that the Wegener-Bergeron-Findeisen process is important for these models to correctly simulate the observed features of mixed-phase clouds.
Gridding Cloud and Irradiance to Quantify Variability at the ARM Southern Great Plains Site
NASA Astrophysics Data System (ADS)
Riihimaki, L.; Long, C. N.; Gaustad, K.
2017-12-01
Ground-based radiometers provide the most accurate measurements of surface irradiance. However, geometry differences between surface point measurements and large area climate model grid boxes or satellite-based footprints can cause systematic differences in surface irradiance comparisons. In this work, irradiance measurements from a network of ground stations around Kansas and Oklahoma at the US Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains facility are examined. Upwelling and downwelling broadband shortwave and longwave radiometer measurements are available at each site as well as surface meteorological measurements. In addition to the measured irradiances, clear sky irradiance and cloud fraction estimates are analyzed using well established methods based on empirical fits to measured clear sky irradiances. Measurements are interpolated onto a 0.25 degree latitude and longitude grid using a Gaussian weight scheme in order to provide a more accurate statistical comparison between ground measurements and a larger area such as that used in climate models, plane parallel radiative transfer calculations, and other statistical and climatological research. Validation of the gridded product will be shown, as well as analysis that quantifies the impact of site location, cloud type, and other factors on the resulting surface irradiance estimates. The results of this work are being incorporated into the Surface Cloud Grid operational data product produced by ARM, and will be made publicly available for use by others.
a Global Registration Algorithm of the Single-Closed Ring Multi-Stations Point Cloud
NASA Astrophysics Data System (ADS)
Yang, R.; Pan, L.; Xiang, Z.; Zeng, H.
2018-04-01
Aimed at the global registration problem of the single-closed ring multi-stations point cloud, a formula in order to calculate the error of rotation matrix was constructed according to the definition of error. The global registration algorithm of multi-station point cloud was derived to minimize the error of rotation matrix. And fast-computing formulas of transformation matrix with whose implementation steps and simulation experiment scheme was given. Compared three different processing schemes of multi-station point cloud, the experimental results showed that the effectiveness of the new global registration method was verified, and it could effectively complete the global registration of point cloud.
SSeCloud: Using secret sharing scheme to secure keys
NASA Astrophysics Data System (ADS)
Hu, Liang; Huang, Yang; Yang, Disheng; Zhang, Yuzhen; Liu, Hengchang
2017-08-01
With the use of cloud storage services, one of the concerns is how to protect sensitive data securely and privately. While users enjoy the convenience of data storage provided by semi-trusted cloud storage providers, they are confronted with all kinds of risks at the same time. In this paper, we present SSeCloud, a secure cloud storage system that improves security and usability by applying secret sharing scheme to secure keys. The system encrypts uploading files on the client side and splits encrypted keys into three shares. Each of them is respectively stored by users, cloud storage providers and the alternative third trusted party. Any two of the parties can reconstruct keys. Evaluation results of prototype system show that SSeCloud provides high security without too much performance penalty.
An Efficient Quantum Somewhat Homomorphic Symmetric Searchable Encryption
NASA Astrophysics Data System (ADS)
Sun, Xiaoqiang; Wang, Ting; Sun, Zhiwei; Wang, Ping; Yu, Jianping; Xie, Weixin
2017-04-01
In 2009, Gentry first introduced an ideal lattices fully homomorphic encryption (FHE) scheme. Later, based on the approximate greatest common divisor problem, learning with errors problem or learning with errors over rings problem, FHE has developed rapidly, along with the low efficiency and computational security. Combined with quantum mechanics, Liang proposed a symmetric quantum somewhat homomorphic encryption (QSHE) scheme based on quantum one-time pad, which is unconditional security. And it was converted to a quantum fully homomorphic encryption scheme, whose evaluation algorithm is based on the secret key. Compared with Liang's QSHE scheme, we propose a more efficient QSHE scheme for classical input states with perfect security, which is used to encrypt the classical message, and the secret key is not required in the evaluation algorithm. Furthermore, an efficient symmetric searchable encryption (SSE) scheme is constructed based on our QSHE scheme. SSE is important in the cloud storage, which allows users to offload search queries to the untrusted cloud. Then the cloud is responsible for returning encrypted files that match search queries (also encrypted), which protects users' privacy.
Addressing Common Cloud-Radiation Errors from 4-hour to 4-week Model Prediction
NASA Astrophysics Data System (ADS)
Benjamin, S.; Sun, S.; Grell, G. A.; Green, B.; Olson, J.; Kenyon, J.; James, E.; Smirnova, T. G.; Brown, J. M.
2017-12-01
Cloud-radiation representation in models for subgrid-scale clouds is a known gap from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours. NOAA/ESRL has been applying common physical parameterizations for scale-aware deep/shallow convection and boundary-layer mixing over this wide range of time and spatial scales, with some progress to be reported in this presentation. The Grell-Freitas scheme (2014, Atmos. Chem. Phys.) and MYNN boundary-layer EDMF scheme (Olson / Benjamin et al. 2016 Mon. Wea. Rev.) have been applied and tested extensively for the NOAA hourly updated 3-km High-Resolution Rapid Refresh (HRRR) and 13-km Rapid Refresh (RAP) model/assimilation systems over the United States and North America, with targeting toward improvement to boundary-layer evolution and cloud-radiation representation in all seasons. This representation is critical for both warm-season severe convective storm forecasting and for winter-storm prediction of snow and mixed precipitation. At the same time the Grell-Freitas scheme has been applied also as an option for subseasonal forecasting toward improved US week 3-4 prediction with the FIM-HYCOM coupled model (Green et al 2017, MWR). Cloud/radiation evaluation using CERES satellite-based estimates have been applied to both 12-h RAP (13km) and also during Weeks 1-4 from 32-day FIM-HYCOM (60km) forecasts. Initial results reveal that improved cloud representation is needed for both resolutions and now is guiding further refinement for cloud representation including with the Grell-Freitas scheme and with the updated MYNN-EDMF scheme (both now also in global testing as well as with the 3km HRRR and 13km RAP models).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heiblum, Reuven H.; Altaratz, Orit; Koren, Ilan
2016-06-07
In Part I of this work a 3D cloud tracking algorithm and phase-space of center of gravity altitude versus cloud liquid water mass (CvM space) were introduced and described in detail. We showed how new physical insight can be gained by following cloud trajectories in the CvM space. Here, this approach is used to investigate aerosol effects on cloud fields of warm cumuli. We show a clear effect of the aerosol loading on the shape and size of CvM clusters. We also find fundamental differences in the CvM space between simulations using bin versus bulk microphysical schemes, with the binmore » scheme precipitation expressing much higher sensitivity to changes in aerosol concentrations. Using the bin microphysical scheme, we find that the increase in cloud center of gravity altitude with increase in aerosol concentrations occurs for a wide range of cloud sizes. This is attributed to reduced sedimentation, increased buoyancy and vertical velocities, and increased environmental instability, all of which are tightly coupled to inhibition of precipitation processes and subsequent feedbacks of clouds on their environment. Many of the physical processes shown here are consistent with processes typically associated with cloud invigoration.« less
Implementation of a gust front head collapse scheme in the WRF numerical model
NASA Astrophysics Data System (ADS)
Lompar, Miloš; Ćurić, Mladjen; Romanic, Djordje
2018-05-01
Gust fronts are thunderstorm-related phenomena usually associated with severe winds which are of great importance in theoretical meteorology, weather forecasting, cloud dynamics and precipitation, and wind engineering. An important feature of gust fronts demonstrated through both theoretical and observational studies is the periodic collapse and rebuild of the gust front head. This cyclic behavior of gust fronts results in periodic forcing of vertical velocity ahead of the parent thunderstorm, which consequently influences the storm dynamics and microphysics. This paper introduces the first gust front pulsation parameterization scheme in the WRF-ARW model (Weather Research and Forecasting-Advanced Research WRF). The influence of this new scheme on model performances is tested through investigation of the characteristics of an idealized supercell cumulonimbus cloud, as well as studying a real case of thunderstorms above the United Arab Emirates. In the ideal case, WRF with the gust front scheme produced more precipitation and showed different time evolution of mixing ratios of cloud water and rain, whereas the mixing ratios of ice and graupel are almost unchanged when compared to the default WRF run without the parameterization of gust front pulsation. The included parameterization did not disturb the general characteristics of thunderstorm cloud, such as the location of updraft and downdrafts, and the overall shape of the cloud. New cloud cells in front of the parent thunderstorm are also evident in both ideal and real cases due to the included forcing of vertical velocity caused by the periodic collapse of the gust front head. Despite some differences between the two WRF simulations and satellite observations, the inclusion of the gust front parameterization scheme produced more cumuliform clouds and seem to match better with real observations. Both WRF simulations gave poor results when it comes to matching the maximum composite radar reflectivity from radar measurement. Similar to the ideal case, WRF model with the gust front scheme gave more precipitation than the default WRF run. In particular, the gust front scheme increased the area characterized with light precipitation and diminished the development of very localized and intense precipitation.
Efficient secure-channel free public key encryption with keyword search for EMRs in cloud storage.
Guo, Lifeng; Yau, Wei-Chuen
2015-02-01
Searchable encryption is an important cryptographic primitive that enables privacy-preserving keyword search on encrypted electronic medical records (EMRs) in cloud storage. Efficiency of such searchable encryption in a medical cloud storage system is very crucial as it involves client platforms such as smartphones or tablets that only have constrained computing power and resources. In this paper, we propose an efficient secure-channel free public key encryption with keyword search (SCF-PEKS) scheme that is proven secure in the standard model. We show that our SCF-PEKS scheme is not only secure against chosen keyword and ciphertext attacks (IND-SCF-CKCA), but also secure against keyword guessing attacks (IND-KGA). Furthermore, our proposed scheme is more efficient than other recent SCF-PEKS schemes in the literature.
Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2
NASA Technical Reports Server (NTRS)
Titlow, James; Baum, Bryan A.
1993-01-01
Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.
NASA Astrophysics Data System (ADS)
Huang, Melin; Huang, Bormin; Huang, Allen H.-L.
2015-10-01
The schemes of cumulus parameterization are responsible for the sub-grid-scale effects of convective and/or shallow clouds, and intended to represent vertical fluxes due to unresolved updrafts and downdrafts and compensating motion outside the clouds. Some schemes additionally provide cloud and precipitation field tendencies in the convective column, and momentum tendencies due to convective transport of momentum. The schemes all provide the convective component of surface rainfall. Betts-Miller-Janjic (BMJ) is one scheme to fulfill such purposes in the weather research and forecast (WRF) model. National Centers for Environmental Prediction (NCEP) has tried to optimize the BMJ scheme for operational application. As there are no interactions among horizontal grid points, this scheme is very suitable for parallel computation. With the advantage of Intel Xeon Phi Many Integrated Core (MIC) architecture, efficient parallelization and vectorization essentials, it allows us to optimize the BMJ scheme. If compared to the original code respectively running on one CPU socket (eight cores) and on one CPU core with Intel Xeon E5-2670, the MIC-based optimization of this scheme running on Xeon Phi coprocessor 7120P improves the performance by 2.4x and 17.0x, respectively.
NASA Astrophysics Data System (ADS)
Liu, J.; Chen, Z.; Horowitz, L. W.; Carlton, A. M. G.; Fan, S.; Cheng, Y.; Ervens, B.; Fu, T. M.; He, C.; Tao, S.
2014-12-01
Secondary organic aerosols (SOA) have a profound influence on air quality and climate, but large uncertainties exist in modeling SOA on the global scale. In this study, five SOA parameterization schemes, including a two-product model (TPM), volatility basis-set (VBS) and three cloud SOA schemes (Ervens et al. (2008, 2014), Fu et al. (2008) , and He et al. (2013)), are implemented into the global chemical transport model (MOZART-4). For each scheme, model simulations are conducted with identical boundary and initial conditions. The VBS scheme produces the highest global annual SOA production (close to 35 Tg·y-1), followed by three cloud schemes (26-30 Tg·y-1) and TPM (23 Tg·y-1). Though sharing a similar partitioning theory to the TPM scheme, the VBS approach simulates the chemical aging of multiple generations of VOCs oxidation products, resulting in a much larger SOA source, particularly from aromatic species, over Europe, the Middle East and Eastern America. The formation of SOA in VBS, which represents the net partitioning of semi-volatile organic compounds from vapor to condensed phase, is highly sensitivity to the aging and wet removal processes of vapor-phase organic compounds. The production of SOA from cloud processes (SOAcld) is constrained by the coincidence of liquid cloud water and water-soluble organic compounds. Therefore, all cloud schemes resolve a fairly similar spatial pattern over the tropical and the mid-latitude continents. The spatiotemporal diversity among SOA parameterizations is largely driven by differences in precursor inputs. Therefore, a deeper understanding of the evolution, wet removal, and phase partitioning of semi-volatile organic compounds, particularly above remote land and oceanic areas, is critical to better constrain the global-scale distribution and related climate forcing of secondary organic aerosols.
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.
2011-01-01
Increases in computing resources have allowed for the utilization of high-resolution weather forecast models capable of resolving cloud microphysical and precipitation processes among varying numbers of hydrometeor categories. Several microphysics schemes are currently available within the Weather Research and Forecasting (WRF) model, ranging from single-moment predictions of precipitation content to double-moment predictions that include a prediction of particle number concentrations. Each scheme incorporates several assumptions related to the size distribution, shape, and fall speed relationships of ice crystals in order to simulate cold-cloud processes and resulting precipitation. Field campaign data offer a means of evaluating the assumptions present within each scheme. The Canadian CloudSat/CALIPSO Validation Project (C3VP) represented collaboration among the CloudSat, CALIPSO, and NASA Global Precipitation Measurement mission communities, to observe cold season precipitation processes relevant to forecast model evaluation and the eventual development of satellite retrievals of cloud properties and precipitation rates. During the C3VP campaign, widespread snowfall occurred on 22 January 2007, sampled by aircraft and surface instrumentation that provided particle size distributions, ice water content, and fall speed estimations along with traditional surface measurements of temperature and precipitation. In this study, four single-moment and two double-moment microphysics schemes were utilized to generate hypothetical WRF forecasts of the event, with C3VP data used in evaluation of their varying assumptions. Schemes that incorporate flexibility in size distribution parameters and density assumptions are shown to be preferable to fixed constants, and that a double-moment representation of the snow category may be beneficial when representing the effects of aggregation. These results may guide forecast centers in optimal configurations of their forecast models for winter weather and identify best practices present within these various schemes.
NASA Technical Reports Server (NTRS)
Molthan, A. L.; Haynes, J. A.; Case, J. L.; Jedlovec, G. L.; Lapenta, W. M.
2008-01-01
As computational power increases, operational forecast models are performing simulations with higher spatial resolution allowing for the transition from sub-grid scale cloud parameterizations to an explicit forecast of cloud characteristics and precipitation through the use of single- or multi-moment bulk water microphysics schemes. investments in space-borne and terrestrial remote sensing have developed the NASA CloudSat Cloud Profiling Radar and the NOAA National Weather Service NEXRAD system, each providing observations related to the bulk properties of clouds and precipitation through measurements of reflectivity. CloudSat and NEXRAD system radars observed light to moderate snowfall in association with a cold-season, midlatitude cyclone traversing the Central United States in February 2007. These systems are responsible for widespread cloud cover and various types of precipitation, are of economic consequence, and pose a challenge to operational forecasters. This event is simulated with the Weather Research and Forecast (WRF) Model, utilizing the NASA Goddard Cumulus Ensemble microphysics scheme. Comparisons are made between WRF-simulated and observed reflectivity available from the CloudSat and NEXRAD systems. The application of CloudSat reflectivity is made possible through the QuickBeam radiative transfer model, with cautious application applied in light of single scattering characteristics and spherical target assumptions. Significant differences are noted within modeled and observed cloud profiles, based upon simulated reflectivity, and modifications to the single-moment scheme are tested through a supplemental WRF forecast that incorporates a temperature dependent snow crystal size distribution.
An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment
Muthurajan, Vinothkumar; Narayanasamy, Balaji
2016-01-01
Cloud computing requires the security upgrade in data transmission approaches. In general, key-based encryption/decryption (symmetric and asymmetric) mechanisms ensure the secure data transfer between the devices. The symmetric key mechanisms (pseudorandom function) provide minimum protection level compared to asymmetric key (RSA, AES, and ECC) schemes. The presence of expired content and the irrelevant resources cause unauthorized data access adversely. This paper investigates how the integrity and secure data transfer are improved based on the Elliptic Curve based Schnorr scheme. This paper proposes a virtual machine based cloud model with Hybrid Cloud Security Algorithm (HCSA) to remove the expired content. The HCSA-based auditing improves the malicious activity prediction during the data transfer. The duplication in the cloud server degrades the performance of EC-Schnorr based encryption schemes. This paper utilizes the blooming filter concept to avoid the cloud server duplication. The combination of EC-Schnorr and blooming filter efficiently improves the security performance. The comparative analysis between proposed HCSA and the existing Distributed Hash Table (DHT) regarding execution time, computational overhead, and auditing time with auditing requests and servers confirms the effectiveness of HCSA in the cloud security model creation. PMID:26981584
An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment.
Muthurajan, Vinothkumar; Narayanasamy, Balaji
2016-01-01
Cloud computing requires the security upgrade in data transmission approaches. In general, key-based encryption/decryption (symmetric and asymmetric) mechanisms ensure the secure data transfer between the devices. The symmetric key mechanisms (pseudorandom function) provide minimum protection level compared to asymmetric key (RSA, AES, and ECC) schemes. The presence of expired content and the irrelevant resources cause unauthorized data access adversely. This paper investigates how the integrity and secure data transfer are improved based on the Elliptic Curve based Schnorr scheme. This paper proposes a virtual machine based cloud model with Hybrid Cloud Security Algorithm (HCSA) to remove the expired content. The HCSA-based auditing improves the malicious activity prediction during the data transfer. The duplication in the cloud server degrades the performance of EC-Schnorr based encryption schemes. This paper utilizes the blooming filter concept to avoid the cloud server duplication. The combination of EC-Schnorr and blooming filter efficiently improves the security performance. The comparative analysis between proposed HCSA and the existing Distributed Hash Table (DHT) regarding execution time, computational overhead, and auditing time with auditing requests and servers confirms the effectiveness of HCSA in the cloud security model creation.
Public Auditing with Privacy Protection in a Multi-User Model of Cloud-Assisted Body Sensor Networks
Li, Song; Cui, Jie; Zhong, Hong; Liu, Lu
2017-01-01
Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users’ medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs’ applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs’ deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models. PMID:28475110
Li, Song; Cui, Jie; Zhong, Hong; Liu, Lu
2017-05-05
Wireless Body Sensor Networks (WBSNs) are gaining importance in the era of the Internet of Things (IoT). The modern medical system is a particular area where the WBSN techniques are being increasingly adopted for various fundamental operations. Despite such increasing deployments of WBSNs, issues such as the infancy in the size, capabilities and limited data processing capacities of the sensor devices restrain their adoption in resource-demanding applications. Though providing computing and storage supplements from cloud servers can potentially enrich the capabilities of the WBSNs devices, data security is one of the prevailing issues that affects the reliability of cloud-assisted services. Sensitive applications such as modern medical systems demand assurance of the privacy of the users' medical records stored in distant cloud servers. Since it is economically impossible to set up private cloud servers for every client, auditing data security managed in the remote servers has necessarily become an integral requirement of WBSNs' applications relying on public cloud servers. To this end, this paper proposes a novel certificateless public auditing scheme with integrated privacy protection. The multi-user model in our scheme supports groups of users to store and share data, thus exhibiting the potential for WBSNs' deployments within community environments. Furthermore, our scheme enriches user experiences by offering public verifiability, forward security mechanisms and revocation of illegal group members. Experimental evaluations demonstrate the security effectiveness of our proposed scheme under the Random Oracle Model (ROM) by outperforming existing cloud-assisted WBSN models.
Mean-state acceleration of cloud-resolving models and large eddy simulations
Jones, C. R.; Bretherton, C. S.; Pritchard, M. S.
2015-10-29
In this study, large eddy simulations and cloud-resolving models (CRMs) are routinely used to simulate boundary layer and deep convective cloud processes, aid in the development of moist physical parameterization for global models, study cloud-climate feedbacks and cloud-aerosol interaction, and as the heart of superparameterized climate models. These models are computationally demanding, placing practical constraints on their use in these applications, especially for long, climate-relevant simulations. In many situations, the horizontal-mean atmospheric structure evolves slowly compared to the turnover time of the most energetic turbulent eddies. We develop a simple scheme to reduce this time scale separation to accelerate themore » evolution of the mean state. Using this approach we are able to accelerate the model evolution by a factor of 2–16 or more in idealized stratocumulus, shallow and deep cumulus convection without substantial loss of accuracy in simulating mean cloud statistics and their sensitivity to climate change perturbations. As a culminating test, we apply this technique to accelerate the embedded CRMs in the Superparameterized Community Atmosphere Model by a factor of 2, thereby showing that the method is robust and stable to realistic perturbations across spatial and temporal scales typical in a GCM.« less
A Parameterization of Dry Thermals and Shallow Cumuli for Mesoscale Numerical Weather Prediction
NASA Astrophysics Data System (ADS)
Pergaud, Julien; Masson, Valéry; Malardel, Sylvie; Couvreux, Fleur
2009-07-01
For numerical weather prediction models and models resolving deep convection, shallow convective ascents are subgrid processes that are not parameterized by classical local turbulent schemes. The mass flux formulation of convective mixing is now largely accepted as an efficient approach for parameterizing the contribution of larger plumes in convective dry and cloudy boundary layers. We propose a new formulation of the EDMF scheme (for Eddy DiffusivityMass Flux) based on a single updraft that improves the representation of dry thermals and shallow convective clouds and conserves a correct representation of stratocumulus in mesoscale models. The definition of entrainment and detrainment in the dry part of the updraft is original, and is specified as proportional to the ratio of buoyancy to vertical velocity. In the cloudy part of the updraft, the classical buoyancy sorting approach is chosen. The main closure of the scheme is based on the mass flux near the surface, which is proportional to the sub-cloud layer convective velocity scale w *. The link with the prognostic grid-scale cloud content and cloud cover and the projection on the non- conservative variables is processed by the cloud scheme. The validation of this new formulation using large-eddy simulations focused on showing the robustness of the scheme to represent three different boundary layer regimes. For dry convective cases, this parameterization enables a correct representation of the countergradient zone where the mass flux part represents the top entrainment (IHOP case). It can also handle the diurnal cycle of boundary-layer cumulus clouds (EUROCSARM) and conserve a realistic evolution of stratocumulus (EUROCSFIRE).
Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System
NASA Technical Reports Server (NTRS)
Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.
1996-01-01
An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.
Parameter Uncertainty on AGCM-simulated Tropical Cyclones
NASA Astrophysics Data System (ADS)
He, F.
2015-12-01
This work studies the parameter uncertainty on tropical cyclone (TC) simulations in Atmospheric General Circulation Models (AGCMs) using the Reed-Jablonowski TC test case, which is illustrated in Community Atmosphere Model (CAM). It examines the impact from 24 parameters across the physical parameterization schemes that represent the convection, turbulence, precipitation and cloud processes in AGCMs. The one-at-a-time (OAT) sensitivity analysis method first quantifies their relative importance on TC simulations and identifies the key parameters to the six different TC characteristics: intensity, precipitation, longwave cloud radiative forcing (LWCF), shortwave cloud radiative forcing (SWCF), cloud liquid water path (LWP) and ice water path (IWP). Then, 8 physical parameters are chosen and perturbed using the Latin-Hypercube Sampling (LHS) method. The comparison between OAT ensemble run and LHS ensemble run shows that the simulated TC intensity is mainly affected by the parcel fractional mass entrainment rate in Zhang-McFarlane (ZM) deep convection scheme. The nonlinear interactive effect among different physical parameters is negligible on simulated TC intensity. In contrast, this nonlinear interactive effect plays a significant role in other simulated tropical cyclone characteristics (precipitation, LWCF, SWCF, LWP and IWP) and greatly enlarge their simulated uncertainties. The statistical emulator Extended Multivariate Adaptive Regression Splines (EMARS) is applied to characterize the response functions for nonlinear effect. Last, we find that the intensity uncertainty caused by physical parameters is in a degree comparable to uncertainty caused by model structure (e.g. grid) and initial conditions (e.g. sea surface temperature, atmospheric moisture). These findings suggest the importance of using the perturbed physics ensemble (PPE) method to revisit tropical cyclone prediction under climate change scenario.
A Secure and Efficient Audit Mechanism for Dynamic Shared Data in Cloud Storage
2014-01-01
With popularization of cloud services, multiple users easily share and update their data through cloud storage. For data integrity and consistency in the cloud storage, the audit mechanisms were proposed. However, existing approaches have some security vulnerabilities and require a lot of computational overheads. This paper proposes a secure and efficient audit mechanism for dynamic shared data in cloud storage. The proposed scheme prevents a malicious cloud service provider from deceiving an auditor. Moreover, it devises a new index table management method and reduces the auditing cost by employing less complex operations. We prove the resistance against some attacks and show less computation cost and shorter time for auditing when compared with conventional approaches. The results present that the proposed scheme is secure and efficient for cloud storage services managing dynamic shared data. PMID:24959630
A secure and efficient audit mechanism for dynamic shared data in cloud storage.
Kwon, Ohmin; Koo, Dongyoung; Shin, Yongjoo; Yoon, Hyunsoo
2014-01-01
With popularization of cloud services, multiple users easily share and update their data through cloud storage. For data integrity and consistency in the cloud storage, the audit mechanisms were proposed. However, existing approaches have some security vulnerabilities and require a lot of computational overheads. This paper proposes a secure and efficient audit mechanism for dynamic shared data in cloud storage. The proposed scheme prevents a malicious cloud service provider from deceiving an auditor. Moreover, it devises a new index table management method and reduces the auditing cost by employing less complex operations. We prove the resistance against some attacks and show less computation cost and shorter time for auditing when compared with conventional approaches. The results present that the proposed scheme is secure and efficient for cloud storage services managing dynamic shared data.
Streaming support for data intensive cloud-based sequence analysis.
Issa, Shadi A; Kienzler, Romeo; El-Kalioby, Mohamed; Tonellato, Peter J; Wall, Dennis; Bruggmann, Rémy; Abouelhoda, Mohamed
2013-01-01
Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of "resources-on-demand" and "pay-as-you-go", scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client's site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation.
NASA Astrophysics Data System (ADS)
Zhou, C.; Zhang, X.; Gong, S.
2015-12-01
A comprehensive aerosol-cloud-precipitation interaction (ACI) scheme has been developed under CMA chemical weather modeling system GRAPES/CUACE. Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model GRAPES at each time step, the cloud condensation nuclei (CCN) is fed online interactively into a two-moment cloud scheme (WDM6) and a convective parameterization to drive the cloud physics and precipitation formation processes. The modeling system has been applied to study the ACI for January 2013 when several persistent haze-fog events and eight precipitation events occurred. The results show that interactive aerosols with the WDM6 in GRAPES/CUACE obviously increase the total cloud water, liquid water content and cloud droplet number concentrations while decrease the mean diameter of cloud droplets with varying magnitudes of the changes in each case and region. These interactive micro-physical properties of clouds improve the calculation of their collection growth rates in some regions and hence the precipitation rate and distributions in the model, showing 24% to 48% enhancements of TS scoring for 6-h precipitation in almost all regions. The interactive aerosols with the WDM6 also reduce the regional mean bias of temperature by 3 °C during certain precipitation events, but the monthly means bias is only reduced by about 0.3°C.
A physically-based retrieval of cloud liquid water from SSM/I measurements
NASA Technical Reports Server (NTRS)
Greenwald, Thomas J.; Stephens, Graeme L.; Vonder Haar, Thomas H.
1992-01-01
A simple physical scheme is proposed for retrieving cloud liquid water over the ice-free global oceans from Special Sensor Microwave/Imager (SSM/I) observations. Details of the microwave retrieval scheme are discussed, and the microwave-derived liquid water amounts are compared with the ground radiometer and AVHRR-derived liquid water for stratocumulus clouds off the coast of California. Global distributions of the liquid water path derived by the method proposed here are presented.
Non-local Second Order Closure Scheme for Boundary Layer Turbulence and Convection
NASA Astrophysics Data System (ADS)
Meyer, Bettina; Schneider, Tapio
2017-04-01
There has been scientific consensus that the uncertainty in the cloud feedback remains the largest source of uncertainty in the prediction of climate parameters like climate sensitivity. To narrow down this uncertainty, not only a better physical understanding of cloud and boundary layer processes is required, but specifically the representation of boundary layer processes in models has to be improved. General climate models use separate parameterisation schemes to model the different boundary layer processes like small-scale turbulence, shallow and deep convection. Small scale turbulence is usually modelled by local diffusive parameterisation schemes, which truncate the hierarchy of moment equations at first order and use second-order equations only to estimate closure parameters. In contrast, the representation of convection requires higher order statistical moments to capture their more complex structure, such as narrow updrafts in a quasi-steady environment. Truncations of moment equations at second order may lead to more accurate parameterizations. At the same time, they offer an opportunity to take spatially correlated structures (e.g., plumes) into account, which are known to be important for convective dynamics. In this project, we study the potential and limits of local and non-local second order closure schemes. A truncation of the momentum equations at second order represents the same dynamics as a quasi-linear version of the equations of motion. We study the three-dimensional quasi-linear dynamics in dry and moist convection by implementing it in a LES model (PyCLES) and compare it to a fully non-linear LES. In the quasi-linear LES, interactions among turbulent eddies are suppressed but nonlinear eddy—mean flow interactions are retained, as they are in the second order closure. In physical terms, suppressing eddy—eddy interactions amounts to suppressing, e.g., interactions among convective plumes, while retaining interactions between plumes and the environment (e.g., entrainment and detrainment). In a second part, we employ the possibility to include non-local statistical correlations in a second-order closure scheme. Such non-local correlations allow to directly incorporate the spatially coherent structures that occur in the form of convective updrafts penetrating the boundary layer. This allows us to extend the work that has been done using assumed-PDF schemes for parameterising boundary layer turbulence and shallow convection in a non-local sense.
a Cumulus Parameterization Study with Special Attention to the Arakawa-Schubert Scheme
NASA Astrophysics Data System (ADS)
Kao, Chih-Yue Jim
Arakawa and Schubert (1974) developed a cumulus parameterization scheme in a framework that conceptually divides the mutual interaction of the cumulus convection and large-scale disturbance into the categories of large -scale budget requirements and the quasi-equilibrium assumption of cloud work function. We have applied the A-S scheme through a semi-prognostic approach to two different data sets: one is for an intense tropical cloud band event; the other is for tropical composite easterly wave disturbances. Both were observed in GATE. The cloud heating and drying effects predicted by the Arakawa-Schubert scheme are found to agree rather well with the observations. However, it is also found that the Arakawa-Schubert scheme underestimates both condensation and evaporation rates substantially when compared with the cumulus ensemble model results (Soong and Tao, 1980; Tao, 1983). An inclusion of the downdraft effects, as formulated by Johnson (1976), appears to alleviate this deficiency. In order to examine how the Arakawa-Schubert scheme works in a fully prognostic problem, a simulation of the evolution and structure of the tropical cloud band, mentioned above, under the influence of an imposed large-scale low -level forcing has been made, using a two-dimensional hydrostatic model with the inclusion of the Arakawa-Schubert scheme. Basically, the model result indicates that the meso-scale convective system is driven by the excess of the convective heating derived from the Arakawa-Schubert scheme over the adiabatic cooling due to the imposed large-scale lifting and induced meso-scale upward motion. However, as the convective system develops, the adiabatic warming due to the subsidence outside the cloud cluster gradually accumulates into a secondary temperature anomaly which subsequently reduces the original temperature contrast and inhibits the further development of the convective system. A 24 hour integration shows that the model is capable of simulating many important features such as the life cycle, intensity of circulation, and rainfall rates.
Introducing the MIT Regional Climate Model (MRCM)
NASA Astrophysics Data System (ADS)
Eltahir, Elfatih A. B.; Winter, Jonathn M.; Marcella, Marc P.; Gianotti, Rebecca L.; Im, Eun-Soon
2013-04-01
During the last decade researchers at MIT have worked on improving the skill of Regional Climate Model version 3 (RegCM3) in simulating climate over different regions through the incorporation of new physical schemes or modification of original schemes. The MIT Regional Climate Model (MRCM) features several modifications over RegCM3 including coupling of Integrated Biosphere Simulator (IBIS), a new surface albedo assignment method, a new convective cloud and rainfall auto-conversion scheme, and a modified boundary layer height and cloud scheme. Here, we introduce the MRCM and briefly describe the major model modifications relative to RegCM3 and their impact on the model performance. The most significant difference relative to the RegCM3 original configuration is coupling the Integrated Biosphere Simulator (IBIS) land-surface scheme (Winter et al., 2009). Based on the simulations using IBIS over the North America, the Maritime Continent, Southwest Asia and West Africa, we demonstrate that the use of IBIS as the land surface scheme results in better representation of surface energy and water budgets in comparison to BATS. Furthermore, the addition of a new irrigation scheme to IBIS makes it possible to investigate the effects of irrigation over any region. Also a new surface albedo assignment method used together with IBIS brings further improvement in simulations of surface radiation (Marcella and Eltahir, 2013). Another important feature of the MRCM is the introduction of a new convective cloud and rainfall auto-conversion scheme (Gianotti and Eltahir, 2013). This modification brings more physical realism into an important component of the model, and succeeds in simulating convective-radiative feedback improving model performance across several radiation fields and rainfall characteristics. Other features of MRCM such as the modified boundary layer height and cloud scheme, and the improvements in the dust emission and transport representations will be discussed.
NASA Technical Reports Server (NTRS)
Li, Xiao-Fan; Sui, C.-H.; Lau, K.-M.; Tao, W.-K.
2004-01-01
Prognostic cloud schemes are increasingly used in weather and climate models in order to better treat cloud-radiation processes. Simplifications are often made in such schemes for computational efficiency, like the scheme being used in the National Centers for Environment Prediction models that excludes some microphysical processes and precipitation-radiation interaction. In this study, sensitivity tests with a 2D cloud resolving model are carried out to examine effects of the excluded microphysical processes and precipitation-radiation interaction on tropical thermodynamics and cloud properties. The model is integrated for 10 days with the imposed vertical velocity derived from the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment. The experiment excluding the depositional growth of snow from cloud ice shows anomalous growth of cloud ice and more than 20% increase of fractional cloud cover, indicating that the lack of the depositional snow growth causes unrealistically large mixing ratio of cloud ice. The experiment excluding the precipitation-radiation interaction displays a significant cooling and drying bias. The analysis of heat and moisture budgets shows that the simulation without the interaction produces more stable upper troposphere and more unstable mid and lower troposphere than does the simulation with the interaction. Thus, the suppressed growth of ice clouds in upper troposphere and stronger radiative cooling in mid and lower troposphere are responsible for the cooling bias, and less evaporation of rain associated with the large-scale subsidence induces the drying in mid and lower troposphere.
NASA Astrophysics Data System (ADS)
Arabas, S.; Jaruga, A.; Pawlowska, H.; Grabowski, W. W.
2012-12-01
Clouds may influence aerosol characteristics of their environment. The relevant processes include wet deposition (rainout or washout) and cloud condensation nuclei (CCN) recycling through evaporation of cloud droplets and drizzle drops. Recycled CCN physicochemical properties may be altered if the evaporated droplets go through collisional growth or irreversible chemical reactions (e.g. SO2 oxidation). The key challenge of representing these processes in a numerical cloud model stems from the need to track properties of activated CCN throughout the cloud lifecycle. Lack of such "memory" characterises the so-called bulk, multi-moment as well as bin representations of cloud microphysics. In this study we apply the particle-based scheme of Shima et al. 2009. Each modelled particle (aka super-droplet) is a numerical proxy for a multiplicity of real-world CCN, cloud, drizzle or rain particles of the same size, nucleus type,and position. Tracking cloud nucleus properties is an inherent feature of the particle-based frameworks, making them suitable for studying aerosol-cloud-aerosol interactions. The super-droplet scheme is furthermore characterized by linear scalability in the number of computational particles, and no numerical diffusion in the condensational and in the Monte-Carlo type collisional growth schemes. The presentation will focus on processing of aerosol by a drizzling stratocumulus deck. The simulations are carried out using a 2D kinematic framework and a VOCALS experiment inspired set-up (see http://www.rap.ucar.edu/~gthompsn/workshop2012/case1/).
Radiative Transfer and Satellite Remote Sensing of Cirrus Clouds Using FIRE-2-IFO Data
NASA Technical Reports Server (NTRS)
2000-01-01
Under the support of the NASA grant, we have developed a new geometric-optics model (GOM2) for the calculation of the single-scattering and polarization properties for arbitrarily oriented hexagonal ice crystals. From comparisons with the results computed by the finite difference time domain (FDTD) method, we show that the novel geometric-optics can be applied to the computation of the extinction cross section and single-scattering albedo for ice crystals with size parameters along the minimum dimension as small as approximately 6. We demonstrate that the present model converges to the conventional ray tracing method for large size parameters and produces single-scattering results close to those computed by the FDTD method for size parameters along the minimum dimension smaller than approximately 20. We demonstrate that neither the conventional geometric optics method nor the Lorenz-Mie theory can be used to approximate the scattering, absorption, and polarization features for hexagonal ice crystals with size parameters from approximately 5 to 20. On the satellite remote sensing algorithm development and validation, we have developed a numerical scheme to identify multilayer cirrus cloud systems using AVHRR data. We have applied this scheme to the satellite data collected over the FIRE-2-IFO area during nine overpasses within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analyses of these satellite data.
The Impact of Microphysics on Intensity and Structure of Hurricanes
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Shi, Jainn; Lang, Steve; Peters-Lidard, Christa
2006-01-01
During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WFW is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WFW model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WW to examine the impact of six different cloud microphysical schemes on hurricane track, intensity and rainfall forecast. We are also performing the inline tracer calculation to comprehend the physical processes @e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes.
NASA Astrophysics Data System (ADS)
Silva Junior, R. S.; Rocha, R. P.; Andrade, M. F.
2007-05-01
The Planetary Boundary Layer (PBL) is the region of the atmosphere that suffers the direct influence of surface processes and the evolution of their characteristics during the day is of great importance for the pollutants dispersion. The aim of the present work is to analyze the most efficient combination of PBL, cumulus convection and cloud microphysics parameterizations for the forecast of the vertical profile of wind speed over Metropolitan Region of São Paulo (MRSP) that presents serious problems of atmospheric pollution. The model used was the WRF/Chem that was integrated for 48 h forecasts during one week of observational experiment that take place in the MRSP during October-November of 2006. The model domain has 72 x 48 grid points, with 18 km of resolution, centered in the MRSP. Considering a mixed-physics ensemble approach the forecasts used a combination of the parameterizations: (a) PBL the schemes of Mellor-Yamada-Janjic (MYJ) and Yonsei University Scheme (YSU); (b) cumulus convections schemes of Grell-Devenyi ensemble (GDE) and Betts-Miller-Janjic (BMJ); (c) cloud microphysics schemes of Purdue Lin (MPL) and NCEP 5-class (MPN). The combinations tested were the following: MYJ-BMJ-MPL, MYJ-BMJ-MPN, MYJ-GDE-MPL, MYJ-GDE-MPN, YSU-BMJ-MPL, YSU-BMJ-MPN, YSU-GDE-MPL, YSU-GDE-MPN, i.e., a set of 8 previsions for day. The model initial and boundary conditions was obtained of the AVN-NCEP model. Besides this data set, the MRSP observed soundings were used to verify the WRF results. The statistical analysis considered the correlation coefficient, root mean square error, mean error between forecasts and observed wind profiles. The results showed that the most suitable combination is the YSU-GDE-MPL. This can be associated to the GDE cumulus convection scheme, which takes into consideration the entrainment process in the clouds, and also the MPL scheme that considers a larger number of classes of water phase, including the ice and mixed phases. For PBL the YSU presents the better approaches to represent the wind speed, where the atmospheric gradients are stronger and the atmosphere is less mixed.
NASA Astrophysics Data System (ADS)
Wang, M.; Peng, Y.; Xie, X.; Liu, Y.
2017-12-01
Aerosol cloud interaction continues to constitute one of the most significant uncertainties for anthropogenic climate perturbations. The parameterization of cloud droplet size distribution and autoconversion process from large scale cloud to rain can influence the estimation of first and second aerosol indirect effects in global climate models. We design a series of experiments focusing on the microphysical cloud scheme of NCAR CAM5 (Community Atmospheric Model Version 5) in transient historical run with realistic sea surface temperature and sea ice. We investigate the effect of three empirical, two semi-empirical and one analytical expressions for droplet size distribution on cloud properties and explore the statistical relationships between aerosol optical thickness (AOT) and simulated cloud variables, including cloud top droplet effective radius (CDER), cloud optical depth (COD), cloud water path (CWP). We also introduce the droplet spectral shape parameter into the autoconversion process to incorporate the effect of droplet size distribution on second aerosol indirect effect. Three satellite datasets (MODIS Terra/ MODIS Aqua/ AVHRR) are used to evaluate the simulated aerosol indirect effect from the model. Evident CDER decreasing with significant AOT increasing is found in the east coast of China to the North Pacific Ocean and the east coast of USA to the North Atlantic Ocean. Analytical and semi-empirical expressions for spectral shape parameterization show stronger first aerosol indirect effect but weaker second aerosol indirect effect than empirical expressions because of the narrower droplet size distribution.
Mesoscale acid deposition modeling studies
NASA Technical Reports Server (NTRS)
Kaplan, Michael L.; Proctor, F. H.; Zack, John W.; Karyampudi, V. Mohan; Price, P. E.; Bousquet, M. D.; Coats, G. D.
1989-01-01
The work performed in support of the EPA/DOE MADS (Mesoscale Acid Deposition) Project included the development of meteorological data bases for the initialization of chemistry models, the testing and implementation of new planetary boundary layer parameterization schemes in the MASS model, the simulation of transport and precipitation for MADS case studies employing the MASS model, and the use of the TASS model in the simulation of cloud statistics and the complex transport of conservative tracers within simulated cumuloform clouds. The work performed in support of the NASA/FAA Wind Shear Program included the use of the TASS model in the simulation of the dynamical processes within convective cloud systems, the analyses of the sensitivity of microburst intensity and general characteristics as a function of the atmospheric environment within which they are formed, comparisons of TASS model microburst simulation results to observed data sets, and the generation of simulated wind shear data bases for use by the aviation meteorological community in the evaluation of flight hazards caused by microbursts.
NASA Technical Reports Server (NTRS)
Betancourt, R. Morales; Lee, D.; Oreopoulos, L.; Sud, Y. C.; Barahona, D.; Nenes, A.
2012-01-01
The salient features of mixed-phase and ice clouds in a GCM cloud scheme are examined using the ice formation parameterizations of Liu and Penner (LP) and Barahona and Nenes (BN). The performance of LP and BN ice nucleation parameterizations were assessed in the GEOS-5 AGCM using the McRAS-AC cloud microphysics framework in single column mode. Four dimensional assimilated data from the intensive observation period of ARM TWP-ICE campaign was used to drive the fluxes and lateral forcing. Simulation experiments where established to test the impact of each parameterization in the resulting cloud fields. Three commonly used IN spectra were utilized in the BN parameterization to described the availability of IN for heterogeneous ice nucleation. The results show large similarities in the cirrus cloud regime between all the schemes tested, in which ice crystal concentrations were within a factor of 10 regardless of the parameterization used. In mixed-phase clouds there are some persistent differences in cloud particle number concentration and size, as well as in cloud fraction, ice water mixing ratio, and ice water path. Contact freezing in the simulated mixed-phase clouds contributed to transfer liquid to ice efficiently, so that on average, the clouds were fully glaciated at T approximately 260K, irrespective of the ice nucleation parameterization used. Comparison of simulated ice water path to available satellite derived observations were also performed, finding that all the schemes tested with the BN parameterization predicted 20 average values of IWP within plus or minus 15% of the observations.
A Secure and Verifiable Outsourced Access Control Scheme in Fog-Cloud Computing.
Fan, Kai; Wang, Junxiong; Wang, Xin; Li, Hui; Yang, Yintang
2017-07-24
With the rapid development of big data and Internet of things (IOT), the number of networking devices and data volume are increasing dramatically. Fog computing, which extends cloud computing to the edge of the network can effectively solve the bottleneck problems of data transmission and data storage. However, security and privacy challenges are also arising in the fog-cloud computing environment. Ciphertext-policy attribute-based encryption (CP-ABE) can be adopted to realize data access control in fog-cloud computing systems. In this paper, we propose a verifiable outsourced multi-authority access control scheme, named VO-MAACS. In our construction, most encryption and decryption computations are outsourced to fog devices and the computation results can be verified by using our verification method. Meanwhile, to address the revocation issue, we design an efficient user and attribute revocation method for it. Finally, analysis and simulation results show that our scheme is both secure and highly efficient.
Improving the Representation of Snow Crystal Properties Within a Single-Moment Microphysics Scheme
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, S. R.
2010-01-01
As computational resources continue their expansion, weather forecast models are transitioning to the use of parameterizations that predict the evolution of hydrometeors and their microphysical processes, rather than estimating the bulk effects of clouds and precipitation that occur on a sub-grid scale. These parameterizations are referred to as single-moment, bulk water microphysics schemes, as they predict the total water mass among hydrometeors in a limited number of classes. Although the development of single moment microphysics schemes have often been driven by the need to predict the structure of convective storms, they may also provide value in predicting accumulations of snowfall. Predicting the accumulation of snowfall presents unique challenges to forecasters and microphysics schemes. In cases where surface temperatures are near freezing, accumulated depth often depends upon the snowfall rate and the ability to overcome an initial warm layer. Precipitation efficiency relates to the dominant ice crystal habit, as dendrites and plates have relatively large surface areas for the accretion of cloud water and ice, but are only favored within a narrow range of ice supersaturation and temperature. Forecast models and their parameterizations must accurately represent the characteristics of snow crystal populations, such as their size distribution, bulk density and fall speed. These properties relate to the vertical distribution of ice within simulated clouds, the temperature profile through latent heat release, and the eventual precipitation rate measured at the surface. The NASA Goddard, single-moment microphysics scheme is available to the operational forecast community as an option within the Weather Research and Forecasting (WRF) model. The NASA Goddard scheme predicts the occurrence of up to six classes of water mass: vapor, cloud ice, cloud water, rain, snow and either graupel or hail.
Evaluating and Improving Cloud Processes in the Multi-Scale Modeling Framework
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ackerman, Thomas P.
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
NASA Astrophysics Data System (ADS)
Bower, Keith; Choularton, Tom; Latham, John; Sahraei, Jalil; Salter, Stephen
2006-11-01
A simplified version of the model of marine stratocumulus clouds developed by Bower, Jones and Choularton [Bower, K.N., Jones, A., and Choularton, T.W., 1999. A modeling study of aerosol processing by stratocumulus clouds and its impact on GCM parameterisations of cloud and aerosol. Atmospheric Research, Vol. 50, Nos. 3-4, The Great Dun Fell Experiment, 1995-special issue, 317-344.] was used to examine the sensitivity of the albedo-enhancement global warming mitigation scheme proposed by Latham [Latham, J., 1990. Control of global warming? Nature 347, 339-340; Latham, J., 2002. Amelioration of global warming by controlled enhancement of the albedo and longevity of low-level maritime clouds. Atmos. Sci. Letters (doi:10.1006/Asle.2002.0048).] to the cloud and environmental aerosol characteristics, as well as those of the seawater aerosol of salt-mass ms and number concentration Δ N, which-under the scheme-are advertently introduced into the clouds. Values of albedo-change Δ A and droplet number concentration Nd were calculated for a wide range of values of ms, Δ N, updraught speed W, cloud thickness Δ Z and cloud-base temperature TB: for three measured aerosol spectra, corresponding to ambient air of negligible, moderate and high levels of pollution. Our choices of parameter value ranges were determined by the extent of their applicability to the mitigation scheme, whose current formulation is still somewhat preliminary, thus rendering unwarranted in this study the utilisation of refinements incorporated into other stratocumulus models. In agreement with earlier studies: (1) Δ A was found to be very sensitive to Δ N and (within certain constraints) insensitive to changes in ms, W, Δ Z and TB; (2) Δ A was greatest for clouds formed in pure air and least for highly polluted air. In many situations considered to be within the ambit of the mitigation scheme, the calculated Δ A values exceeded those estimated by earlier workers as being necessary to produce a cooling sufficient to compensate, globally, for the warming resulting from a doubling of the atmospheric carbon dioxide concentration. Our calculations provide quantitative support for the physical viability of the mitigation scheme and offer new insights into its technological requirements.
Development of Spaceborne Radar Simulator by NICT and JAXA using JMA Cloud-resolving Model
NASA Astrophysics Data System (ADS)
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, snow, cloud water, cloud ice and hail (4-ice scheme only). We examined a case of an intersection with the TRMM PR and the CloudSat CPR on 6th April 2008 over sea surface in the south of Kyushu Island of Japan. In this work, observed rainfall systems are simulated with one-way double nested domains having horizontal grid sizes of 5 km (outer) and 2 km (inner). Data used here are from the inner domain only. Results of the PR indicated better performances of 2-moment bulk schemes. It suggests that prognostic number concentrations of frozen hydrometeors are more effective in high altitudes and constant number concentrations can lead to the overestimation of the snow there. For three-ice schemes, simulated received power data overestimated above freezing levels with reference to the observed data. In contrast, the overestimation of frozen particles was heavily reduced for the four-ice scheme.
Investigating the scale-adaptivity of a shallow cumulus parameterization scheme with LES
NASA Astrophysics Data System (ADS)
Brast, Maren; Schemann, Vera; Neggers, Roel
2017-04-01
In this study we investigate the scale-adaptivity of a new parameterization scheme for shallow cumulus clouds in the gray zone. The Eddy-Diffusivity Multiple Mass-Flux (or ED(MF)n ) scheme is a bin-macrophysics scheme, in which subgrid transport is formulated in terms of discretized size densities. While scale-adaptivity in the ED-component is achieved using a pragmatic blending approach, the MF-component is filtered such that only the transport by plumes smaller than the grid size is maintained. For testing, ED(MF)n is implemented in a large-eddy simulation (LES) model, replacing the original subgrid-scheme for turbulent transport. LES thus plays the role of a non-hydrostatic testing ground, which can be run at different resolutions to study the behavior of the parameterization scheme in the boundary-layer gray zone. In this range convective cumulus clouds are partially resolved. We find that at high resolutions the clouds and the turbulent transport are predominantly resolved by the LES, and the transport represented by ED(MF)n is small. This partitioning changes towards coarser resolutions, with the representation of shallow cumulus clouds becoming exclusively carried by the ED(MF)n. The way the partitioning changes with grid-spacing matches the results of previous LES studies, suggesting some scale-adaptivity is captured. Sensitivity studies show that a scale-inadaptive ED component stays too active at high resolutions, and that the results are fairly insensitive to the number of transporting updrafts in the ED(MF)n scheme. Other assumptions in the scheme, such as the distribution of updrafts across sizes and the value of the area fraction covered by updrafts, are found to affect the location of the gray zone.
Improving the representation of mixed-phase cloud microphysics in the ICON-LEM
NASA Astrophysics Data System (ADS)
Tonttila, Juha; Hoose, Corinna; Milbrandt, Jason; Morrison, Hugh
2017-04-01
The representation of ice-phase cloud microphysics in ICON-LEM (the Large-Eddy Model configuration of the ICOsahedral Nonhydrostatic model) is improved by implementing the recently published Predicted Particle Properties (P3) scheme into the model. In the typical two-moment microphysical schemes, such as that previously used in ICON-LEM, ice-phase particles must be partitioned into several prescribed categories. It is inherently difficult to distinguish between categories such as graupel and hail based on just the particle size, yet this partitioning may significantly affect the simulation of convective clouds. The P3 scheme avoids the problems associated with predefined ice-phase categories that are inherent in traditional microphysics schemes by introducing the concept of "free" ice-phase categories, whereby the prognostic variables enable the prediction of a wide range of smoothly varying physical properties and hence particle types. To our knowledge, this is the first application of the P3 scheme in a large-eddy model with horizontal grid spacings on the order of 100 m. We will present results from ICON-LEM simulations with the new P3 scheme comprising idealized stratiform and convective cloud cases. We will also present real-case limited-area simulations focusing on the HOPE (HD(CP)2 Observational Prototype Experiment) intensive observation campaign. The results are compared with a matching set of simulations employing the two-moment scheme and the performance of the model is also evaluated against observations in the context of the HOPE simulations, comprising data from ground based remote sensing instruments.
NASA Astrophysics Data System (ADS)
Ma, Zhanshan; Liu, Qijun; Zhao, Chuanfeng; Shen, Xueshun; Wang, Yuan; Jiang, Jonathan H.; Li, Zhe; Yung, Yuk
2018-03-01
An explicit prognostic cloud-cover scheme (PROGCS) is implemented into the Global/Regional Assimilation and Prediction System (GRAPES) for global middle-range numerical weather predication system (GRAPES_GFS) to improve the model performance in simulating cloud cover and radiation. Unlike the previous diagnostic cloud-cover scheme (DIAGCS), PROGCS considers the formation and dissipation of cloud cover by physically connecting it to the cumulus convection and large-scale stratiform condensation processes. Our simulation results show that clouds in mid-high latitudes arise mainly from large-scale stratiform condensation processes, while cumulus convection and large-scale condensation processes jointly determine cloud cover in low latitudes. Compared with DIAGCS, PROGCS captures more consistent vertical distributions of cloud cover with the observations from Atmospheric Radiation Measurements (ARM) program at the Southern Great Plains (SGP) site and simulates more realistic diurnal cycle of marine stratocumulus with the ERA-Interim reanalysis data. The low, high, and total cloud covers that are determined via PROGCS appear to be more realistic than those simulated via DIAGCS when both are compared with satellite retrievals though the former maintains slight negative biases. In addition, the simulations of outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) from PROGCS runs have been considerably improved as well, resulting in less biases in radiative heating rates at heights below 850 hPa and above 400 hPa of GRAPES_GFS. Our results indicate that a prognostic method of cloud-cover calculation has significant advantage over the conventional diagnostic one, and it should be adopted in both weather and climate simulation and forecast.
NASA Astrophysics Data System (ADS)
Hoose, C.; Hande, L. B.; Mohler, O.; Niemand, M.; Paukert, M.; Reichardt, I.; Ullrich, R.
2016-12-01
Between 0 and -37°C, ice formation in clouds is triggered by aerosol particles acting as heterogeneous ice nuclei. At lower temperatures, heterogeneous ice nucleation on aerosols can occur at lower supersaturations than homogeneous freezing of solutes. In laboratory experiments, the ability of different aerosol species (e.g. desert dusts, soot, biological particles) has been studied in detail and quantified via various theoretical or empirical parameterization approaches. For experiments in the AIDA cloud chamber, we have quantified the ice nucleation efficiency via a temperature- and supersaturation dependent ice nucleation active site density. Here we present a new empirical parameterization scheme for immersion and deposition ice nucleation on desert dust and soot based on these experimental data. The application of this parameterization to the simulation of cirrus clouds, deep convective clouds and orographic clouds will be shown, including the extension of the scheme to the treatment of freezing of rain drops. The results are compared to other heterogeneous ice nucleation schemes. Furthermore, an aerosol-dependent parameterization of contact ice nucleation is presented.
Streaming Support for Data Intensive Cloud-Based Sequence Analysis
Issa, Shadi A.; Kienzler, Romeo; El-Kalioby, Mohamed; Tonellato, Peter J.; Wall, Dennis; Bruggmann, Rémy; Abouelhoda, Mohamed
2013-01-01
Cloud computing provides a promising solution to the genomics data deluge problem resulting from the advent of next-generation sequencing (NGS) technology. Based on the concepts of “resources-on-demand” and “pay-as-you-go”, scientists with no or limited infrastructure can have access to scalable and cost-effective computational resources. However, the large size of NGS data causes a significant data transfer latency from the client's site to the cloud, which presents a bottleneck for using cloud computing services. In this paper, we provide a streaming-based scheme to overcome this problem, where the NGS data is processed while being transferred to the cloud. Our scheme targets the wide class of NGS data analysis tasks, where the NGS sequences can be processed independently from one another. We also provide the elastream package that supports the use of this scheme with individual analysis programs or with workflow systems. Experiments presented in this paper show that our solution mitigates the effect of data transfer latency and saves both time and cost of computation. PMID:23710461
NASA Technical Reports Server (NTRS)
Stano, Geoffrey T.; Fuelberg, Henry E.; Roeder, William P.
2010-01-01
This research addresses the 45th Weather Squadron's (45WS) need for improved guidance regarding lightning cessation at Cape Canaveral Air Force Station and Kennedy Space Center (KSC). KSC's Lightning Detection and Ranging (LDAR) network was the primary observational tool to investigate both cloud-to-ground and intracloud lightning. Five statistical and empirical schemes were created from LDAR, sounding, and radar parameters derived from 116 storms. Four of the five schemes were unsuitable for operational use since lightning advisories would be canceled prematurely, leading to safety risks to personnel. These include a correlation and regression tree analysis, three variants of multiple linear regression, event time trending, and the time delay between the greatest height of the maximum dBZ value to the last flash. These schemes failed to adequately forecast the maximum interval, the greatest time between any two flashes in the storm. The majority of storms had a maximum interval less than 10 min, which biased the schemes toward small values. Success was achieved with the percentile method (PM) by separating the maximum interval into percentiles for the 100 dependent storms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kao, C.Y.J.; Bossert, J.E.; Winterkamp, J.
1993-10-01
One of the objectives of the DOE ARM Program is to improve the parameterization of clouds in general circulation models (GCMs). The approach taken in this research is two fold. We first examine the behavior of cumulus parameterization schemes by comparing their performance against the results from explicit cloud simulations with state-of-the-art microphysics. This is conducted in a two-dimensional (2-D) configuration of an idealized convective system. We then apply the cumulus parameterization schemes to realistic three-dimensional (3-D) simulations over the western US for a case with an enormous amount of convection in an extended period of five days. In themore » 2-D idealized tests, cloud effects are parameterized in the ``parameterization cases`` with a coarse resolution, whereas each cloud is explicitly resolved by the ``microphysics cases`` with a much finer resolution. Thus, the capability of the parameterization schemes in reproducing the growth and life cycle of a convective system can then be evaluated. These 2-D tests will form the basis for further 3-D realistic simulations which have the model resolution equivalent to that of the next generation of GCMs. Two cumulus parameterizations are used in this research: the Arakawa-Schubert (A-S) scheme (Arakawa and Schubert, 1974) used in Kao and Ogura (1987) and the Kuo scheme (Kuo, 1974) used in Tremback (1990). The numerical model used in this research is the Regional Atmospheric Modeling System (RAMS) developed at Colorado State University (CSU).« less
Process-model simulations of cloud albedo enhancement by aerosols in the Arctic.
Kravitz, Ben; Wang, Hailong; Rasch, Philip J; Morrison, Hugh; Solomon, Amy B
2014-12-28
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. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Process-model simulations of cloud albedo enhancement by aerosols in the Arctic
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
The direct assimilation of cloud-affected satellite infrared radiance in the NCEP 3D-Hybrid system
NASA Astrophysics Data System (ADS)
Zhang, X.
2016-12-01
A function has been developed in NCEP 3D-Hybrid system to make use of Infrared radiances from Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat-10(MSG-10) satellite in overcast cloudy conditions where effective cloud fractions were greater than 0.9. These cloudy radiances provide new information that currently assimilated in clear-sky condition from SEVIRI MSG-10. The model state vector is locally extended at observation locations, to include cloud top pressure as cloud parameters. This parameter describing a single-layer cloud are simultaneously estimated together with temperature and humidity inside the main analysis. Assimilation experiments have been run with the new scheme in which overcast radiance from SEVIRI MSG-10 are used in addition to the available clear-sky data. Two water vapor channels ( 6.2 and 7.3μm) and window channels (8.5, 11.2, 12.3 and 13.3μm) from SEVIRI MSG-10 are assimilated in the experiments. The overcast data locations typically represent 10% or less of the total due to the application of stringent quality control. However, The extra data that are used give rise to modified increments (largest for temperature and humidity) at and above the diagnosed cloud top. Also it improves the analysis fit to independent radiosonde observations and results in some small, but statistically significant, improvements in forecast quality.
NASA Astrophysics Data System (ADS)
Lu, Daren; Huo, Juan; Zhang, W.; Liu, J.
A series of satellite sensors in visible and infrared wavelengths have been successfully operated on board a number of research satellites, e.g. NOAA/AVHRR, the MODIS onboard Terra and Aqua, etc. A number of cloud and aerosol products are produced and released in recent years. However, the validation of the product quality and accuracy are still a challenge to the atmospheric remote sensing community. In this paper, we suggest a ground based validation scheme for satellite-derived cloud and aerosol products by using combined visible and thermal infrared all sky imaging observations as well as surface meteorological observations. In the scheme, a visible digital camera with a fish-eye lens is used to continuously monitor the all sky with the view angle greater than 180 deg. The digital camera system is calibrated for both its geometry and radiance (broad blue, green, and red band) so as to a retrieval method can be used to detect the clear and cloudy sky spatial distribution and their temporal variations. A calibrated scanning thermal infrared thermometer is used to monitor the all sky brightness temperature distribution. An algorithm is developed to detect the clear and cloudy sky as well as cloud base height by using sky brightness distribution and surface temperature and humidity as input. Based on these composite retrieval of clear and cloudy sky distribution, it can be used to validate the satellite retrievals in the sense of real-simultaneous comparison and statistics, respectively. What will be presented in this talk include the results of the field observations and comparisons completed in Beijing (40 deg N, 116.5 deg E) in year 2003 and 2004. This work is supported by NSFC grant No. 4002700, and MOST grant No 2001CCA02200
Integration of hybrid wireless networks in cloud services oriented enterprise information systems
NASA Astrophysics Data System (ADS)
Li, Shancang; Xu, Lida; Wang, Xinheng; Wang, Jue
2012-05-01
This article presents a hybrid wireless network integration scheme in cloud services-based enterprise information systems (EISs). With the emerging hybrid wireless networks and cloud computing technologies, it is necessary to develop a scheme that can seamlessly integrate these new technologies into existing EISs. By combining the hybrid wireless networks and computing in EIS, a new framework is proposed, which includes frontend layer, middle layer and backend layers connected to IP EISs. Based on a collaborative architecture, cloud services management framework and process diagram are presented. As a key feature, the proposed approach integrates access control functionalities within the hybrid framework that provide users with filtered views on available cloud services based on cloud service access requirements and user security credentials. In future work, we will implement the proposed framework over SwanMesh platform by integrating the UPnP standard into an enterprise information system.
Li, Rui; Dong, Xue; Guo, Jingchao; Fu, Yunfei; Zhao, Chun; Wang, Yu; Min, Qilong
2017-10-23
Mineral dust is the most important natural source of atmospheric ice nuclei (IN) which may significantly mediate the properties of ice cloud through heterogeneous nucleation and lead to crucial impacts on hydrological and energy cycle. The potential dust IN effect on cloud top temperature (CTT) in a well-developed mesoscale convective system (MCS) was studied using both satellite observations and cloud resolving model (CRM) simulations. We combined satellite observations from passive spectrometer, active cloud radar, lidar, and wind field simulations from CRM to identify the place where ice cloud mixed with dust particles. For given ice water path, the CTT of dust-mixed cloud is warmer than that in relatively pristine cloud. The probability distribution function (PDF) of CTT for dust-mixed clouds shifted to the warmer end and showed two peaks at about -45 °C and -25 °C. The PDF for relatively pristine cloud only show one peak at -55 °C. Cloud simulations with different microphysical schemes agreed well with each other and showed better agreement with satellite observations in pristine clouds, but they showed large discrepancies in dust-mixed clouds. Some microphysical schemes failed to predict the warm peak of CTT related to heterogeneous ice formation.
Uncertainty in aerosol hygroscopicity resulting from semi-volatile organic compounds
NASA Astrophysics Data System (ADS)
Goulden, Olivia; Crooks, Matthew; Connolly, Paul
2018-01-01
We present a novel method of exploring the effect of uncertainties in aerosol properties on cloud droplet number using existing cloud droplet activation parameterisations. Aerosol properties of a single involatile particle mode are randomly sampled within an uncertainty range and resulting maximum supersaturations and critical diameters calculated using the cloud droplet activation scheme. Hygroscopicity parameters are subsequently derived and the values of the mean and uncertainty are found to be comparable to experimental observations. A recently proposed cloud droplet activation scheme that includes the effects of co-condensation of semi-volatile organic compounds (SVOCs) onto a single lognormal mode of involatile particles is also considered. In addition to the uncertainties associated with the involatile particles, concentrations, volatility distributions and chemical composition of the SVOCs are randomly sampled and hygroscopicity parameters are derived using the cloud droplet activation scheme. The inclusion of SVOCs is found to have a significant effect on the hygroscopicity and contributes a large uncertainty. For non-volatile particles that are effective cloud condensation nuclei, the co-condensation of SVOCs reduces their actual hygroscopicity by approximately 25 %. A new concept of an effective hygroscopicity parameter is introduced that can computationally efficiently simulate the effect of SVOCs on cloud droplet number concentration without direct modelling of the organic compounds. These effective hygroscopicities can be as much as a factor of 2 higher than those of the non-volatile particles onto which the volatile organic compounds condense.
CALIPSO Observations of Near-Cloud Aerosol Properties as a Function of Cloud Fraction
NASA Technical Reports Server (NTRS)
Yang, Weidong; Marshak, Alexander; Varnai, Tamas; Wood, Robert
2015-01-01
This paper uses spaceborne lidar data to study how near-cloud aerosol statistics of attenuated backscatter depend on cloud fraction. The results for a large region around the Azores show that: (1) far-from-cloud aerosol statistics are dominated by samples from scenes with lower cloud fractions, while near-cloud aerosol statistics are dominated by samples from scenes with higher cloud fractions; (2) near-cloud enhancements of attenuated backscatter occur for any cloud fraction but are most pronounced for higher cloud fractions; (3) the difference in the enhancements for different cloud fractions is most significant within 5km from clouds; (4) near-cloud enhancements can be well approximated by logarithmic functions of cloud fraction and distance to clouds. These findings demonstrate that if variability in cloud fraction across the scenes used to composite aerosol statistics are not considered, a sampling artifact will affect these statistics calculated as a function of distance to clouds. For the Azores-region dataset examined here, this artifact occurs mostly within 5 km from clouds, and exaggerates the near-cloud enhancements of lidar backscatter and color ratio by about 30. This shows that for accurate characterization of the changes in aerosol properties with distance to clouds, it is important to account for the impact of changes in cloud fraction.
Trusted measurement model based on multitenant behaviors.
Ning, Zhen-Hu; Shen, Chang-Xiang; Zhao, Yong; Liang, Peng
2014-01-01
With a fast growing pervasive computing, especially cloud computing, the behaviour measurement is at the core and plays a vital role. A new behaviour measurement tailored for Multitenants in cloud computing is needed urgently to fundamentally establish trust relationship. Based on our previous research, we propose an improved trust relationship scheme which captures the world of cloud computing where multitenants share the same physical computing platform. Here, we first present the related work on multitenant behaviour; secondly, we give the scheme of behaviour measurement where decoupling of multitenants is taken into account; thirdly, we explicitly explain our decoupling algorithm for multitenants; fourthly, we introduce a new way of similarity calculation for deviation control, which fits the coupled multitenants under study well; lastly, we design the experiments to test our scheme.
Trusted Measurement Model Based on Multitenant Behaviors
Ning, Zhen-Hu; Shen, Chang-Xiang; Zhao, Yong; Liang, Peng
2014-01-01
With a fast growing pervasive computing, especially cloud computing, the behaviour measurement is at the core and plays a vital role. A new behaviour measurement tailored for Multitenants in cloud computing is needed urgently to fundamentally establish trust relationship. Based on our previous research, we propose an improved trust relationship scheme which captures the world of cloud computing where multitenants share the same physical computing platform. Here, we first present the related work on multitenant behaviour; secondly, we give the scheme of behaviour measurement where decoupling of multitenants is taken into account; thirdly, we explicitly explain our decoupling algorithm for multitenants; fourthly, we introduce a new way of similarity calculation for deviation control, which fits the coupled multitenants under study well; lastly, we design the experiments to test our scheme. PMID:24987731
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berg, Larry K.; Gustafson, William I.; Kassianov, Evgueni I.
A new treatment for shallow clouds has been introduced into the Weather Research and Forecasting (WRF) model. The new scheme, called the cumulus potential (CuP) scheme, replaces the ad-hoc trigger function used in the Kain-Fritsch cumulus parameterization with a trigger function related to the distribution of temperature and humidity in the convective boundary layer via probability density functions (PDFs). An additional modification to the default version of WRF is the computation of a cumulus cloud fraction based on the time scales relevant for shallow cumuli. Results from three case studies over the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM)more » site in north central Oklahoma are presented. These days were selected because of the presence of shallow cumuli over the ARM site. The modified version of WRF does a much better job predicting the cloud fraction and the downwelling shortwave irradiance thancontrol simulations utilizing the default Kain-Fritsch scheme. The modified scheme includes a number of additional free parameters, including the number and size of bins used to define the PDF, the minimum frequency of a bin within the PDF before that bin is considered for shallow clouds to form, and the critical cumulative frequency of bins required to trigger deep convection. A series of tests were undertaken to evaluate the sensitivity of the simulations to these parameters. Overall, the scheme was found to be relatively insensitive to each of the parameters.« less
A Secure and Verifiable Outsourced Access Control Scheme in Fog-Cloud Computing
Fan, Kai; Wang, Junxiong; Wang, Xin; Li, Hui; Yang, Yintang
2017-01-01
With the rapid development of big data and Internet of things (IOT), the number of networking devices and data volume are increasing dramatically. Fog computing, which extends cloud computing to the edge of the network can effectively solve the bottleneck problems of data transmission and data storage. However, security and privacy challenges are also arising in the fog-cloud computing environment. Ciphertext-policy attribute-based encryption (CP-ABE) can be adopted to realize data access control in fog-cloud computing systems. In this paper, we propose a verifiable outsourced multi-authority access control scheme, named VO-MAACS. In our construction, most encryption and decryption computations are outsourced to fog devices and the computation results can be verified by using our verification method. Meanwhile, to address the revocation issue, we design an efficient user and attribute revocation method for it. Finally, analysis and simulation results show that our scheme is both secure and highly efficient. PMID:28737733
Lagrangian condensation microphysics with Twomey CCN activation
NASA Astrophysics Data System (ADS)
Grabowski, Wojciech W.; Dziekan, Piotr; Pawlowska, Hanna
2018-01-01
We report the development of a novel Lagrangian microphysics methodology for simulations of warm ice-free clouds. The approach applies the traditional Eulerian method for the momentum and continuous thermodynamic fields such as the temperature and water vapor mixing ratio, and uses Lagrangian super-droplets
to represent condensed phase such as cloud droplets and drizzle or rain drops. In other applications of the Lagrangian warm-rain microphysics, the super-droplets outside clouds represent unactivated cloud condensation nuclei (CCN) that become activated upon entering a cloud and can further grow through diffusional and collisional processes. The original methodology allows for the detailed study of not only effects of CCN on cloud microphysics and dynamics, but also CCN processing by a cloud. However, when cloud processing is not of interest, a simpler and computationally more efficient approach can be used with super-droplets forming only when CCN is activated and no super-droplet existing outside a cloud. This is possible by applying the Twomey activation scheme where the local supersaturation dictates the concentration of cloud droplets that need to be present inside a cloudy volume, as typically used in Eulerian bin microphysics schemes. Since a cloud volume is a small fraction of the computational domain volume, the Twomey super-droplets provide significant computational advantage when compared to the original super-droplet methodology. Additional advantage comes from significantly longer time steps that can be used when modeling of CCN deliquescence is avoided. Moreover, other formulation of the droplet activation can be applied in case of low vertical resolution of the host model, for instance, linking the concentration of activated cloud droplets to the local updraft speed. This paper discusses the development and testing of the Twomey super-droplet methodology, focusing on the activation and diffusional growth. Details of the activation implementation, transport of super-droplets in the physical space, and the coupling between super-droplets and the Eulerian temperature and water vapor field are discussed in detail. Some of these are relevant to the original super-droplet methodology as well and to the ice phase modeling using the Lagrangian approach. As a computational example, the scheme is applied to an idealized moist thermal rising in a stratified environment, with the original super-droplet methodology providing a benchmark to which the new scheme is compared.
NASA Technical Reports Server (NTRS)
Ovchinnikov, Mikhail; Ackerman, Andrew S.; Avramov, Alexander; Cheng, Anning; Fan, Jiwen; Fridlind, Ann M.; Ghan, Steven; Harrington, Jerry; Hoose, Corinna; Korolev, Alexei;
2014-01-01
Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP), in agreement with earlier studies. In contrast to previous intercomparison studies, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSDs) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case. Sensitivity tests indicate LWP and IWP are much closer to the bin model simulations when a modified shape factor which is similar to that predicted by bin model simulation is used in bulk scheme. These results demonstrate the importance of representation of ice PSD in determining the partitioning of liquid and ice and the longevity of mixed-phase clouds.
The Impact of Microphysics on Intensity and Structure of Hurricanes and Mesoscale Convective Systems
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Shi, Jainn J.; Jou, Ben Jong-Dao; Lee, Wen-Chau; Lin, Pay-Liam; Chang, Mei-Yu
2007-01-01
During the past decade, both research and operational numerical weather prediction models, e.g. Weather Research and Forecast (WRF) model, have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. WRF is a next-generation mesoscale forecast model and assimilation system that has incorporated modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options such as Purdue Lin et al. (1983), WSM 6-class and Thompson microphysics schemes. We have recently implemented three sophisticated cloud microphysics schemes into WRF. The cloud microphysics schemes have been extensively tested and applied for different mesoscale systems in different geographical locations. The performances of these schemes have been compared to those from other WRF microphysics options. We are performing sensitivity tests in using WRF to examine the impact of six different cloud microphysical schemes on precipitation processes associated hurricanes and mesoscale convective systems developed at different geographic locations [Oklahoma (IHOP), Louisiana (Hurricane Katrina), Canada (C3VP - snow events), Washington (fire storm), India (Monsoon), Taiwan (TiMREX - terrain)]. We will determine the microphysical schemes for good simulated convective systems in these geographic locations. We are also performing the inline tracer calculation to comprehend the physical processes (i.e., boundary layer and each quadrant in the boundary layer) related to the development and structure of hurricanes and mesoscale convective systems.
NASA Technical Reports Server (NTRS)
Johnson, Daniel E.; Tao, W.-K.; Simpson, J.; Sui, C.-H.; Einaudi, Franco (Technical Monitor)
2001-01-01
Interactions between deep tropical clouds over the western Pacific warm pool and the larger-scale environment are key to understanding climate change. Cloud models are an extremely useful tool in simulating and providing statistical information on heat and moisture transfer processes between cloud systems and the environment, and can therefore be utilized to substantially improve cloud parameterizations in climate models. In this paper, the Goddard Cumulus Ensemble (GCE) cloud-resolving model is used in multi-day simulations of deep tropical convective activity over the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Large-scale temperature and moisture advective tendencies, and horizontal momentum from the TOGA-COARE Intensive Flux Array (IFA) region, are applied to the GCE version which incorporates cyclical boundary conditions. Sensitivity experiments show that grid domain size produces the largest response to domain-mean temperature and moisture deviations, as well as cloudiness, when compared to grid horizontal or vertical resolution, and advection scheme. It is found that a minimum grid-domain size of 500 km is needed to adequately resolve the convective cloud features. The control experiment shows that the atmospheric heating and moistening is primarily a response to cloud latent processes of condensation/evaporation, and deposition/sublimation, and to a lesser extent, melting of ice particles. Air-sea exchange of heat and moisture is found to be significant, but of secondary importance, while the radiational response is small. The simulated rainfall and atmospheric heating and moistening, agrees well with observations, and performs favorably to other models simulating this case.
NASA Technical Reports Server (NTRS)
Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert
2011-01-01
We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.
NASA Astrophysics Data System (ADS)
Johnson, E. S.; Rupper, S.; Steenburgh, W. J.; Strong, C.; Kochanski, A.
2017-12-01
Climate model outputs are often used as inputs to glacier energy and mass balance models, which are essential glaciological tools for testing glacier sensitivity, providing mass balance estimates in regions with little glaciological data, and providing a means to model future changes. Climate model outputs, however, are sensitive to the choice of physical parameterizations, such as those for cloud microphysics, land-surface schemes, surface layer options, etc. Furthermore, glacier mass balance (MB) estimates that use these climate model outputs as inputs are likely sensitive to the specific parameterization schemes, but this sensitivity has not been carefully assessed. Here we evaluate the sensitivity of glacier MB estimates across the Indus Basin to the selection of cloud microphysics parameterizations in the Weather Research and Forecasting Model (WRF). Cloud microphysics parameterizations differ in how they specify the size distributions of hydrometeors, the rate of graupel and snow production, their fall speed assumptions, the rates at which they convert from one hydrometeor type to the other, etc. While glacier MB estimates are likely sensitive to other parameterizations in WRF, our preliminary results suggest that glacier MB is highly sensitive to the timing, frequency, and amount of snowfall, which is influenced by the cloud microphysics parameterization. To this end, the Indus Basin is an ideal study site, as it has both westerly (winter) and monsoonal (summer) precipitation influences, is a data-sparse region (so models are critical), and still has lingering questions as to glacier importance for local and regional resources. WRF is run at a 4 km grid scale using two commonly used parameterizations: the Thompson scheme and the Goddard scheme. On average, these parameterizations result in minimal differences in annual precipitation. However, localized regions exhibit differences in precipitation of up to 3 m w.e. a-1. The different schemes also impact the radiative budgets over the glacierized areas. Our results show that glacier MB estimates can differ by up to 45% depending on the chosen cloud microphysics scheme. These findings highlight the need to better account for uncertainties in meteorological inputs into glacier energy and mass balance models.
NASA Astrophysics Data System (ADS)
Dipu, Sudhakar; Quaas, Johannes; Wolke, Ralf; Stoll, Jens; Mühlbauer, Andreas; Sourdeval, Odran; Salzmann, Marc; Heinold, Bernd; Tegen, Ina
2017-06-01
The regional atmospheric model Consortium for Small-scale Modeling (COSMO) coupled to the Multi-Scale Chemistry Aerosol Transport model (MUSCAT) is extended in this work to represent aerosol-cloud interactions. Previously, only one-way interactions (scavenging of aerosol and in-cloud chemistry) and aerosol-radiation interactions were included in this model. The new version allows for a microphysical aerosol effect on clouds. For this, we use the optional two-moment cloud microphysical scheme in COSMO and the online-computed aerosol information for cloud condensation nuclei concentrations (Cccn), replacing the constant Cccn profile. In the radiation scheme, we have implemented a droplet-size-dependent cloud optical depth, allowing now for aerosol-cloud-radiation interactions. To evaluate the models with satellite data, the Cloud Feedback Model Intercomparison Project Observation Simulator Package (COSP) has been implemented. A case study has been carried out to understand the effects of the modifications, where the modified modeling system is applied over the European domain with a horizontal resolution of 0.25° × 0.25°. To reduce the complexity in aerosol-cloud interactions, only warm-phase clouds are considered. We found that the online-coupled aerosol introduces significant changes for some cloud microphysical properties. The cloud effective radius shows an increase of 9.5 %, and the cloud droplet number concentration is reduced by 21.5 %.
Bae, Soo Ya; Hong, Song -You; Lim, Kyo-Sun Sunny
2016-01-01
A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics and radiation processes. At each model time step, the calculated effective radii of hydrometeors from the WDM6 scheme are linked to the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme to consider the cloud effects in radiative flux calculation. This coupling effect of cloud properties between the WDM6 and RRTMG algorithms is examined for a heavy rainfall event in Korea during 25–27 July 2011, and itmore » is compared to the results from the control simulation in which the effective radius is prescribed as a constant value. It is found that the derived radii of hydrometeors in the WDM6 scheme are generally larger than the prescribed values in the RRTMG scheme. Consequently, shortwave fluxes reaching the ground (SWDOWN) are increased over less cloudy regions, showing a better agreement with a satellite image. The overall distribution of the 24-hour accumulated rainfall is not affected but its amount is changed. In conclusion, a spurious rainfall peak over the Yellow Sea is alleviated, whereas the local maximum in the central part of the peninsula is increased.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bae, Soo Ya; Hong, Song -You; Lim, Kyo-Sun Sunny
A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics and radiation processes. At each model time step, the calculated effective radii of hydrometeors from the WDM6 scheme are linked to the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme to consider the cloud effects in radiative flux calculation. This coupling effect of cloud properties between the WDM6 and RRTMG algorithms is examined for a heavy rainfall event in Korea during 25–27 July 2011, and itmore » is compared to the results from the control simulation in which the effective radius is prescribed as a constant value. It is found that the derived radii of hydrometeors in the WDM6 scheme are generally larger than the prescribed values in the RRTMG scheme. Consequently, shortwave fluxes reaching the ground (SWDOWN) are increased over less cloudy regions, showing a better agreement with a satellite image. The overall distribution of the 24-hour accumulated rainfall is not affected but its amount is changed. In conclusion, a spurious rainfall peak over the Yellow Sea is alleviated, whereas the local maximum in the central part of the peninsula is increased.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bae, Soo Ya; Hong, Song-You; Lim, Kyo-Sun Sunny
A method to explicitly calculate the effective radius of hydrometeors in the Weather Research Forecasting (WRF) double-moment 6-class (WDM6) microphysics scheme is designed to tackle the physical inconsistency in cloud properties between the microphysics and radiation processes. At each model time step, the calculated effective radii of hydrometeors from the WDM6 scheme are linked to the Rapid Radiative Transfer Model for GCMs (RRTMG) scheme to consider the cloud effects in radiative flux calculation. This coupling effect of cloud properties between the WDM6 and RRTMG algorithms is examined for a heavy rainfall event in Korea during 25–27 July 2011, and itmore » is compared to the results from the control simulation in which the effective radius is prescribed as a constant value. It is found that the derived radii of hydrometeors in the WDM6 scheme are generally larger than the prescribed values in the RRTMG scheme. Consequently, shortwave fluxes reaching the ground (SWDOWN) are increased over less cloudy regions, showing a better agreement with a satellite image. The overall distribution of the 24-hour accumulated rainfall is not affected but its amount is changed. A spurious rainfall peak over the Yellow Sea is alleviated, whereas the local maximum in the central part of the peninsula is increased.« less
A detailed investigation of proposed gas-phase syntheses of ammonia in dense interstellar clouds
NASA Technical Reports Server (NTRS)
Herbst, Eric; Defrees, D. J.; Mclean, A. D.
1987-01-01
The initial reactions of the Herbst and Klemperer (1973) and the Dalgarno (1974) schemes (I and II, respectively) for the gas-phase synthesis of ammonia in dense interstellar clouds were investigated. The rate of the slightly endothermic reaction between N(+) and H2 to yield NH(+) and H (scheme I) under interstellar conditions was reinvestigated under thermal and nonthermal conditions based on laboratory data. It was found that the relative importance of this reaction in synthesizing ammonia is determined by how the laboratory data at low temperature are interpreted. On the other hand, the exothermic reaction between N and H3(+) to form NH2(+) + H (scheme II) was calculated to possess significant activation energy and, therefore, to have a negligible rate coefficient under interstellar conditions. Consequently, this reaction cannot take place appreciably in interstellar clouds.
Knowledge Reasoning with Semantic Data for Real-Time Data Processing in Smart Factory
Wang, Shiyong; Li, Di; Liu, Chengliang
2018-01-01
The application of high-bandwidth networks and cloud computing in manufacturing systems will be followed by mass data. Industrial data analysis plays important roles in condition monitoring, performance optimization, flexibility, and transparency of the manufacturing system. However, the currently existing architectures are mainly for offline data analysis, not suitable for real-time data processing. In this paper, we first define the smart factory as a cloud-assisted and self-organized manufacturing system in which physical entities such as machines, conveyors, and products organize production through intelligent negotiation and the cloud supervises this self-organized process for fault detection and troubleshooting based on data analysis. Then, we propose a scheme to integrate knowledge reasoning and semantic data where the reasoning engine processes the ontology model with real time semantic data coming from the production process. Based on these ideas, we build a benchmarking system for smart candy packing application that supports direct consumer customization and flexible hybrid production, and the data are collected and processed in real time for fault diagnosis and statistical analysis. PMID:29415444
Applying the WRF Double-Moment Six-Class Microphysics Scheme in the GRAPES_Meso Model: A Case Study
NASA Astrophysics Data System (ADS)
Zhang, Meng; Wang, Hong; Zhang, Xiaoye; Peng, Yue; Che, Huizheng
2018-04-01
This study incorporated the Weather Research and Forecasting (WRF) model double-moment 6-class (WDM6) microphysics scheme into the mesoscale version of the Global/Regional Assimilation and PrEdiction System (GRAPES_Meso). A rainfall event that occurred during 3-5 June 2015 around Beijing was simulated by using the WDM6, the WRF single-moment 6-class scheme (WSM6), and the NCEP 5-class scheme, respectively. The results show that both the distribution and magnitude of the rainfall simulated with WDM6 were more consistent with the observation. Compared with WDM6, WSM6 simulated larger cloud liquid water content, which provided more water vapor for graupel growth, leading to increased precipitation in the cold-rain processes. For areas with the warmrain processes, the sensitivity experiments using WDM6 showed that an increase in cloud condensation nuclei (CCN) number concentration led to enhanced CCN activation ratio and larger cloud droplet number concentration ( N c) but decreased cloud droplet effective diameter. The formation of more small-size cloud droplets resulted in a decrease in raindrop number concentration ( N r), inhibiting the warm-rain processes, thus gradually decreasing the amount of precipitation. For areas mainly with the cold-rain processes, the overall amount of precipitation increased; however, it gradually decreased when the CCN number concentration reached a certain magnitude. Hence, the effect of CCN number concentration on precipitation exhibits significant differences in different rainfall areas of the same precipitation event.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ovchinnikov, Mikhail; Ackerman, Andrew; Avramov, Alex
Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP) and potential cloud dissipation, in agreement with earlier studies. By comparing simulations with the same microphysics coupled to different dynamical cores as well as the same dynamics coupled to differentmore » microphysics schemes, it is found that the ice water path (IWP) is mainly controlled by ice microphysics, while the inter-model differences in LWP are largely driven by physics and numerics of the dynamical cores. In contrast to previous intercomparisons, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSD) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case.« less
The 20-22 January 2007 Snow Events over Canada: Microphysical Properties
NASA Technical Reports Server (NTRS)
Tao. W.K.; Shi, J.J.; Matsui, T.; Hao, A.; Lang, S.; Peters-Lidard, C.; Skofronick-Jackson, G.; Petersen, W.; Cifelli, R.; Rutledge, S.
2009-01-01
One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve precipitation measurements in mid- and high-latitudes during cold seasons through the use of high-frequency passive microwave radiometry. Toward this end, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for snowstorm events (January 20-22, 2007) that took place over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) ground site (Centre for Atmospheric Research Experiments - CARE) in Ontario, Canada. In this paper, the performance of the Goddard cloud microphysics scheme both with 2ice (ice and snow) and 3ice (ice, snow and graupel) as well as other WRF microphysics schemes will be presented. The results are compared with data from the Environment Canada (EC) King Radar, an operational C-band radar located near the CARE site. In addition, the WRF model output is used to drive the Goddard SDSU to calculate radiances and backscattering signals consistent with direct satellite observations for evaluating the model results.
NASA Astrophysics Data System (ADS)
Schneider, Tapio; Lan, Shiwei; Stuart, Andrew; Teixeira, João.
2017-12-01
Climate projections continue to be marred by large uncertainties, which originate in processes that need to be parameterized, such as clouds, convection, and ecosystems. But rapid progress is now within reach. New computational tools and methods from data assimilation and machine learning make it possible to integrate global observations and local high-resolution simulations in an Earth system model (ESM) that systematically learns from both and quantifies uncertainties. Here we propose a blueprint for such an ESM. We outline how parameterization schemes can learn from global observations and targeted high-resolution simulations, for example, of clouds and convection, through matching low-order statistics between ESMs, observations, and high-resolution simulations. We illustrate learning algorithms for ESMs with a simple dynamical system that shares characteristics of the climate system; and we discuss the opportunities the proposed framework presents and the challenges that remain to realize it.
Bayesian cloud detection for MERIS, AATSR, and their combination
NASA Astrophysics Data System (ADS)
Hollstein, A.; Fischer, J.; Carbajal Henken, C.; Preusker, R.
2014-11-01
A broad range of different of Bayesian cloud detection schemes is applied to measurements from the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The cloud masks were designed to be numerically efficient and suited for the processing of large amounts of data. Results from the classical and naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as well as for their combination. A sensitivity study on the resolution of multidimensional histograms, which were post-processed by Gaussian smoothing, shows how theoretically insufficient amounts of truth data can be used to set up accurate classical Bayesian cloud masks. Sets of exploited features from single and derived channels are numerically optimized and results for naive and classical Bayesian cloud masks are presented. The application of the Bayesian approach is discussed in terms of reproducing existing algorithms, enhancing existing algorithms, increasing the robustness of existing algorithms, and on setting up new classification schemes based on manually classified scenes.
The GRAPE aerosol retrieval algorithm
NASA Astrophysics Data System (ADS)
Thomas, G. E.; Poulsen, C. A.; Sayer, A. M.; Marsh, S. H.; Dean, S. M.; Carboni, E.; Siddans, R.; Grainger, R. G.; Lawrence, B. N.
2009-11-01
The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations - this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.
The GRAPE aerosol retrieval algorithm
NASA Astrophysics Data System (ADS)
Thomas, G. E.; Poulsen, C. A.; Sayer, A. M.; Marsh, S. H.; Dean, S. M.; Carboni, E.; Siddans, R.; Grainger, R. G.; Lawrence, B. N.
2009-04-01
The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations - this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.
Cloud cover determination in polar regions from satellite imagery
NASA Technical Reports Server (NTRS)
Barry, R. G.; Maslanik, J. A.; Key, J. R.
1987-01-01
A definition is undertaken of the spectral and spatial characteristics of clouds and surface conditions in the polar regions, and to the creation of calibrated, geometrically correct data sets suitable for quantitative analysis. Ways are explored in which this information can be applied to cloud classifications as new methods or as extensions to existing classification schemes. A methodology is developed that uses automated techniques to merge Advanced Very High Resolution Radiometer (AVHRR) and Scanning Multichannel Microwave Radiometer (SMMR) data, and to apply first-order calibration and zenith angle corrections to the AVHRR imagery. Cloud cover and surface types are manually interpreted, and manual methods are used to define relatively pure training areas to describe the textural and multispectral characteristics of clouds over several surface conditions. The effects of viewing angle and bidirectional reflectance differences are studied for several classes, and the effectiveness of some key components of existing classification schemes is tested.
Centralized Duplicate Removal Video Storage System with Privacy Preservation in IoT.
Yan, Hongyang; Li, Xuan; Wang, Yu; Jia, Chunfu
2018-06-04
In recent years, the Internet of Things (IoT) has found wide application and attracted much attention. Since most of the end-terminals in IoT have limited capabilities for storage and computing, it has become a trend to outsource the data from local to cloud computing. To further reduce the communication bandwidth and storage space, data deduplication has been widely adopted to eliminate the redundant data. However, since data collected in IoT are sensitive and closely related to users' personal information, the privacy protection of users' information becomes a challenge. As the channels, like the wireless channels between the terminals and the cloud servers in IoT, are public and the cloud servers are not fully trusted, data have to be encrypted before being uploaded to the cloud. However, encryption makes the performance of deduplication by the cloud server difficult because the ciphertext will be different even if the underlying plaintext is identical. In this paper, we build a centralized privacy-preserving duplicate removal storage system, which supports both file-level and block-level deduplication. In order to avoid the leakage of statistical information of data, Intel Software Guard Extensions (SGX) technology is utilized to protect the deduplication process on the cloud server. The results of the experimental analysis demonstrate that the new scheme can significantly improve the deduplication efficiency and enhance the security. It is envisioned that the duplicated removal system with privacy preservation will be of great use in the centralized storage environment of IoT.
DOE Office of Scientific and Technical Information (OSTI.GOV)
McFarquhar, Greg
We proposed to analyze in-situ cloud data collected during ARM/ASR field campaigns to create databases of cloud microphysical properties and their uncertainties as needed for the development of improved cloud parameterizations for models and remote sensing retrievals, and for evaluation of model simulations and retrievals. In particular, we proposed to analyze data collected over the Southern Great Plains (SGP) during the Mid-latitude Continental Convective Clouds Experiment (MC3E), the Storm Peak Laboratory Cloud Property Validation Experiment (STORMVEX), the Small Particles in Cirrus (SPARTICUS) Experiment and the Routine AAF Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign,more » over the North Slope of Alaska during the Indirect and Semi-Direct Aerosol Campaign (ISDAC) and the Mixed-Phase Arctic Cloud Experiment (M-PACE), and over the Tropical Western Pacific (TWP) during The Tropical Warm Pool International Cloud Experiment (TWP-ICE), to meet the following 3 objectives; derive statistical databases of single ice particle properties (aspect ratio AR, dominant habit, mass, projected area) and distributions of ice crystals (size distributions SDs, mass-dimension m-D, area-dimension A-D relations, mass-weighted fall speeds, single-scattering properties, total concentrations N, ice mass contents IWC), complete with uncertainty estimates; assess processes by which aerosols modulate cloud properties in arctic stratus and mid-latitude cumuli, and quantify aerosol’s influence in context of varying meteorological and surface conditions; and determine how ice cloud microphysical, single-scattering and fall-out properties and contributions of small ice crystals to such properties vary according to location, environment, surface, meteorological and aerosol conditions, and develop parameterizations of such effects.In this report we describe the accomplishments that we made on all 3 research objectives.« less
NASA Astrophysics Data System (ADS)
Lamraoui, F.; Booth, J. F.; Naud, C. M.
2017-12-01
The representation of subgrid-scale processes of low-level marine clouds located in the post-cold-frontal region poses a serious challenge for climate models. More precisely, the boundary layer parameterizations are predominantly designed for individual regimes that can evolve gradually over time and does not accommodate the cold front passage that can overly modify the boundary layer rapidly. Also, the microphysics schemes respond differently to the quick development of the boundary layer schemes, especially under unstable conditions. To improve the understanding of cloud physics in the post-cold frontal region, the present study focuses on exploring the relationship between cloud properties, the local processes and large-scale conditions. In order to address these questions, we explore the WRF sensitivity to the interaction between various combinations of the boundary layer and microphysics parameterizations, including the Community Atmospheric Model version 5 (CAM5) physical package in a perturbed physics ensemble. Then, we evaluate these simulations against ground-based ARM observations over the Azores. The WRF-based simulations demonstrate particular sensitivities of the marine cold front passage and the associated post-cold frontal clouds to the domain size, the resolution and the physical parameterizations. First, it is found that in multiple different case studies the model cannot generate the cold front passage when the domain size is larger than 3000 km2. Instead, the modeled cold front stalls, which shows the importance of properly capturing the synoptic scale conditions. The simulation reveals persistent delay in capturing the cold front passage and also an underestimated duration of the post-cold-frontal conditions. Analysis of the perturbed physics ensemble shows that changing the microphysics scheme leads to larger differences in the modeled clouds than changing the boundary layer scheme. The in-cloud heating tendencies are analyzed to explain this sensitivity.
NASA Technical Reports Server (NTRS)
Barahona, Donifan; Molod, Andrea M.; Bacmeister, Julio; Nenes, Athanasios; Gettelman, Andrew; Morrison, Hugh; Phillips, Vaughan,; Eichmann, Andrew F.
2013-01-01
This work presents the development of a two-moment cloud microphysics scheme within the version 5 of the NASA Goddard Earth Observing System (GEOS-5). The scheme includes the implementation of a comprehensive stratiform microphysics module, a new cloud coverage scheme that allows ice supersaturation and a new microphysics module embedded within the moist convection parameterization of GEOS-5. Comprehensive physically-based descriptions of ice nucleation, including homogeneous and heterogeneous freezing, and liquid droplet activation are implemented to describe the formation of cloud particles in stratiform clouds and convective cumulus. The effect of preexisting ice crystals on the formation of cirrus clouds is also accounted for. A new parameterization of the subgrid scale vertical velocity distribution accounting for turbulence and gravity wave motion is developed. The implementation of the new microphysics significantly improves the representation of liquid water and ice in GEOS-5. Evaluation of the model shows agreement of the simulated droplet and ice crystal effective and volumetric radius with satellite retrievals and in situ observations. The simulated global distribution of supersaturation is also in agreement with observations. It was found that when using the new microphysics the fraction of condensate that remains as liquid follows a sigmoidal increase with temperature which differs from the linear increase assumed in most models and is in better agreement with available observations. The performance of the new microphysics in reproducing the observed total cloud fraction, longwave and shortwave cloud forcing, and total precipitation is similar to the operational version of GEOS-5 and in agreement with satellite retrievals. However the new microphysics tends to underestimate the coverage of persistent low level stratocumulus. Sensitivity studies showed that the simulated cloud properties are robust to moderate variation in cloud microphysical parameters. However significant sensitivity in ice cloud properties was found to variation in the dispersion of the ice crystal size distribution and the critical size for ice autoconversion. The implementation of the new microphysics leads to a more realistic representation of cloud processes in GEOS-5 and allows the linkage of cloud properties to aerosol emissions.
Yu, Si; Gui, Xiaolin; Lin, Jiancai; Tian, Feng; Zhao, Jianqiang; Dai, Min
2014-01-01
Cloud computing gets increasing attention for its capacity to leverage developers from infrastructure management tasks. However, recent works reveal that side channel attacks can lead to privacy leakage in the cloud. Enhancing isolation between users is an effective solution to eliminate the attack. In this paper, to eliminate side channel attacks, we investigate the isolation enhancement scheme from the aspect of virtual machine (VM) management. The security-awareness VMs management scheme (SVMS), a VMs isolation enhancement scheme to defend against side channel attacks, is proposed. First, we use the aggressive conflict of interest relation (ACIR) and aggressive in ally with relation (AIAR) to describe user constraint relations. Second, based on the Chinese wall policy, we put forward four isolation rules. Third, the VMs placement and migration algorithms are designed to enforce VMs isolation between the conflict users. Finally, based on the normal distribution, we conduct a series of experiments to evaluate SVMS. The experimental results show that SVMS is efficient in guaranteeing isolation between VMs owned by conflict users, while the resource utilization rate decreases but not by much.
NASA Astrophysics Data System (ADS)
Shaposhnikov, Dmitry S.; Rodin, Alexander V.; Medvedev, Alexander S.; Fedorova, Anna A.; Kuroda, Takeshi; Hartogh, Paul
2018-02-01
We present a new implementation of the hydrological cycle scheme into a general circulation model of the Martian atmosphere. The model includes a semi-Lagrangian transport scheme for water vapor and ice and accounts for microphysics of phase transitions between them. The hydrological scheme includes processes of saturation, nucleation, particle growth, sublimation, and sedimentation under the assumption of a variable size distribution. The scheme has been implemented into the Max Planck Institute Martian general circulation model and tested assuming monomodal and bimodal lognormal distributions of ice condensation nuclei. We present a comparison of the simulated annual variations, horizontal and vertical distributions of water vapor, and ice clouds with the available observations from instruments on board Mars orbiters. The accounting for bimodality of aerosol particle distribution improves the simulations of the annual hydrological cycle, including predicted ice clouds mass, opacity, number density, and particle radii. The increased number density and lower nucleation rates bring the simulated cloud opacities closer to observations. Simulations show a weak effect of the excess of small aerosol particles on the simulated water vapor distributions.
Gui, Xiaolin; Lin, Jiancai; Tian, Feng; Zhao, Jianqiang; Dai, Min
2014-01-01
Cloud computing gets increasing attention for its capacity to leverage developers from infrastructure management tasks. However, recent works reveal that side channel attacks can lead to privacy leakage in the cloud. Enhancing isolation between users is an effective solution to eliminate the attack. In this paper, to eliminate side channel attacks, we investigate the isolation enhancement scheme from the aspect of virtual machine (VM) management. The security-awareness VMs management scheme (SVMS), a VMs isolation enhancement scheme to defend against side channel attacks, is proposed. First, we use the aggressive conflict of interest relation (ACIR) and aggressive in ally with relation (AIAR) to describe user constraint relations. Second, based on the Chinese wall policy, we put forward four isolation rules. Third, the VMs placement and migration algorithms are designed to enforce VMs isolation between the conflict users. Finally, based on the normal distribution, we conduct a series of experiments to evaluate SVMS. The experimental results show that SVMS is efficient in guaranteeing isolation between VMs owned by conflict users, while the resource utilization rate decreases but not by much. PMID:24688434
Direct Lagrangian tracking simulations of particles in vertically-developing atmospheric clouds
NASA Astrophysics Data System (ADS)
Onishi, Ryo; Kunishima, Yuichi
2017-11-01
We have been developing the Lagrangian Cloud Simulator (LCS), which follows the so-called Euler-Lagrangian framework, where flow motion and scalar transportations (i.e., temperature and humidity) are computed with the Euler method and particle motion with the Lagrangian method. The LCS simulation considers the hydrodynamic interaction between approaching particles for robust collision detection. This leads to reliable simulations of collision growth of cloud droplets. Recently the activation process, in which aerosol particles become tiny liquid droplets, has been implemented in the LCS. The present LCS can therefore consider the whole warm-rain precipitation processes -activation, condensation, collision and drop precipitation. In this talk, after briefly introducing the LCS, we will show kinematic simulations using the LCS for quasi-one dimensional domain, i.e., vertically elongated 3D domain. They are compared with one-dimensional kinematic simulations using a spectral-bin cloud microphysics scheme, which is based on the Euler method. The comparisons show fairly good agreement with small discrepancies, the source of which will be presented. The Lagrangian statistics, obtained for the first time for the vertical domain, will be the center of discussion. This research was supported by MEXT as ``Exploratory Challenge on Post-K computer'' (Frontiers of Basic Science: Challenging the Limits).
NASA Astrophysics Data System (ADS)
Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young
2016-07-01
Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.
Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young
2016-07-28
Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.
Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young
2016-01-01
Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes. PMID:27465296
A New Framework to Compare Mass-Flux Schemes Within the AROME Numerical Weather Prediction Model
NASA Astrophysics Data System (ADS)
Riette, Sébastien; Lac, Christine
2016-08-01
In the Application of Research to Operations at Mesoscale (AROME) numerical weather forecast model used in operations at Météo-France, five mass-flux schemes are available to parametrize shallow convection at kilometre resolution. All but one are based on the eddy-diffusivity-mass-flux approach, and differ in entrainment/detrainment, the updraft vertical velocity equation and the closure assumption. The fifth is based on a more classical mass-flux approach. Screen-level scores obtained with these schemes show few discrepancies and are not sufficient to highlight behaviour differences. Here, we describe and use a new experimental framework, able to compare and discriminate among different schemes. For a year, daily forecast experiments were conducted over small domains centred on the five French metropolitan radio-sounding locations. Cloud base, planetary boundary-layer height and normalized vertical profiles of specific humidity, potential temperature, wind speed and cloud condensate were compared with observations, and with each other. The framework allowed the behaviour of the different schemes in and above the boundary layer to be characterized. In particular, the impact of the entrainment/detrainment formulation, closure assumption and cloud scheme were clearly visible. Differences mainly concerned the transport intensity thus allowing schemes to be separated into two groups, with stronger or weaker updrafts. In the AROME model (with all interactions and the possible existence of compensating errors), evaluation diagnostics gave the advantage to the first group.
A Goddard Multi-Scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;
2008-01-01
Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. 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 Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article.
Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)
Guo, Zhun; Wang, Minghuai; Qian, Yun; ...
2015-07-03
In this study, we investigate the sensitivity of simulated low clouds to 14 selected tunable parameters of Cloud Layers Unified By Binormals (CLUBB), a higher order closure (HOC) scheme, and 4 parameters of the Zhang-McFarlane (ZM) deep convection scheme in the Community Atmosphere Model version 5 (CAM5). A quasi-Monte Carlo (QMC) sampling approach is adopted to effectively explore the high-dimensional parameter space and a generalized linear model is applied to study the responses of simulated cloud fields to tunable parameters. Our results show that the variance in simulated low-cloud properties (cloud fraction and liquid water path) can be explained bymore » the selected tunable parameters in two different ways: macrophysics itself and its interaction with microphysics. First, the parameters related to dynamic and thermodynamic turbulent structure and double Gaussians closure are found to be the most influential parameters for simulating low clouds. The spatial distributions of the parameter contributions show clear cloud-regime dependence. Second, because of the coupling between cloud macrophysics and cloud microphysics, the coefficient of the dissipation term in the total water variance equation is influential. This parameter affects the variance of in-cloud cloud water, which further influences microphysical process rates, such as autoconversion, and eventually low-cloud fraction. Furthermore, this study improves understanding of HOC behavior associated with parameter uncertainties and provides valuable insights for the interaction of macrophysics and microphysics.« less
NASA Astrophysics Data System (ADS)
Mielikainen, Jarno; Huang, Bormin; Huang, Allen
2015-10-01
The Thompson cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Thompson scheme incorporates a large number of improvements. Thus, we have optimized the speed of this important part of WRF. Intel Many Integrated Core (MIC) ushers in a new era of supercomputing speed, performance, and compatibility. It allows the developers to run code at trillions of calculations per second using the familiar programming model. In this paper, we present our results of optimizing the Thompson microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. New optimizations for an updated Thompson scheme are discusses in this paper. The optimizations improved the performance of the original Thompson code on Xeon Phi 7120P by a factor of 1.8x. Furthermore, the same optimizations improved the performance of the Thompson on a dual socket configuration of eight core Intel Xeon E5-2670 CPUs by a factor of 1.8x compared to the original Thompson code.
An examination of the effects of explicit cloud water in the UCLA GCM
NASA Technical Reports Server (NTRS)
Ose, Tomoaki
1993-01-01
The effect of explicit cloud water on the climate simulation by the University of California of Los Angeles GCM is investigated by adding the mixing ratios of cloud ice and cloud liquid water to the prognostic variables of the model. The detrained cloud ice and cloud liquid water are obtained by the microphysical calculation in the Arakawa-Schubert (1974) cumulus scheme. The results are compared with the observations concerned with cloudiness, planetary albedo, OLR, and the dependence of cloud water content on temperature.
NASA Technical Reports Server (NTRS)
Tao, W.-K.; Shi, J.; Chen, S. S>
2007-01-01
Advances in computing power allow atmospheric prediction models to be mn at progressively finer scales of resolution, using increasingly more sophisticated physical parameterizations and numerical methods. The representation of cloud microphysical processes is a key component of these models, over the past decade both research and operational numerical weather prediction models have started using more complex microphysical schemes that were originally developed for high-resolution cloud-resolving models (CRMs). A recent report to the United States Weather Research Program (USWRP) Science Steering Committee specifically calls for the replacement of implicit cumulus parameterization schemes with explicit bulk schemes in numerical weather prediction (NWP) as part of a community effort to improve quantitative precipitation forecasts (QPF). An improved Goddard bulk microphysical parameterization is implemented into a state-of the-art of next generation of Weather Research and Forecasting (WRF) model. High-resolution model simulations are conducted to examine the impact of microphysical schemes on two different weather events (a midlatitude linear convective system and an Atllan"ic hurricane). The results suggest that microphysics has a major impact on the organization and precipitation processes associated with a summer midlatitude convective line system. The 31CE scheme with a cloud ice-snow-hail configuration led to a better agreement with observation in terms of simulated narrow convective line and rainfall intensity. This is because the 3ICE-hail scheme includes dense ice precipitating (hail) particle with very fast fall speed (over 10 m/s). For an Atlantic hurricane case, varying the microphysical schemes had no significant impact on the track forecast but did affect the intensity (important for air-sea interaction)
NASA Astrophysics Data System (ADS)
Choudhury, Devanil; Das, Someshwar
2017-06-01
The Advanced Research WRF (ARW) model is used to simulate Very Severe Cyclonic Storms (VSCS) Hudhud (7-13 October, 2014), Phailin (8-14 October, 2013) and Lehar (24-29 November, 2013) to investigate the sensitivity to microphysical schemes on the skill of forecasting track and intensity of the tropical cyclones for high-resolution (9 and 3 km) 120-hr model integration. For cloud resolving grid scale (<5 km) cloud microphysics plays an important role. The performance of the Goddard, Thompson, LIN and NSSL schemes are evaluated and compared with observations and a CONTROL forecast. This study is aimed to investigate the sensitivity to microphysics on the track and intensity with explicitly resolved convection scheme. It shows that the Goddard one-moment bulk liquid-ice microphysical scheme provided the highest skill on the track whereas for intensity both Thompson and Goddard microphysical schemes perform better. The Thompson scheme indicates the highest skill in intensity at 48, 96 and 120 hr, whereas at 24 and 72 hr, the Goddard scheme provides the highest skill in intensity. It is known that higher resolution domain produces better intensity and structure of the cyclones and it is desirable to resolve the convection with sufficiently high resolution and with the use of explicit cloud physics. This study suggests that the Goddard cumulus ensemble microphysical scheme is suitable for high resolution ARW simulation for TC's track and intensity over the BoB. Although the present study is based on only three cyclones, it could be useful for planning real-time predictions using ARW modelling system.
Simulation of the West African Monsoon using the MIT Regional Climate Model
NASA Astrophysics Data System (ADS)
Im, Eun-Soon; Gianotti, Rebecca L.; Eltahir, Elfatih A. B.
2013-04-01
We test the performance of the MIT Regional Climate Model (MRCM) in simulating the West African Monsoon. MRCM introduces several improvements over Regional Climate Model version 3 (RegCM3) including coupling of Integrated Biosphere Simulator (IBIS) land surface scheme, a new albedo assignment method, a new convective cloud and rainfall auto-conversion scheme, and a modified boundary layer height and cloud scheme. Using MRCM, we carried out a series of experiments implementing two different land surface schemes (IBIS and BATS) and three convection schemes (Grell with the Fritsch-Chappell closure, standard Emanuel, and modified Emanuel that includes the new convective cloud scheme). Our analysis primarily focused on comparing the precipitation characteristics, surface energy balance and large scale circulations against various observations. We document a significant sensitivity of the West African monsoon simulation to the choices of the land surface and convection schemes. In spite of several deficiencies, the simulation with the combination of IBIS and modified Emanuel schemes shows the best performance reflected in a marked improvement of precipitation in terms of spatial distribution and monsoon features. In particular, the coupling of IBIS leads to representations of the surface energy balance and partitioning that are consistent with observations. Therefore, the major components of the surface energy budget (including radiation fluxes) in the IBIS simulations are in better agreement with observation than those from our BATS simulation, or from previous similar studies (e.g Steiner et al., 2009), both qualitatively and quantitatively. The IBIS simulations also reasonably reproduce the dynamical structure of vertically stratified behavior of the atmospheric circulation with three major components: westerly monsoon flow, African Easterly Jet (AEJ), and Tropical Easterly Jet (TEJ). In addition, since the modified Emanuel scheme tends to reduce the precipitation amount, it improves the precipitation over regions suffering from systematic wet bias.
OS2: Oblivious similarity based searching for encrypted data outsourced to an untrusted domain
Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem
2017-01-01
Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search (OS2) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, OS2 ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables OS2 to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of OS2 is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations. PMID:28692697
Pervez, Zeeshan; Ahmad, Mahmood; Khattak, Asad Masood; Ramzan, Naeem; Khan, Wajahat Ali
2017-01-01
Public cloud storage services are becoming prevalent and myriad data sharing, archiving and collaborative services have emerged which harness the pay-as-you-go business model of public cloud. To ensure privacy and confidentiality often encrypted data is outsourced to such services, which further complicates the process of accessing relevant data by using search queries. Search over encrypted data schemes solve this problem by exploiting cryptographic primitives and secure indexing to identify outsourced data that satisfy the search criteria. Almost all of these schemes rely on exact matching between the encrypted data and search criteria. A few schemes which extend the notion of exact matching to similarity based search, lack realism as those schemes rely on trusted third parties or due to increase storage and computational complexity. In this paper we propose Oblivious Similarity based Search ([Formula: see text]) for encrypted data. It enables authorized users to model their own encrypted search queries which are resilient to typographical errors. Unlike conventional methodologies, [Formula: see text] ranks the search results by using similarity measure offering a better search experience than exact matching. It utilizes encrypted bloom filter and probabilistic homomorphic encryption to enable authorized users to access relevant data without revealing results of search query evaluation process to the untrusted cloud service provider. Encrypted bloom filter based search enables [Formula: see text] to reduce search space to potentially relevant encrypted data avoiding unnecessary computation on public cloud. The efficacy of [Formula: see text] is evaluated on Google App Engine for various bloom filter lengths on different cloud configurations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fan, Jiwen; Han, Bin; Varble, Adam
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,more » 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.« less
NASA Astrophysics Data System (ADS)
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 droplet size and number concentration, but also the spectral width of the cloud droplet size distribution, the 3M scheme is well suited to simulate aerosol-cloud-precipitation interactions within a three-dimensional regional cloud model. Moreover, the additional variability predicted on the hydrometeor distributions provides beneficial input for forward models to link the simulated microphysical processes with observations as well as to assess both ground-based and satellite retrieval methods. In this presentation, we provide an overview of the 7 South East Asian Studies / Biomass-burning Aerosols and Stratocumulus Environment: Lifecycles and Interactions Experiment (7-SEAS/BASELInE) operations during the spring of 2013. Preliminary analyses of pre-monsoon Sc system lifecycles observed during the first-ever deployment of a ground-based cloud radar to northern Vietnam will be also be presented. Initial results from GCE model simulations of these Sc using double-moment and the new 3M bulk microphysics schemes under various aerosol loadings will be used to showcase the 3M scheme as well as provide insight into how the impact of aerosols on cloud and precipitation processes in stratocumulus over land may manifest themselves in simulated remote-sensing signals. Applications and future work involving ongoing 7-SEAS campaigns aimed at improving our understanding of aerosol-cloud-precipitation interactions of will also be discussed.
The sensitivities of in cloud and cloud top phase distributions to primary ice formation in ICON-LEM
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Tang, W.; Yang, K.; Sun, Z.; Qin, J.; Niu, X.
2016-12-01
A fast parameterization scheme named SUNFLUX is used in this study to estimate instantaneous surface solar radiation (SSR) based on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard both Terra and Aqua platforms. The scheme mainly takes into account the absorption and scattering processes due to clouds, aerosols and gas in the atmosphere. The estimated instantaneous SSR is evaluated against surface observations obtained from seven stations of the Surface Radiation Budget Network (SURFRAD), four stations in the North China Plain (NCP) and 40 stations of the Baseline Surface Radiation Network (BSRN). The statistical results for evaluation against these three datasets show that the relative root-mean-square error (RMSE) values of SUNFLUX are less than 15%, 16% and 17%, respectively. Daily SSR is derived through temporal upscaling from the MODIS-based instantaneous SSR estimates, and is validated against surface observations. The relative RMSE values for daily SSR estimates are about 16% at the seven SURFRAD stations, four NCP stations, 40 BSRN stations and 90 China Meteorological Administration (CMA) radiation stations.
Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Zhijin; Sha, Feng; Liu, Yangang
2016-02-02
This five-year award supports the project “Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements (FASTER)”. The goal of this project is to produce accurate, consistent and comprehensive data sets for initializing both single column models (SCMs) and cloud resolving models (CRMs) using data assimilation. A multi-scale three-dimensional variational data assimilation scheme (MS-3DVAR) has been implemented. This MS-3DVAR system is built on top of WRF/GSI. The Community Gridpoint Statistical Interpolation (GSI) system is an operational data assimilation system at the National Centers for Environmental Prediction (NCEP) and has been implemented in the Weather Research and Forecast (WRF) model.more » This MS-3DVAR is further enhanced by the incorporation of a land surface 3DVAR scheme and a comprehensive aerosol 3DVAR scheme. The data assimilation implementation focuses in the ARM SGP region. ARM measurements are assimilated along with other available satellite and radar data. Reanalyses are then generated for a few selected period of time. This comprehensive data assimilation system has also been employed for other ARM-related applications.« less
Emerging Security Mechanisms for Medical Cyber Physical Systems.
Kocabas, Ovunc; Soyata, Tolga; Aktas, Mehmet K
2016-01-01
The following decade will witness a surge in remote health-monitoring systems that are based on body-worn monitoring devices. These Medical Cyber Physical Systems (MCPS) will be capable of transmitting the acquired data to a private or public cloud for storage and processing. Machine learning algorithms running in the cloud and processing this data can provide decision support to healthcare professionals. There is no doubt that the security and privacy of the medical data is one of the most important concerns in designing an MCPS. In this paper, we depict the general architecture of an MCPS consisting of four layers: data acquisition, data aggregation, cloud processing, and action. Due to the differences in hardware and communication capabilities of each layer, different encryption schemes must be used to guarantee data privacy within that layer. We survey conventional and emerging encryption schemes based on their ability to provide secure storage, data sharing, and secure computation. Our detailed experimental evaluation of each scheme shows that while the emerging encryption schemes enable exciting new features such as secure sharing and secure computation, they introduce several orders-of-magnitude computational and storage overhead. We conclude our paper by outlining future research directions to improve the usability of the emerging encryption schemes in an MCPS.
Research on cloud background infrared radiation simulation based on fractal and statistical data
NASA Astrophysics Data System (ADS)
Liu, Xingrun; Xu, Qingshan; Li, Xia; Wu, Kaifeng; Dong, Yanbing
2018-02-01
Cloud is an important natural phenomenon, and its radiation causes serious interference to infrared detector. Based on fractal and statistical data, a method is proposed to realize cloud background simulation, and cloud infrared radiation data field is assigned using satellite radiation data of cloud. A cloud infrared radiation simulation model is established using matlab, and it can generate cloud background infrared images for different cloud types (low cloud, middle cloud, and high cloud) in different months, bands and sensor zenith angles.
Optical Algorithm for Cloud Shadow Detection Over Water
2013-02-01
REPORT DATE (DD-MM-YYYY) 05-02-2013 2. REPORT TYPE Journal Article 3. DATES COVERED (From ■ To) 4. TITLE AND SUBTITLE Optical Algorithm for Cloud...particularly over humid tropical regions. Throughout the year, about two-thirds of the Earth’s surface is always covered by clouds [1]. The problem...V. Khlopenkov and A. P. Trishchenko, "SPARC: New cloud, snow , cloud shadow detection scheme for historical I-km AVHHR data over Canada," / Atmos
Modeling of the Wegener Bergeron Findeisen process—implications for aerosol indirect effects
NASA Astrophysics Data System (ADS)
Storelvmo, T.; Kristjánsson, J. E.; Lohmann, U.; Iversen, T.; Kirkevåg, A.; Seland, Ø.
2008-10-01
A new parameterization of the Wegener-Bergeron-Findeisen (WBF) process has been developed, and implemented in the general circulation model CAM-Oslo. The new parameterization scheme has important implications for the process of phase transition in mixed-phase clouds. The new treatment of the WBF process replaces a previous formulation, in which the onset of the WBF effect depended on a threshold value of the mixing ratio of cloud ice. As no observational guidance for such a threshold value exists, the previous treatment added uncertainty to estimates of aerosol effects on mixed-phase clouds. The new scheme takes subgrid variability into account when simulating the WBF process, allowing for smoother phase transitions in mixed-phase clouds compared to the previous approach. The new parameterization yields a model state which gives reasonable agreement with observed quantities, allowing for calculations of aerosol effects on mixed-phase clouds involving a reduced number of tunable parameters. Furthermore, we find a significant sensitivity to perturbations in ice nuclei concentrations with the new parameterization, which leads to a reversal of the traditional cloud lifetime effect.
Wu, Yilun; Lu, Xicheng; Su, Jinshu; Chen, Peixin
2016-12-01
Preserving the privacy of electronic medical records (EMRs) is extremely important especially when medical systems adopt cloud services to store patients' electronic medical records. Considering both the privacy and the utilization of EMRs, some medical systems apply searchable encryption to encrypt EMRs and enable authorized users to search over these encrypted records. Since individuals would like to share their EMRs with multiple persons, how to design an efficient searchable encryption for sharable EMRs is still a very challenge work. In this paper, we propose a cost-efficient secure channel free searchable encryption (SCF-PEKS) scheme for sharable EMRs. Comparing with existing SCF-PEKS solutions, our scheme reduces the storage overhead and achieves better computation performance. Moreover, our scheme can guard against keyword guessing attack, which is neglected by most of the existing schemes. Finally, we implement both our scheme and a latest medical-based scheme to evaluate the performance. The evaluation results show that our scheme performs much better performance than the latest one for sharable EMRs.
NASA Technical Reports Server (NTRS)
Jasperson, W. H.; Nastrom, G. D.; Davis, R. E.; Holdeman, J. D.
1984-01-01
Summary studies are presented for the entire cloud observation archieve from the NASA Global Atmospheric Sampling Program (GASP). Studies are also presented for GASP particle concentration data gathered concurrently with the cloud observations. Cloud encounters are shown on about 15 percent of the data samples overall, but the probability of cloud encounter is shown to vary significantly with altitude, latitude, and distance from the tropopause. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover, and the cloud encounter statistics are shown to be consistent with the classical mid-latitude cyclone model. Observations of clouds spaced more closely than 90 minutes are shown to be statistically dependent. The statistics for cloud and particle encounter are utilized to estimate the frequency of cloud encounter on long range airline routes, and to assess the probability and extent of laminar flow loss due to cloud or particle encounter by aircraft utilizing laminar flow control (LFC). It is shown that the probability of extended cloud encounter is too low, of itself, to make LFC impractical.
NASA Astrophysics Data System (ADS)
LIU, J.; Bi, Y.; Duan, S.; Lu, D.
2017-12-01
It is well-known that cloud characteristics, such as top and base heights and their layering structure of micro-physical parameters, spatial coverage and temporal duration are very important factors influencing both radiation budget and its vertical partitioning as well as hydrological cycle through precipitation data. Also, cloud structure and their statistical distribution and typical values will have respective characteristics with geographical and seasonal variation. Ka band radar is a powerful tool to obtain above parameters around the world, such as ARM cloud radar at the Oklahoma US, Since 2006, Cloudsat is one of NASA's A-Train satellite constellation, continuously observe the cloud structure with global coverage, but only twice a day it monitor clouds over same local site at same local time.By using IAP Ka band Doppler radar which has been operating continuously since early 2013 over the roof of IAP building in Beijing, we obtained the statistical characteristic of clouds, including cloud layering, cloud top and base heights, as well as the thickness of each cloud layer and their distribution, and were analyzed monthly and seasonal and diurnal variation, statistical analysis of cloud reflectivity profiles is also made. The analysis covers both non-precipitating clouds and precipitating clouds. Also, some preliminary comparison of the results with Cloudsat/Calipso products for same period and same area are made.
NASA Astrophysics Data System (ADS)
Wang, H.; Kravitz, B.; Rasch, P. J.; Morrison, H.; Solomon, A.
2014-12-01
Previous process-oriented modeling studies have highlighted the dependence of effectiveness of cloud brightening by aerosols on cloud regimes in warm marine boundary layer. Cloud microphysical processes in clouds that contain ice, and hence the mechanisms that drive aerosol-cloud interactions, are more complicated than in warm clouds. Interactions between ice particles and liquid drops add additional levels of complexity to aerosol effects. A cloud-resolving model is used to study aerosol-cloud interactions in the Arctic triggered by strong aerosol emissions, through either geoengineering injection or concentrated sources such as shipping and fires. An updated cloud microphysical scheme with prognostic aerosol and cloud particle numbers is employed. Model simulations are performed in pure super-cooled liquid and mixed-phase clouds, separately, with or without an injection of aerosols into either a clean or a more polluted Arctic boundary layer. Vertical mixing and cloud scavenging of particles injected from the surface is still quite efficient in the less turbulent cold environment. Overall, the injection of aerosols into the Arctic boundary layer can delay the collapse of the boundary layer and increase low-cloud albedo. The pure liquid clouds are more susceptible to the increase in aerosol number concentration than the mixed-phase clouds. Rain production processes are more effectively suppressed by aerosol injection, whereas ice precipitation (snow) is affected less; thus the effectiveness of brightening mixed-phase clouds is lower than for liquid-only clouds. Aerosol injection into a clean boundary layer results in a greater cloud albedo increase than injection into a polluted one, consistent with current knowledge about aerosol-cloud interactions. Unlike previous studies investigating warm clouds, the impact of dynamical feedback due to precipitation changes is small. According to these results, which are dependent upon the representation of ice nucleation processes in the employed microphysical scheme, Arctic geoengineering/shipping could have substantial local radiative effects, but is unlikely to be effective as the sole means of counterbalancing warming due to climate change.
Evaluation of ERA-interim and MERRA Cloudiness in the Southern Oceans
NASA Technical Reports Server (NTRS)
Naud, Catherine M.; Booth, James F.; Del Genio, Anthony D.
2014-01-01
The Southern Ocean cloud cover modeled by the Interim ECMWF Re-Analysis (ERA-Interim) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) reanalyses are compared against Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) observations. ERA-Interim monthly mean cloud amounts match the observations within 5%, while MERRA significantly underestimates the cloud amount. For a compositing analysis of clouds in warm season extratropical cyclones, both reanalyses show a low bias in cloud cover. They display a larger bias to the west of the cyclones in the region of subsidence behind the cold fronts. This low bias is larger for MERRA than for ERA-Interim. Both MODIS and MISR retrievals indicate that the clouds in this sector are at a low altitude, often composed of liquid, and of a broken nature. The combined CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) cloud profiles confirm these passive observations, but they also reveal that low-level clouds in other parts of the cyclones are also not properly represented in the reanalyses. The two reanalyses are in fairly good agreement for the dynamic and thermodynamic characteristics of the cyclones, suggesting that the cloud, convection, or boundary layer schemes are the problem instead. An examination of the lower-tropospheric stability distribution in the cyclones from both reanalyses suggests that the parameterization of shallow cumulus clouds may contribute in a large part to the problem. However, the differences in the cloud schemes and in particular in the precipitation processes, which may also contribute, cannot be excluded.
Cloud-free resolution element statistics program
NASA Technical Reports Server (NTRS)
Liley, B.; Martin, C. D.
1971-01-01
Computer program computes number of cloud-free elements in field-of-view and percentage of total field-of-view occupied by clouds. Human error is eliminated by using visual estimation to compute cloud statistics from aerial photographs.
A Fourier approach to cloud motion estimation
NASA Technical Reports Server (NTRS)
Arking, A.; Lo, R. C.; Rosenfield, A.
1977-01-01
A Fourier technique is described for estimating cloud motion from pairs of pictures using the phase of the cross spectral density. The method allows motion estimates to be made for individual spatial frequencies, which are related to cloud pattern dimensions. Results obtained are presented and compared with the results of a Fourier domain cross correlation scheme. Using both artificial and real cloud data show that the technique is relatively sensitive to the presence of mixtures of motions, changes in cloud shape, and edge effects.
Liu, Zheng; Muhlbauer, Andreas; Ackerman, Thomas
2015-11-05
In this paper, we evaluate high-level clouds in a cloud resolving model during two convective cases, ARM9707 and KWAJEX. The simulated joint histograms of cloud occurrence and radar reflectivity compare well with cloud radar and satellite observations when using a two-moment microphysics scheme. However, simulations performed with a single moment microphysical scheme exhibit low biases of approximately 20 dB. During convective events, two-moment microphysical overestimate the amount of high-level cloud and one-moment microphysics precipitate too readily and underestimate the amount and height of high-level cloud. For ARM9707, persistent large positive biases in high-level cloud are found, which are not sensitivemore » to changes in ice particle fall velocity and ice nuclei number concentration in the two-moment microphysics. These biases are caused by biases in large-scale forcing and maintained by the periodic lateral boundary conditions. The combined effects include significant biases in high-level cloud amount, radiation, and high sensitivity of cloud amount to nudging time scale in both convective cases. The high sensitivity of high-level cloud amount to the thermodynamic nudging time scale suggests that thermodynamic nudging can be a powerful ‘‘tuning’’ parameter for the simulated cloud and radiation but should be applied with caution. The role of the periodic lateral boundary conditions in reinforcing the biases in cloud and radiation suggests that reducing the uncertainty in the large-scale forcing in high levels is important for similar convective cases and has far reaching implications for simulating high-level clouds in super-parameterized global climate models such as the multiscale modeling framework.« less
A multi-sensor approach to the retrieval and model validation of global cloudiness
NASA Astrophysics Data System (ADS)
Miller, Steven D.
2000-11-01
The ephemeral clouds have represented a daunting challenge to the atmospheric modeling community from the very beginning. Our inability to resolve them by means of traditional passive sensors to the level of detail required for characterizing their complicated role in the climate feedback system has lead us to explore other resources at our disposal. This research seeks to illustrate and, where applicable, quantify the ways in which active (e.g., radar and lidar) remote sensing devices on existing and proposed platforms can serve to improve our current understanding of cloud and cloud processes in terms of (1)their role in the improvement of cloud property retrievals and (2)their application to the validation/development of clouds in numerical weather prediction models. A new retrieval technique which employs active sensors to constrain cloud boundaries in the vertical is shown to decrease the parameter uncertainties with respect to traditional passive methods in excess of 20% for effective particle radius, and 10-20% for optical depth when considering night-time retrievals of cirrus. These results are brought together with detailed cloud profile sampling from the Lidar In-space Technology Experiment (LITE) to conduct the first global-scale active sensor validation of ECMWF short-range forecasts. The comparisons display remarkable agreement in cloud spatial distribution. A weighted statistical analysis yields hit rates between 75-90%, threat scores 45-75%, probabilities of detection ~80%, and false alarm rates 10-45%. The results suggest that, given the level of realism displayed currently by the ECMWF prognostic cloud scheme forecasts, the reanalysis data may be considered as a new resource for global cloud information. A practical application of these findings has been outlined in the context of defining Cloud-Sat instrument requirements based on virtual orbital observations created from ECMWF global cloud distributions of liquid and ice water contents. This research gives cause for new hope in capturing the complex radiative, convective, and dynamical feedback mechanisms associated with clouds in the climate feedback system. Further, it appeals to the need for an improved collaborative rapport between the now largely disjoint modeling and measurement communities.
Statistical properties of a cloud ensemble - A numerical study
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Simpson, Joanne; Soong, Su-Tzai
1987-01-01
The statistical properties of cloud ensembles under a specified large-scale environment, such as mass flux by cloud drafts and vertical velocity as well as the condensation and evaporation associated with these cloud drafts, are examined using a three-dimensional numerical cloud ensemble model described by Soong and Ogura (1980) and Tao and Soong (1986). The cloud drafts are classified as active and inactive, and separate contributions to cloud statistics in areas of different cloud activity are then evaluated. The model results compare well with results obtained from aircraft measurements of a well-organized ITCZ rainband that occurred on August 12, 1974, during the Global Atmospheric Research Program's Atlantic Tropical Experiment.
Robust Spacecraft Component Detection in Point Clouds.
Wei, Quanmao; Jiang, Zhiguo; Zhang, Haopeng
2018-03-21
Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.
Robust Spacecraft Component Detection in Point Clouds
Wei, Quanmao; Jiang, Zhiguo
2018-01-01
Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density. PMID:29561828
New Concepts for Refinement of Cumulus Parameterization in GCM's the Arakawa-Schubert Framework
NASA Technical Reports Server (NTRS)
Sud, Y. C.; Walker, G. K.; Lau, William (Technical Monitor)
2002-01-01
Several state-of-the-art models including the one employed in this study use the Arakawa-Schubert framework for moist convection, and Sundqvist formulation of stratiform. clouds, for moist physics, in-cloud condensation, and precipitation. Despite a variety of cloud parameterization methodologies developed by several modelers including the authors, most of the parameterized cloud-models have similar deficiencies. These consist of: (a) not enough shallow clouds, (b) too many deep clouds; (c) several layers of clouds in a vertically demoralized model as opposed to only a few levels of observed clouds, and (d) higher than normal incidence of double ITCZ (Inter-tropical Convergence Zone). Even after several upgrades consisting of a sophisticated cloud-microphysics and sub-grid scale orographic precipitation into the Data Assimilation Office (DAO)'s atmospheric model (called GEOS-2 GCM) at two different resolutions, we found that the above deficiencies remained persistent. The two empirical solutions often used to counter the aforestated deficiencies consist of a) diffusion of moisture and heat within the lower troposphere to artificially force the shallow clouds; and b) arbitrarily invoke evaporation of in-cloud water for low-level clouds. Even though helpful, these implementations lack a strong physical rationale. Our research shows that two missing physical conditions can ameliorate the aforestated cloud-parameterization deficiencies. First, requiring an ascending cloud airmass to be saturated at its starting point will not only make the cloud instantly buoyant all through its ascent, but also provide the essential work function (buoyancy energy) that would promote more shallow clouds. Second, we argue that training clouds that are unstable to a finite vertical displacement, even if neutrally buoyant in their ambient environment, must continue to rise and entrain causing evaporation of in-cloud water. These concepts have not been invoked in any of the cloud parameterization schemes so far. We introduced them into the DAO-GEOS-2 GCM with McRAS (Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme).
NASA Astrophysics Data System (ADS)
Lin, Guofen; Hong, Hanshu; Xia, Yunhao; Sun, Zhixin
2017-10-01
Attribute-based encryption (ABE) is an interesting cryptographic technique for flexible cloud data sharing access control. However, some open challenges hinder its practical application. In previous schemes, all attributes are considered as in the same status while they are not in most of practical scenarios. Meanwhile, the size of access policy increases dramatically with the raise of its expressiveness complexity. In addition, current research hardly notices that mobile front-end devices, such as smartphones, are poor in computational performance while too much bilinear pairing computation is needed for ABE. In this paper, we propose a key-policy weighted attribute-based encryption without bilinear pairing computation (KP-WABE-WB) for secure cloud data sharing access control. A simple weighted mechanism is presented to describe different importance of each attribute. We introduce a novel construction of ABE without executing any bilinear pairing computation. Compared to previous schemes, our scheme has a better performance in expressiveness of access policy and computational efficiency.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yu, F.; Luo, G.; Pryor, S. C.
Recent laboratory chamber studies indicate a significant role for highly oxidized low-volatility organics in new particle formation (NPF), but the actual role of these highly oxidized low-volatility organics in atmospheric NPF remains uncertain. Here, particle size distributions (PSDs) measured in nine forest areas in North America are used to characterize the occurrence and intensity of NPF and to evaluate model simulations using an empirical formulation in which formation rate is a function of the concentrations of sulfuric acid and low-volatility organics from alpha-pinene oxidation (Nucl-Org), and using an ion-mediated nucleation mechanism (excluding organics) (Nucl-IMN). On average, NPF occurred on ~more » 70 % of days during March for the four forest sites with springtime PSD measurements, while NPF occurred on only ~ 10 % of days in July for all nine forest sites. Both Nucl-Org and Nucl-IMN schemes capture the observed high frequency of NPF in spring, but the Nucl-Org scheme significantly overpredicts while the Nucl-IMN scheme slightly underpredicts NPF and particle number concentrations in summer. Statistical analyses of observed and simulated ultrafine particle number concentrations and frequency of NPF events indicate that the scheme without organics agrees better overall with observations. The two schemes predict quite different nucleation rates (including their spatial patterns), concentrations of cloud condensation nuclei, and aerosol first indirect radiative forcing in North America, highlighting the need to reduce NPF uncertainties in regional and global earth system models.« less
NASA Technical Reports Server (NTRS)
Manning, Robert M.
1991-01-01
The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.
Vial, Jessica; Bony, Sandrine; Dufresne, Jean-Louis; Roehrig, Romain
2016-12-01
Several studies have pointed out the dependence of low-cloud feedbacks on the strength of the lower-tropospheric convective mixing. By analyzing a series of single-column model experiments run by a climate model using two different convective parametrizations, this study elucidates the physical mechanisms through which marine boundary-layer clouds depend on this mixing in the present-day climate and under surface warming. An increased lower-tropospheric convective mixing leads to a reduction of low-cloud fraction. However, the rate of decrease strongly depends on how the surface latent heat flux couples to the convective mixing and to boundary-layer cloud radiative effects: (i) on the one hand, the latent heat flux is enhanced by the lower-tropospheric drying induced by the convective mixing, which damps the reduction of the low-cloud fraction, (ii) on the other hand, the latent heat flux is reduced as the lower troposphere stabilizes under the effect of reduced low-cloud radiative cooling, which enhances the reduction of the low-cloud fraction. The relative importance of these two different processes depends on the closure of the convective parameterization. The convective scheme that favors the coupling between latent heat flux and low-cloud radiative cooling exhibits a stronger sensitivity of low-clouds to convective mixing in the present-day climate, and a stronger low-cloud feedback in response to surface warming. In this model, the low-cloud feedback is stronger when the present-day convective mixing is weaker and when present-day clouds are shallower and more radiatively active. The implications of these insights for constraining the strength of low-cloud feedbacks observationally is discussed.
Bony, Sandrine; Dufresne, Jean‐Louis; Roehrig, Romain
2016-01-01
Abstract Several studies have pointed out the dependence of low‐cloud feedbacks on the strength of the lower‐tropospheric convective mixing. By analyzing a series of single‐column model experiments run by a climate model using two different convective parametrizations, this study elucidates the physical mechanisms through which marine boundary‐layer clouds depend on this mixing in the present‐day climate and under surface warming. An increased lower‐tropospheric convective mixing leads to a reduction of low‐cloud fraction. However, the rate of decrease strongly depends on how the surface latent heat flux couples to the convective mixing and to boundary‐layer cloud radiative effects: (i) on the one hand, the latent heat flux is enhanced by the lower‐tropospheric drying induced by the convective mixing, which damps the reduction of the low‐cloud fraction, (ii) on the other hand, the latent heat flux is reduced as the lower troposphere stabilizes under the effect of reduced low‐cloud radiative cooling, which enhances the reduction of the low‐cloud fraction. The relative importance of these two different processes depends on the closure of the convective parameterization. The convective scheme that favors the coupling between latent heat flux and low‐cloud radiative cooling exhibits a stronger sensitivity of low‐clouds to convective mixing in the present‐day climate, and a stronger low‐cloud feedback in response to surface warming. In this model, the low‐cloud feedback is stronger when the present‐day convective mixing is weaker and when present‐day clouds are shallower and more radiatively active. The implications of these insights for constraining the strength of low‐cloud feedbacks observationally is discussed. PMID:28239438
NASA Technical Reports Server (NTRS)
Jasperson, W. H.; Nastron, G. D.; Davis, R. E.; Holdeman, J. D.
1984-01-01
Summary studies are presented for the entire cloud observation archive from the NASA Global Atmospheric Sampling Program (GASP). Studies are also presented for GASP particle-concentration data gathered concurrently with the cloud observations. Cloud encounters are shown on about 15 percent of the data samples overall, but the probability of cloud encounter is shown to vary significantly with altitude, latitude, and distance from the tropopause. Several meteorological circulation features are apparent in the latitudinal distribution of cloud cover, and the cloud-encounter statistics are shown to be consistent with the classical mid-latitude cyclone model. Observations of clouds spaced more closely than 90 minutes are shown to be statistically dependent. The statistics for cloud and particle encounter are utilized to estimate the frequency of cloud encounter on long-range airline routes, and to assess the probability and extent of laminaar flow loss due to cloud or particle encounter by aircraft utilizing laminar flow control (LFC). It is shown that the probability of extended cloud encounter is too low, of itself, to make LFC impractical. This report is presented in two volumes. Volume I contains the narrative, analysis, and conclusions. Volume II contains five supporting appendixes.
Nowcasting Cloud Fields for U.S. Air Force Special Operations
2017-03-01
application of Bayes’ Rule offers many advantages over Kernel Density Estimation (KDE) and other commonly used statistical post-processing methods...reflectance and probability of cloud. A statistical post-processing technique is applied using Bayesian estimation to train the system from a set of past...nowcasting, low cloud forecasting, cloud reflectance, ISR, Bayesian estimation, statistical post-processing, machine learning 15. NUMBER OF PAGES
Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Demek, Scott R.
2010-01-01
Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.
NASA Astrophysics Data System (ADS)
Tan, Ivy; Storelvmo, Trude
2015-04-01
Substantial improvements have been made to the cloud microphysical schemes used in the latest generation of global climate models (GCMs), however, an outstanding weakness of these schemes lies in the arbitrariness of their tuning parameters, which are also notoriously fraught with uncertainties. Despite the growing effort in improving the cloud microphysical schemes in GCMs, most of this effort has neglected to focus on improving the ability of GCMs to accurately simulate the present-day global distribution of thermodynamic phase partitioning in mixed-phase clouds. Liquid droplets and ice crystals not only influence the Earth's radiative budget and hence climate sensitivity via their contrasting optical properties, but also through the effects of their lifetimes in the atmosphere. The current study employs NCAR's CAM5.1, and uses observations of cloud phase obtained by NASA's CALIOP lidar over a 79-month period (November 2007 to June 2014) guide the accurate simulation of the global distribution of mixed-phase clouds in 20∘ latitudinal bands at the -10∘ C, -20∘C and -30∘C isotherms, by adjusting six relevant cloud microphysical tuning parameters in the CAM5.1 via Quasi-Monte Carlo sampling. Among the parameters include those that control the Wegener-Bergeron-Findeisen (WBF) timescale for the conversion of supercooled liquid droplets to ice and snow in mixed-phase clouds, the fraction of ice nuclei that nucleate ice in the atmosphere, ice crystal sedimentation speed, and wet scavenging in stratiform and convective clouds. Using a Generalized Linear Model as a variance-based sensitivity analysis, the relative contributions of each of the six parameters are quantified to gain a better understanding of the importance of their individual and two-way interaction effects on the liquid to ice proportion in mixed-phase clouds. Thus, the methodology implemented in the current study aims to search for the combination of cloud microphysical parameters in a GCM that produce the most accurate reproduction of observations of cloud thermodynamic phase, while simultaneously assessing the weaknesses of the parameterizations in the model. We find that the simulated proportion of liquid to ice in mixed-phase clouds is dominated by the fraction of active ice nuclei in the atmosphere and the WBF timescale. In a follow-up to this study, we apply these results to a fully-coupled GCM, CESM, and find that cloud thermodynamic phase has profound ramifications for the uncertainty associated with climate sensitivity estimates.
Improvement of a Privacy Authentication Scheme Based on Cloud for Medical Environment.
Chiou, Shin-Yan; Ying, Zhaoqin; Liu, Junqiang
2016-04-01
Medical systems allow patients to receive care at different hospitals. However, this entails considerable inconvenience through the need to transport patients and their medical records between hospitals. The development of Telecare Medicine Information Systems (TMIS) makes it easier for patients to seek medical treatment and to store and access medical records. However, medical data stored in TMIS is not encrypted, leaving patients' private data vulnerable to external leaks. In 2014, scholars proposed a new cloud-based medical information model and authentication scheme which would not only allow patients to remotely access medical services but also protects patient privacy. However, this scheme still fails to provide patient anonymity and message authentication. Furthermore, this scheme only stores patient medical data, without allowing patients to directly access medical advice. Therefore, we propose a new authentication scheme, which provides anonymity, unlinkability, and message authentication, and allows patients to directly and remotely consult with doctors. In addition, our proposed scheme is more efficient in terms of computation cost. The proposed system was implemented in Android system to demonstrate its workability.
NASA Astrophysics Data System (ADS)
Urbanek, Benedikt; Groß, Silke; Wirth, Martin
2017-04-01
Cirrus clouds impose high uncertainties on weather and climate prediction, as knowledge on important processes is still incomplete. For instance it remains unclear how cloud optical, microphysical, and radiative properties change as the cirrus evolves. To gain better understanding of cirrus clouds, their optical and microphysical properties and their changes with cirrus cloud evolution the ML-CIRRUS campaign was conducted in March and April 2014. Measurements with a combined in-situ and remote sensing payload were performed with the German research aircraft HALO based in Oberpfaffenhofen. 16 research flights with altogether 88 flight hours were performed over the North-Atlantic, western and central Europe to probe different cirrus cloud regimes and cirrus clouds at different stages of evolution. One of the key remotes sensing instruments during ML-CIRRUS was the airborne differential absorption and high spectral lidar system WALES. It measures the 2-dimensional distribution of water vapor inside and outside of cirrus clouds as well as the optical properties of the clouds. Bases on these airborne lidar measurements a novel classification scheme to derive the stage of cirrus cloud evolution was developed. It identifies regions of ice nucleation, particle growth by deposition of water vapor, and ice sublimation. This method is used to investigate differences in the distribution and value of optical properties as well as in the distribution of water vapor and relative humidity depending on the stage of evolution of the cloud. We will present the lidar based classification scheme and its application on a wave driven cirrus cloud case, and we will show first results of the dependence of optical cloud properties and relative humidity distributions on the determined stage of evolution.
Observational and Modeling Studies of Clouds and the Hydrological Cycle
NASA Technical Reports Server (NTRS)
Somerville, Richard C. J.
1997-01-01
Our approach involved validating parameterizations directly against measurements from field programs, and using this validation to tune existing parameterizations and to guide the development of new ones. We have used a single-column model (SCM) to make the link between observations and parameterizations of clouds, including explicit cloud microphysics (e.g., prognostic cloud liquid water used to determine cloud radiative properties). Surface and satellite radiation measurements were used to provide an initial evaluation of the performance of the different parameterizations. The results of this evaluation will then used to develop improved cloud and cloud-radiation schemes, which were tested in GCM experiments.
Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms
NASA Astrophysics Data System (ADS)
Sednev, I.; Menon, S.; McFarquhar, G.
2008-06-01
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 9th-10th 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 due to freezing of supercooled water in both saturated and undersaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.
Simulating mixed-phase Arctic stratus clouds: sensitivity to ice initiation mechanisms
NASA Astrophysics Data System (ADS)
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 due to freezing of supercooled water in both saturated and subsaturated (w.r.t. water) environments is as important as primary ice crystal origination from water vapor. We also find that the BFP is a process mainly responsible for the rates of glaciation of simulated clouds. These glaciation rates cannot be adequately represented by a water-ice saturation adjustment scheme that only depends on temperature and liquid and solid hydrometeors' contents as is widely used in bulk microphysics schemes and are better represented by processes that also account for supersaturation changes as the hydrometeors grow.
Privacy-Enhanced and Multifunctional Health Data Aggregation under Differential Privacy Guarantees
Ren, Hao; Li, Hongwei; Liang, Xiaohui; He, Shibo; Dai, Yuanshun; Zhao, Lian
2016-01-01
With the rapid growth of the health data scale, the limited storage and computation resources of wireless body area sensor networks (WBANs) is becoming a barrier to their development. Therefore, outsourcing the encrypted health data to the cloud has been an appealing strategy. However, date aggregation will become difficult. Some recently-proposed schemes try to address this problem. However, there are still some functions and privacy issues that are not discussed. In this paper, we propose a privacy-enhanced and multifunctional health data aggregation scheme (PMHA-DP) under differential privacy. Specifically, we achieve a new aggregation function, weighted average (WAAS), and design a privacy-enhanced aggregation scheme (PAAS) to protect the aggregated data from cloud servers. Besides, a histogram aggregation scheme with high accuracy is proposed. PMHA-DP supports fault tolerance while preserving data privacy. The performance evaluation shows that the proposal leads to less communication overhead than the existing one. PMID:27626417
Privacy-Enhanced and Multifunctional Health Data Aggregation under Differential Privacy Guarantees.
Ren, Hao; Li, Hongwei; Liang, Xiaohui; He, Shibo; Dai, Yuanshun; Zhao, Lian
2016-09-10
With the rapid growth of the health data scale, the limited storage and computation resources of wireless body area sensor networks (WBANs) is becoming a barrier to their development. Therefore, outsourcing the encrypted health data to the cloud has been an appealing strategy. However, date aggregation will become difficult. Some recently-proposed schemes try to address this problem. However, there are still some functions and privacy issues that are not discussed. In this paper, we propose a privacy-enhanced and multifunctional health data aggregation scheme (PMHA-DP) under differential privacy. Specifically, we achieve a new aggregation function, weighted average (WAAS), and design a privacy-enhanced aggregation scheme (PAAS) to protect the aggregated data from cloud servers. Besides, a histogram aggregation scheme with high accuracy is proposed. PMHA-DP supports fault tolerance while preserving data privacy. The performance evaluation shows that the proposal leads to less communication overhead than the existing one.
ARM - Midlatitude Continental Convective Clouds
Jensen, Mike; Bartholomew, Mary Jane; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos
2012-01-19
Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.
ARM - Midlatitude Continental Convective Clouds (comstock-hvps)
Jensen, Mike; Comstock, Jennifer; Genio, Anthony Del; Giangrande, Scott; Kollias, Pavlos
2012-01-06
Convective processes play a critical role in the Earth's energy balance through the redistribution of heat and moisture in the atmosphere and their link to the hydrological cycle. Accurate representation of convective processes in numerical models is vital towards improving current and future simulations of Earths climate system. Despite improvements in computing power, current operational weather and global climate models are unable to resolve the natural temporal and spatial scales important to convective processes and therefore must turn to parameterization schemes to represent these processes. In turn, parameterization schemes in cloud-resolving models need to be evaluated for their generality and application to a variety of atmospheric conditions. Data from field campaigns with appropriate forcing descriptors have been traditionally used by modelers for evaluating and improving parameterization schemes.
NASA Astrophysics Data System (ADS)
Aubé, M.; Simoneau, A.
2018-05-01
Illumina is one of the most physically detailed artificial night sky brightness model to date. It has been in continuous development since 2005 [1]. In 2016-17, many improvements were made to the Illumina code including an overhead cloud scheme, an improved blocking scheme for subgrid obstacles (trees and buildings), and most importantly, a full hyperspectral modeling approach. Code optimization resulted in significant reduction in execution time enabling users to run the model on standard personal computers for some applications. After describing the new schemes introduced in the model, we give some examples of applications for a peri-urban and a rural site both located inside the International Dark Sky reserve of Mont-Mégantic (QC, Canada).
Improving the Representation of Snow Crystal Properties within a Single-Moment Microphysics Scheme
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.
2010-01-01
The assumptions of a single-moment microphysics scheme (NASA Goddard) were evaluated using a variety of surface, aircraft and radar data sets. Fixed distribution intercepts and snow bulk densities fail to represent the vertical variability and diversity of crystal populations for this event. Temperature-based equations have merit, but they can be adversely affected by complex temperature profiles that are inverted or isothermal. Column-based approaches can mitigate complex profiles of temperature but are restricted by the ability of the model to represent cloud depth. Spheres are insufficient for use in CloudSat reflectivity comparisons due to Mie resonance, but reasonable for Rayleigh scattering applications. Microphysics schemes will benefit from a greater range of snow crystal characteristics to accommodate naturally occurring diversity.
Cloud Simulations in Response to Turbulence Parameterizations in the GISS Model E GCM
NASA Technical Reports Server (NTRS)
Yao, Mao-Sung; Cheng, Ye
2013-01-01
The response of cloud simulations to turbulence parameterizations is studied systematically using the GISS general circulation model (GCM) E2 employed in the Intergovernmental Panel on Climate Change's (IPCC) Fifth Assessment Report (AR5).Without the turbulence parameterization, the relative humidity (RH) and the low cloud cover peak unrealistically close to the surface; with the dry convection or with only the local turbulence parameterization, these two quantities improve their vertical structures, but the vertical transport of water vapor is still weak in the planetary boundary layers (PBLs); with both local and nonlocal turbulence parameterizations, the RH and low cloud cover have better vertical structures in all latitudes due to more significant vertical transport of water vapor in the PBL. The study also compares the cloud and radiation climatologies obtained from an experiment using a newer version of turbulence parameterization being developed at GISS with those obtained from the AR5 version. This newer scheme differs from the AR5 version in computing nonlocal transports, turbulent length scale, and PBL height and shows significant improvements in cloud and radiation simulations, especially over the subtropical eastern oceans and the southern oceans. The diagnosed PBL heights appear to correlate well with the low cloud distribution over oceans. This suggests that a cloud-producing scheme needs to be constructed in a framework that also takes the turbulence into consideration.
Scheduling multimedia services in cloud computing environment
NASA Astrophysics Data System (ADS)
Liu, Yunchang; Li, Chunlin; Luo, Youlong; Shao, Yanling; Zhang, Jing
2018-02-01
Currently, security is a critical factor for multimedia services running in the cloud computing environment. As an effective mechanism, trust can improve security level and mitigate attacks within cloud computing environments. Unfortunately, existing scheduling strategy for multimedia service in the cloud computing environment do not integrate trust mechanism when making scheduling decisions. In this paper, we propose a scheduling scheme for multimedia services in multi clouds. At first, a novel scheduling architecture is presented. Then, We build a trust model including both subjective trust and objective trust to evaluate the trust degree of multimedia service providers. By employing Bayesian theory, the subjective trust degree between multimedia service providers and users is obtained. According to the attributes of QoS, the objective trust degree of multimedia service providers is calculated. Finally, a scheduling algorithm integrating trust of entities is proposed by considering the deadline, cost and trust requirements of multimedia services. The scheduling algorithm heuristically hunts for reasonable resource allocations and satisfies the requirement of trust and meets deadlines for the multimedia services. Detailed simulated experiments demonstrate the effectiveness and feasibility of the proposed trust scheduling scheme.
The beta distribution: A statistical model for world cloud cover
NASA Technical Reports Server (NTRS)
Falls, L. W.
1973-01-01
Much work has been performed in developing empirical global cloud cover models. This investigation was made to determine an underlying theoretical statistical distribution to represent worldwide cloud cover. The beta distribution with probability density function is given to represent the variability of this random variable. It is shown that the beta distribution possesses the versatile statistical characteristics necessary to assume the wide variety of shapes exhibited by cloud cover. A total of 160 representative empirical cloud cover distributions were investigated and the conclusion was reached that this study provides sufficient statical evidence to accept the beta probability distribution as the underlying model for world cloud cover.
Aerosols and Aerosol-related haze forecasting in China Meteorological Adminstration
NASA Astrophysics Data System (ADS)
Zhou, Chunhong; Zhang, Xiaoye; Gong, Sunling; Liu, Hongli; Xue, Min
2017-04-01
CMA Unified Atmospheric Chemistry Environmental Forecasting System (CUACE) is a unified numerical chemical weather forecasting system with BC, OC, Sulfate, Nitrate, Ammonia, Dust and Sea-Salt aerosols and their sources, gas to particle processes, SOA, microphysics and transformation. With an open interface, CUACE has been online coupled to mesoscale model MM5 and the new NWP system GRAPES (Global/Regional Assimilation and Prediction Enhanced System)min CMA. With Chinese Emissions from Cao and Zhang(2012 and 2013), a forecasting system called CUACE/Haze-fog has been running in real time in CMA and issue 5-days PM10, O3 and Visibility forecasts. A comprehensive ACI scheme has also been developed in CUACE Calculated by a sectional aerosol activation scheme based on the information of size and mass from CUACE and the thermal-dynamic and humid states from the weather model at each time step, the cloud condensation nuclei (CCN) is fed online interactively into a two-moment cloud scheme (WDM6) and a convective parameterization to drive the cloud physics and precipitation formation processes. The results show that interactive aerosols with the WDM6 in CUACE obviously improve the clouds properties and the precipitation, showing 24% to 48% enhancements of TS scoring for 6-h precipitation .
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.
2004-01-01
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.; Johnson, D.; Remer, L.
2004-01-01
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.
Fine-grained Database Field Search Using Attribute-Based Encryption for E-Healthcare Clouds.
Guo, Cheng; Zhuang, Ruhan; Jie, Yingmo; Ren, Yizhi; Wu, Ting; Choo, Kim-Kwang Raymond
2016-11-01
An effectively designed e-healthcare system can significantly enhance the quality of access and experience of healthcare users, including facilitating medical and healthcare providers in ensuring a smooth delivery of services. Ensuring the security of patients' electronic health records (EHRs) in the e-healthcare system is an active research area. EHRs may be outsourced to a third-party, such as a community healthcare cloud service provider for storage due to cost-saving measures. Generally, encrypting the EHRs when they are stored in the system (i.e. data-at-rest) or prior to outsourcing the data is used to ensure data confidentiality. Searchable encryption (SE) scheme is a promising technique that can ensure the protection of private information without compromising on performance. In this paper, we propose a novel framework for controlling access to EHRs stored in semi-trusted cloud servers (e.g. a private cloud or a community cloud). To achieve fine-grained access control for EHRs, we leverage the ciphertext-policy attribute-based encryption (CP-ABE) technique to encrypt tables published by hospitals, including patients' EHRs, and the table is stored in the database with the primary key being the patient's unique identity. Our framework can enable different users with different privileges to search on different database fields. Differ from previous attempts to secure outsourcing of data, we emphasize the control of the searches of the fields within the database. We demonstrate the utility of the scheme by evaluating the scheme using datasets from the University of California, Irvine.
GEWEX Cloud Systems Study (GCSS)
NASA Technical Reports Server (NTRS)
Moncrieff, Mitch
1993-01-01
The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.
NASA Astrophysics Data System (ADS)
Cecchini, Micael A.; Machado, Luiz A. T.; Wendisch, Manfred; Costa, Anja; Krämer, Martina; Andreae, Meinrat O.; Afchine, Armin; Albrecht, Rachel I.; Artaxo, Paulo; Borrmann, Stephan; Fütterer, Daniel; Klimach, Thomas; Mahnke, Christoph; Martin, Scot T.; Minikin, Andreas; Molleker, Sergej; Pardo, Lianet H.; Pöhlker, Christopher; Pöhlker, Mira L.; Pöschl, Ulrich; Rosenfeld, Daniel; Weinzierl, Bernadett
2017-12-01
The behavior of tropical clouds remains a major open scientific question, resulting in poor representation by models. One challenge is to realistically reproduce cloud droplet size distributions (DSDs) and their evolution over time and space. Many applications, not limited to models, use the gamma function to represent DSDs. However, even though the statistical characteristics of the gamma parameters have been widely studied, there is almost no study dedicated to understanding the phase space of this function and the associated physics. This phase space can be defined by the three parameters that define the DSD intercept, shape, and curvature. Gamma phase space may provide a common framework for parameterizations and intercomparisons. Here, we introduce the phase space approach and its characteristics, focusing on warm-phase microphysical cloud properties and the transition to the mixed-phase layer. We show that trajectories in this phase space can represent DSD evolution and can be related to growth processes. Condensational and collisional growth may be interpreted as pseudo-forces that induce displacements in opposite directions within the phase space. The actually observed movements in the phase space are a result of the combination of such pseudo-forces. Additionally, aerosol effects can be evaluated given their significant impact on DSDs. The DSDs associated with liquid droplets that favor cloud glaciation can be delimited in the phase space, which can help models to adequately predict the transition to the mixed phase. We also consider possible ways to constrain the DSD in two-moment bulk microphysics schemes, in which the relative dispersion parameter of the DSD can play a significant role. Overall, the gamma phase space approach can be an invaluable tool for studying cloud microphysical evolution and can be readily applied in many scenarios that rely on gamma DSDs.
Uncertainty associated with convective wet removal of entrained aerosols in a global climate model
NASA Astrophysics Data System (ADS)
Croft, B.; Pierce, J. R.; Martin, R. V.; Hoose, C.; Lohmann, U.
2012-11-01
The uncertainties associated with the wet removal of aerosols entrained above convective cloud bases are investigated in a global aerosol-climate model (ECHAM5-HAM) under a set of limiting assumptions for the wet removal of the entrained aerosols. The limiting assumptions for the wet removal of entrained aerosols are negligible scavenging and vigorous scavenging (either through activation, with size-dependent impaction scavenging, or with the prescribed fractions of the standard model). To facilitate this process-based study, an explicit representation of cloud-droplet-borne and ice-crystal-borne aerosol mass and number, for the purpose of wet removal, is introduced into the ECHAM5-HAM model. This replaces and is compared with the prescribed cloud-droplet-borne and ice-crystal-borne aerosol fraction scavenging scheme of the standard model. A 20% to 35% uncertainty in simulated global, annual mean aerosol mass burdens and optical depth (AOD) is attributed to different assumptions for the wet removal of aerosols entrained above convective cloud bases. Assumptions about the removal of aerosols entrained above convective cloud bases control modeled upper tropospheric aerosol concentrations by as much as one order of magnitude. Simulated aerosols entrained above convective cloud bases contribute 20% to 50% of modeled global, annual mean aerosol mass convective wet deposition (about 5% to 10% of the total dry and wet deposition), depending on the aerosol species, when including wet scavenging of those entrained aerosols (either by activation, size-dependent impaction, or with the prescribed fraction scheme). Among the simulations, the prescribed fraction and size-dependent impaction schemes yield the largest global, annual mean aerosol mass convective wet deposition (by about two-fold). However, the prescribed fraction scheme has more vigorous convective mixed-phase wet removal (by two to five-fold relative to the size-dependent impaction scheme) since nearly all entrained accumulation and coarse mode aerosols are assumed to be cloud-droplet borne or ice-crystal borne, and evaporation due to the Bergeron-Findeisen process is neglected. The simulated convective wet scavenging of entrained accumulation and coarse mode aerosols has feedbacks on new particle formation and the number of Aitken mode aerosols, which control stratiform and convective cloud droplet number concentrations and yield precipitation changes in the ECHAM5-HAM model. However, the geographic distribution of aerosol annual mean convective wet deposition change in the model is driven by changes to the assumptions regarding the scavenging of aerosols entrained above cloud bases rather than by precipitation changes, except for sea salt deposition in the tropics. Uncertainty in the seasonal, regional cycles of AOD due to assumptions about entrained aerosol wet scavenging is similar in magnitude to the estimated error in the AOD retrievals. The uncertainty in aerosol concentrations, burdens, and AOD attributed to different assumptions for the wet scavenging of aerosols entrained above convective cloud bases in a global model motivates the ongoing need to better understand and model the activation and impaction processes that aerosols undergo after entrainment into convective updrafts.
NASA Astrophysics Data System (ADS)
McKague, Darren Shawn
2001-12-01
The statistical properties of clouds and precipitation on a global scale are important to our understanding of climate. Inversion methods exist to retrieve the needed cloud and precipitation properties from satellite data pixel-by-pixel that can then be summarized over large data sets to obtain the desired statistics. These methods can be quite computationally expensive, and typically don't provide errors on the statistics. A new method is developed to directly retrieve probability distributions of parameters from the distribution of measured radiances. The method also provides estimates of the errors on the retrieved distributions. The method can retrieve joint distributions of parameters that allows for the study of the connection between parameters. A forward radiative transfer model creates a mapping from retrieval parameter space to radiance space. A Monte Carlo procedure uses the mapping to transform probability density from the observed radiance histogram to a two- dimensional retrieval property probability distribution function (PDF). An estimate of the uncertainty in the retrieved PDF is calculated from random realizations of the radiance to retrieval parameter PDF transformation given the uncertainty of the observed radiances, the radiance PDF, the forward radiative transfer, the finite number of prior state vectors, and the non-unique mapping to retrieval parameter space. The retrieval method is also applied to the remote sensing of precipitation from SSM/I microwave data. A method of stochastically generating hydrometeor fields based on the fields from a numerical cloud model is used to create the precipitation parameter radiance space transformation. The impact of vertical and horizontal variability within the hydrometeor fields has a significant impact on algorithm performance. Beamfilling factors are computed from the simulated hydrometeor fields. The beamfilling factors vary quite a bit depending upon the horizontal structure of the rain. The algorithm is applied to SSM/I images from the eastern tropical Pacific and is compared to PDFs of rain rate computed using pixel-by-pixel retrievals from Wilheit and from Liu and Curry. Differences exist between the three methods, but good general agreement is seen between the PDF retrieval algorithm and the algorithm of Liu and Curry. (Abstract shortened by UMI.)
Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation
NASA Technical Reports Server (NTRS)
Platnick, Steven E.
2011-01-01
The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.
A Multi-scale Modeling System with Unified Physics to Study Precipitation Processes
NASA Astrophysics Data System (ADS)
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.
ESPC Coupled Global Prediction System
2015-09-30
numerical transport algorithms. Adapted from WRF , a Semi-Lagrangian advection scheme is being implemented in the vertical in NAVGEM to process the...used in the sedimentation of cloud species, especially in the WRF research-community model for all cloud microphysics modules. We have started to
Efficient proof of ownership for cloud storage systems
NASA Astrophysics Data System (ADS)
Zhong, Weiwei; Liu, Zhusong
2017-08-01
Cloud storage system through the deduplication technology to save disk space and bandwidth, but the use of this technology has appeared targeted security attacks: the attacker can deceive the server to obtain ownership of the file by get the hash value of original file. In order to solve the above security problems and the different security requirements of the files in the cloud storage system, an efficient and information-theoretical secure proof of ownership sceme is proposed to support the file rating. Through the K-means algorithm to implement file rating, and use random seed technology and pre-calculation method to achieve safe and efficient proof of ownership scheme. Finally, the scheme is information-theoretical secure, and achieve better performance in the most sensitive areas of client-side I/O and computation.
Modeling CO 2 ice clouds with a Mars Global Climate Model
NASA Astrophysics Data System (ADS)
Audouard, Joachim; Määttänen, Anni; Listowski, Constantino; Millour, Ehouarn; Forget, Francois; Spiga, Aymeric
2016-10-01
Since the first claimed detection of CO2 ice clouds by the Mariner campaign (Herr and Pimentel, 1970), more recent observations and modelling works have put new constraints concerning their altitude, region, time and mechanisms of formation (Clancy and Sandor, 1998; Montmessin et al., 2007; Colaprete et al., 2008; Määttänen et al., 2010; Vincendon et al., 2011; Spiga et al. 2012; Listowski et al. 2014). CO2 clouds are observed at the poles at low altitudes (< 20 km) during the winter and at high altitudes (60-110 km) in the equatorial regions during the first half of the year. However, Martian CO2 clouds's variability and dynamics remain somehow elusive.Towards an understanding of Martian CO2 clouds and especially of their precise radiative impact on the climate throughout the history of the planet, including their formation and evolution in a Global Climate Model (GCM) is necessary.Adapting the CO2 clouds microphysics modeling work of Listowski et al. (2013; 2014), we aim at implementing a complete CO2 clouds scheme in the GCM of the Laboratoire de Météorologie Dynamique (LMD, Forget et al., 1999). It covers CO2 microphysics, growth, evolution and dynamics with a methodology inspired from the water ice clouds scheme recently included in the LMD GCM (Navarro et al., 2014).Two main factors control the formation and evolution of CO2 clouds in the Martian atmosphere: sufficient supersaturation of CO2 is needed and condensation nuclei must be available. Topography-induced gravity-waves (GW) are expected to propagate to the upper atmosphere where they produce cold pockets of supersaturated CO2 (Spiga et al., 2012), thus allowing the formation of clouds provided enough condensation nuclei are present. Such supersaturations have been observed by various instruments, in situ (Schofield et al., 1997) and from orbit (Montmessin et al., 2006, 2011; Forget et al., 2009).Using a GW-induced temperature profile and the 1-D version of the GCM, we simulate the formation of CO2 clouds in the mesosphere and investigate the sensitivity of our microphysics scheme. First results and steps towards the integration in the 3-D GCM will be presented and discussed at the conference.This work is funded by the Laboratory of Excellence ESEP.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang Q.; Lee Y.; Gustafson Jr., W. I.
2011-12-02
This study assesses the ability of the recent chemistry version (v3.3) of the Weather Research and Forecasting (WRF-Chem) model to simulate boundary layer structure, aerosols, stratocumulus clouds, and energy fluxes over the Southeast Pacific Ocean. Measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) and satellite retrievals (i.e., products from the MODerate resolution Imaging Spectroradiometer (MODIS), Clouds and Earth's Radiant Energy System (CERES), and GOES-10) are used for this assessment. The Morrison double-moment microphysics scheme is newly coupled with interactive aerosols in the model. The 31-day (15 October-16 November 2008) WRF-Chem simulation with aerosol-cloud interactions (AERO hereafter) is also comparedmore » to a simulation (MET hereafter) with fixed cloud droplet number concentrations in the microphysics scheme and simplified cloud and aerosol treatments in the radiation scheme. The well-simulated aerosol quantities (aerosol number, mass composition and optical properties), and the inclusion of full aerosol-cloud couplings lead to significant improvements in many features of the simulated stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness. In addition to accounting for the aerosol direct and semi-direct effects, these improvements feed back to the simulation of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengthens the temperature and humidity gradients within the capping inversion layer and lowers the marine boundary layer (MBL) depth by 130 m from that of the MET simulation. These differences are associated with weaker entrainment and stronger mean subsidence at the top of the MBL in AERO. Mean top-of-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with observations in AERO, compared to the MET simulation. Nevertheless, biases in some of the simulated meteorological quantities (e.g., MBL temperature and humidity) and aerosol quantities (e.g., underestimations of accumulation mode aerosol number) might affect simulated stratocumulus and energy fluxes over the Southeastern Pacific, and require further investigation. The well-simulated timing and outflow patterns of polluted and clean episodes demonstrate the model's ability to capture daily/synoptic scale variations of aerosol and cloud properties, and suggest that the model is suitable for studying atmospheric processes associated with pollution outflow over the ocean. The overall performance of the regional model in simulating mesoscale clouds and boundary layer properties is encouraging and suggests that reproducing gradients of aerosol and cloud droplet concentrations and coupling cloud-aerosol-radiation processes are important when simulating marine stratocumulus over the Southeast Pacific.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, X.; Klein, S. A.; Ma, H. -Y.
The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less
Zheng, X.; Klein, S. A.; Ma, H. -Y.; ...
2017-08-24
The Community Atmosphere Model (CAM) adopts Cloud Layers Unified By Binormals (CLUBB) scheme and an updated microphysics (MG2) scheme for a more unified treatment of cloud processes. This makes interactions between parameterizations tighter and more explicit. In this study, a cloudy planetary boundary layer (PBL) oscillation related to interaction between CLUBB and MG2 is identified in CAM. This highlights the need for consistency between the coupled subgrid processes in climate model development. This oscillation occurs most often in the marine cumulus cloud regime. The oscillation occurs only if the modeled PBL is strongly decoupled and precipitation evaporates below the cloud.more » Two aspects of the parameterized coupling assumptions between CLUBB and MG2 schemes cause the oscillation: (1) a parameterized relationship between rain evaporation and CLUBB's subgrid spatial variance of moisture and heat that induces an extra cooling in the lower PBL and (2) rain evaporation which happens at a too low an altitude because of the precipitation fraction parameterization in MG2. Either one of these two conditions can overly stabilize the PBL and reduce the upward moisture transport to the cloud layer so that the PBL collapses. Global simulations prove that turning off the evaporation-variance coupling and improving the precipitation fraction parameterization effectively reduces the cloudy PBL oscillation in marine cumulus clouds. By evaluating the causes of the oscillation in CAM, we have identified the PBL processes that should be examined in models having similar oscillations. This study may draw the attention of the modeling and observational communities to the issue of coupling between parameterized physical processes.« less
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man
2006-01-01
A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.
Improved cloud parameterization for Arctic climate simulations based on satellite data
NASA Astrophysics Data System (ADS)
Klaus, Daniel; Dethloff, Klaus; Dorn, Wolfgang; Rinke, Annette
2015-04-01
The defective representation of Arctic cloud processes and properties remains a crucial problem in climate modelling and in reanalysis products. Satellite-based cloud observations (MODIS and CPR/CALIOP) and single-column model simulations (HIRHAM5-SCM) were exploited to evaluate and improve the simulated Arctic cloud cover of the atmospheric regional climate model HIRHAM5. The ECMWF reanalysis dataset 'ERA-Interim' (ERAint) was used for the model initialization, the lateral boundary forcing as well as the dynamical relaxation inside the pan-Arctic domain. HIRHAM5 has a horizontal resolution of 0.25° and uses 40 pressure-based and terrain-following vertical levels. In comparison with the satellite observations, the HIRHAM5 control run (HH5ctrl) systematically overestimates total cloud cover, but to a lesser extent than ERAint. The underestimation of high- and mid-level clouds is strongly outweighed by the overestimation of low-level clouds. Numerous sensitivity studies with HIRHAM5-SCM suggest (1) the parameter tuning, enabling a more efficient Bergeron-Findeisen process, combined with (2) an extension of the prognostic-statistical (PS) cloud scheme, enabling the use of negatively skewed beta distributions. This improved model setup was then used in a corresponding HIRHAM5 sensitivity run (HH5sens). While the simulated high- and mid-level cloud cover is improved only to a limited extent, the large overestimation of low-level clouds can be systematically and significantly reduced, especially over sea ice. Consequently, the multi-year annual mean area average of total cloud cover with respect to sea ice is almost 14% lower than in HH5ctrl. Overall, HH5sens slightly underestimates the observed total cloud cover but shows a halved multi-year annual mean bias of 2.2% relative to CPR/CALIOP at all latitudes north of 60° N. Importantly, HH5sens produces a more realistic ratio between the cloud water and ice content. The considerably improved cloud simulation manifests in a more correct radiative transfer and better energy budget in the atmospheric boundary layer and results also in a more realistic surface energy budget associated with more reasonable turbulent fluxes. All this mitigates the positive temperature, relative humidity and horizontal wind speed biases in the lower model levels.
NASA Technical Reports Server (NTRS)
Holdaway, Daniel; Kent, James
2015-01-01
The linearity of a selection of common advection schemes is tested and examined with a view to their use in the tangent linear and adjoint versions of an atmospheric general circulation model. The schemes are tested within a simple offline one-dimensional periodic domain as well as using a simplified and complete configuration of the linearised version of NASA's Goddard Earth Observing System version 5 (GEOS-5). All schemes which prevent the development of negative values and preserve the shape of the solution are confirmed to have nonlinear behaviour. The piecewise parabolic method (PPM) with certain flux limiters, including that used by default in GEOS-5, is found to support linear growth near the shocks. This property can cause the rapid development of unrealistically large perturbations within the tangent linear and adjoint models. It is shown that these schemes with flux limiters should not be used within the linearised version of a transport scheme. The results from tests using GEOS-5 show that the current default scheme (a version of PPM) is not suitable for the tangent linear and adjoint model, and that using a linear third-order scheme for the linearised model produces better behaviour. Using the third-order scheme for the linearised model improves the correlations between the linear and non-linear perturbation trajectories for cloud liquid water and cloud liquid ice in GEOS-5.
The application of time series models to cloud field morphology analysis
NASA Technical Reports Server (NTRS)
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.
NASA Technical Reports Server (NTRS)
Han, Mei; Braun, Scott A.; Olson, William S.; Persson, P. Ola G.; Bao, Jian-Wen
2009-01-01
Seen by the human eye, precipitation particles are commonly drops of rain, flakes of snow, or lumps of hail that reach the ground. Remote sensors and numerical models usually deal with information about large collections of rain, snow, and hail (or graupel --also called soft hail ) in a volume of air. Therefore, the size and number of the precipitation particles and how particles interact, evolve, and fall within the volume of air need to be represented using physical laws and mathematical tools, which are often implemented as cloud and precipitation microphysical parameterizations in numerical models. To account for the complexity of the precipitation physical processes, scientists have developed various types of such schemes in models. The accuracy of numerical weather forecasting may vary dramatically when different types of these schemes are employed. Therefore, systematic evaluations of cloud and precipitation schemes are of great importance for improvement of weather forecasts. This study is one such endeavor; it pursues quantitative assessment of all the available cloud and precipitation microphysical schemes in a weather model (MM5) through comparison with the observations obtained by National Aeronautics and Space Administration (NASA) s and Japan Aerospace Exploration Agency (JAXA) s Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and microwave imager (TMI). When satellite sensors (like PR or TMI) detect information from precipitation particles, they cannot directly observe the microphysical quantities (e.g., water species phase, density, size, and amount etc.). Instead, they tell how much radiation is absorbed by rain, reflected away from the sensor by snow or graupel, or reflected back to the satellite. On the other hand, the microphysical quantities in the model are usually well represented in microphysical schemes and can be converted to radiative properties that can be directly compared to the corresponding PR and TMI observations. This study employs this method to evaluate the accuracy of the simulated radiative properties by the MM5 model with different microphysical schemes. It is found that the representations of particle density, size, and mass in the different schemes in the MM5 model determine the model s performance when predicting a winter storm over the eastern Pacific Ocean. Schemes lacking moderate density particles (i.e. graupel), with snow flakes that are too large, or with excessive mass of snow or graupel lead to degraded prediction of the radiative properties as observed by the TRMM satellite. This study demonstrates the uniqueness of the combination of both an active microwave sensor (PR) and passive microwave sensor (TMI) onboard TRMM on assessing the accuracy of numerical weather forecasting. It improves our understanding of the physical and radiative properties of different types of precipitation particles and provides suggestions for better representation of cloud and precipitation processes in numerical models. It would, ultimately, contribute to answering questions like "Why did it not rain when the forecast says it would?"
Secure Nearest Neighbor Query on Crowd-Sensing Data
Cheng, Ke; Wang, Liangmin; Zhong, Hong
2016-01-01
Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU) situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes. PMID:27669253
Secure Nearest Neighbor Query on Crowd-Sensing Data.
Cheng, Ke; Wang, Liangmin; Zhong, Hong
2016-09-22
Nearest neighbor queries are fundamental in location-based services, and secure nearest neighbor queries mainly focus on how to securely and quickly retrieve the nearest neighbor in the outsourced cloud server. However, the previous big data system structure has changed because of the crowd-sensing data. On the one hand, sensing data terminals as the data owner are numerous and mistrustful, while, on the other hand, in most cases, the terminals find it difficult to finish many safety operation due to computation and storage capability constraints. In light of they Multi Owners and Multi Users (MOMU) situation in the crowd-sensing data cloud environment, this paper presents a secure nearest neighbor query scheme based on the proxy server architecture, which is constructed by protocols of secure two-party computation and secure Voronoi diagram algorithm. It not only preserves the data confidentiality and query privacy but also effectively resists the collusion between the cloud server and the data owners or users. Finally, extensive theoretical and experimental evaluations are presented to show that our proposed scheme achieves a superior balance between the security and query performance compared to other schemes.
FRR: fair remote retrieval of outsourced private medical records in electronic health networks.
Wang, Huaqun; Wu, Qianhong; Qin, Bo; Domingo-Ferrer, Josep
2014-08-01
Cloud computing is emerging as the next-generation IT architecture. However, cloud computing also raises security and privacy concerns since the users have no physical control over the outsourced data. This paper focuses on fairly retrieving encrypted private medical records outsourced to remote untrusted cloud servers in the case of medical accidents and disputes. Our goal is to enable an independent committee to fairly recover the original private medical records so that medical investigation can be carried out in a convincing way. We achieve this goal with a fair remote retrieval (FRR) model in which either t investigation committee members cooperatively retrieve the original medical data or none of them can get any information on the medical records. We realize the first FRR scheme by exploiting fair multi-member key exchange and homomorphic privately verifiable tags. Based on the standard computational Diffie-Hellman (CDH) assumption, our scheme is provably secure in the random oracle model (ROM). A detailed performance analysis and experimental results show that our scheme is efficient in terms of communication and computation. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Song, Hwan-Jin; Sohn, Byung-Ju
2018-01-01
The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warmtype rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warmtype heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collisioncoalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.
NASA Astrophysics Data System (ADS)
Song, Hwan-Jin; Sohn, Byung-Ju
2018-05-01
The Korean peninsula is the region of distinctly showing the heavy rain associated with relatively low storm height and small ice water content in the upper part of cloud system (i.e., so-called warm-type heavy rainfall). The satellite observations for the warm-type rain over Korea led to a conjecture that the cloud microphysics parameterization suitable for the continental deep convection may not work well for the warm-type heavy rainfall over the Korean peninsula. Therefore, there is a growing need to examine the performance of cloud microphysics schemes for simulating the warm-type heavy rain structures over the Korean peninsula. This study aims to evaluate the capabilities of eight microphysics schemes in the Weather Research and Forecasting (WRF) model how warm-type heavy rain structures can be simulated, in reference to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity measurements. The results indicate that the WRF Double Moment 6-class (WDM6) scheme simulated best the vertical structure of warm-type heavy rain by virtue of a reasonable collision-coalescence process between liquid droplets and the smallest amount of snow. Nonetheless the WDM6 scheme appears to have limitations that need to be improved upon for a realistic reflectivity structure, in terms of the reflectivity slope below the melting layer, discontinuity in reflectivity profiles around the melting layer, and overestimation of upper-level reflectivity due to high graupel content.
NASA Technical Reports Server (NTRS)
Weger, R. C.; Lee, J.; Zhu, Tianri; Welch, R. M.
1992-01-01
The current controversy existing in reference to the regularity vs. clustering in cloud fields is examined by means of analysis and simulation studies based upon nearest-neighbor cumulative distribution statistics. It is shown that the Poisson representation of random point processes is superior to pseudorandom-number-generated models and that pseudorandom-number-generated models bias the observed nearest-neighbor statistics towards regularity. Interpretation of this nearest-neighbor statistics is discussed for many cases of superpositions of clustering, randomness, and regularity. A detailed analysis is carried out of cumulus cloud field spatial distributions based upon Landsat, AVHRR, and Skylab data, showing that, when both large and small clouds are included in the cloud field distributions, the cloud field always has a strong clustering signal.
Spring and summer contrast in new particle formation over nine forest areas in North America
Yu, F.; Luo, G.; Pryor, S. C.; ...
2015-12-18
Recent laboratory chamber studies indicate a significant role for highly oxidized low-volatility organics in new particle formation (NPF), but the actual role of these highly oxidized low-volatility organics in atmospheric NPF remains uncertain. Here, particle size distributions (PSDs) measured in nine forest areas in North America are used to characterize the occurrence and intensity of NPF and to evaluate model simulations using an empirical formulation in which formation rate is a function of the concentrations of sulfuric acid and low-volatility organics from alpha-pinene oxidation (Nucl-Org), and using an ion-mediated nucleation mechanism (excluding organics) (Nucl-IMN). On average, NPF occurred on ~more » 70 % of days during March for the four forest sites with springtime PSD measurements, while NPF occurred on only ~ 10 % of days in July for all nine forest sites. Both Nucl-Org and Nucl-IMN schemes capture the observed high frequency of NPF in spring, but the Nucl-Org scheme significantly overpredicts while the Nucl-IMN scheme slightly underpredicts NPF and particle number concentrations in summer. Statistical analyses of observed and simulated ultrafine particle number concentrations and frequency of NPF events indicate that the scheme without organics agrees better overall with observations. The two schemes predict quite different nucleation rates (including their spatial patterns), concentrations of cloud condensation nuclei, and aerosol first indirect radiative forcing in North America, highlighting the need to reduce NPF uncertainties in regional and global earth system models.« less
NASA Technical Reports Server (NTRS)
Shi, J. J.; Tao, W.-K.; Matsui, T.; Cifelli, R.; Huo, A.; Lang, S.; Tokay, A.; Peters-Lidard, C.; Jackson, G.; Rutledge, S.;
2009-01-01
One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold season precipitation measurements in middle and high latitudes through the use of high-frequency passive microwave radiometry. For this, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a satellite data simulation unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for two snowstorm events, a lake effect and a synoptic event, that occurred between 20 and 22 January 2007 over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) site in Ontario, Canada. The 24h-accumulated snowfall predicted by the WRF model with the Goddard microphysics was comparable to the observed accumulated snowfall by the ground-based radar for both events. The model correctly predicted the onset and ending of both snow events at the CARE site. WRF simulations capture the basic cloud properties as seen by the ground-based radar and satellite (i.e., CloudSAT, AMSU-B) observations as well as the observed cloud streak organization in the lake event. This latter result reveals that WRF was able to capture the cloud macro-structure reasonably well.
Evaluation of wind field statistics near and inside clouds using a coherent Doppler lidar
NASA Astrophysics Data System (ADS)
Lottman, Brian Todd
1998-09-01
This work proposes advanced techniques for measuring the spatial wind field statistics near and inside clouds using a vertically pointing solid state coherent Doppler lidar on a fixed ground based platform. The coherent Doppler lidar is an ideal instrument for high spatial and temporal resolution velocity estimates. The basic parameters of lidar are discussed, including a complete statistical description of the Doppler lidar signal. This description is extended to cases with simple functional forms for aerosol backscatter and velocity. An estimate for the mean velocity over a sensing volume is produced by estimating the mean spectra. There are many traditional spectral estimators, which are useful for conditions with slowly varying velocity and backscatter. A new class of estimators (novel) is introduced that produces reliable velocity estimates for conditions with large variations in aerosol backscatter and velocity with range, such as cloud conditions. Performance of traditional and novel estimators is computed for a variety of deterministic atmospheric conditions using computer simulated data. Wind field statistics are produced for actual data for a cloud deck, and for multi- layer clouds. Unique results include detection of possible spectral signatures for rain, estimates for the structure function inside a cloud deck, reliable velocity estimation techniques near and inside thin clouds, and estimates for simple wind field statistics between cloud layers.
NASA Astrophysics Data System (ADS)
Paukert, M.; Hoose, C.; Simmel, M.
2017-03-01
In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. In contrast, the immersion freezing of larger drops—"rain"—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. Here we introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation in raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.
Sensitivity of aerosol loading and properties to cloudiness
NASA Astrophysics Data System (ADS)
Iversen, T.; Seland, O.; Kirkevag, A.; Kristjansson, J. E.
2005-12-01
Clouds influence aerosols in various ways. Sulfate is swiftly produced in liquid phase provided there is both sulfur dioxide and oxidants available. Nucleation and Aitken mode aerosol particles efficiently grow in size by collision and coagulation with cloud droplets. When precipitation is formed, aerosol and precursor gases may be quickly removed bay rainout. The dynamics associated with clouds in some cases may swiftly mix aerosols deeply into the troposphere. In some cases Aitken-mode particles may be formed in cloud droplets by splitting agglomerates of particulate matter such as black carbon In this presentation we will discuss how global cloudiness may influence the burden, residence time, and spatial distribution of sulfate, black carbon and particulate organic matter. A similar physico-chemical scheme for there compounds has been implemented in three generations of the NCAR community climate model (CCM3, CAM2 and CAM3). The scheme is documented in the literature and is a part of the Aerocom-intercomparison. There are many differences between these models. With respect to aerosols, a major difference is that CAM3 has a considerably higher global cloud volume and more then twice the amount of cloud water than CAM2 and CCM3. Atmospheric simulations have been made with prescribed ocean temperatures. It is slightly surprising to discover that certain aspects of the aerosols are not particularly sensitive to these differences in cloud availability. This sensitivity will be compared to sensitivities with respect to processing in deep convective clouds.
Yassin, Ali A
2014-01-01
Now, the security of digital images is considered more and more essential and fingerprint plays the main role in the world of image. Furthermore, fingerprint recognition is a scheme of biometric verification that applies pattern recognition techniques depending on image of fingerprint individually. In the cloud environment, an adversary has the ability to intercept information and must be secured from eavesdroppers. Unluckily, encryption and decryption functions are slow and they are often hard. Fingerprint techniques required extra hardware and software; it is masqueraded by artificial gummy fingers (spoof attacks). Additionally, when a large number of users are being verified at the same time, the mechanism will become slow. In this paper, we employed each of the partial encryptions of user's fingerprint and discrete wavelet transform to obtain a new scheme of fingerprint verification. Moreover, our proposed scheme can overcome those problems; it does not require cost, reduces the computational supplies for huge volumes of fingerprint images, and resists well-known attacks. In addition, experimental results illustrate that our proposed scheme has a good performance of user's fingerprint verification.
Yassin, Ali A.
2014-01-01
Now, the security of digital images is considered more and more essential and fingerprint plays the main role in the world of image. Furthermore, fingerprint recognition is a scheme of biometric verification that applies pattern recognition techniques depending on image of fingerprint individually. In the cloud environment, an adversary has the ability to intercept information and must be secured from eavesdroppers. Unluckily, encryption and decryption functions are slow and they are often hard. Fingerprint techniques required extra hardware and software; it is masqueraded by artificial gummy fingers (spoof attacks). Additionally, when a large number of users are being verified at the same time, the mechanism will become slow. In this paper, we employed each of the partial encryptions of user's fingerprint and discrete wavelet transform to obtain a new scheme of fingerprint verification. Moreover, our proposed scheme can overcome those problems; it does not require cost, reduces the computational supplies for huge volumes of fingerprint images, and resists well-known attacks. In addition, experimental results illustrate that our proposed scheme has a good performance of user's fingerprint verification. PMID:27355051
NASA Astrophysics Data System (ADS)
Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.
2007-03-01
This study presents an empirical relation that links layer integrated depolarization ratios, the extinction coefficients, and effective radii of water clouds, based on Monte Carlo simulations of CALIPSO lidar observations. Combined with cloud effective radius retrieved from MODIS, cloud liquid water content and effective number density of water clouds are estimated from CALIPSO lidar depolarization measurements in this study. Global statistics of the cloud liquid water content and effective number density are presented.
NASA Astrophysics Data System (ADS)
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.
NASA Technical Reports Server (NTRS)
Iguchi, Takamichi; Nakajima, Teruyuki; Khain, Alexander P.; Saito, Kazuo; Takemura, Toshihiko; Okamoto, Hajime; Nishizawa, Tomoaki; Tao, Wei-Kuo
2012-01-01
Numerical weather prediction (NWP) simulations using the Japan Meteorological Agency NonhydrostaticModel (JMA-NHM) are conducted for three precipitation events observed by shipborne or spaceborneW-band cloud radars. Spectral bin and single-moment bulk cloud microphysics schemes are employed separatelyfor an intercomparative study. A radar product simulator that is compatible with both microphysicsschemes is developed to enable a direct comparison between simulation and observation with respect to theequivalent radar reflectivity factor Ze, Doppler velocity (DV), and path-integrated attenuation (PIA). Ingeneral, the bin model simulation shows better agreement with the observed data than the bulk modelsimulation. The correction of the terminal fall velocities of snowflakes using those of hail further improves theresult of the bin model simulation. The results indicate that there are substantial uncertainties in the masssizeand sizeterminal fall velocity relations of snowflakes or in the calculation of terminal fall velocity of snowaloft. For the bulk microphysics, the overestimation of Ze is observed as a result of a significant predominanceof snow over cloud ice due to substantial deposition growth directly to snow. The DV comparison shows thata correction for the fall velocity of hydrometeors considering a change of particle size should be introducedeven in single-moment bulk cloud microphysics.
The radiation schemes in the Weather Research and Forecasting (WRF) model have previously not accounted for the presence of subgrid-scale cumulus clouds, thereby resulting in unattenuated shortwave radiation, which can lead to overly energetic convection and overpredicted surface...
Implementation & Evaluation of a New Shallow Convection Scheme in WRF
Clouds are well-known to be a crucial component of the weather and climate system since they transport heat, moisture and momentum vertically in the atmosphere, and strongly modify shortwave and longwave radiation budgets. From the air quality point of view, cloud processes, in p...
FINAL REPORT (DE-FG02-97ER62338): Single-column modeling, GCM parameterizations, and ARM data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Richard C. J. Somerville
2009-02-27
Our overall goal is the development of new and improved parameterizations of cloud-radiation effects and related processes, using ARM data at all three ARM sites, and the implementation and testing of these parameterizations in global models. To test recently developed prognostic parameterizations based on detailed cloud microphysics, we have compared SCM (single-column model) output with ARM observations at the SGP, NSA and TWP sites. We focus on the predicted cloud amounts and on a suite of radiative quantities strongly dependent on clouds, such as downwelling surface shortwave radiation. Our results demonstrate the superiority of parameterizations based on comprehensive treatments ofmore » cloud microphysics and cloud-radiative interactions. At the SGP and NSA sites, the SCM results simulate the ARM measurements well and are demonstrably more realistic than typical parameterizations found in conventional operational forecasting models. At the TWP site, the model performance depends strongly on details of the scheme, and the results of our diagnostic tests suggest ways to develop improved parameterizations better suited to simulating cloud-radiation interactions in the tropics generally. These advances have made it possible to take the next step and build on this progress, by incorporating our parameterization schemes in state-of-the-art three-dimensional atmospheric models, and diagnosing and evaluating the results using independent data. Because the improved cloud-radiation results have been obtained largely via implementing detailed and physically comprehensive cloud microphysics, we anticipate that improved predictions of hydrologic cycle components, and hence of precipitation, may also be achievable.« less
Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas
2018-04-13
Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Inanlouganji, Alireza; Reddy, T. Agami; Katipamula, Srinivas
Forecasting solar irradiation has acquired immense importance in view of the exponential increase in the number of solar photovoltaic (PV) system installations. In this article, analyses results involving statistical and machine-learning techniques to predict solar irradiation for different forecasting horizons are reported. Yearlong typical meteorological year 3 (TMY3) datasets from three cities in the United States with different climatic conditions have been used in this analysis. A simple forecast approach that assumes consecutive days to be identical serves as a baseline model to compare forecasting alternatives. To account for seasonal variability and to capture short-term fluctuations, different variants of themore » lagged moving average (LMX) model with cloud cover as the input variable are evaluated. Finally, the proposed LMX model is evaluated against an artificial neural network (ANN) model. How the one-hour and 24-hour models can be used in conjunction to predict different short-term rolling horizons is discussed, and this joint application is illustrated for a four-hour rolling horizon forecast scheme. Lastly, the effect of using predicted cloud cover values, instead of measured ones, on the accuracy of the models is assessed. Results show that LMX models do not degrade in forecast accuracy if models are trained with the forecast cloud cover data.« less
Cloud Size Distributions from Multi-sensor Observations of Shallow Cumulus Clouds
NASA Astrophysics Data System (ADS)
Kleiss, J.; Riley, E.; Kassianov, E.; Long, C. N.; Riihimaki, L.; Berg, L. K.
2017-12-01
Combined radar-lidar observations have been used for almost two decades to document temporal changes of shallow cumulus clouds at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Facility's Southern Great Plains (SGP) site in Oklahoma, USA. Since the ARM zenith-pointed radars and lidars have a narrow field-of-view (FOV), the documented cloud statistics, such as distributions of cloud chord length (or horizontal length scale), represent only a slice along the wind direction of a region surrounding the SGP site, and thus may not be representative for this region. To investigate this impact, we compare cloud statistics obtained from wide-FOV sky images collected by ground-based observations at the SGP site to those from the narrow FOV active sensors. The main wide-FOV cloud statistics considered are cloud area distributions of shallow cumulus clouds, which are frequently required to evaluate model performance, such as routine large eddy simulation (LES) currently being conducted by the ARM LASSO (LES ARM Symbiotic Simulation and Observation) project. We obtain complementary macrophysical properties of shallow cumulus clouds, such as cloud chord length, base height and thickness, from the combined radar-lidar observations. To better understand the broader observational context where these narrow FOV cloud statistics occur, we compare them to collocated and coincident cloud area distributions from wide-FOV sky images and high-resolution satellite images. We discuss the comparison results and illustrate the possibility to generate a long-term climatology of cloud size distributions from multi-sensor observations at the SGP site.
NASA Technical Reports Server (NTRS)
Li, Xiaowen; Tao, Wei-Kuo; Khain, Alexander P.; Simpson, Joanne; Johnson, Daniel E.
2009-01-01
Part I of this paper compares two simulations, one using a bulk and the other a detailed bin microphysical scheme, of a long-lasting, continental mesoscale convective system with leading convection and trailing stratiform region. Diagnostic studies and sensitivity tests are carried out in Part II to explain the simulated contrasts in the spatial and temporal variations by the two microphysical schemes and to understand the interactions between cloud microphysics and storm dynamics. It is found that the fixed raindrop size distribution in the bulk scheme artificially enhances rain evaporation rate and produces a stronger near surface cool pool compared with the bin simulation. In the bulk simulation, cool pool circulation dominates the near-surface environmental wind shear in contrast to the near-balance between cool pool and wind shear in the bin simulation. This is the main reason for the contrasting quasi-steady states simulated in Part I. Sensitivity tests also show that large amounts of fast-falling hail produced in the original bulk scheme not only result in a narrow trailing stratiform region but also act to further exacerbate the strong cool pool simulated in the bulk parameterization. An empirical formula for a correction factor, r(q(sub r)) = 0.11q(sub r)(exp -1.27) + 0.98, is developed to correct the overestimation of rain evaporation in the bulk model, where r is the ratio of the rain evaporation rate between the bulk and bin simulations and q(sub r)(g per kilogram) is the rain mixing ratio. This formula offers a practical fix for the simple bulk scheme in rain evaporation parameterization.
NASA Technical Reports Server (NTRS)
Li, Xiao-Wen; Tao, Wei-Kuo; Khain, Alexander P.; Simpson, Joanne; Johnson, Daniel E.
2004-01-01
A cloud-resolving model is used to study sensitivities of two different microphysical schemes, one is the bulk type, and the other is an explicit bin scheme, in simulating a mid-latitude squall line case (PRE-STORM, June 10-11, 1985). Simulations using different microphysical schemes are compared with each other and also with the observations. Both the bulk and bin models reproduce the general features during the developing and mature stage of the system. The leading convective zone, the trailing stratiform region, the horizontal wind flow patterns, pressure perturbation associated with the storm dynamics, and the cool pool in front of the system all agree well with the observations. Both the observations and the bulk scheme simulation serve as validations for the newly incorporated bin scheme. However, it is also shown that, the bulk and bin simulations have distinct differences, most notably in the stratiform region. Weak convective cells exist in the stratiform region in the bulk simulation, but not in the bin simulation. These weak convective cells in the stratiform region are remnants of the previous stronger convections at the leading edge of the system. The bin simulation, on the other hand, has a horizontally homogeneous stratiform cloud structure, which agrees better with the observations. Preliminary examinations of the downdraft core strength, the potential temperature perturbation, and the evaporative cooling rate show that the differences between the bulk and bin models are due mainly to the stronger low-level evaporative cooling in convective zone simulated in the bulk model. Further quantitative analysis and sensitivity tests for this case using both the bulk and bin models will be presented in a companion paper.
Secure image retrieval with multiple keys
NASA Astrophysics Data System (ADS)
Liang, Haihua; Zhang, Xinpeng; Wei, Qiuhan; Cheng, Hang
2018-03-01
This article proposes a secure image retrieval scheme under a multiuser scenario. In this scheme, the owner first encrypts and uploads images and their corresponding features to the cloud; then, the user submits the encrypted feature of the query image to the cloud; next, the cloud compares the encrypted features and returns encrypted images with similar content to the user. To find the nearest neighbor in the encrypted features, an encryption with multiple keys is proposed, in which the query feature of each user is encrypted by his/her own key. To improve the key security and space utilization, global optimization and Gaussian distribution are, respectively, employed to generate multiple keys. The experiments show that the proposed encryption can provide effective and secure image retrieval for each user and ensure confidentiality of the query feature of each user.
A Numerical Study of Cirrus Clouds. Part I: Model Description.
NASA Astrophysics Data System (ADS)
Liu, Hui-Chun; Wang, Pao K.; Schlesinger, Robert E.
2003-04-01
This article, the first of a two-part series, presents a detailed description of a two-dimensional numerical cloud model directed toward elucidating the physical processes governing the evolution of cirrus clouds. The two primary scientific purposes of this work are (a) to determine the evolution and maintenance mechanisms of cirrus clouds and try to explain why some cirrus can persist for a long time; and (b) to investigate the influence of certain physical factors such as radiation, ice crystal habit, latent heat, ventilation effects, and aggregation mechanisms on the evolution of cirrus. The second part will discuss sets of model experiments that were run to address objectives (a) and (b), respectively.As set forth in this paper, the aforementioned two-dimensional numerical model, which comprises the research tool for this study, is organized into three modules that embody dynamics, microphysics, and radiation. The dynamic module develops a set of equations to describe shallow moist convection, also parameterizing turbulence by using a 1.5-order closure scheme. The microphysical module uses a double-moment scheme to simulate the evolution of the size distribution of ice particles. Heterogeneous and homogeneous nucleation of haze particles are included, along with other ice crystal processes such as diffusional growth, sedimentation, and aggregation. The radiation module uses a two-stream radiative transfer scheme to determine the radiative fluxes and heating rates, while the cloud optical properties are determined by the modified anomalous diffraction theory (MADT) for ice particles. One of the main advantages of this cirrus model is its explicit formulation of the microphysical and radiative properties as functions of ice crystal habit.
NASA Astrophysics Data System (ADS)
De Meij, A.; Vinuesa, J.-F.; Maupas, V.
2018-05-01
The sensitivity of different microphysics and dynamics schemes on calculated global horizontal irradiation (GHI) values in the Weather Research Forecasting (WRF) model is studied. 13 sensitivity simulations were performed for which the microphysics, cumulus parameterization schemes and land surface models were changed. Firstly we evaluated the model's performance by comparing calculated GHI values for the Base Case with observations for the Reunion Island for 2014. In general, the model calculates the largest bias during the austral summer. This indicates that the model is less accurate in timing the formation and dissipation of clouds during the summer, when higher water vapor quantities are present in the atmosphere than during the austral winter. Secondly, the model sensitivity on changing the microphysics, cumulus parameterization and land surface models on calculated GHI values is evaluated. The sensitivity simulations showed that changing the microphysics from the Thompson scheme (or Single-Moment 6-class scheme) to the Morrison double-moment scheme, the relative bias improves from 45% to 10%. The underlying reason for this improvement is that the Morrison double-moment scheme predicts the mass and number concentrations of five hydrometeors, which help to improve the calculation of the densities, size and lifetime of the cloud droplets. While the single moment schemes only predicts the mass for less hydrometeors. Changing the cumulus parameterization schemes and land surface models does not have a large impact on GHI calculations.
Cloud computing task scheduling strategy based on improved differential evolution algorithm
NASA Astrophysics Data System (ADS)
Ge, Junwei; He, Qian; Fang, Yiqiu
2017-04-01
In order to optimize the cloud computing task scheduling scheme, an improved differential evolution algorithm for cloud computing task scheduling is proposed. Firstly, the cloud computing task scheduling model, according to the model of the fitness function, and then used improved optimization calculation of the fitness function of the evolutionary algorithm, according to the evolution of generation of dynamic selection strategy through dynamic mutation strategy to ensure the global and local search ability. The performance test experiment was carried out in the CloudSim simulation platform, the experimental results show that the improved differential evolution algorithm can reduce the cloud computing task execution time and user cost saving, good implementation of the optimal scheduling of cloud computing tasks.
Lin, Tsung-Hung; Tsung, Chen-Kun; Lee, Tian-Fu; Wang, Zeng-Bo
2017-12-03
The security is a critical issue for business purposes. For example, the cloud meeting must consider strong security to maintain the communication privacy. Considering the scenario with cloud meeting, we apply extended chaotic map to present passwordless group authentication key agreement, termed as Passwordless Group Authentication Key Agreement (PL-GAKA). PL-GAKA improves the computation efficiency for the simple group password-based authenticated key agreement (SGPAKE) proposed by Lee et al. in terms of computing the session key. Since the extended chaotic map has equivalent security level to the Diffie-Hellman key exchange scheme applied by SGPAKE, the security of PL-GAKA is not sacrificed when improving the computation efficiency. Moreover, PL-GAKA is a passwordless scheme, so the password maintenance is not necessary. Short-term authentication is considered, hence the communication security is stronger than other protocols by dynamically generating session key in each cloud meeting. In our analysis, we first prove that each meeting member can get the correct information during the meeting. We analyze common security issues for the proposed PL-GAKA in terms of session key security, mutual authentication, perfect forward security, and data integrity. Moreover, we also demonstrate that communicating in PL-GAKA is secure when suffering replay attacks, impersonation attacks, privileged insider attacks, and stolen-verifier attacks. Eventually, an overall comparison is given to show the performance between PL-GAKA, SGPAKE and related solutions.
Marine boundary layer cloud regimes and POC formation in an LES coupled to a bulk aerosol scheme
NASA Astrophysics Data System (ADS)
Berner, A. H.; Bretherton, C. S.; Wood, R.; Muhlbauer, A.
2013-07-01
A large-eddy simulation (LES) coupled to a new bulk aerosol scheme is used to study long-lived regimes of aerosol-boundary layer cloud-precipitation interaction and the development of pockets of open cells (POCs) in subtropical stratocumulus cloud layers. The aerosol scheme prognoses mass and number concentration of a single log-normal accumulation mode with surface and entrainment sources, evolving subject to processing of activated aerosol and scavenging of dry aerosol by cloud and rain. The LES with the aerosol scheme is applied to a range of steadily-forced simulations idealized from a well-observed POC case. The long-term system evolution is explored with extended two-dimensional simulations of up to 20 days, mostly with diurnally-averaged insolation. One three-dimensional two-day simulation confirms the initial development of the corresponding two-dimensional case. With weak mean subsidence, an initially aerosol-rich mixed layer deepens, the capping stratocumulus cloud slowly thickens and increasingly depletes aerosol via precipitation accretion, then the boundary layer transitions within a few hours into an open-cell regime with scattered precipitating cumuli, in which entrainment is much weaker. The inversion slowly collapses for several days until the cumulus clouds are too shallow to efficiently precipitate. Inversion cloud then reforms and radiatively drives renewed entrainment, allowing the boundary layer to deepen and become more aerosol-rich, until the stratocumulus layer thickens enough to undergo another cycle of open-cell formation. If mean subsidence is stronger, the stratocumulus never thickens enough to initiate drizzle and settles into a steady state. With lower initial aerosol concentrations, this system quickly transitions into open cells, collapses, and redevelops into a different steady state with a shallow, optically thin cloud layer. In these steady states, interstitial scavenging by cloud droplets is the main sink of aerosol number. The system is described in a reduced two-dimensional phase plane with inversion height and boundary-layer average aerosol concentrations as the state variables. Simulations with a full diurnal cycle show similar evolutions, except that open-cell formation is phase-locked into the early morning hours. The same steadily-forced modeling framework is applied to the development and evolution of a POC and the surrounding overcast boundary layer. An initial aerosol perturbation applied to a portion of the model domain leads that portion to transition into open-cell convection, forming a POC. Reduced entrainment in the POC induces a negative feedback between areal fraction covered by the POC and boundary layer depth changes. This stabilizes the system by controlling liquid water path and precipitation sinks of aerosol number in the overcast region, while also preventing boundary-layer collapse within the POC, allowing the POC and overcast to coexist indefinitely in a quasi-steady equilibrium.
NASA Astrophysics Data System (ADS)
Neggers, R.
2017-12-01
Recent advances in supercomputing have introduced a "grey zone" in the representation of cumulus convection in general circulation models, in which this process is partially resolved. Cumulus parameterizations need to be made scale-aware and scale-adaptive to be able to conceptually and practically deal with this situation. A potential way forward are schemes formulated in terms of discretized Cloud Size Densities, or CSDs. Advantages include i) the introduction of scale-awareness at the foundation of the scheme, and ii) the possibility to apply size-filtering of parameterized convective transport and clouds. The CSD is a new variable that requires closure; this concerns its shape, its range, but also variability in cloud number that can appear due to i) subsampling effects and ii) organization in a cloud field. The goal of this study is to gain insight by means of sub-domain analyses of various large-domain LES realizations of cumulus cloud populations. For a series of three-dimensional snapshots, each with a different degree of organization, the cloud size distribution is calculated in all subdomains, for a range of subdomain sizes. The standard deviation of the number of clouds of a certain size is found to decrease with the subdomain size, following a powerlaw scaling corresponding to an inverse-linear dependence. Cloud number variability also increases with cloud size; this reflects that subsampling affects the largest clouds first, due to their typically larger neighbor spacing. Rewriting this dependence in terms of two dimensionless groups, by dividing by cloud number and cloud size respectively, yields a data collapse. Organization in the cloud field is found to act on top of this primary dependence, by enhancing the cloud number variability at the smaller sizes. This behavior reflects that small clouds start to "live" on top of larger structures such as cold pools, favoring or inhibiting their formation (as illustrated by the attached figure of cloud mask). Powerlaw scaling is still evident, but with a reduced exponent, suggesting that this behavior could be parameterized.
NASA Astrophysics Data System (ADS)
Witte, M.; Morrison, H.; Jensen, J. B.; Bansemer, A.; Gettelman, A.
2017-12-01
The spatial covariance of cloud and rain water (or in simpler terms, small and large drops, respectively) is an important quantity for accurate prediction of the accretion rate in bulk microphysical parameterizations that account for subgrid variability using assumed probability density functions (pdfs). Past diagnoses of this covariance from remote sensing, in situ measurements and large eddy simulation output have implicitly assumed that the magnitude of the covariance is insensitive to grain size (i.e. horizontal resolution) and averaging length, but this is not the case because both cloud and rain water exhibit scale invariance across a wide range of scales - from tens of centimeters to tens of kilometers in the case of cloud water, a range that we will show is primarily limited by instrumentation and sampling issues. Since the individual variances systematically vary as a function of spatial scale, it should be expected that the covariance follows a similar relationship. In this study, we quantify the scaling properties of cloud and rain water content and their covariability from high frequency in situ aircraft measurements of marine stratocumulus taken over the southeastern Pacific Ocean aboard the NSF/NCAR C-130 during the VOCALS-REx field experiment of October-November 2008. First we confirm that cloud and rain water scale in distinct manners, indicating that there is a statistically and potentially physically significant difference in the spatial structure of the two fields. Next, we demonstrate that the covariance is a strong function of spatial scale, which implies important caveats regarding the ability of limited-area models with domains smaller than a few tens of kilometers across to accurately reproduce the spatial organization of precipitation. Finally, we present preliminary work on the development of a scale-aware parameterization of cloud-rain water subgrid covariability based in multifractal analysis intended for application in large-scale model microphysics schemes.
NASA Astrophysics Data System (ADS)
Pu, Zhaoxia; Lin, Chao; Dong, Xiquan; Krueger, Steven K.
2018-01-01
Mesoscale convective systems (MCSs) and their associated cloud properties are the important factors that influence the aviation activities, yet they present a forecasting challenge in numerical weather prediction. In this study, the sensitivity of numerical simulations of an MCS over the US Southern Great Plains to ice hydrometeors in bulk microphysics (MP) schemes has been investigated using the Weather Research and Forecasting (WRF) model. It is found that the simulated structure, life cycle, cloud coverage, and precipitation of the convective system as well as its associated cold pools are sensitive to three selected MP schemes, namely, the WRF single-moment 6-class (WSM6), WRF double-moment 6-class (WDM6, with the double-moment treatment of warm-rain only), and Morrison double-moment (MORR, with the double-moment representation of both warm-rain and ice) schemes. Compared with observations, the WRF simulation with WSM6 only produces a less organized convection structure with a short lifetime, while WDM6 can produce the structure and length of the MCS very well. Both simulations heavily underestimate the precipitation amount, the height of the radar echo top, and stratiform cloud fractions. With MORR, the model performs well in predicting the lifetime, cloud coverage, echo top, and precipitation amount of the convection. Overall results demonstrate the importance of including double-moment representation of ice hydrometeors along with warm-rain. Additional experiments are performed to further examine the role of ice hydrometeors in numerical simulations of the MCS. Results indicate that replacing graupel with hail in the MORR scheme improves the prediction of the convective structure, especially in the convective core region.
Understanding the Microphysical Properties of Developing Cloud Clusters during TCS-08
2011-09-30
resolution (1.67-km) sensitivity simulations have been performed using Typhoon Mawar (2005) from the western North Pacific to demonstrate considerable...cloud-resolving) scheme is used in the model. Initial calculations of some basic cloud properties from infrared imagery for Typhoon Mawar indicate that...Figure 4: Intensity traces of simulated Typhoon Mawar (2005) showing sea-level pressure on the left axis and maximum wind speed on the right axis
Evaluation of Model Microphysics Within Precipitation Bands of Extratropical Cyclones
NASA Technical Reports Server (NTRS)
Colle, Brian A.; Yu, Ruyi; Molthan, Andrew L.; Nesbitt, Steven
2014-01-01
It is hypothesized microphysical predictions have greater uncertainties/errors when there are complex interactions that result from mixed phased processes like riming. Use Global Precipitation Measurement (GPM) Mission ground validation studies in Ontario, Canada to verify and improve parameterizations. The WRF realistically simulated the warm frontal snowband at relatively short lead times (1014 h). The snowband structire is sensitive to the microphysical parameterization used in WRF. The Goddard and SBUYLin most realistically predicted the band structure, but overpredicted snow content. The double moment Morrison scheme best produced the slope of the snow distribution, but it underpredicted the intercept. All schemes and the radar derived (which used dry snow ZR) underpredicted the surface precipitation amount, likely because there was more cloud water than expected. The Morrison had the most cloud water and the best precipitation prediction of all schemes.
Cloud encounter statistics in the 28.5-43.5 KFT altitude region from four years of GASP observations
NASA Technical Reports Server (NTRS)
Jasperson, W. H.; Nastrom, G. D.; Davis, R. E.; Holdeman, J. D.
1983-01-01
The results of an analysis of cloud encounter measurements taken at aircraft flight altitudes as part of the Global Atmospheric Sampling Program are summarized. The results can be used in estimating the probability of cloud encounter and in assessing the economic feasibility of laminar flow control aircraft along particular routes. The data presented clearly show the tropical circulation and its seasonal migration; characteristics of the mid-latitude regime, such as the large-scale traveling cyclones in the winter and increased convective activity in the summer, can be isolated in the data. The cloud encounter statistics are shown to be consistent with the mid-latitude cyclone model. A model for TIC (time-in-clouds), a cloud encounter statistic, is presented for several common airline routes.
NASA Astrophysics Data System (ADS)
Thomas, G.
2015-12-01
The ESA Climate Change Initiative (CCI) programme has provided a mechanism for the production of new long-term data records of essential climate variables (ECVs) defined by WMO Global Climate Observing System (GCOS). These include consistent cloud (from the MODIS, AVHRR, ATSR-2 and AATSR instruments) and aerosol (from ATSR-2 and AATSR) products produced using the Optimal Retrieval of Aerosol and Cloud (ORAC) scheme. This talk will present an overview of the newly produced ORAC cloud and aerosol datasets, their evaluation and a joint aerosol-cloud product produced for the 1995-2012 ATSR-2-AATSR data record.
Retrieval of Ice Cloud Properties Using Variable Phase Functions
NASA Astrophysics Data System (ADS)
Heck, Patrick W.; Minnis, Patrick; Yang, Ping; Chang, Fu-Lung; Palikonda, Rabindra; Arduini, Robert F.; Sun-Mack, Sunny
2009-03-01
An enhancement to NASA Langley's Visible Infrared Solar-infrared Split-window Technique (VISST) is developed to identify and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice cloud phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, cloud optical depths are reduced, hence, cloud height is increased. Cloud effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real-time retrievals at Langley.
Investigating mixed phase clouds using a synergy of ground based remote sensing measurements
NASA Astrophysics Data System (ADS)
Gierens, Rosa; Kneifel, Stefan; Löhnert, Ulrich
2017-04-01
Low level mixed phase clouds occur frequently in the Arctic, and can persist from hours to several days. However, the processes that lead to the commonality and persistence of these clouds are not well understood. The aim of our work is to get a more detailed understanding of the dynamics of and the processes in Arctic mixed phase clouds using a combination of instruments operating at the AWIPEV station in Svalbard. In addition, an aircraft campaign collecting in situ measurements inside mixed phase clouds above the station is planned for May-June 2017. The in situ data will be used for developing and validating retrievals for microphysical properties from Doppler cloud radar measurements. Once observational data for cloud properties is obtained, it can be used for evaluating model performance, for studies combining modeling and observational approaches, and eventually lead to developing model parameterizations of mixed phase microphysics. To describe the low-level mixed phase clouds, and the atmospheric conditions in which they occur, we present a case study of a persistent mixed phase cloud observed above the AWIPEV station. In the frame of the Arctic Amplification: Climate Relevant Atmospheric and Surface Processes and Feedback Mechanisms ((AC)3) -project, a millimeter wavelength cloud radar was installed at the site in June 2016. The high vertical (4 m in the lowest layer) and temporal (2.5 sec) resolution allows for a detailed description of the structure of the cloud. In addition to radar reflectivity and mean vertical velocity, we also utilize the higher moments of the Doppler spectra, such as skewness and kurtosis. To supplement the radar measurements, a ceilometer is used to detect liquid layers inside the cloud. Liquid water path and integrated water vapor are estimated using a microwave radiometer, which together with soundings can also provide temperature and humidity profiles in the lower troposphere. Moreover, a three-dimensional wind field is be obtained from a Doppler wind lidar. Furthermore, the Cloudnet scheme (www.cloud-net.org), that combines radar, lidar and microwave radiometer observations with a forecast model to provide a best estimate of cloud properties, is used for identifying mixed phase clouds. The continuous measurements carried out at AWIPEV make it possible to characterize the macro- and micro- physical properties of mixed-phase clouds on a long-term, statistical basis. The Arctic observations are compared to a 5-year observational data set from Jülich Observatory for Cloud Evolution (JOYCE) in Western Germany. The occurrence of different types of clouds (with focus on mixed-phase and super-cooled clouds), the distribution of ice and liquid within the clouds, the turbulent environment as well as the temperatures where the different phases are occurring are investigated.
NASA Technical Reports Server (NTRS)
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.
The Impact of Microphysical Schemes on Intensity and Track of Hurricane
NASA Technical Reports Server (NTRS)
Tao, W. K.; Shi, J. J.; Chen, S. S.; Lang, S.; Lin, P.; Hong, S. Y.; Peters-Lidard, C.; Hou, A.
2010-01-01
During the past decade, both research and operational numerical weather prediction models [e.g. Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with a 1-2 km or less horizontal resolutions. The WRF is a next-generation meso-scale forecast model and assimilation system that has incorporated a modern software framework, advanced dynamics, numeric and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. The WRF model can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At Goddard, four different cloud microphysics schemes (warm rain only, two-class of ice, two three-class of ice with either graupel or hail) are implemented into the WRF. The performances of these schemes have been compared to those from other WRF microphysics scheme options for an Atlantic hurricane case. In addition, a brief review and comparison on the previous modeling studies on the impact of microphysics schemes and microphysical processes on intensity and track of hurricane will be presented. Generally, almost all modeling studies found that the microphysics schemes did not have major impacts on track forecast, but did have more effect on the intensity. All modeling studies found that the simulated hurricane has rapid deepening and/or intensification for the warm rain-only case. It is because all hydrometeors were very large raindrops, and they fell out quickly at and near the eye-wall region. This would hydrostatically produce the lowest pressure. In addition, these modeling studies suggested that the simulated hurricane becomes unrealistically strong by removing the evaporative cooling of cloud droplets and melting of ice particles. This is due to the much weaker downdraft simulated. However, there are many differences between different modeling studies and these differences were identified and discussed.
Impact of Aerosol Processing on Orographic Clouds
NASA Astrophysics Data System (ADS)
Pousse-Nottelmann, Sara; Zubler, Elias M.; Lohmann, Ulrike
2010-05-01
Aerosol particles undergo significant modifications during their residence time in the atmosphere. Physical processes like coagulation, coating and water uptake, and aqueous surface chemistry alter the aerosol size distribution and composition. At this, clouds play a primary role as physical and chemical processing inside cloud droplets contributes considerably to the changes in aerosol particles. A previous study estimates that on global average atmospheric particles are cycled three times through a cloud before being removed from the atmosphere [1]. An explicit and detailed treatment of cloud-borne particles has been implemented in the regional weather forecast and climate model COSMO-CLM. The employed model version includes a two-moment cloud microphysical scheme [2] that has been coupled to the aerosol microphysical scheme M7 [3] as described by Muhlbauer and Lohmann, 2008 [4]. So far, the formation, transfer and removal of cloud-borne aerosol number and mass were not considered in the model. Following the parameterization for cloud-borne particles developed by Hoose et al., 2008 [5], distinction between in-droplet and in-crystal particles is made to more physically account for processes in mixed-phase clouds, such as the Wegener-Bergeron-Findeisen process and contact and immersion freezing. In our model, this approach has been extended to allow for aerosol particles in five different hydrometeors: cloud droplets, rain drops, ice crystals, snow flakes and graupel. We account for nucleation scavenging, freezing and melting processes, autoconversion, accretion, aggregation, riming and selfcollection, collisions between interstitial aerosol particles and hydrometeors, ice multiplication, sedimentation, evaporation and sublimation. The new scheme allows an evaluation of the cloud cycling of aerosol particles by tracking the particles even when scavenged into hydrometeors. Global simulations of aerosol processing in clouds have recently been conducted by Hoose et al. [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.
Impacts of a Fire Smoke Plume on Deep Convective Clouds Observed during DC3
NASA Astrophysics Data System (ADS)
Takeishi, A.; Storelvmo, T.; Zagar, M.
2014-12-01
While the ability of aerosols to act as cloud condensation nuclei (CCN) and ice nuclei (IN) is well recognized, the effects of changing aerosol number concentrations on convective clouds have only been studied extensively in recent years. As deep convective clouds can produce heavy precipitation and may sometimes bring severe damages, especially in the tropics, we need to understand the changes in the convective systems that could stem from aerosol perturbations. By perturbing convective clouds, it has also been proposed that aerosols can affect large-scale climate. According to the convective invigoration mechanism, an increase in the aerosol concentration could lead to a larger amount of rainfall and higher vertical velocities in convective clouds, due to an increase in the latent heat release aloft. With some of the satellite observations supporting this mechanism, it is necessary to understand how sensitive the model simulations actually are to aerosol perturbations. This study uses the Weather Research and Forecasting (WRF) model as a cloud-resolving model to reproduce deep convective clouds observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. The convective cloud of our interest was observed in northeastern Colorado on June 22nd in 2012, with a plume of forest fire smoke flowing into its core. Compared to other convective cells observed in the same area on different days, our aircraft data analysis shows that the convective cloud in question included more organic aerosols and more CCN. These indicate the influence of the biomass burning. We compare the results from simulations with different microphysics schemes and different cloud or ice number concentrations. These sensitivity tests tell us how different the amount and the pattern of precipitation would have been if the aerosol concentration had been higher or lower on that day. Both the sensitivity to aerosol perturbation and the reproducibility of the storm are shown to highly depend on the choice of the microphysics scheme.
The three-dimensional structure of cumulus clouds over the ocean. 1: Structural analysis
NASA Technical Reports Server (NTRS)
Kuo, Kwo-Sen; Welch, Ronald M.; Weger, Ronald C.; Engelstad, Mark A.; Sengupta, S. K.
1993-01-01
Thermal channel (channel 6, 10.4-12.5 micrometers) images of five Landsat thematic mapper cumulus scenes over the ocean are examined. These images are thresholded using the standard International Satellite Cloud Climatology Project (ISCCP) thermal threshold algorithm. The individual clouds in the cloud fields are segmented to obtain their structural statistics which include size distribution, orientation angle, horizontal aspect ratio, and perimeter-to-area (PtA) relationship. The cloud size distributions exhibit a double power law with the smaller clouds having a smaller absolute exponent. The cloud orientation angles, horizontal aspect ratios, and PtA exponents are found in good agreement with earlier studies. A technique also is developed to recognize individual cells within a cloud so that statistics of cloud cellular structure can be obtained. Cell structural statistics are computed for each cloud. Unicellular clouds are generally smaller (less than or equal to 1 km) and have smaller PtA exponents, while multicellular clouds are larger (greater than or equal to 1 km) and have larger PtA exponents. Cell structural statistics are similar to those of the smaller clouds. When each cell is approximated as a quadric surface using a linear least squares fit, most cells have the shape of a hyperboloid of one sheet, but about 15% of the cells are best modeled by a hyperboloid of two sheets. Less than 1% of the clouds are ellipsoidal. The number of cells in a cloud increases slightly faster than linearly with increasing cloud size. The mean nearest neighbor distance between cells in a cloud, however, appears to increase linearly with increasing cloud size and to reach a maximum when the cloud effective diameter is about 10 km; then it decreases with increasing cloud size. Sensitivity studies of threshold and lapse rate show that neither has a significant impact upon the results. A goodness-of-fit ratio is used to provide a quantitative measure of the individual cloud results. Significantly improved results are obtained after applying a smoothing operator, suggesting the eliminating subresolution scale variations with higher spatial resolution may yield even better shape analyses.
Saide, Pablo E; Thompson, Gregory; Eidhammer, Trude; da Silva, Arlindo M; Pierce, R Bradley; Carmichael, Gregory R
2016-09-16
We use the WRF system to study the impacts of biomass burning smoke from Central America on several tornado outbreaks occurring in the US during spring. The model is configured with an aerosol-aware microphysics parameterization capable of resolving aerosol-cloud-radiation interactions in a cost-efficient way for numerical weather prediction (NWP) applications. Primary aerosol emissions are included and smoke emissions are constrained using an inverse modeling technique and satellite-based AOD observations. Simulations turning on and off fire emissions reveal smoke presence in all tornado outbreaks being studied and show an increase in aerosol number concentrations due to smoke. However, the likelihood of occurrence and intensification of tornadoes is higher due to smoke only in cases where cloud droplet number concentration in low level clouds increases considerably in a way that modifies the environmental conditions where the tornadoes are formed (shallower cloud bases and higher low-level wind shear). Smoke absorption and vertical extent also play a role, with smoke absorption at cloud-level tending to burn-off clouds and smoke absorption above clouds resulting in an increased capping inversion. Comparing these and WRF-Chem simulations configured with a more complex representation of aerosol size and composition and different optical properties, microphysics and activation schemes, we find similarities in terms of the simulated aerosol optical depths and aerosol impacts on near-storm environments. This provides reliability on the aerosol-aware microphysics scheme as a less computationally expensive alternative to WRF-Chem for its use in applications such as NWP and cloud-resolving simulations.
NASA Technical Reports Server (NTRS)
Saide, Pablo E.; Thompson, Gregory; Eidhammer, Trude; Da Silva, Arlindo M.; Pierce, R. Bradley; Carmichael, Gregory R.
2016-01-01
We use the WRF system to study the impacts of biomass burning smoke from Central America on several tornado outbreaks occurring in the US during spring. The model is configured with an aerosol-aware microphysics parameterization capable of resolving aerosol-cloud-radiation interactions in a cost-efficient way for numerical weather prediction (NWP) applications. Primary aerosol emissions are included and smoke emissions are constrained using an inverse modeling technique and satellite-based AOD observations. Simulations turning on and off fire emissions reveal smoke presence in all tornado outbreaks being studied and show an increase in aerosol number concentrations due to smoke. However, the likelihood of occurrence and intensification of tornadoes is higher due to smoke only in cases where cloud droplet number concentration in low level clouds increases considerably in a way that modifies the environmental conditions where the tornadoes are formed (shallower cloud bases and higher low-level wind shear). Smoke absorption and vertical extent also play a role, with smoke absorption at cloud-level tending to burn-off clouds and smoke absorption above clouds resulting in an increased capping inversion. Comparing these and WRF-Chem simulations configured with a more complex representation of aerosol size and composition and different optical properties, microphysics and activation schemes, we find similarities in terms of the simulated aerosol optical depths and aerosol impacts on near-storm environments. This provides reliability on the aerosol-aware microphysics scheme as a less computationally expensive alternative to WRFChem for its use in applications such as NWP and cloud-resolving simulations.
Paukert, M.; Hoose, C.; Simmel, M.
2017-02-21
In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. Conversely, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. We introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation inmore » raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This also provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Paukert, M.; Hoose, C.; Simmel, M.
In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. Conversely, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. We introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation inmore » raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This also provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.« less
The effect of clouds on the earth's radiation budget
NASA Technical Reports Server (NTRS)
Ziskin, Daniel; Strobel, Darrell F.
1991-01-01
The radiative fluxes from the Earth Radiation Budget Experiment (ERBE) and the cloud properties from the International Satellite Cloud Climatology Project (ISCCP) over Indonesia for the months of June and July of 1985 and 1986 were analyzed to determine the cloud sensitivity coefficients. The method involved a linear least squares regression between co-incident flux and cloud coverage measurements. The calculated slope is identified as the cloud sensitivity. It was found that the correlations between the total cloud fraction and radiation parameters were modest. However, correlations between cloud fraction and IR flux were improved by separating clouds by height. Likewise, correlations between the visible flux and cloud fractions were improved by distinguishing clouds based on optical depth. Calculating correlations between the net fluxes and either height or optical depth segregated cloud fractions were somewhat improved. When clouds were classified in terms of their height and optical depth, correlations among all the radiation components were improved. Mean cloud sensitivities based on the regression of radiative fluxes against height and optical depth separated cloud types are presented. Results are compared to a one-dimensional radiation model with a simple cloud parameterization scheme.
Electric Field Magnitude and Radar Reflectivity as a Function of Distance from Cloud Edge
NASA Technical Reports Server (NTRS)
Ward, Jennifer G.; Merceret, Francis J.
2004-01-01
The results of analyses of data collected during a field investigation of thunderstorm anvil and debris clouds are reported. Statistics of the magnitude of the electric field are determined as a function of distance from cloud edge. Statistics of radar reflectivity near cloud edge are also determined. Both analyses use in-situ airborne field mill and cloud physics data coupled with ground-based radar measurements obtained in east-central Florida during the summer convective season. Electric fields outside of anvil and debris clouds averaged less than 3 kV/m. The average radar reflectivity at the cloud edge ranged between 0 and 5 dBZ.
NASA Astrophysics Data System (ADS)
Meneguz, Elena; Thomson, David; Witham, Claire; Kusmierczyk-Michulec, Jolanta
2015-04-01
NAME is a Lagrangian atmospheric dispersion model used by the Met Office to predict the dispersion of both natural and man-made contaminants in the atmosphere, e.g. volcanic ash, radioactive particles and chemical species. Atmospheric convection is responsible for transport and mixing of air resulting in a large exchange of heat and energy above the boundary layer. Although convection can transport material through the whole troposphere, convective clouds have a small horizontal length scale (of the order of few kilometres). Therefore, for large-scale transport the horizontal scale on which the convection exists is below the global NWP resolution used as input to NAME and convection must be parametrized. Prior to the work presented here, the enhanced vertical mixing generated by non-resolved convection was reproduced by randomly redistributing Lagrangian particles between the cloud base and cloud top with probability equal to 1/25th of the NWP predicted convective cloud fraction. Such a scheme is essentially diffusive and it does not make optimal use of all the information provided by the driving meteorological model. To make up for these shortcomings and make the parametrization more physically based, the convection scheme has been recently revised. The resulting version, presented in this paper, is now based on the balance equation between upward, entrainment and detrainment fluxes. In particular, upward mass fluxes are calculated with empirical formulas derived from Cloud Resolving Models and using the NWP convective precipitation diagnostic as closure. The fluxes are used to estimate how many particles entrain, move upward and detrain. Lastly, the scheme is completed by applying a compensating subsidence flux. The performance of the updated convection scheme is benchmarked against available observational data of passive tracers. In particular, radioxenon is a noble gas that can undergo significant long range transport: this study makes use of observations of the isotope 133Xe available at International Monitoring System stations around the South Pacific Ocean. In addition, timeseries of modelled output concentrations obtained using NAME on a grid of 25 km size are compared with those obtained with FLEXPART, another well-known atmospheric dispersion model used by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) and other scientific communities. Findings are discussed and discrepancies investigated.
Provenance based data integrity checking and verification in cloud environments
Haq, Inam Ul; Jan, Bilal; Khan, Fakhri Alam; Ahmad, Awais
2017-01-01
Cloud computing is a recent tendency in IT that moves computing and data away from desktop and hand-held devices into large scale processing hubs and data centers respectively. It has been proposed as an effective solution for data outsourcing and on demand computing to control the rising cost of IT setups and management in enterprises. However, with Cloud platforms user’s data is moved into remotely located storages such that users lose control over their data. This unique feature of the Cloud is facing many security and privacy challenges which need to be clearly understood and resolved. One of the important concerns that needs to be addressed is to provide the proof of data integrity, i.e., correctness of the user’s data stored in the Cloud storage. The data in Clouds is physically not accessible to the users. Therefore, a mechanism is required where users can check if the integrity of their valuable data is maintained or compromised. For this purpose some methods are proposed like mirroring, checksumming and using third party auditors amongst others. However, these methods use extra storage space by maintaining multiple copies of data or the presence of a third party verifier is required. In this paper, we address the problem of proving data integrity in Cloud computing by proposing a scheme through which users are able to check the integrity of their data stored in Clouds. In addition, users can track the violation of data integrity if occurred. For this purpose, we utilize a relatively new concept in the Cloud computing called “Data Provenance”. Our scheme is capable to reduce the need of any third party services, additional hardware support and the replication of data items on client side for integrity checking. PMID:28545151
Provenance based data integrity checking and verification in cloud environments.
Imran, Muhammad; Hlavacs, Helmut; Haq, Inam Ul; Jan, Bilal; Khan, Fakhri Alam; Ahmad, Awais
2017-01-01
Cloud computing is a recent tendency in IT that moves computing and data away from desktop and hand-held devices into large scale processing hubs and data centers respectively. It has been proposed as an effective solution for data outsourcing and on demand computing to control the rising cost of IT setups and management in enterprises. However, with Cloud platforms user's data is moved into remotely located storages such that users lose control over their data. This unique feature of the Cloud is facing many security and privacy challenges which need to be clearly understood and resolved. One of the important concerns that needs to be addressed is to provide the proof of data integrity, i.e., correctness of the user's data stored in the Cloud storage. The data in Clouds is physically not accessible to the users. Therefore, a mechanism is required where users can check if the integrity of their valuable data is maintained or compromised. For this purpose some methods are proposed like mirroring, checksumming and using third party auditors amongst others. However, these methods use extra storage space by maintaining multiple copies of data or the presence of a third party verifier is required. In this paper, we address the problem of proving data integrity in Cloud computing by proposing a scheme through which users are able to check the integrity of their data stored in Clouds. In addition, users can track the violation of data integrity if occurred. For this purpose, we utilize a relatively new concept in the Cloud computing called "Data Provenance". Our scheme is capable to reduce the need of any third party services, additional hardware support and the replication of data items on client side for integrity checking.
A microphysical pathway analysis to investigate aerosol effects on convective clouds
NASA Astrophysics Data System (ADS)
Heikenfeld, Max; White, Bethan; Labbouz, Laurent; Stier, Philip
2017-04-01
The impact of aerosols on ice- and mixed-phase processes in convective clouds remains highly uncertain, which has strong implications for estimates of the role of aerosol-cloud interactions in the climate system. The wide range of interacting microphysical processes are still poorly understood and generally not resolved in global climate models. To understand and visualise these processes and to conduct a detailed pathway analysis, we have added diagnostic output of all individual process rates for number and mass mixing ratios to two commonly-used cloud microphysics schemes (Thompson and Morrison) in WRF. This allows us to investigate the response of individual processes to changes in aerosol conditions and the propagation of perturbations throughout the development of convective clouds. Aerosol effects on cloud microphysics could strongly depend on the representation of these interactions in the model. We use different model complexities with regard to aerosol-cloud interactions ranging from simulations with different levels of fixed cloud droplet number concentration (CDNC) as a proxy for aerosol, to prognostic CDNC with fixed modal aerosol distributions. Furthermore, we have implemented the HAM aerosol model in WRF-chem to also perform simulations with a fully interactive aerosol scheme. We employ a hierarchy of simulation types to understand the evolution of cloud microphysical perturbations in atmospheric convection. Idealised supercell simulations are chosen to present and test the analysis methods for a strongly confined and well-studied case. We then extend the analysis to large case study simulations of tropical convection over the Amazon rainforest. For both cases we apply our analyses to individually tracked convective cells. Our results show the impact of model uncertainties on the understanding of aerosol-convection interactions and have implications for improving process representation in models.
Shen, Qinghua; Liang, Xiaohui; Shen, Xuemin; Lin, Xiaodong; Luo, Henry Y
2014-03-01
In this paper, we propose an e-health monitoring system with minimum service delay and privacy preservation by exploiting geo-distributed clouds. In the system, the resource allocation scheme enables the distributed cloud servers to cooperatively assign the servers to the requested users under the load balance condition. Thus, the service delay for users is minimized. In addition, a traffic-shaping algorithm is proposed. The traffic-shaping algorithm converts the user health data traffic to the nonhealth data traffic such that the capability of traffic analysis attacks is largely reduced. Through the numerical analysis, we show the efficiency of the proposed traffic-shaping algorithm in terms of service delay and privacy preservation. Furthermore, through the simulations, we demonstrate that the proposed resource allocation scheme significantly reduces the service delay compared to two other alternatives using jointly the short queue and distributed control law.
Attribution of the present-day total greenhouse effect
NASA Astrophysics Data System (ADS)
Schmidt, Gavin A.; Ruedy, Reto A.; Miller, Ron L.; Lacis, Andy A.
2010-10-01
The relative contributions of atmospheric long-wave absorbers to the present-day global greenhouse effect are among the most misquoted statistics in public discussions of climate change. Much of the interest in these values is however due to an implicit assumption that these contributions are directly relevant for the question of climate sensitivity. Motivated by the need for a clear reference for this issue, we review the existing literature and use the Goddard Institute for Space Studies ModelE radiation module to provide an overview of the role of each absorber at the present-day and under doubled CO2. With a straightforward scheme for allocating overlaps, we find that water vapor is the dominant contributor (˜50% of the effect), followed by clouds (˜25%) and then CO2 with ˜20%. All other absorbers play only minor roles. In a doubled CO2 scenario, this allocation is essentially unchanged, even though the magnitude of the total greenhouse effect is significantly larger than the initial radiative forcing, underscoring the importance of feedbacks from water vapor and clouds to climate sensitivity.
Identity-Based Authentication for Cloud Computing
NASA Astrophysics Data System (ADS)
Li, Hongwei; Dai, Yuanshun; Tian, Ling; Yang, Haomiao
Cloud computing is a recently developed new technology for complex systems with massive-scale services sharing among numerous users. Therefore, authentication of both users and services is a significant issue for the trust and security of the cloud computing. SSL Authentication Protocol (SAP), once applied in cloud computing, will become so complicated that users will undergo a heavily loaded point both in computation and communication. This paper, based on the identity-based hierarchical model for cloud computing (IBHMCC) and its corresponding encryption and signature schemes, presented a new identity-based authentication protocol for cloud computing and services. Through simulation testing, it is shown that the authentication protocol is more lightweight and efficient than SAP, specially the more lightweight user side. Such merit of our model with great scalability is very suited to the massive-scale cloud.
NASA Technical Reports Server (NTRS)
Cohen, Charles
1998-01-01
A method is developed which uses numerical tracers to make accurate diagnoses of entraimnent and detrainment rates and of the properties of the entrained and detrained air in numerically simulated clouds. The numerical advection scheme is modified to make it nondispersive, as required by the use of the tracers. Tests of the new method are made, and an appropriate definition of clouds is selected. Distributions of mixing fractions in the model consistently show maximums at the end points, for nearly undilute environmental air or nearly undilute cloud air, with a uniform distribution between. The cumulonimbus clouds simulated here entrain air that had been substantially changed by the clouds, and detrained air that is not necessarily representative of the cloud air at the same level.
NASA Astrophysics Data System (ADS)
Klaus, D.; Dethloff, K.; Dorn, W.; Rinke, A.; Wu, D. L.
2016-05-01
Cloud observations from the CloudSat and CALIPSO satellites helped to explain the reduced total cloud cover (Ctot) in the atmospheric regional climate model HIRHAM5 with modified cloud physics. Arctic climate conditions are found to be better reproduced with (1) a more efficient Bergeron-Findeisen process and (2) a more generalized subgrid-scale variability of total water content. As a result, the annual cycle of Ctot is improved over sea ice, associated with an almost 14% smaller area average than in the control simulation. The modified cloud scheme reduces the Ctot bias with respect to the satellite observations. Except for autumn, the cloud reduction over sea ice improves low-level temperature profiles compared to drifting station data. The HIRHAM5 sensitivity study highlights the need for improving accuracy of low-level (<700 m) cloud observations, as these clouds exert a strong impact on the near-surface climate.
Efficient Cryptography for the Next Generation Secure Cloud
ERIC Educational Resources Information Center
Kupcu, Alptekin
2010-01-01
Peer-to-peer (P2P) systems, and client-server type storage and computation outsourcing constitute some of the major applications that the next generation cloud schemes will address. Since these applications are just emerging, it is the perfect time to design them with security and privacy in mind. Furthermore, considering the high-churn…
NASA Astrophysics Data System (ADS)
Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.
2014-10-01
Purdue-Lin scheme is a relatively sophisticated microphysics scheme in the Weather Research and Forecasting (WRF) model. The scheme includes six classes of hydro meteors: water vapor, cloud water, raid, cloud ice, snow and graupel. The scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. In this paper, we accelerate the Purdue Lin scheme using Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi is a high performance coprocessor consists of up to 61 cores. The Xeon Phi is connected to a CPU via the PCI Express (PICe) bus. In this paper, we will discuss in detail the code optimization issues encountered while tuning the Purdue-Lin microphysics Fortran code for Xeon Phi. In particularly, getting a good performance required utilizing multiple cores, the wide vector operations and make efficient use of memory. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 4.2x. Furthermore, the same optimizations improved performance on Intel Xeon E5-2603 CPU by a factor of 1.2x compared to the original code.
Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud
Florence, A. Paulin; Shanthi, V.; Simon, C. B. Sunil
2016-01-01
Cloud computing is a new technology which supports resource sharing on a “Pay as you go” basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption. PMID:27239551
Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud.
Florence, A Paulin; Shanthi, V; Simon, C B Sunil
2016-01-01
Cloud computing is a new technology which supports resource sharing on a "Pay as you go" basis around the world. It provides various services such as SaaS, IaaS, and PaaS. Computation is a part of IaaS and the entire computational requests are to be served efficiently with optimal power utilization in the cloud. Recently, various algorithms are developed to reduce power consumption and even Dynamic Voltage and Frequency Scaling (DVFS) scheme is also used in this perspective. In this paper we have devised methodology which analyzes the behavior of the given cloud request and identifies the associated type of algorithm. Once the type of algorithm is identified, using their asymptotic notations, its time complexity is calculated. Using best fit strategy the appropriate host is identified and the incoming job is allocated to the victimized host. Using the measured time complexity the required clock frequency of the host is measured. According to that CPU frequency is scaled up or down using DVFS scheme, enabling energy to be saved up to 55% of total Watts consumption.
Sensitivity study of the wet deposition schemes in the modelling of the Fukushima accident.
NASA Astrophysics Data System (ADS)
Quérel, Arnaud; Quélo, Denis; Roustan, Yelva; Mathieu, Anne; Kajino, Mizuo; Sekiyama, Thomas; Adachi, Kouji; Didier, Damien; Igarashi, Yasuhito
2016-04-01
The Fukushima-Daiichi release of radioactivity is a relevant event to study the atmospheric dispersion modelling of radionuclides. Actually, the atmospheric deposition onto the ground may be studied through the map of measured Cs-137 established consecutively to the accident. The limits of detection were low enough to make the measurements possible as far as 250km from the nuclear power plant. This large scale deposition has been modelled with the Eulerian model ldX. However, several weeks of emissions in multiple weather conditions make it a real challenge. Besides, these measurements are accumulated deposition of Cs-137 over the whole period and do not inform of deposition mechanisms involved: in-cloud, below-cloud, dry deposition. A comprehensive sensitivity analysis is performed in order to understand wet deposition mechanisms. It has been shown in a previous study (Quérel et al, 2016) that the choice of the wet deposition scheme has a strong impact on the assessment of the deposition patterns. Nevertheless, a "best" scheme could not be highlighted as it depends on the selected criteria: the ranking differs according to the statistical indicators considered (correlation, figure of merit in space and factor 2). A possibility to explain the difficulty to discriminate between several schemes was the uncertainties in the modelling, resulting from the meteorological data for instance. Since the move of the plume is not properly modelled, the deposition processes are applied with an inaccurate activity in the air. In the framework of the SAKURA project, an MRI-IRSN collaboration, new meteorological fields at higher resolution (Sekiyama et al., 2013) were provided and allows to reconsider the previous study. An updated study including these new meteorology data is presented. In addition, a focus on several releases causing deposition in located areas during known period was done. This helps to better understand the mechanisms of deposition involved following the Fukushima release. Quérel et al, 2016, accepted for publication in IJEP Sekiyama et al., 2013, Ensemble simulation of the atmospheric radionuclides discharged by the Fukushima nuclear accident. Presented at the EGU General Assembly, Vienne, pp. EGU2013-1695.
NASA Astrophysics Data System (ADS)
Antón, M.; Kroon, M.; López, M.; Vilaplana, J. M.; Bañón, M.; van der A, R.; Veefkind, J. P.; Stammes, P.; Alados-Arboledas, L.
2011-11-01
This article focuses on the validation of the total ozone column (TOC) data set acquired by the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite remote sensing instruments using the Total Ozone Retrieval Scheme for the GOME Instrument Based on the Ozone Monitoring Instrument (TOGOMI) and Total Ozone Retrieval Scheme for the SCIAMACHY Instrument Based on the Ozone Monitoring Instrument (TOSOMI) retrieval algorithms developed by the Royal Netherlands Meteorological Institute. In this analysis, spatially colocated, daily averaged ground-based observations performed by five well-calibrated Brewer spectrophotometers at the Iberian Peninsula are used. The period of study runs from January 2004 to December 2009. The agreement between satellite and ground-based TOC data is excellent (R2 higher than 0.94). Nevertheless, the TOC data derived from both satellite instruments underestimate the ground-based data. On average, this underestimation is 1.1% for GOME and 1.3% for SCIAMACHY. The SCIAMACHY-Brewer TOC differences show a significant solar zenith angle (SZA) dependence which causes a systematic seasonal dependence. By contrast, GOME-Brewer TOC differences show no significant SZA dependence and hence no seasonality although processed with exactly the same algorithm. The satellite-Brewer TOC differences for the two satellite instruments show a clear and similar dependence on the viewing zenith angle under cloudy conditions. In addition, both the GOME-Brewer and SCIAMACHY-Brewer TOC differences reveal a very similar behavior with respect to the satellite cloud properties, being cloud fraction and cloud top pressure, which originate from the same cloud algorithm (Fast Retrieval Scheme for Clouds from the Oxygen A-Band (FRESCO+)) in both the TOSOMI and TOGOMI retrieval algorithms.
NASA Astrophysics Data System (ADS)
Song, Xiaoliang; Zhang, Guang J.
2018-03-01
Several improvements are implemented in the Zhang-McFarlane (ZM) convection scheme to investigate the roles of convection parameterization in the formation of double intertropical convergence zone (ITCZ) bias in the NCAR CESM1.2.1. It is shown that the prominent double ITCZ biases of precipitation, sea surface temperature (SST), and wind stress in the standard CESM1.2.1 are largely eliminated in all seasons with the use of these improvements in convection scheme. This study for the first time demonstrates that the modifications of convection scheme can eliminate the double ITCZ biases in all seasons, including boreal winter and spring. Further analysis shows that the elimination of the double ITCZ bias is achieved not by improving other possible contributors, such as stratus cloud bias off the west coast of South America and cloud/radiation biases over the Southern Ocean, but by modifying the convection scheme itself. This study demonstrates that convection scheme is the primary contributor to the double ITCZ bias in the CESM1.2.1, and provides a possible solution to the long-standing double ITCZ problem. The atmospheric model simulations forced by observed SST show that the original ZM convection scheme tends to produce double ITCZ bias in high SST scenario, while the modified convection scheme does not. The impact of changes in each core component of convection scheme on the double ITCZ bias in atmospheric model is identified and further investigated.
a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery
NASA Astrophysics Data System (ADS)
Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.
2018-04-01
Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.
NASA Astrophysics Data System (ADS)
Cesana, G.; Waliser, D. E.; Jiang, X.; Li, J. L. F.
2014-12-01
The ubiquitous presence of clouds within the troposphere contributes to modulate the radiative balance of the earth-atmosphere system. Depending on their cloud phase, clouds may have different microphysical and macrophysical properties, and hence, different radiative effects. In this study, we took advantage of climate runs from the GASS-YoTC and AMIP multi-model experiments to document the differences associated to the cloud phase parameterizations of 16 GCMs. A particular emphasize has been put on the vertical structure of the transition between liquid and ice in clouds. A way to intercompare the models regardless of their cloud fraction is to study the ratio of the ice mass to the total mass of the condensed water. To address the challenge of evaluating the modeled cloud phase, we profited from the cloud phase climatology so called CALIPSO-GOCCP, which separates liquid clouds from ice clouds at global scale, with a high vertical resolution (480m), above all surfaces. We also used reanalysis data and GPCP satellite observations to investigate the influence of the temperature, the relative humidity, the vertical wind speed and the precipitations on the cloud phase transition. In 12 (of 16) models, there are too few super cooled liquid in clouds compared to observations, mostly in the high troposphere. We exhibited evidences of the link between the cloud phase transition and the humidity, the vertical wind speed as well as the precipitations. Some cloud phase schemes are more affected by the humidity and the vertical velocity and some other by the precipitations. Although a few models can reproduce the observe relation between cloud phase and temperature, humidity, vertical velocity or precipitations, none of them perform well for all the parameters. An important result of this study is that the T-dependent phase parameterizations do not allow simulating the complexity of the observed cloud phase transition. Unfortunately, more complex microphysics schemes do not succeed to reproduce all the processes neither. Finally, thanks to the combined use of CALIPSO-GOCCP and ECMWF water vapor pressure, we showed an updated version of the Clausius-Clapeyron water vapor phase diagram. This diagram represents a new tool to improve the simulation of the cloud phase transition in climate models.
Evaluation and Applications of Cloud Climatologies from CALIOP
NASA Technical Reports Server (NTRS)
Winker, David; Getzewitch, Brian; Vaughan, Mark
2008-01-01
Clouds have a major impact on the Earth radiation budget and differences in the representation of clouds in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing cloud climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous cloud and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average cloud cover measured by CALIOP is about 75%, significantly higher than for existing cloud climatologies due to the sensitivity of CALIOP to optically thin cloud. Day/night biases in cloud detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a cloud climatology, characteristics of cloud cover statistics derived from CALIOP data, and applications of those statistics.
Process-model Simulations of Cloud Albedo Enhancement by Aerosols in the Arctic
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kravitz, Benjamin S.; Wang, Hailong; Rasch, Philip J.
2014-11-17
A cloud-resolving model is used to simulate the effectiveness of Arctic marine cloud brightening via injection of cloud condensation nuclei (CCN). 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. Because nearly all of the albedo effects are in the liquid phase due to the removal of ice water by snowfall when ice processes are involved, albedo increases are stronger for pure liquid clouds than mixed-phase clouds.more » 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 due to precipitation changes are small.« less
Lee, Tian-Fu; Wang, Zeng-Bo
2017-01-01
The security is a critical issue for business purposes. For example, the cloud meeting must consider strong security to maintain the communication privacy. Considering the scenario with cloud meeting, we apply extended chaotic map to present passwordless group authentication key agreement, termed as Passwordless Group Authentication Key Agreement (PL-GAKA). PL-GAKA improves the computation efficiency for the simple group password-based authenticated key agreement (SGPAKE) proposed by Lee et al. in terms of computing the session key. Since the extended chaotic map has equivalent security level to the Diffie–Hellman key exchange scheme applied by SGPAKE, the security of PL-GAKA is not sacrificed when improving the computation efficiency. Moreover, PL-GAKA is a passwordless scheme, so the password maintenance is not necessary. Short-term authentication is considered, hence the communication security is stronger than other protocols by dynamically generating session key in each cloud meeting. In our analysis, we first prove that each meeting member can get the correct information during the meeting. We analyze common security issues for the proposed PL-GAKA in terms of session key security, mutual authentication, perfect forward security, and data integrity. Moreover, we also demonstrate that communicating in PL-GAKA is secure when suffering replay attacks, impersonation attacks, privileged insider attacks, and stolen-verifier attacks. Eventually, an overall comparison is given to show the performance between PL-GAKA, SGPAKE and related solutions. PMID:29207509
Cross stratum resources protection in fog-computing-based radio over fiber networks for 5G services
NASA Astrophysics Data System (ADS)
Guo, Shaoyong; Shao, Sujie; Wang, Yao; Yang, Hui
2017-09-01
In order to meet the requirement of internet of things (IoT) and 5G, the cloud radio access network is a paradigm which converges all base stations computational resources into a cloud baseband unit (BBU) pool, while the distributed radio frequency signals are collected by remote radio head (RRH). A precondition for centralized processing in the BBU pool is an interconnection fronthaul network with high capacity and low delay. However, it has become more complex and frequent in the interaction between RRH and BBU and resource scheduling among BBUs in cloud. Cloud radio over fiber network has been proposed in our previous work already. In order to overcome the complexity and latency, in this paper, we first present a novel cross stratum resources protection (CSRP) architecture in fog-computing-based radio over fiber networks (F-RoFN) for 5G services. Additionally, a cross stratum protection (CSP) scheme considering the network survivability is introduced in the proposed architecture. The CSRP with CSP scheme can effectively pull the remote processing resource locally to implement the cooperative radio resource management, enhance the responsiveness and resilience to the dynamic end-to-end 5G service demands, and globally optimize optical network, wireless and fog resources. The feasibility and efficiency of the proposed architecture with CSP scheme are verified on our software defined networking testbed in terms of service latency, transmission success rate, resource occupation rate and blocking probability.
NASA Astrophysics Data System (ADS)
Hsu, Kuo-Hsien
2012-11-01
Formosat-2 image is a kind of high-spatial-resolution (2 meters GSD) remote sensing satellite data, which includes one panchromatic band and four multispectral bands (Blue, Green, Red, near-infrared). An essential sector in the daily processing of received Formosat-2 image is to estimate the cloud statistic of image using Automatic Cloud Coverage Assessment (ACCA) algorithm. The information of cloud statistic of image is subsequently recorded as an important metadata for image product catalog. In this paper, we propose an ACCA method with two consecutive stages: preprocessing and post-processing analysis. For pre-processing analysis, the un-supervised K-means classification, Sobel's method, thresholding method, non-cloudy pixels reexamination, and cross-band filter method are implemented in sequence for cloud statistic determination. For post-processing analysis, Box-Counting fractal method is implemented. In other words, the cloud statistic is firstly determined via pre-processing analysis, the correctness of cloud statistic of image of different spectral band is eventually cross-examined qualitatively and quantitatively via post-processing analysis. The selection of an appropriate thresholding method is very critical to the result of ACCA method. Therefore, in this work, We firstly conduct a series of experiments of the clustering-based and spatial thresholding methods that include Otsu's, Local Entropy(LE), Joint Entropy(JE), Global Entropy(GE), and Global Relative Entropy(GRE) method, for performance comparison. The result shows that Otsu's and GE methods both perform better than others for Formosat-2 image. Additionally, our proposed ACCA method by selecting Otsu's method as the threshoding method has successfully extracted the cloudy pixels of Formosat-2 image for accurate cloud statistic estimation.
NASA Technical Reports Server (NTRS)
Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.;
2006-01-01
If the aerosol composition and size distribution below cloud are uniform, the vertical profile of cloud condensation nuclei (CCN) concentration can be retrieved entirely from surface measurements of CCN concentration and particle humidification function and surface-based retrievals of relative humidity and aerosol extinction or backscatter. This provides the potential for long-term measurements of CCN concentrations near cloud base. We have used a combination of aircraft, surface in situ, and surface remote sensing measurements to test various aspects of the retrieval scheme. Our analysis leads us to the following conclusions. The retrieval works better for supersaturations of 0.1% than for 1% because CCN concentrations at 0.1% are controlled by the same particles that control extinction and backscatter. If in situ measurements of extinction are used, the retrieval explains a majority of the CCN variance at high supersaturation for at least two and perhaps five of the eight flights examined. The retrieval of the vertical profile of the humidification factor is not the major limitation of the CCN retrieval scheme. Vertical structure in the aerosol size distribution and composition is the dominant source of error in the CCN retrieval, but this vertical structure is difficult to measure from remote sensing at visible wavelengths.
Yang, Hui; He, Yongqi; Zhang, Jie; Ji, Yuefeng; Bai, Wei; Lee, Young
2016-04-18
Cloud radio access network (C-RAN) has become a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing using cloud BBUs. In our previous work, we implemented cross stratum optimization of optical network and application stratums resources that allows to accommodate the services in optical networks. In view of this, this study extends to consider the multiple dimensional resources optimization of radio, optical and BBU processing in 5G age. We propose a novel multi-stratum resources optimization (MSRO) architecture with network functions virtualization for cloud-based radio over optical fiber networks (C-RoFN) using software defined control. A global evaluation scheme (GES) for MSRO in C-RoFN is introduced based on the proposed architecture. The MSRO can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical and BBU resources effectively to maximize radio coverage. The efficiency and feasibility of the proposed architecture are experimentally demonstrated on OpenFlow-based enhanced SDN testbed. The performance of GES under heavy traffic load scenario is also quantitatively evaluated based on MSRO architecture in terms of resource occupation rate and path provisioning latency, compared with other provisioning scheme.
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man; Wong, Takmeng; Wielicki, Bruce a.; Parker, Lindsay; Lin, Bing; Eitzen, Zachary A.; Branson, Mark
2006-01-01
Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January-August 1998 are examined using the Tropical Rainfall Measuring Mission/ Clouds and the Earth s Radiant Energy System single scanner footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud-object size, sea surface temperature (SST), and satellite precessing cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the Earth composed of satellite footprints within a single dominant cloud-system type. It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100 - 150 km (small), 150 - 300 km (medium), and > 300 km (large), respectively, except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed towards high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precessing cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This result suggests that the fixed anvil temperature hypothesis of Hartmann and Larson may be valid for the large-size category. Combining with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SSTs where large-scale dynamics plays important roles, statistical characteristics of cloud microphysical properties, optical depth and albedo are not sensitive to the SST, but those of cloud macrophysical properties are strongly dependent upon the SST. Frequency distributions of vertical velocity from the European Center for Medium-range Weather Forecasts model that is matched to each cloud object are used to interpret some of the findings in this study.
Application of microarray analysis on computer cluster and cloud platforms.
Bernau, C; Boulesteix, A-L; Knaus, J
2013-01-01
Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.
NASA Technical Reports Server (NTRS)
Weinman, James A.; Garan, Louis
1987-01-01
A more advanced cloud pattern analysis algorithm was subsequently developed to take the shape and brightness of the various clouds into account in a manner that is more consistent with the human analyst's perception of GOES cloud imagery. The results of that classification scheme were compared with precipitation probabilities observed from ships of opportunity off the U.S. east coast to derive empirical regressions between cloud types and precipitation probability. The cloud morphology was then quantitatively and objectively used to map precipitation probabilities during two winter months during which severe cold air outbreaks were observed over the northwest Atlantic. Precipitation probabilities associated with various cloud types are summarized. Maps of precipitation probability derived from the cloud morphology analysis program for two months and the precipitation probability derived from thirty years of ship observation were observed.
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Li, X.; Khain, A.; Simpson, S.
2005-01-01
Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds, Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, a detailed spectral-bin microphysical scheme was implemented into the the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.
A scheme for parameterizing ice cloud water content in general circulation models
NASA Technical Reports Server (NTRS)
Heymsfield, Andrew J.; Donner, Leo J.
1989-01-01
A method for specifying ice water content in GCMs is developed, based on theory and in-cloud measurements. A theoretical development of the conceptual precipitation model is given and the aircraft flights used to characterize the ice mass distribution in deep ice clouds is discussed. Ice water content values derived from the theoretical parameterization are compared with the measured values. The results demonstrate that a simple parameterization for atmospheric ice content can account for ice contents observed in several synoptic contexts.
A Comprehensive Two-moment Warm Microphysical Bulk Scheme :
NASA Astrophysics Data System (ADS)
Caro, D.; Wobrock, W.; Flossmann, A.; Chaumerliac, N.
The microphysic properties of gaz, aerosol particles, and hydrometeors have impli- cations at local scale (precipitations, pollution peak,..), at regional scale (inundation, acid rains,...), and also, at global scale (radiative forcing,...). So, a multi-scale study is necessary to understand and forecast in a good way meteorological phenomena con- cerning clouds. However, it cannot be carried with detailed microphysic model, on account of computers limitations. So, microphysical bulk schemes have to estimate the n´ large scale z properties of clouds due to smaller scale processes and charac- teristics. So, the development of such bulk scheme is rather important to go further in the knowledge of earth climate and in the forecasting of intense meteorological phenomena. Here, a quasi-spectral microphysic warm scheme has been developed to predict the concentrations and mixing ratios of aerosols, cloud droplets and raindrops. It considers, explicitely and analytically, the nucleation of droplets (Abdul-Razzak et al., 2000), condensation/evaporation (Chaumerliac et al., 1987), the breakup and collision-coalescence processes with the Long (1974) Ss kernels and the Berry and ´ Reinhardt (1974) Ss autoconversion parameterization, but also, the aerosols and gaz ´ scavenging. First, the parameterization has been estimated in the simplest dynamic framework of an air parcel model, with the results of the detailed scavenging model, DESCAM (Flossmann et al., 1985). Then, it has been tested, in the dynamic frame- work of a kinematic model (Szumowski et al., 1998) dedicated to the HaRP cam- paign (Hawaiian Rainband Project, 1990), with the observations and with the results of the two dimensional detailed microphysic scheme, DESCAM 2-D (Flossmann et al., 1988), implement in the CLARK model (Clark and Farley, 1984).
Fan, Jiwen; Han, Bin; Varble, Adam; ...
2017-09-06
An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Z e > 45 dBZ) than observed but a much narrower stratiform area. Furthermore, the magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speedmore » are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Z e in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low-level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low-level vertical wind shear, and rear-inflow jets. We found that updraft velocity variability between schemes is mainly controlled by differences in simulated ice-related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no-ice simulations mainly because of scheme differences in collision-coalescence parameterizations.« less
NASA Technical Reports Server (NTRS)
Cummings, Kristin A.; Pickering, Kenneth E.; Barth, M.; Weinheimer, A.; Bela, M.; Li, Y.; Allen, D.; Bruning, E.; MacGorman, D.; Rutledge, S.;
2014-01-01
The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were added to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.
NASA Technical Reports Server (NTRS)
Cummings, Kristin A.; Pickering, Kenneth E.; Barth, M.; Weinheimer, A.; Bela, M.; Li, Y.; Allen, D.; Bruning, E.; MacGorman, D.; Rutledge, S.;
2014-01-01
The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). Based on the measurements taken of the 29-30 May 2012 Oklahoma thunderstorm, an analysis against a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the same event at 3-km horizontal resolution was performed. One of the main objectives was to include various flash rate parameterization schemes (FRPSs) in the model and identify which scheme(s) best captured the flash rates observed by the National Lightning Detection Network (NLDN) and Oklahoma Lightning Mapping Array (LMA). The comparison indicates how well the schemes predicted the timing, location, and number of lightning flashes. The FRPSs implemented in the model were based on the simulated thunderstorms physical features, such as maximum vertical velocity, cloud top height, and updraft volume. Adjustment factors were applied to each FRPS to best capture the observed flash trend and a sensitivity study was performed to compare the range in model-simulated lightning-generated nitrogen oxides (LNOx) generated by each FRPS over the storms lifetime. Based on the best FRPS, model-simulated LNOx was compared against aircraft measured NOx. The trace gas analysis, along with the increased detail in the model specification of the vertical distribution of lightning flashes as suggested by the LMA data, provide guidance in determining the scenario of NO production per intracloud and cloud-to-ground flash that best matches the NOx mixing ratios observed by the aircraft.
A Systematic Survey of Star Formation with the ORION MIDEX Mission
NASA Astrophysics Data System (ADS)
Scowen, P.; Morse, J.; Beasley, M.; Hester, J.; Windhorst, R.; Desch, S.; Jansen, R.; Calzetti, D.; Padgett, D.; Hartigan, P.; Oey, S.; Bally, J.; Gallagher, J.; O'Connell, R.; Kennicutt, R.; Lauer, T.
2004-05-01
The ORION MIDEX mission is a 1.2m UV-visual observatory orbiting at L2 that will conduct the first-ever high spatial resolution survey of a statistically significant sample of visible star-forming environments in the Solar neighborhood in emission lines and continuum. This survey will be used to characterize the star and planet forming environments within 2.5 kpc of the Sun, infer global properties and star formation history in these regions, understand how the environment influences the process of star and planet formation, and develop a classification scheme for star forming regions incorporating the earlier results. Based on these findings we will then conduct a similar high spatial resolution survey of large portions of the Magellanic Clouds, applying the classification scheme from local star forming environments to analogous regions in nearby galaxies, extending the classification scheme to regions that do not have nearby analogs but are common in external galaxies. The results from the local survey will allow us to infer characteristics of low mass star forming environments in the Magellanic Clouds, study the spatial distribution of star forming environments and analyze stellar population photometry to trace star formation history. Finally we will image a representative sample of external galaxies using the same filters used to characterize nearby star formation regions. We will map the distribution of star forming region type as a function of galactic environment for galaxies out to 5 Mpc to infer the distribution and history of low-mass star formation over galactic scales, characterize the stellar content and star formation history of galaxies, and relate these results to the current star forming environments in these galaxies. Ultimately we intend to use these diagnostics to extrapolate to star formation environments in the higher redshift Universe. We will also present an update on the technology development, project planning and operations for the proposed mission.
Space-based Observations of Star Formation using ORION: THE MIDEX
NASA Astrophysics Data System (ADS)
Scowen, P.; Morse, J.; Beasley, M.; Hester, J.; Windhorst, R.; Jansen, R.; Lauer, T.; Danielson, E.; Sepulveda, C.; Olarte, G.; ORION MIDEX Science Team
2003-12-01
The ORION MIDEX mission is a 1.2m UV-visual observatory orbiting at L2 that will conduct the first-ever high spatial resolution survey of a statistically significant sample of visible star-forming environments in the Solar neighborhood in emission lines and continuum. This survey will be used to characterize the star and planet forming environments within 2.5 kpc of the Sun, infer global properties and star formation history in these regions, understand how the environment influences the process of star and planet formation, and develop a classification scheme for star forming regions incorporating the earlier results. Based on these findings we will then conduct a similar high spatial resolution survey of large portions of the Magellanic Clouds, applying the classification scheme from local star forming environments to analogous regions in nearby galaxies, extending the classification scheme to regions that do not have nearby analogs but are common in external galaxies. The results from the local survey will allow us to infer characteristics of low mass star forming environments in the Magellanic Clouds, study the spatial distribution of star forming environments and analyze stellar population photometry to trace star formation history. Finally we will image a representative sample of external galaxies using the same filters used to characterize nearby star formation regions. We will map the distribution of star forming region type as a function of galactic environment for galaxies out to 5 Mpc to infer the distribution and history of low-mass star formation over galactic scales, characterize the stellar content and star formation history of galaxies, and relate these results to the current star forming environments in these galaxies. Ultimately we intend to use these diagnostics to extrapolate to star formation environments in the higher redshift Universe. We will also present details on technology development, project planning and operations for the proposed mission.
ORION: Hierarchical Space-based Observations of Star Formation, From Near to Far
NASA Astrophysics Data System (ADS)
Scowen, P. A.; Morse, J. A.; Beasley, M.; Veach, T.; ORION Science Team
2005-12-01
The ORION MIDEX mission is a 1.2m UV-visual observatory orbiting at L2 that will conduct the first-ever high spatial resolution survey of a statistically significant sample of visible star-forming environments in the Solar neighborhood in emission lines and continuum. This survey will be used to characterize the star and planet forming environments within 2.5 kpc of the Sun, infer global properties and star formation history in these regions, understand how the environment influences the process of star and planet formation, and develop a classification scheme for star forming regions incorporating the earlier results. Based on these findings we will then conduct a similar high spatial resolution survey of large portions of the Magellanic Clouds, applying the classification scheme from local star forming environments to analogous regions in nearby galaxies, extending the classification scheme to regions that do not have nearby analogs but are common in external galaxies. The results from the local survey will allow us to infer characteristics of low mass star forming environments in the Magellanic Clouds, study the spatial distribution of star forming environments and analyze stellar population photometry to trace star formation history. Finally we will image a representative sample of external galaxies using the same filters used to characterize nearby star formation regions. We will map the distribution of star forming region type as a function of galactic environment for galaxies out to 5 Mpc to infer the distribution and history of low-mass star formation over galactic scales, characterize the stellar content and star formation history of galaxies, and relate these results to the current star forming environments in these galaxies. Ultimately we intend to use these diagnostics to extrapolate to star formation environments in the higher redshift Universe. We will also present details on technology development, project planning and operations for the proposed mission.
A Systematic Survey of Star Formation with the ORION MIDEX Mission
NASA Astrophysics Data System (ADS)
Scowen, P.; Morse, J.; Beasley, M.; Hester, J.; Windhorst, R.; Desch, S.; Jansen, R.; Calzetti, D.; Padgett, D.; Hartigan, P.; Oey, S.; Bally, J.; Gallagher, J.; O'Connell, R.; Kennicutt, R.; Lauer, T.; McCaughrean, M.
2004-12-01
The ORION MIDEX mission is a 1.2m UV-visual observatory orbiting at L2 that will conduct the first-ever high spatial resolution survey of a statistically significant sample of visible star-forming environments in the Solar neighborhood in emission lines and continuum. This survey will be used to characterize the star and planet forming environments within 2.5 kpc of the Sun, infer global properties and star formation history in these regions, understand how the environment influences the process of star and planet formation, and develop a classification scheme for star forming regions incorporating the earlier results. Based on these findings we will then conduct a similar high spatial resolution survey of large portions of the Magellanic Clouds, applying the classification scheme from local star forming environments to analogous regions in nearby galaxies, extending the classification scheme to regions that do not have nearby analogs but are common in external galaxies. The results from the local survey will allow us to infer characteristics of low mass star forming environments in the Magellanic Clouds, study the spatial distribution of star forming environments and analyze stellar population photometry to trace star formation history. Finally we will image a representative sample of external galaxies using the same filters used to characterize nearby star formation regions. We will map the distribution of star forming region type as a function of galactic environment for galaxies out to 5 Mpc to infer the distribution and history of low-mass star formation over galactic scales, characterize the stellar content and star formation history of galaxies, and relate these results to the current star forming environments in these galaxies. Ultimately we intend to use these diagnostics to extrapolate to star formation environments in the higher redshift Universe. We will also present an update on the technology development, project planning and operations for the proposed mission.
Clustering, randomness, and regularity in cloud fields. 4. Stratocumulus cloud fields
NASA Astrophysics Data System (ADS)
Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.
1994-07-01
To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (>900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.
Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields
NASA Technical Reports Server (NTRS)
Lee, J.; Chou, J.; Weger, R. C.; Welch, R. M.
1994-01-01
To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.
An efficient quantum scheme for Private Set Intersection
NASA Astrophysics Data System (ADS)
Shi, Run-hua; Mu, Yi; Zhong, Hong; Cui, Jie; Zhang, Shun
2016-01-01
Private Set Intersection allows a client to privately compute set intersection with the collaboration of the server, which is one of the most fundamental and key problems within the multiparty collaborative computation of protecting the privacy of the parties. In this paper, we first present a cheat-sensitive quantum scheme for Private Set Intersection. Compared with classical schemes, our scheme has lower communication complexity, which is independent of the size of the server's set. Therefore, it is very suitable for big data services in Cloud or large-scale client-server networks.
The atmospheric boundary layer — advances in knowledge and application
NASA Astrophysics Data System (ADS)
Garratt, J. R.; Hess, G. D.; Physick, W. L.; Bougeault, P.
1996-02-01
We summarise major activities and advances in boundary-layer knowledge in the 25 years since 1970, with emphasis on the application of this knowledge to surface and boundary-layer parametrisation schemes in numerical models of the atmosphere. Progress in three areas is discussed: (i) the mesoscale modelling of selected phenomena; (ii) numerical weather prediction; and (iii) climate simulations. Future trends are identified, including the incorporation into models of advanced cloud schemes and interactive canopy schemes, and the nesting of high resolution boundary-layer schemes in global climate models.
High-resolution weather forecasting is affected by many aspects, i.e. model initial conditions, subgrid-scale cumulus convection and cloud microphysics schemes. Recent 12km grid studies using the Weather Research and Forecasting (WRF) model have identified the importance of inco...
A QR Code Based Zero-Watermarking Scheme for Authentication of Medical Images in Teleradiology Cloud
Seenivasagam, V.; Velumani, R.
2013-01-01
Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)—Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks. PMID:23970943
Seenivasagam, V; Velumani, R
2013-01-01
Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)-Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kollias, Pavlos
This is a multi-institutional, collaborative project using a three-tier modeling approach to bridge field observations and global cloud-permitting models, with emphases on cloud population structural evolution through various large-scale environments. Our contribution was in data analysis for the generation of high value cloud and precipitation products and derive cloud statistics for model validation. There are two areas in data analysis that we contributed: the development of a synergistic cloud and precipitation cloud classification that identify different cloud (e.g. shallow cumulus, cirrus) and precipitation types (shallow, deep, convective, stratiform) using profiling ARM observations and the development of a quantitative precipitation ratemore » retrieval algorithm using profiling ARM observations. Similar efforts have been developed in the past for precipitation (weather radars), but not for the millimeter-wavelength (cloud) radar deployed at the ARM sites.« less
Shallow cloud statistics over Tropical Western Pacific: CAM5 versus ARM Comparison
NASA Astrophysics Data System (ADS)
Chandra, A.; Zhang, C.; Klein, S. A.; Ma, H. Y.; Kollias, P.; Xie, S.
2014-12-01
The role of shallow convection in the tropical convective cloud life cycle has received increasing interest because of its sensitivity to simulate large-scale tropical disturbances such as MJO. Though previous studies have proposed several hypotheses to explain the role of shallow clouds in the convective life cycle, our understanding on the role of shallow clouds is still premature. There are more questions needs to be addressed related to the role of different cloud population, conditions favorable for shallow to deep convection transitions, and their characteristics at different stages of the convective cloud life. The present study aims to improve the understanding of the shallow clouds by documenting the role of different shallow cloud population for the Year of Tropical Convection period using Atmospheric Radiation Measurement observations at the Tropical Western Pacific Manus site. The performance of the CAM5 model to simulate shallow clouds are tested using observed cloud statistics.
Li, Zhengqiang; Li, Kaitao; Li, Li; Xu, Hua; Xie, Yisong; Ma, Yan; Li, Donghui; Goloub, Philippe; Yuan, Yinlin; Zheng, Xiaobing
2018-02-10
Polarization observation of sky radiation is the frontier approach to improve the remote sensing of atmospheric components, e.g., aerosol and clouds. The polarization calibration of the ground-based Sun-sky radiometer is the basis for obtaining accurate degree of linear polarization (DOLP) measurement. In this paper, a DOLP calibration method based on a laboratory polarized light source (POLBOX) is introduced in detail. Combined with the CE318-DP Sun-sky polarized radiometer, a calibration scheme for DOLP measurement is established for the spectral range of 440-1640 nm. Based on the calibration results of the Sun-sky radiometer observation network, the polarization calibration coefficient and the DOLP calibration residual are analyzed statistically. The results show that the DOLP residual of the calibration scheme is about 0.0012, and thus it can be estimated that the final DOLP calibration accuracy of this method is about 0.005. Finally, it is verified that the accuracy of the calibration results is in accordance with the expected results by comparing the simulated DOLP with the vector radiative transfer calculations.
Jets and Water Clouds on Jupiter
NASA Astrophysics Data System (ADS)
Lian, Yuan; Showman, A. P.
2012-10-01
Ground-based and spacecraft observations show that Jupiter exhibits multiple banded zonal jet structures. These banded jets correlate with dark and bright clouds, often called "belts" and "zones". The mechanisms that produce these banded zonal jets and clouds are poorly understood. Our previous studies showed that the latent heat released by condensation of water vapor could produce equatorial superrotation along with multiple zonal jets in the mid-to-high latitudes. However, that previous work assumed complete and instant removal of condensate and therefore could not predict the cloud formation. Here we present an improved 3D Jupiter model to investigate some effects of cloud microphysics on large-scale dynamics using a closed water cycle that includes condensation, three-dimensional advection of cloud material by the large-scale circulation, evaporation and sedimentation. We use a dry convective adjustment scheme to adjust the temperature towards a dry adiabat when atmospheric columns become convectively unstable, and the tracers are mixed within the unstable layers accordingly. Other physics parameterizations included in our model are the bottom drag and internal heat flux as well as the choices of either Newtonian heating scheme or gray radiative transfer. Given the poorly understood cloud microphysics, we perform case studies by treating the particle size and condensation/evaporation time scale as free parameters. We find that, in some cases, the active water cycle can produce multiple banded jets and clouds. However, the equatorial jet is generally very weak in all the cases because of insufficient supply of eastward eddy momentum fluxes. These differences may result from differences in the overall vertical stratification, baroclinicity, and moisture distribution in our new models relative to the older ones; we expect to elucidate the dynamical mechanisms in continuing work.
Retrieval of cloud properties from POLDER-3 data using the neural network approach
NASA Astrophysics Data System (ADS)
Di Noia, A.; Hasekamp, O. P.
2017-12-01
Satellite multi-angle spectroplarimetry is a useful technique for observing the microphysical properties of clouds and aerosols. Most of the algorithms for the retrieval of cloud and aerosol properties from satellite measurements require multiple calls to radiative transfer models, which make the retrieval computationally expensive. A traditional alternative to these schemes is represented by lookup-tables (LUTs), where the retrieval is performed by choosing, within a predefined database of combinations of clouds or aerosol properties, the combination that best fits the measurements. LUT retrievals are quicker than full-physics, iterative retrievals, but their accuracy is limited by the number of entries stored in the LUT. Another retrieval method capable of producing very quick retrievals without a big sacrifice in accuracy is the neural network method. Neural network methods are routinely applied to several types of satellite measurements, but their application to multi-angle spectropolarimetric data is still in its early stage, because of the difficulty of accounting for the angular variability of the measurements in the training process. We have recently developed a neural network scheme for the retrieval of cloud properties from POLDER-3 data. The neural network retrieval is trained using synthetic measurements performed for realistic combinations of cloud properties and measurement angles, and is able to process an entire orbit in about 20 seconds. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products during one year show encouraging retrieval performance for cloud optical thickness and effective radius. A discussion of the setup of the neural network and of the validation results will be the main topic of our presentation.
NASA Astrophysics Data System (ADS)
Saide, Pablo E.; Thompson, Gregory; Eidhammer, Trude; da Silva, Arlindo M.; Pierce, R. Bradley; Carmichael, Gregory R.
2016-09-01
We use the Weather Research and Forecasting (WRF) system to study the impacts of biomass burning smoke from Central America on several tornado outbreaks occurring in the U.S. during spring. The model is configured with an aerosol-aware microphysics parameterization capable of resolving aerosol-cloud-radiation interactions in a cost-efficient way for numerical weather prediction (NWP) applications. Primary aerosol emissions are included, and smoke emissions are constrained using an inverse modeling technique and satellite-based aerosol optical depth observations. Simulations turning on and off fire emissions reveal smoke presence in all tornado outbreaks being studied and show an increase in aerosol number concentrations due to smoke. However, the likelihood of occurrence and intensification of tornadoes is higher due to smoke only in cases where cloud droplet number concentration in low-level clouds increases considerably in a way that modifies the environmental conditions where the tornadoes are formed (shallower cloud bases and higher low-level wind shear). Smoke absorption and vertical extent also play a role, with smoke absorption at cloud-level tending to burn-off clouds and smoke absorption above clouds resulting in an increased capping inversion. Comparing these and WRF-Chem simulations configured with a more complex representation of aerosol size and composition and different optical properties, microphysics, and activation schemes, we find similarities in terms of the simulated aerosol optical depths and aerosol impacts on near-storm environments. This provides reliability on the aerosol-aware microphysics scheme as a less computationally expensive alternative to WRF-Chem for its use in applications such as NWP and cloud-resolving simulations.
Saide, Pablo E.; Thompson, Gregory; Eidhammer, Trude; da Silva, Arlindo M.; Pierce, R. Bradley; Carmichael, Gregory R.
2018-01-01
We use the WRF system to study the impacts of biomass burning smoke from Central America on several tornado outbreaks occurring in the US during spring. The model is configured with an aerosol-aware microphysics parameterization capable of resolving aerosol-cloud-radiation interactions in a cost-efficient way for numerical weather prediction (NWP) applications. Primary aerosol emissions are included and smoke emissions are constrained using an inverse modeling technique and satellite-based AOD observations. Simulations turning on and off fire emissions reveal smoke presence in all tornado outbreaks being studied and show an increase in aerosol number concentrations due to smoke. However, the likelihood of occurrence and intensification of tornadoes is higher due to smoke only in cases where cloud droplet number concentration in low level clouds increases considerably in a way that modifies the environmental conditions where the tornadoes are formed (shallower cloud bases and higher low-level wind shear). Smoke absorption and vertical extent also play a role, with smoke absorption at cloud-level tending to burn-off clouds and smoke absorption above clouds resulting in an increased capping inversion. Comparing these and WRF-Chem simulations configured with a more complex representation of aerosol size and composition and different optical properties, microphysics and activation schemes, we find similarities in terms of the simulated aerosol optical depths and aerosol impacts on near-storm environments. This provides reliability on the aerosol-aware microphysics scheme as a less computationally expensive alternative to WRF-Chem for its use in applications such as NWP and cloud-resolving simulations. PMID:29619287
HTML5 microdata as a semantic container for medical information exchange.
Kimura, Eizen; Kobayashi, Shinji; Ishihara, Ken
2014-01-01
Achieving interoperability between clinical electronic medical records (EMR) systems and cloud computing systems is challenging because of the lack of a universal reference method as a standard for information exchange with a secure connection. Here we describe an information exchange scheme using HTML5 microdata, where the standard semantic container is an HTML document. We embed HL7 messages describing laboratory test results in the microdata. We also annotate items in the clinical research report with the microdata. We mapped the laboratory test result data into the clinical research report using an HL7 selector specified in the microdata. This scheme can provide secure cooperation between the cloud-based service and the EMR system.
Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds.
Pressel, Kyle G; Mishra, Siddhartha; Schneider, Tapio; Kaul, Colleen M; Tan, Zhihong
2017-06-01
Stratocumulus clouds are the most common type of boundary layer cloud; their radiative effects strongly modulate climate. Large eddy simulations (LES) of stratocumulus clouds often struggle to maintain fidelity to observations because of the sharp gradients occurring at the entrainment interfacial layer at the cloud top. The challenge posed to LES by stratocumulus clouds is evident in the wide range of solutions found in the LES intercomparison based on the DYCOMS-II field campaign, where simulated liquid water paths for identical initial and boundary conditions varied by a factor of nearly 12. Here we revisit the DYCOMS-II RF01 case and show that the wide range of previous LES results can be realized in a single LES code by varying only the numerical treatment of the equations of motion and the nature of subgrid-scale (SGS) closures. The simulations that maintain the greatest fidelity to DYCOMS-II observations are identified. The results show that using weighted essentially non-oscillatory (WENO) numerics for all resolved advective terms and no explicit SGS closure consistently produces the highest-fidelity simulations. This suggests that the numerical dissipation inherent in WENO schemes functions as a high-quality, implicit SGS closure for this stratocumulus case. Conversely, using oscillatory centered difference numerical schemes for momentum advection, WENO numerics for scalars, and explicitly modeled SGS fluxes consistently produces the lowest-fidelity simulations. We attribute this to the production of anomalously large SGS fluxes near the cloud tops through the interaction of numerical error in the momentum field with the scalar SGS model.
Numerics and subgrid‐scale modeling in large eddy simulations of stratocumulus clouds
Mishra, Siddhartha; Schneider, Tapio; Kaul, Colleen M.; Tan, Zhihong
2017-01-01
Abstract Stratocumulus clouds are the most common type of boundary layer cloud; their radiative effects strongly modulate climate. Large eddy simulations (LES) of stratocumulus clouds often struggle to maintain fidelity to observations because of the sharp gradients occurring at the entrainment interfacial layer at the cloud top. The challenge posed to LES by stratocumulus clouds is evident in the wide range of solutions found in the LES intercomparison based on the DYCOMS‐II field campaign, where simulated liquid water paths for identical initial and boundary conditions varied by a factor of nearly 12. Here we revisit the DYCOMS‐II RF01 case and show that the wide range of previous LES results can be realized in a single LES code by varying only the numerical treatment of the equations of motion and the nature of subgrid‐scale (SGS) closures. The simulations that maintain the greatest fidelity to DYCOMS‐II observations are identified. The results show that using weighted essentially non‐oscillatory (WENO) numerics for all resolved advective terms and no explicit SGS closure consistently produces the highest‐fidelity simulations. This suggests that the numerical dissipation inherent in WENO schemes functions as a high‐quality, implicit SGS closure for this stratocumulus case. Conversely, using oscillatory centered difference numerical schemes for momentum advection, WENO numerics for scalars, and explicitly modeled SGS fluxes consistently produces the lowest‐fidelity simulations. We attribute this to the production of anomalously large SGS fluxes near the cloud tops through the interaction of numerical error in the momentum field with the scalar SGS model. PMID:28943997
The Impact of Microphysical Schemes on Hurricane Intensity and Track
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Shi, Jainn Jong; Chen, Shuyi S.; Lang, Stephen; Lin, Pay-Liam; Hong, Song-You; Peters-Lidard, Christa; Hou, Arthur
2011-01-01
During the past decade, both research and operational numerical weather prediction models [e.g. the Weather Research and Forecasting Model (WRF)] have started using more complex microphysical schemes originally developed for high-resolution cloud resolving models (CRMs) with 1-2 km or less horizontal resolutions. WRF is a next-generation meso-scale forecast model and assimilation system. It incorporates a modern software framework, advanced dynamics, numerics and data assimilation techniques, a multiple moveable nesting capability, and improved physical packages. WRF can be used for a wide range of applications, from idealized research to operational forecasting, with an emphasis on horizontal grid sizes in the range of 1-10 km. The current WRF includes several different microphysics options. At NASA Goddard, four different cloud microphysics options have been implemented into WRF. The performance of these schemes is compared to those of the other microphysics schemes available in WRF for an Atlantic hurricane case (Katrina). In addition, a brief review of previous modeling studies on the impact of microphysics schemes and processes on the intensity and track of hurricanes is presented and compared against the current Katrina study. In general, all of the studies show that microphysics schemes do not have a major impact on track forecasts but do have more of an effect on the simulated intensity. Also, nearly all of the previous studies found that simulated hurricanes had the strongest deepening or intensification when using only warm rain physics. This is because all of the simulated precipitating hydrometeors are large raindrops that quickly fall out near the eye-wall region, which would hydrostatically produce the lowest pressure. In addition, these studies suggested that intensities become unrealistically strong when evaporative cooling from cloud droplets and melting from ice particles are removed as this results in much weaker downdrafts in the simulated storms. However, there are many differences between the different modeling studies, which are identified and discussed.
NASA Technical Reports Server (NTRS)
Varnai, Tamas; Yang, Weidong; Marshak, Alexander
2016-01-01
CALIOP shows stronger near-cloud changes in aerosol properties at higher cloud fractions. Cloud fraction variations explain a third of near-cloud changes in overall aerosol statistics. Cloud fraction and aerosol particle size distribution have a complex relationship.
Probability density cloud as a geometrical tool to describe statistics of scattered light.
Yaitskova, Natalia
2017-04-01
First-order statistics of scattered light is described using the representation of the probability density cloud, which visualizes a two-dimensional distribution for complex amplitude. The geometric parameters of the cloud are studied in detail and are connected to the statistical properties of phase. The moment-generating function for intensity is obtained in a closed form through these parameters. An example of exponentially modified normal distribution is provided to illustrate the functioning of this geometrical approach.
NASA Technical Reports Server (NTRS)
Myhill, Elizabeth A.; Boss, Alan P.
1993-01-01
In Boss & Myhill (1992) we described the derivation and testing of a spherical coordinate-based scheme for solving the hydrodynamic equations governing the gravitational collapse of nonisothermal, nonmagnetic, inviscid, radiative, three-dimensional protostellar clouds. Here we discuss a Cartesian coordinate-based scheme based on the same set of hydrodynamic equations. As with the spherical coorrdinate-based code, the Cartesian coordinate-based scheme employs explicit Eulerian methods which are both spatially and temporally second-order accurate. We begin by describing the hydrodynamic equations in Cartesian coordinates and the numerical methods used in this particular code. Following Finn & Hawley (1989), we pay special attention to the proper implementations of high-order accuracy, finite difference methods. We evaluate the ability of the Cartesian scheme to handle shock propagation problems, and through convergence testing, we show that the code is indeed second-order accurate. To compare the Cartesian scheme discussed here with the spherical coordinate-based scheme discussed in Boss & Myhill (1992), the two codes are used to calculate the standard isothermal collapse test case described by Bodenheimer & Boss (1981). We find that with the improved codes, the intermediate bar-configuration found previously disappears, and the cloud fragments directly into a binary protostellar system. Finally, we present the results from both codes of a new test for nonisothermal protostellar collapse.
NASA Astrophysics Data System (ADS)
Zhang, Sijin; Austin, Geoff; Sutherland-Stacey, Luke
2014-05-01
Reverse Kessler warm rain processes were implemented within the Weather Research and Forecasting Model (WRF) and coupled with a Newtonian relaxation, or nudging technique designed to improve quantitative precipitation forecasting (QPF) in New Zealand by making use of observed radar reflectivity and modest computing facilities. One of the reasons for developing such a scheme, rather than using 4D-Var for example, is that radar VAR scheme in general, and 4D-Var in particular, requires computational resources beyond the capability of most university groups and indeed some national forecasting centres of small countries like New Zealand. The new scheme adjusts the model water vapor mixing ratio profiles based on observed reflectivity at each time step within an assimilation time window. The whole scheme can be divided into following steps: (i) The radar reflectivity is firstly converted to rain water, and (ii) then the rain water is used to derive cloud water content according to the reverse Kessler scheme; (iii) The cloud water content associated water vapor mixing ratio is then calculated based on the saturation adjustment processes; (iv) Finally the adjusted water vapor is nudged into the model and the model background is updated. 13 rainfall cases which occurred in the summer of 2011/2012 in New Zealand were used to evaluate the new scheme, different forecast scores were calculated and showed that the new scheme was able to improve precipitation forecasts on average up to around 7 hours ahead depending on different verification thresholds.
NASA Technical Reports Server (NTRS)
Mcdougal, David S. (Editor)
1990-01-01
FIRE (First ISCCP Regional Experiment) is a U.S. cloud-radiation research program formed in 1984 to increase the basic understanding of cirrus and marine stratocumulus cloud systems, to develop realistic parameterizations for these systems, and to validate and improve ISCCP cloud product retrievals. Presentations of results culminating the first 5 years of FIRE research activities were highlighted. The 1986 Cirrus Intensive Field Observations (IFO), the 1987 Marine Stratocumulus IFO, the Extended Time Observations (ETO), and modeling activities are described. Collaborative efforts involving the comparison of multiple data sets, incorporation of data measurements into modeling activities, validation of ISCCP cloud parameters, and development of parameterization schemes for General Circulation Models (GCMs) are described.
NASA Astrophysics Data System (ADS)
Dai, Fushan; Yu, Rucong; Zhang, Xuehong; Yu, Yongqiang; Li, Jianglong
2003-05-01
Like many other coupled models, the Flexible coupled General Circulation Model (FGCM-0) suffers from the spurious “Double ITCZ”. In order to understand the “Double ITCZ” in FGCM-0, this study first examines the low-level cloud cover and the bulk stability of the low troposphere over the eastern subtropical Pacific simulated by the National Center for Atmospheric Research (NCAR) Community Climate Model version 3 (CCM3), which is the atmosphere component model of FGCM-0. It is found that the bulk stability of the low troposphere simulated by CCM3 is very consistent with the one derived from the National Center for Environmental Prediction (NCEP) reanalysis, but the simulated low-level cloud cover is much less than that derived from the International Satellite Cloud Climatology Project (ISCCP) D2 data. Based on the regression equations between the low-level cloud cover from the ISCCP data and the bulk stability of the low troposphere derived from the NCEP reanalysis, the parameterization scheme of low-level cloud in CCM3 is modified and used in sensitivity experiments to examine the impact of low-level cloud over the eastern subtropical Pacific on the spurious “Double ITCZ” in FGCM-0. Results show that the modified scheme causes the simulated low-level cloud cover to be improved locally over the cold oceans. Increasing the low-level cloud cover off Peru not only significantly alleviates the SST warm biases in the southeastern tropical Pacific, but also causes the equatorial cold tongue to be strengthened and to extend further west. Increasing the low-level cloud fraction off California effectively reduces the SST warm biases in ITCZ north of the equator. In order to examine the feedback between the SST and low-level cloud cover off Peru, one additional sensitivity experiment is performed in which the SST over the cold ocean off Peru is restored. It shows that decreasing the SST results in similar impacts over the wide regions from the southeastern tropical Pacific northwestwards to the western/central equatorial Pacific as increasing the low-level cloud cover does.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Song, Hua; Zhang, Zhibo; Ma, Po-Lun
This paper presents a two-step evaluation of the marine boundary layer (MBL) cloud properties from two Community Atmospheric Model (version 5.3, CAM5) simulations, one based on the CAM5 standard parameterization schemes (CAM5-Base), and the other on the Cloud Layers Unified By Binormals (CLUBB) scheme (CAM5-CLUBB). In the first step, we compare the cloud properties directly from model outputs between the two simulations. We find that the CAM5-CLUBB run produces more MBL clouds in the tropical and subtropical large-scale descending regions. Moreover, the stratocumulus (Sc) to cumulus (Cu) cloud regime transition is much smoother in CAM5-CLUBB than in CAM5-Base. In addition,more » in CAM5-Base we find some grid cells with very small low cloud fraction (<20%) to have very high in-cloud water content (mixing ratio up to 400mg/kg). We find no such grid cells in the CAM5-CLUBB run. However, we also note that both simulations, especially CAM5-CLUBB, produce a significant amount of “empty” low cloud cells with significant cloud fraction (up to 70%) and near-zero in-cloud water content. In the second step, we use satellite observations from CERES, MODIS and CloudSat to evaluate the simulated MBL cloud properties by employing the COSP satellite simulators. We note that a feature of the COSP-MODIS simulator to mimic the minimum detection threshold of MODIS cloud masking removes much more low clouds from CAM5-CLUBB than it does from CAM5-Base. This leads to a surprising result — in the large-scale descending regions CAM5-CLUBB has a smaller COSP-MODIS cloud fraction and weaker shortwave cloud radiative forcing than CAM5-Base. A sensitivity study suggests that this is because CAM5-CLUBB suffers more from the above-mentioned “empty” clouds issue than CAM5-Base. The COSP-MODIS cloud droplet effective radius in CAM5-CLUBB shows a spatial increase from coastal St toward Cu, which is in qualitative agreement with MODIS observations. In contrast, COSP-MODIS cloud droplet effective radius in CAM5-Base almost remains a constant. In comparison with CloudSat observations, the histogram of the radar reflectivity from modeled MBL clouds is too narrow without a distinct separation between cloud and drizzle modes. Moreover, the probability of drizzle in both simulations is almost twice as high as the observation. Future studies are needed to understand the causes of these differences and their potential connection with the “empty” cloud issues in the model.« less
NASA Technical Reports Server (NTRS)
Luo, Yali; Xu, Kuan-Man; Morrison, Hugh; McFarquhar, Greg M.; Wang, Zhien; Zhang, Gong
2007-01-01
A cloud-resolving model (CRM) is used to simulate the multiple-layer mixed-phase stratiform (MPS) clouds that occurred during a three-and-a-half day subperiod of the Department of Energy-Atmospheric Radiation Measurement Program s Mixed-Phase Arctic Cloud Experiment (M-PACE). The CRM is implemented with an advanced two-moment microphysics scheme, a state-of-the-art radiative transfer scheme, and a complicated third-order turbulence closure. Concurrent meteorological, aerosol, and ice nucleus measurements are used to initialize the CRM. The CRM is prescribed by time-varying large-scale advective tendencies of temperature and moisture and surface turbulent fluxes of sensible and latent heat. The CRM reproduces the occurrences of the single- and double-layer MPS clouds as revealed by the M-PACE observations. However, the simulated first cloud layer is lower and the second cloud layer thicker compared to observations. The magnitude of the simulated liquid water path agrees with that observed, but its temporal variation is more pronounced than that observed. As in an earlier study of single-layer cloud, the CRM also captures the major characteristics in the vertical distributions and temporal variations of liquid water content (LWC), total ice water content (IWC), droplet number concentration and ice crystal number concentration (nis) as suggested by the aircraft observations. However, the simulated mean values differ significantly from the observed. The magnitude of nis is especially underestimated by one order of magnitude. Sensitivity experiments suggest that the lower cloud layer is closely related to the surface fluxes of sensible and latent heat; the upper cloud layer is probably initialized by the large-scale advective cooling/moistening and maintained through the strong longwave (LW) radiative cooling near the cloud top which enhances the dynamical circulation; artificially turning off all ice-phase microphysical processes results in an increase in LWP by a factor of 3 due to interactions between the excessive LW radiative cooling and extra cloud water; heating caused by phase change of hydrometeors could affect the LWC and cloud top height by partially canceling out the LW radiative cooling. It is further shown that the resolved dynamical circulation appears to contribute more greatly to the evolution of the MPS cloud layers than the parameterized subgrid-scale circulation.
Empirical and modeled synoptic cloud climatology of the Arctic Ocean
NASA Technical Reports Server (NTRS)
Barry, R. G.; Newell, J. P.; Schweiger, A.; Crane, R. G.
1986-01-01
A set of cloud cover data were developed for the Arctic during the climatically important spring/early summer transition months. Parallel with the determination of mean monthly cloud conditions, data for different synoptic pressure patterns were also composited as a means of evaluating the role of synoptic variability on Arctic cloud regimes. In order to carry out this analysis, a synoptic classification scheme was developed for the Arctic using an objective typing procedure. A second major objective was to analyze model output of pressure fields and cloud parameters from a control run of the Goddard Institue for Space Studies climate model for the same area and to intercompare the synoptic climatatology of the model with that based on the observational data.
NASA Astrophysics Data System (ADS)
Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris
2017-04-01
Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the apparent benefit from using ensembles for cloudy radiance assimilation in an EnVar context.
Towards Dynamic Remote Data Auditing in Computational Clouds
Khurram Khan, Muhammad; Anuar, Nor Badrul
2014-01-01
Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server. PMID:25121114
Towards dynamic remote data auditing in computational clouds.
Sookhak, Mehdi; Akhunzada, Adnan; Gani, Abdullah; Khurram Khan, Muhammad; Anuar, Nor Badrul
2014-01-01
Cloud computing is a significant shift of computational paradigm where computing as a utility and storing data remotely have a great potential. Enterprise and businesses are now more interested in outsourcing their data to the cloud to lessen the burden of local data storage and maintenance. However, the outsourced data and the computation outcomes are not continuously trustworthy due to the lack of control and physical possession of the data owners. To better streamline this issue, researchers have now focused on designing remote data auditing (RDA) techniques. The majority of these techniques, however, are only applicable for static archive data and are not subject to audit the dynamically updated outsourced data. We propose an effectual RDA technique based on algebraic signature properties for cloud storage system and also present a new data structure capable of efficiently supporting dynamic data operations like append, insert, modify, and delete. Moreover, this data structure empowers our method to be applicable for large-scale data with minimum computation cost. The comparative analysis with the state-of-the-art RDA schemes shows that the proposed scheme is secure and highly efficient in terms of the computation and communication overhead on the auditor and server.
CLEPS 1.0: A new protocol for cloud aqueous phase oxidation of VOC mechanisms
NASA Astrophysics Data System (ADS)
Mouchel-Vallon, Camille; Deguillaume, Laurent; Monod, Anne; Perroux, Hélène; Rose, Clémence; Ghigo, Giovanni; Long, Yoann; Leriche, Maud; Aumont, Bernard; Patryl, Luc; Armand, Patrick; Chaumerliac, Nadine
2017-03-01
A new detailed aqueous phase mechanism named the Cloud Explicit Physico-chemical Scheme (CLEPS 1.0) is proposed to describe the oxidation of water soluble organic compounds resulting from isoprene oxidation. It is based on structure activity relationships (SARs) which provide global rate constants together with branching ratios for HOṡ abstraction and addition on atmospheric organic compounds. The GROMHE SAR allows the evaluation of Henry's law constants for undocumented organic compounds. This new aqueous phase mechanism is coupled with the MCM v3.3.1 gas phase mechanism through a mass transfer scheme between gas phase and aqueous phase. The resulting multiphase mechanism has then been implemented in a model based on the Dynamically Simple Model for Atmospheric Chemical Complexity (DSMACC) using the Kinetic PreProcessor (KPP) that can serve to analyze data from cloud chamber experiments and field campaigns. The simulation of permanent cloud under low-NOx conditions describes the formation of oxidized monoacids and diacids in the aqueous phase as well as a significant influence on the gas phase chemistry and composition and shows that the aqueous phase reactivity leads to an efficient fragmentation and functionalization of organic compounds.
NASA Astrophysics Data System (ADS)
Dai, Guangyao; Wu, Songhua; Song, Xiaoquan; Zhai, Xiaochun
2018-04-01
Cirrus clouds affect the energy budget and hydrological cycle of the earth's atmosphere. The Tibetan Plateau (TP) plays a significant role in the global and regional climate. Optical and geometrical properties of cirrus clouds in the TP were measured in July-August 2014 by lidar and radiosonde. The statistics and temperature dependences of the corresponding properties are analyzed. The cirrus cloud formations are discussed with respect to temperature deviation and dynamic processes.
Thayer-Calder, K.; Gettelman, A.; Craig, C.; ...
2015-06-30
Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into amore » microphysics scheme.This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less
Thayer-Calder, Katherine; Gettelman, A.; Craig, Cheryl; ...
2015-12-01
Most global climate models parameterize separate cloud types using separate parameterizations.This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations. Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysicsmore » scheme. This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Results describing the mean climate and tropical variability from global simulations are presented. In conclusion, the new model shows a degradation in precipitation skill but improvements in short-wave cloud forcing, liquid water path, long-wave cloud forcing, perceptible water, and tropical wave simulation. Also presented are estimations of computational expense and investigation of sensitivity to number of subcolumns.« less
NASA Astrophysics Data System (ADS)
Kalina, E. A.; Biswas, M.; Newman, K.; Grell, E. D.; Bernardet, L.; Frimel, J.; Carson, L.
2017-12-01
The parameterization of moist physics in numerical weather prediction models plays an important role in modulating tropical cyclone structure, intensity, and evolution. The Hurricane Weather Research and Forecast system (HWRF), the National Oceanic and Atmospheric Administration's operational model for tropical cyclone prediction, uses the Scale-Aware Simplified Arakawa-Schubert (SASAS) cumulus scheme and a modified version of the Ferrier-Aligo (FA) microphysics scheme to parameterize moist physics. The FA scheme contains a number of simplifications that allow it to run efficiently in an operational setting, which includes prescribing values for hydrometeor number concentrations (i.e., single-moment microphysics) and advecting the total condensate rather than the individual hydrometeor species. To investigate the impact of these simplifying assumptions on the HWRF forecast, the FA scheme was replaced with the more complex double-moment Thompson microphysics scheme, which individually advects cloud ice, cloud water, rain, snow, and graupel. Retrospective HWRF forecasts of tropical cyclones that occurred in the Atlantic and eastern Pacific ocean basins from 2015-2017 were then simulated and compared to those produced by the operational HWRF configuration. Both traditional model verification metrics (i.e., tropical cyclone track and intensity) and process-oriented metrics (e.g., storm size, precipitation structure, and heating rates from the microphysics scheme) will be presented and compared. The sensitivity of these results to the cumulus scheme used (i.e., the operational SASAS versus the Grell-Freitas scheme) also will be examined. Finally, the merits of replacing the moist physics schemes that are used operationally with the alternatives tested here will be discussed from a standpoint of forecast accuracy versus computational resources.
Assimilation of Satellite to Improve Cloud Simulation in Wrf Model
NASA Astrophysics Data System (ADS)
Park, Y. H.; Pour Biazar, A.; McNider, R. T.
2012-12-01
A simple approach has been introduced to improve cloud simulation spatially and temporally in a meteorological model. The first step for this approach is to use Geostationary Operational Environmental Satellite (GOES) observations to identify clouds and estimate the clouds structure. Then by comparing GOES observations to model cloud field, we identify areas in which model has under-predicted or over-predicted clouds. Next, by introducing subsidence in areas with over-prediction and lifting in areas with under-prediction, erroneous clouds are removed and new clouds are formed. The technique estimates a vertical velocity needed for the cloud correction and then uses a one dimensional variation schemes (1D_Var) to calculate the horizontal divergence components and the consequent horizontal wind components needed to sustain such vertical velocity. Finally, the new horizontal winds are provided as a nudging field to the model. This nudging provides the dynamical support needed to create/clear clouds in a sustainable manner. The technique was implemented and tested in the Weather Research and Forecast (WRF) Model and resulted in substantial improvement in model simulated clouds. Some of the results are presented here.
Impact of cloud timing on surface temperature and related hydroclimatic dynamics
NASA Astrophysics Data System (ADS)
Porporato, A. M.; Yin, J.
2015-12-01
Cloud feedbacks have long been identified as one of the largest source of uncertainty in climate change predictions. Differences in the spatial distribution of clouds and the related impact on surface temperature and climate dynamics have been recently emphasized in quasi-equilibrium General Circulation Models (GCM). However, much less attention has been paid to the temporal variation of cloud presence and thickness. Clouds in fact shade the solar radiation during the daytime, but also acts as greenhouse gas to reduce the emission of longwave radiation to the outer space anytime of the day. Thus it is logical to expect that even small differences in timing and thickness of clouds could result in very different predictions in GCMs. In this study, these two effects of cloud dynamics are analyzed by tracking the cloud impacts on longwave and shortwave radiation in a minimalist transient thermal balance model of the land surface. The marked changes in surface temperature due to alterations in the timing of onset of clouds demonstrate that capturing temporal variation of cloud at sub-daily scale should be a priority in cloud parameterization schemes in GCMs.
From the Campus to the Cloud: The Online Peer Assisted Learning Scheme
ERIC Educational Resources Information Center
Beaumont, Tim J.; Mannion, Aaron P.; Shen, Brice O.
2012-01-01
This paper reports on an online version of Peer Assisted Study Sessions (PASS), also known as Supplemental Instruction (SI), which was trialled in two subjects in the University of Melbourne in 2011. The program, named the Online Peer Assisted Learning (OPAL) scheme, was implemented with the aims of extending the benefits of a successful peer…
NASA Astrophysics Data System (ADS)
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.
NASA Astrophysics Data System (ADS)
Boichu, Marie; Clarisse, Lieven; Khvorostyanov, Dmitry; Clerbaux, Cathy
2014-04-01
Forecasting the dispersal of volcanic clouds during an eruption is of primary importance, especially for ensuring aviation safety. As volcanic emissions are characterized by rapid variations of emission rate and height, the (generally) high level of uncertainty in the emission parameters represents a critical issue that limits the robustness of volcanic cloud dispersal forecasts. An inverse modeling scheme, combining satellite observations of the volcanic cloud with a regional chemistry-transport model, allows reconstructing this source term at high temporal resolution. We demonstrate here how a progressive assimilation of freshly acquired satellite observations, via such an inverse modeling procedure, allows for delivering robust sulfur dioxide (SO2) cloud dispersal forecasts during the eruption. This approach provides a computationally cheap estimate of the expected location and mass loading of volcanic clouds, including the identification of SO2-rich parts.
NASA Astrophysics Data System (ADS)
Kwiatek, Grzegorz; Martínez-Garzón, Patricia; Dresen, Georg; Bohnhoff, Marco; Sone, Hiroki; Hartline, Craig
2015-10-01
The long-term temporal and spatial changes in statistical, source, and stress characteristics of one cluster of induced seismicity recorded at The Geysers geothermal field (U.S.) are analyzed in relation to the field operations, fluid migration, and constraints on the maximum likely magnitude. Two injection wells, Prati-9 and Prati-29, located in the northwestern part of the field and their associated seismicity composed of 1776 events recorded throughout a 7 year period were analyzed. The seismicity catalog was relocated, and the source characteristics including focal mechanisms and static source parameters were refined using first-motion polarity, spectral fitting, and mesh spectral ratio analysis techniques. The source characteristics together with statistical parameters (b value) and cluster dynamics were used to investigate and understand the details of fluid migration scheme in the vicinity of injection wells. The observed temporal, spatial, and source characteristics were clearly attributed to fluid injection and fluid migration toward greater depths, involving increasing pore pressure in the reservoir. The seasonal changes of injection rates were found to directly impact the shape and spatial extent of the seismic cloud. A tendency of larger seismic events to occur closer to injection wells and a correlation between the spatial extent of the seismic cloud and source sizes of the largest events was observed suggesting geometrical constraints on the maximum likely magnitude and its correlation to the average injection rate and volume of fluids present in the reservoir.
A secure medical data exchange protocol based on cloud environment.
Chen, Chin-Ling; Yang, Tsai-Tung; Shih, Tzay-Farn
2014-09-01
In recent years, health care technologies already became matured such as electronic medical records that can be easily stored. However, how to get medical resources more convenient is currently concern issue. In spite of many literatures discussed about medical systems, but these literatures should face many security challenges. The most important issue is patients' privacy. Therefore, we propose a secure medical data exchange protocol based on cloud environment. In our scheme, we use mobile device's characteristics, allowing peoples use medical resources on the cloud environment to seek medical advice conveniently.
Aerosol specification in single-column Community Atmosphere Model version 5
Lebassi-Habtezion, B.; Caldwell, P. M.
2015-03-27
Single-column model (SCM) capability is an important tool for general circulation model development. In this study, the SCM mode of version 5 of the Community Atmosphere Model (CAM5) is shown to handle aerosol initialization and advection improperly, resulting in aerosol, cloud-droplet, and ice crystal concentrations which are typically much lower than observed or simulated by CAM5 in global mode. This deficiency has a major impact on stratiform cloud simulations but has little impact on convective case studies because aerosol is currently not used by CAM5 convective schemes and convective cases are typically longer in duration (so initialization is less important).more » By imposing fixed aerosol or cloud-droplet and crystal number concentrations, the aerosol issues described above can be avoided. Sensitivity studies using these idealizations suggest that the Meyers et al. (1992) ice nucleation scheme prevents mixed-phase cloud from existing by producing too many ice crystals. Microphysics is shown to strongly deplete cloud water in stratiform cases, indicating problems with sequential splitting in CAM5 and the need for careful interpretation of output from sequentially split climate models. Droplet concentration in the general circulation model (GCM) version of CAM5 is also shown to be far too low (~ 25 cm −3) at the southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Qing; Gustafson, William I.; Fast, Jerome D.
2011-12-02
In the recent chemistry version (v3.3) of the Weather Research and Forecasting (WRF-Chem) model, we have coupled the Morrison double-moment microphysics scheme with interactive aerosols so that full two-way aerosol-cloud interactions are included in simulations. We have used this new WRF-Chem functionality in a study focused on assessing predictions of aerosols, marine stratocumulus clouds, and their interactions over the Southeast Pacific using measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) and satellite retrievals. This study also serves as a detailed analysis of our WRF-Chem simulations contributed to the VOCALS model Assessment (VOCA) project. The WRF-Chem 31-day (October 15-November 16,more » 2008) simulation with aerosol-cloud interactions (AERO hereafter) is also compared to a simulation (MET hereafter) with fixed cloud droplet number concentrations assumed by the default in Morrison microphysics scheme with no interactive aerosols. The well-predicted aerosol properties such as number, mass composition, and optical depth lead to significant improvements in many features of the predicted stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness, and cloud macrostructure such as cloud depth and cloud base height. These improvements in addition to the aerosol direct and semi-direct effects, in turn, feed back to the prediction of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengths temperature and humidity gradients within capping inversion layer and lowers the MBL depth by 150 m from that of the MET simulation. Mean top-of-the-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with observations in AERO, compared to the MET simulation. Nevertheless, biases in some of the simulated meteorological quantities (e.g., MBL temperature and humidity over the remote ocean) and aerosol quantities (e.g., overestimations of supermicron sea salt mass) might affect simulated stratocumulus and energy fluxes over the SEP, and require further investigations. Although not perfect, the overall performance of the regional model in simulating mesoscale aerosol-cloud interactions is encouraging and suggests that the inclusion of spatially varying aerosol characteristics is important when simulating marine stratocumulus over the southeastern Pacific.« less
AN EXPLORATION OF THE STATISTICAL SIGNATURES OF STELLAR FEEDBACK
DOE Office of Scientific and Technical Information (OSTI.GOV)
Boyden, Ryan D.; Offner, Stella S. R.; Koch, Eric W.
2016-12-20
All molecular clouds are observed to be turbulent, but the origin, means of sustenance, and evolution of the turbulence remain debated. One possibility is that stellar feedback injects enough energy into the cloud to drive observed motions on parsec scales. Recent numerical studies of molecular clouds have found that feedback from stars, such as protostellar outflows and winds, injects energy and impacts turbulence. We expand upon these studies by analyzing magnetohydrodynamic simulations of molecular clouds, including stellar winds, with a range of stellar mass-loss rates and magnetic field strengths. We generate synthetic {sup 12}CO(1–0) maps assuming that the simulations aremore » at the distance of the nearby Perseus molecular cloud. By comparing the outputs from different initial conditions and evolutionary times, we identify differences in the synthetic observations and characterize these using common astrostatistics. We quantify the different statistical responses using a variety of metrics proposed in the literature. We find that multiple astrostatistics, including the principal component analysis, the spectral correlation function, and the velocity coordinate spectrum (VCS), are sensitive to changes in stellar mass-loss rates and/or time evolution. A few statistics, including the Cramer statistic and VCS, are sensitive to the magnetic field strength. These findings demonstrate that stellar feedback influences molecular cloud turbulence and can be identified and quantified observationally using such statistics.« less
A-Train Based Observational Metrics for Model Evaluation in Extratropical Cyclones
NASA Technical Reports Server (NTRS)
Naud, Catherine M.; Booth, James F.; Del Genio, Anthony D.; van den Heever, Susan C.; Posselt, Derek J.
2015-01-01
Extratropical cyclones contribute most of the precipitation in the midlatitudes, i.e. up to 70 during winter in the northern hemisphere, and can generate flooding, extreme winds, blizzards and have large socio-economic impacts. As such, it is important that general circulation models (GCMs) accurately represent these systems so their evolution in a warming climate can be understood. However, there are still uncertainties on whether warming will increase their frequency of occurrence, their intensity and how much rain or snow they bring. Part of the issue is that models have trouble representing their strength, but models also have biases in the amount of clouds and precipitation they produce. This is caused by potential issues in various aspects of the models: convection, boundary layer, and cloud scheme to only mention a few. In order to pinpoint which aspects of the models need improvement for a better representation of extratropical cyclone precipitation and cloudiness, we will present A-train based observational metrics: cyclone-centered, warm and cold frontal composites of cloud amount and type, precipitation rate and frequency of occurrence. Using the same method to extract similar fields from the model, we will present an evaluation of the GISS-ModelE2 and the IPSL-LMDZ-5B models, based on their AR5 and more recent versions. The AR5 version of the GISS model underestimates cloud cover in extratropical cyclones while the IPSL AR5 version overestimates it. In addition, we will show how the observed CloudSat-CALIPSO cloud vertical distribution across cold fronts changes with moisture amount and cyclone strength, and test if the two models successfully represent these changes. We will also show how CloudSat-CALIPSO derived cloud type (i.e. convective vs. stratiform) evolves across warm fronts as cyclones age, and again how this is represented in the models. Our third process-based analysis concerns cumulus clouds in the post-cold frontal region and how their amount relates to the stability of the boundary layer. This test uses Aqua cloud and vertical atmospheric profiles and when applied to the model output can help assess the accuracy of the convection, boundary layer and cloud scheme.
Fleets of enduring drones to probe atmospheric phenomena with clouds
NASA Astrophysics Data System (ADS)
Lacroix, Simon; Roberts, Greg; Benard, Emmanuel; Bronz, Murat; Burnet, Frédéric; Bouhoubeiny, Elkhedim; Condomines, Jean-Philippe; Doll, Carsten; Hattenberger, Gautier; Lamraoui, Fayçal; Renzaglia, Alessandro; Reymann, Christophe
2016-04-01
A full spatio-temporal four-dimensional characterization of the microphysics and dynamics of cloud formation including the onset of precipitation has never been reached. Such a characterization would yield a better understanding of clouds, e.g. to assess the dominant mixing mechanism and the main source of cloudy updraft dilution. It is the sampling strategy that matters: fully characterizing the evolution over time of the various parameters (P, T, 3D wind, liquid water content, aerosols...) within a cloud volume requires dense spatial sampling for durations of the order of one hour. A fleet of autonomous lightweight UAVs that coordinate themselves in real-time as an intelligent network can fulfill this purpose. The SkyScanner project targets the development of a fleet of autonomous UAVs to adaptively sample cumuli, so as to provide relevant data to address long standing questions in atmospheric science. It mixes basic researches and experimental developments, and gathers scientists in UAV conception, in optimal flight control, in intelligent cooperative behaviors, and of course atmospheric scientists. Two directions of researches are explored: optimal UAV conception and control, and optimal control of a fleet of UAVs. The design of UAVs for atmospheric science involves the satisfaction of trade-offs between payload, endurance, ease of deployment... A rational conception scheme that integrates the constraints to optimize a series of criteria, in particular energy consumption, would yield the definition of efficient UAVs. This requires a fine modeling of each involved sub-system and phenomenon, from the motor/propeller efficiency to the aerodynamics at small scale, including the flight control algorithms. The definition of mission profiles is also essential, considering the aerodynamics of clouds, to allow energy harvesting schemes that exploit thermals or gusts. The conception also integrates specific sensors, in particular wind sensor, for which classic technologies are challenged at the low speeds of lightweight UAVs. The overall control of the fleet so as to gather series of synchronized data in the cloud volume is a poorly informed and highly constrained adaptive sampling problem, in which the UAV motions must be defined to maximize the amount of gathered information and the mission duration. The overall approach casts the problem in a hierarchy of two modeling and decision stages. A macroscopic parametrized model of the cloud is built from the gathered data and exploited at the higher level by an operator, who sets information gathering goals. A subset of the UAV fleet is allocated to each goal, considering the current fleet state. These high level goals are handled by the lower level, which autonomously optimizes the selected UAVs trajectories using an on-line updated dense model of the variables of interest. Building the models involves Gaussian processes techniques (kriging) to fuse the gathered data with a generic cumulus conceptual model, the latter being defined from thorough statistics on realistic MesoNH cloud simulations. The model is exploited by a planner to generate trajectories that minimize the uncertainty in the map, while steering the vehicles within the air flows to save energy.
NASA Technical Reports Server (NTRS)
Haggerty, Julie; McDonough, Frank; Black, Jennifer; Landott, Scott; Wolff, Cory; Mueller, Steven; Minnis, Patrick; Smith, William, Jr.
2008-01-01
Operational products used by the U.S. Federal Aviation Administration to alert pilots of hazardous icing provide nowcast and short-term forecast estimates of the potential for the presence of supercooled liquid water and supercooled large droplets. The Current Icing Product (CIP) system employs basic satellite-derived information, including a cloud mask and cloud top temperature estimates, together with multiple other data sources to produce a gridded, three-dimensional, hourly depiction of icing probability and severity. Advanced satellite-derived cloud products developed at the NASA Langley Research Center (LaRC) provide a more detailed description of cloud properties (primarily at cloud top) compared to the basic satellite-derived information used currently in CIP. Cloud hydrometeor phase, liquid water path, cloud effective temperature, and cloud top height as estimated by the LaRC algorithms are into the CIP fuzzy logic scheme and a confidence value is determined. Examples of CIP products before and after the integration of the LaRC satellite-derived products will be presented at the conference.
NASA Astrophysics Data System (ADS)
Lee, H.-H.; Chen, S.-H.; Kleeman, M. J.; Zhang, H.; DeNero, S. P.; Joe, D. K.
2015-11-01
The source-oriented Weather Research and Forecasting chemistry model (SOWC) was modified to include warm cloud processes and applied to investigate how aerosol mixing states influence fog formation and optical properties in the atmosphere. SOWC tracks a 6-dimensional chemical variable (X, Z, Y, Size Bins, Source Types, Species) through an explicit simulation of atmospheric chemistry and physics. A source-oriented cloud condensation nuclei module was implemented into the SOWC model to simulate warm clouds using the modified two-moment Purdue Lin microphysics scheme. The Goddard shortwave and longwave radiation schemes were modified to interact with source-oriented aerosols and cloud droplets so that aerosol direct and indirect effects could be studied. The enhanced SOWC model was applied to study a fog event that occurred on 17 January 2011, in the Central Valley of California. Tule fog occurred because an atmospheric river effectively advected high moisture into the Central Valley and nighttime drainage flow brought cold air from mountains into the valley. The SOWC model produced reasonable liquid water path, spatial distribution and duration of fog events. The inclusion of aerosol-radiation interaction only slightly modified simulation results since cloud optical thickness dominated the radiation budget in fog events. The source-oriented mixture representation of particles reduced cloud droplet number relative to the internal mixture approach that artificially coats hydrophobic particles with hygroscopic components. The fraction of aerosols activating into CCN at a supersaturation of 0.5 % in the Central Valley decreased from 94 % in the internal mixture model to 80 % in the source-oriented model. This increased surface energy flux by 3-5 W m-2 and surface temperature by as much as 0.25 K in the daytime.
NASA Astrophysics Data System (ADS)
Christensen, M.; McGarragh, G.; Thomas, G.; Povey, A.; Proud, S.; Poulsen, C. A.; Grainger, R. G.
2016-12-01
Radiative forcing by clouds, aerosols, and their interactions constitute some of the largest sources of uncertainties in the climate system (Chapter 7 IPCC, 2013). It is essential to understand the past through examination of long-term satellite observation records to provide insight into the uncertainty characteristics of these radiative forcers. As part of the ESA CCI (Climate Change Initiative) we have recently implemented a broadband radiative flux algorithm (known as BUGSrad) into the Optimal Retrieval for Aerosol and Cloud (ORAC) scheme. ORAC achieves radiative consistency of its aerosol and cloud products through an optimal estimation scheme and is highly versatile, enabling retrievals for numerous satellite sensors: ATSR, MODIS, VIIRS, AVHRR, SLSTR, SEVIRI, and AHI. An analysis of the 17-year well-calibrated Along Track Scanning Radiometer (ATSR) data is used to quantify trends in cloud and aerosol radiative effects over a wide range of spatiotemporal scales. The El Niño Southern Oscillation stands out as the largest contributing mode of variability to the radiative energy balance (long wave and shortwave fluxes) at the top of the atmosphere. Furthermore, trends in planetary albedo show substantial decreases across the Arctic Ocean (likely due to the melting of sea ice and snow) and modest increases in regions dominated by stratocumulus (e.g., off the coast of California) through notable increases in cloud fraction and liquid water path. Finally, changes in volcanic activity and biomass burning aerosol over this period show sizeable radiative forcing impacts at local-scales. We will demonstrate that radiative forcing from aerosols and clouds have played a significant role in the identified key climate processes using 17 years of satellite observational data.
Geometric Data Perturbation-Based Personal Health Record Transactions in Cloud Computing
Balasubramaniam, S.; Kavitha, V.
2015-01-01
Cloud computing is a new delivery model for information technology services and it typically involves the provision of dynamically scalable and often virtualized resources over the Internet. However, cloud computing raises concerns on how cloud service providers, user organizations, and governments should handle such information and interactions. Personal health records represent an emerging patient-centric model for health information exchange, and they are outsourced for storage by third parties, such as cloud providers. With these records, it is necessary for each patient to encrypt their own personal health data before uploading them to cloud servers. Current techniques for encryption primarily rely on conventional cryptographic approaches. However, key management issues remain largely unsolved with these cryptographic-based encryption techniques. We propose that personal health record transactions be managed using geometric data perturbation in cloud computing. In our proposed scheme, the personal health record database is perturbed using geometric data perturbation and outsourced to the Amazon EC2 cloud. PMID:25767826
Geometric data perturbation-based personal health record transactions in cloud computing.
Balasubramaniam, S; Kavitha, V
2015-01-01
Cloud computing is a new delivery model for information technology services and it typically involves the provision of dynamically scalable and often virtualized resources over the Internet. However, cloud computing raises concerns on how cloud service providers, user organizations, and governments should handle such information and interactions. Personal health records represent an emerging patient-centric model for health information exchange, and they are outsourced for storage by third parties, such as cloud providers. With these records, it is necessary for each patient to encrypt their own personal health data before uploading them to cloud servers. Current techniques for encryption primarily rely on conventional cryptographic approaches. However, key management issues remain largely unsolved with these cryptographic-based encryption techniques. We propose that personal health record transactions be managed using geometric data perturbation in cloud computing. In our proposed scheme, the personal health record database is perturbed using geometric data perturbation and outsourced to the Amazon EC2 cloud.
NASA Technical Reports Server (NTRS)
Wiscombe, W.
1999-01-01
The purpose of this paper is discuss the concept of fractal dimension; multifractal statistics as an extension of this; the use of simple multifractal statistics (power spectrum, structure function) to characterize cloud liquid water data; and to understand the use of multifractal cloud liquid water models based on real data as input to Monte Carlo radiation models of shortwave radiation transfer in 3D clouds, and the consequences of this in two areas: the design of aircraft field programs to measure cloud absorptance; and the explanation of the famous "Landsat scale break" in measured radiance.
Intel Xeon Phi accelerated Weather Research and Forecasting (WRF) Goddard microphysics scheme
NASA Astrophysics Data System (ADS)
Mielikainen, J.; Huang, B.; Huang, A. H.-L.
2014-12-01
The Weather Research and Forecasting (WRF) model is a numerical weather prediction system designed to serve both atmospheric research and operational forecasting needs. The WRF development is a done in collaboration around the globe. Furthermore, the WRF is used by academic atmospheric scientists, weather forecasters at the operational centers and so on. The WRF contains several physics components. The most time consuming one is the microphysics. One microphysics scheme is the Goddard cloud microphysics scheme. It is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the Goddard scheme code. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU does. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is one familiar to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discussed in this paper. The results show that the optimizations improved performance of Goddard microphysics scheme on Xeon Phi 7120P by a factor of 4.7×. In addition, the optimizations reduced the Goddard microphysics scheme's share of the total WRF processing time from 20.0 to 7.5%. Furthermore, the same optimizations improved performance on Intel Xeon E5-2670 by a factor of 2.8× compared to the original code.
Comparison of Histograms for Use in Cloud Observation and Modeling
NASA Technical Reports Server (NTRS)
Green, Lisa; Xu, Kuan-Man
2005-01-01
Cloud observation and cloud modeling data can be presented in histograms for each characteristic to be measured. Combining information from single-cloud histograms yields a summary histogram. Summary histograms can be compared to each other to reach conclusions about the behavior of an ensemble of clouds in different places at different times or about the accuracy of a particular cloud model. As in any scientific comparison, it is necessary to decide whether any apparent differences are statistically significant. The usual methods of deciding statistical significance when comparing histograms do not apply in this case because they assume independent data. Thus, a new method is necessary. The proposed method uses the Euclidean distance metric and bootstrapping to calculate the significance level.
NASA Astrophysics Data System (ADS)
Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.
2007-06-01
This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.
NASA Technical Reports Server (NTRS)
Xu, Kuan-Man; Wong, Takmeng; Wielicki, Bruce A.; Parker, Lindsay
2006-01-01
Three boundary-layer cloud object types, stratus, stratocumulus and cumulus, that occurred over the Pacific Ocean during January-August 1998, are identified from the CERES (Clouds and the Earth s Radiant Energy System) single scanner footprint (SSF) data from the TRMM (Tropical Rainfall Measuring Mission) satellite. This study emphasizes the differences and similarities in the characteristics of each cloud-object type between the tropical and subtropical regions and among different size categories and among small geographic areas. Both the frequencies of occurrence and statistical distributions of cloud physical properties are analyzed. In terms of frequencies of occurrence, stratocumulus clouds dominate the entire boundary layer cloud population in all regions and among all size categories. Stratus clouds are more prevalent in the subtropics and near the coastal regions, while cumulus clouds are relatively prevalent over open ocean and the equatorial regions, particularly, within the small size categories. The largest size category of stratus cloud objects occurs more frequently in the subtropics than in the tropics and has much larger average size than its cumulus and stratocumulus counterparts. Each of the three cloud object types exhibits small differences in statistical distributions of cloud optical depth, liquid water path, TOA albedo and perhaps cloud-top height, but large differences in those of cloud-top temperature and OLR between the tropics and subtropics. Differences in the sea surface temperature (SST) distributions between the tropics and subtropics influence some of the cloud macrophysical properties, but cloud microphysical properties and albedo for each cloud object type are likely determined by (local) boundary-layer dynamics and structures. Systematic variations of cloud optical depth, TOA albedo, cloud-top height, OLR and SST with cloud object sizes are pronounced for the stratocumulus and stratus types, which are related to systematic variations of the strength of inversion with cloud object sizes, produced by large-scale subsidence. The differences in cloud macrophysical properties over small regions are significantly larger than those of cloud microphysical properties and TOA albedo, suggesting a greater control of (local) large-scale dynamics and other factors on cloud object properties. When the three cloud object types are combined, the relative population among the three types is the most important factor for determining the cloud object properties in a Pacific transect where the transition of boundary-layer cloud types takes place.
Bias Reduction as Guidance for Developing Convection and Cloud Parameterization in GFDL AM4/CM4
NASA Astrophysics Data System (ADS)
Zhao, M.; Held, I.; Golaz, C.
2016-12-01
The representations of moist convection and clouds are challenging in global climate models and they are known to be important to climate simulations at all spatial and temporal scales. Many climate simulation biases can be traced to deficiencies in convection and cloud parameterizations. I will present some key biases that we are concerned about and the efforts that we have made to reduce the biases during the development of NOAA's Geophysical Fluid Dynamics Laboratory (GFDL) new generation global climate model AM4/CM4. In particular, I will present a modified version of the moist convection scheme that is based on the University of Washington Shallow Cumulus scheme (UWShCu, Bretherton et. al 2004). The new scheme produces marked improvement in simulation of the Madden-Julian Oscillation (MJO) and the El Niño-Southern Oscillation (ENSO) compared to that used in AM3 and HIRAM. AM4/CM4 also produces high quality simulation of global distribution of cloud radiative effects and the precipitation with realistic mean climate state. This differs from models of improved MJO but with a much deteriorated mean state. The modifications to the UWShCu include an additional bulk plume for representing deep convection. The entrainment rate in the deep plume is parameterized to be a function of column-integrated relative humidity. The deep convective closure is based on relaxation of the convective available potential energy (CAPE) or cloud work function. The plumes' precipitation efficiency is optimized for better simulations of the cloud radiative effects. Precipitation re-evaporation is included in both shallow and deep plumes. In addition, a parameterization of convective gustiness is included with an energy source driven by cold pool derived from precipitation re-evaporation within the boundary layer and energy sink due to dissipation. I will present the motivations of these changes which are driven by reducing some aspects of the AM4/CM4 biases. Finally, I will also present the biases in current AM4/CM4 and challenges to further reduce them.
Insights into low-latitude cloud feedbacks from high-resolution models.
Bretherton, Christopher S
2015-11-13
Cloud feedbacks are a leading source of uncertainty in the climate sensitivity simulated by global climate models (GCMs). Low-latitude boundary-layer and cumulus cloud regimes are particularly problematic, because they are sustained by tight interactions between clouds and unresolved turbulent circulations. Turbulence-resolving models better simulate such cloud regimes and support the GCM consensus that they contribute to positive global cloud feedbacks. Large-eddy simulations using sub-100 m grid spacings over small computational domains elucidate marine boundary-layer cloud response to greenhouse warming. Four observationally supported mechanisms contribute: 'thermodynamic' cloudiness reduction from warming of the atmosphere-ocean column, 'radiative' cloudiness reduction from CO2- and H2O-induced increase in atmospheric emissivity aloft, 'stability-induced' cloud increase from increased lower tropospheric stratification, and 'dynamical' cloudiness increase from reduced subsidence. The cloudiness reduction mechanisms typically dominate, giving positive shortwave cloud feedback. Cloud-resolving models with horizontal grid spacings of a few kilometres illuminate how cumulonimbus cloud systems affect climate feedbacks. Limited-area simulations and superparameterized GCMs show upward shift and slight reduction of cloud cover in a warmer climate, implying positive cloud feedbacks. A global cloud-resolving model suggests tropical cirrus increases in a warmer climate, producing positive longwave cloud feedback, but results are sensitive to subgrid turbulence and ice microphysics schemes. © 2015 The Author(s).
Jiang, Shunrong; Zhu, Xiaoyan; Wang, Liangmin
2015-01-01
Mobile healthcare social networks (MHSNs) have emerged as a promising next-generation healthcare system, which will significantly improve the quality of life. However, there are many security and privacy concerns before personal health information (PHI) is shared with other parities. To ensure patients’ full control over their PHI, we propose a fine-grained and scalable data access control scheme based on attribute-based encryption (ABE). Besides, policies themselves for PHI sharing may be sensitive and may reveal information about underlying PHI or about data owners or recipients. In our scheme, we let each attribute contain an attribute name and its value and adopt the Bloom filter to efficiently check attributes before decryption. Thus, the data privacy and policy privacy can be preserved in our proposed scheme. Moreover, considering the fact that the computational cost grows with the complexity of the access policy and the limitation of the resource and energy in a smart phone, we outsource ABE decryption to the cloud while preventing the cloud from learning anything about the content and access policy. The security and performance analysis is carried out to demonstrate that our proposed scheme can achieve fine-grained access policies for PHI sharing in MHSNs. PMID:26404300
Jiang, Shunrong; Zhu, Xiaoyan; Wang, Liangmin
2015-09-03
Mobile healthcare social networks (MHSNs) have emerged as a promising next-generation healthcare system, which will significantly improve the quality of life. However, there are many security and privacy concerns before personal health information (PHI) is shared with other parities. To ensure patients' full control over their PHI, we propose a fine-grained and scalable data access control scheme based on attribute-based encryption (ABE). Besides, policies themselves for PHI sharing may be sensitive and may reveal information about underlying PHI or about data owners or recipients. In our scheme, we let each attribute contain an attribute name and its value and adopt the Bloom filter to efficiently check attributes before decryption. Thus, the data privacy and policy privacy can be preserved in our proposed scheme. Moreover, considering the fact that the computational cost grows with the complexity of the access policy and the limitation of the resource and energy in a smart phone, we outsource ABE decryption to the cloud while preventing the cloud from learning anything about the content and access policy. The security and performance analysis is carried out to demonstrate that our proposed scheme can achieve fine-grained access policies for PHI sharing in MHSNs.
NASA Astrophysics Data System (ADS)
Rothenberg, Daniel; Avramov, Alexander; Wang, Chien
2018-06-01
Interactions between aerosol particles and clouds contribute a great deal of uncertainty to the scientific community's understanding of anthropogenic climate forcing. Aerosol particles serve as the nucleation sites for cloud droplets, establishing a direct linkage between anthropogenic particulate emissions and clouds in the climate system. To resolve this linkage, the community has developed parameterizations of aerosol activation which can be used in global climate models to interactively predict cloud droplet number concentrations (CDNCs). However, different activation schemes can exhibit different sensitivities to aerosol perturbations in different meteorological or pollution regimes. To assess the impact these different sensitivities have on climate forcing, we have coupled three different core activation schemes and variants with the CESM-MARC (two-Moment, Multi-Modal, Mixing-state-resolving Aerosol model for Research of Climate (MARC) coupled with the National Center for Atmospheric Research's (NCAR) Community Earth System Model (CESM; version 1.2)). Although the model produces a reasonable present-day CDNC climatology when compared with observations regardless of the scheme used, ΔCDNCs between the present and preindustrial era regionally increase by over 100 % in zonal mean when using the most sensitive parameterization. These differences in activation sensitivity may lead to a different evolution of the model meteorology, and ultimately to a spread of over 0.8 W m-2 in global average shortwave indirect effect (AIE) diagnosed from the model, a range which is as large as the inter-model spread from the AeroCom intercomparison. Model-derived AIE strongly scales with the simulated preindustrial CDNC burden, and those models with the greatest preindustrial CDNC tend to have the smallest AIE, regardless of their ΔCDNC. This suggests that present-day evaluations of aerosol-climate models may not provide useful constraints on the magnitude of the AIE, which will arise from differences in model estimates of the preindustrial aerosol and cloud climatology.
Study of Huizhou architecture component point cloud in surface reconstruction
NASA Astrophysics Data System (ADS)
Zhang, Runmei; Wang, Guangyin; Ma, Jixiang; Wu, Yulu; Zhang, Guangbin
2017-06-01
Surface reconfiguration softwares have many problems such as complicated operation on point cloud data, too many interaction definitions, and too stringent requirements for inputing data. Thus, it has not been widely popularized so far. This paper selects the unique Huizhou Architecture chuandou wooden beam framework as the research object, and presents a complete set of implementation in data acquisition from point, point cloud preprocessing and finally implemented surface reconstruction. Firstly, preprocessing the acquired point cloud data, including segmentation and filtering. Secondly, the surface’s normals are deduced directly from the point cloud dataset. Finally, the surface reconstruction is studied by using Greedy Projection Triangulation Algorithm. Comparing the reconstructed model with the three-dimensional surface reconstruction softwares, the results show that the proposed scheme is more smooth, time efficient and portable.
Explicit prediction of ice clouds in general circulation models
NASA Astrophysics Data System (ADS)
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) and falling snow (diagnosed) components. An empirical parameterization of the effect of upward turbulent water fluxes in cloud layers is obtained from the CRM simulations by (1) identifying the time-scale of conversion of cloud ice to snow as the key parameter, and (2) regressing it onto cloud differential IR heating and environmental static stability. The updated UCLA-GCM achieves close agreement with observations in global mean top of atmosphere fluxes (within 1--4 W/m2). Artificially suppressing the impact of cloud turbulent fluxes reduces the global mean ice water path by a factor of 3 and produces errors in each of solar and IR fluxes at the top of atmosphere of about 5--6 W/m2.
NASA Technical Reports Server (NTRS)
Lang, Stephen E.; Tao, Wei-Kuo; Chern, Jiun-Dar; Wu, Di; Li, Xiaowen
2015-01-01
Numerous cloud microphysical schemes designed for cloud and mesoscale models are currently in use, ranging from simple bulk to multi-moment, multi-class to explicit bin schemes. This study details the benefits of adding a 4th ice class (hail) to an already improved 3-class ice bulk microphysics scheme developed for the Goddard Cumulus Ensemble model based on Rutledge and Hobbs (1983,1984). Besides the addition and modification of several hail processes from Lin et al. (1983), further modifications were made to the 3-ice processes, including allowing greater ice super saturation and mitigating spurious evaporationsublimation in the saturation adjustment scheme, allowing graupelhail to become snow via vapor growth and hail to become graupel via riming, and the inclusion of a rain evaporation correction and vapor diffusivity factor. The improved 3-ice snowgraupel size-mapping schemes were adjusted to be more stable at higher mixing rations and to increase the aggregation effect for snow. A snow density mapping was also added. The new scheme was applied to an intense continental squall line and a weaker, loosely-organized continental case using three different hail intercepts. Peak simulated reflectivities agree well with radar for both the intense and weaker case and were better than earlier 3-ice versions when using a moderate and large intercept for hail, respectively. Simulated reflectivity distributions versus height were also improved versus radar in both cases compared to earlier 3-ice versions. The bin-based rain evaporation correction affected the squall line case more but did not change the overall agreement in reflectivity distributions.
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo; Li, Xiaowen; Khain, Alexander; Matsui, Toshihisa; Lang, Stephen; Simpson, Joanne
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.
Intercomparison of microphysical datasets collected from CAIPEEX observations and WRF simulation
NASA Astrophysics Data System (ADS)
Pattnaik, S.; Goswami, B.; Kulkarni, J.
2009-12-01
In the first phase of ongoing Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) program of Indian Institute of Tropical Meteorology (IITM), intensive cloud microphysical datasets are collected over India during the May through September, 2009. This study is designed to evaluate the forecast skills of existing cloud microphysical parameterization schemes (i.e. single moment/double moments) within the WRF-ARW model (Version 3.1.1) during different intensive observation periods (IOP) over the targeted regions spreading all across India. Basic meteorological and cloud microphysical parameters obtained from the model simulations are validated against the observed data set collected during CAIPEEX program. For this study, we have considered three IOP phases (i.e. May 23-27, June 11-15, July 3-7) carried out over northern, central and western India respectively. This study emphasizes the thrust to understand the mechanism of evolution, intensification and distribution of simulated precipitation forecast upto day four (i.e. 96 hour forecast). Efforts have also been made to carryout few important microphysics sensitivity experiments within the explicit schemes to investigate their respective impact on the formation and distribution of vital cloud parameters (e.g. cloud liquid water, frozen hydrometeors) and model rainfall forecast over the IOP regions. The characteristic features of liquid and frozen hydrometers in the pre-monsoon and monsoon regimes are examined from model forecast as well as from CAIPEEX observation data set for different IOPs. The model is integrated in a triply nested fashion with an innermost nest explicitly resolved at a horizontal resolution of 4km.In this presentation preliminary results from aforementioned research initiatives will be introduced.
NASA Technical Reports Server (NTRS)
Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent
2012-01-01
The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.
NASA Astrophysics Data System (ADS)
Protat, A.; Delanoë, J.; May, P. T.; Haynes, J.; Jakob, C.; O'Connor, E.; Pope, M.; Wheeler, M. C.
2011-08-01
The high complexity of cloud parameterizations now held in models puts more pressure on observational studies to provide useful means to evaluate them. One approach to the problem put forth in the modelling community is to evaluate under what atmospheric conditions the parameterizations fail to simulate the cloud properties and under what conditions they do a good job. It is the ambition of this paper to characterize the variability of the statistical properties of tropical ice clouds in different tropical "regimes" recently identified in the literature to aid the development of better process-oriented parameterizations in models. For this purpose, the statistical properties of non-precipitating tropical ice clouds over Darwin, Australia are characterized using ground-based radar-lidar observations from the Atmospheric Radiation Measurement (ARM) Program. The ice cloud properties analysed are the frequency of ice cloud occurrence, the morphological properties (cloud top height and thickness), and the microphysical and radiative properties (ice water content, visible extinction, effective radius, and total concentration). The variability of these tropical ice cloud properties is then studied as a function of the large-scale cloud regimes derived from the International Satellite Cloud Climatology Project (ISCCP), the amplitude and phase of the Madden-Julian Oscillation (MJO), and the large-scale atmospheric regime as derived from a long-term record of radiosonde observations over Darwin. The vertical variability of ice cloud occurrence and microphysical properties is largest in all regimes (1.5 order of magnitude for ice water content and extinction, a factor 3 in effective radius, and three orders of magnitude in concentration, typically). 98 % of ice clouds in our dataset are characterized by either a small cloud fraction (smaller than 0.3) or a very large cloud fraction (larger than 0.9). In the ice part of the troposphere three distinct layers characterized by different statistically-dominant microphysical processes are identified. The variability of the ice cloud properties as a function of the large-scale atmospheric regime, cloud regime, and MJO phase is large, producing mean differences of up to a factor 8 in the frequency of ice cloud occurrence between large-scale atmospheric regimes and mean differences of a factor 2 typically in all microphysical properties. Finally, the diurnal cycle of the frequency of occurrence of ice clouds is also very different between regimes and MJO phases, with diurnal amplitudes of the vertically-integrated frequency of ice cloud occurrence ranging from as low as 0.2 (weak diurnal amplitude) to values in excess of 2.0 (very large diurnal amplitude). Modellers should now use these results to check if their model cloud parameterizations are capable of translating a given atmospheric forcing into the correct statistical ice cloud properties.
A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment
Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda
2017-01-01
In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment. PMID:28629131
A Hybrid Scheme for Fine-Grained Search and Access Authorization in Fog Computing Environment.
Xiao, Min; Zhou, Jing; Liu, Xuejiao; Jiang, Mingda
2017-06-17
In the fog computing environment, the encrypted sensitive data may be transferred to multiple fog nodes on the edge of a network for low latency; thus, fog nodes need to implement a search over encrypted data as a cloud server. Since the fog nodes tend to provide service for IoT applications often running on resource-constrained end devices, it is necessary to design lightweight solutions. At present, there is little research on this issue. In this paper, we propose a fine-grained owner-forced data search and access authorization scheme spanning user-fog-cloud for resource constrained end users. Compared to existing schemes only supporting either index encryption with search ability or data encryption with fine-grained access control ability, the proposed hybrid scheme supports both abilities simultaneously, and index ciphertext and data ciphertext are constructed based on a single ciphertext-policy attribute based encryption (CP-ABE) primitive and share the same key pair, thus the data access efficiency is significantly improved and the cost of key management is greatly reduced. Moreover, in the proposed scheme, the resource constrained end devices are allowed to rapidly assemble ciphertexts online and securely outsource most of decryption task to fog nodes, and mediated encryption mechanism is also adopted to achieve instantaneous user revocation instead of re-encrypting ciphertexts with many copies in many fog nodes. The security and the performance analysis show that our scheme is suitable for a fog computing environment.
NASA Technical Reports Server (NTRS)
Slobin, S. D.; Piazzolla, S.
2002-01-01
Cloud opacity is one of the main atmospheric physical phenomena that can jeopardize the successful completion of an optical link between a spacecraft and a ground station. Hence, the site location chosen for a telescope used for optical communications must rely on knowledge of weather and cloud cover statistics for the geographical area where the telescope itself is located.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Newsom, R. K.; Sivaraman, C.; Shippert, T. R.
Accurate height-resolved measurements of higher-order statistical moments of vertical velocity fluctuations are crucial for improved understanding of turbulent mixing and diffusion, convective initiation, and cloud life cycles. The Atmospheric Radiation Measurement (ARM) Climate Research Facility operates coherent Doppler lidar systems at several sites around the globe. These instruments provide measurements of clear-air vertical velocity profiles in the lower troposphere with a nominal temporal resolution of 1 sec and height resolution of 30 m. The purpose of the Doppler lidar vertical velocity statistics (DLWSTATS) value-added product (VAP) is to produce height- and time-resolved estimates of vertical velocity variance, skewness, and kurtosismore » from these raw measurements. The VAP also produces estimates of cloud properties, including cloud-base height (CBH), cloud frequency, cloud-base vertical velocity, and cloud-base updraft fraction.« less
NASA Astrophysics Data System (ADS)
Heus, Thijs; Jonker, Harm J. J.; van den Akker, Harry E. A.; Griffith, Eric J.; Koutek, Michal; Post, Frits H.
2009-03-01
In this study, a new method is developed to investigate the entire life cycle of shallow cumuli in large eddy simulations. Although trained observers have no problem in distinguishing the different life stages of a cloud, this process proves difficult to automate, because cloud-splitting and cloud-merging events complicate the distinction between a single system divided in several cloudy parts and two independent systems that collided. Because the human perception is well equipped to capture and to make sense of these time-dependent three-dimensional features, a combination of automated constraints and human inspection in a three-dimensional virtual reality environment is used to select clouds that are exemplary in their behavior throughout their entire life span. Three specific cases (ARM, BOMEX, and BOMEX without large-scale forcings) are analyzed in this way, and the considerable number of selected clouds warrants reliable statistics of cloud properties conditioned on the phase in their life cycle. The most dominant feature in this statistical life cycle analysis is the pulsating growth that is present throughout the entire lifetime of the cloud, independent of the case and of the large-scale forcings. The pulses are a self-sustained phenomenon, driven by a balance between buoyancy and horizontal convergence of dry air. The convective inhibition just above the cloud base plays a crucial role as a barrier for the cloud to overcome in its infancy stage, and as a buffer region later on, ensuring a steady supply of buoyancy into the cloud.
Global Multispectral Cloud Retrievals from MODIS
NASA Technical Reports Server (NTRS)
King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Riedi, Jerome C.; Baum, Bryan A.
2003-01-01
The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18,1999 and Aqua spacecraft on May 4,2002. It achieved its final orbit and began Earth observations on February 24, 2000 for Terra and June 24, 2002 for Aqua. A comprehensive set of remote sensing algorithms for cloud masking and the retrieval of cloud physical and optical properties has been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various cloud properties being analyzed on a global basis from both Terra and Aqua, and will show characteristics of cloud optical and microphysical properties as a function of latitude for land and ocean separately, and contrast the statistical properties of similar cloud types in various parts of the world.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fan, Jiwen; Liu, Yi-Chin; Xu, Kuan-Man
2015-04-27
The ultimate goal of this study is to improve representation of convective transport by cumulus parameterization for meso-scale and climate models. As Part I of the study, we perform extensive evaluations of cloud-resolving simulations of a squall line and mesoscale convective complexes in mid-latitude continent and tropical regions using the Weather Research and Forecasting (WRF) model with spectral-bin microphysics (SBM) and with two double-moment bulk microphysics schemes: a modified Morrison (MOR) and Milbrandt and Yau (MY2). Compared to observations, in general, SBM gives better simulations of precipitation, vertical velocity of convective cores, and the vertically decreasing trend of radar reflectivitymore » than MOR and MY2, and therefore will be used for analysis of scale-dependence of eddy transport in Part II. The common features of the simulations for all convective systems are (1) the model tends to overestimate convection intensity in the middle and upper troposphere, but SBM can alleviate much of the overestimation and reproduce the observed convection intensity well; (2) the model greatly overestimates radar reflectivity in convective cores (SBM predicts smaller radar reflectivity but does not remove the large overestimation); and (3) the model performs better for mid-latitude convective systems than tropical system. The modeled mass fluxes of the mid latitude systems are not sensitive to microphysics schemes, but are very sensitive for the tropical case indicating strong microphysics modification to convection. Cloud microphysical measurements of rain, snow and graupel in convective cores will be critically important to further elucidate issues within cloud microphysics schemes.« less
Statistical analysis of lightning electric field measured under Malaysian condition
NASA Astrophysics Data System (ADS)
Salimi, Behnam; Mehranzamir, Kamyar; Abdul-Malek, Zulkurnain
2014-02-01
Lightning is an electrical discharge during thunderstorms that can be either within clouds (Inter-Cloud), or between clouds and ground (Cloud-Ground). The Lightning characteristics and their statistical information are the foundation for the design of lightning protection system as well as for the calculation of lightning radiated fields. Nowadays, there are various techniques to detect lightning signals and to determine various parameters produced by a lightning flash. Each technique provides its own claimed performances. In this paper, the characteristics of captured broadband electric fields generated by cloud-to-ground lightning discharges in South of Malaysia are analyzed. A total of 130 cloud-to-ground lightning flashes from 3 separate thunderstorm events (each event lasts for about 4-5 hours) were examined. Statistical analyses of the following signal parameters were presented: preliminary breakdown pulse train time duration, time interval between preliminary breakdowns and return stroke, multiplicity of stroke, and percentages of single stroke only. The BIL model is also introduced to characterize the lightning signature patterns. Observations on the statistical analyses show that about 79% of lightning signals fit well with the BIL model. The maximum and minimum of preliminary breakdown time duration of the observed lightning signals are 84 ms and 560 us, respectively. The findings of the statistical results show that 7.6% of the flashes were single stroke flashes, and the maximum number of strokes recorded was 14 multiple strokes per flash. A preliminary breakdown signature in more than 95% of the flashes can be identified.
NASA Astrophysics Data System (ADS)
Garratt, J. R.
1993-03-01
Aspects of the land-surface and boundary-layer treatments in some 20 or so atmospheric general circulation models (GCMS) are summarized. In only a small fraction of these have significant sensitivity studies been carried out and published. Predominantly, the sensitivity studies focus upon the parameterization of land-surface processes and specification of land-surface properties-the most important of these include albedo, roughness length, soil moisture status, and vegetation density. The impacts of surface albedo and soil moisture upon the climate simulated in GCMs with bare-soil land surfaces are well known. Continental evaporation and precipitation tend to decrease with increased albedo and decreased soil moisture availability. For example, results from numerous studies give an average decrease in continental precipitation of 1 mm day1 in response to an average albedo increase of 0.13. Few conclusive studies have been carried out on the impact of a gross roughness-length change-the primary study included an important statistical assessment of the impact upon the mean July climate around the globe of a decreased continental roughness (by three orders of magnitude). For example, such a decrease reduced the precipitation over Amazonia by 1 to 2 mm day1.The inclusion of a canopy scheme in a GCM ensures the combined impacts of roughness (canopies tend to be rougher than bare soil), albedo (canopies tend to be less reflective than bare soil), and soil-moisture availability (canopies prevent the near-surface soil region from drying out and can access the deep soil moisture) upon the simulated climate. The most revealing studies to date involve the regional impact of Amazonian deforestation. The results of four such studies show that replacing tropical forest with a degraded pasture results in decreased evaporation ( 1 mm day1) and precipitation (1-2 mm day1), and increased near-surface air temperatures (2 K).Sensitivity studies as a whole suggest the need for a realistic surface representation in general circulation models of the atmosphere. It is not yet clear how detailed this representation needs to be, but even allowing for the importance of surface processes, the parameterization of boundary-layer and convective clouds probably represents a greater challenge to improved climate simulations. This is illustrated in the case of surface net radiation for Aniazonia, which is not well simulated and tends to be overestimated, leading to evaporation rates that are too large. Underestimates in cloudiness, cloud albedo, and clear-sky shortwave absorption, rather than in surface albedo, appear to be the main culprits.There are three major tasks that confront the researcher so far as the development and validation of atmospheric boundary-layer (ABL) and surface schemes in GCMs are concerned:(i) There is a need to as' critically the impact of `improved' parameterization schemes on WM simulations, taking into account the problem of natural variability and hence the statistical significance of the induced changes.(ii) There is a need to compare GCM simulations of surface and ABL behavior (particularly regarding the diurnal cycle of surface fluxes, air temperature, and ABL depth) with observations over a range of surface types (vegetation, desert, ocean). In this context, area-average values of surface fluxes will be required to calibrate directly the ABL/land-surface scheme in the GCM.(iii) There is a need for intercomparisons of ABL and land-surface schemes used in GCMS, both for one- dimensional stand-alone models and for GCMs that incorporate the respective schemes.
NASA Astrophysics Data System (ADS)
Lee, Hsiang-He; Chen, Shu-Hua; Kleeman, Michael J.; Zhang, Hongliang; DeNero, Steven P.; Joe, David K.
2016-07-01
The source-oriented Weather Research and Forecasting chemistry model (SOWC) was modified to include warm cloud processes and was applied to investigate how aerosol mixing states influence fog formation and optical properties in the atmosphere. SOWC tracks a 6-D chemical variable (X, Z, Y, size bins, source types, species) through an explicit simulation of atmospheric chemistry and physics. A source-oriented cloud condensation nuclei module was implemented into the SOWC model to simulate warm clouds using the modified two-moment Purdue Lin microphysics scheme. The Goddard shortwave and long-wave radiation schemes were modified to interact with source-oriented aerosols and cloud droplets so that aerosol direct and indirect effects could be studied. The enhanced SOWC model was applied to study a fog event that occurred on 17 January 2011, in the Central Valley of California. Tule fog occurred because an atmospheric river effectively advected high moisture into the Central Valley and nighttime drainage flow brought cold air from mountains into the valley. The SOWC model produced reasonable liquid water path, spatial distribution and duration of fog events. The inclusion of aerosol-radiation interaction only slightly modified simulation results since cloud optical thickness dominated the radiation budget in fog events. The source-oriented mixture representation of particles reduced cloud droplet number relative to the internal mixture approach that artificially coats hydrophobic particles with hygroscopic components. The fraction of aerosols activating into cloud condensation nuclei (CCN) at a supersaturation of 0.5 % in the Central Valley decreased from 94 % in the internal mixture model to 80 % in the source-oriented model. This increased surface energy flux by 3-5 W m-2 and surface temperature by as much as 0.25 K in the daytime.
NASA Technical Reports Server (NTRS)
Stanfield, Ryan E.; Dong, Xiquan; Xi, Baike; Del Genio, Anthony D.; Minnis, Patrick; Doelling, David; Loeb, Norman
2014-01-01
In Part I of this study, the NASA GISS Coupled Model Intercomparison Project (CMIP5) and post-CMIP5 (herein called C5 and P5, respectively) simulated cloud properties were assessed utilizing multiple satellite observations, with a particular focus on the southern midlatitudes (SMLs). This study applies the knowledge gained from Part I of this series to evaluate the modeled TOA radiation budgets and cloud radiative effects (CREs) globally using CERES EBAF (CE) satellite observations and the impact of regional cloud properties and water vapor on the TOA radiation budgets. Comparisons revealed that the P5- and C5-simulated global means of clear-sky and all-sky outgoing longwave radiation (OLR) match well with CE observations, while biases are observed regionally. Negative biases are found in both P5- and C5-simulated clear-sky OLR. P5-simulated all-sky albedo slightly increased over the SMLs due to the increase in low-level cloud fraction from the new planetary boundary layer (PBL) scheme. Shortwave, longwave, and net CRE are quantitatively analyzed as well. Regions of strong large-scale atmospheric upwelling/downwelling motion are also defined to compare regional differences across multiple cloud and radiative variables. In general, the P5 and C5 simulations agree with the observations better over the downwelling regime than over the upwelling regime. Comparing the results herein with the cloud property comparisons presented in Part I, the modeled TOA radiation budgets and CREs agree well with the CE observations. These results, combined with results in Part I, have quantitatively estimated how much improvement is found in the P5-simulated cloud and radiative properties, particularly over the SMLs and tropics, due to the implementation of the new PBL and convection schemes.
NASA Astrophysics Data System (ADS)
Wu, M.; Liu, X.; Luo, T.; Wang, Z.; Yang, K.; Wu, C.; Wang, H.; Zhang, K.
2017-12-01
Mineral dust plays an important role in the Earth's climate system due to its effects on radiation budgets, clouds, chemistry and biosphere. However, modeled dust aerosol is not well constrained and large uncertainties exist in modeled dust lifecycles. We evaluate dust spatial distributions in the Community Earth System Model (CESM) with new dust extinction retrievals (Luo et al., 2015a, b) based on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO) and CloudSat measurement, with special focus on the Asian dust transport across the Pacific. It is shown that the default CESM underestimates the dust extinction over the Pacific by 1-2 order of magnitude. Especially, the model fails to capture the observed high values of dust extinction occurring from 850 to 500 hPa across the North Pacific (20°N-50°N). Modeled dust optical depth (DOD) decreases faster across the Pacific compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging SpectroRadiometer (MISR) observations. Sensitivity experiments with altered emission, vertical transport and deposition schemes have been conducted to identify the key process impacting dust transport. For that purpose, two new dust emission schemes by Kok et al. (2014a, b) and Ginoux et al. (2001), a new dry deposition scheme by Petroff and Zhang (2010) are implemented to the CESM. In addition, a new unified scheme for convective transport and wet removal of aerosols (Wang et al., 2013) is implemented to the same version of CESM to examine the influence of convective transport and wet deposition on dust transport. It is found that changes in wet scavenging and convective transport can strongly impact dust transport over the Pacific compared to changes in other processes. One of the new emission schemes further decreases the dust extinction across the Pacific. Dust extinction across the Pacific slightly increases when dry deposition velocity for fine particles is reduced.
Classifying stages of cirrus life-cycle evolution
NASA Astrophysics Data System (ADS)
Urbanek, Benedikt; Groß, Silke; Schäfler, Andreas; Wirth, Martin
2018-04-01
Airborne lidar backscatter data is used to determine in- and out-of-cloud regions. Lidar measurements of water vapor together with model temperature fields are used to calculate relative humidity over ice (RHi). Based on temperature and RHi we identify different stages of cirrus evolution: homogeneous and heterogeneous freezing, depositional growth, ice sublimation and sedimentation. We will present our classification scheme and first applications on mid-latitude cirrus clouds.
NASA Technical Reports Server (NTRS)
Molthan, Andrew L.; Jedlovec, Gary J.; Lapenta, William M.
2008-01-01
The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.
NASA Astrophysics Data System (ADS)
Xiao, Hui; Yin, Yan; Jin, Lianji; Chen, Qian; Chen, Jinghua
2015-08-01
The Weather Research Forecast (WRF) mesoscale model coupled with a detailed bin microphysics scheme is used to investigate the impact of aerosol particles serving as cloud condensation nuclei and ice nuclei on orographic clouds and precipitation. A mixed-phase orographic cloud developed under two scenarios of aerosol (a typical continental background and a relatively polluted urban condition) and ice nuclei over an idealized mountain is simulated. The results show that, when the initial aerosol condition is changed from the relatively clean case to the polluted scenario, more droplets are activated, leading to a delay in precipitation, but the precipitation amount over the terrain is increased by about 10%. A detailed analysis of the microphysical processes indicates that ice-phase particles play an important role in cloud development, and their contribution to precipitation becomes more important with increasing aerosol particle concentrations. The growth of ice-phase particles through riming and Wegener-Bergeron-Findeisen regime is more effective under more polluted conditions, mainly due to the increased number of droplets with a diameter of 10-30 µm. Sensitivity tests also show that a tenfold increase in the concentration of ice crystals formed from ice nucleation leads to about 7% increase in precipitation, and the sensitivity of the precipitation to changes in the concentration and size distribution of aerosol particles is becoming less pronounced when the concentration of ice crystals is also increased.
Modeling Jupiter's Great Red Spot with an Active Hydrological Cycle
NASA Astrophysics Data System (ADS)
Palotai, C. J.; Dowling, T. E.; Morales-Juberías, R.
2003-05-01
We are studying the interaction of Jupiter's hydrological cycle with the formation and maintenance of its long-lived vortices and jet streams using numerical simulations. We are particularly interested in establishing the importance of the large convective storm system to the northwest of Jupiter's Great Red Spot (GRS). We have adapted into the EPIC model the cloud microphysics scheme used at Colorado State University (Fowler et al. 1996, J. Cli. 9, 489), which contains prognostic equations for vapor, liquid cloud, ice cloud, rain and snow. We are focussing on the role of water, but the EPIC model can also handle multiple species (water, ammonia, etc.). Processes that are currently working in the microphysics model include large-scale condensation/deposition, cloud evaporation, melting/freezing, and Bergeron-Findeisen diffusional growth of ice from supercooled liquid. The form of precipitation on gas giants is a major unknown. We are currently using a simple scheme for precipitation, but are studying the effect that processes known to be important in terrestrial models have on our results, including formation and accretion of rain and snow, preciptation evaporation, detrainment and cloud-top entrainment. We will present comparisons of ``dry'' and ``wet'' runs of a channel Jupiter EPIC simulation covering -40S to the equator that includes various initial water-vapor profiles and a GRS model. The effects of latent heating on the energy budget and vertical transport will be discussed. This research is funded by NASA's Planetary Atmospheres and EPSCoR Programs.
NASA Technical Reports Server (NTRS)
Oreopoulos, L.; Chou, M.-D.; Khairoutdinov, M.; Barker, H. W.; Cahalan, R. F.
2003-01-01
We test the performance of the shortwave (SW) and longwave (LW) Column Radiation Models (CORAMs) of Chou and collaborators with heterogeneous cloud fields from a global single-day dataset produced by NCAR's Community Atmospheric Model with a 2-D CRM installed in each gridbox. The original SW version of the CORAM performs quite well compared to reference Independent Column Approximation (ICA) calculations for boundary fluxes, largely due to the success of a combined overlap and cloud scaling parameterization scheme. The absolute magnitude of errors relative to ICA are even smaller for the LW CORAM which applies similar overlap. The vertical distribution of heating and cooling within the atmosphere is also simulated quite well with daily-averaged zonal errors always below 0.3 K/d for SW heating rates and 0.6 K/d for LW cooling rates. The SW CORAM's performance improves by introducing a scheme that accounts for cloud inhomogeneity. These results suggest that previous studies demonstrating the inaccuracy of plane-parallel models may have unfairly focused on worst scenario cases, and that current radiative transfer algorithms of General Circulation Models (GCMs) may be more capable than previously thought in estimating realistic spatial and temporal averages of radiative fluxes, as long as they are provided with correct mean cloud profiles. However, even if the errors of the particular CORAMs are small, they seem to be systematic, and the impact of the biases can be fully assessed only with GCM climate simulations.
Two-stage atlas subset selection in multi-atlas based image segmentation.
Zhao, Tingting; Ruan, Dan
2015-06-01
Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas subset selection scheme for multi-atlas based segmentation. It achieves good segmentation accuracy with significantly reduced computation cost, making it a suitable configuration in the presence of extensive heterogeneous atlases.
NASA Astrophysics Data System (ADS)
Lee, H.; Fridlind, A. M.; Ackerman, A. S.; Kollias, P.
2017-12-01
Cloud radar Doppler spectra provide rich information for evaluating the fidelity of particle size distributions from cloud models. The intrinsic simplifications of bulk microphysics schemes generally preclude the generation of plausible Doppler spectra, unlike bin microphysics schemes, which develop particle size distributions more organically at substantial computational expense. However, bin microphysics schemes face the difficulty of numerical diffusion leading to overly rapid large drop formation, particularly while solving the stochastic collection equation (SCE). Because such numerical diffusion can cause an even greater overestimation of radar reflectivity, an accurate method for solving the SCE is essential for bin microphysics schemes to accurately simulate Doppler spectra. While several methods have been proposed to solve the SCE, here we examine those of Berry and Reinhardt (1974, BR74), Jacobson et al. (1994, J94), and Bott (2000, B00). Using a simple box model to simulate drop size distribution evolution during precipitation formation with a realistic kernel, it is shown that each method yields a converged solution as the resolution of the drop size grid increases. However, the BR74 and B00 methods yield nearly identical size distributions in time, whereas the J94 method produces consistently larger drops throughout the simulation. In contrast to an earlier study, the performance of the B00 method is found to be satisfactory; it converges at relatively low resolution and long time steps, and its computational efficiency is the best among the three methods considered here. Finally, a series of idealized stratocumulus large-eddy simulations are performed using the J94 and B00 methods. The reflectivity size distributions and Doppler spectra obtained from the different SCE solution methods are presented and compared with observations.
NASA Astrophysics Data System (ADS)
Peters, Karsten; Jakob, Christian; Möbis, Benjamin
2015-04-01
An adequate representation of convective processes in numerical models of the atmospheric circulation (general circulation models, GCMs) remains one of the grand challenges in atmospheric science. In particular, the models struggle with correctly representing the spatial distribution and high variability of tropical convection. It is thought that this model deficiency partly results from formulating current convection parameterisation schemes in a purely deterministic manner. Here, we use observations of tropical convection to inform the design of a novel convection parameterisation with stochastic elements. The novel scheme is built around the Stochastic MultiCloud Model (SMCM, Khouider et al 2010). We present the progress made in utilising SMCM-based estimates of updraft area fractions at cloud base as part of the deep convection scheme of a GCM. The updraft area fractions are used to yield one part of the cloud base mass-flux used in the closure assumption of convective mass-flux schemes. The closure thus receives a stochastic component, potentially improving modeled convective variability and coherence. For initial investigations, we apply the above methodology to the operational convective parameterisation of the ECHAM6 GCM. We perform 5-year AMIP simulations, i.e. with prescribed observed SSTs. We find that with the SMCM, convection is weaker and more coherent and continuous from timestep to timestep compared to the standard model. Total global precipitation is reduced in the SMCM run, but this reduces i) the overall error compared to observed global precipitation (GPCP) and ii) middle tropical tropospheric temperature biases compared to ERA-Interim. Hovmoeller diagrams indicate a slightly higher degree of convective organisation compared to the base case and Wheeler-Kiladis frequency wavenumber diagrams indicate slightly more spectral power in the MJO range.
Ozone formation during an episode over Europe: A 3-D chemical/transport model simulation
NASA Technical Reports Server (NTRS)
Berntsen, Terje; Isaksen, Ivar S. A.
1994-01-01
A 3-D regional photochemical tracer/transport model for Europe and the Eastern Atlantic has been developed based on the NASA/GISS CTM. The model resolution is 4x5 degrees latitude and longitude with 9 layers in the vertical (7 in the troposphere). Advective winds, convection statistics and other meteorological data from the NASA/GISS GCM are used. An extensive gas-phase chemical scheme based on the scheme used in our global 2D model has been incorporated in the 3D model. In this work ozone formation in the troposphere is studied with the 3D model during a 5 day period starting June 30. Extensive local ozone production is found and the relationship between the source regions and the downwind areas are discussed. Variations in local ozone formation as a function of total emission rate, as well as the composition of the emissions (HC/NO(x)) ratio and isoprene emissions) are elucidated. An important vertical transport process in the troposphere is by convective clouds. The 3D model includes an explicit parameterization of this process. It is shown that this process has significant influence on the calculated surface ozone concentrations.
cOSPREY: A Cloud-Based Distributed Algorithm for Large-Scale Computational Protein Design
Pan, Yuchao; Dong, Yuxi; Zhou, Jingtian; Hallen, Mark; Donald, Bruce R.; Xu, Wei
2016-01-01
Abstract Finding the global minimum energy conformation (GMEC) of a huge combinatorial search space is the key challenge in computational protein design (CPD) problems. Traditional algorithms lack a scalable and efficient distributed design scheme, preventing researchers from taking full advantage of current cloud infrastructures. We design cloud OSPREY (cOSPREY), an extension to a widely used protein design software OSPREY, to allow the original design framework to scale to the commercial cloud infrastructures. We propose several novel designs to integrate both algorithm and system optimizations, such as GMEC-specific pruning, state search partitioning, asynchronous algorithm state sharing, and fault tolerance. We evaluate cOSPREY on three different cloud platforms using different technologies and show that it can solve a number of large-scale protein design problems that have not been possible with previous approaches. PMID:27154509
Broadening of cloud droplet spectra through turbulent entrainment and eddy hopping
NASA Astrophysics Data System (ADS)
Abade, Gustavo; Grabowski, Wojciech; Pawlowska, Hanna
2017-11-01
This work discusses the effect of cloud turbulence and turbulent entrainment on the evolution of the cloud droplet-size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events, modeled as a random Poisson process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate and the mean fraction of environmental air entrained in an event are specified as external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. They are either unactivated cloud condensation nuclei (CCN) or cloud droplets that form from activated CCN. The model accounts for the transport of environmental CCN into the cloud by the entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using a linear model. We show that turbulence plays an important role in aiding entrained CCN to activate, providing a source of small cloud droplets and thus broadening the droplet size distribution. Further simulation results will be reported at the meeting.
Automated Detection of Clouds in Satellite Imagery
NASA Technical Reports Server (NTRS)
Jedlovec, Gary
2010-01-01
Many different approaches have been used to automatically detect clouds in satellite imagery. Most approaches are deterministic and provide a binary cloud - no cloud product used in a variety of applications. Some of these applications require the identification of cloudy pixels for cloud parameter retrieval, while others require only an ability to mask out clouds for the retrieval of surface or atmospheric parameters in the absence of clouds. A few approaches estimate a probability of the presence of a cloud at each point in an image. These probabilities allow a user to select cloud information based on the tolerance of the application to uncertainty in the estimate. Many automated cloud detection techniques develop sophisticated tests using a combination of visible and infrared channels to determine the presence of clouds in both day and night imagery. Visible channels are quite effective in detecting clouds during the day, as long as test thresholds properly account for variations in surface features and atmospheric scattering. Cloud detection at night is more challenging, since only courser resolution infrared measurements are available. A few schemes use just two infrared channels for day and night cloud detection. The most influential factor in the success of a particular technique is the determination of the thresholds for each cloud test. The techniques which perform the best usually have thresholds that are varied based on the geographic region, time of year, time of day and solar angle.
NASA Astrophysics Data System (ADS)
Hazra, Anupam; Chaudhari, Hemantkumar S.; Saha, Subodh Kumar; Pokhrel, Samir; Goswami, B. N.
2017-10-01
Simulation of the spatial and temporal structure of the monsoon intraseasonal oscillations (MISOs), which have effects on the seasonal mean and annual cycle of Indian summer monsoon (ISM) rainfall, remains a grand challenge for the state-of-the-art global coupled models. Biases in simulation of the amplitude and northward propagation of MISOs and related dry rainfall bias over ISM region in climate models are limiting the current skill of monsoon prediction. Recent observations indicate that the convective microphysics of clouds may be critical in simulating the observed MISOs. The hypothesis is strongly supported by high fidelity in simulation of the amplitude and space-time spectra of MISO by a coupled climate model, when our physically based modified cloud microphysics scheme is implemented in conjunction with a modified new Simple Arakawa Schubert (nSAS) convective parameterization scheme. Improved simulation of MISOs appears to have been aided by much improved simulation of the observed high cloud fraction and convective to stratiform rain fractions and resulted into a much improved simulation of the ISM rainfall, monsoon onset, and the annual cycle.
NASA Astrophysics Data System (ADS)
Keslake, Tim; Chipperfield, Martyn; Mann, Graham; Flemming, Johannes; Remy, Sam; Dhomse, Sandip; Morgan, Will
2016-04-01
The C-IFS (Composition Integrated Forecast System) developed under the MACC series of projects and to be continued under the Copernicus Atmospheric Monitoring System, provides global operational forecasts and re-analyses of atmospheric composition at high spatial resolution (T255, ~80km). Currently there are 2 aerosol schemes implemented within C-IFS, a mass-based scheme with externally mixed particle types and an aerosol microphysics scheme (GLOMAP-mode). The simpler mass-based scheme is the current operational system, also used in the existing system to assimilate satellite measurements of aerosol optical depth (AOD) for improved forecast capability. The microphysical GLOMAP scheme has now been implemented and evaluated in the latest C-IFS cycle alongside the mass-based scheme. The upgrade to the microphysical scheme provides for higher fidelity aerosol-radiation and aerosol-cloud interactions, accounting for global variations in size distribution and mixing state, and additional aerosol properties such as cloud condensation nuclei concentrations. The new scheme will also provide increased aerosol information when used as lateral boundary conditions for regional air quality models. Here we present a series of experiments highlighting the influence and accuracy of the two different aerosol schemes and the impact of MODIS AOD assimilation. In particular, we focus on the influence of biomass burning emissions on aerosol properties in the Amazon, comparing to ground-based and aircraft observations from the 2012 SAMBBA campaign. Biomass burning can affect regional air quality, human health, regional weather and the local energy budget. Tropical biomass burning generates particles primarily composed of particulate organic matter (POM) and black carbon (BC), the local ratio of these two different constituents often determining the properties and subsequent impacts of the aerosol particles. Therefore, the model's ability to capture the concentrations of these two carbonaceous aerosol types, during the tropical dry season, is essential for quantifying these wide ranging impacts. Comparisons to SAMBBA aircraft observations show that while both schemes underestimate POM and BC mass concentrations, the GLOMAP scheme provides a more accurate simulation. When satellite AOD is assimilated into the GEMS-AER scheme, the model is successfully adjusted, capturing observed mass concentrations to a good degree of accuracy.
Characterization of Cloud Water-Content Distribution
NASA Technical Reports Server (NTRS)
Lee, Seungwon
2010-01-01
The development of realistic cloud parameterizations for climate models requires accurate characterizations of subgrid distributions of thermodynamic variables. To this end, a software tool was developed to characterize cloud water-content distributions in climate-model sub-grid scales. This software characterizes distributions of cloud water content with respect to cloud phase, cloud type, precipitation occurrence, and geo-location using CloudSat radar measurements. It uses a statistical method called maximum likelihood estimation to estimate the probability density function of the cloud water content.
NASA Technical Reports Server (NTRS)
Matsui, Toshihisa; Masunaga, Hirohiko; Kreidenweis, Sonia M.; Pielke, Roger A., Sr.; Tao, Wei-Kuo; Chin, Mian; Kaufman, Yoram J.
2006-01-01
This study examines variability in marine low cloud properties derived from semi-global observations by the Tropical Rainfall Measuring Mission (TRMM) satellite, as linked to the aerosol index (AI) and lower-tropospheric stability (LTS). AI is derived from the Moderate Resolution Imaging Spectroradiometer (Terra MODIS) sensor and the Goddard Chemistry Aerosol Radiation and Transportation (GOCART) model, and is used to represent column-integrated aerosol concentrations. LTS is derived from the NCEP/NCAR reanalysis, and represents the background thermodynamic environment in which the clouds form. Global statistics reveal that cloud droplet size tends to be smallest in polluted (high-AI) and strong inversion (high-LTS) environments. Statistical quantification shows that cloud droplet size is better correlated with AI than it is with LTS. Simultaneously, the cloud liquid water path (CLWP) tends to decrease as AI increases. This correlation does not support the hypothesis or assumption that constant or increased CLWP is associated with high aerosol concentrations. Global variability in corrected cloud albedo (CCA), the product of cloud optical depth and cloud fraction, is very well explained by LTS, while both AI and LTS are needed to explain local variability in CCA. Most of the local correlations between AI and cloud properties are similar to the results from the global statistics, while weak anomalous aerosol-cloud correlations appear locally in the regions where simultaneous high (low) AI and low (high) LTS compensate each other. Daytime diurnal cycles explain additional variability in cloud properties. CCA has the largest diurnal cycle in high-LTS regions. Cloud droplet size and CLWP have weak diurnal cycles that differ between clean and polluted environments. The combined results suggest that investigations of marine low cloud radiative forcing and its relationship to hypothesized aerosol indirect effects must consider the combined effects of aerosols, thermodynamics, and the diurnal cycle.
Optical observations related to the molecular chemistry in diffuse interstellar clouds
NASA Technical Reports Server (NTRS)
Federman, S. R.
1987-01-01
Observations, which have been published since 1979, of molecular species in diffuse clouds are discussed. Particular attention is given to the ultraviolet measurements of CO with the Copernicus and IUE satellites and to ground-based optical measurements of CH, CH(+), CN, and 02. These data encompass large enough samples to test the chemical schemes expected to occur in diffuse clouds. Upper limits for other species (e.g., H2O, H2O(+), and C3) place restrictions on the pathways for molecular production. Moreover, analysis of the rotational distribution of the C2 molecule results in the determination of the physical conditions of the cloud. These parameters, including density, temperature, and the intensity of the radiation field, are necessary for modeling the chemistry.
New Approaches to Parameterizing Convection
NASA Technical Reports Server (NTRS)
Randall, David A.; Lappen, Cara-Lyn
1999-01-01
Many general circulation models (GCMs) currently use separate schemes for planetary boundary layer (PBL) processes, shallow and deep cumulus (Cu) convection, and stratiform clouds. The conventional distinctions. among these processes are somewhat arbitrary. For example, in the stratocumulus-to-cumulus transition region, stratocumulus clouds break up into a combination of shallow cumulus and broken stratocumulus. Shallow cumulus clouds may be considered to reside completely within the PBL, or they may be regarded as starting in the PBL but terminating above it. Deeper cumulus clouds often originate within the PBL with also can originate aloft. To the extent that our models separately parameterize physical processes which interact strongly on small space and time scales, the currently fashionable practice of modularization may be doing more harm than good.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Larson, Vincent; Gettelman, Andrew; Morrison, Hugh
In state-of-the-art climate models, each cloud type is treated using its own separate cloud parameterization and its own separate microphysics parameterization. This use of separate schemes for separate cloud regimes is undesirable because it is theoretically unfounded, it hampers interpretation of results, and it leads to the temptation to overtune parameters. In this grant, we are creating a climate model that contains a unified cloud parameterization and a unified microphysics parameterization. This model will be used to address the problems of excessive frequency of drizzle in climate models and excessively early onset of deep convection in the Tropics over land.more » The resulting model will be compared with ARM observations.« less
DETERMINATION OF CLOUD PARAMETERS FOR NEROS II FROM DIGITAL SATELLITE DATA
As part of the input for their regional-scale photochemical oxidant model of air pollution, known as the Regional Oxidant Model, requires statistical descriptions of total cloud amount, cumulus cloud amount, and cumulus cloud top height for certain regions and dates. These statis...
NASA Technical Reports Server (NTRS)
Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Yang, Ping; Schluessel, Peter; Strow, Larrabee
2007-01-01
An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. This retrieval algorithm is applied to the MetOp satellite Infrared Atmospheric Sounding Interferometer (IASI) launched on October 19, 2006. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI measurements are obtained and presented.
NASA Astrophysics Data System (ADS)
Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.
2014-10-01
The Goddard cloud microphysics scheme is a sophisticated cloud microphysics scheme in the Weather Research and Forecasting (WRF) model. The WRF is a widely used weather prediction system in the world. It development is a done in collaborative around the globe. The Goddard microphysics scheme is very suitable for massively parallel computation as there are no interactions among horizontal grid points. Compared to the earlier microphysics schemes, the Goddard scheme incorporates a large number of improvements. Thus, we have optimized the code of this important part of WRF. In this paper, we present our results of optimizing the Goddard microphysics scheme on Intel Many Integrated Core Architecture (MIC) hardware. The Intel Xeon Phi coprocessor is the first product based on Intel MIC architecture, and it consists of up to 61 cores connected by a high performance on-die bidirectional interconnect. The Intel MIC is capable of executing a full operating system and entire programs rather than just kernels as the GPU do. The MIC coprocessor supports all important Intel development tools. Thus, the development environment is familiar one to a vast number of CPU developers. Although, getting a maximum performance out of MICs will require using some novel optimization techniques. Those optimization techniques are discusses in this paper. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 4.7x. Furthermore, the same optimizations improved performance on a dual socket Intel Xeon E5-2670 system by a factor of 2.8x compared to the original code.
NASA Astrophysics Data System (ADS)
Garrett, T. J.; Alva, S.; Glenn, I. B.; Krueger, S. K.
2015-12-01
There are two possible approaches for parameterizing sub-grid cloud dynamics in a coarser grid model. The most common is to use a fine scale model to explicitly resolve the mechanistic details of clouds to the best extent possible, and then to parameterize these behaviors cloud state for the coarser grid. A second is to invoke physical intuition and some very general theoretical principles from equilibrium statistical mechanics. This approach avoids any requirement to resolve time-dependent processes in order to arrive at a suitable solution. The second approach is widely used elsewhere in the atmospheric sciences: for example the Planck function for blackbody radiation is derived this way, where no mention is made of the complexities of modeling a large ensemble of time-dependent radiation-dipole interactions in order to obtain the "grid-scale" spectrum of thermal emission by the blackbody as a whole. We find that this statistical approach may be equally suitable for modeling convective clouds. Specifically, we make the physical argument that the dissipation of buoyant energy in convective clouds is done through mixing across a cloud perimeter. From thermodynamic reasoning, one might then anticipate that vertically stacked isentropic surfaces are characterized by a power law dlnN/dlnP = -1, where N(P) is the number clouds of perimeter P. In a Giga-LES simulation of convective clouds within a 100 km square domain we find that such a power law does appear to characterize simulated cloud perimeters along isentropes, provided a sufficient cloudy sample. The suggestion is that it may be possible to parameterize certain important aspects of cloud state without appealing to computationally expensive dynamic simulations.
Qian, Yun; Yan, Huiping; Berg, Larry K.; ...
2016-10-28
Accuracy of turbulence parameterization in representing Planetary Boundary Layer (PBL) processes in climate models is critical for predicting the initiation and development of clouds, air quality issues, and underlying surface-atmosphere-cloud interactions. In this study, we 1) evaluate WRF model-simulated spatial patterns of precipitation and surface fluxes, as well as vertical profiles of potential temperature, humidity, moist static energy and moisture tendency terms as simulated by WRF at various spatial resolutions and with PBL, surface layer and shallow convection schemes against measurements, 2) identify model biases by examining the moisture tendency terms contributed by PBL and convection processes through nudging experiments,more » and 3) evaluate the dependence of modeled surface latent heat (LH) fluxes onPBL and surface layer schemes over the tropical ocean. The results show that PBL and surface parameterizations have surprisingly large impacts on precipitation, convection initiation and surface moisture fluxes over tropical oceans. All of the parameterizations tested tend to overpredict moisture in PBL and free atmosphere, and consequently result in larger moist static energy and precipitation. Moisture nudging tends to suppress the initiation of convection and reduces the excess precipitation. The reduction in precipitation bias in turn reduces the surface wind and LH flux biases, which suggests that the model drifts at least partly because of a positive feedback between precipitation and surface fluxes. The updated shallow convection scheme KF-CuP tends to suppress the initiation and development of deep convection, consequently decreasing precipitation. The Eta surface layer scheme predicts more reasonable LH fluxes and the LH-Wind Speed relationship than the MM5 scheme, especially when coupled with the MYJ scheme. By examining various parameterization schemes in WRF, we identify sources of biases and weaknesses of current PBL, surface layer and shallow convection schemes in reproducing PBL processes, the initiation of convection and intra-seasonal variability of precipitation.« less
The HIRLAM fast radiation scheme for mesoscale numerical weather prediction models
NASA Astrophysics Data System (ADS)
Rontu, Laura; Gleeson, Emily; Räisänen, Petri; Pagh Nielsen, Kristian; Savijärvi, Hannu; Hansen Sass, Bent
2017-07-01
This paper provides an overview of the HLRADIA shortwave (SW) and longwave (LW) broadband radiation schemes used in the HIRLAM numerical weather prediction (NWP) model and available in the HARMONIE-AROME mesoscale NWP model. The advantage of broadband, over spectral, schemes is that they can be called more frequently within the model, without compromising on computational efficiency. In mesoscale models fast interactions between clouds and radiation and the surface and radiation can be of greater importance than accounting for the spectral details of clear-sky radiation; thus calling the routines more frequently can be of greater benefit than the deterioration due to loss of spectral details. Fast but physically based radiation parametrizations are expected to be valuable for high-resolution ensemble forecasting, because as well as the speed of their execution, they may provide realistic physical perturbations. Results from single-column diagnostic experiments based on CIRC benchmark cases and an evaluation of 10 years of radiation output from the FMI operational archive of HIRLAM forecasts indicate that HLRADIA performs sufficiently well with respect to the clear-sky downwelling SW and longwave LW fluxes at the surface. In general, HLRADIA tends to overestimate surface fluxes, with the exception of LW fluxes under cold and dry conditions. The most obvious overestimation of the surface SW flux was seen in the cloudy cases in the 10-year comparison; this bias may be related to using a cloud inhomogeneity correction, which was too large. According to the CIRC comparisons, the outgoing LW and SW fluxes at the top of atmosphere are mostly overestimated by HLRADIA and the net LW flux is underestimated above clouds. The absorption of SW radiation by the atmosphere seems to be underestimated and LW absorption seems to be overestimated. Despite these issues, the overall results are satisfying and work on the improvement of HLRADIA for the use in HARMONIE-AROME NWP system is ongoing. In a HARMONIE-AROME 3-D forecast experiment we have shown that the frequency of the call for the radiation parametrization and choice of the parametrization scheme makes a difference to the surface radiation fluxes and changes the spatial distribution of the vertically integrated cloud cover and precipitation.
A new interstellar molecule - Tricarbon monoxide
NASA Technical Reports Server (NTRS)
Matthews, H. E.; Irvine, W. M.; Friberg, P.; Brown, R. D.; Godfrey, P. D.
1984-01-01
The C3O molecule, whose pure rotational spectrum has only recently been studied in the laboratory, has been detected in the cold, dark interstellar Taurus Molecular Cloud 1. Since C3O is the first interstelar carbon chain molecule to contain oxygen, its existence places an important new constraint on chemical schemes for cold interstellar clouds. The abundance of C3O can be understood in terms of purely gas-phase ion-molecule chemistry.
Active sensor synergy for arctic cloud microphysics
NASA Astrophysics Data System (ADS)
Sato, Kaori; Okamoto, Hajime; Katagiri, Shuichiro; Shiobara, Masataka; Yabuki, Masanori; Takano, Toshiaki
2018-04-01
In this study, we focus on the retrieval of liquid and ice-phase cloud microphysics from spaceborne and ground-based lidar-cloud radar synergy. As an application of the cloud retrieval algorithm developed for the EarthCARE satellite mission (JAXA-ESA) [1], the derived statistics of cloud microphysical properties in high latitudes and their relation to the Arctic climate are investigated.
NASA Astrophysics Data System (ADS)
Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos
2017-04-01
The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for the cloud liquid phases. The relative error for the retrieved integrated frozen water content (FWP, i.e., ice+snow+graupel) is below 40% for 0.1kg/m2 < FWP < 0.5kg/m2 and below 20% for FWP > 0.5 kg/m2.
A simple biota removal algorithm for 35 GHz cloud radar measurements
NASA Astrophysics Data System (ADS)
Kalapureddy, Madhu Chandra R.; Sukanya, Patra; Das, Subrata K.; Deshpande, Sachin M.; Pandithurai, Govindan; Pazamany, Andrew L.; Ambuj K., Jha; Chakravarty, Kaustav; Kalekar, Prasad; Krishna Devisetty, Hari; Annam, Sreenivas
2018-03-01
Cloud radar reflectivity profiles can be an important measurement for the investigation of cloud vertical structure (CVS). However, extracting intended meteorological cloud content from the measurement often demands an effective technique or algorithm that can reduce error and observational uncertainties in the recorded data. In this work, a technique is proposed to identify and separate cloud and non-hydrometeor echoes using the radar Doppler spectral moments profile measurements. The point and volume target-based theoretical radar sensitivity curves are used for removing the receiver noise floor and identified radar echoes are scrutinized according to the signal decorrelation period. Here, it is hypothesized that cloud echoes are observed to be temporally more coherent and homogenous and have a longer correlation period than biota. That can be checked statistically using ˜ 4 s sliding mean and standard deviation value of reflectivity profiles. The above step helps in screen out clouds critically by filtering out the biota. The final important step strives for the retrieval of cloud height. The proposed algorithm potentially identifies cloud height solely through the systematic characterization of Z variability using the local atmospheric vertical structure knowledge besides to the theoretical, statistical and echo tracing tools. Thus, characterization of high-resolution cloud radar reflectivity profile measurements has been done with the theoretical echo sensitivity curves and observed echo statistics for the true cloud height tracking (TEST). TEST showed superior performance in screening out clouds and filtering out isolated insects. TEST constrained with polarimetric measurements was found to be more promising under high-density biota whereas TEST combined with linear depolarization ratio and spectral width perform potentially to filter out biota within the highly turbulent shallow cumulus clouds in the convective boundary layer (CBL). This TEST technique is promisingly simple in realization but powerful in performance due to the flexibility in constraining, identifying and filtering out the biota and screening out the true cloud content, especially the CBL clouds. Therefore, the TEST algorithm is superior for screening out the low-level clouds that are strongly linked to the rainmaking mechanism associated with the Indian Summer Monsoon region's CVS.
NASA Astrophysics Data System (ADS)
Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.
2012-12-01
The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.
NASA Technical Reports Server (NTRS)
Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.
2012-01-01
The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.
NASA Technical Reports Server (NTRS)
Larsen, P. A.
1972-01-01
A determination was made of the areal extent of terrain obscured by clouds and cloud shadows on a portion of an Apollo 9 photograph at the instant of exposure. This photogrammetrically determined area was then compared to the cloud coverage reported by surface weather observers at approximately the same time and location, as a check on result quality. Stereograms prepared from Apollo 9 vertical photographs, illustrating various percentages of cloud coverage, are presented to help provide a quantitative appreciation of the degradation of terrain photography by clouds and their attendant shadows. A scheme, developed for the U.S. Navy, utilizing pattern recognition techniques for determining cloud motion from sequences of satellite photographs, is summarized. Clouds, turbulence, haze, and solar altitude, four elements of our natural environment which affect aerial photographic missions, are each discussed in terms of their effects on imagery obtained by aerial photography. Data of a type useful to aerial photographic mission planners, expressing photographic ground coverage in terms of flying height above terrain and camera focal length, for a standard aerial photograph format, are provided. Two oblique orbital photographs taken during the Apollo 9 flight are shown, and photo-interpretations, discussing the cloud types imaged and certain visible geographical features, are provided.
Wang, Minghuai; Larson, Vincent E.; Ghan, Steven; ...
2015-04-18
In this study, a higher-order turbulence closure scheme, called Cloud Layers Unified by Binormals (CLUBB), is implemented into a Multi-scale Modeling Framework (MMF) model to improve low cloud simulations. The performance of CLUBB in MMF simulations with two different microphysics configurations (one-moment cloud microphysics without aerosol treatment and two-moment cloud microphysics coupled with aerosol treatment) is evaluated against observations and further compared with results from the Community Atmosphere Model, Version 5 (CAM5) with conventional cloud parameterizations. CLUBB is found to improve low cloud simulations in the MMF, and the improvement is particularly evident in the stratocumulus-to-cumulus transition regions. Compared tomore » the single-moment cloud microphysics, CLUBB with two-moment microphysics produces clouds that are closer to the coast, and agrees better with observations. In the stratocumulus-to cumulus transition regions, CLUBB with two-moment cloud microphysics produces shortwave cloud forcing in better agreement with observations, while CLUBB with single moment cloud microphysics overestimates shortwave cloud forcing. CLUBB is further found to produce quantitatively similar improvements in the MMF and CAM5, with slightly better performance in the MMF simulations (e.g., MMF with CLUBB generally produces low clouds that are closer to the coast than CAM5 with CLUBB). As a result, improved low cloud simulations in MMF make it an even more attractive tool for studying aerosol-cloud-precipitation interactions.« less
Climatology analysis of cirrus cloud in ARM site: South Great Plain
NASA Astrophysics Data System (ADS)
Olayinka, K.
2017-12-01
Cirrus cloud play an important role in the atmospheric energy balance and hence in the earth's climate system. The properties of optically thin clouds can be determined from measurements of transmission of the direct solar beam. The accuracy of cloud optical properties determined in this way is compromised by contamination of the direct transmission by light that is scattered into the sensors field of view. With the forward scattering correction method developed by Min et al., (2004), the accuracy of thin cloud retrievals from MFRSR has been improved. Our result shows over 30% of cirrus cloud present in the atmosphere are within optical depth between (1-2). In this study, we do statistics studies on cirrus clouds properties based on multi-years cirrus cloud measurements from MFRSR at ARM site from the South Great Plain (SGP) site due to its relatively easy accessibility, wide variability of climate cloud types and surface flux properties, large seasonal variation in temperature and specific humidity. Through the statistic studies, temporal and spatial variations of cirrus clouds are investigated. Since the presence of cirrus cloud increases the effect of greenhouse gases, we will retrieve the aerosol optical depth in all the cirrus cloud regions using a radiative transfer model for atmospheric correction. Calculate thin clouds optical depth (COD), and aerosol optical depth (AOD) using a radiative transfer model algorithm, e.g.: MODTRAN (MODerate resolution atmospheric TRANsmission)
Physical View of Cloud Seeding
ERIC Educational Resources Information Center
Tribus, Myron
1970-01-01
Reviews experimental data on various aspects of climate control. Includes a discussion of (1) the physics of cloud seeding, (2) the applications of cloud seeding, and (3) the role of statistics in the field of weather modification. Bibliography. (LC)
A Cloud Microphysics Model for the Gas Giant Planets
NASA Astrophysics Data System (ADS)
Palotai, Csaba J.; Le Beau, Raymond P.; Shankar, Ramanakumar; Flom, Abigail; Lashley, Jacob; McCabe, Tyler
2016-10-01
Recent studies have significantly increased the quality and the number of observed meteorological features on the jovian planets, revealing banded cloud structures and discrete features. Our current understanding of the formation and decay of those clouds also defines the conceptual modes about the underlying atmospheric dynamics. The full interpretation of the new observational data set and the related theories requires modeling these features in a general circulation model (GCM). Here, we present details of our bulk cloud microphysics model that was designed to simulate clouds in the Explicit Planetary Hybrid-Isentropic Coordinate (EPIC) GCM for the jovian planets. The cloud module includes hydrological cycles for each condensable species that consist of interactive vapor, cloud and precipitation phases and it also accounts for latent heating and cooling throughout the transfer processes (Palotai and Dowling, 2008. Icarus, 194, 303-326). Previously, the self-organizing clouds in our simulations successfully reproduced the vertical and horizontal ammonia cloud structure in the vicinity of Jupiter's Great Red Spot and Oval BA (Palotai et al. 2014, Icarus, 232, 141-156). In our recent work, we extended this model to include water clouds on Jupiter and Saturn, ammonia clouds on Saturn, and methane clouds on Uranus and Neptune. Details of our cloud parameterization scheme, our initial results and their comparison with observations will be shown. The latest version of EPIC model is available as open source software from NASA's PDS Atmospheres Node.
Modeling and parameterization of horizontally inhomogeneous cloud radiative properties
NASA Technical Reports Server (NTRS)
Welch, R. M.
1995-01-01
One of the fundamental difficulties in modeling cloud fields is the large variability of cloud optical properties (liquid water content, reflectance, emissivity). The stratocumulus and cirrus clouds, under special consideration for FIRE, exhibit spatial variability on scales of 1 km or less. While it is impractical to model individual cloud elements, the research direction is to model a statistical ensembles of cloud elements with mean-cloud properties specified. The major areas of this investigation are: (1) analysis of cloud field properties; (2) intercomparison of cloud radiative model results with satellite observations; (3) radiative parameterization of cloud fields; and (4) development of improved cloud classification algorithms.
Shallow cumuli ensemble statistics for development of a stochastic parameterization
NASA Astrophysics Data System (ADS)
Sakradzija, Mirjana; Seifert, Axel; Heus, Thijs
2014-05-01
According to a conventional deterministic approach to the parameterization of moist convection in numerical atmospheric models, a given large scale forcing produces an unique response from the unresolved convective processes. This representation leaves out the small-scale variability of convection, as it is known from the empirical studies of deep and shallow convective cloud ensembles, there is a whole distribution of sub-grid states corresponding to the given large scale forcing. Moreover, this distribution gets broader with the increasing model resolution. This behavior is also consistent with our theoretical understanding of a coarse-grained nonlinear system. We propose an approach to represent the variability of the unresolved shallow-convective states, including the dependence of the sub-grid states distribution spread and shape on the model horizontal resolution. Starting from the Gibbs canonical ensemble theory, Craig and Cohen (2006) developed a theory for the fluctuations in a deep convective ensemble. The micro-states of a deep convective cloud ensemble are characterized by the cloud-base mass flux, which, according to the theory, is exponentially distributed (Boltzmann distribution). Following their work, we study the shallow cumulus ensemble statistics and the distribution of the cloud-base mass flux. We employ a Large-Eddy Simulation model (LES) and a cloud tracking algorithm, followed by a conditional sampling of clouds at the cloud base level, to retrieve the information about the individual cloud life cycles and the cloud ensemble as a whole. In the case of shallow cumulus cloud ensemble, the distribution of micro-states is a generalized exponential distribution. Based on the empirical and theoretical findings, a stochastic model has been developed to simulate the shallow convective cloud ensemble and to test the convective ensemble theory. Stochastic model simulates a compound random process, with the number of convective elements drawn from a Poisson distribution, and cloud properties sub-sampled from a generalized ensemble distribution. We study the role of the different cloud subtypes in a shallow convective ensemble and how the diverse cloud properties and cloud lifetimes affect the system macro-state. To what extent does the cloud-base mass flux distribution deviate from the simple Boltzmann distribution and how does it affect the results from the stochastic model? Is the memory, provided by the finite lifetime of individual clouds, of importance for the ensemble statistics? We also test for the minimal information given as an input to the stochastic model, able to reproduce the ensemble mean statistics and the variability in a convective ensemble. An important property of the resulting distribution of the sub-grid convective states is its scale-adaptivity - the smaller the grid-size, the broader the compound distribution of the sub-grid states.
NASA Astrophysics Data System (ADS)
Dupont, J. C.; Haeffelin, M.; Morille, Y.; Noel, V.; Keckhut, P.; Comstock, J.; Winker, D.; Chervet, P.; Roblin, A.
2009-04-01
Cirrus clouds not only play a major role in the energy budget of the Earth-Atmosphere system, but are also important in the hydrological cycle [Stephens et al., 1990; Webster, 1994]. According to satellite passive remote sensing, high-altitude clouds cover as much as 40% of the earth's surface on average (Liou 1986; Stubenrauch et al., 2006) and can reach 70% of cloud cover over the Tropics (Wang et al., 1996; Nazaryan et al., 2008). Hence, given their very large cloud cover, they have a major role in the climate system (Lynch et al. 2001). Cirrus clouds can be classified into three distinct families according to their optical thickness, namely subvisible clouds (OD<0.03), semi-transparent clouds (0.03
A Bulk Microphysics Parameterization with Multiple Ice Precipitation Categories.
NASA Astrophysics Data System (ADS)
Straka, Jerry M.; Mansell, Edward R.
2005-04-01
A single-moment bulk microphysics scheme with multiple ice precipitation categories is described. It has 2 liquid hydrometeor categories (cloud droplets and rain) and 10 ice categories that are characterized by habit, size, and density—two ice crystal habits (column and plate), rimed cloud ice, snow (ice crystal aggregates), three categories of graupel with different densities and intercepts, frozen drops, small hail, and large hail. The concept of riming history is implemented for conversions among the graupel and frozen drops categories. The multiple precipitation ice categories allow a range of particle densities and fall velocities for simulating a variety of convective storms with minimal parameter tuning. The scheme is applied to two cases—an idealized continental multicell storm that demonstrates the ice precipitation process, and a small Florida maritime storm in which the warm rain process is important.
Analysis of an ABE Scheme with Verifiable Outsourced Decryption.
Liao, Yongjian; He, Yichuan; Li, Fagen; Jiang, Shaoquan; Zhou, Shijie
2018-01-10
Attribute-based encryption (ABE) is a popular cryptographic technology to protect the security of users' data in cloud computing. In order to reduce its decryption cost, outsourcing the decryption of ciphertexts is an available method, which enables users to outsource a large number of decryption operations to the cloud service provider. To guarantee the correctness of transformed ciphertexts computed by the cloud server via the outsourced decryption, it is necessary to check the correctness of the outsourced decryption to ensure security for the data of users. Recently, Li et al. proposed a full verifiability of the outsourced decryption of ABE scheme (ABE-VOD) for the authorized users and unauthorized users, which can simultaneously check the correctness of the transformed ciphertext for both them. However, in this paper we show that their ABE-VOD scheme cannot obtain the results which they had shown, such as finding out all invalid ciphertexts, and checking the correctness of the transformed ciphertext for the authorized user via checking it for the unauthorized user. We first construct some invalid ciphertexts which can pass the validity checking in the decryption algorithm. That means their "verify-then-decrypt" skill is unavailable. Next, we show that the method to check the validity of the outsourced decryption for the authorized users via checking it for the unauthorized users is not always correct. That is to say, there exist some invalid ciphertexts which can pass the validity checking for the unauthorized user, but cannot pass the validity checking for the authorized user.
Analysis of an ABE Scheme with Verifiable Outsourced Decryption
He, Yichuan; Li, Fagen; Jiang, Shaoquan; Zhou, Shijie
2018-01-01
Attribute-based encryption (ABE) is a popular cryptographic technology to protect the security of users’ data in cloud computing. In order to reduce its decryption cost, outsourcing the decryption of ciphertexts is an available method, which enables users to outsource a large number of decryption operations to the cloud service provider. To guarantee the correctness of transformed ciphertexts computed by the cloud server via the outsourced decryption, it is necessary to check the correctness of the outsourced decryption to ensure security for the data of users. Recently, Li et al. proposed a full verifiability of the outsourced decryption of ABE scheme (ABE-VOD) for the authorized users and unauthorized users, which can simultaneously check the correctness of the transformed ciphertext for both them. However, in this paper we show that their ABE-VOD scheme cannot obtain the results which they had shown, such as finding out all invalid ciphertexts, and checking the correctness of the transformed ciphertext for the authorized user via checking it for the unauthorized user. We first construct some invalid ciphertexts which can pass the validity checking in the decryption algorithm. That means their “verify-then-decrypt” skill is unavailable. Next, we show that the method to check the validity of the outsourced decryption for the authorized users via checking it for the unauthorized users is not always correct. That is to say, there exist some invalid ciphertexts which can pass the validity checking for the unauthorized user, but cannot pass the validity checking for the authorized user. PMID:29320418
Deng, Yong-Yuan; Chen, Chin-Ling; Tsaur, Woei-Jiunn; Tang, Yung-Wen; Chen, Jung-Hsuan
2017-12-15
As sensor networks and cloud computation technologies have rapidly developed over recent years, many services and applications integrating these technologies into daily life have come together as an Internet of Things (IoT). At the same time, aging populations have increased the need for expanded and more efficient elderly care services. Fortunately, elderly people can now wear sensing devices which relay data to a personal wireless device, forming a body area network (BAN). These personal wireless devices collect and integrate patients' personal physiological data, and then transmit the data to the backend of the network for related diagnostics. However, a great deal of the information transmitted by such systems is sensitive data, and must therefore be subject to stringent security protocols. Protecting this data from unauthorized access is thus an important issue in IoT-related research. In regard to a cloud healthcare environment, scholars have proposed a secure mechanism to protect sensitive patient information. Their schemes provide a general architecture; however, these previous schemes still have some vulnerability, and thus cannot guarantee complete security. This paper proposes a secure and lightweight body-sensor network based on the Internet of Things for cloud healthcare environments, in order to address the vulnerabilities discovered in previous schemes. The proposed authentication mechanism is applied to a medical reader to provide a more comprehensive architecture while also providing mutual authentication, and guaranteeing data integrity, user untraceability, and forward and backward secrecy, in addition to being resistant to replay attack.