Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

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.

Insights into low-latitude cloud feedbacks from high-resolution models.

PubMed

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).

A Mixed Phase Tale: New Ways of using in-situ cloud observations to reduce climate model biases in Southern Ocean

NASA Astrophysics Data System (ADS)

Gettelman, A.; Stith, J. L.

2014-12-01

Southern ocean clouds are a critical part of the earth's energy budget, and significant biases in the climatology of these clouds exist in models used to predict climate change. We compare in situ measurements of cloud microphysical properties of ice and liquid over the S. Ocean with constrained output from the atmospheric component of an Earth System Model. Observations taken during the HIAPER (the NSF/NCAR G-V aircraft) Pole-to-Pole Observations (HIPPO) multi-year field campaign are compared with simulations from the atmospheric component of the Community Earth System Model (CESM). Remarkably, CESM is able to accurately simulate the locations of cloud formation, and even cloud microphysical properties are comparable between the model and observations. Significantly, the simulations do not predict sufficient supercooled liquid. Altering the model cloud and aerosol processes to better reproduce the observations of supercooled liquid acts to reduce long-standing biases in S. Ocean clouds in CESM, which are typical of other models. Furthermore, sensitivity tests show where better observational constraints on aerosols and cloud microphysics can reduce uncertainty and biases in global models. These results are intended to show how we can connect large scale simulations with field observations in the S. Ocean to better understand Southern Ocean cloud processes and reduce biases in global climate simulations.

On the validation of cloud parametrization schemes in numerical atmospheric models with satellite data from ISCCP

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.

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

NASA Astrophysics Data System (ADS)

Zhang, Junhua; Lohmann, Ulrike

2003-08-01

The single column model of the Canadian Centre for Climate Modeling and Analysis (CCCma) climate model is used to simulate Arctic spring cloud properties observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. The model is driven by the rawinsonde observations constrained European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis data. Five cloud parameterizations, including three statistical and two explicit schemes, are compared and the sensitivity to mixed phase cloud parameterizations is studied. Using the original mixed phase cloud parameterization of the model, the statistical cloud schemes produce more cloud cover, cloud water, and precipitation than the explicit schemes and in general agree better with observations. The mixed phase cloud parameterization from ECMWF decreases the initial saturation specific humidity threshold of cloud formation. This improves the simulated cloud cover in the explicit schemes and reduces the difference between the different cloud schemes. On the other hand, because the ECMWF mixed phase cloud scheme does not consider the Bergeron-Findeisen process, less ice crystals are formed. This leads to a higher liquid water path and less precipitation than what was observed.

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.

Simulation of Shallow Cumuli and Their Transition to Deep Convective Clouds by Cloud-resolving Models with Different Third-order Turbulence Closures

NASA Technical Reports Server (NTRS)

Cheng, Anning; Xu, Kuan-Man

2006-01-01

The abilities of cloud-resolving models (CRMs) with the double-Gaussian based and the single-Gaussian based third-order closures (TOCs) to simulate the shallow cumuli and their transition to deep convective clouds are compared in this study. The single-Gaussian based TOC is fully prognostic (FP), while the double-Gaussian based TOC is partially prognostic (PP). The latter only predicts three important third-order moments while the former predicts all the thirdorder moments. A shallow cumulus case is simulated by single-column versions of the FP and PP TOC models. The PP TOC improves the simulation of shallow cumulus greatly over the FP TOC by producing more realistic cloud structures. Large differences between the FP and PP TOC simulations appear in the cloud layer of the second- and third-order moments, which are related mainly to the underestimate of the cloud height in the FP TOC simulation. Sensitivity experiments and analysis of probability density functions (PDFs) used in the TOCs show that both the turbulence-scale condensation and higher-order moments are important to realistic simulations of the boundary-layer shallow cumuli. A shallow to deep convective cloud transition case is also simulated by the 2-D versions of the FP and PP TOC models. Both CRMs can capture the transition from the shallow cumuli to deep convective clouds. The PP simulations produce more and deeper shallow cumuli than the FP simulations, but the FP simulations produce larger and wider convective clouds than the PP simulations. The temporal evolutions of cloud and precipitation are closely related to the turbulent transport, the cold pool and the cloud-scale circulation. The large amount of turbulent mixing associated with the shallow cumuli slows down the increase of the convective available potential energy and inhibits the early transition to deep convective clouds in the PP simulation. When the deep convective clouds fully develop and the precipitation is produced, the cold pools produced by the evaporation of the precipitation are not favorable to the formation of shallow cumuli.

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.

Assessing the accuracy of MISR and MISR-simulated cloud top heights using CloudSat- and CALIPSO-retrieved hydrometeor profiles

NASA Astrophysics Data System (ADS)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally

2017-03-01

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped clouds agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped clouds between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low-altitude cloud cover. The MISR-simulated and MISR-retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

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.

RACORO continental boundary layer cloud investigations. 3. Separation of parameterization biases in single-column model CAM5 simulations of shallow cumulus

DOE PAGES

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

How consistent are precipitation patterns predicted by GCMs in the absence of cloud radiative effects?

NASA Astrophysics Data System (ADS)

Popke, Dagmar; Bony, Sandrine; Mauritsen, Thorsten; Stevens, Bjorn

2015-04-01

Model simulations with state-of-the-art general circulation models reveal a strong disagreement concerning the simulated regional precipitation patterns and their changes with warming. The deviating precipitation response even persists when reducing the model experiment complexity to aquaplanet simulation with forced sea surface temperatures (Stevens and Bony, 2013). To assess feedbacks between clouds and radiation on precipitation responses we analyze data from 5 models performing the aquaplanet simulations of the Clouds On Off Klima Intercomparison Experiment (COOKIE), where the interaction of clouds and radiation is inhibited. Although cloud radiative effects are then disabled, the precipitation patterns among models are as diverse as with cloud radiative effects switched on. Disentangling differing model responses in such simplified experiments thus appears to be key to better understanding the simulated regional precipitation in more standard configurations. By analyzing the local moisture and moist static energy budgets in the COOKIE experiments we investigate likely causes for the disagreement among models. References Stevens, B. & S. Bony: What Are Climate Models Missing?, Science, 2013, 340, 1053-1054

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

NASA Technical Reports Server (NTRS)

Chen, C.; Zak, J. A.

1989-01-01

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

Using High-Resolution Satellite Observations for Evaluation of Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations. Part I: South China Sea Monsoon Experiment

NASA Astrophysics Data System (ADS)

Zhou, Y.; Hou, A.; Lau, W. K.; Shie, C.; Tao, W.; Lin, X.; Chou, M.; Olson, W. S.; Grecu, M.

2006-05-01

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model during the South China Sea Monsoon Experiment (SCSMEX) is compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) radiation and cloud retrievals. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. Mesoscale organization is adequately simulated except when environmental wind shear is very weak. The partitions between convective and stratiform rain are also close to TMI and PR classification. However, the model simulated rain spectrum is quite different from either TMI or PR measurements. The model produces more heavy rains and light rains (less than 0.1 mm/hr) than the observations. The model also produces heavier vertical hydrometer profiles of rain, graupel when compared with TMI retrievals and PR radar reflectivity. Comparing GCE simulated OLR and cloud properties with CERES measurements found that the model has much larger domain averaged OLR due to smaller total cloud fraction and a much skewed distribution of OLR and cloud top than CERES observations, indicating that the model's cloud field is not wide spread, consistent with the model's precipitation activity. These results will be used as guidance for improving the model's microphysics.

Assessment of NASA GISS CMIP5 ModelE simulated clouds and TOA radiation budgets using satellite observations over the southern mid-latitudes

NASA Astrophysics Data System (ADS)

Stanfield, Ryan Evan

Past, current, and future climates have been simulated by the National Aeronautics and Space Administration (NASA) Goddard Institute for Space Studies (GISS) ModelE Global Circulation Model (GCM) and summarized by the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC, AR4). New simulations from the updated CMIP5 version of the NASA GISS ModelE GCM were recently released to the public community during the summer of 2011 and will be included in the upcoming IPCC AR5 ensemble of simulations. Due to the recent nature of these simulations, they have not yet been extensively validated against observations. To assess the NASA GISS-E2-R GCM, model simulated clouds and cloud properties are compared to observational cloud properties derived from the Clouds and Earth's Radiant Energy System (CERES) project using MODerate Resolution Imaging Spectroradiometer (MODIS) data for the period of March 2000 through December 2005. Over the 6-year period, the global average modeled cloud fractions are within 1% of observations. However, further study however shows large regional biases between the GCM simulations and CERES-MODIS observations. The southern mid-latitudes (SML) were chosen as a focus region due to model errors across multiple GCMs within the recent phase 5 of the Coupled Model Intercomparison Project (CMIP5). Over the SML, the GISS GCM undersimulates total cloud fraction over 20%, but oversimulates total water path by 2 g m-2. Simulated vertical cloud distributions over the SML when compared to both CERES-MODIS and CloudSat/CALIPSO observations show a drastic undersimulation of low level clouds by the GISS GCM, but higher fractions of thicker clouds. To assess the impact of GISS simulated clouds on the TOA radiation budgets, the modeled TOA radiation budgets are compared to CERES EBAF observations. Because modeled low-level cloud fraction is much lower than observed over the SML, modeled reflected shortwave (SW) flux at the TOA is 13 W m -2 lower and outgoing longwave radiation (OLR) is 3 W m-2 higher than observations. Finally, cloud radiative effects (CRE) are calculated and compared with observations to fully assess the impact of clouds on the TOA radiation budgets. The difference in clear-sky reflected SW flux between model and observation is only +4 W m-2 while the SW CRE difference is up to 17 W m-2, indicating that most of the bias in SW CRE results from the all-sky bias between the model and observation. A sizeable negative bias of 10 W m-2 in simulated clear-sky OLR has been found due to a dry bias in calculating observed clear-sky OLR and lack of upper-level water vapor at the 100-mb level in the model. The dry bias impacts CRE LW, with the model undersimulating by 13 W m-2. The CRE NET difference is only 5 W m-2 due to the cancellation of SW and LW CRE biases.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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 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.

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

DOE PAGES

Mechem, David B.; Giangrande, Scott E.

2018-03-01

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.« less

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

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

Mechem, David B.; Giangrande, Scott E.

Here, the controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large–eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud topmore » occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time–varying three–dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.« less

The Challenge of Identifying Controls on Cloud Properties and Precipitation Onset for Cumulus Congestus Sampled During MC3E

NASA Astrophysics Data System (ADS)

Mechem, David B.; Giangrande, Scott E.

2018-03-01

Controls on precipitation onset and the transition from shallow cumulus to congestus are explored using a suite of 16 large-eddy simulations based on the 25 May 2011 event from the Midlatitude Continental Convective Clouds Experiment (MC3E). The thermodynamic variables in the model are relaxed at various timescales to observationally constrained temperature and moisture profiles in order to better reproduce the observed behavior of precipitation onset and total precipitation. Three of the simulations stand out as best matching the precipitation observations and also perform well for independent comparisons of cloud fraction, precipitation area fraction, and evolution of cloud top occurrence. All three simulations exhibit a destabilization over time, which leads to a transition to deeper clouds, but the evolution of traditional stability metrics by themselves is not able to explain differences in the simulations. Conditionally sampled cloud properties (in particular, mean cloud buoyancy), however, do elicit differences among the simulations. The inability of environmental profiles alone to discern subtle differences among the simulations and the usefulness of conditionally sampled model quantities argue for hybrid observational/modeling approaches. These combined approaches enable a more complete physical understanding of cloud systems by combining observational sampling of time-varying three-dimensional meteorological quantities and cloud properties, along with detailed representation of cloud microphysical and dynamical processes from numerical models.

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles

NASA Astrophysics Data System (ADS)

Vergara-Temprado, Jesús; Miltenberger, Annette K.; Furtado, Kalli; Grosvenor, Daniel P.; Shipway, Ben J.; Hill, Adrian A.; Wilkinson, Jonathan M.; Field, Paul R.; Murray, Benjamin J.; Carslaw, Ken S.

2018-03-01

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions.

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles

PubMed Central

Miltenberger, Annette K.; Furtado, Kalli; Grosvenor, Daniel P.; Shipway, Ben J.; Hill, Adrian A.; Wilkinson, Jonathan M.; Field, Paul R.

2018-01-01

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions. PMID:29490918

Simulations and Evaluation of Mesoscale Convective Systems in a Multi-scale Modeling Framework (MMF)

NASA Astrophysics Data System (ADS)

Chern, J. D.; Tao, W. K.

2017-12-01

It is well known that the mesoscale convective systems (MCS) produce more than 50% of rainfall in most tropical regions and play important roles in regional and global water cycles. Simulation of MCSs in global and climate models is a very challenging problem. Typical MCSs have horizontal scale of a few hundred kilometers. Models with a domain of several hundred kilometers and fine enough resolution to properly simulate individual clouds are required to realistically simulate MCSs. The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has shown some capabilities of simulating organized MCS-like storm signals and propagations. However, its embedded CRMs typically have small domain (less than 128 km) and coarse resolution ( 4 km) that cannot realistically simulate MCSs and individual clouds. In this study, a series of simulations were performed using the Goddard MMF. The impacts of the domain size and model grid resolution of the embedded CRMs on simulating MCSs are examined. The changes of cloud structure, occurrence, and properties such as cloud types, updraft and downdraft, latent heating profile, and cold pool strength in the embedded CRMs are examined in details. The simulated MCS characteristics are evaluated against satellite measurements using the Goddard Satellite Data Simulator Unit. The results indicate that embedded CRMs with large domain and fine resolution tend to produce better simulations compared to those simulations with typical MMF configuration (128 km domain size and 4 km model grid spacing).

Direct Comparisons of Ice Cloud Macro- and Microphysical Properties Simulated by the Community Atmosphere Model CAM5 with HIPPO Aircraft Observations

NASA Astrophysics Data System (ADS)

Wu, C.; Liu, X.; Diao, M.; Zhang, K.; Gettelman, A.

2015-12-01

A dominant source of uncertainty within climate system modeling lies in the representation of cloud processes. This is not only because of the great complexity in cloud microphysics, but also because of the large variations of cloud amount and macroscopic properties in time and space. In this study, the cloud properties simulated by the Community Atmosphere Model version 5.4 (CAM5.4) are evaluated using the HIAPER Pole-to-Pole Observations (HIPPO, 2009-2011). CAM5.4 is driven by the meteorology (U, V, and T) from GEOS5 analysis, while water vapor, hydrometeors and aerosols are calculated by the model itself. For direct comparison of CAM5.4 and HIPPO observations, model output is collocated with HIPPO flights. Generally, the model has an ability to capture specific cloud systems of meso- to large-scales. In total, the model can reproduce 80% of observed cloud occurrences inside model grid boxes, and even higher (93%) for ice clouds (T≤-40°C). However, the model produces plenty of clouds that are not presented in the observation. The model also simulates significantly larger cloud fraction including for ice clouds compared to the observation. Further analysis shows that the overestimation is a result of bias in relative humidity (RH) in the model. The bias of RH can be mostly attributed to the discrepancies of water vapor, and to a lesser extent to those of temperature. Down to the micro-scale level of ice clouds, the model can simulate reasonably well the magnitude of ice and snow number concentration (Ni, with diameter larger than 75 μm). However, the model simulates fewer occurrences of Ni>50 L-1. This can be partially ascribed to the low bias of aerosol number concentration (Naer, with diameter between 0.1-1 μm) simulated by the model. Moreover, the model significantly underestimates both the number mean diameter (Di,n) and the volume mean diameter (Di,v) of ice/snow. The result shows that the underestimation may be related to a weaker positive relationship between Di,n and Naer and/or the underestimation of Naer. Finally, it is suggested that better representation of sub-grid variability of meteorology (e.g., water vapor) is needed to improve the formation and evolution of ice clouds in the model.

Evaluation of cloud-resolving model simulations of midlatitude cirrus with ARM and A-train observations

DOE PAGES

Muhlbauer, A.; Ackerman, T. P.; Lawson, R. P.; ...

2015-07-14

Cirrus clouds are ubiquitous in the upper troposphere and still constitute one of the largest uncertainties in climate predictions. Our paper evaluates cloud-resolving model (CRM) and cloud system-resolving model (CSRM) simulations of a midlatitude cirrus case with comprehensive observations collected under the auspices of the Atmospheric Radiation Measurements (ARM) program and with spaceborne observations from the National Aeronautics and Space Administration A-train satellites. The CRM simulations are driven with periodic boundary conditions and ARM forcing data, whereas the CSRM simulations are driven by the ERA-Interim product. Vertical profiles of temperature, relative humidity, and wind speeds are reasonably well simulated bymore » the CSRM and CRM, but there are remaining biases in the temperature, wind speeds, and relative humidity, which can be mitigated through nudging the model simulations toward the observed radiosonde profiles. Simulated vertical velocities are underestimated in all simulations except in the CRM simulations with grid spacings of 500 m or finer, which suggests that turbulent vertical air motions in cirrus clouds need to be parameterized in general circulation models and in CSRM simulations with horizontal grid spacings on the order of 1 km. The simulated ice water content and ice number concentrations agree with the observations in the CSRM but are underestimated in the CRM simulations. The underestimation of ice number concentrations is consistent with the overestimation of radar reflectivity in the CRM simulations and suggests that the model produces too many large ice particles especially toward the cloud base. Simulated cloud profiles are rather insensitive to perturbations in the initial conditions or the dimensionality of the model domain, but the treatment of the forcing data has a considerable effect on the outcome of the model simulations. Despite considerable progress in observations and microphysical parameterizations, simulating the microphysical, macrophysical, and radiative properties of cirrus remains challenging. Comparing model simulations with observations from multiple instruments and observational platforms is important for revealing model deficiencies and for providing rigorous benchmarks. But, there still is considerable need for reducing observational uncertainties and providing better observations especially for relative humidity and for the size distribution and chemical composition of aerosols in the upper troposphere.« less

Introducing Convective Cloud Microphysics to a Deep Convection Parameterization Facilitating Aerosol Indirect Effects

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.

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

NASA Astrophysics Data System (ADS)

Dodson, Jason B.

Deep convective clouds (DCCs) play an important role in regulating global climate through vertical mass flux, vertical water transport, and radiation. For general circulation models (GCMs) to simulate the global climate realistically, they must simulate DCCs realistically. GCMs have traditionally used cumulus parameterizations (CPs). Much recent research has shown that multiple persistent unrealistic behaviors in GCMs are related to limitations of CPs. Two alternatives to CPs exist: the global cloud-resolving model (GCRM), and the multiscale modeling framework (MMF). Both can directly simulate the coarser features of DCCs because of their multi-kilometer horizontal resolutions, and can simulate large-scale meteorological processes more realistically than GCMs. However, the question of realistic behavior of simulated DCCs remains. How closely do simulated DCCs resemble observed DCCs? In this study I examine the behavior of DCCs in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and Superparameterized Community Atmospheric Model (SP-CAM), the latter with both single-moment and double-moment microphysics. I place particular emphasis on the relationship between cloud vertical structure and convective environment. I also emphasize the transition between shallow clouds and mature DCCs. The spatial domains used are the tropical oceans and the contiguous United States (CONUS), the latter of which produces frequent vigorous convection during the summer. CloudSat is used to observe DCCs, and A-Train and reanalysis data are used to represent the large-scale environment in which the clouds form. The CloudSat cloud mask and radar reflectivity profiles for CONUS cumuliform clouds (defined as clouds with a base within the planetary boundary layer) during boreal summer are first averaged and compared. Both NICAM and SP-CAM greatly underestimate the vertical growth of cumuliform clouds. Then they are sorted by three large-scale environmental variables: total preciptable water (TPW), surface air temperature (SAT), and 500hPa vertical velocity (W500), representing the dynamical and thermodynamical environment in which the clouds form. The sorted CloudSat profiles are then compared with NICAM and SP-CAM profiles simulated with the Quickbeam CloudSat simulator. Both models have considerable difficulty representing the relationship of SAT and clouds over CONUS. For TPW and W500, shallow clouds transition to DCCs at higher values than observed. This may be an indication of the models' inability to represent the formation of DCCs in marginal convective environments. NICAM develops tall DCCs in highly favorable environments, but SP-CAM appears to be incapable of developing tall DCCs in almost any environment. The use of double moment microphysics in SP-CAM improves the frequency of deep clouds and their relationship with TPW, but not SAT. Both models underpredict radar reflectivity in the upper cloud of mature DCCs. SP-CAM with single moment microphysics has a particularly unrealistic DCC reflectivity profile, but with double moment microphysics it improves substantially. SP-CAM with double-moment microphysics unexpectedly appears to weaken DCC updraft strength as TPW increases, but otherwise both NICAM and SP-CAM represent the environment-versus-DCC relationships fairly realistically.

Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem

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

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

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

Larson, Vincent

2016-11-25

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

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.

Study on wet scavenging of atmospheric pollutants in south Brazil

NASA Astrophysics Data System (ADS)

Wiegand, Flavio; Pereira, Felipe Norte; Teixeira, Elba Calesso

2011-09-01

The present paper presents the study of in-cloud and below-cloud SO 2 and SO 42-scavenging processes by applying numerical models in the Candiota region, located in the state of Rio Grande do Sul, South Brazil. The BRAMS (Brazilian Regional Atmospheric Modeling System) model was applied to simulate the vertical structure of the clouds, and the B.V.2 (Below-Cloud Beheng Version 2) scavenging model was applied to simulate in-cloud and below-cloud scavenging processes of the pollutants SO 2 and SO 42-. Five events in 2004 were selected for this study and were sampled at the Candiota Airport station. The concentrations of SO 2 and SO 42- sampled in the air and the simulated meteorological parameters of rainfall episodes were used as input data in the B.V.2, which simulates raindrop interactions associated with the scavenging process. Results for the Candiota region showed that in-cloud scavenging processes were more significant than below-cloud scavenging processes for two of the five events studied, with a contribution of approximately 90-100% of SO 2 and SO 42- concentrations in rainwater. A few adjustments to the original version of B.V.2 were made to allow simulation of scavenging processes in several types of clouds, not only cumulus humilis and cumulus congestus.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

Lagrangian cloud model (LCM) is a fundamentally new approach of cloud simulation, in which the flow field is simulated by large eddy simulation and droplets are treated as Lagrangian particles undergoing cloud microphysics. LCM enables us to investigate raindrop formation and examine the parameterization of cloud microphysics directly by tracking the history of individual Lagrangian droplets simulated by LCM. Analysis of the magnitude of raindrop formation and the background physical conditions at the moment at which every Lagrangian droplet grows from cloud droplets to raindrops in a shallow cumulus cloud reveals how and under which condition raindrops are formed. It also provides information how autoconversion and accretion appear and evolve within a cloud, and how they are affected by various factors such as cloud water mixing ratio, rain water mixing ratio, aerosol concentration, drop size distribution, and dissipation rate. Based on these results, the parameterizations of autoconversion and accretion, such as Kessler (1969), Tripoli and Cotton (1980), Beheng (1994), and Kharioutdonov and Kogan (2000), are examined, and the modifications to improve the parameterizations are proposed.

An Evaluation of Marine Boundary Layer Cloud Property Simulations in the Community Atmosphere Model Using Satellite Observations: Conventional Subgrid Parameterization versus CLUBB

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

Scattering in infrared radiative transfer: A comparison between the spectrally averaging model JURASSIC and the line-by-line model KOPRA

NASA Astrophysics Data System (ADS)

Griessbach, Sabine; Hoffmann, Lars; Höpfner, Michael; Riese, Martin; Spang, Reinhold

2013-09-01

The viability of a spectrally averaging model to perform radiative transfer calculations in the infrared including scattering by atmospheric particles is examined for the application of infrared limb remote sensing measurements. Here we focus on the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) aboard the European Space Agency's Envisat. Various spectra for clear air and cloudy conditions were simulated with a spectrally averaging radiative transfer model and a line-by-line radiative transfer model for three atmospheric window regions (825-830, 946-951, 1224-1228 cm-1) and compared to each other. The results are rated in terms of the MIPAS noise equivalent spectral radiance (NESR). The clear air simulations generally agree within one NESR. The cloud simulations neglecting the scattering source term agree within two NESR. The differences between the cloud simulations including the scattering source term are generally below three and always below four NESR. We conclude that the spectrally averaging approach is well suited for fast and accurate infrared radiative transfer simulations including scattering by clouds. We found that the main source for the differences between the cloud simulations of both models is the cloud edge sampling. Furthermore we reasoned that this model comparison for clouds is also valid for atmospheric aerosol in general.

Dependence of stratocumulus-topped boundary-layer entrainment on cloud-water sedimentation: Impact on global aerosol indirect effect in GISS ModelE3 single column model and global simulations

NASA Astrophysics Data System (ADS)

Ackerman, A. S.; Kelley, M.; Cheng, Y.; Fridlind, A. M.; Del Genio, A. D.; Bauer, S.

2017-12-01

Reduction in cloud-water sedimentation induced by increasing droplet concentrations has been shown in large-eddy simulations (LES) and direct numerical simulation (DNS) to enhance boundary-layer entrainment, thereby reducing cloud liquid water path and offsetting the Twomey effect when the overlying air is sufficiently dry, which is typical. Among recent upgrades to ModelE3, the latest version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM), are a two-moment stratiform cloud microphysics treatment with prognostic precipitation and a moist turbulence scheme that includes an option in its entrainment closure of a simple parameterization for the effect of cloud-water sedimentation. Single column model (SCM) simulations are compared to LES results for a stratocumulus case study and show that invoking the sedimentation-entrainment parameterization option indeed reduces the dependence of cloud liquid water path on increasing aerosol concentrations. Impacts of variations of the SCM configuration and the sedimentation-entrainment parameterization will be explored. Its impact on global aerosol indirect forcing in the framework of idealized atmospheric GCM simulations will also be assessed.

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.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

A Novel Cost Based Model for Energy Consumption in Cloud Computing

PubMed Central

Horri, A.; Dastghaibyfard, Gh.

2015-01-01

Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. PMID:25705716

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

PubMed

Horri, A; Dastghaibyfard, Gh

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A Novel Tool for Simulating Aerosol-cloud Interactions with a Sectional Model Implemented to a Large-Eddy Simulator

NASA Astrophysics Data System (ADS)

Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Maalick, Z.; Korhonen, H.; Liqing, H.

2015-12-01

A new cloud-resolving model setup for studying aerosol-cloud interactions, with a special emphasis on partitioning and wet deposition of semi-volatile aerosol species, is presented. The model is based on modified versions of two well-established model components: the Large-Eddy Simulator (LES) UCLALES, and the sectional aerosol model SALSA, previously employed in the ECHAM climate model family. Implementation of the UCLALES-SALSA is described in detail. As the basis for this work, SALSA has been extended to include a sectional representation of the size distributions of cloud droplets and precipitation. Microphysical processes operating on clouds and precipitation have also been added. Given our main motivation, the cloud droplet size bins are defined according to the dry particle diameter. The droplet wet diameter is solved dynamically through condensation equations, but represents an average droplet diameter inside each size bin. This approach allows for accurate tracking of the aerosol properties inside clouds, but minimizes the computational cost. Since the actual cloud droplet diameter is not fully resolved inside the size bins, processes such as precipitation formation rely on parameterizations. For realistic growth of drizzle drops to rain, which is critical for the aerosol wet deposition, the precipitation size bins are defined according to the actual drop size. With these additions, the implementation of the SALSA model replaces most of the microphysical and thermodynamical components within the LES. The cloud properties and aerosol-cloud interactions simulated by the model are analysed and evaluated against detailed cloud microphysical boxmodel results and in-situ aerosol-cloud interaction observations from the Puijo measurement station in Kuopio, Finland. The ability of the model to reproduce the impacts of wet deposition on the aerosol population is demonstrated.

Modeling Lidar Multiple Scattering

NASA Astrophysics Data System (ADS)

Sato, Kaori; Okamoto, Hajime; Ishimoto, Hiroshi

2016-06-01

A practical model to simulate multiply scattered lidar returns from inhomogeneous cloud layers are developed based on Backward Monte Carlo (BMC) simulations. The estimated time delay of the backscattered intensities returning from different vertical grids by the developed model agreed well with that directly obtained from BMC calculations. The method was applied to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data to improve the synergetic retrieval of cloud microphysics with CloudSat radar data at optically thick cloud grids. Preliminary results for retrieving mass fraction of co-existing cloud particles and drizzle size particles within lowlevel clouds are demonstrated.

Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles.

PubMed

Vergara-Temprado, Jesús; Miltenberger, Annette K; Furtado, Kalli; Grosvenor, Daniel P; Shipway, Ben J; Hill, Adrian A; Wilkinson, Jonathan M; Field, Paul R; Murray, Benjamin J; Carslaw, Ken S

2018-03-13

Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions. Copyright © 2018 the Author(s). Published by PNAS.

Evaluation of high-level clouds in cloud resolving model simulations with ARM and KWAJEX observations

DOE PAGES

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

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

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

Low-cloud characteristics over the tropical western Pacific from ARM observations and CAM5 simulations

DOE PAGES

Chandra, Arunchandra S.; Zhang, Chidong; Klein, Stephen A.; ...

2015-09-10

Here, this study evaluates the ability of the Community Atmospheric Model version 5 (CAM5) to reproduce low clouds observed by the Atmospheric Radiation Measurement (ARM) cloud radar at Manus Island of the tropical western Pacific during the Years of Tropical Convection. Here low clouds are defined as clouds with their tops below the freezing level and bases within the boundary layer. Low-cloud statistics in CAM5 simulations and ARM observations are compared in terms of their general occurrence, mean vertical profiles, fraction of precipitating versus nonprecipitating events, diurnal cycle, and monthly time series. Other types of clouds are included to putmore » the comparison in a broader context. The comparison shows that the model overproduces total clouds and their precipitation fraction but underestimates low clouds in general. The model, however, produces excessive low clouds in a thin layer between 954 and 930 hPa, which coincides with excessive humidity near the top of the mixed layer. This suggests that the erroneously excessive low clouds stem from parameterization of both cloud and turbulence mixing. The model also fails to produce the observed diurnal cycle in low clouds, not exclusively due to the model coarse grid spacing that does not resolve Manus Island. Lastly, this study demonstrates the utility of ARM long-term cloud observations in the tropical western Pacific in verifying low clouds simulated by global climate models, illustrates issues of using ARM observations in model validation, and provides an example of severe model biases in producing observed low clouds in the tropical western Pacific.« less

Cloud evaluation using satellite simulators and cloud changes for global nonhydrostatic simulations with NICAM

NASA Astrophysics Data System (ADS)

Satoh, M.; Noda, A. T.; Kodama, C.; Yamada, Y.; Hashino, T.

2012-12-01

Global cloud distributions and properties simulated by the global nonhydrostatic model, NICAM (Nonhydrostatic Icosahedral Atmospheric Model), are evaluated and their future changes are discussed. First, we evaluated the simulated cloud properties produced by a case study of the 3.5km mesh experiment of NICAM using the satellite simulator package (the Joint-simulator) with cloud microphysics oriented approach (Hashino et al. 2012). Then, we analyzed future cloud changes using various sets of simulations under the present and the future global warming conditions. The results show that the zonal averaged ice water path (IWP) generally decreases or marginally unchanged in the tropics, while IWP in the extra-tropics increases. The upper cloud fraction increases both in the tropics and in the extra-tropics in general. We further analyzed contributions of cloud systems such as cloud clusters, tropical cyclones (TCs), and storm-tracks to these changes. Probability distribution of the larger cloud clusters decreases, while that of the smaller ones increases, consistent with the decrease in the number of tropical cyclones in the future climate. Average liquid water path (LWP) and IWP associated with each tropical cyclone are diagnosed, and it is found that both the associated LWP and IWP increase under the warmer condition. Even though, since the number of the intensive cloud systems decrease, the average IWP decreases. It should be remarked that the change in TC tracks largely contribute to the change in the horizontal distribution of clouds. The NICAM simulations also show that the storm-tracks shift poleward, and the storms become less frequent and stronger in the extra-tropics, similar to the results of other general circulation models. Both LWP and IWP associated with the storms also increase in the warmer climate in the NICAM simulations. This results in increase in the upper clouds under the warmer climate condition, as described by Miura et al. (2005). References: Hashino, T., Satoh, M., Hagihara, Y., Kubota, T., Matsui, T., Nasuno, T., and Okamoto, H. (2012), Evaluating Global Cloud Distribution and Microphysics from the NICAM against CloudSat and CALIPSO, J. Geophys. Res., submitted. Miura, H., Tomita,H., Nasuno,T., Iga, S., Satoh,M., and Matsuno, T. (2005), A climate sensitivity test using a global cloud resolving model under an aqua planet condition, Geophys. Res. Lett., 32, L19717, doi:10.1029/2005GL023672.

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.;

Macroscopic impacts of cloud and precipitation processes on maritime shallow convection as simulated by a large eddy simulation model with bin microphysics

DOE PAGES

Grabowski, W. W.; Wang, L. -P.; Prabha, T. V.

2015-01-27

This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large eddy model applying warm-rain bin microphysics. Simulations with and without collision–coalescence are considered with cloud condensation nuclei (CCN) concentrations of 30, 60, 120, and 240 mg -1. Simulations with collision–coalescence include either the standard gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts modelmore » results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the effects of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. Model results show a systematic shift in the cloud-top height distributions, with an increasing contribution of deeper clouds for stronger precipitating cases. We show that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013); namely, the increase of drizzle/rain leads to a more efficient condensate offloading in the upper parts of the cloud field. A second effect involves suppression of the cloud droplet evaporation near cloud edges in low-CCN simulations, as documented in previous studies (e.g., Xue and Feingold, 2006). We pose the question whether the effects of cloud turbulence on drizzle/rain formation in shallow cumuli can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.« less

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.

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

NASA Astrophysics Data System (ADS)

Voigt, A.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

Changes induced by perturbed aerosol conditions in moderately deep mixed-phase convective clouds (cloud top height ˜ 5 km) developing along sea-breeze convergence lines are investigated with high-resolution numerical model simulations. The simulations utilise the newly developed Cloud-AeroSol Interacting Microphysics (CASIM) module for the Unified Model (UM), which allows for the representation of the two-way interaction between cloud and aerosol fields. Simulations are evaluated against observations collected during the COnvective Precipitation Experiment (COPE) field campaign over the southwestern peninsula of the UK in 2013. The simulations compare favourably with observed thermodynamic profiles, cloud base cloud droplet number concentrations (CDNC), cloud depth, and radar reflectivity statistics. Including the modification of aerosol fields by cloud microphysical processes improves the correspondence with observed CDNC values and spatial variability, but reduces the agreement with observations for average cloud size and cloud top height. Accumulated precipitation is suppressed for higher-aerosol conditions before clouds become organised along the sea-breeze convergence lines. Changes in precipitation are smaller in simulations with aerosol processing. The precipitation suppression is due to less efficient precipitation production by warm-phase microphysics, consistent with parcel model predictions. In contrast, after convective cells organise along the sea-breeze convergence zone, accumulated precipitation increases with aerosol concentrations. Condensate production increases with the aerosol concentrations due to higher vertical velocities in the convective cores and higher cloud top heights. However, for the highest-aerosol scenarios, no further increase in the condensate production occurs, as clouds grow into an upper-level stable layer. In these cases, the reduced precipitation efficiency (PE) dominates the precipitation response and no further precipitation enhancement occurs. Previous studies of deep convective clouds have related larger vertical velocities under high-aerosol conditions to enhanced latent heating from freezing. In the presented simulations changes in latent heating above the 0°C are negligible, but latent heating from condensation increases with aerosol concentrations. It is hypothesised that this increase is related to changes in the cloud field structure reducing the mixing of environmental air into the convective core. The precipitation response of the deeper mixed-phase clouds along well-established convergence lines can be the opposite of predictions from parcel models. This occurs when clouds interact with a pre-existing thermodynamic environment and cloud field structural changes occur that are not captured by simple parcel model approaches.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Cloud-radiative effects on implied oceanic energy transport as simulated by atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Gleckler, P. J.; Randall, D. A.; Boer, G.; Colman, R.; Dix, M.; Galin, V.; Helfand, M.; Kiehl, J.; Kitoh, A.; Lau, W.

1995-01-01

This paper summarizes the ocean surface net energy flux simulated by fifteen atmospheric general circulation models constrained by realistically-varying sea surface temperatures and sea ice as part of the Atmospheric Model Intercomparison Project. In general, the simulated energy fluxes are within the very large observational uncertainties. However, the annual mean oceanic meridional heat transport that would be required to balance the simulated surface fluxes is shown to be critically sensitive to the radiative effects of clouds, to the extent that even the sign of the Southern Hemisphere ocean heat transport can be affected by the errors in simulated cloud-radiation interactions. It is suggested that improved treatment of cloud radiative effects should help in the development of coupled atmosphere-ocean general circulation models.

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

NASA Technical Reports Server (NTRS)

Zak, J. A.

1989-01-01

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

Parametric behaviors of CLUBB in simulations of low clouds in the Community Atmosphere Model (CAM)

DOE PAGES

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

Advancing cloud lifecycle representation in numerical models using innovative analysis methods that bridge arm observations over a breadth of scales

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

Tselioudis, George

2016-03-04

From its location on the subtropics-midlatitude boundary, the Azores is influenced by both the subtropical high pressure and the midlatitude baroclinic storm regimes, and therefore experiences a wide range of cloud structures, from fair-weather scenes to stratocumulus sheets to deep convective systems. This project combined three types of data sets to study cloud variability in the Azores: a satellite analysis of cloud regimes, a reanalysis characterization of storminess, and a 19-month field campaign that occurred on Graciosa Island. Combined analysis of the three data sets provides a detailed picture of cloud variability and the respective dynamic influences, with emphasis onmore » low clouds that constitute a major uncertainty source in climate model simulations. The satellite cloud regime analysis shows that the Azores cloud distribution is similar to the mean global distribution and can therefore be used to evaluate cloud simulation in global models. Regime analysis of low clouds shows that stratocumulus decks occur under the influence of the Azores high-pressure system, while shallow cumulus clouds are sustained by cold-air outbreaks, as revealed by their preference for post-frontal environments and northwesterly flows. An evaluation of CMIP5 climate model cloud regimes over the Azores shows that all models severely underpredict shallow cumulus clouds, while most models also underpredict the occurrence of stratocumulus cloud decks. It is demonstrated that carefully selected case studies can be related through regime analysis to climatological cloud distributions, and a methodology is suggested utilizing process-resolving model simulations of individual cases to better understand cloud-dynamics interactions and attempt to explain and correct climate model cloud deficiencies.« less

Testing the Two-Layer Model for Correcting Near Cloud Reflectance Enhancement Using LES SHDOM Simulated Radiances

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Varnai, Tamas; Levy, Robert

2016-01-01

A transition zone exists between cloudy skies and clear sky; such that, clouds scatter solar radiation into clear-sky regions. From a satellite perspective, it appears that clouds enhance the radiation nearby. We seek a simple method to estimate this enhancement, since it is so computationally expensive to account for all three-dimensional (3-D) scattering processes. In previous studies, we developed a simple two-layer model (2LM) that estimated the radiation scattered via cloud-molecular interactions. Here we have developed a new model to account for cloud-surface interaction (CSI). We test the models by comparing to calculations provided by full 3-D radiative transfer simulations of realistic cloud scenes. For these scenes, the Moderate Resolution Imaging Spectroradiometer (MODIS)-like radiance fields were computed from the Spherical Harmonic Discrete Ordinate Method (SHDOM), based on a large number of cumulus fields simulated by the University of California, Los Angeles (UCLA) large eddy simulation (LES) model. We find that the original 2LM model that estimates cloud-air molecule interactions accounts for 64 of the total reflectance enhancement and the new model (2LM+CSI) that also includes cloud-surface interactions accounts for nearly 80. We discuss the possibility of accounting for cloud-aerosol radiative interactions in 3-D cloud-induced reflectance enhancement, which may explain the remaining 20 of enhancements. Because these are simple models, these corrections can be applied to global satellite observations (e.g., MODIS) and help to reduce biases in aerosol and other clear-sky retrievals.

Use NU-WRF and GCE Model to Simulate the Precipitation Processes During MC3E Campaign

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Wu, Di; Matsui, Toshi; Li, Xiaowen; Zeng, Xiping; Peter-Lidard, Christa; Hou, Arthur

2012-01-01

One of major CRM approaches to studying precipitation processes is sometimes referred to as "cloud ensemble modeling". This approach allows many clouds of various sizes and stages of their lifecycles to be present at any given simulation time. Large-scale effects derived from observations are imposed into CRMs as forcing, and cyclic lateral boundaries are used. The advantage of this approach is that model results in terms of rainfall and QI and Q2 usually are in good agreement with observations. In addition, the model results provide cloud statistics that represent different types of clouds/cloud systems during their lifetime (life cycle). The large-scale forcing derived from MC3EI will be used to drive GCE model simulations. The model-simulated results will be compared with observations from MC3E. These GCE model-simulated datasets are especially valuable for LH algorithm developers. In addition, the regional scale model with very high-resolution, NASA Unified WRF is also used to real time forecast during the MC3E campaign to ensure that the precipitation and other meteorological forecasts are available to the flight planning team and to interpret the forecast results in terms of proposed flight scenarios. Post Mission simulations are conducted to examine the sensitivity of initial and lateral boundary conditions to cloud and precipitation processes and rainfall. We will compare model results in terms of precipitation and surface rainfall using GCE model and NU-WRF

Regime-based evaluation of cloudiness in CMIP5 models

NASA Astrophysics Data System (ADS)

Jin, Daeho; Oreopoulos, Lazaros; Lee, Dongmin

2017-01-01

The concept of cloud regimes (CRs) is used to develop a framework for evaluating the cloudiness of 12 fifth Coupled Model Intercomparison Project (CMIP5) models. Reference CRs come from existing global International Satellite Cloud Climatology Project (ISCCP) weather states. The evaluation is made possible by the implementation in several CMIP5 models of the ISCCP simulator generating in each grid cell daily joint histograms of cloud optical thickness and cloud top pressure. Model performance is assessed with several metrics such as CR global cloud fraction (CF), CR relative frequency of occurrence (RFO), their product [long-term average total cloud amount (TCA)], cross-correlations of CR RFO maps, and a metric of resemblance between model and ISCCP CRs. In terms of CR global RFO, arguably the most fundamental metric, the models perform unsatisfactorily overall, except for CRs representing thick storm clouds. Because model CR CF is internally constrained by our method, RFO discrepancies yield also substantial TCA errors. Our results support previous findings that CMIP5 models underestimate cloudiness. The multi-model mean performs well in matching observed RFO maps for many CRs, but is still not the best for this or other metrics. When overall performance across all CRs is assessed, some models, despite shortcomings, apparently outperform Moderate Resolution Imaging Spectroradiometer cloud observations evaluated against ISCCP like another model output. Lastly, contrasting cloud simulation performance against each model's equilibrium climate sensitivity in order to gain insight on whether good cloud simulation pairs with particular values of this parameter, yields no clear conclusions.

Filtering and Gridding Satellite Observations of Cloud Variables to Compare with Climate Model Output

NASA Astrophysics Data System (ADS)

Pitts, K.; Nasiri, S. L.; Smith, N.

2013-12-01

Global climate models have improved considerably over the years, yet clouds still represent a large factor of uncertainty for these models. Comparisons of model-simulated cloud variables with equivalent satellite cloud products are the best way to start diagnosing the differences between model output and observations. Gridded (level 3) cloud products from many different satellites and instruments are required for a full analysis, but these products are created by different science teams using different algorithms and filtering criteria to create similar, but not directly comparable, cloud products. This study makes use of a recently developed uniform space-time gridding algorithm to create a new set of gridded cloud products from each satellite instrument's level 2 data of interest which are each filtered using the same criteria, allowing for a more direct comparison between satellite products. The filtering is done via several variables such as cloud top pressure/height, thermodynamic phase, optical properties, satellite viewing angle, and sun zenith angle. The filtering criteria are determined based on the variable being analyzed and the science question at hand. Each comparison of different variables may require different filtering strategies as no single approach is appropriate for all problems. Beyond inter-satellite data comparison, these new sets of uniformly gridded satellite products can also be used for comparison with model-simulated cloud variables. Of particular interest to this study are the differences in the vertical distributions of ice and liquid water content between the satellite retrievals and model simulations, especially in the mid-troposphere where there are mixed-phase clouds to consider. This presentation will demonstrate the proof of concept through comparisons of cloud water path from Aqua MODIS retrievals and NASA GISS-E2-[R/H] model simulations archived in the CMIP5 data portal.

Statistical Evaluation of CRM-Simulated Cloud and Precipitation Structures Using Multi- sensor TRMM Measurements and Retrievals

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.

Mean-state acceleration of cloud-resolving models and large eddy simulations

DOE PAGES

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

Design, Evaluation and GCM-Performance of a New Parameterization for Microphysics of Clouds with Relaxed Arakawa-Schubert Scheme (McRas)

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.

Use of High-Resolution Satellite Observations to Evaluate Cloud and Precipitation Statistics from Cloud-Resolving Model Simulations

NASA Astrophysics Data System (ADS)

Zhou, Y.; Tao, W.; Hou, A. Y.; Zeng, X.; Shie, C.

2007-12-01

The cloud and precipitation statistics simulated by 3D Goddard Cumulus Ensemble (GCE) model for different environmental conditions, i.e., the South China Sea Monsoon Experiment (SCSMEX), CRYSTAL-FACE, and KAWJEX are compared with Tropical Rainfall Measuring Mission (TRMM) TMI and PR rainfall measurements and as well as cloud observations from the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments. It is found that GCE is capable of simulating major convective system development and reproducing total surface rainfall amount as compared with rainfall estimated from the soundings. The model presents large discrepancies in rain spectrum and vertical hydrometer profiles. The discrepancy in the precipitation field is also consistent with the cloud and radiation observations. The study will focus on the effects of large scale forcing and microphysics to the simulated model- observation discrepancies.

Role of clouds, aerosols, and aerosol-cloud interaction in 20th century simulations with GISS ModelE2

NASA Astrophysics Data System (ADS)

Nazarenko, L.; Rind, D. H.; Bauer, S.; Del Genio, A. D.

2015-12-01

Simulations of aerosols, clouds and their interaction contribute to the major source of uncertainty in predicting the changing Earth's energy and in estimating future climate. Anthropogenic contribution of aerosols affects the properties of clouds through aerosol indirect effects. Three different versions of NASA GISS global climate model are presented for simulation of the twentieth century climate change. All versions have fully interactive tracers of aerosols and chemistry in both the troposphere and stratosphere. All chemical species are simulated prognostically consistent with atmospheric physics in the model and the emissions of short-lived precursors [Shindell et al., 2006]. One version does not include the aerosol indirect effect on clouds. The other two versions include a parameterization of the interactive first indirect aerosol effect on clouds following Menon et al. [2010]. One of these two models has the Multiconfiguration Aerosol Tracker of Mixing state (MATRIX) that permits detailed treatment of aerosol mixing state, size, and aerosol-cloud activation. The main purpose of this study is evaluation of aerosol-clouds interactions and feedbacks, as well as cloud and aerosol radiative forcings, for the twentieth century climate under different assumptions and parameterizations for aerosol, clouds and their interactions in the climate models. The change of global surface air temperature based on linear trend ranges from +0.8°C to +1.2°C between 1850 and 2012. Water cloud optical thickness increases with increasing temperature in all versions with the largest increase in models with interactive indirect effect of aerosols on clouds, which leads to the total (shortwave and longwave) cloud radiative cooling trend at the top of the atmosphere. Menon, S., D. Koch, G. Beig, S. Sahu, J. Fasullo, and D. Orlikowski (2010), Black carbon aerosols and the third polar ice cap, Atmos. Chem. Phys., 10,4559-4571, doi:10.5194/acp-10-4559-2010. Shindell, D., G. Faluvegi, N. Unger, E. Aguilar, G.A. Schmidt, D.M. Koch, S.E. Bauer, and J.R. Miller (2006), Simulations of preindustrial, present-day, and 2100 conditions in the NASA GISS composition and climate model G-PUCCINI, Atmos. Chem. Phys., 6, 4427-4459.

Evaluating and improving cloud phase in the Community Atmosphere Model version 5 using spaceborne lidar observations

NASA Astrophysics Data System (ADS)

Kay, Jennifer E.; Bourdages, Line; Miller, Nathaniel B.; Morrison, Ariel; Yettella, Vineel; Chepfer, Helene; Eaton, Brian

2016-04-01

Spaceborne lidar observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state-of-the-art global coupled climate model (Community Earth System Model). By embedding a lidar simulator within CAM5, the idiosyncrasies of spaceborne lidar cloud detection and phase assignment are replicated. As a result, this study makes scale-aware and definition-aware comparisons between model-simulated and observed cloud amount and cloud phase. In the global mean, CAM5 has insufficient liquid cloud and excessive ice cloud when compared to CALIPSO observations. Over the ice-covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons. Having important implications for projections of future sea level rise, a liquid cloud deficit contributes to a cold bias of 2-3°C for summer daily maximum near-surface air temperatures at Summit, Greenland. Over the midlatitude storm tracks, CAM5 has excessive ice cloud and insufficient liquid cloud. Storm track cloud phase biases in CAM5 maximize over the Southern Ocean, which also has larger-than-observed seasonal variations in cloud phase. Physical parameter modifications reduce the Southern Ocean cloud phase and shortwave radiation biases in CAM5 and illustrate the power of the CALIPSO observations as an observational constraint. The results also highlight the importance of using a regime-based, as opposed to a geographic-based, model evaluation approach. More generally, the results demonstrate the importance and value of simulator-enabled comparisons of cloud phase in models used for future climate projection.

Automating NEURON Simulation Deployment in Cloud Resources.

PubMed

Stockton, David B; Santamaria, Fidel

2017-01-01

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the OpenStack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon's proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model.

Automating NEURON Simulation Deployment in Cloud Resources

PubMed Central

Santamaria, Fidel

2016-01-01

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the Open-Stack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon’s proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model. PMID:27655341

Comparison of three ice cloud optical schemes in climate simulations with community atmospheric model version 5

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.

Limits to Cloud Susceptibility

NASA Technical Reports Server (NTRS)

Coakley, James A., Jr.

2002-01-01

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

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.

Intercomparison of cloud model simulations of Arctic mixed-phase boundary layer clouds observed during SHEBA/FIRE-ACE

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

Morrison, H.; Zuidema, Paquita; Ackerman, Andrew

2011-06-16

An intercomparison of six cloud-resolving and large-eddy simulation models is presented. This case study is based on observations of a persistent mixed-phase boundary layer cloud gathered on 7 May, 1998 from the Surface Heat Budget of Arctic Ocean (SHEBA) and First ISCCP Regional Experiment - Arctic Cloud Experiment (FIRE-ACE). Ice nucleation is constrained in the simulations in a way that holds the ice crystal concentration approximately fixed, with two sets of sensitivity runs in addition to the baseline simulations utilizing different specified ice nucleus (IN) concentrations. All of the baseline and sensitivity simulations group into two distinct quasi-steady states associatedmore » with either persistent mixed-phase clouds or all-ice clouds after the first few hours of integration, implying the existence of multiple equilibria. These two states are associated with distinctly different microphysical, thermodynamic, and radiative characteristics. Most but not all of the models produce a persistent mixed-phase cloud qualitatively similar to observations using the baseline IN/crystal concentration, while small increases in the IN/crystal concentration generally lead to rapid glaciation and conversion to the all-ice state. Budget analysis indicates that larger ice deposition rates associated with increased IN/crystal concentrations have a limited direct impact on dissipation of liquid in these simulations. However, the impact of increased ice deposition is greatly enhanced by several interaction pathways that lead to an increased surface precipitation flux, weaker cloud top radiative cooling and cloud dynamics, and reduced vertical mixing, promoting rapid glaciation of the mixed-phase cloud for deposition rates in the cloud layer greater than about 1-2x10-5 g kg-1 s-1. These results indicate the critical importance of precipitation-radiative-dynamical interactions in simulating cloud phase, which have been neglected in previous fixed-dynamical parcel studies of the cloud phase parameter space. Large sensitivity to the IN/crystal concentration also suggests the need for improved understanding of ice nucleation and its parameterization in models.« less

Aerosol Processing in Mixed-Phase Clouds in ECHAM5-HAM: Comparison of Single-Column Model Simulations to Observations

NASA Astrophysics Data System (ADS)

Hoose, C.; Lohmann, U.; Stier, P.; Verheggen, B.; Weingartner, E.; Herich, H.

2007-12-01

The global aerosol-climate model ECHAM5-HAM (Stier et al., 2005) has been extended by an explicit treatment of cloud-borne particles. Two additional modes for in-droplet and in-crystal particles are introduced, which are coupled to the number of cloud droplet and ice crystal concentrations simulated by the ECHAM5 double-moment cloud microphysics scheme (Lohmann et al., 2007). Transfer, production and removal of cloud-borne aerosol number and mass by cloud droplet activation, collision scavenging, aqueous-phase sulfate production, freezing, melting, evaporation, sublimation and precipitation formation are taken into account. The model performance is demonstrated and validated with observations of the evolution of total and interstitial aerosol concentrations and size distributions during three different mixed-phase cloud events at the alpine high-altitude research station Jungfraujoch (Switzerland) (Verheggen et al, 2007). Although the single-column simulations can not be compared one-to-one with the observations, the governing processes in the evolution of the cloud and aerosol parameters are captured qualitatively well. High scavenged fractions are found during the presence of liquid water, while the release of particles during the Bergeron-Findeisen process results in low scavenged fractions after cloud glaciation. The observed coexistence of liquid and ice, which might be related to cloud heterogeneity at subgrid scales, can only be simulated in the model when forcing non-equilibrium conditions. References: U. Lohmann et al., Cloud microphysics and aerosol indirect effects in the global climate model ECHAM5-HAM, Atmos. Chem. Phys. 7, 3425-3446 (2007) P. Stier et al., The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys. 5, 1125-1156 (2005) B. Verheggen et al., Aerosol partitioning between the interstitial and the condensed phase in mixed-phase clouds, Accepted for publication in J. Geophys. Res. (2007)

Evaluation of cloud fraction and its radiative effect simulated by IPCC AR4 global models against ARM surface observations

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

Qian, Yun; Long, Charles N.; Wang, Hailong

2012-02-17

Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulations in the IPCC AR4 GCMs against ARM ground measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity, for both inter-model deviation and model-measurement discrepancy. Our intercomparisons of three CF or sky-cover related dataset reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The results also show that the model-observation and the inter-model deviations have a similar magnitude for themore » total CF (TCF) and the normalized cloud effect, and they are twice as large as the surface downward solar radiation and cloud transmissivity. This implies that the other cloud properties, such as cloud optical depth and height, have a similar magnitude of disparity to TCF among the GCMs, and suggests that a better agreement among the GCMs in solar radiative fluxes could be the result of compensating errors in either cloud vertical structure, cloud optical depth or cloud fraction. Similar deviation pattern between inter-model and model-measurement suggests that the climate models tend to generate larger bias against observations for those variables with larger inter-model deviation. The simulated TCF from IPCC AR4 GCMs are very scattered through all seasons over three ARM sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). The GCMs perform better at SGP than at Manus and NSA in simulating the seasonal variation and probability distribution of TCF; however, the TCF in these models is remarkably underpredicted and cloud transmissivity is less susceptible to the change of TCF than the observed at SGP. Much larger inter-model deviation and model bias are found over NSA than the other sites in estimating the TCF, cloud transmissivity and cloud-radiation interaction, suggesting that the Arctic region continues to challenge cloud simulations in climate models. Most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels in the tropics. The high altitude CF is much larger in the GCMs than the observation and the inter-model variability of CF also reaches maximum at high levels in the tropics. Most of the GCMs tend to underpredict CF by 50-150% relative to the measurement average at low and middle levels over SGP. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near surface over the Arctic. The internal variability of CF simulated in ensemble runs with the same model is very minimal.« less

The influence of Cloud Longwave Scattering together with a state-of-the-art Ice Longwave Optical Parameterization in Climate Model Simulations

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.

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

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

Assessment of marine boundary layer cloud simulations in the CAM with CLUBB and updated microphysics scheme based on ARM observations from the Azores

DOE PAGES

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

Large Eddy Simulations of Continental Boundary Layer Clouds Observed during the RACORO Field Campaign

NASA Astrophysics Data System (ADS)

Endo, S.; Fridlind, A. M.; Lin, W.; Vogelmann, A. M.; Toto, T.; Liu, Y.

2013-12-01

Three cases of boundary layer clouds are analyzed in the FAst-physics System TEstbed and Research (FASTER) project, based on continental boundary-layer-cloud observations during the RACORO Campaign [Routine Atmospheric Radiation Measurement (ARM) Aerial Facility (AAF) Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations] at the ARM Climate Research Facility's Southern Great Plains (SGP) site. The three 60-hour case study periods are selected to capture the temporal evolution of cumulus, stratiform, and drizzling boundary-layer cloud systems under a range of conditions, intentionally including those that are relatively more mixed or transitional in nature versus being of a purely canonical type. Multi-modal and temporally varying aerosol number size distribution profiles are derived from aircraft observations. Large eddy simulations (LESs) are performed for the three case study periods using the GISS Distributed Hydrodynamic Aerosol and Radiative Modeling Application (DHARMA) model and the WRF-FASTER model, which is the Weather Research and Forecasting (WRF) model implemented with forcing ingestion and other functions to constitute a flexible LES. The two LES models commonly capture the significant transitions of cloud-topped boundary layers in the three periods: diurnal evolution of cumulus layers repeating over multiple days, nighttime evolution/daytime diminution of thick stratus, and daytime breakup of stratus and stratocumulus clouds. Simulated transitions of thermodynamic structures of the cloud-topped boundary layers are examined by balloon-borne soundings and ground-based remote sensors. Aircraft observations are then used to statistically evaluate the predicted cloud droplet number size distributions under varying aerosol and cloud conditions. An ensemble approach is used to refine the model configuration for the combined use of observations with parallel LES and single-column model simulations. See Lin et al. poster for single-column model investigation.

Simulating the Current Water Cycle with the NASA Ames Mars Global Climate Model

NASA Astrophysics Data System (ADS)

Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Brecht, A. S.; Urata, R. A.; Montmessin, F.

2017-12-01

The water cycle is a critical component of the current Mars climate system, and it is now widely recognized that water ice clouds significantly affect the nature of the simulated water cycle. Two processes are key to implementing clouds in a Mars global climate model (GCM): the microphysical processes of formation and dissipation, and their radiative effects on atmospheric heating/cooling rates. Together, these processes alter the thermal structure, change the atmospheric dynamics, and regulate inter-hemispheric transport. We have made considerable progress using the NASA Ames Mars GCM to simulate the current-day water cycle with radiatively active clouds. Cloud fields from our baseline simulation are in generally good agreement with observations. The predicted seasonal extent and peak IR optical depths are consistent MGS/TES observations. Additionally, the thermal response to the clouds in the aphelion cloud belt (ACB) is generally consistent with observations and other climate model predictions. Notably, there is a distinct gap in the predicted clouds over the North Residual Cap (NRC) during local summer, but the clouds reappear in this simulation over the NRC earlier than the observations indicate. Polar clouds are predicted near the seasonal CO2 ice caps, but the column thicknesses of these clouds are generally too thick compared to observations. Our baseline simulation is dry compared to MGS/TES-observed water vapor abundances, particularly in the tropics and subtropics. These areas of disagreement appear to be a consistent with other current water cycle GCMs. Future avenues of investigation will target improving our understanding of what controls the vertical extent of clouds and the apparent seasonal evolution of cloud particle sizes within the ACB.

Sensitivity of a cloud parameterization package in the National Center for Atmospheric Research Community Climate Model

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.

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

Regime-Based Evaluation of Cloudiness in CMIP5 Models

NASA Technical Reports Server (NTRS)

Jin, Daeho; Oraiopoulos, Lazaros; Lee, Dong Min

2016-01-01

The concept of Cloud Regimes (CRs) is used to develop a framework for evaluating the cloudiness of 12 fifth Coupled Model Intercomparison Project (CMIP5) models. Reference CRs come from existing global International Satellite Cloud Climatology Project (ISCCP) weather states. The evaluation is made possible by the implementation in several CMIP5 models of the ISCCP simulator generating for each gridcell daily joint histograms of cloud optical thickness and cloud top pressure. Model performance is assessed with several metrics such as CR global cloud fraction (CF), CR relative frequency of occurrence (RFO), their product (long-term average total cloud amount [TCA]), cross-correlations of CR RFO maps, and a metric of resemblance between model and ISCCP CRs. In terms of CR global RFO, arguably the most fundamental metric, the models perform unsatisfactorily overall, except for CRs representing thick storm clouds. Because model CR CF is internally constrained by our method, RFO discrepancies yield also substantial TCA errors. Our findings support previous studies showing that CMIP5 models underestimate cloudiness. The multi-model mean performs well in matching observed RFO maps for many CRs, but is not the best for this or other metrics. When overall performance across all CRs is assessed, some models, despite their shortcomings, apparently outperform Moderate Resolution Imaging Spectroradiometer (MODIS) cloud observations evaluated against ISCCP as if they were another model output. Lastly, cloud simulation performance is contrasted with each model's equilibrium climate sensitivity (ECS) in order to gain insight on whether good cloud simulation pairs with particular values of this parameter.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

Despite the increasing sophistication of climate models, the amount of surface warming expected from a doubling of atmospheric CO_2 (equilibrium climate sensitivity) remains stubbornly uncertain, in part because of differences in how models simulate the change in global albedo due to clouds (the shortwave cloud feedback). Here, model differences in the shortwave cloud feedback are found to be closely related to the spatial pattern of the cloud contribution to albedo (α) in simulations of the current climate: high-feedback models exhibit lower (higher) α in regions of warm (cool) sea-surface temperatures, and therefore predict a larger reduction in global-mean α as temperatures rise and warm regions expand. The spatial pattern of α is found to be strongly predictive (r=0.84) of a model's global cloud feedback, with satellite observations indicating a most-likely value of 0.58± 0.31 Wm^{-2} K^{-1} (90% confidence). This estimate is higher than the model-average cloud feedback of 0.43 Wm^{-2} K^{-1}, with half the range of uncertainty. The observational constraint on climate sensitivity is weaker but still significant, suggesting a likely value of 3.68 ± 1.30 K (90% confidence), which also favors the upper range of model estimates. These results suggest that uncertainty in model estimates of the global cloud feedback may be substantially reduced by ensuring a realistic distribution of clouds between regions of warm and cool SSTs in simulations of the current climate.

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.

Application of the CloudSat and NEXRAD Radars Toward Improvements in High Resolution Operational Forecasts

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.

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains

DOE PAGES

Van Weverberg, K.; Morcrette, C. J.; Petch, J.; ...

2018-02-28

Many Numerical Weather Prediction (NWP) and climate models exhibit too warm lower tropospheres near the midlatitude continents. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in nine model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor, and aerosols are quantified, using an array of radiation measurement stationsmore » near the Atmospheric Radiation Measurement Southern Great Plains site. Furthermore, an in-depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although nonnegligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud radiative effects dominate in the cloud-related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.« less

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains

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

Van Weverberg, K.; Morcrette, C. J.; Petch, J.

Many Numerical Weather Prediction (NWP) and climate models exhibit too warm lower tropospheres near the midlatitude continents. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in nine model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor, and aerosols are quantified, using an array of radiation measurement stationsmore » near the Atmospheric Radiation Measurement Southern Great Plains site. Furthermore, an in-depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although nonnegligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud radiative effects dominate in the cloud-related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.« less

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains

NASA Astrophysics Data System (ADS)

Van Weverberg, K.; Morcrette, C. J.; Petch, J.; Klein, S. A.; Ma, H.-Y.; Zhang, C.; Xie, S.; Tang, Q.; Gustafson, W. I.; Qian, Y.; Berg, L. K.; Liu, Y.; Huang, M.; Ahlgrimm, M.; Forbes, R.; Bazile, E.; Roehrig, R.; Cole, J.; Merryfield, W.; Lee, W.-S.; Cheruy, F.; Mellul, L.; Wang, Y.-C.; Johnson, K.; Thieman, M. M.

2018-04-01

Many Numerical Weather Prediction (NWP) and climate models exhibit too warm lower tropospheres near the midlatitude continents. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in nine model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor, and aerosols are quantified, using an array of radiation measurement stations near the Atmospheric Radiation Measurement Southern Great Plains site. Furthermore, an in-depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although nonnegligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud radiative effects dominate in the cloud-related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.

Relationships of Upper Tropospheric Water Vapor, Clouds and SST: MLS Observations, ECMWF Analyses and GCM Simulations

NASA Technical Reports Server (NTRS)

Su, Hui; Waliser, Duane E.; Jiang, Jonathan H.; Li, Jui-lin; Read, William G.; Waters, Joe W.; Tompkins, Adrian M.

2006-01-01

The relationships of upper tropospheric water vapor (UTWV), cloud ice and sea surface temperature (SST) are examined in the annual cycles of ECMWF analyses and simulations from 15 atmosphere-ocean coupled models which were contributed to the IPCC AR4. The results are compared with the observed relationships based on UTWV and cloud ice measurements from MLS on Aura. It is shown that the ECMWF analyses produce positive correlations between UTWV, cloud ice and SST, similar to the MLS data. The rate of the increase of cloud ice and UTWV with SST is about 30% larger than that for MLS. For the IPCC simulations, the relationships between UTWV, cloud ice and SST are qualitatively captured. However, the magnitudes of the simulated cloud ice show a considerable disagreement between models, by nearly a factor of 10. The amplitudes of the approximate linear relations between UTWV, cloud ice and SST vary by a factor up to 4.

On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Zeng, Xiping; Tao, Wei-Kuo; Lang, Stephen; Hou, Arthur Y.; Zhang, Minghua; Simpson, Joanne

2008-01-01

Month-long large-scale forcing data from two field campaigns are used to drive a cloud-resolving model (CRM) and produce ensemble simulations of clouds and precipitation. Observational data are then used to evaluate the model results. To improve the model results, a new parameterization of the Bergeron process is proposed that incorporates the number concentration of ice nuclei (IN). Numerical simulations reveal that atmospheric ensembles are sensitive to IN concentration and ice crystal multiplication. Two- (2D) and three-dimensional (3D) simulations are carried out to address the sensitivity of atmospheric ensembles to model dimensionality. It is found that the ensembles with high IN concentration are more sensitive to dimensionality than those with low IN concentration. Both the analytic solutions of linear dry models and the CRM output show that there are more convective cores with stronger updrafts in 3D simulations than in 2D, which explains the differing sensitivity of the ensembles to dimensionality at different IN concentrations.

A Quantitative Investigation of Entrainment and Detrainment in Numerically Simulated Convective Clouds. Pt. 1; Model Development

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.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

SPARSE—A subgrid particle averaged Reynolds stress equivalent model: testing with a priori closure

PubMed Central

Davis, Sean L.; Sen, Oishik; Udaykumar, H. S.

2017-01-01

A Lagrangian particle cloud model is proposed that accounts for the effects of Reynolds-averaged particle and turbulent stresses and the averaged carrier-phase velocity of the subparticle cloud scale on the averaged motion and velocity of the cloud. The SPARSE (subgrid particle averaged Reynolds stress equivalent) model is based on a combination of a truncated Taylor expansion of a drag correction function and Reynolds averaging. It reduces the required number of computational parcels to trace a cloud of particles in Eulerian–Lagrangian methods for the simulation of particle-laden flow. Closure is performed in an a priori manner using a reference simulation where all particles in the cloud are traced individually with a point-particle model. Comparison of a first-order model and SPARSE with the reference simulation in one dimension shows that both the stress and the averaging of the carrier-phase velocity on the cloud subscale affect the averaged motion of the particle. A three-dimensional isotropic turbulence computation shows that only one computational parcel is sufficient to accurately trace a cloud of tens of thousands of particles. PMID:28413341

SPARSE-A subgrid particle averaged Reynolds stress equivalent model: testing with a priori closure.

PubMed

Davis, Sean L; Jacobs, Gustaaf B; Sen, Oishik; Udaykumar, H S

2017-03-01

A Lagrangian particle cloud model is proposed that accounts for the effects of Reynolds-averaged particle and turbulent stresses and the averaged carrier-phase velocity of the subparticle cloud scale on the averaged motion and velocity of the cloud. The SPARSE (subgrid particle averaged Reynolds stress equivalent) model is based on a combination of a truncated Taylor expansion of a drag correction function and Reynolds averaging. It reduces the required number of computational parcels to trace a cloud of particles in Eulerian-Lagrangian methods for the simulation of particle-laden flow. Closure is performed in an a priori manner using a reference simulation where all particles in the cloud are traced individually with a point-particle model. Comparison of a first-order model and SPARSE with the reference simulation in one dimension shows that both the stress and the averaging of the carrier-phase velocity on the cloud subscale affect the averaged motion of the particle. A three-dimensional isotropic turbulence computation shows that only one computational parcel is sufficient to accurately trace a cloud of tens of thousands of particles.

Tropical Oceanic Precipitation Processes over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.- K.; Johnson, D.

1998-01-01

Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere, The vertical distribution of convective latent-heat release modulates the large-scale circulations of the tropics, Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate models simulate cloud processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMS) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and cloud systems, The major objective of this paper is to investigate the latent heating, moisture and momenti,im budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (CCE) model which includes a 3-class ice-phase microphysical scheme, The model domain contains 256 x 256 grid points (using 2 km resolution) in the horizontal and 38 grid points (to a depth of 22 km depth) in the vertical, The 2D domain has 1024 grid points. The simulations are performed over a 7 day time period. We will examine (1) the precipitation processes (i.e., condensation/evaporation) and their interaction with warm pool; (2) the heating and moisture budgets in the convective and stratiform regions; (3) the cloud (upward-downward) mass fluxes in convective and stratiform regions; (4) characteristics of clouds (such as cloud size, updraft intensity and cloud lifetime) and the comparison of clouds with Radar observations. Differences and similarities in organization of convection between simulated 2D and 3D cloud systems. Preliminary results indicated that there is major differences between 2D and 3D simulated stratiform rainfall amount and convective updraft and downdraft mass fluxes.

Assessing regional scale predictions of aerosols, marine stratocumulus, and their interactions during VOCALS-REx using WRF-Chem

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

Determination of Ice Cloud Models Using MODIS and MISR Data

NASA Technical Reports Server (NTRS)

Xie, Yu; Yang, Ping; Kattawar, George W.; Minnis, Patrick; Hu, Yongxiang; Wu, Dong L.

2012-01-01

Representation of ice clouds in radiative transfer simulations is subject to uncertainties associated with the shapes and sizes of ice crystals within cirrus clouds. In this study, we examined several ice cloud models consisting of smooth, roughened, homogeneous and inhomogeneous hexagonal ice crystals with various aspect ratios. The sensitivity of the bulk scattering properties and solar reflectances of cirrus clouds to specific ice cloud models is investigated using the improved geometric optics method (IGOM) and the discrete ordinates radiative transfer (DISORT) model. The ice crystal habit fractions in the ice cloud model may significantly affect the simulations of cloud reflectances. A new algorithm was developed to help determine an appropriate ice cloud model for application to the satellite-based retrieval of ice cloud properties. The ice cloud particle size retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data, collocated with Multi-angle Imaging Spectroradiometer (MISR) observations, is used to infer the optical thicknesses of ice clouds for nine MISR viewing angles. The relative differences between view-dependent cloud optical thickness and the averaged value over the nine MISR viewing angles can vary from -0.5 to 0.5 and are used to evaluate the ice cloud models. In the case for 2 July 2009, the ice cloud model with mixed ice crystal habits is the best fit to the observations (the root mean square (RMS) error of cloud optical thickness reaches 0.365). This ice cloud model also produces consistent cloud property retrievals for the nine MISR viewing configurations within the measurement uncertainties.

A Ground-Based Doppler Radar and Micropulse Lidar Forward Simulator for GCM Evaluation of Arctic Mixed-Phase Clouds: Moving Forward Towards an Apples-to-apples Comparison of Hydrometeor Phase

NASA Astrophysics Data System (ADS)

Lamer, K.; Fridlind, A. M.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2017-12-01

An important aspect of evaluating Artic cloud representation in a general circulation model (GCM) consists of using observational benchmarks which are as equivalent as possible to model output in order to avoid methodological bias and focus on correctly diagnosing model dynamical and microphysical misrepresentations. However, current cloud observing systems are known to suffer from biases such as limited sensitivity, and stronger response to large or small hydrometeors. Fortunately, while these observational biases cannot be corrected, they are often well understood and can be reproduced in forward simulations. Here a ground-based millimeter wavelength Doppler radar and micropulse lidar forward simulator able to interface with output from the Goddard Institute for Space Studies (GISS) ModelE GCM is presented. ModelE stratiform hydrometeor fraction, mixing ratio, mass-weighted fall speed and effective radius are forward simulated to vertically-resolved profiles of radar reflectivity, Doppler velocity and spectrum width as well as lidar backscatter and depolarization ratio. These forward simulated fields are then compared to Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) ground-based observations to assess cloud vertical structure (CVS). Model evalution of Arctic mixed-phase cloud would also benefit from hydrometeor phase evaluation. While phase retrieval from synergetic observations often generates large uncertainties, the same retrieval algorithm can be applied to observed and forward-simulated radar-lidar fields, thereby producing retrieved hydrometeor properties with potentially the same uncertainties. Comparing hydrometeor properties retrieved in exactly the same way aims to produce the best apples-to-apples comparisons between GCM ouputs and observations. The use of a comprenhensive ground-based forward simulator coupled with a hydrometeor classification retrieval algorithm provides a new perspective for GCM evaluation of Arctic mixed-phase clouds from the ground where low-level supercooled liquid layer are more easily observed and where additional environmental properties such as cloud condensation nuclei are quantified. This should help assist in choosing between several possible diagnostic ice nucleation schemes for ModelE stratiform cloud.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Coupling Spectral-bin Cloud Microphysics with the MOSAIC Aerosol Model in WRF-Chem: Methodology and Results for Marine Stratocumulus Clouds

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

Gao, Wenhua; Fan, Jiwen; Easter, Richard C.

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

CesrTA Retarding Field Analyzer Modeling Results

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

Calvey, J.R.; Celata, C.M.; Crittenden, J.A.

2010-05-23

Retarding field analyzers (RFAs) provide an effective measure of the local electron cloud density and energy distribution. Proper interpretation of RFA data can yield information about the behavior of the cloud, as well as the surface properties of the instrumented vacuum chamber. However, due to the complex interaction of the cloud with the RFA itself, understanding these measurements can be nontrivial. This paper examines different methods for interpreting RFA data via cloud simulation programs. Techniques include postprocessing the output of a simulation code to predict the RFA response; and incorporating an RFA model into the cloud modeling program itself.

Assessing cloud radiative effects on tropospheric photolysis rates and key oxidants during aircraft campaigns using satellite cloud observations and a global chemical transport model

NASA Astrophysics Data System (ADS)

Zhang, B.; Liu, H.; Crawford, J. H.; Chen, G.; Voulgarakis, A.; Fairlie, T. D.; Duncan, B. N.; Ham, S. H.; Kato, S.; Payer Sulprizio, M.; Yantosca, R.

2017-12-01

Clouds affect tropospheric photochemistry through modifying solar radiation that determines photolysis rates. Observational and modeling studies have indicated that photolysis rates are enhanced above and in the upper portion of cloud layers and are reduced below optically thick clouds due to their dominant backscattering effect. However, large uncertainties exist in the representation of cloud spatiotemporal (especially vertical) distributions in global models, which makes understanding of cloud radiative effects on tropospheric chemistry challenging. Our previous study using a global 3-D chemical transport model (GEOS-Chem) driven by various meteorological data sets showed that the radiative effects of clouds on photochemistry are more sensitive to the differences in the vertical distribution of clouds than to those in the magnitude of column cloud optical depths. In this work, we evaluate monthly mean cloud optical properties and distributions in the MERRA-2 reanalysis with those in C3M, a 3-D cloud data product developed at NASA Langley Research Center and merged from multiple A-Train satellite (CERES, CloudSat, CALIPSO, and MODIS) observations. We conduct tropospheric chemistry simulations for the periods of several aircraft campaigns, including ARCTAS (April, June-July, 2008), DC3 (May-June, 2012), and SEAC4RS (August-September, 2013) with GEOS-Chem driven by MERRA-2. We compare model simulations with and without constraints of cloud optical properties and distributions from C3M, and evaluate model photolysis rates (J[O1D] and J[NO2]) and key oxidants (e.g., OH and ozone) with aircraft profile measurements. We will assess whether the constraints provided by C3M improve model simulations of photolysis rates and oxidants as well as their variabilities.

Evaluating the cloud radiative forcing over East Asia during summer simulated by CMIP5 models

NASA Astrophysics Data System (ADS)

Lin, Z.; Wang, Y.; Liu, X.

2017-12-01

A large degree of uncertainty in global climate models (GCMs) can be attributed to the representation of clouds and its radiative forcing (CRF). In this study, the simulated CRFs, total cloud fraction (CF) and cloud properties over East Asia from 20 CMIP5 AMIP models are evaluated and compared with multiple satellite observations, and the possible causes for the CRF bias in the CMIP5 models are then investigated. Based on the satellite observation, strong Long wave CRF (LWCRF) and Short wave CRF (SWCRF) are found to be located over Southwestern China, with minimum SWCRF less than -130Wm-2 and this is associated with the large amount of cloud in the region. By contrast, weak CRFs are located over Northwest China and Western Pacific region because of less cloud amount. In Northeastern China, the strong SWCRF and week LWCRF can be found due to the dominant low-level cloud. In Eastern China, the CRFs is moderate due to the co-existence of the multi-layer cloud. CMIP5 models can basically capture the structure of CRFs in East Asia, with the spatial correlation coefficient between 0.5 and 0.9. But most models underestimate CRFs in East Asia, which is highly associated with the underestimation of cloud amount in the region. The performance of CMIP5 models varies in different part of East Asian region, with a larger deviation in Eastern China (EC). Further investigation suggests that, underestimation of the cloud amount in EC can lead to the weak bias of CRFs in EC, however, this CRF bias can be cancelled out by the overestimation effect of CRF due to excessive cloud optical depth (COD) simulated by the models. The annual cycle of simulated CRF over Eastern China is also examined, and it is found, CMIP models are unable to reproduce the northward migration of CRF in summer monsoon season, which is closely related with northward shift of East Asian summer monsoon rain belt.

Comparisons of Mixed-Phase Icing Cloud Simulations with Experiments Conducted at the NASA Propulsion Systems Laboratory

NASA Technical Reports Server (NTRS)

Bartkus, Tadas P.; Struk, Peter M.; Tsao, Jen-Ching

2017-01-01

This paper builds on previous work that compares numerical simulations of mixed-phase icing clouds with experimental data. The model couples the thermal interaction between ice particles and water droplets of the icing cloud with the flowing air of an icing wind tunnel for simulation of NASA Glenn Research Centers (GRC) Propulsion Systems Laboratory (PSL). Measurements were taken during the Fundamentals of Ice Crystal Icing Physics Tests at the PSL tunnel in March 2016. The tests simulated ice-crystal and mixed-phase icing that relate to ice accretions within turbofan engines. Experimentally measured air temperature, humidity, total water content, liquid and ice water content, as well as cloud particle size, are compared with model predictions. The model showed good trend agreement with experimentally measured values, but often over-predicted aero-thermodynamic changes. This discrepancy is likely attributed to radial variations that this one-dimensional model does not address. One of the key findings of this work is that greater aero-thermodynamic changes occur when humidity conditions are low. In addition a range of mixed-phase clouds can be achieved by varying only the tunnel humidity conditions, but the range of humidities to generate a mixed-phase cloud becomes smaller when clouds are composed of smaller particles. In general, the model predicted melt fraction well, in particular with clouds composed of larger particle sizes.

Simulation of the brightness temperatures observed by the visible infrared imaging radiometer suite instrument

NASA Astrophysics Data System (ADS)

Evrard, Rebecca L.; Ding, Yifeng

2018-01-01

Clouds play a large role in the Earth's global energy budget, but the impact of cirrus clouds is still widely questioned and researched. Cirrus clouds reside high in the atmosphere and due to cold temperatures are comprised of ice crystals. Gaining a better understanding of ice cloud optical properties and the distribution of cirrus clouds provides an explanation for the contribution of cirrus clouds to the global energy budget. Using radiative transfer models (RTMs), accurate simulations of cirrus clouds can enhance the understanding of the global energy budget as well as improve the use of global climate models. A newer, faster RTM such as the visible infrared imaging radiometer suite (VIIRS) fast radiative transfer model (VFRTM) is compared to a rigorous RTM such as the line-by-line radiative transfer model plus the discrete ordinates radiative transfer program. By comparing brightness temperature (BT) simulations from both models, the accuracy of the VFRTM can be obtained. This study shows root-mean-square error <0.2 K for BT difference using reanalysis data for atmospheric profiles and updated ice particle habit information from the moderate-resolution imaging spectroradiometer collection 6. At a higher resolution, the simulated results of the VFRTM are compared to the observations of VIIRS resulting in a <1.5 % error from the VFRTM for all cases. The VFRTM is validated and is an appropriate RTM to use for global cloud retrievals.

Tradeoffs in Acceleration and Initialization of Superparameterized Global Atmospheric Models for MJO and Climate Science

NASA Astrophysics Data System (ADS)

Pritchard, M. S.; Bretherton, C. S.; DeMott, C. A.

2014-12-01

New trade-offs are discussed in the cloud superparameterization approach to explicitly representing deep convection in global climate models. Intrinsic predictability tests show that the memory of cloud-resolving-scale organization is not critical for producing desired modes of organized convection such as the Madden-Julian Oscillation (MJO). This has implications for the feasibility of data assimilation and real-world initialization for superparameterized weather forecasting. Climate simulation sensitivity tests demonstrate that 400% acceleration of cloud superparameterization is possible by restricting the 32-128 km scale regime without deteriorating the realism of the simulated MJO but the number of cloud resolving model grid columns is discovered to constrain the efficiency of vertical mixing, with consequences for the simulated liquid cloud climatology. Tuning opportunities for next generation accelerated superparameterized climate models are discussed.

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium- and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Ni o) and March 2000 (weak La Ni a). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category. It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation. Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud top height while it overestimates the differences in the observed outgoing longwave radiation and cloud top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and in space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems.

Simulating the Effects of Semivolatile Compounds on Cloud Processing of Aerosol

NASA Astrophysics Data System (ADS)

Kokkola, H.; Kudzotsa, I.; Tonttila, J.; Raatikainen, T.; Romakkaniemi, S.

2017-12-01

Aerosol removal processes largely dictate how well aerosol is transported in the atmosphere and thus the aerosol load over remote regions depends on how effectively aerosol is removed during its transport from the source regions. This means that in order to model the global distribution aerosol, both in vertical and horizontal, wet deposition processes have to be properly modelled. However, in large scale models, the description of wet removal and the vertical redistribution of aerosol by cloud processes is often extremely simplified.Here we present a novel aerosol-cloud model SALSA, where the aerosol properties are tracked through different cloud processes. These processes include: cloud droplet activation, precipitation formation, ice nucleation, melting, and evaporation. It is a sectional model that includes separate size sections for non-activated aerosol, cloud droplets, precipitation droplets, and ice crystals. The aerosol-cloud model was coupled to a large eddy model UCLALES which simulates the boundary-layer dynamics. In this study, the model has been applied in studying the wet removal as well as interactions between aerosol, clouds, and semi-volatile compounds, ammonia and nitric acid. These semi-volative compounds are special in the sense that they co-condense together with water during cloud activation and have been suggested to form droplets that can be considered cloud-droplet-like already in subsaturated conditions. In our model, we calculate the kinetic partitioning of ammonia and sulfate thus explicitly taking into account the effect of ammonia and nitric acid in the cloud formation. Our simulations indicate that especially in polluted conditions, these compounds significantly affect the properties of cloud droplets thus significantly affecting the lifecycle of different aerosol compounds.

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

NASA Astrophysics Data System (ADS)

Zhou, Cheng; Penner, Joyce E.

2017-01-01

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

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

Penner, Joyce E.; Zhou, Cheng

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks

NASA Astrophysics Data System (ADS)

Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.

2017-12-01

Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.

Using the Atmospheric Radiation Measurement (ARM) Datasets to Evaluate Climate Models in Simulating Diurnal and Seasonal Variations of Tropical Clouds

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

Wang, Hailong; Burleyson, Casey D.; Ma, Po-Lun

We use the long-term Atmospheric Radiation Measurement (ARM) datasets collected at the three Tropical Western Pacific (TWP) sites as a tropical testbed to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. We conducted a series of CAM5 simulations at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean totalmore » cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in the frequency of ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m-2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, feedback on clouds. Both the CAM5 model and ARM observations show distinct diurnal cycles in total, stratiform and convective cloud fractions; however, they are out-of-phase by 12 hours and the biases vary by site. Our results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. We also found that the modelled gridmean surface longwave fluxes are systematically larger than site measurements when the grid that the ARM sites reside in is partially covered by ocean. The modeled longwave fluxes at such sites also lack a discernable diurnal cycle because the ocean part of the grid is warmer and less sensitive to radiative heating/cooling compared to land. Higher spatial resolution is more helpful is this regard. Our testbed approach can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional model simulations at high spatial resolutions.« less

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

NASA Astrophysics Data System (ADS)

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

2010-04-01

Anthropogenic aerosols serve as a source of both cloud condensation nuclei (CCN) and ice nuclei (IN) and affect microphysical properties of clouds. Increasing aerosol number concentrations is hypothesized to retard the cloud droplet collision/coalescence and the riming in mixed-phase clouds, thereby decreasing orographic precipitation. This study presents results from a model intercomparison of 2-D simulations of aerosol-cloud-precipitation interactions in stratiform orographic mixed-phase clouds. The sensitivity of orographic precipitation to changes in the aerosol number concentrations is analyzed and compared for various dynamical and thermodynamical situations. Furthermore, the sensitivities of microphysical processes such as collision/coalescence, aggregation and riming to changes in the aerosol number concentrations are evaluated and compared. The participating models are the Consortium for Small-Scale Modeling's (COSMO) model with bulk-microphysics, the Weather Research and Forecasting (WRF) model with bin-microphysics and the University of Wisconsin modeling system (UWNMS) with a spectral ice-habit prediction microphysics scheme. All models are operated on a cloud-resolving scale with 2 km horizontal grid spacing. The results of the model intercomparison suggest that the sensitivity of orographic precipitation to aerosol modifications varies greatly from case to case and from model to model. Neither a precipitation decrease nor a precipitation increase is found robustly in all simulations. Qualitative robust results can only be found for a subset of the simulations but even then quantitative agreement is scarce. Estimates of the second indirect aerosol effect on orographic precipitation are found to range from -19% to 0% depending on the simulated case and the model. Similarly, riming is shown to decrease in some cases and models whereas it increases in others which implies that a decrease in riming with increasing aerosol load is not a robust result. Furthermore, it is found that neither a decrease in cloud droplet coalescence nor a decrease in riming necessarily implies a decrease in precipitation due to compensation effects by other microphysical pathways. The simulations suggest that mixed-phase conditions play an important role in reducing the overall susceptibility of clouds and precipitation with respect to changes in the aerosols number concentrations. As a consequence the indirect aerosol effect on precipitation is suggested to be less pronounced or even inverted in regions with high terrain (e.g., the Alps or Rocky Mountains) or in regions where mixed-phase microphysics climatologically plays an important role for orographic precipitation.

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

NASA Technical Reports Server (NTRS)

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

2003-01-01

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

A Study of the Response of Deep Tropical Clouds to Mesoscale Processes. Part 1; Modeling Strategies and Simulations of TOGA-COARE 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.

Evaluation of NASA GISS post-CMIP5 single column model simulated clouds and precipitation using ARM Southern Great Plains observations

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.

Aerosol processing in mixed-phase clouds in ECHAM5-HAM: Model description and comparison to observations

NASA Astrophysics Data System (ADS)

Hoose, C.; Lohmann, U.; Stier, P.; Verheggen, B.; Weingartner, E.

2008-04-01

The global aerosol-climate model ECHAM5-HAM has been extended by an explicit treatment of cloud-borne particles. Two additional modes for in-droplet and in-crystal particles are introduced, which are coupled to the number of cloud droplet and ice crystal concentrations simulated by the ECHAM5 double-moment cloud microphysics scheme. Transfer, production, and removal of cloud-borne aerosol number and mass by cloud droplet activation, collision scavenging, aqueous-phase sulfate production, freezing, melting, evaporation, sublimation, and precipitation formation are taken into account. The model performance is demonstrated and validated with observations of the evolution of total and interstitial aerosol concentrations and size distributions during three different mixed-phase cloud events at the alpine high-altitude research station Jungfraujoch (Switzerland). Although the single-column simulations cannot be compared one-to-one with the observations, the governing processes in the evolution of the cloud and aerosol parameters are captured qualitatively well. High scavenged fractions are found during the presence of liquid water, while the release of particles during the Bergeron-Findeisen process results in low scavenged fractions after cloud glaciation. The observed coexistence of liquid and ice, which might be related to cloud heterogeneity at subgrid scales, can only be simulated in the model when assuming nonequilibrium conditions.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

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

Evans, Stuart; Marchand, Roger; Ackerman, Thomas

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

NASA Astrophysics Data System (ADS)

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; Donner, Leo; Golaz, Jean-Christophe; Seman, Charles

2017-12-01

We define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, and high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. We find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.

Diagnosing Cloud Biases in the GFDL AM3 Model With Atmospheric Classification

DOE PAGES

Evans, Stuart; Marchand, Roger; Ackerman, Thomas; ...

2017-11-16

In this paper, we define a set of 21 atmospheric states, or recurring weather patterns, for a region surrounding the Atmospheric Radiation Measurement Program's Southern Great Plains site using an iterative clustering technique. The states are defined using dynamic and thermodynamic variables from reanalysis, tested for statistical significance with cloud radar data from the Southern Great Plains site, and are determined every 6 h for 14 years, creating a time series of atmospheric state. The states represent the various stages of the progression of synoptic systems through the region (e.g., warm fronts, warm sectors, cold fronts, cold northerly advection, andmore » high-pressure anticyclones) with a subset of states representing summertime conditions with varying degrees of convective activity. We use the states to classify output from the NOAA/Geophysical Fluid Dynamics Laboratory AM3 model to test the model's simulation of the frequency of occurrence of the states and of the cloud occurrence during each state. The model roughly simulates the frequency of occurrence of the states but exhibits systematic cloud occurrence biases. Comparison of observed and model-simulated International Satellite Cloud Climatology Project histograms of cloud top pressure and optical thickness shows that the model lacks high thin cloud under all conditions, but biases in thick cloud are state-dependent. Frontal conditions in the model do not produce enough thick cloud, while fair-weather conditions produce too much. Finally, we find that increasing the horizontal resolution of the model improves the representation of thick clouds under all conditions but has little effect on high thin clouds. However, increasing resolution also changes the distribution of states, causing an increase in total cloud occurrence bias.« less

Microphysics of Clouds with the Relaxed Arakawa-Schubert Scheme (McRAS). Part I: Design and Evaluation with GATE Phase III Data.

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).

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

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.

The Cloud Feedback Model Intercomparison Project Observational Simulator Package: Version 2

NASA Astrophysics Data System (ADS)

Swales, Dustin J.; Pincus, Robert; Bodas-Salcedo, Alejandro

2018-01-01

The Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) gathers together a collection of observation proxies or satellite simulators that translate model-simulated cloud properties to synthetic observations as would be obtained by a range of satellite observing systems. This paper introduces COSP2, an evolution focusing on more explicit and consistent separation between host model, coupling infrastructure, and individual observing proxies. Revisions also enhance flexibility by allowing for model-specific representation of sub-grid-scale cloudiness, provide greater clarity by clearly separating tasks, support greater use of shared code and data including shared inputs across simulators, and follow more uniform software standards to simplify implementation across a wide range of platforms. The complete package including a testing suite is freely available.

A Single-column Model Ensemble Approach Applied to the TWP-ICE Experiment

NASA Technical Reports Server (NTRS)

Davies, L.; Jakob, C.; Cheung, K.; DelGenio, A.; Hill, A.; Hume, T.; Keane, R. J.; Komori, T.; Larson, V. E.; Lin, Y.;

A laboratory investigation of the variability of cloud reflected radiance fields

NASA Technical Reports Server (NTRS)

Mckee, T. B.; Cox, S. K.

1986-01-01

A method to determine the radiative properties of complex cloud fields was developed. A Cloud field optical simulator (CFOS) was constructed to simulate the interaction of cloud fields with visible radiation. The CFOS was verified by comparing experimental results from it with calculations performed with a Monte Carlo radiative transfer model. A software library was developed to process, reduce, and display CFOS data. The CFSOS was utilized to study the reflected radiane patterns from simulated cloud fields.

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.

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.

Laboratory simulations show diabatic heating drives cumulus-cloud evolution and entrainment

PubMed Central

Narasimha, Roddam; Diwan, Sourabh Suhas; Duvvuri, Subrahmanyam; Sreenivas, K. R.; Bhat, G. S.

2011-01-01

Clouds are the largest source of uncertainty in climate science, and remain a weak link in modeling tropical circulation. A major challenge is to establish connections between particulate microphysics and macroscale turbulent dynamics in cumulus clouds. Here we address the issue from the latter standpoint. First we show how to create bench-scale flows that reproduce a variety of cumulus-cloud forms (including two genera and three species), and track complete cloud life cycles—e.g., from a “cauliflower” congestus to a dissipating fractus. The flow model used is a transient plume with volumetric diabatic heating scaled dynamically to simulate latent-heat release from phase changes in clouds. Laser-based diagnostics of steady plumes reveal Riehl–Malkus type protected cores. They also show that, unlike the constancy implied by early self-similar plume models, the diabatic heating raises the Taylor entrainment coefficient just above cloud base, depressing it at higher levels. This behavior is consistent with cloud-dilution rates found in recent numerical simulations of steady deep convection, and with aircraft-based observations of homogeneous mixing in clouds. In-cloud diabatic heating thus emerges as the key driver in cloud development, and could well provide a major link between microphysics and cloud-scale dynamics. PMID:21918112

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

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.

Extension of four-dimensional atmospheric models. [and cloud cover data bank

NASA Technical Reports Server (NTRS)

Fowler, M. G.; Lisa, A. S.; Tung, S. L.

1975-01-01

The cloud data bank, the 4-D atmospheric model, and a set of computer programs designed to simulate meteorological conditions for any location above the earth are described in turns of space vehicle design and simulation of vehicle reentry trajectories. Topics discussed include: the relationship between satellite and surface observed cloud cover using LANDSAT 1 photographs and including the effects of cloud shadows; extension of the 4-D model to the altitude of 52 km; and addition of the u and v wind components to the 4-D model of means and variances at 1 km levels from the surface to 25 km. Results of the cloud cover analysis are presented along with the stratospheric model and the tropospheric wind profiles.

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

PubMed

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

2018-03-07

Aerosols affect climate by modifying cloud properties through their role as cloud condensation nuclei or ice nuclei, called aerosol-cloud interactions. In most global climate models (GCMs), the aerosol-cloud interactions are represented by empirical parameterisations, in which the mass of cloud liquid water (LWP) is assumed to increase monotonically with increasing aerosol loading. Recent satellite observations, however, have yielded contradictory results: LWP can decrease with increasing aerosol loading. This difference implies that GCMs overestimate the aerosol effect, but the reasons for the difference are not obvious. Here, we reproduce satellite-observed LWP responses using a global simulation with explicit representations of cloud microphysics, instead of the parameterisations. Our analyses reveal that the decrease in LWP originates from the response of evaporation and condensation processes to aerosol perturbations, which are not represented in GCMs. The explicit representation of cloud microphysics in global scale modelling reduces the uncertainty of climate prediction.

Techniques and resources for storm-scale numerical weather prediction

NASA Technical Reports Server (NTRS)

Droegemeier, Kelvin; Grell, Georg; Doyle, James; Soong, Su-Tzai; Skamarock, William; Bacon, David; Staniforth, Andrew; Crook, Andrew; Wilhelmson, Robert

1993-01-01

The topics discussed include the following: multiscale application of the 5th-generation PSU/NCAR mesoscale model, the coupling of nonhydrostatic atmospheric and hydrostatic ocean models for air-sea interaction studies; a numerical simulation of cloud formation over complex topography; adaptive grid simulations of convection; an unstructured grid, nonhydrostatic meso/cloud scale model; efficient mesoscale modeling for multiple scales using variable resolution; initialization of cloud-scale models with Doppler radar data; and making effective use of future computing architectures, networks, and visualization software.

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects

NASA Astrophysics Data System (ADS)

Gu, B.; Yang, P.; Kuo, C. P.; Mlawer, E. J.

2017-12-01

Evaluation of RRTMG and Fu-Liou RTM Performance against LBLRTM-DISORT Simulations and CERES Data in terms of Ice Clouds Radiative Effects Boyan Gu1, Ping Yang1, Chia-Pang Kuo1, Eli J. Mlawer2 Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA Atmospheric and Environmental Research (AER), Lexington, MA 02421, USA Ice clouds play an important role in climate system, especially in the Earth's radiation balance and hydrological cycle. However, the representation of ice cloud radiative effects (CRE) remains significant uncertainty, because scattering properties of ice clouds are not well considered in general circulation models (GCM). We analyze the strengths and weakness of the Rapid Radiative Transfer Model for GCM Applications (RRTMG) and Fu-Liou Radiative Transfer Model (RTM) against rigorous LBLRTM-DISORT (a combination of Line-By-Line Radiative Transfer Model and Discrete Ordinate Radiative Transfer Model) calculations and CERES (Clouds and the Earth's Radiant Energy System) flux observations. In total, 6 US standard atmospheric profiles and 42 atmospheric profiles from Atmospheric and Environmental Research (AER) Company are used to evaluate the RRTMG and Fu-Liou RTM by LBLRTM-DISORT calculations from 0 to 3250 cm-1. Ice cloud radiative effect simulations with RRTMG and Fu-Liou RTM are initialized using the ice cloud properties from MODIS collection-6 products. Simulations of single layer ice cloud CRE by RRTMG and LBLRTM-DISORT show that RRTMG, neglecting scattering, overestimates the TOA flux by about 0-15 W/m2 depending on the cloud particle size and optical depth, and the most significant overestimation occurs when the particle effective radius is small (around 10 μm) and the cloud optical depth is intermediate (about 1-10). The overestimation reduces significantly when the similarity rule is applied to RRTMG. We combine ice cloud properties from MODIS Collection-6 and atmospheric profiles from the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) reanalysis to simulate ice cloud CRE, which is compared with CERES observations.

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

NASA Astrophysics Data System (ADS)

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

2010-09-01

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

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

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

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

DOE PAGES

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

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.

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

USDA-ARS?s Scientific Manuscript database

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

Evaluation of Cloud Microphysics in JMA-NHM Simulations Using Bin or Bulk Microphysical Schemes through Comparison with Cloud Radar Observations

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.

Evaluating rainfall errors in global climate models through cloud regimes

NASA Astrophysics Data System (ADS)

Tan, Jackson; Oreopoulos, Lazaros; Jakob, Christian; Jin, Daeho

2017-07-01

Global climate models suffer from a persistent shortcoming in their simulation of rainfall by producing too much drizzle and too little intense rain. This erroneous distribution of rainfall is a result of deficiencies in the representation of underlying processes of rainfall formation. In the real world, clouds are precursors to rainfall and the distribution of clouds is intimately linked to the rainfall over the area. This study examines the model representation of tropical rainfall using the cloud regime concept. In observations, these cloud regimes are derived from cluster analysis of joint-histograms of cloud properties retrieved from passive satellite measurements. With the implementation of satellite simulators, comparable cloud regimes can be defined in models. This enables us to contrast the rainfall distributions of cloud regimes in 11 CMIP5 models to observations and decompose the rainfall errors by cloud regimes. Many models underestimate the rainfall from the organized convective cloud regime, which in observation provides half of the total rain in the tropics. Furthermore, these rainfall errors are relatively independent of the model's accuracy in representing this cloud regime. Error decomposition reveals that the biases are compensated in some models by a more frequent occurrence of the cloud regime and most models exhibit substantial cancellation of rainfall errors from different regimes and regions. Therefore, underlying relatively accurate total rainfall in models are significant cancellation of rainfall errors from different cloud types and regions. The fact that a good representation of clouds does not lead to appreciable improvement in rainfall suggests a certain disconnect in the cloud-precipitation processes of global climate models.

Can CFMIP2 models reproduce the leading modes of cloud vertical structure in the CALIPSO-GOCCP observations?

NASA Astrophysics Data System (ADS)

Wang, Fang; Yang, Song

2018-02-01

Using principal component (PC) analysis, three leading modes of cloud vertical structure (CVS) are revealed by the GCM-Oriented CALIPSO Cloud Product (GOCCP), i.e. tropical high, subtropical anticyclonic and extratropical cyclonic cloud modes (THCM, SACM and ECCM, respectively). THCM mainly reflect the contrast between tropical high clouds and clouds in middle/high latitudes. SACM is closely associated with middle-high clouds in tropical convective cores, few-cloud regimes in subtropical anticyclonic clouds and stratocumulus over subtropical eastern oceans. ECCM mainly corresponds to clouds along extratropical cyclonic regions. Models of phase 2 of Cloud Feedback Model Intercomparison Project (CFMIP2) well reproduce the THCM, but SACM and ECCM are generally poorly simulated compared to GOCCP. Standardized PCs corresponding to CVS modes are generally captured, whereas original PCs (OPCs) are consistently underestimated (overestimated) for THCM (SACM and ECCM) by CFMIP2 models. The effects of CVS modes on relative cloud radiative forcing (RSCRF/RLCRF) (RSCRF being calculated at the surface while RLCRF at the top of atmosphere) are studied in terms of principal component regression method. Results show that CFMIP2 models tend to overestimate (underestimated or simulate the opposite sign) RSCRF/RLCRF radiative effects (REs) of ECCM (THCM and SACM) in unit global mean OPC compared to observations. These RE biases may be attributed to two factors, one of which is underestimation (overestimation) of low/middle clouds (high clouds) (also known as stronger (weaker) REs in unit low/middle (high) clouds) in simulated global mean cloud profiles, the other is eigenvector biases in CVS modes (especially for SACM and ECCM). It is suggested that much more attention should be paid on improvement of CVS, especially cloud parameterization associated with particular physical processes (e.g. downwelling regimes with the Hadley circulation, extratropical storm tracks and others), which may be crucial to reduce the CRF biases in current climate models.

The diurnal cycle of clouds and precipitation at the ARM SGP site: Cloud radar observations and simulations from the multiscale modeling framework

DOE PAGES

Zhao, Wei; Marchand, Roger; Fu, Qiang

2017-07-08

Millimeter Wavelength Cloud Radar (MMCR) data from December 1996 to December 2010, collected at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site, are used to examine the diurnal cycle of hydrometeor occurrence. These data are categorized into clouds (-40 dBZ e ≤ reflectivity < -10 dBZ e), drizzle and light precipitation (-10 dBZ e ≤ reflectivity < 10 dBZ e), and heavy precipitation (reflectivity ≥ 10 dBZ e). The same criteria are implemented for the observation-equivalent reflectivity calculated by feeding outputs from a Multiscale Modeling Framework (MMF) climate model into a radar simulator.more » The MMF model consists of the National Center for Atmospheric Research Community Atmosphere Model with conventional cloud parameterizations replaced by a cloud-resolving model. We find that a radar simulator combined with the simple reflectivity categories can be an effective approach for evaluating diurnal variations in model hydrometeor occurrence. It is shown that the MMF only marginally captures observed increases in the occurrence of boundary layer clouds after sunrise in spring and autumn and does not capture diurnal changes in boundary layer clouds during the summer. Above the boundary layer, the MMF captures reasonably well diurnal variations in the vertical structure of clouds and light and heavy precipitation in the summer but not in the spring.« less

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

NASA Technical Reports Server (NTRS)

Tao, W-K.

2003-01-01

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

Realistic natural atmospheric phenomena and weather effects for interactive virtual environments

NASA Astrophysics Data System (ADS)

McLoughlin, Leigh

Clouds and the weather are important aspects of any natural outdoor scene, but existing dynamic techniques within computer graphics only offer the simplest of cloud representations. The problem that this work looks to address is how to provide a means of simulating clouds and weather features such as precipitation, that are suitable for virtual environments. Techniques for cloud simulation are available within the area of meteorology, but numerical weather prediction systems are computationally expensive, give more numerical accuracy than we require for graphics and are restricted to the laws of physics. Within computer graphics, we often need to direct and adjust physical features or to bend reality to meet artistic goals, which is a key difference between the subjects of computer graphics and physical science. Pure physically-based simulations, however, evolve their solutions according to pre-set rules and are notoriously difficult to control. The challenge then is for the solution to be computationally lightweight and able to be directed in some measure while at the same time producing believable results. This work presents a lightweight physically-based cloud simulation scheme that simulates the dynamic properties of cloud formation and weather effects. The system simulates water vapour, cloud water, cloud ice, rain, snow and hail. The water model incorporates control parameters and the cloud model uses an arbitrary vertical temperature profile, with a tool described to allow the user to define this. The result of this work is that clouds can now be simulated in near real-time complete with precipitation. The temperature profile and tool then provide a means of directing the resulting formation..

Performance Analysis of Cloud Computing Architectures Using Discrete Event Simulation

NASA Technical Reports Server (NTRS)

Stocker, John C.; Golomb, Andrew M.

2011-01-01

Cloud computing offers the economic benefit of on-demand resource allocation to meet changing enterprise computing needs. However, the flexibility of cloud computing is disadvantaged when compared to traditional hosting in providing predictable application and service performance. Cloud computing relies on resource scheduling in a virtualized network-centric server environment, which makes static performance analysis infeasible. We developed a discrete event simulation model to evaluate the overall effectiveness of organizations in executing their workflow in traditional and cloud computing architectures. The two part model framework characterizes both the demand using a probability distribution for each type of service request as well as enterprise computing resource constraints. Our simulations provide quantitative analysis to design and provision computing architectures that maximize overall mission effectiveness. We share our analysis of key resource constraints in cloud computing architectures and findings on the appropriateness of cloud computing in various applications.

From large-eddy simulation to multi-UAVs sampling of shallow cumulus clouds

NASA Astrophysics Data System (ADS)

Lamraoui, Fayçal; Roberts, Greg; Burnet, Frédéric

2016-04-01

In-situ sampling of clouds that can provide simultaneous measurements at satisfying spatio-temporal resolutions to capture 3D small scale physical processes continues to present challenges. This project (SKYSCANNER) aims at bringing together cloud sampling strategies using a swarm of unmanned aerial vehicles (UAVs) based on Large-eddy simulation (LES). The multi-UAV-based field campaigns with a personalized sampling strategy for individual clouds and cloud fields will significantly improve the understanding of the unresolved cloud physical processes. An extensive set of LES experiments for case studies from ARM-SGP site have been performed using MesoNH model at high resolutions down to 10 m. The carried out simulations led to establishing a macroscopic model that quantifies the interrelationship between micro- and macrophysical properties of shallow convective clouds. Both the geometry and evolution of individual clouds are critical to multi-UAV cloud sampling and path planning. The preliminary findings of the current project reveal several linear relationships that associate many cloud geometric parameters to cloud related meteorological variables. In addition, the horizontal wind speed indicates a proportional impact on cloud number concentration as well as triggering and prolonging the occurrence of cumulus clouds. In the framework of the joint collaboration that involves a Multidisciplinary Team (including institutes specializing in aviation, robotics and atmospheric science), this model will be a reference point for multi-UAVs sampling strategies and path planning.

Evaluation of a Cloud Resolving Model Using TRMM Observations for Multiscale Modeling Applications

NASA Technical Reports Server (NTRS)

Posselt, Derek J.; L'Ecuyer, Tristan; Tao, Wei-Kuo; Hou, Arthur Y.; Stephens, Graeme L.

2007-01-01

The climate change simulation community is moving toward use of global cloud resolving models (CRMs), however, current computational resources are not sufficient to run global CRMs over the hundreds of years necessary to produce climate change estimates. As an intermediate step between conventional general circulation models (GCMs) and global CRMs, many climate analysis centers are embedding a CRM in each grid cell of a conventional GCM. These Multiscale Modeling Frameworks (MMFs) represent a theoretical advance over the use of conventional GCM cloud and convection parameterizations, but have been shown to exhibit an overproduction of precipitation in the tropics during the northern hemisphere summer. In this study, simulations of clouds, precipitation, and radiation over the South China Sea using the CRM component of the NASA Goddard MMF are evaluated using retrievals derived from the instruments aboard the Tropical Rainfall Measuring Mission (TRMM) satellite platform for a 46-day time period that spans 5 May - 20 June 1998. The NASA Goddard Cumulus Ensemble (GCE) model is forced with observed largescale forcing derived from soundings taken during the intensive observing period of the South China Sea Monsoon Experiment. It is found that the GCE configuration used in the NASA Goddard MMF responds too vigorously to the imposed large-scale forcing, accumulating too much moisture and producing too much cloud cover during convective phases, and overdrying the atmosphere and suppressing clouds during monsoon break periods. Sensitivity experiments reveal that changes to ice cloud microphysical parameters have a relatively large effect on simulated clouds, precipitation, and radiation, while changes to grid spacing and domain length have little effect on simulation results. The results motivate a more detailed and quantitative exploration of the sources and magnitude of the uncertainty associated with specified cloud microphysical parameters in the CRM components of MMFs.

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

DOE PAGES

Zhou, Cheng; Penner, Joyce E.

2017-01-02

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

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

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

Zhou, Cheng; Penner, Joyce E.

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

A Madden-Julian oscillation event realistically simulated by a global cloud-resolving model.

PubMed

Miura, Hiroaki; Satoh, Masaki; Nasuno, Tomoe; Noda, Akira T; Oouchi, Kazuyoshi

2007-12-14

A Madden-Julian Oscillation (MJO) is a massive weather event consisting of deep convection coupled with atmospheric circulation, moving slowly eastward over the Indian and Pacific Oceans. Despite its enormous influence on many weather and climate systems worldwide, it has proven very difficult to simulate an MJO because of assumptions about cumulus clouds in global meteorological models. Using a model that allows direct coupling of the atmospheric circulation and clouds, we successfully simulated the slow eastward migration of an MJO event. Topography, the zonal sea surface temperature gradient, and interplay between eastward- and westward-propagating signals controlled the timing of the eastward transition of the convective center. Our results demonstrate the potential making of month-long MJO predictions when global cloud-resolving models with realistic initial conditions are used.

Comparison of tropical cyclogenesis processes in climate model and cloud-resolving model simulations using moist static energy budget analysis

NASA Astrophysics Data System (ADS)

Wing, Allison; Camargo, Suzana; Sobel, Adam; Kim, Daehyun; Murakami, Hiroyuki; Reed, Kevin; Vecchi, Gabriel; Wehner, Michael; Zarzycki, Colin; Zhao, Ming

2017-04-01

In recent years, climate models have improved such that high-resolution simulations are able to reproduce the climatology of tropical cyclone activity with some fidelity and show some skill in seasonal forecasting. However biases remain in many models, motivating a better understanding of what factors control the representation of tropical cyclone activity in climate models. We explore the tropical cyclogenesis processes in five high-resolution climate models, including both coupled and uncoupled configurations. Our analysis framework focuses on how convection, moisture, clouds and related processes are coupled and employs budgets of column moist static energy and the spatial variance of column moist static energy. The latter was originally developed to study the mechanisms of tropical convective organization in idealized cloud-resolving models, and allows us to quantify the different feedback processes responsible for the amplification of moist static energy anomalies associated with the organization of convection and cyclogenesis. We track the formation and evolution of tropical cyclones in the climate model simulations and apply our analysis both along the individual tracks and composited over many tropical cyclones. We then compare the genesis processes; in particular, the role of cloud-radiation interactions, to those of spontaneous tropical cyclogenesis in idealized cloud-resolving model simulations.

Numerical simulation of cloud and precipitation structure during GALE IOP-2

NASA Technical Reports Server (NTRS)

Robertson, F. R.; Perkey, D. J.; Seablom, M. S.

1988-01-01

A regional scale model, LAMPS (Limited Area Mesoscale Prediction System), is used to investigate cloud and precipitation structure that accompanied a short wave system during a portion of GALE IOP-2. A comparison of satellite imagery and model fields indicates that much of the large mesoscale organization of condensation has been captured by the simulation. In addition to reproducing a realistic phasing of two baroclinic zones associated with a split cold front, a reasonable simulation of the gross mesoscale cloud distribution has been achieved.

GCSS Idealized Cirrus Model Comparison Project

NASA Technical Reports Server (NTRS)

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

Importance of including ammonium sulfate ((NH4)2SO4) aerosols for ice cloud parameterization in GCMs

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

Bhattacharjee, P. S.; Sud, Yogesh C.; Liu, Xiaohong

2010-02-22

A common deficiency of many cloud-physics parameterizations including the NASA’s microphysics of clouds with aerosol- cloud interactions (hereafter called McRAS-AC) is that they simulate less (larger) than the observed ice cloud particle number (size). A single column model (SCM) of McRAS-AC and Global Circulation Model (GCM) physics together with an adiabatic parcel model (APM) for ice-cloud nucleation (IN) of aerosols were used to systematically examine the influence of ammonium sulfate ((NH4)2SO4) aerosols, not included in the present formulations of McRAS-AC. Specifically, the influence of (NH4)2SO4 aerosols on the optical properties of both liquid and ice clouds were analyzed. First anmore » (NH4)2SO4 parameterization was included in the APM to assess its effect vis-à-vis that of the other aerosols. Subsequently, several evaluation tests were conducted over the ARM-SGP and thirteen other locations (sorted into pristine and polluted conditions) distributed over marine and continental sites with the SCM. The statistics of the simulated cloud climatology were evaluated against the available ground and satellite data. The results showed that inclusion of (NH4)2SO4 in the SCM made a remarkable improvement in the simulated effective radius of ice clouds. However, the corresponding ice-cloud optical thickness increased more than is observed. This can be caused by lack of cloud advection and evaporation. We argue that this deficiency can be mitigated by adjusting the other tunable parameters of McRAS-AC such as precipitation efficiency. Inclusion of ice cloud particle splintering introduced through well- established empirical equations is found to further improve the results. Preliminary tests show that these changes make a substantial improvement in simulating the cloud optical properties in the GCM, particularly by simulating a far more realistic cloud distribution over the ITCZ.« less

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

NASA Technical Reports Server (NTRS)

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

An ARM data-oriented diagnostics package to evaluate the climate model simulation

NASA Astrophysics Data System (ADS)

Zhang, C.; Xie, S.

2016-12-01

A set of diagnostics that utilize long-term high frequency measurements from the DOE Atmospheric Radiation Measurement (ARM) program is developed for evaluating the regional simulation of clouds, radiation and precipitation in climate models. The diagnostics results are computed and visualized automatically in a python-based package that aims to serve as an easy entry point for evaluating climate simulations using the ARM data, as well as the CMIP5 multi-model simulations. Basic performance metrics are computed to measure the accuracy of mean state and variability of simulated regional climate. The evaluated physical quantities include vertical profiles of clouds, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, radiative fluxes, aerosol and cloud microphysical properties. Process-oriented diagnostics focusing on individual cloud and precipitation-related phenomena are developed for the evaluation and development of specific model physical parameterizations. Application of the ARM diagnostics package will be presented in the AGU session. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344, IM release number is: LLNL-ABS-698645.

CGILS: Results from the First Phase of an International Project to Understand the Physical Mechanisms of Low Cloud Feedbacks in Single Column Models

NASA Technical Reports Server (NTRS)

Zhang, Minghua; Bretherton, Christopher S.; Blossey, Peter N.; Austin, Phillip H.; Bacmeister, Julio T.; Bony, Sandrine; Brient, Florent; Cheedela, Suvarchal K.; Cheng, Anning; DelGenio, Anthony;

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties

NASA Technical Reports Server (NTRS)

Stanfield, Ryan E.; Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Del Genio, Anthony D.; Minnia, Patrick; Jiang, Jonathan H.

2014-01-01

Although many improvements have been made in phase 5 of the Coupled Model Intercomparison Project (CMIP5), clouds remain a significant source of uncertainty in general circulation models (GCMs) because their structural and optical properties are strongly dependent upon interactions between aerosol/cloud microphysics and dynamics that are unresolved in such models. Recent changes to the planetary boundary layer (PBL) turbulence and moist convection parameterizations in the NASA GISS Model E2 atmospheric GCM(post-CMIP5, hereafter P5) have improved cloud simulations significantly compared to its CMIP5 (hereafter C5) predecessor. A study has been performed to evaluate these changes between the P5 and C5 versions of the GCM, both of which used prescribed sea surface temperatures. P5 and C5 simulated cloud fraction (CF), liquid water path (LWP), ice water path (IWP), cloud water path (CWP), precipitable water vapor (PWV), and relative humidity (RH) have been compared to multiple satellite observations including the Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectroradiometer (CERES-MODIS, hereafter CM), CloudSat- Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; hereafter CC), Atmospheric Infrared Sounder (AIRS), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Although some improvements are observed in the P5 simulation on a global scale, large improvements have been found over the southern midlatitudes (SMLs), where correlations increased and both bias and root-mean-square error (RMSE) significantly decreased, in relation to the previous C5 simulation, when compared to observations. Changes to the PBL scheme have resulted in improved total column CFs, particularly over the SMLs where marine boundary layer (MBL) CFs have increased by nearly 20% relative to the previous C5 simulation. Globally, the P5 simulated CWPs are 25 gm22 lower than the previous C5 results. The P5 version of the GCM simulates PWV and RH higher than its C5 counterpart and agrees well with the AMSR-E and AIRS observations. The moister atmospheric conditions simulated by P5 are consistent with the CF comparison and provide a strong support for the increase in MBL clouds over the SMLs. Over the tropics, the P5 version of the GCM simulated total column CFs and CWPs are slightly lower than the previous C5 results, primarily as a result of the shallower tropical boundary layer in P5 relative to C5 in regions outside the marine stratocumulus decks.

Analysis of the Diurnal Cycle of Precipitation and its Relation to Cloud Radiative Forcing Using TRMM Products

NASA Technical Reports Server (NTRS)

Randall, David A.; Fowler, Laura D.; Lin, Xin

1998-01-01

In order to improve our understanding of the interactions between clouds, radiation, and the hydrological cycle simulated in the Colorado State University General Circulation Model (CSU GCM), we focused our research on the analysis of the diurnal cycle of precipitation, top-of-the-atmosphere and surface radiation budgets, and cloudiness using 10-year long Atmospheric Model Intercomparison Project (AMIP) simulations. Comparisons the simulated diurnal cycle were made against the diurnal cycle of Earth Radiation Budget Experiment (ERBE) radiation budget and International Satellite Cloud Climatology Project (ISCCP) cloud products. This report summarizes our major findings over the Amazon Basin.

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.

Effects of Doubled CO2 on Tropical Sea-Surface Temperature (SSTs) for Onset of Deep Convection and Maximum SST-GCM Simulations Based Inferences

NASA Technical Reports Server (NTRS)

Sud, Y. C.; Walker, G. K.; Zhou, Y. P.; Schmidt, Gavin A.; Lau, K. M.; Cahalan, R. F.

2008-01-01

A primary concern of CO2-induced warming is the associated rise of tropical (10S-10N) seasurface temperatures (SSTs). GISS Model-E was used to produce two sets of simulations-one with the present-day and one with doubled CO2 in the atmosphere. The intrinsic usefulness of model guidance in the tropics was confirmed when the model simulated realistic convective coupling between SSTs and atmospheric soundings and that the simulated-data correlations between SSTs and 300 hPa moiststatic energies were found to be similar to the observed. Model predicted SST limits: (i) one for the onset of deep convection and (ii) one for maximum SST, increased in the doubled C02 case. Changes in cloud heights, cloud frequencies, and cloud mass-fractions showed that convective-cloud changes increased the SSTs, while warmer mixed-layer of the doubled CO2 contained approximately 10% more water vapor; clearly that would be conducive to more intense storms and hurricanes.

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

DOE PAGES

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

2017-10-24

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

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

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

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

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

Testing ice microphysics parameterizations in the NCAR Community Atmospheric Model Version 3 using Tropical Warm Pool-International Cloud Experiment data

DOE PAGES

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

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

DOE PAGES

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; ...

2017-01-01

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

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

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

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

Comparative evaluation of polarimetric and bi-spectral cloud microphysics retrievals: Retrieval closure experiments and comparisons based on idealized and LES case studies

NASA Astrophysics Data System (ADS)

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

2016-12-01

A remote sensing cloud retrieval simulator, created by coupling an LES cloud model with vector radiative transfer (RT) models is the ideal framework for assessing cloud remote sensing techniques. This simulator serves as a tool for understanding bi-spectral and polarimetric retrievals by comparing them directly to LES cloud properties (retrieval closure comparison) and for comparing the retrieval techniques to one another. Our simulator utilizes the DHARMA LES [Ackerman et al., 2004] with cloud properties based on marine boundary layer (MBL) clouds observed during the DYCOMS-II and ATEX field campaigns. The cloud reflectances are produced by the vectorized RT models based on polarized doubling adding and monte carlo techniques (PDA, MCPOL). Retrievals are performed utilizing techniques as similar as possible to those implemented on their corresponding well known instruments; polarimetric retrievals are based on techniques implemented for polarimeters (POLDER, AirMSPI, and RSP) and bi-spectral retrievals are performed using the Nakajima-King LUT method utilized on a number of spectral instruments (MODIS and VIIRS). Retrieval comparisons focus on cloud droplet effective radius (re), effective variance (ve), and cloud optical thickness (τ). This work explores the sensitivities of these two retrieval techniques to various observation limitations, such as spatial resolution/cloud inhomogeneity, impact of 3D radiative effects, and angular resolution requirements. With future remote sensing missions like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important to understand how these retrieval techniques compare to one another. The cloud retrieval simulator we've developed allows us to probe these important questions in a realistically relevant test bed.

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.

Near-Surface Meteorology During the Arctic Summer Cloud Ocean Study (ASCOS): Evaluation of Reanalyses and Global Climate Models.

NASA Technical Reports Server (NTRS)

De Boer, G.; Shupe, M.D.; Caldwell, P.M.; Bauer, Susanne E.; Persson, O.; Boyle, J.S.; Kelley, M.; Klein, S.A.; Tjernstrom, M.

2014-01-01

Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)- Interim reanalysis, National Center for Environmental Prediction (NCEP)-National Center for Atmospheric Research (NCAR) reanalysis, and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute for Space Studies) ModelE2) in simulation of the high Arctic environment. Quantities analyzed include near surface meteorological variables such as temperature, pressure, humidity and winds, surface-based estimates of cloud and precipitation properties, the surface energy budget, and lower atmospheric temperature structure. In general, the models perform well in simulating large-scale dynamical quantities such as pressure and winds. Near-surface temperature and lower atmospheric stability, along with surface energy budget terms, are not as well represented due largely to errors in simulation of cloud occurrence, phase and altitude. Additionally, a development version of CAM5, which features improved handling of cloud macro physics, has demonstrated to improve simulation of cloud properties and liquid water amount. The ASCOS period additionally provides an excellent example of the benefits gained by evaluating individual budget terms, rather than simply evaluating the net end product, with large compensating errors between individual surface energy budget terms that result in the best net energy budget.

RACORO continental boundary layer cloud investigations. 2. Large-eddy simulations of cumulus clouds and evaluation with in-situ and ground-based observations

DOE PAGES

Endo, Satoshi; Fridlind, Ann M.; Lin, Wuyin; ...

2015-06-19

A 60-hour case study of continental boundary layer cumulus clouds is examined using two large-eddy simulation (LES) models. The case is based on observations obtained during the RACORO Campaign (Routine Atmospheric Radiation Measurement [ARM] Aerial Facility [AAF] Clouds with Low Optical Water Depths [CLOWD] Optical Radiative Observations) at the ARM Climate Research Facility's Southern Great Plains site. The LES models are driven by continuous large-scale and surface forcings, and are constrained by multi-modal and temporally varying aerosol number size distribution profiles derived from aircraft observations. We compare simulated cloud macrophysical and microphysical properties with ground-based remote sensing and aircraft observations.more » The LES simulations capture the observed transitions of the evolving cumulus-topped boundary layers during the three daytime periods, and generally reproduce variations of droplet number concentration with liquid water content (LWC), corresponding to the gradient between the cloud centers and cloud edges at given heights. The observed LWC values fall within the range of simulated values; the observed droplet number concentrations are commonly higher than simulated, but differences remain on par with potential estimation errors in the aircraft measurements. Sensitivity studies examine the influences of bin microphysics versus bulk microphysics, aerosol advection, supersaturation treatment, and aerosol hygroscopicity. Simulated macrophysical cloud properties are found to be insensitive in this non-precipitating case, but microphysical properties are especially sensitive to bulk microphysics supersaturation treatment and aerosol hygroscopicity.« less

How Models Simulate the Radiative Effect in the Transition Zone of the Aerosol-Cloud Continuum

NASA Astrophysics Data System (ADS)

Calbo Angrill, J.; González, J. A.; Long, C. N.; McComiskey, A. C.

2017-12-01

Several studies have pointed towards dealing with clouds and aerosols as two manifestations of what is essentially the same physical phenomenon: a suspension of tiny particles in the air. Although the two extreme cases (i.e., pure aerosol and well-defined cloud) are easily distinguished, and obviously produce different radiative effects, there are many situations in the transition (or "twilight") zone. In a recent paper [Calbó et al., Atmos. Res. 2017, j.atmosres.2017.06.010], the authors of the current communication estimated that about 10% of time there might be a suspension of particles in the air that is difficult to distinguish as either cloud or aerosol. Radiative transfer models, however, simulate the effect of clouds and aerosols with different modules, routines, or parameterizations. In this study, we apply a sensitivity analysis approach to assess the ability of two radiative transfer models (SBDART and RRTM) in simulating the radiative effect of a suspension of particles with characteristics in the boundary between cloud and aerosol. We simulate this kind of suspension either in "cloud mode" or in "aerosol mode" and setting different values of optical depth, droplet size, water path, aerosol type, cloud height, etc. Irradiances both for solar and infrared bands are studied, both at ground level and at the top of the atmosphere, and all analyses are repeated for different solar zenith angles. We obtain that (a) water clouds and ice clouds have similar radiative effects if they have the same optical depth; (b) the spread of effects regarding different aerosol type/aerosol characteristics is remarkable; (c) radiative effects of an aerosol layer and of a cloud layer are different, even if they have similar optical depth; (d) for a given effect on the diffuse component, the effect on the direct component is usually greater (more extinction of direct beam) by aerosols than by clouds; (e) radiative transfer models are somewhat limited when simulating the effects of a suspension of particles in the transition zone, as the approach to this zone as an aerosol or as a cloud produces different results.

On the Representation of Ice Nucleation in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

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.

CLaMS-Ice: Large-scale cirrus cloud simulations in comparison with observations

NASA Astrophysics Data System (ADS)

Costa, Anja; Rolf, Christian; Grooß, Jens-Uwe; Spichtinger, Peter; Afchine, Armin; Spelten, Nicole; Dreiling, Volker; Zöger, Martin; Krämer, Martina

2016-04-01

Cirrus clouds are an element of uncertainty in the climate system and have received increasing attention since the last IPCC reports. The interactions of different freezing mechanisms, sedimentation rates, updraft velocity fluctuations and other factors that determine the formation and evolution of those clouds is still not fully understood. Thus, a reliable representation of cirrus clouds in models representing real atmospheric conditions is still a challenging task. At last year's EGU, Rolf et al. (2015) introduced the new large-scale microphysical cirrus cloud model CLaMS-Ice: based on trajectories calculated with CLaMS (McKenna et al., 2002 and Konopka et al. 2007), it simulates the development of cirrus clouds relying on the cirrus bulk model by Spichtinger and Gierens (2009). The qualitative agreement between CLaMS-Ice simulations and observations could be demonstrated at that time. Now we present a detailed quantitative comparison between standard ECMWF products, CLaMS-Ice simulations, and in-situ measurements obtained during the ML-Cirrus campaign 2014. We discuss the agreement of the parameters temperature (observational data: BAHAMAS), relative humidity (SHARC), cloud occurrence, cloud particle concentration, ice water content and cloud particle radii (all NIXE-CAPS). Due to the precise trajectories based on ECMWF wind and temperature fields, CLaMS-Ice represents the cirrus cloud vertical and horizontal coverage more accurately than the ECMWF ice water content (IWC) fields. We demonstrate how CLaMS-Ice can be used to evaluate different input settings (e.g. amount of ice nuclei, freezing thresholds, sedimentation settings) that lead to cirrus clouds with the microphysical properties observed during ML-Cirrus (2014).

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

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.

Improving Subtropical Boundary Layer Cloudiness in the 2011 NCEP GFS

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

Fletcher, J. K.; Bretherton, Christopher S.; Xiao, Heng

2014-09-23

The current operational version of National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) shows significant low cloud bias. These biases also appear in the Coupled Forecast System (CFS), which is developed from the GFS. These low cloud biases degrade seasonal and longer climate forecasts, particularly of short-wave cloud radiative forcing, and affect predicted sea surface temperature. Reducing this bias in the GFS will aid the development of future CFS versions and contributes to NCEP's goal of unified weather and climate modelling. Changes are made to the shallow convection and planetary boundary layer parameterisations to make them more consistentmore » with current knowledge of these processes and to reduce the low cloud bias. These changes are tested in a single-column version of GFS and in global simulations with GFS coupled to a dynamical ocean model. In the single-column model, we focus on changing parameters that set the following: the strength of shallow cumulus lateral entrainment, the conversion of updraught liquid water to precipitation and grid-scale condensate, shallow cumulus cloud top, and the effect of shallow convection in stratocumulus environments. Results show that these changes improve the single-column simulations when compared to large eddy simulations, in particular through decreasing the precipitation efficiency of boundary layer clouds. These changes, combined with a few other model improvements, also reduce boundary layer cloud and albedo biases in global coupled simulations.« less

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

NASA Technical Reports Server (NTRS)

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

2010-01-01

In recent years, exponentially increasing computer power 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 sq km 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 models can be run in grid size similar to cloud resolving models 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, W8F). (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling systems to study the interactions between clouds, precipitation, and aerosols will be presented. Also how to use the multi-satellite simulator to improve precipitation processes will be discussed.

Using Multi-Scale Modeling Systems to Study the Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2010-01-01

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

Cloud Coverage Enhancement and Nocturnal Drizzle Suppression in Stratocumulus by Aerosols

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, Owen B.; Stevens, David E.; Coakley, James A., Jr.; Gore, Warren J. (Technical Monitor)

2002-01-01

Recent satellite observations of ship tracks surprisingly indicate that cloud water decreases with increasing droplet concentrations. However, we find by analyzing detailed simulations of stratocumulus that the reported trend is likely an artifact of sampling, only overcast clouds. The simulations instead show cloud coverage increasing with droplet concentrations, accounting for 25% of cloud albedo increase at moderate droplet concentrations. Our simulations also show that increases in cloud water from drizzle suppression (by increasing droplet concentrations) are favored only at night or at extremely low droplet concentrations, suggesting that the indirect aerosol forcing is overestimated in climate change projections by many general circulation models.

Direct comparisons of ice cloud macro- and microphysical properties simulated by the Community Atmosphere Model version 5 with HIPPO aircraft observations

NASA Astrophysics Data System (ADS)

Wu, Chenglai; Liu, Xiaohong; Diao, Minghui; Zhang, Kai; Gettelman, Andrew; Lu, Zheng; Penner, Joyce E.; Lin, Zhaohui

2017-04-01

In this study we evaluate cloud properties simulated by the Community Atmosphere Model version 5 (CAM5) using in situ measurements from the HIAPER Pole-to-Pole Observations (HIPPO) campaign for the period of 2009 to 2011. The modeled wind and temperature are nudged towards reanalysis. Model results collocated with HIPPO flight tracks are directly compared with the observations, and model sensitivities to the representations of ice nucleation and growth are also examined. Generally, CAM5 is able to capture specific cloud systems in terms of vertical configuration and horizontal extension. In total, the model reproduces 79.8 % of observed cloud occurrences inside model grid boxes and even higher (94.3 %) for ice clouds (T ≤ -40 °C). The missing cloud occurrences in the model are primarily ascribed to the fact that the model cannot account for the high spatial variability of observed relative humidity (RH). Furthermore, model RH biases are mostly attributed to the discrepancies in water vapor, rather than temperature. At the micro-scale of ice clouds, the model captures the observed increase of ice crystal mean sizes with temperature, albeit with smaller sizes than the observations. The model underestimates the observed ice number concentration (Ni) and ice water content (IWC) for ice crystals larger than 75 µm in diameter. Modeled IWC and Ni are more sensitive to the threshold diameter for autoconversion of cloud ice to snow (Dcs), while simulated ice crystal mean size is more sensitive to ice nucleation parameterizations than to Dcs. Our results highlight the need for further improvements to the sub-grid RH variability and ice nucleation and growth in the model.

On the Representation of Cloud Phase in Global Climate Models, and its Importance for Simulations of Climate Forcings and Feedbacks

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.

A Model for Particle Microphysics,Turbulent Mixing, and Radiative Transfer in the Stratocumulus-Topped Marine Boundary Layer and Comparisons with Measurements

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, Owen B.; Hobbs, Peter V.

1995-01-01

A detailed 1D model of the stratocumulus-topped marine boundary layer is described. The model has three coupled components: a microphysics module that resolves the size distributions of aerosols and cloud droplets, a turbulence module that treats vertical mixing between layers, and a multiple wavelength radiative transfer module that calculates radiative heating rates and cloud optical properties. The results of a 12-h model simulation reproduce reasonably well the bulk thermodynamics, microphysical properties, and radiative fluxes measured in an approx. 500-m thick, summertime marine stratocumulus cloud layer by Nicholls. However, in this case, the model predictions of turbulent fluxes between the cloud and subcloud layers exceed the measurements. Results of model simulations are also compared to measurements of a marine stratus layer made under gate conditions and with measurements of a high, thin marine stratocumulus layer. The variations in cloud properties are generally reproduced by the model, although it underpredicts the entrainment of overlying air at cloud top under gale conditions. Sensitivities of the model results are explored. The vertical profile of cloud droplet concentration is sensitive to the lower size cutoff of the droplet size distribution due to the presence of unactivated haze particles in the lower region of the modeled cloud. Increases in total droplet concentrations do not always produce less drizzle and more cloud water in the model. The radius of the mean droplet volume does not correlate consistently with drizzle, but the effective droplet radius does. The greatest impacts on cloud properties predicted by the model are produced by halving the width of the size distribution of input condensation nuclei and by omitting the effect of cloud-top radiative cooling on the condensational growth of cloud droplets. The omission of infrared scattering produces noticeable changes in cloud properties. The collection efficiencies for droplets less than 30-micron radius, and the value of the accommodation coefficient for condensational droplet growth, have noticeable effects on cloud properties. The divergence of the horizontal wind also has a significant effect on a 12-h model simulation of cloud structure. Conclusions drawn from the model are tentative because of the limitations of the 1D model framework. A principal simplification is that the model assumes horizontal homogeneity, and, therefore, does not resolve updrafts and downdrafts. Likely consequences of this simplification include overprediction of the growth of droplets by condensation in the upper region of the cloud, underprediction of droplet condensational growth in the lower region of the cloud, and under-prediction of peak supersaturations.

A Model for Particle Microphysics, Turbulent Mixing, and Radiative Transfer in the Stratocumulus-Topped Marine Boundary Layer and Comparisons with Measurements

NASA Technical Reports Server (NTRS)

Ackerman, Andrew S.; Toon, Owen B.; Hobbs, Peter V.

1995-01-01

A detailed 1D model of the stratocumulus-topped marine boundary layer is described. The model has three coupled components: a microphysics module that resolves the size distributions of aerosols and cloud droplets, a turbulence module that treats vertical mixing between layers, and a multiple wavelength radiative transfer module that calculates radiative heating rates and cloud optical properties. The results of a 12-h model simulation reproduce reasonably well the bulk thermodynamics, microphysical properties, and radiative fluxes measured in an approx. 500-m thick, summertime marine stratocumulus cloud layer by Nicholls. However, in this case, the model predictions of turbulent fluxes between the cloud and subcloud layers exceed the measurements. Results of model simulations are also compared to measurements of a marine stratus layer made under gale conditions and with measurements of a high, thin marine stratocumulus layer. The variations in cloud properties are generally reproduced by the model, although it underpredicts the entrainment of overlying air at cloud top under gale conditions. Sensitivities of the model results are explored. The vertical profile of cloud droplet concentration is sensitive to the lower size cutoff of the droplet size distribution due to the presence of unactivated haze particles in the lower region of the modeled cloud. Increases in total droplet concentrations do not always produce less drizzle and more cloud water in the model. The radius of the mean droplet volume does not correlate consistently with drizzle, but the effective droplet radius does. The greatest impacts on cloud properties predicted by the model are produced by halving the width of the size distribution of input condensation nuclei and by omitting the effect of cloud-top radiative cooling on the condensational growth of cloud droplets. The omission of infrared scattering produces noticeable changes in cloud properties. The collection efficiencies for droplets less than 30-micrometers radius, and the value of the accommodation coefficient for condensational droplet growth, have noticeable effects on cloud properties. The divergence of the horizontal wind also has a significant effect on a 12-h model simulation of cloud structure. Conclusions drawn from the model are tentative because of the limitations of the 1D model framework. A principal simplification is that the model assumes horizontal homogeneity, and, therefore, does not resolve updrafts and downdrafts. Likely consequences of this simplification include overprediction of the growth of droplets by condensation in the upper region of the cloud, underprediction of droplet condensational growth in the lower region of the cloud, and underprediction of peak supersaturations.

A Single Column Model Ensemble Approach Applied to the TWP-ICE Experiment

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

Davies, Laura; Jakob, Christian; Cheung, K.

2013-06-27

Single column models (SCM) are useful testbeds for investigating the parameterisation schemes of numerical weather prediction and climate models. The usefulness of SCM simulations are limited, however, by the accuracy of the best-estimate large-scale data prescribed. One method to address this uncertainty is to perform ensemble simulations of the SCM. This study first derives an ensemble of large-scale data for the Tropical Warm Pool International Cloud Experiment (TWP-ICE) based on an estimate of a possible source of error in the best-estimate product. This data is then used to carry out simulations with 11 SCM and 2 cloud-resolving models (CRM). Best-estimatemore » simulations are also performed. All models show that moisture related variables are close to observations and there are limited differences between the best-estimate and ensemble mean values. The models, however, show different sensitivities to changes in the forcing particularly when weakly forced. The ensemble simulations highlight important differences in the moisture budget between the SCM and CRM. Systematic differences are also apparent in the ensemble mean vertical structure of cloud variables. The ensemble is further used to investigate relations between cloud variables and precipitation identifying large differences between CRM and SCM. This study highlights that additional information can be gained by performing ensemble simulations enhancing the information derived from models using the more traditional single best-estimate simulation.« less

Global Simulations of Ice nucleation and Ice Supersaturation with an Improved Cloud Scheme in the Community Atmosphere Model

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

Can nudging be used to quantify model sensitivities in precipitation and cloud forcing?

NASA Astrophysics Data System (ADS)

Lin, Guangxing; Wan, Hui; Zhang, Kai; Qian, Yun; Ghan, Steven J.

2016-09-01

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

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations

NASA Astrophysics Data System (ADS)

Stanfield, R. E.; Dong, X.; Xi, B.; Kennedy, A. D.; Del Genio, A. D.; Minnis, P.; Loeb, N. G.; Doelling, D.

2013-05-01

Marine Boundary Layer (MBL) Clouds are an extremely important part of the climate system. Their treatment in climate models is a large source of uncertainty that will harm future projection of the Earth's climate. Zhang et al. (2005, CMIP3) compared the GCMs simulated cloud fractions (CF) with NASA CERES and ISCCP results and found that most GCMs underestimated mid-latitude MBL clouds but overestimated their optical depth. The underestimated CF and overestimated cloud optical thickness in the models offset each other when calculating TOA radiation budgets. Recent studies (Jiang et al. 2012; Stanfield et al. 2013; and Dolinar et al. 2013) have found there has not been much improvement from CMIP3 to CMIP5 for MBL clouds. Most GCMs still simulate fewer mid-latitude MBL clouds. In this study, we compare the NASA GISS CMIP5 and Post-CMIP5 results with NASA CERES cloud properties (SYN1deg) and TOA radiation budgets (EBAF), as well as CloudSat-CALIPSO cloud products. Special attention has been paid over the Southern mid-latitudes (~ 30-60 °S) where the total cloud fractions can reach up to 80-90% with MBL clouds being the dominant cloud type. Comparisons have shown that the globally averaged total CFs and TOA radiation budgets from CMIP5 agreed well with satellite observations, however, there are significant regional differences. For example, most CMIP5 models underestimated MBL clouds over the Southern mid-latitudes, including the GISS GCM, resulting in less reflected (or more absorbed) shortwave flux at TOA. The preliminary results from NASA GISS post-CMIP5 have made many improvements, and agree much better with satellite observations. These improvements are attributed to a new PBL parameterization, where more/less clouds can be simulated when the PBL gets deeper/shallower. This update has a large effect on radiation and clouds.

Cloud feedback mechanisms and their representation in global climate models

DOE PAGES

Ceppi, Paulo; Brient, Florent; Zelinka, Mark D.; ...

2017-05-11

Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). Thesemore » cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.« less

Cloud feedback mechanisms and their representation in global climate models

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

Ceppi, Paulo; Brient, Florent; Zelinka, Mark D.

Cloud feedback—the change in top-of-atmosphere radiative flux resulting from the cloud response to warming—constitutes by far the largest source of uncertainty in the climate response to CO 2 forcing simulated by global climate models (GCMs). In this paper, we review the main mechanisms for cloud feedbacks, and discuss their representation in climate models and the sources of intermodel spread. Global-mean cloud feedback in GCMs results from three main effects: (1) rising free-tropospheric clouds (a positive longwave effect); (2) decreasing tropical low cloud amount (a positive shortwave [SW] effect); (3) increasing high-latitude low cloud optical depth (a negative SW effect). Thesemore » cloud responses simulated by GCMs are qualitatively supported by theory, high-resolution modeling, and observations. Rising high clouds are consistent with the fixed anvil temperature (FAT) hypothesis, whereby enhanced upper-tropospheric radiative cooling causes anvil cloud tops to remain at a nearly fixed temperature as the atmosphere warms. Tropical low cloud amount decreases are driven by a delicate balance between the effects of vertical turbulent fluxes, radiative cooling, large-scale subsidence, and lower-tropospheric stability on the boundary-layer moisture budget. High-latitude low cloud optical depth increases are dominated by phase changes in mixed-phase clouds. Finally, the causes of intermodel spread in cloud feedback are discussed, focusing particularly on the role of unresolved parameterized processes such as cloud microphysics, turbulence, and convection.« less

Point cloud modeling using the homogeneous transformation for non-cooperative pose estimation

NASA Astrophysics Data System (ADS)

Lim, Tae W.

2015-06-01

A modeling process to simulate point cloud range data that a lidar (light detection and ranging) sensor produces is presented in this paper in order to support the development of non-cooperative pose (relative attitude and position) estimation approaches which will help improve proximity operation capabilities between two adjacent vehicles. The algorithms in the modeling process were based on the homogeneous transformation, which has been employed extensively in robotics and computer graphics, as well as in recently developed pose estimation algorithms. Using a flash lidar in a laboratory testing environment, point cloud data of a test article was simulated and compared against the measured point cloud data. The simulated and measured data sets match closely, validating the modeling process. The modeling capability enables close examination of the characteristics of point cloud images of an object as it undergoes various translational and rotational motions. Relevant characteristics that will be crucial in non-cooperative pose estimation were identified such as shift, shadowing, perspective projection, jagged edges, and differential point cloud density. These characteristics will have to be considered in developing effective non-cooperative pose estimation algorithms. The modeling capability will allow extensive non-cooperative pose estimation performance simulations prior to field testing, saving development cost and providing performance metrics of the pose estimation concepts and algorithms under evaluation. The modeling process also provides "truth" pose of the test objects with respect to the sensor frame so that the pose estimation error can be quantified.

Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

DOE PAGES

Chen, Ying; Zhang, Yang; Fan, Jiwen; ...

2015-08-18

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM 2.5, and PM 10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Application of an Online-Coupled Regional Climate Model, WRF-CAM5, over East Asia for Examination of Ice Nucleation Schemes: Part I. Comprehensive Model Evaluation and Trend Analysis for 2006 and 2011

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

Chen, Ying; Zhang, Yang; Fan, Jiwen

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM2.5, and PM10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

Application of an online-coupled regional climate model, WRF-CAM5, over East Asia for examination of ice nucleation schemes: Part I. Comprehensive model evaluation and trend analysis for 2006 and 2011

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

Chen, Ying; Zhang, Yang; Fan, Jiwen

Online-coupled climate and chemistry models are necessary to realistically represent the interactions between climate variables and chemical species and accurately simulate aerosol direct and indirect effects on cloud, precipitation, and radiation. In this Part I of a two-part paper, simulations from the Weather Research and Forecasting model coupled with the physics package of Community Atmosphere Model (WRF-CAM5) are conducted with the default heterogeneous ice nucleation parameterization over East Asia for two full years: 2006 and 2011. A comprehensive model evaluation is performed using satellite and surface observations. The model shows an overall acceptable performance for major meteorological variables at themore » surface and in the boundary layer, as well as column variables (e.g., precipitation, cloud fraction, precipitating water vapor, downward longwave and shortwave radiation). Moderate to large biases exist for cloud condensation nuclei over oceanic areas, cloud variables (e.g., cloud droplet number concentration, cloud liquid and ice water paths, cloud optical depth, longwave and shortwave cloud forcing). These biases indicate a need to improve the model treatments for cloud processes, especially cloud droplets and ice nucleation, as well as to reduce uncertainty in the satellite retrievals. The model simulates well the column abundances of chemical species except for column SO 2 but relatively poor for surface concentrations of several species such as CO, NO 2, SO 2, PM 2.5, and PM 10. Several reasons could contribute to the underestimation of major chemical species in East Asia including underestimations of anthropogenic emissions and natural dust emissions, uncertainties in the spatial and vertical distributions of the anthropogenic emissions, as well as biases in meteorological, radiative, and cloud predictions. Despite moderate to large biases in the chemical predictions, the model performance is generally consistent with or even better than that reported for East Asia with only a few exceptions. The model generally reproduces the observed seasonal variations and the difference between 2006 and 2011 for most variables or chemical species. Overall, these results demonstrate promising skills of WRF-CAM5 for long-term simulations at a regional scale and suggest several areas of potential improvements.« less

CO2 Condensation Models for Mars

NASA Technical Reports Server (NTRS)

Colaprete, A.; Haberle, R.

2004-01-01

During the polar night in both hemispheres of Mars, regions of low thermal emission, frequently referred to as "cold spots", have been observed by Mariner 9, Viking and Mars Global Surveyor (MGS) spacecraft. These cold spots vary in time and appear to be associated with topographic features suggesting that they are the result of a spectral-emission effect due to surface accumulation of fine-grained frost or snow. Presented here are simulations of the Martian polar night using the NASA Ames General Circulation Cloud Model. This cloud model incorporates all the microphysical processes of carbon dioxide cloud formation, including nucleation, condensation and sedimentation and is coupled to a surface frost scheme that includes both direct surface condensation and precipitation. Using this cloud model we simulate the Mars polar nights and compare model results to observations from the Thermal Emission Spectrometer (TES) and the Mars Orbiter Laser Altimeter (MOLA). Model predictions of "cold spots" compare well with TES observations of low emissivity regions, both spatially and as a function of season. The model predicted frequency of CO2 cloud formation also agrees well with MOLA observations of polar night cloud echoes. Together the simulations and observations in the North indicate a distinct shift in atmospheric state centered about Ls 270 which we believe may be associated with the strength of the polar vortex.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing.

PubMed

Li, Zhixin; Su, Dandan; Zhu, Haijiang; Li, Wei; Zhang, Fan; Li, Ruirui

2017-01-08

Synthetic Aperture Radar (SAR) raw data simulation is a fundamental problem in radar system design and imaging algorithm research. The growth of surveying swath and resolution results in a significant increase in data volume and simulation period, which can be considered to be a comprehensive data intensive and computing intensive issue. Although several high performance computing (HPC) methods have demonstrated their potential for accelerating simulation, the input/output (I/O) bottleneck of huge raw data has not been eased. In this paper, we propose a cloud computing based SAR raw data simulation algorithm, which employs the MapReduce model to accelerate the raw data computing and the Hadoop distributed file system (HDFS) for fast I/O access. The MapReduce model is designed for the irregular parallel accumulation of raw data simulation, which greatly reduces the parallel efficiency of graphics processing unit (GPU) based simulation methods. In addition, three kinds of optimization strategies are put forward from the aspects of programming model, HDFS configuration and scheduling. The experimental results show that the cloud computing based algorithm achieves 4_ speedup over the baseline serial approach in an 8-node cloud environment, and each optimization strategy can improve about 20%. This work proves that the proposed cloud algorithm is capable of solving the computing intensive and data intensive issues in SAR raw data simulation, and is easily extended to large scale computing to achieve higher acceleration.

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2016-01-05

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less

An ensemble constrained variational analysis of atmospheric forcing data and its application to evaluate clouds in CAM5: Ensemble 3DCVA and Its Application

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

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

Large-scale atmospheric forcing data can greatly impact the simulations of atmospheric process models including Large Eddy Simulations (LES), Cloud Resolving Models (CRMs) and Single-Column Models (SCMs), and impact the development of physical parameterizations in global climate models. This study describes the development of an ensemble variationally constrained objective analysis of atmospheric large-scale forcing data and its application to evaluate the cloud biases in the Community Atmospheric Model (CAM5). Sensitivities of the variational objective analysis to background data, error covariance matrix and constraint variables are described and used to quantify the uncertainties in the large-scale forcing data. Application of the ensemblemore » forcing in the CAM5 SCM during March 2000 intensive operational period (IOP) at the Southern Great Plains (SGP) of the Atmospheric Radiation Measurement (ARM) program shows systematic biases in the model simulations that cannot be explained by the uncertainty of large-scale forcing data, which points to the deficiencies of physical parameterizations. The SCM is shown to overestimate high clouds and underestimate low clouds. These biases are found to also exist in the global simulation of CAM5 when it is compared with satellite data.« less

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

NASA Astrophysics Data System (ADS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Hélène; Douville, Hervé; Good, Peter; Kay, Jennifer E.; Klein, Stephen A.; Marchand, Roger; Medeiros, Brian; Pier Siebesma, A.; Skinner, Christopher B.; Stevens, Bjorn; Tselioudis, George; Tsushima, Yoko; Watanabe, Masahiro

2017-01-01

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

1. How well do clouds and other relevant variables simulated by models agree with observations?

2. What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?

3. Which models have the most credible representations of processes relevant to the simulation of clouds?

4. How do clouds and their changes interact with other elements of the climate system?

Cloud Properties Simulated by a Single-Column Model. Part II: Evaluation of Cumulus Detrainment and Ice-phase Microphysics Using a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Luo, Yali; Krueger, Steven K.; Xu, Kuan-Man

2005-01-01

This paper is the second in a series in which kilometer-scale-resolving observations from the Atmospheric Radiation Measurement program and a cloud-resolving model (CRM) are used to evaluate the single-column model (SCM) version of the National Centers for Environmental Prediction Global Forecast System model. Part I demonstrated that kilometer-scale cirrus properties simulated by the SCM significantly differ from the cloud radar observations while the CRM simulation reproduced most of the cirrus properties as revealed by the observations. The present study describes an evaluation, through a comparison with the CRM, of the SCM's representation of detrainment from deep cumulus and ice-phase microphysics in an effort to better understand the findings of Part I. It is found that detrainment occurs too infrequently at a single level at a time in the SCM, although the detrainment rate averaged over the entire simulation period is somewhat comparable to that of the CRM simulation. Relatively too much detrained ice is sublimated when first detrained. Snow falls over too deep of a layer due to the assumption that snow source and sink terms exactly balance within one time step in the SCM. These characteristics in the SCM parameterizations may explain many of the differences in the cirrus properties between the SCM and the observations (or between the SCM and the CRM). A possible improvement for the SCM consists of the inclusion of multiple cumulus cloud types as in the original Arakawa-Schubert scheme, prognostically determining the stratiform cloud fraction and snow mixing ratio. This would allow better representation of the detrainment from deep convection, better coupling of the volume of detrained air with cloud fraction, and better representation of snow field.

Ice Cloud Backscatter Study and Comparison with CALIPSO and MODIS Satellite Data

NASA Technical Reports Server (NTRS)

Ding, Jiachen; Yang, Ping; Holz, Robert E.; Platnick, Steven; Meyer, Kerry G.; Vaughan, Mark A.; Hu, Yongxiang; King, Michael D.

2016-01-01

An invariant imbedding T-matrix (II-TM) method is used to calculate the single-scattering properties of 8-column aggregate ice crystals. The II-TM based backscatter values are compared with those calculated by the improved geometric-optics method (IGOM) to refine the backscattering properties of the ice cloud radiative model used in the MODIS Collection 6 cloud optical property product. The integrated attenuated backscatter-to-cloud optical depth (IAB-ICOD) relation is derived from simulations using a CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite) lidar simulator based on a Monte Carlo radiative transfer model. By comparing the simulation results and co-located CALIPSO and MODIS (Moderate Resolution Imaging Spectroradiometer) observations, the non-uniform zonal distribution of ice clouds over ocean is characterized in terms of a mixture of smooth and rough ice particles. The percentage of the smooth particles is approximately 6 percent and 9 percent for tropical and mid-latitude ice clouds, respectively.

Evaluation of Long-Term Cloud-Resolving Model Simulations Using Satellite Radiance Observations and Multi-Frequency Satellite Simulators

NASA Technical Reports Server (NTRS)

Matsui, Toshihisa; Zeng, Xiping; Tao, Wei-Kuo; Masunaga, Hirohiko; Olson, William S.; Lang, Stephen

2008-01-01

This paper proposes a methodology known as the Tropical Rainfall Measuring Mission (TRMM) Triple-Sensor Three-step Evaluation Framework (T3EF) for the systematic evaluation of precipitating cloud types and microphysics in a cloud-resolving model (CRM). T3EF utilizes multi-frequency satellite simulators and novel statistics of multi-frequency radiance and backscattering signals observed from the TRMM satellite. Specifically, T3EF compares CRM and satellite observations in the form of combined probability distributions of precipitation radar (PR) reflectivity, polarization-corrected microwave brightness temperature (Tb), and infrared Tb to evaluate the candidate CRM. T3EF is used to evaluate the Goddard Cumulus Ensemble (GCE) model for cases involving the South China Sea Monsoon Experiment (SCSMEX) and Kwajalein Experiment (KWAJEX). This evaluation reveals that the GCE properly captures the satellite-measured frequencies of different precipitating cloud types in the SCSMEX case but underestimates the frequencies of deep convective and deep stratiform types in the KWAJEX case. Moreover, the GCE tends to simulate excessively large and abundant frozen condensates in deep convective clouds as inferred from the overestimated GCE-simulated radar reflectivities and microwave Tb depressions. Unveiling the detailed errors in the GCE s performance provides the best direction for model improvements.

Simulating Roll Clouds associated with Low-Level Convergence.

NASA Astrophysics Data System (ADS)

Prasad, A. A.; Sherwood, S. C.

2015-12-01

Convective initiation often takes place when features such as fronts and/or rolls collide, merge or otherwise meet. Rolls indicate boundary layer convergence and may initiate thunderstorms. These are often seen in satellite and radar imagery prior to the onset of deep convection. However, links between convergence driven rolls and convection are poor in global models. The poor representation of convection is the source of many model biases, especially over the Maritime Continent in the Tropics. We simulate low-level convergence lines over north-eastern Australia using the Weather Research and Forecasting (WRF) Model (version 3.7). The simulations are events from September-October 2002 driven by sea breeze circulations. Cloud lines associated with bore-waves that form along the low-level convergence lines are thoroughly investigated in this study with comparisons from satellite and surface observations. Initial simulations for a series of cloud lines observed on 4th October, 2002 over the Gulf of Carpentaria showed greater agreement in the timing and propagation of the disturbance and the low-level convergence, however the cloud lines or streets of roll clouds were not properly captured by the model. Results from a number of WRF simulations with different microphysics, cumulus and planetary boundary layer schemes, resolution and boundary conditions will also be discussed.

[Retrieval of the Optical Thickness and Cloud Top Height of Cirrus Clouds Based on AIRS IR High Spectral Resolution Data].

PubMed

Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai

2015-05-01

A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable.

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.

Strategic Implications of Cloud Computing for Modeling and Simulation (Briefing)

DTIC Science & Technology

2016-04-01

of Promises with Cloud • Cost efficiency • Unlimited storage • Backup and recovery • Automatic software integration • Easy access to information...activities that wrap the actual exercise itself (e.g., travel for exercise support, data collection, integration , etc.). Cloud -based simulation would...requiring quick delivery rather than fewer large messages requiring high bandwidth. Cloud environments tend to be better at providing high-bandwidth

TOWARDS ICE FORMATION CLOSURE IN MIXED-PHASE BOUNDARY LAYER CLOUDS DURING ISDAC

NASA Astrophysics Data System (ADS)

Avramov, A.; Ackerman, A. S.; Fridlind, A. M.; van Diedenhoven, B.; Korolev, A. V.

2009-12-01

Mixed-phase stratus clouds are ubiquitous in the Arctic during the winter and transition seasons. Despite their important role in various climate feedback mechanisms they are not well understood and are difficult to represent faithfully in cloud models. In particular, models of all types experience difficulties reproducing observed ice concentrations and liquid/ice water partitioning in these clouds. Previous studies have demonstrated that simulated ice concentrations and ice water content are critically dependent on ice nucleation modes and ice crystal habit assumed in simulations. In this study we use large-eddy simulations with size-resolved microphysics to determine whether uncertainties in ice nucleus concentrations, ice nucleation mechanisms, ice crystal habits and large-scale forcing are sufficient to account for the difference between simulated and observed quantities. We present results of simulations of two case studies based on observations taken during the recent Indirect and Semi-Direct Aerosol Campaign (ISDAC) on April 8 and 26, 2008. The model simulations are evaluated through extensive comparison with in-situ observations and ground-based remote sensing measurements.

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.

A Melting Layer Model for Passive/Active Microwave Remote Sensing Applications. Part 2; Simulation of TRMM Observations

NASA Technical Reports Server (NTRS)

Olson, William S.; Bauer, Peter; Kummerow, Christian D.; Tao, Wei-Kuo

2000-01-01

The one-dimensional, steady-state melting layer model developed in Part I of this study is used to calculate both the microphysical and radiative properties of melting precipitation, based upon the computed concentrations of snow and graupel just above the freezing level at applicable horizontal gridpoints of 3-dimensional cloud resolving model simulations. The modified 3-dimensional distributions of precipitation properties serve as input to radiative transfer calculations of upwelling radiances and radar extinction/reflectivities at the TRMM Microwave Imager (TMI) and Precipitation Radar (PR) frequencies, respectively. At the resolution of the cloud resolving model grids (approx. 1 km), upwelling radiances generally increase if mixed-phase precipitation is included in the model atmosphere. The magnitude of the increase depends upon the optical thickness of the cloud and precipitation, as well as the scattering characteristics of ice-phase precipitation aloft. Over the set of cloud resolving model simulations utilized in this study, maximum radiance increases of 43, 28, 18, and 10 K are simulated at 10.65, 19.35 GHz, 37.0, and 85.5 GHz, respectively. The impact of melting on TMI-measured radiances is determined not only by the physics of the melting particles but also by the horizontal extent of the melting precipitation, since the lower-frequency channels have footprints that extend over 10''s of kilometers. At TMI resolution, the maximum radiance increases are 16, 15, 12, and 9 K at the same frequencies. Simulated PR extinction and reflectivities in the melting layer can increase dramatically if mixed-phase precipitation is included, a result consistent with previous studies. Maximum increases of 0.46 (-2 dB) in extinction optical depth and 5 dBZ in reflectivity are simulated based upon the set of cloud resolving model simulations.

New insight of Arctic cloud parameterization from regional climate model simulations, satellite-based, and drifting station data

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.

Optical property retrievals of subvisual cirrus clouds from OSIRIS limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2012-08-01

We present a technique for retrieving the optical properties of subvisual cirrus clouds detected by OSIRIS, a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Optical properties from an in-situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is demonstrated that the retrieved extinction profile models accurately the measured in-cloud radiances from OSIRIS. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

A Quantitative Investigation of Entrainment and Detrainment in Numerically Simulated Convective Clouds. Pt. 2; Simulations of Cumulonimbus Clouds

NASA Technical Reports Server (NTRS)

Cohen, Charles

1998-01-01

Deep cumulonimbus clouds are simulated using a model that makes accurate diagnoses of entrainment and detrainment rates and of the properties of entrained and detrained air. Clouds generated by a variety of initial thermodynamic soundings are compared. In the simulations, updraft entrainment rates are large near and above cloud base, through the entire depth of the conditionally unstable layer. Stronger updrafts in a more unstable environment are better able to entrain relatively undisturbed environmental air, while weaker updrafts can entrain only air that has been modified by the clouds. When the maximum buoyancy is large, the updraft includes parcels with a wide range of buoyancies, while weaker clouds are more horizontally uniform. Strong downdrafts originate from levels at which updrafts detrain, and their mass flux depends on the mass flux of the updraft. The magnitude of mixing between cloud and environment, not the entrainment rate, varies inversely with the cloud radius. How much of the mixed air is entrained depends on the buoyancy.

Ice Cloud Formation and Dehydration in the Tropical Tropopause Layer

NASA Technical Reports Server (NTRS)

Jensen, Eric; Gore, Warren J. (Technical Monitor)

2002-01-01

Stratospheric water vapor is important not only for its greenhouse forcing, but also because it plays a significant role in stratospheric chemistry. Several recent studies have focused on the potential for dehydration due to ice cloud formation in air rising slowly through the tropical tropopause layer (TTL). Holton and Gettelman showed that temperature variations associated with horizontal transport of air in the TTL can drive ice cloud formation and dehydration, and Gettelman et al. recently examined the cloud formation and dehydration along kinematic trajectories using simple assumptions about the cloud properties. In this study, a Lagrangian, one-dimensional cloud model has been used to further investigate cloud formation and dehydration as air is transported horizontally and vertically through the TTL. Time-height curtains of temperature are extracted from meteorological analyses. The model tracks the growth, advection, and sedimentation of individual cloud particles. The regional distribution of clouds simulated in the model is comparable to the subvisible cirrus distribution indicated by SAGE II. The simulated cloud properties and cloud frequencies depend strongly on the assumed supersaturation threshold for ice nucleation. The clouds typically do not dehydrate the air along trajectories down to the temperature minimum saturation mixing ratio. Rather the water vapor mixing ratio crossing the tropopause along trajectories is 10-50% larger than the saturation mixing ratio. I will also discuss the impacts of Kelvin waves and gravity waves on cloud properties and dehydration efficiency. These simulations can be used to determine whether observed lower stratospheric water vapor mixing ratios can be explained by dehydration associated with in situ TTL cloud formation alone.

Numerics and subgrid-scale modeling in large eddy simulations of stratocumulus clouds.

PubMed

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

PubMed Central

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

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

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

Wang, Zhien

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

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

Inspite of significant improvement in numerical model physics, resolution and numerics, the general circulation models (GCMs) find it difficult to simulate realistic seasonal and intraseasonal variabilities over global tropics and particularly over Indian summer monsoon (ISM) region. The bias is mainly attributed to the improper representation of physical processes. Among all the processes, the cloud and convective processes appear to play a major role in modulating model bias. In recent times, NCEP CFSv2 model is being adopted under Monsoon Mission for dynamical monsoon forecast over Indian region. The analyses of climate free run of CFSv2 in two resolutions namely at T126 and T382, show largely similar bias in simulating seasonal rainfall, in capturing the intraseasonal variability at different scales over the global tropics and also in capturing tropical waves. Thus, the biases of CFSv2 indicate a deficiency in model's parameterization of cloud and convective processes. Keeping this in background and also for the need to improve the model fidelity, two approaches have been adopted. Firstly, in the superparameterization, 32 cloud resolving models each with a horizontal resolution of 4 km are embedded in each GCM (CFSv2) grid and the conventional sub-grid scale convective parameterization is deactivated. This is done to demonstrate the role of resolving cloud processes which otherwise remain unresolved. The superparameterized CFSv2 (SP-CFS) is developed on a coarser version T62. The model is integrated for six and half years in climate free run mode being initialised from 16 May 2008. The analyses reveal that SP-CFS simulates a significantly improved mean state as compared to default CFS. The systematic bias of lesser rainfall over Indian land mass, colder troposphere has substantially been improved. Most importantly the convectively coupled equatorial waves and the eastward propagating MJO has been found to be simulated with more fidelity in SP-CFS. The reason of such betterment in model mean state has been found to be due to the systematic improvement in moisture field, temperature profile and moist instability. The model also has better simulated the cloud and rainfall relation. This initiative demonstrates the role of cloud processes on the mean state of coupled GCM. As the superparameterization approach is computationally expensive, so in another approach, the conventional Simplified Arakawa Schubert (SAS) scheme is replaced by a revised SAS scheme (RSAS) and also the old and simplified cloud scheme of Zhao-Karr (1997) has been replaced by WSM6 in CFSV2 (hereafter CFS-CR). The primary objective of such modifications is to improve the distribution of convective rain in the model by using RSAS and the grid-scale or the large scale nonconvective rain by WSM6. The WSM6 computes the tendency of six class (water vapour, cloud water, ice, snow, graupel, rain water) hydrometeors at each of the model grid and contributes in the low, middle and high cloud fraction. By incorporating WSM6, for the first time in a global climate model, we are able to show a reasonable simulation of cloud ice and cloud liquid water distribution vertically and spatially as compared to Cloudsat observations. The CFS-CR has also showed improvement in simulating annual rainfall cycle and intraseasonal variability over the ISM region. These improvements in CFS-CR are likely to be associated with improvement of the convective and stratiform rainfall distribution in the model. These initiatives clearly address a long standing issue of resolving the cloud processes in climate model and demonstrate that the improved cloud and convective process paramterizations can eventually reduce the systematic bias and improve the model fidelity.

Life Cycle of Tropical Convection and Anvil in Observations and Models

NASA Astrophysics Data System (ADS)

McFarlane, S. A.; Hagos, S. M.; Comstock, J. M.

2011-12-01

Tropical convective clouds are important elements of the hydrological cycle and produce extensive cirrus anvils that strongly affect the tropical radiative energy balance. To improve simulations of the global water and energy cycles and accurately predict both precipitation and cloud radiative feedbacks, models need to realistically simulate the lifecycle of tropical convection, including the formation and radiative properties of ice anvil clouds. By combining remote sensing datasets from precipitation and cloud radars at the Atmospheric Radiation Measurement (ARM) Darwin site with geostationary satellite data, we can develop observational understanding of the lifetime of convective systems and the links between the properties of convective systems and their associated anvil clouds. The relationships between convection and anvil in model simulations can then be compared to those seen in the observations to identify areas for improvement in the model simulations. We identify and track tropical convective systems in the Tropical Western Pacific using geostationary satellite observations. We present statistics of the tropical convective systems including size, age, and intensity and classify the lifecycle stage of each system as developing, mature, or dissipating. For systems that cross over the ARM Darwin site, information on convective intensity and anvil properties are obtained from the C-Pol precipitation radar and MMCR cloud radar, respectively, and are examined as a function of the system lifecycle. Initial results from applying the convective identification and tracking algorithm to a tropical simulation from the Weather Research and Forecasting (WRF) model run show that the model produces reasonable overall statistics of convective systems, but details of the life cycle (such as diurnal cycle, system tracks) differ from the observations. Further work will focus on the role of atmospheric temperature and moisture profiles in the model's convective life cycle.

Using In Situ Observations and Satellite Retrievals to Constrain Large-Eddy Simulations and Single-Column Simulations: Implications for Boundary-Layer Cloud Parameterization in the NASA GISS GCM

NASA Astrophysics Data System (ADS)

Remillard, J.

2015-12-01

Two low-cloud periods from the CAP-MBL deployment of the ARM Mobile Facility at the Azores are selected through a cluster analysis of ISCCP cloud property matrices, so as to represent two low-cloud weather states that the GISS GCM severely underpredicts not only in that region but also globally. The two cases represent (1) shallow cumulus clouds occurring in a cold-air outbreak behind a cold front, and (2) stratocumulus clouds occurring when the region was dominated by a high-pressure system. Observations and MERRA reanalysis are used to derive specifications used for large-eddy simulations (LES) and single-column model (SCM) simulations. The LES captures the major differences in horizontal structure between the two low-cloud fields, but there are unconstrained uncertainties in cloud microphysics and challenges in reproducing W-band Doppler radar moments. The SCM run on the vertical grid used for CMIP-5 runs of the GCM does a poor job of representing the shallow cumulus case and is unable to maintain an overcast deck in the stratocumulus case, providing some clues regarding problems with low-cloud representation in the GCM. SCM sensitivity tests with a finer vertical grid in the boundary layer show substantial improvement in the representation of cloud amount for both cases. GCM simulations with CMIP-5 versus finer vertical gridding in the boundary layer are compared with observations. The adoption of a two-moment cloud microphysics scheme in the GCM is also tested in this framework. The methodology followed in this study, with the process-based examination of different time and space scales in both models and observations, represents a prototype for GCM cloud parameterization improvements.

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2017-12-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.

Top-down and Bottom-up aerosol-cloud-closure: towards understanding sources of unvertainty in deriving cloud radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, K.; Roberts, G.; Calmer, R.; Nicoll, K.; Hashimshoni, E.; Rosenfeld, D.; Ovadnevaite, J.; Preissler, J.; Ceburnis, D.; O'Dowd, C. D. D.; Russell, L. M.

2016-12-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head atmospheric research station in Galway, Ireland in August 2015. Instrument platforms include ground-based, unmanned aerial vehicles (UAV), and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction, or a 5-hole probe for 3D wind vectors. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in-situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 W m-2 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNC) were within 30% of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment, and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in-situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux.

Evaluation of a single column model at the Southern Great Plains climate research facility

NASA Astrophysics Data System (ADS)

Kennedy, Aaron D.

Despite recent advancements in global climate modeling, models produce a large range of climate sensitivities for the Earth. This range of sensitivities results in part from uncertainties in modeling clouds. To understand and to improve cloud parameterizations in Global Climate Models (GCMs), simulations should be evaluated using observations of clouds. Detailed studies can be conducted at Atmospheric Radiation Measurements (ARM) sites which provide adequate observations and forcing for Single Column Model (SCM) studies. Unfortunately, forcing for SCMs is sparse and not available for many locations or times. This study had two main goals: (1) evaluate clouds from the GISS Model E AR5 SCM at the ARM Southern Great Plains site and (2) determine whether reanalysis-based forcing was feasible at this location. To accomplish these goals, multiple model runs were conducted from 1999--2008 using forcing provided by ARM and forcing developed from the North American Regional Reanalysis (NARR). To better understand cloud biases and differences in the forcings, atmospheric states were classified using Self Organizing Maps (SOMs). Although model simulations had many similarities with the observations, there were several noticeable biases. Deep clouds had a negative bias year-round and this was attributed to clouds being too thin during frontal systems and a lack of convection during the spring and summer. These results were consistent regardless of the forcing used. During August, SCM simulations had a positive bias for low clouds. This bias varied with the forcing suggesting that part of the problem was tied to errors in the forcing. NARR forcing had many favorable characteristics when compared to ARM observations and forcing. In particular, temperature and wind information were more accurate than ARM when compared to balloon soundings. During the cool season, NARR forcing produced results similar to ARM with reasonable precipitation and a similar cloud field. Although NARR vertical velocities were weaker than ARM during the convective season, these simulations were able to capture the majority of convective events. The limiting factor for NARR was humidity biases in the upper troposphere during the summer months. Prior to releasing this forcing to the modeling community, this issue must be investigated further.

The Sensitivity of Tropical Squall Lines (GATE and TOGA COARE) to Surface Fluxes: Cloud Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Wang, Yansen; Tao, Wei-Kuo; Simpson, Joanne; Lang, Stephen

1999-01-01

Two tropical squall lines from TOGA COARE and GATE were simulated using a two-dimensional cloud-resolving model to examine the impact of surface fluxes on tropical squall line development and associated precipitation processes. The important question of how CAPE in clear and cloudy areas is maintained in the tropics is also investigated. Although the cloud structure and precipitation intensity are different between the TOGA COARE and GATE squall line cases, the effects of the surface fluxes on the amount of rainfall and on the cloud development processes are quite similar. The simulated total surface rainfall amount in the runs without surface fluxes is about 67% of the rainfall simulated with surface fluxes. The area where surface fluxes originated was categorized into clear and cloudy regions according to whether there was cloud in the vertical column. The model results indicated that the surface fluxes from the large clear air environment are the dominant moisture source for tropical squall line development even though the surface fluxes in the cloud region display a large peak. The high-energy air from the boundary layer in the clear area is what feeds the convection while the CAPE is removed by the convection. The surface rainfall was only reduced 8 to 9% percent in the simulations without surface fluxes in the cloud region. Trajectory and water budget analysis also indicated that most moisture (92%) was from the boundary layer of the clear air environment.

Use of ARM Products in Reanalysis Applications and IPCC Model Assessment

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

Walsh, John E; Chapman, William L

2011-09-30

Year-3 of the project was spent developing an observed cloud climatology for Barrow, AK and relating the observed cloud fractions to the surface circulation patterns and locally observed winds. Armed with this information, we identified errors and sources of errors of cloud fraction simulations by numerical models in the Arctic. Specifically, we compared the cloud simulations output by the North American Regional Reanalysis (NARR) to corresponding observed cloud fractions obtained by the Department of Energy's Atmospheric Radiation Measurement (ARM) program for four mid-season months: (January, April, July, and October). Reanalyses are obtained from numerical weather prediction models that are notmore » run in real-time. Instead, a reanalysis model ingests a wide variety of historical observations for the purpose of producing a gridded dataset of many model-derived quantities that are as temporally homogeneous as possible. Therefore, reanalysis output can be used as a proxy for observations, although some biases and other errors are inevitable because of model parameterizations and observational gaps. In the observational analysis we documented the seasonality of cloudiness at the north slope including cloud base height and dependence on synoptic regime. We followed this with an evaluation of the associations of wind-speed and direction and cloud amounts in both the observational record and the reanalysis model. The Barrow cloud fraction data show that clear conditions are most often associated with anomalous high pressure to the north of Barrow, especially in spring and early summer. Overcast skies are most commonly associated with anomalous low pressure to the south. The observational analysis shows that low, boundary layer clouds are the most common type of cloud observed North Slope ARM observing site. However, these near-surface clouds are a major source of errors in the NARR simulations. When compared to observations, the NARR over-simulates the fraction of low clouds during the winter months, and under-simulates the fraction of low clouds during the summer months. The NARR wind speeds at the North Slope are correlated to the observed ARM wind speeds at Barrow. The following correlations were obtained using the 3-hourly data: Jan (0.84); Apr (0.83); Jul (0.69); Oct (0.79). A negative bias (undersimulation) exists in the reanalysis wind speeds for January through July, but is typically 3ms-1 or less in magnitude. Overall, the magnitude of the wind vector is undersimulated approximately 74% of the time in the cold season months and 85% of the time July, but only about half of the time in October. Wind direction biases in the model are generally small (10-20 degrees), but they are generally in the leftward-turning direction in all months. We also synthesized NARR atmospheric output into a composite analysis of the synoptic conditions that are present when the reanalysis model fails in its simulations of Arctic cloud fractions, and similarly, those conditions present when the model simulates accurate cloud fractions. Cold season errors were highest when high pressure was located north of Barrow favoring anomalous winds and longer fetches from the northeast. In addition, larger cloud fraction biases were found on days with relatively calm winds (2-5 m/s). The most pronounced oversimulation biases associated with poorly simulated clouds occur during conditions with very low cloud-base heights (< 50 m). In contrast, the model appears more adept at capturing cloudless conditions in the spring than the winter with oversimulations occurring just 5% of the time in spring compared to 20% in the winter months. During the warm season, low level clouds are present in 32% of the time with onshore flow and less than half this frequent in offshore wind conditions. Composite sea level pressure fields indicate that clear sky conditions typically result when high pressure is centered at or near Barrow, AK. Overcast days are associated with generally lower sea level pressures near the North Slope and onshore flow from the NW in most months. Warm season errors were highest when high pressure was persistent to the north of Barrow, AK. This synoptic situation results in onshore flow for the North Slope with persistent winds from the east and northeast. In these situations, the predominant climatological synoptic situation, the NARR model under-simulates summer clouds on the North Slope. In general, the NARR often fails to capture clouds in the lowest 200 meters of the atmosphere. We conclude that the cloud model parameterization fails to cature boundary layer clouds like Arctic stratus and fog, which are observed in 65% of the undersimulations. These NARR undersimulations occur most often during onshore flow environments, such as when high pressure is located north of Barrow and the prevailing winds are from the northeast. In these cases, the airflow is along a fetch of scattered sea ice and open ocean (ice concentrations between 0 and 100%). NARR treats sea ice as a binary function. Grid cells are either considered a slap of ice cover, or totally open ocean. We note that implementing provisions for partial sea ice concentrations in the reanalysis model may help in more accurately depicting surface moisture fluxes and associated model-derived low cloud amounts.« less

Theoretical Models of Protostellar Binary and Multiple Systems with AMR Simulations

NASA Astrophysics Data System (ADS)

Matsumoto, Tomoaki; Tokuda, Kazuki; Onishi, Toshikazu; Inutsuka, Shu-ichiro; Saigo, Kazuya; Takakuwa, Shigehisa

2017-05-01

We present theoretical models for protostellar binary and multiple systems based on the high-resolution numerical simulation with an adaptive mesh refinement (AMR) code, SFUMATO. The recent ALMA observations have revealed early phases of the binary and multiple star formation with high spatial resolutions. These observations should be compared with theoretical models with high spatial resolutions. We present two theoretical models for (1) a high density molecular cloud core, MC27/L1521F, and (2) a protobinary system, L1551 NE. For the model for MC27, we performed numerical simulations for gravitational collapse of a turbulent cloud core. The cloud core exhibits fragmentation during the collapse, and dynamical interaction between the fragments produces an arc-like structure, which is one of the prominent structures observed by ALMA. For the model for L1551 NE, we performed numerical simulations of gas accretion onto protobinary. The simulations exhibit asymmetry of a circumbinary disk. Such asymmetry has been also observed by ALMA in the circumbinary disk of L1551 NE.

The simulation of molecular clouds formation in the Milky Way

NASA Astrophysics Data System (ADS)

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

2013-01-01

Using 3D hydrodynamic calculations we simulate formation of molecular clouds in the Galaxy. The simulations take into account molecular hydrogen chemical kinetics, cooling and heating processes. Comprehensive gravitational potential accounts for contributions from the stellar bulge, two- and four-armed spiral structure, stellar disc, dark halo and takes into account self-gravitation of the gaseous component. Gas clouds in our model form in the spiral arms due to shear and wiggle instabilities and turn into molecular clouds after t ≳ 100 Myr. At the times t ˜ 100-300 Myr the clouds form hierarchical structures and agglomerations with the sizes of 100 pc and greater. We analyse physical properties of the simulated clouds and find that synthetic statistical distributions like mass spectrum, `mass-size' relation and velocity dispersion are close to those observed in the Galaxy. The synthetic l-v (galactic longitude-radial velocity) diagram of the simulated molecular gas distribution resembles observed one and displays a structure with appearance similar to molecular ring of the Galaxy. Existence of this structure in our modelling can be explained by superposition of emission from the galactic bar and the spiral arms at ˜3-4 kpc.

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

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

Gao, Wenhua; Sui, Chung-Hsiung; Fan, Jiwen

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

Impact of Aerosols on Convective Clouds and Precipitation

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Jen-Ping; Li, Zhanqing; Wang, Chien; Zhang, Chidong

2012-01-01

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major agent for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. Here we review past efforts and summarize our current understanding of the effect of aerosols on convective precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations, are presented. Specifically, this paper addresses the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from largescale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions for gaining a better understanding of aerosol--cloud-precipitation interactions are suggested.

Clouds-radiation interactions in a general circulation model - Impact upon the planetary radiation balance

NASA Technical Reports Server (NTRS)

Smith, Laura D.; Vonder Haar, Thomas H.

1991-01-01

Simultaneously conducted observations of the earth radiation budget and the cloud amount estimates, taken during the June 1979 - May 1980 Nimbus 7 mission were used to show interactions between the cloud amount and raidation and to verify a long-term climate simulation obtained with the latest version of the NCAR Community Climate Model (CCM). The parameterization of the radiative, dynamic, and thermodynamic processes produced the mean radiation and cloud quantities that were in reasonable agreement with satellite observations, but at the expense of simulating their short-term fluctuations. The results support the assumption that the inclusion of the cloud liquid water (ice) variable would be the best mean to reduce the blinking of clouds in NCAR CCM.

A Method for Obtaining High Frequency, Global, IR-Based Convective Cloud Tops for Studies of the TTL

NASA Technical Reports Server (NTRS)

Pfister, Leonhard; Ueyama, Rei; Jensen, Eric; Schoeberl, Mark

2017-01-01

Models of varying complexity that simulate water vapor and clouds in the Tropical Tropopause Layer (TTL) show that including convection directly is essential to properly simulating the water vapor and cloud distribution. In boreal winter, for example, simulations without convection yield a water vapor distribution that is too uniform with longitude, as well as minimal cloud distributions. Two things are important for convective simulations. First, it is important to get the convective cloud top potential temperature correctly, since unrealistically high values (reaching above the cold point tropopause too frequently) will cause excessive hydration of the stratosphere. Second, one must capture the time variation as well, since hydration by convection depends on the local relative humidity (temperature), which has substantial variation on synoptic time scales in the TTL. This paper describes a method for obtaining high frequency (3-hourly) global convective cloud top distributions which can be used in trajectory models. The method uses rainfall thresholds, standard IR brightness temperatures, meteorological temperature analyses, and physically realistic and documented corrections IR brightness temperature corrections to derive cloud top altitudes and potential temperatures. The cloud top altitudes compare well with combined CLOUDSAT and CALIPSO data, both in time-averaged overall vertical and horizontal distributions and in individual cases (correlations of .65-.7). An important finding is that there is significant uncertainty (nearly .5 km) in evaluating the statistical distribution of convective cloud tops even using lidar. Deep convection whose tops are in regions of high relative humidity (such as much of the TTL), will cause clouds to form above the actual convection. It is often difficult to distinguish these clouds from the actual convective cloud due to the uncertainties of evaluating ice water content from lidar measurements. Comparison with models show that calculated cloud top altitudes are generally higher than those calculated by global analyses (e.g., MERRA). Interannual variability in the distribution of convective cloud top altitudes is also investigated.

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

NASA Technical Reports Server (NTRS)

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

Dynamic Turbulence Modelling in Large-eddy Simulations of the Cloud-topped Atmospheric Boundary Layer

NASA Technical Reports Server (NTRS)

Kirkpatrick, M. P.; Mansour, N. N.; Ackerman, A. S.; Stevens, D. E.

2003-01-01

The use of large eddy simulation, or LES, to study the atmospheric boundary layer dates back to the early 1970s when Deardor (1972) used a three-dimensional simulation to determine velocity and temperature scales in the convective boundary layer. In 1974 he applied LES to the problem of mixing layer entrainment (Deardor 1974) and in 1980 to the cloud-topped boundary layer (Deardor 1980b). Since that time the LES approach has been applied to atmospheric boundary layer problems by numerous authors. While LES has been shown to be relatively robust for simple cases such as a clear, convective boundary layer (Mason 1989), simulation of the cloud-topped boundary layer has proved more of a challenge. The combination of small length scales and anisotropic turbulence coupled with cloud microphysics and radiation effects places a heavy burden on the turbulence model, especially in the cloud-top region. Consequently, over the past few decades considerable effort has been devoted to developing turbulence models that are better able to parameterize these processes. Much of this work has involved taking parameterizations developed for neutral boundary layers and deriving corrections to account for buoyancy effects associated with the background stratification and local buoyancy sources due to radiative and latent heat transfer within the cloud (see Lilly 1962; Deardor 1980a; Mason 1989; MacVean & Mason 1990, for example). In this paper we hope to contribute to this effort by presenting a number of turbulence models in which the model coefficients are calculated dynamically during the simulation rather than being prescribed a priori.

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.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

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

Assessment and validation of the community radiative transfer model for ice cloud conditions

NASA Astrophysics Data System (ADS)

Yi, Bingqi; Yang, Ping; Weng, Fuzhong; Liu, Quanhua

2014-11-01

The performance of the Community Radiative Transfer Model (CRTM) under ice cloud conditions is evaluated and improved with the implementation of MODIS collection 6 ice cloud optical property model based on the use of severely roughened solid column aggregates and a modified Gamma particle size distribution. New ice cloud bulk scattering properties (namely, the extinction efficiency, single-scattering albedo, asymmetry factor, and scattering phase function) suitable for application to the CRTM are calculated by using the most up-to-date ice particle optical property library. CRTM-based simulations illustrate reasonable accuracy in comparison with the counterparts derived from a combination of the Discrete Ordinate Radiative Transfer (DISORT) model and the Line-by-line Radiative Transfer Model (LBLRTM). Furthermore, simulations of the top of the atmosphere brightness temperature with CRTM for the Crosstrack Infrared Sounder (CrIS) are carried out to further evaluate the updated CRTM ice cloud optical property look-up table.

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

Rudkevich, Aleksandr; Goldis, Evgeniy

This research conducted by the Newton Energy Group, LLC (NEG) is dedicated to the development of pCloud: a Cloud-based Power Market Simulation Environment. pCloud is offering power industry stakeholders the capability to model electricity markets and is organized around the Software as a Service (SaaS) concept -- a software application delivery model in which software is centrally hosted and provided to many users via the internet. During the Phase I of this project NEG developed a prototype design for pCloud as a SaaS-based commercial service offering, system architecture supporting that design, ensured feasibility of key architecture's elements, formed technological partnershipsmore » and negotiated commercial agreements with partners, conducted market research and other related activities and secured funding for continue development of pCloud between the end of Phase I and beginning of Phase II, if awarded. Based on the results of Phase I activities, NEG has established that the development of a cloud-based power market simulation environment within the Windows Azure platform is technologically feasible, can be accomplished within the budget and timeframe available through the Phase II SBIR award with additional external funding. NEG believes that pCloud has the potential to become a game-changing technology for the modeling and analysis of electricity markets. This potential is due to the following critical advantages of pCloud over its competition: - Standardized access to advanced and proven power market simulators offered by third parties. - Automated parallelization of simulations and dynamic provisioning of computing resources on the cloud. This combination of automation and scalability dramatically reduces turn-around time while offering the capability to increase the number of analyzed scenarios by a factor of 10, 100 or even 1000. - Access to ready-to-use data and to cloud-based resources leading to a reduction in software, hardware, and IT costs. - Competitive pricing structure, which will make high-volume usage of simulation services affordable. - Availability and affordability of high quality power simulators, which presently only large corporate clients can afford, will level the playing field in developing regional energy policies, determining prudent cost recovery mechanisms and assuring just and reasonable rates to consumers. - Users that presently do not have the resources to internally maintain modeling capabilities will now be able to run simulations. This will invite more players into the industry, ultimately leading to more transparent and liquid power markets.« less

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

NASA Astrophysics Data System (ADS)

Lenaerts, Jan T. M.; Van Tricht, Kristof; Lhermitte, Stef; L'Ecuyer, Tristan S.

2017-04-01

Clouds play a pivotal role in the surface energy budget of the polar regions. Here we use two largely independent data sets of cloud and surface downwelling radiation observations derived by satellite remote sensing (2007-2010) to evaluate simulated clouds and radiation over both polar ice sheets and oceans in state-of-the-art atmospheric reanalyses (ERA-Interim and Modern Era Retrospective-Analysis for Research and Applications-2) and the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model ensemble. First, we show that, compared to Clouds and the Earth's Radiant Energy System-Energy Balanced and Filled, CloudSat-CALIPSO better represents cloud liquid and ice water path over high latitudes, owing to its recent explicit determination of cloud phase that will be part of its new R05 release. The reanalyses and climate models disagree widely on the amount of cloud liquid and ice in the polar regions. Compared to the observations, we find significant but inconsistent biases in the model simulations of cloud liquid and ice water, as well as in the downwelling radiation components. The CMIP5 models display a wide range of cloud characteristics of the polar regions, especially with regard to cloud liquid water, limiting the representativeness of the multimodel mean. A few CMIP5 models (CNRM, GISS, GFDL, and IPSL_CM5b) clearly outperform the others, which enhances credibility in their projected future cloud and radiation changes over high latitudes. Given the rapid changes in polar regions and global feedbacks involved, future climate model developments should target improved representation of polar clouds. To that end, remote sensing observations are crucial, in spite of large remaining observational uncertainties, which is evidenced by the substantial differences between the two data sets.

A multilinear regression methodology to analyze the effect of atmospheric and surface forcing on Arctic clouds

NASA Astrophysics Data System (ADS)

Boeke, R.; Taylor, P. C.; Li, Y.

2017-12-01

Arctic cloud amount as simulated in CMIP5 models displays large intermodel spread- models disagree on the processes important for cloud formation as well as the radiative impact of clouds. The radiative response to cloud forcing can be better assessed when the drivers of Arctic cloud formation are known. Arctic cloud amount (CA) is a function of both atmospheric and surface conditions, and it is crucial to separate the influences of unique processes to understand why the models are different. This study uses a multilinear regression methodology to determine cloud changes using 3 variables as predictors: lower tropospheric stability (LTS), 500-hPa vertical velocity (ω500), and sea ice concentration (SIC). These three explanatory variables were chosen because their effects on clouds can be attributed to unique climate processes: LTS is a thermodynamic indicator of the relationship between clouds and atmospheric stability, SIC determines the interaction between clouds and the surface, and ω500 is a metric for dynamical change. Vertical, seasonal profiles of necessary variables are obtained from the Coupled Model Intercomparison Project 5 (CMIP5) historical simulation, an ocean-atmosphere couple model forced with the best-estimate natural and anthropogenic radiative forcing from 1850-2005, and statistical significance tests are used to confirm the regression equation. A unique heuristic model will be constructed for each climate model and for observations, and models will be tested by their ability to capture the observed cloud amount and behavior. Lastly, the intermodel spread in Arctic cloud amount will be attributed to individual processes, ranking the relative contributions of each factor to shed light on emergent constraints in the Arctic cloud radiative effect.

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

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional singlecolumn models in simulating various types of clouds and cloud systems from Merent geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloudscale model (termed a super-parameterization or multiscale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameteridon NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production nms will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, (2) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Simulations of Variability and Waves at Cloud Altitudes Using a Venus Middle Atmosphere General Circulation Model

NASA Astrophysics Data System (ADS)

Parish, H. F.; Mitchell, J.

2017-12-01

We have developed a Venus general circulation model, the Venus Middle atmosphere Model (VMM), to simulate the atmosphere from just below the cloud deck 40 km altitude to around 100 km altitude. Our primary goal is to assess the influence of waves on the variability of winds and temperatures observed around Venus' cloud deck. Venus' deep atmosphere is not simulated directly in the VMM model, so the effects of waves propagating upwards from the lower atmosphere is represented by forcing at the lower boundary of the model. Sensitivity tests allow appropriate amplitudes for the wave forcing to be determined by comparison with Venus Express and probe measurements and allow the influence of waves on the cloud-level atmosphere to be investigated. Observations at cloud altitudes are characterized by waves with a wide variety of periods and wavelengths, including gravity waves, thermal tides, Rossby waves, and Kelvin waves. These waves may be generated within the cloud deck by instabilities, or may propagate up from the deep atmosphere. Our development of the VMM is motivated by the fact that the circulation and dynamics between the surface and the cloud levels are not well measured and wind velocities below 40 km altitude cannot be observed remotely, so we focus on the dynamics at cloud levels and above. Initial results from the VMM with a simplified radiation scheme have been validated by comparison with Pioneer Venus and Venus Express observations and show reasonable agreement with the measurements.

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Simpson, J.; Baker, D.; Braun, S.; Chou, M.-D.; Ferrier, B.; Johnson, D.; Khain, A.; Lang, S.; Lynn, B.

2001-01-01

The response of cloud systems to their environment is an important link in a chain of processes responsible for monsoons, frontal depression, El Nino Southern Oscillation (ENSO) episodes and other climate variations (e.g., 30-60 day intra-seasonal oscillations). Numerical models of cloud properties provide essential insights into the interactions of clouds with each other, with their surroundings, and with land and ocean surfaces. Significant advances are currently being made in the modeling of rainfall and rain-related cloud processes, ranging in scales from the very small up to the simulation of an extensive population of raining cumulus clouds in a tropical- or midlatitude-storm environment. The Goddard Cumulus Ensemble (GCE) model is a multi-dimensional nonhydrostatic dynamic/microphysical cloud resolving model. It has been used to simulate many different mesoscale convective systems that occurred in various geographic locations. In this paper, recent GCE model improvements (microphysics, radiation and surface processes) will be described as well as their impact on the development of precipitation events from various geographic locations. The performance of these new physical processes will be examined by comparing the model results with observations. In addition, the explicit interactive processes between cloud, radiation and surface processes will be discussed.

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

NASA Technical Reports Server (NTRS)

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

2013-01-01

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

Ultra-clean Layers (UCLs) and Low Albedo Clouds ("gray clouds") in the Marine Boundary Layer - CSET aircraft data, 2-D bin spectral cloud parcel model, large eddy simulation and satellite observations from CALIPSO, MODIS and COSMIC

NASA Astrophysics Data System (ADS)

O, K. T.; Wood, R.; Bretherton, C. S.; Eastman, R. M.; Tseng, H. H.

2016-12-01

During the 2015 Cloud System Evolution in the Trades (CSET) field program (CSET, Jul-Aug 2015, subtropical NE Pacific), the NSF/NCAR G-V aircraft frequently encountered ultra clean layers (hereafter UCLs) with extremely low accumulation mode aerosol (i.e. diameter da> 100nm) concentration (hereafter Na), and low albedo ( 0.2) warm clouds (termed "gray clouds" in our study) with low droplet concentration (hereafter Nd). The analysis of CSET aircraft data shows that (1) UCLs and gray clouds are mostly commonly found at a height of 1.5-2km, typically close to the top of the MBL, (2) UCLs and gray cloud coverage as high as 40-60% between 135W and 155W (i.e. Sc-Cu transition region) but occur very infrequently east of 130W (i.e. shallow, near-coastal stratocumulus region), and (3) UCLs and gray clouds exhibit remarkably low turbulence compared with non-UCL clear sky and clouds. It should be noted that most previous aircraft sampling of low clouds occurred close to the Californian coast, so the prevalence of UCLs and gray clouds has not been previously noted. Based on the analysis of aircraft data, we hypothesize that gray clouds result from detrainment of cloud close to the top of precipitating trade cumuli, and UCLs are remnants of these layers when gray clouds evaporates. The simulations in our study are performed using 2-D bin spectral cloud parcel model and version 6.9 of the System for Atmospheric Modeling (SAM). Our idealized simulations suggest that collision-coalescence plays a crucial role in reducing Nd such that gray clouds can easily form via collision-coalescence in layers detrained from the cloud top at trade cumulus regime, but can not form at stratocumulus regime. Upon evaporation of gray clouds, only few accumulation mode aerosols are returned to the clear sky, leaving horizontally-extensive UCLs (i.e. clean clear sky). Analysis of CSET flight data and idealized model simulations both suggest cloud top/PBL height may play an important role in the formation of UCLs and gray clouds. In our satellite observation study, the comparison between PBL height (from COSMIC and MODIS) and fraction of low optical depth cloud (from MODIS and CALIPSO) at NEP trade cumulus regime (20-35N, 140-155W) also suggest a strong positive correlation.

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx

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

Saide, Pablo; Spak, S. N.; Carmichael, Gregory

2012-03-30

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign averaged longitudinal gradients, and highlight differences in model simulations with (W) and without wet (NW) deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptualmore » model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, including the reliability required for policy analysis and geo-engineering applications.« less

Contributions of Uncertainty in Droplet Nucleation to the Indirect Effect in Global Models

NASA Astrophysics Data System (ADS)

Rothenberg, D. A.; Wang, C.; Avramov, A.

2016-12-01

Anthropogenic aerosol perturbations to clouds and climate (the indirect effect, or AIE) contribute significant uncertainty towards understanding contemporary climate change. Despite refinements over the past two decades, modern global aerosol-climate models widely disagree on the magnitude of AIE, and wholly disagree with satellite estimates. Part of the spread in estimates of AIE arises from a lack of constraints on what exactly comprised the pre-industrial atmospheric aerosol burden, but another component is attributable to inter-model differences in simulating the chain of aerosol-cloud-precipitation processes which ultimately produce the indirect effect. Thus, one way to help constrain AIE is to thoroughly investigate the differences in aerosol-cloud processes and interactions occurring in these models. We have configured one model, the CESM/MARC, with a suite of parameterizations affecting droplet activation. Each configuration produces similar climatologies with respect to precipitation and cloud macrophysics, but shows different sensitivies to aerosol perturbation - up to 1 W/m^2 differences in AIE. Regional differences in simulated aerosol-cloud interactions, especially in marine regions with little anthropogenic pollution, contribute to the spread in these AIE estimates. The baseline pre-industrial droplet number concentration in marine regions dominated by natural aerosol strongly predicts the magnitude of each model's AIE, suggesting that targeted observations of cloud microphysical properties across different cloud regimes and their sensitivity to aerosol influences could help provide firm constraints and targets for models. Additionally, we have performed supplemental fully-coupled (atmosphere/ocean) simulations with each model configuration, allowing the model to relax to equilibrium following a change in aerosol emissions. These simulations allow us to assess the slower-timescale responses to aerosol perturbations. The spread in fast model responses (which produce the noted changes in indirect effect or forcing) gives rise to large differences in the equilibrium climate state of each configuration. We show that these changes in equilibrium climate state have implications for AIE estimates from model configurations tuned to the present-day climate.

Final Technical Report for Project "Improving the Simulation of Arctic Clouds in CCSM3"

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

Stephen J. Vavrus

2008-11-15

This project has focused on the simulation of Arctic clouds in CCSM3 and how the modeled cloud amount (and climate) can be improved substantially by altering the parameterized low cloud fraction. The new formula, dubbed 'freeezedry', alleviates the bias of excessive low clouds during polar winter by reducing the cloud amount under very dry conditions. During winter, freezedry decreases the low cloud amount over the coldest regions in high latitudes by over 50% locally and more than 30% averaged across the Arctic (Fig. 1). The cloud reduction causes an Arctic-wide drop of 15 W m{sup -2} in surface cloud radiativemore » forcing (CRF) during winter and about a 50% decrease in mean annual Arctic CRF. Consequently, wintertime surface temperatures fall by up to 4 K on land and 2-8 K over the Arctic Ocean, thus significantly reducing the model's pronounced warm bias (Fig. 1). While improving the polar climate simulation in CCSM3, freezedry has virtually no influence outside of very cold regions (Fig. 2) or during summer (Fig. 3), which are space and time domains that were not targeted. Furthermore, the simplicity of this parameterization allows it to be readily incorporated into other GCMs, many of which also suffer from excessive wintertime polar cloudiness, based on the results from the CMIP3 archive (Vavrus et al., 2008). Freezedry also affects CCSM3's sensitivity to greenhouse forcing. In a transient-CO{sub 2} experiment, the model version with freezedry warms up to 20% less in the North Polar and South Polar regions (1.5 K and 0.5 K smaller warming, respectively) (Fig. 4). Paradoxically, the muted high-latitude response occurs despite a much larger increase in cloud amount with freezedry during non-summer months (when clouds warm the surface), apparently because of the colder modern reference climate. These results of the freezedry parameterization have recently been published (Vavrus and D. Waliser, 2008: An improved parameterization for simulating Arctic cloud amount in the CCSM3 climate model. J. Climate, 21, 5673-5687.). The article also provides a novel synthesis of surface- and satellite-based Arctic cloud observations that show how much the new freezedry parameterization improves the simulated cloud amount in high latitudes (Fig. 3). Freezedry has been incorporated into the CCSM3.5 version, in which it successfully limits the excessive polar clouds, and may be used in CCSM4. Material from this work is also appearing in a synthesis article on future Arctic cloud changes (Vavrus, D. Waliser, J. Francis, and A. Schweiger, 'Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4', accepted in Climate Dynamics) and was used in a collaborative paper on Arctic cloud-sea ice coupling (Schweiger, A., R. Lindsay, S. Vavrus, and J. Francis, 2008: Relationships between Arctic sea ice and clouds during autumn. J. Climate, 21, 4799-4810.). This research was presented at the 2007 CCSM Annual Workshop, as well as the CCSM's 2007 Atmospheric Model Working Group and Polar Working Group Meetings. The findings were also shown at the 2007 Climate Change Prediction Program's Science Team Meeting. In addition, I served as an instructor at the International Arctic Research Center's (IARC) Summer School on Arctic Climate Modeling in Fairbanks this summer, where I presented on the challenges and techniques used in simulating polar clouds. I also contributed to the development of a new Arctic System Model by attending a workshop in Colorado this summer on this fledgling project. Finally, an outreach activity for the general public has been the development of an interactive web site () that displays Arctic cloud amount in the CMIP3 climate model archive under present and future scenarios. This site allows users to make polar and global maps of a variety of climate variables to investigate the individual and ensemble-mean GCM response to greenhouse warming and the extent to which models adequately represent Arctic clouds in the modern climate. This site was used extensively in the IARC summer school projects. This work has also led to a collaboration this year during a 4-month visit I made to NCAR through its Faculty Fellowship Program. I worked with scientists Marika Holland, David Bailey, Andrew Gettleman, and Jen Kay, who are researching polar climate and/or clouds. I met with this group frequently during my visit, leading to some fruitful interactions. This work led to the discovery of a tightly coupled response of clouds and sea ice during intervals of rapid sea ice loss in greenhouse simulations, as well as advising on the evolving CCSM3.5 to CCSM4 model development. This involvement with NCAR also led to a longer-term connection, as I have recently begun a two-year stint on the SSC for CCSM.« less

Impact of Resolution on Simulation of Closed Mesoscale Cellular Convection Identified by Dynamically Guided Watershed Segmentation

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

Martini, Matus N.; Gustafson, William I.; Yang, Qing

2014-11-18

Organized mesoscale cellular convection (MCC) is a common feature of marine stratocumulus that forms in response to a balance between mesoscale dynamics and smaller scale processes such as cloud radiative cooling and microphysics. We use the Weather Research and Forecasting model with chemistry (WRF-Chem) and fully coupled cloud-aerosol interactions to simulate marine low clouds during the VOCALS-REx campaign over the southeast Pacific. A suite of experiments with 3- and 9-km grid spacing indicates resolution-dependent behavior. The simulations with finer grid spacing have smaller liquid water paths and cloud fractions, while cloud tops are higher. The observed diurnal cycle is reasonablymore » well simulated. To isolate organized MCC characteristics we develop a new automated method, which uses a variation of the watershed segmentation technique that combines the detection of cloud boundaries with a test for coincident vertical velocity characteristics. This ensures that the detected cloud fields are dynamically consistent for closed MCC, the most common MCC type over the VOCALS-REx region. We demonstrate that the 3-km simulation is able to reproduce the scaling between horizontal cell size and boundary layer height seen in satellite observations. However, the 9-km simulation is unable to resolve smaller circulations corresponding to shallower boundary layers, instead producing invariant MCC horizontal scale for all simulated boundary layers depths. The results imply that climate models with grid spacing of roughly 3 km or smaller may be needed to properly simulate the MCC structure in the marine stratocumulus regions.« less

Simulations of cloud-radiation interaction using large-scale forcing derived from the CINDY/DYNAMO northern sounding array

DOE PAGES

Wang, Shuguang; Sobel, Adam H.; Fridlind, Ann; ...

2015-09-25

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 dataset derived from the DYNAMO northern sounding array observations, and carried out in a doubly-periodic domain using the Weather Research and Forecasting (WRF) model. simulatedmore » cloud properties and radiative fluxes are compared to those derived from the S-Polka radar and satellite observations. Furthermore, 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.« less

CAUSES: Attribution of Surface Radiation Biases in NWP and Climate Models near the U.S. Southern Great Plains

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

Van Weverberg, K.; Morcrette, C. J.; Petch, J.

Many numerical weather prediction (NWP) and climate models exhibit too warm lower tropospheres near the mid-latitude continents. This warm bias has been extensively studied before, but evidence about its origin remains inconclusive. Some studies point to deficiencies in the deep convective or low clouds. Other studies found an important contribution from errors in the land surface properties. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. Documenting these radiation errors is hence an important step towards understanding and alleviating themore » warm bias. This paper presents an attribution study to quantify the net radiation biases in 9 model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, integrated water vapor (IWV) and aerosols are quantified, using an array of radiation measurement stations near the ARM SGP site. Furthermore, an in depth-analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface SW radiation is overestimated (LW underestimated) in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation in all but one model, which has a dominant albedo issue. Using a cloud regime analysis, it was shown that missing deep cloud events and/or simulating deep clouds with too weak cloud-radiative effects account for most of these cloud-related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud, but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly however, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, the deep cloud problem in many models could be related to too weak convective cloud detrainment and too large precipitation efficiencies. This does not rule out that previously documented issues with the evaporative fraction contribute to the warm bias as well, since the majority of the models underestimate the surface rain rates overall, as they miss the observed large nocturnal precipitation peak.« less

Coupled fvGCM-GCE Modeling System, TRMM Latent Heating and Cloud Library

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2004-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to imiprove the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. I this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the Goddard research plan of using Weather Research Forecast (WRF) model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

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

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud- resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D Goddard Cumulus Ensemble (GCE) model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF in being developed and production runs will be conducted at the beginning of 2005. In this talk, I will present: (1) A brief review on GCE model and its applications on precipitation processes, ( 2 ) The Goddard MMF and the major difference between two existing MMFs (CSU MMF and Goddard MMF), (3) A cloud library generated by Goddard MMF, and 3D GCE model, and (4) A brief discussion on the GCE model on developing a global cloud simulator.

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part 2; TOA Radiation Budget and CREs

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.

Impact of Biomass Burning Aerosols on Cloud Formation in Coastal Regions

NASA Astrophysics Data System (ADS)

Nair, U. S.; Wu, Y.; Reid, J. S.

2017-12-01

In the tropics, shallow and deep convective cloud structures organize in hierarchy of spatial scales ranging from meso-gamma (2-20 km) to planetary scales (40,000km). At the lower end of the spectrum is shallow convection over the open ocean, whose upscale growth is dependent upon mesoscale convergence triggers. In this context, cloud systems associated with land breezes that propagate long distances into open ocean areas are important. We utilized numerical model simulations to examine the impact of biomass burning on such cloud systems in the maritime continent, specifically along the coastal regions of Sarawak. Numerical model simulations conducted using the Weather Research and Forecasting Chemistry (WRF-Chem) model show spatial patterns of smoke that show good agreement to satellite observations. Analysis of model simulations show that, during daytime the horizontal convective rolls (HCRs) that form over land play an important role in organizing transport of smoke in the coastal regions. Alternating patterns of low and high smoke concentrations that are well correlated to the wavelengths of HCRs are found in both the simulations and satellite observations. During night time, smoke transport is modulated by the land breeze circulation and a band of enhanced smoke concentration is found along the land breeze front. Biomass burning aerosols are ingested by the convective clouds that form along the land breeze and leads to changes in total water path, cloud structure and precipitation formation.

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

NASA Technical Reports Server (NTRS)

Tao, W.-K.

2006-01-01

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

Evaluation of Cirrus Cloud Simulations using ARM Data-Development of Case Study Data Set

NASA Technical Reports Server (NTRS)

Starr, David OC.; Demoz, Belay; Wang, Yansen; Lin, Ruei-Fong; Lare, Andrew; Mace, Jay; Poellot, Michael; Sassen, Kenneth; Brown, Philip

2002-01-01

Cloud-resolving models (CRMs) are being increasingly used to develop parametric treatments of clouds and related processes for use in global climate models (GCMs). CRMs represent the integrated knowledge of the physical processes acting to determine cloud system lifecycle and are well matched to typical observational data in terms of physical parameters/measurables and scale-resolved physical processes. Thus, they are suitable for direct comparison to field observations for model validation and improvement. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. The objective is to compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. Progress is assessing cloud and other environmental conditions will be described. Results of preliminary simulations using a regional cloud system model (MM5) and a CRM will be discussed. Focal science questions for the model comparison are strongly based on results of the idealized GCSS WG2 cirrus cloud model comparison projects (Idealized Cirrus Cloud Model Comparison Project and Cirrus Parcel Model Comparison Project), which will also be briefly summarized.

Production of Lightning NO(x) and its Vertical Distribution Calculated from 3-D Cloud-scale Chemical Transport Model Simulations

NASA Technical Reports Server (NTRS)

Ott, Lesley; Pickering, Kenneth; Stenchikov, Georgiy; Allen, Dale; DeCaria, Alex; Ridley, Brian; Lin, Ruei-Fong; Lang, Steve; Tao, Wei-Kuo

2009-01-01

A 3-D cloud scale chemical transport model that includes a parameterized source of lightning NO(x), based on observed flash rates has been used to simulate six midlatitude and subtropical thunderstorms observed during four field projects. Production per intracloud (P(sub IC) and cloud-to-ground (P(sub CG)) flash is estimated by assuming various values of P(sub IC) and P(sub CG) for each storm and determining which production scenario yields NO(x) mixing ratios that compare most favorably with in-cloud aircraft observations. We obtain a mean P(sub CG) value of 500 moles NO (7 kg N) per flash. The results of this analysis also suggest that on average, P(sub IC) may be nearly equal to P(sub CG), which is contrary to the common assumption that intracloud flashes are significantly less productive of NO than are cloud-to-ground flashes. This study also presents vertical profiles of the mass of lightning NO(x), after convection based on 3-D cloud-scale model simulations. The results suggest that following convection, a large percentage of lightning NO(x), remains in the middle and upper troposphere where it originated, while only a small percentage is found near the surface. The results of this work differ from profiles calculated from 2-D cloud-scale model simulations with a simpler lightning parameterization that were peaked near the surface and in the upper troposphere (referred to as a "C-shaped" profile). The new model results (a backward C-shaped profile) suggest that chemical transport models that assume a C-shaped vertical profile of lightning NO(x) mass may place too much mass neat the surface and too little in the middle troposphere.

Analysis and numerical simulation of a laboratory analog of radiatively induced cloud-top entrainment.

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

Kerstein, Alan R.; Sayler, Bentley J.; Wunsch, Scott Edward

2010-11-01

Numerical simulations using the One-Dimensional-Turbulence model are compared to water-tank measurements [B. J. Sayler and R. E. Breidenthal, J. Geophys. Res. 103 (D8), 8827 (1998)] emulating convection and entrainment in stratiform clouds driven by cloud-top cooling. Measured dependences of the entrainment rate on Richardson number, molecular transport coefficients, and other experimental parameters are reproduced. Additional parameter variations suggest more complicated dependences of the entrainment rate than previously anticipated. A simple algebraic model indicates the ways in which laboratory and cloud entrainment behaviors might be similar and different.

Progress Towards Achieving the Challenge of Indian Summer Monsoon Climate Simulation in a Coupled Ocean-Atmosphere Model

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.

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

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.

Trusted computing strengthens cloud authentication.

PubMed

Ghazizadeh, Eghbal; Zamani, Mazdak; Ab Manan, Jamalul-lail; Alizadeh, Mojtaba

2014-01-01

Cloud computing is a new generation of technology which is designed to provide the commercial necessities, solve the IT management issues, and run the appropriate applications. Another entry on the list of cloud functions which has been handled internally is Identity Access Management (IAM). Companies encounter IAM as security challenges while adopting more technologies became apparent. Trust Multi-tenancy and trusted computing based on a Trusted Platform Module (TPM) are great technologies for solving the trust and security concerns in the cloud identity environment. Single sign-on (SSO) and OpenID have been released to solve security and privacy problems for cloud identity. This paper proposes the use of trusted computing, Federated Identity Management, and OpenID Web SSO to solve identity theft in the cloud. Besides, this proposed model has been simulated in .Net environment. Security analyzing, simulation, and BLP confidential model are three ways to evaluate and analyze our proposed model.

Trusted Computing Strengthens Cloud Authentication

PubMed Central

2014-01-01

Cloud computing is a new generation of technology which is designed to provide the commercial necessities, solve the IT management issues, and run the appropriate applications. Another entry on the list of cloud functions which has been handled internally is Identity Access Management (IAM). Companies encounter IAM as security challenges while adopting more technologies became apparent. Trust Multi-tenancy and trusted computing based on a Trusted Platform Module (TPM) are great technologies for solving the trust and security concerns in the cloud identity environment. Single sign-on (SSO) and OpenID have been released to solve security and privacy problems for cloud identity. This paper proposes the use of trusted computing, Federated Identity Management, and OpenID Web SSO to solve identity theft in the cloud. Besides, this proposed model has been simulated in .Net environment. Security analyzing, simulation, and BLP confidential model are three ways to evaluate and analyze our proposed model. PMID:24701149

SST Variation Due to Interactive Convective-Radiative Processes

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shie, C.-L.; Johnson, D.; Simpson, J.; Li, X.; Sui, C.-H.

2000-01-01

The recent linking of Cloud-Resolving Models (CRMs) to Ocean-Mixed Layer (OML) models has provided a powerful new means of quantifying the role of cloud systems in ocean-atmosphere coupling. This is due to the fact that the CRM can better resolve clouds and cloud systems and allow for explicit cloud-radiation interaction. For example, Anderson (1997) applied an atmospheric forcing associated with a CRM simulated squall line to a 3-D OML model (one way or passive interaction). His results suggested that the spatial variability resulting from the squall forcing can last at least 24 hours when forced with otherwise spatially uniform fluxes. In addition, the sea surface salinity (SSS) variability continuously decreased following the forcing, while some of the SST variability remained when a diurnal mixed layer capped off the surface structure. The forcing used in the OML model, however, focused on shorter time (8 h) and smaller spatial scales (100-120 km). In this study, the 3-D Goddard Cumulus Ensemble Model (GCE; 512 x 512 x 23 cu km, 2-km horizontal resolution) is used to simulate convective active episodes occurring in the Western Pacific warm pool and Eastern Atlantic regions. The model is integrated for seven days, and the simulated results are coupled to an OML model to better understand the impact of precipitation and changes in the planetary boundary layer upon SST variation. We will specifically examine and compare the results of linking the OML model with various spatially-averaged outputs from GCE simulations (i.e., 2 km vs. 10-50 km horizontal resolutions), in order to help understand the SST sensitivity to multi-scale influences. This will allow us to assess the importance of explicitly simulated deep and shallow clouds, as well as the subgrid-scale effects (in coarse-model runs) upon SST variation. Results using both 1-D and 2-D OML models will be evaluated to assess the effects of horizontal advection.

A Fast Synthetic Aperture Radar Raw Data Simulation Using Cloud Computing

PubMed Central

Li, Zhixin; Su, Dandan; Zhu, Haijiang; Li, Wei; Zhang, Fan; Li, Ruirui

2017-01-01

Synthetic Aperture Radar (SAR) raw data simulation is a fundamental problem in radar system design and imaging algorithm research. The growth of surveying swath and resolution results in a significant increase in data volume and simulation period, which can be considered to be a comprehensive data intensive and computing intensive issue. Although several high performance computing (HPC) methods have demonstrated their potential for accelerating simulation, the input/output (I/O) bottleneck of huge raw data has not been eased. In this paper, we propose a cloud computing based SAR raw data simulation algorithm, which employs the MapReduce model to accelerate the raw data computing and the Hadoop distributed file system (HDFS) for fast I/O access. The MapReduce model is designed for the irregular parallel accumulation of raw data simulation, which greatly reduces the parallel efficiency of graphics processing unit (GPU) based simulation methods. In addition, three kinds of optimization strategies are put forward from the aspects of programming model, HDFS configuration and scheduling. The experimental results show that the cloud computing based algorithm achieves 4× speedup over the baseline serial approach in an 8-node cloud environment, and each optimization strategy can improve about 20%. This work proves that the proposed cloud algorithm is capable of solving the computing intensive and data intensive issues in SAR raw data simulation, and is easily extended to large scale computing to achieve higher acceleration. PMID:28075343

Evaluation of Cloud-Resolving Model Intercomparison Simulations Using TWP-ICE Observations: Precipitation and Cloud Structure

NASA Technical Reports Server (NTRS)

Varble, Adam; Fridlind, Ann M.; Zipser, Edward J.; Ackerman, Andrew S.; Chaboureau, Jean-Pierre; Fan, Jiwen; Hill, Adrian; McFarlane, Sally A.; Pinty, Jean-Pierre; Shipway, Ben

2011-01-01

The Tropical Warm Pool.International Cloud Experiment (TWP ]ICE) provided extensive observational data sets designed to initialize, force, and constrain atmospheric model simulations. In this first of a two ]part study, precipitation and cloud structures within nine cloud ]resolving model simulations are compared with scanning radar reflectivity and satellite infrared brightness temperature observations during an active monsoon period from 19 to 25 January 2006. Seven of nine simulations overestimate convective area by 20% or more leading to general overestimation of convective rainfall. This is balanced by underestimation of stratiform rainfall by 5% to 50% despite overestimation of stratiform area by up to 65% because of a preponderance of very low stratiform rain rates in all simulations. All simulations fail to reproduce observed radar reflectivity distributions above the melting level in convective regions and throughout the troposphere in stratiform regions. Observed precipitation ]sized ice reaches higher altitudes than simulated precipitation ]sized ice despite some simulations that predict lower than observed top ]of ]atmosphere infrared brightness temperatures. For the simulations that overestimate radar reflectivity aloft, graupel is the cause with one ]moment microphysics schemes whereas snow is the cause with two ]moment microphysics schemes. Differences in simulated radar reflectivity are more highly correlated with differences in mass mean melted diameter (Dm) than differences in ice water content. Dm is largely dependent on the mass ]dimension relationship and gamma size distribution parameters such as size intercept (N0) and shape parameter (m). Having variable density, variable N0, or m greater than zero produces radar reflectivities closest to those observed.

Cloud-based simulations on Google Exacycle reveal ligand modulation of GPCR activation pathways

NASA Astrophysics Data System (ADS)

Kohlhoff, Kai J.; Shukla, Diwakar; Lawrenz, Morgan; Bowman, Gregory R.; Konerding, David E.; Belov, Dan; Altman, Russ B.; Pande, Vijay S.

2014-01-01

Simulations can provide tremendous insight into the atomistic details of biological mechanisms, but micro- to millisecond timescales are historically only accessible on dedicated supercomputers. We demonstrate that cloud computing is a viable alternative that brings long-timescale processes within reach of a broader community. We used Google's Exacycle cloud-computing platform to simulate two milliseconds of dynamics of a major drug target, the G-protein-coupled receptor β2AR. Markov state models aggregate independent simulations into a single statistical model that is validated by previous computational and experimental results. Moreover, our models provide an atomistic description of the activation of a G-protein-coupled receptor and reveal multiple activation pathways. Agonists and inverse agonists interact differentially with these pathways, with profound implications for drug design.

Uncertainties of Large-Scale Forcing Caused by Surface Turbulence Flux Measurements and the Impacts on Cloud Simulations at the ARM SGP Site

NASA Astrophysics Data System (ADS)

Tang, S.; Xie, S.; Tang, Q.; Zhang, Y.

2017-12-01

Two types of instruments, the eddy correlation flux measurement system (ECOR) and the energy balance Bowen ratio system (EBBR), are used at the Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP) site to measure surface latent and sensible fluxes. ECOR and EBBR typically sample different land surface types, and the domain-mean surface fluxes derived from ECOR and EBBR are not always consistent. The uncertainties of the surface fluxes will have impacts on the derived large-scale forcing data and further affect the simulations of single-column models (SCM), cloud-resolving models (CRM) and large-eddy simulation models (LES), especially for the shallow-cumulus clouds which are mainly driven by surface forcing. This study aims to quantify the uncertainties of the large-scale forcing caused by surface turbulence flux measurements and investigate the impacts on cloud simulations using long-term observations from the ARM SGP site.

Coupled fvGCM-GCE Modeling System: TRMM Latent Heating and Cloud Library

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2005-01-01

Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that cloud-resolving models (CRMs) agree with observations better than traditional single-column models in simulating various types of clouds and cloud systems from different geographic locations. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a super-parameterization or multi-scale modeling framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign cloud related datasets can provide initial conditions as well as validation for both the MMF and CRMs. A seed fund is available at NASA Goddard to build a MMF based on the 2D GCE model and the Goddard finite volume general circulation model (fvGCM). A prototype MMF will be developed by the end of 2004 and production runs will be conducted at the beginning of 2005. The purpose of this proposal is to augment the current Goddard MMF and other cloud modeling activities. In this talk, I will present: (1) A summary of the second Cloud Modeling Workshop took place at NASA Goddard, (2) A summary of the third TRMM Latent Heating Workshop took place at Nara Japan, (3) A brief discussion on the GCE model on developing a global cloud simulator.

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

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

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.

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

A cloud-evaporation parameterization for general ciculation models

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

Schlesinger, M.E.; Oh, J.H.

1993-04-01

An evaporation-zone (EZ) model for cloud evaporation is developed. In this model a cloud consists of I [open quotes]cloudlets,[close quotes] each comprising cloud droplets with radii from zero to r[sub max], the latter value depending on the drop size distribution (DSD). Evaporation occurs only within the EZ comprised of J[le]I cloudlets. When the cloudlet at cloud edge evaporates, the EZ progresses one cloudlet into the cloud's interior. This eventually results in evaporation of the cloud in time t[sub E] = K(H/h)r[sup 2][sub max](1[minus]S[sub e])[sup [minus]1] where H is the cloud thickness, h the EZ thickness, S[sub e] the environmental saturationmore » ratio, and K a constant. Values of t[sub E](1[minus]S[sub e]) versus h are presented for eight observed DSDs. For use in atmospheric general circulation models (GCMs), the cloud evaporation process is represented by dm/dt=[minus](1[minus]S[sub e])m/[tau], where m is the cloud-water mixing ratio and [tau]=K(H/h)r[sup 2][sub max]n[sup [minus]1]. With parameter n chosen sufficiently large, a GCM cloud will evaporate virtually entirely in time t[sub E], for example, 99.3% for n = 5. Values of [tau] for use in the multilayer atmospheric CRCM have been determined by performing ten perpetual-January simulations and ten perpetual-July simulations, each set of ten for prescribed pairs of [tau] values for stratiform ([tau][sub s]) and cumuloform ([tau][sub c]) clouds. An optimum choice of [tau][sub s] and [tau][sub c], based on minimizing the errors of the model's simulated cloudiness, planetary albedo, outgoing longwave radiation, and precipitation, is [tau][sub s]=[tau][sub c] = 3 min. This corresponds to t[sub E](1-S[sub e]) = 15 min for both stratiform and cumuloform clouds; hence, to an EZ thickness of about 0.6-0.8 m for stratus, stratocumulus, and altostratus clouds, 2-3 m for nimbostratus and cumulus clouds, and 17 m for cumulonimbus clouds. 18 refs., 6 figs.« less

Simulation of the Pinatubo aerosol cloud in general circulation model

NASA Technical Reports Server (NTRS)

Boville, Byron A.; Holton, James R.; Mote, Philip W.

1991-01-01

The global transport and dispersion of the Pinatubo aerosol cloud are simulated by means of a high-resolution stratospheric version of the NCAR Community Climate Model (CCM2) with an annual cycle. A passive tracer was injected into the model stratosphere over the Philippine Islands on June 15, and the transport was simulated for 180 d using an accurate semi-Lagrangian advection scheme. The simulated volcanic aerosol cloud initially drifted westward and expanded in longitude and latitude. The bulk of the aerosol cloud dispersed zonally to form a continuous belt in longitude, and remained confined to the tropics, centered near the 20-mb level for the entire 180-d model run, although a small amount was transported episodically into the upper troposphere in association with convective disturbances. Aerosol transported to the troposphere was dispersed within a few weeks into the Northern Hemisphere extratropics. In the Southern Hemisphere, the aerosol was mixed into the region equatorward of the core of the polar night jet during the first 50 d, but penetration into southern polar latitudes was delayed until the final warming in November.

An application of statistical mechanics for representing equilibrium perimeter distributions of tropical convective clouds

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.

Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2013-01-01

We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System), a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

Cloud Model Bat Algorithm

PubMed Central

Zhou, Yongquan; Xie, Jian; Li, Liangliang; Ma, Mingzhi

2014-01-01

Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodeling echolocation model based on living and preying characteristics of bats, utilizing the transformation theory of cloud model to depict the qualitative concept: “bats approach their prey.” Furthermore, Lévy flight mode and population information communication mechanism of bats are introduced to balance the advantage between exploration and exploitation. The simulation results show that the cloud model bat algorithm has good performance on functions optimization. PMID:24967425

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

Low-cloud response to a warmer climate is still pointed out as being the largest source of uncertainty in the last generation of climate models. To date there is no consensus among the models on whether the tropical low cloudiness would increase or decrease in a warmer climate. In addition, it has been shown that - depending on their climate sensitivity - the models either predict deeper or shallower low clouds. Recently, several relationships between inter-model characteristics of the present-day climate and future climate changes have been highlighted. These so-called emergent constraints aim to target relevant model improvements and to constrain models' projections based on current climate observations. Here we propose to use - for the first time - 10 years of CALIPSO cloud statistics to assess the ability of the models to represent the vertical structure of tropical low clouds for abnormally warm SST. We use a simulator approach to compare observations and simulations and focus on the low-layered clouds (i.e. z < 3.2km) as well the more detailed level perspective of clouds (40 levels from 0 to 19km). Results show that in most models an increase of the SST leads to a decrease of the low-layer cloud fraction. Vertically, the clouds deepen namely by decreasing the cloud fraction in the lowest levels and increasing it around the top of the boundary-layer. This feature is coincident with an increase of the high-level cloud fraction (z > 6.5km). Although the models' spread is large, the multi-model mean captures the observed variations but with a smaller amplitude. We then employ the GISS model to investigate how changes in cloud parameterizations affect the response of low clouds to warmer SSTs on the one hand; and how they affect the variations of the model's cloud profiles with respect to environmental parameters on the other hand. Finally, we use CALIPSO observations to constrain the model by determining i) what set of parameters allows reproducing the observed relationships and ii) what are the consequences on the cloud feedbacks. These results point toward process-oriented constraints of low-cloud responses to surface warming and environmental parameters.

Low Cloud Feedback to Surface Warming in the World's First Global Climate Model with Explicit Embedded Boundary Layer Turbulence

NASA Astrophysics Data System (ADS)

Parishani, H.; Pritchard, M. S.; Bretherton, C. S.; Wyant, M. C.; Khairoutdinov, M.; Singh, B.

2017-12-01

Biases and parameterization formulation uncertainties in the representation of boundary layer clouds remain a leading source of possible systematic error in climate projections. Here we show the first results of cloud feedback to +4K SST warming in a new experimental climate model, the ``Ultra-Parameterized (UP)'' Community Atmosphere Model, UPCAM. We have developed UPCAM as an unusually high-resolution implementation of cloud superparameterization (SP) in which a global set of cloud resolving arrays is embedded in a host global climate model. In UP, the cloud-resolving scale includes sufficient internal resolution to explicitly generate the turbulent eddies that form marine stratocumulus and trade cumulus clouds. This is computationally costly but complements other available approaches for studying low clouds and their climate interaction, by avoiding parameterization of the relevant scales. In a recent publication we have shown that UP, while not without its own complexity trade-offs, can produce encouraging improvements in low cloud climatology in multi-month simulations of the present climate and is a promising target for exascale computing (Parishani et al. 2017). Here we show results of its low cloud feedback to warming in multi-year simulations for the first time. References: Parishani, H., M. S. Pritchard, C. S. Bretherton, M. C. Wyant, and M. Khairoutdinov (2017), Toward low-cloud-permitting cloud superparameterization with explicit boundary layer turbulence, J. Adv. Model. Earth Syst., 9, doi:10.1002/2017MS000968.

Intercomparison of Large-Eddy Simulations of Arctic Mixed-Phase Clouds: Importance of Ice Size Distribution Assumptions

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;

Improving and Understanding Climate Models: Scale-Aware Parameterization of Cloud Water Inhomogeneity and Sensitivity of MJO Simulation to Physical Parameters in a Convection Scheme

NASA Astrophysics Data System (ADS)

Xie, Xin

Microphysics and convection parameterizations are two key components in a climate model to simulate realistic climatology and variability of cloud distribution and the cycles of energy and water. When a model has varying grid size or simulations have to be run with different resolutions, scale-aware parameterization is desirable so that we do not have to tune model parameters tailored to a particular grid size. The subgrid variability of cloud hydrometers is known to impact microphysics processes in climate models and is found to highly depend on spatial scale. A scale- aware liquid cloud subgrid variability parameterization is derived and implemented in the Community Earth System Model (CESM) in this study using long-term radar-based ground measurements from the Atmospheric Radiation Measurement (ARM) program. When used in the default CESM1 with the finite-volume dynamic core where a constant liquid inhomogeneity parameter was assumed, the newly developed parameterization reduces the cloud inhomogeneity in high latitudes and increases it in low latitudes. This is due to both the smaller grid size in high latitudes, and larger grid size in low latitudes in the longitude-latitude grid setting of CESM as well as the variation of the stability of the atmosphere. The single column model and general circulation model (GCM) sensitivity experiments show that the new parameterization increases the cloud liquid water path in polar regions and decreases it in low latitudes. Current CESM1 simulation suffers from the bias of both the pacific double ITCZ precipitation and weak Madden-Julian oscillation (MJO). Previous studies show that convective parameterization with multiple plumes may have the capability to alleviate such biases in a more uniform and physical way. A multiple-plume mass flux convective parameterization is used in Community Atmospheric Model (CAM) to investigate the sensitivity of MJO simulations. We show that MJO simulation is sensitive to entrainment rate specification. We found that shallow plumes can generate and sustain the MJO propagation in the model.

Simulating the evolution of optically dark HI clouds in the Virgo cluster : will no-one rid me of this turbulent sphere ?

NASA Astrophysics Data System (ADS)

Taylor, R.; Wünsch, R.; Palouš, J.

2018-05-01

Most detected neutral atomic hydrogen (HI) at low redshift is associated with optically bright galaxies. However, a handful of HI clouds are known which appear to be optically dark and have no nearby potential progenitor galaxies, making tidal debris an unlikely explanation. In particular, 6 clouds identified by the Arecibo Galaxy Environment Survey are interesting due to the combination of their small size, isolation, and especially their broad line widths atypical of other such clouds. A recent suggestion is that these clouds exist in pressure equilibrium with the intracluster medium, with the line width arising from turbulent internal motions. Here we explore that possibility by using the FLASH code to perform a series of 3D hydro simulations. Our clouds are modelled using spherical Gaussian density profiles, embedded in a hot, low-density gas representing the intracluster medium. The simulations account for heating and cooling of the gas, and we vary the structure and strength of their internal motions. We create synthetic HI spectra, and find that none of our simulations reproduce the observed cloud parameters for longer than ˜100 Myr : the clouds either collapse, disperse, or experience rapid heating which would cause ionisation and render them undetectable to HI surveys. While the turbulent motions required to explain the high line widths generate structures which appear to be inherently unstable, making this an unlikely explanation for the observed clouds, these simulations demonstrate the importance of including the intracluster medium in any model seeking to explain the existence of these objects.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-09-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-11-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Radiative Feedback of Forming Star Clusters on Their GMC Environments: Theory and Simulation

NASA Astrophysics Data System (ADS)

Howard, C. S.; Pudritz, R. E.; Harris, W. E.

2013-07-01

Star clusters form from dense clumps within a molecular cloud. Radiation from these newly formed clusters feeds back on their natal molecular cloud through heating and ionization which ultimately stops gas accretion into the cluster. Recent studies suggest that radiative feedback effects from a single cluster may be sufficient to disrupt an entire cloud over a short timescale. Simulating cluster formation on a large scale, however, is computationally demanding due to the high number of stars involved. For this reason, we present a model for representing the radiative output of an entire cluster which involves randomly sampling an initial mass function (IMF) as the cluster accretes mass. We show that this model is able to reproduce the star formation histories of observed clusters. To examine the degree to which radiative feedback shapes the evolution of a molecular cloud, we use the FLASH adaptive-mesh refinement hydrodynamics code to simulate cluster formation in a turbulent cloud. Unlike previous studies, sink particles are used to represent a forming cluster rather than individual stars. Our cluster model is then coupled with a raytracing scheme to treat radiative transfer as the clusters grow in mass. This poster will outline the details of our model and present preliminary results from our 3D hydrodynamical simulations.

A Fast Visible-Infrared Imaging Radiometer Suite Simulator for Cloudy Atmopheres

NASA Technical Reports Server (NTRS)

Liu, Chao; Yang, Ping; Nasiri, Shaima L.; Platnick, Steven; Meyer, Kerry G.; Wang, Chen Xi; Ding, Shouguo

2015-01-01

A fast instrument simulator is developed to simulate the observations made in cloudy atmospheres by the Visible Infrared Imaging Radiometer Suite (VIIRS). The correlated k-distribution (CKD) technique is used to compute the transmissivity of absorbing atmospheric gases. The bulk scattering properties of ice clouds used in this study are based on the ice model used for the MODIS Collection 6 ice cloud products. Two fast radiative transfer models based on pre-computed ice cloud look-up-tables are used for the VIIRS solar and infrared channels. The accuracy and efficiency of the fast simulator are quantify in comparison with a combination of the rigorous line-by-line (LBLRTM) and discrete ordinate radiative transfer (DISORT) models. Relative errors are less than 2 for simulated TOA reflectances for the solar channels and the brightness temperature differences for the infrared channels are less than 0.2 K. The simulator is over three orders of magnitude faster than the benchmark LBLRTM+DISORT model. Furthermore, the cloudy atmosphere reflectances and brightness temperatures from the fast VIIRS simulator compare favorably with those from VIIRS observations.

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)].

Cirrus cloud model parameterizations: Incorporating realistic ice particle generation

NASA Technical Reports Server (NTRS)

Sassen, Kenneth; Dodd, G. C.; Starr, David OC.

1990-01-01

Recent cirrus cloud modeling studies have involved the application of a time-dependent, two dimensional Eulerian model, with generalized cloud microphysical parameterizations drawn from experimental findings. For computing the ice versus vapor phase changes, the ice mass content is linked to the maintenance of a relative humidity with respect to ice (RHI) of 105 percent; ice growth occurs both with regard to the introduction of new particles and the growth of existing particles. In a simplified cloud model designed to investigate the basic role of various physical processes in the growth and maintenance of cirrus clouds, these parametric relations are justifiable. In comparison, the one dimensional cloud microphysical model recently applied to evaluating the nucleation and growth of ice crystals in cirrus clouds explicitly treated populations of haze and cloud droplets, and ice crystals. Although these two modeling approaches are clearly incompatible, the goal of the present numerical study is to develop a parametric treatment of new ice particle generation, on the basis of detailed microphysical model findings, for incorporation into improved cirrus growth models. For example, the relation between temperature and the relative humidity required to generate ice crystals from ammonium sulfate haze droplets, whose probability of freezing through the homogeneous nucleation mode are a combined function of time and droplet molality, volume, and temperature. As an example of this approach, the results of cloud microphysical simulations are presented showing the rather narrow domain in the temperature/humidity field where new ice crystals can be generated. The microphysical simulations point out the need for detailed CCN studies at cirrus altitudes and haze droplet measurements within cirrus clouds, but also suggest that a relatively simple treatment of ice particle generation, which includes cloud chemistry, can be incorporated into cirrus cloud growth.

Retrieval of cloud microphysical parameters from INSAT-3D: a feasibility study using radiative transfer simulations

NASA Astrophysics Data System (ADS)

Jinya, John; Bipasha, Paul S.

2016-05-01

Clouds strongly modulate the Earths energy balance and its atmosphere through their interaction with the solar and terrestrial radiation. They interact with radiation in various ways like scattering, emission and absorption. By observing these changes in radiation at different wavelength, cloud properties can be estimated. Cloud properties are of utmost importance in studying different weather and climate phenomena. At present, no satellite provides cloud microphysical parameters over the Indian region with high temporal resolution. INSAT-3D imager observations in 6 spectral channels from geostationary platform offer opportunity to study continuous cloud properties over Indian region. Visible (0.65 μm) and shortwave-infrared (1.67 μm) channel radiances can be used to retrieve cloud microphysical parameters such as cloud optical thickness (COT) and cloud effective radius (CER). In this paper, we have carried out a feasibility study with the objective of cloud microphysics retrieval. For this, an inter-comparison of 15 globally available radiative transfer models (RTM) were carried out with the aim of generating a Look-up- Table (LUT). SBDART model was chosen for the simulations. The sensitivity of each spectral channel to different cloud properties was investigated. The inputs to the RT model were configured over our study region (50°S - 50°N and 20°E - 130°E) and a large number of simulations were carried out using random input vectors to generate the LUT. The determination of cloud optical thickness and cloud effective radius from spectral reflectance measurements constitutes the inverse problem and is typically solved by comparing the measured reflectances with entries in LUT and searching for the combination of COT and CER that gives the best fit. The products are available on the website www.mosdac.gov.in

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

NASA Technical Reports Server (NTRS)

Matsui, T.; Santanello, J.; Shi, J. J.; Tao, W.-K.; Wu, D.; Peters-Lidard, C.; Kemp, E.; Chin, M.; Starr, D.; Sekiguchi, M.;

Understanding Ice Supersaturation, Particle Growth, and Number Concentration in Cirrus Clouds

NASA Technical Reports Server (NTRS)

Comstock, Jennifer M.; Lin, Ruei-Fong; Starr, David O'C.; Yang, Ping

2008-01-01

Many factors control the ice supersaturation and microphysical properties in cirrus clouds. We explore the effects of dynamic forcing, ice nucleation mechanisms, and ice crystal growth rate on the evolution and distribution of water vapor and cloud properties in nighttime cirrus clouds using a one-dimensional cloud model with bin microphysics and remote sensing measurements obtained at the Department of Energy's Atmospheric Radiation Measurement (ARM) Climate Research Facility located near Lamont, OK. We forced the model using both large-scale vertical ascent and, for the first time, mean mesoscale velocity derived from radar Doppler velocity measurements. Both heterogeneous and homogeneous nucleation processes are explored, where a classical theory heterogeneous scheme is compared with empirical representations. We evaluated model simulations by examining both bulk cloud properties and distributions of measured radar reflectivity, lidar extinction, and water vapor profiles, as well as retrieved cloud microphysical properties. Our results suggest that mesoscale variability is the primary mechanism needed to reproduce observed quantities. Model sensitivity to the ice growth rate is also investigated. The most realistic simulations as compared with observations are forced using mesoscale waves, include fast ice crystal growth, and initiate ice by either homogeneous or heterogeneous nucleation. Simulated ice crystal number concentrations (tens to hundreds particles per liter) are typically two orders of magnitude smaller than previously published results based on aircraft measurements in cirrus clouds, although higher concentrations are possible in isolated pockets within the nucleation zone.

Three-dimensional simulations of cumulus congestus clouds on GATE day 261

NASA Technical Reports Server (NTRS)

Simpson, J.; Van Helvoirt, G.; Mccumber, M.

1982-01-01

Schlesinger's (1978) three-dimensional cumulus model is applied to showering congestus clouds on day 261 of GATE. Model results are compared with each other and with observations to analyze the effects of varying shear and altered sounding. Relationships between shear, mesovortices and dynamic entrainment are examined, as well as the model clouds' impact on the environment as a function of shear. The simulations appear to resemble reality in many important aspects. Altostratus layers observed on day 261 are found to be a by-product of convection in three-dimensional shear. Rapid erosion of cloud base to 3.6 km is related to the ambient thermal structure, with wind shear and initial perturbation playing a secondary role. Some of the apparent conflict regarding lateral versus cloud-top entrainment is clarified, as well as some factors governing convective downdraft structure and intensity.

The impact of low-level cloud over the eastern subtropical Pacific on the ``Double ITCZ'' in LASG FGCM-0

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.

Large Eddy Simulation of Cirrus Clouds

NASA Technical Reports Server (NTRS)

Wu, Ting; Cotton, William R.

1999-01-01

The Regional Atmospheric Modeling System (RAMS) with mesoscale interactive nested-grids and a Large-Eddy Simulation (LES) version of RAMS, coupled to two-moment microphysics and a new two-stream radiative code were used to investigate the dynamic, microphysical, and radiative aspects of the November 26, 1991 cirrus event. Wu (1998) describes the results of that research in full detail and is enclosed as Appendix 1. The mesoscale nested grid simulation successfully reproduced the large scale circulation as compared to the Mesoscale Analysis and Prediction System's (MAPS) analyses and other observations. Three cloud bands which match nicely to the three cloud lines identified in an observational study (Mace et al., 1995) are predicted on Grid #2 of the nested grids, even though the mesoscale simulation predicts a larger west-east cloud width than what was observed. Large-eddy simulations (LES) were performed to study the dynamical, microphysical, and radiative processes in the 26 November 1991 FIRE 11 cirrus event. The LES model is based on the RAMS version 3b developed at Colorado State University. It includes a new radiation scheme developed by Harrington (1997) and a new subgrid scale model developed by Kosovic (1996). The LES model simulated a single cloud layer for Case 1 and a two-layer cloud structure for Case 2. The simulations demonstrated that latent heat release can play a significant role in the formation and development of cirrus clouds. For the thin cirrus in Case 1, the latent heat release was insufficient for the cirrus clouds to become positively buoyant. However, in some special cases such as Case 2, positively buoyant cells can be embedded within the cirrus layers. These cells were so active that the rising updraft induced its own pressure perturbations that affected the cloud evolution. Vertical profiles of the total radiative and latent heating rates indicated that for well developed, deep, and active cirrus clouds, radiative cooling and latent heating could be comparable in magnitude in the cloudy layer. This implies that latent heating cannot be neglected in the construction of a cirrus cloud model. The probability density function (PDF) of w was analyzed to assist in the parameterization of cloud-scale velocities in large-scale models. For the more radiatively-driven, thin cirrus case, the PDFs are approximately Gaussian. However, in the interior of the deep, convectively unstable case, the PDFs of w are multi-modal and very broad, indicating that parameterizing cloud-scale motions for such clouds can be very challenging. The results of this research are described in detail in a paper submitted to the Journal of Atmospheric Science (Wu and Cotton, 1999), which is enclosed as Appendix 2. Using soundings extracted from a mesoscale simulation of the November 26, 1991 cirrus event, the radiative effects on vapor deposition/sublimation of ice crystals was studied using a two-dimensional cloud-resolving model (CRM) version of RAMS, coupled to an explicit bin-resolving microphysics. The CRM simulations of the November 26, 1991 cirrus event demonstrate that the radiative impact on the diffusional growth (or sublimation) of ice crystals is significant. In this case, the ice particles experienced radiative warming. Model results show that radiative feedbacks in the diffusional growth of ice particles can be very complex. Radiative warming of an ice particle will restrict the particle's diffusional growth. In the case of radiative warming, ice particles larger than a certain size will experience so much radiative warming that surface ice saturation vapor pressures become large enough to cause sublimation of the larger crystals, while smaller crystals are growing by vapor deposition. However, ice mass production can be enhanced in the case of radiative cooling of an ice particle. For the November 26, 1991 cirrus event, radiative feedback results in significant reduction in the total ice mass, especially in the production of large ice crystals, and consequently, both radiative and dynamic properties of the cirrus cloud are significantly affected. A complete description of this research has been submitted as a paper to the Journal of Atmospheric Science (Wu et al., 1999), and included as Appendix 3.

Assimilation of GOES-Derived Cloud Fields Into MM5

NASA Astrophysics Data System (ADS)

Biazar, A. P.; Doty, K. G.; McNider, R.

2007-12-01

This approach for the assimilation of GOES-derived cloud data into an atmospheric model (the Fifth-Generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model, or MM5) was performed in two steps. In the first step, multiple linear regression equations were developed using a control MM5 simulation to develop relationships for several dependent variables in model columns that had one or more layers of clouds. In the second step, the regression equations were applied during an MM5 simulation with assimilation in which the hourly GOES satellite data were used to determine the cloud locations and some of the cloud properties, but with all the other variables being determined by the model data. The satellite-derived fields used were shortwave cloud albedo and cloud top pressure. Ten multiple linear regression equations were developed for the following dependent variables: total cloud depth, number of cloud layers, depth of the layer that contains the maximum vertical velocity, the maximum vertical velocity, the height of the maximum vertical velocity, the estimated 1-h stable (i.e., grid scale) precipitation rate, the estimated 1-h convective precipitation rate, the height of the level with the maximum positive diabatic heating, the magnitude of the maximum positive diabatic heating, and the largest continuous layer of upward motion. The horizontal components of the divergent wind were adjusted to be consistent with the regression estimate of the maximum vertical velocity. The new total horizontal wind field with these new divergent components was then used to nudge an ongoing MM5 model simulation towards the target vertical velocity. Other adjustments included diabatic heating and moistening at specified levels. Where the model simulation had clouds when the satellite data indicated clear conditions, procedures were taken to remove or diminish the errant clouds. The results for the period of 0000 UTC 28 June - 0000 UTC 16 July 1999 for both a continental 32-km grid and an 8-km grid over the Southeastern United States indicate a significant improvement in the cloud bias statistics. The main improvement was the reduction of high bias values that indicated times and locations in the control run when there were model clouds but when the satellite indicated clear conditions. The importance of this technique is that it has been able to assimilate the observed clouds in the model in a dynamically sustainable manner. Acknowledgments. This work was partially funded by the following grants: a GEWEX grant from NASA , the Cooperative Agreement between the University of Alabama in Huntsville and the Minerals Management Service on Gulf of Mexico Issues, a NASA applications grant, and a NSF grant.

Simulations of Cloud-Radiation Interaction Using Large-Scale Forcing Derived from the CINDY/DYNAMO Northern Sounding Array

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.

Cloud draft structure and trace gas transport

NASA Technical Reports Server (NTRS)

Scala, John R.; Tao, Wei-Kuo; Thompson, Anne M.; Simpson, Joanne; Garstang, Michael; Pickering, Kenneth E.; Browell, Edward V.; Sachse, Glen W.; Gregory, Gerald L.; Torres, Arnold L.

1990-01-01

During the second Amazon Boundary Layer Experiment (ABLE 2B), meteorological observations, chemical measurements, and model simulations are utilized in order to interpret convective cloud draft structure and to analyze its role in transport and vertical distribution of trace gases. One-dimensional photochemical model results suggest that the observed poststorm changes in ozone concentration can be attributed to convective transports rather than photochemical production and the results of a two-dimensional time-dependent cloud model simulation are presented for the May 6, 1987 squall system. The mesoscale convective system exhibited evidence of significant midlevel detrainment in addition to transports to anvil heights. Chemical measurements of O3 and CO obtained in the convective environment are used to predict photochemical production within the troposphere and to corroborate the cloud model results.

GCM Simulations of the Aerosol Indirect Effect: Sensitivity to Cloud Parameterization and Aerosol Burden

NASA Technical Reports Server (NTRS)

Menon, Surabi; DelGenio, Anthony D.; Koch, Dorothy; Tselioudis, George; Hansen, James E. (Technical Monitor)

2001-01-01

We describe the coupling of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to an online sulfur chemistry model and source models for organic matter and sea-salt that is used to estimate the aerosol indirect effect. The cloud droplet number concentration is diagnosed empirically from field experiment datasets over land and ocean that observe droplet number and all three aerosol types simultaneously; corrections are made for implied variations in cloud turbulence levels. The resulting cloud droplet number is used to calculate variations in droplet effective radius, which in turn allows us to predict aerosol effects on cloud optical thickness and microphysical process rates. We calculate the aerosol indirect effect by differencing the top-of-the-atmosphere net cloud radiative forcing for simulations with present-day vs. pre-industrial emissions. Both the first (radiative) and second (microphysical) indirect effects are explored. We test the sensitivity of our results to cloud parameterization assumptions that control the vertical distribution of cloud occurrence, the autoconversion rate, and the aerosol scavenging rate, each of which feeds back significantly on the model aerosol burden. The global mean aerosol indirect effect for all three aerosol types ranges from -1.55 to -4.36 W m(exp -2) in our simulations. The results are quite sensitive to the pre-industrial background aerosol burden, with low pre-industrial burdens giving strong indirect effects, and to a lesser extent to the anthropogenic aerosol burden, with large burdens giving somewhat larger indirect effects. Because of this dependence on the background aerosol, model diagnostics such as albedo-particle size correlations and column cloud susceptibility, for which satellite validation products are available, are not good predictors of the resulting indirect effect.

GCM Simulations of the Aerosol Indirect Effect: Sensitivity to Cloud Parameterization and Aerosol Burden

NASA Technical Reports Server (NTRS)

Menon, Surabi; DelGenio, Anthony D.; Koch, Dorothy; Tselioudis, George; Hansen, James E. (Technical Monitor)

2001-01-01

We describe the coupling of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to an online sulfur chemistry model and source models for organic matter and sea-salt that is used to estimate the aerosol indirect effect. The cloud droplet number concentration is diagnosed empirically from field experiment datasets over land and ocean that observe droplet number and all three aerosol types simultaneously; corrections are made for implied variations in cloud turbulence levels. The resulting cloud droplet number is used to calculate variations in droplet effective radius, which in turn allows us to predict aerosol effects on cloud optical thickness and microphysical process rates. We calculate the aerosol indirect effect by differencing the top-of-the-atmosphere net cloud radiative forcing for simulations with present-day vs. pre-industrial emissions. Both the first (radiative) and second (microphysical) indirect effects are explored. We test the sensitivity of our results to cloud parameterization assumptions that control the vertical distribution of cloud occurrence, the autoconversion rate, and the aerosol scavenging rate, each of which feeds back significantly on the model aerosol burden. The global mean aerosol indirect effect for all three aerosol types ranges from -1.55 to -4.36 W/sq m in our simulations. The results are quite sensitive to the pre-industrial background aerosol burden, with low pre-industrial burdens giving strong indirect effects, and to a lesser extent to the anthropogenic aerosol burden, with large burdens giving somewhat larger indirect effects. Because of this dependence on the background aerosol, model diagnostics such as albedo-particle size correlations and column cloud susceptibility, for which satellite validation products are available, are not good predictors of the resulting indirect effect.

Evaluating WRF-Chem aerosol indirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx

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

Saide P. E.; Springston S.; Spak, S. N.

2012-03-29

We evaluate a regional-scale simulation with the WRF-Chem model for the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx), which sampled the Southeast Pacific's persistent stratocumulus deck. Evaluation of VOCALS-REx ship-based and three aircraft observations focuses on analyzing how aerosol loading affects marine boundary layer (MBL) dynamics and cloud microphysics. We compare local time series and campaign-averaged longitudinal gradients, and highlight differences in model simulations with (W) and without (NW) wet deposition processes. The higher aerosol loadings in the NW case produce considerable changes in MBL dynamics and cloud microphysics, in accordance with the established conceptualmore » model of aerosol indirect effects. These include increase in cloud albedo, increase in MBL and cloud heights, drizzle suppression, increase in liquid water content, and increase in cloud lifetime. Moreover, better statistical representation of aerosol mass and number concentration improves model fidelity in reproducing observed spatial and temporal variability in cloud properties, including top and base height, droplet concentration, water content, rain rate, optical depth (COD) and liquid water path (LWP). Together, these help to quantify confidence in WRF-Chem's modeled aerosol-cloud interactions, especially in the activation parameterization, while identifying structural and parametric uncertainties including: irreversibility in rain wet removal; overestimation of marine DMS and sea salt emissions, and accelerated aqueous sulfate conversion. Our findings suggest that WRF-Chem simulates marine cloud-aerosol interactions at a level sufficient for applications in forecasting weather and air quality and studying aerosol climate forcing, and may do so with the reliability required for policy analysis.« less

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.

Microphysical processing of aerosol particles in orographic clouds

NASA Astrophysics Data System (ADS)

Pousse-Nottelmann, S.; Zubler, E. M.; Lohmann, U.

2015-08-01

An explicit and detailed treatment of cloud-borne particles allowing for the consideration of aerosol cycling in clouds has been implemented into COSMO-Model, the regional weather forecast and climate model of the Consortium for Small-scale Modeling (COSMO). The effects of aerosol scavenging, cloud microphysical processing and regeneration upon cloud evaporation on the aerosol population and on subsequent cloud formation are investigated. For this, two-dimensional idealized simulations of moist flow over two bell-shaped mountains were carried out varying the treatment of aerosol scavenging and regeneration processes for a warm-phase and a mixed-phase orographic cloud. The results allowed us to identify different aerosol cycling mechanisms. In the simulated non-precipitating warm-phase cloud, aerosol mass is incorporated into cloud droplets by activation scavenging and released back to the atmosphere upon cloud droplet evaporation. In the mixed-phase cloud, a first cycle comprises cloud droplet activation and evaporation via the Wegener-Bergeron-Findeisen (WBF) process. A second cycle includes below-cloud scavenging by precipitating snow particles and snow sublimation and is connected to the first cycle via the riming process which transfers aerosol mass from cloud droplets to snowflakes. In the simulated mixed-phase cloud, only a negligible part of the total aerosol mass is incorporated into ice crystals. Sedimenting snowflakes reaching the surface remove aerosol mass from the atmosphere. The results show that aerosol processing and regeneration lead to a vertical redistribution of aerosol mass and number. Thereby, the processes impact the total aerosol number and mass and additionally alter the shape of the aerosol size distributions by enhancing the internally mixed/soluble Aitken and accumulation mode and generating coarse-mode particles. Concerning subsequent cloud formation at the second mountain, accounting for aerosol processing and regeneration increases the cloud droplet number concentration with possible implications for the ice crystal number concentration.

Microphysics in Multi-scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo

2012-01-01

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), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.

Simulations of the observation of clouds and aerosols with the Experimental Lidar in Space Equipment system.

PubMed

Liu, Z; Voelger, P; Sugimoto, N

2000-06-20

We carried out a simulation study for the observation of clouds and aerosols with the Japanese Experimental Lidar in Space Equipment (ELISE), which is a two-wavelength backscatter lidar with three detection channels. The National Space Development Agency of Japan plans to launch the ELISE on the Mission Demonstrate Satellite 2 (MDS-2). In the simulations, the lidar return signals for the ELISE are calculated for an artificial, two-dimensional atmospheric model including different types of clouds and aerosols. The signal detection processes are simulated realistically by inclusion of various sources of noise. The lidar signals that are generated are then used as input for simulations of data analysis with inversion algorithms to investigate retrieval of the optical properties of clouds and aerosols. The results demonstrate that the ELISE can provide global data on the structures and optical properties of clouds and aerosols. We also conducted an analysis of the effects of cloud inhomogeneity on retrievals from averaged lidar profiles. We show that the effects are significant for space lidar observations of optically thick broken clouds.

Comparison of aerosol optical properties above clouds between POLDER and AeroCom models over the South East Atlantic Ocean during the fire season: POLDER/AeroCom Comparison Above Clouds

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

Peers, F.; Bellouin, N.; Waquet, F.

Aerosol properties above clouds have been retrieved over the South East Atlantic Ocean during the fire season 2006 using satellite observations from POLDER (Polarization and Directionality of Earth Reflectances). From June to October, POLDER has observed a mean Above-Cloud Aerosol Optical Thickness (ACAOT) of 0.28 and a mean Above-Clouds Single Scattering Albedo (ACSSA) of 0.87 at 550nm. These results have been used to evaluate the simulation of aerosols above clouds in 5 AeroCom (Aerosol Comparisons between Observations and Models) models (GOCART, HadGEM3, ECHAM5-HAM2, OsloCTM2 and SPRINTARS). Most models do not reproduce the observed large aerosol load episodes. The comparison highlightsmore » the importance of the injection height and the vertical transport parameterizations to simulate the large ACAOT observed by POLDER. Furthermore, some models overestimate the ACSSA. In accordance with recent recommendations of the black carbon refractive index, a higher prescription of the imaginary part allows a better comparison with POLDER’s ACSSA.« less

Evaluation of the NASA GISS AR5 SCM/GCM at the ARM SGP Site using Self Organizing Maps

NASA Astrophysics Data System (ADS)

Kennedy, A. D.; Dong, X.; Xi, B.; Del Genio, A. D.; Wolf, A.

2011-12-01

Understanding and improving clouds in climate models requires moving beyond comparing annual and seasonal means. Errors can offset resulting in models getting the right long-term solution for the wrong reasons. For example, cloud parameterization errors may be balanced by the model incorrectly simulating the frequency distribution of atmospheric states. To faithfully evaluate climate models it is necessary to partition results into specific regimes. This has been completed in the past by evaluating models by their ability to produce cloud regimes as determined by observational products from satellites. An alternative approach is to first classify meteorological regimes (i.e., synoptic pattern and forcing) and then determine what types of clouds occur for each class. In this study, a competitive neural network known as the Self Organizing Map (SOM) is first used to classify synoptic patterns from a reanalysis over the Southern Great Plains (SGP) region during the period 1999-2008. These results are then used to evaluate simulated clouds from the AR5 version of the NASA GISS Model E Single Column Model (SCM). Unlike past studies that narrowed classes into several categories, this study assumes that the atmosphere is capable of producing an infinite amount of states. As a result, SOMs were generated with a large number of classes for specific months when model errors were found. With nearly ten years of forcing data, an adequate number of samples have been used to determine how cloud fraction varies across the SOM and to distinguish cloud errors. Barring major forcing errors, SCM studies can be thought of as what the GCM would simulate if the dynamics were perfect. As a result, simulated and observed CFs frequently occur for the same atmospheric states. For example, physically deep clouds during the winter months occur for a small number of classes in the SOM. Although the model produces clouds during the correct states, CFs are consistently too low. Instead, the model has a positive bias of thinner clouds during these classes that were associated with low-pressure systems and fronts. To determine if this and other SCM errors are present in the GCM, the Atmospheric Model Intercomparison Project (AMIP) run for the NASA GISS GCM will also be investigated. The SOM will be used to classify atmospheric states within the GCM to determine how well the GCM captures the PDF of observed atmospheric states. Together, these comparisons will allow for a thorough evaluation of the model at the ARM SGP site.

Short-range precipitation forecasts using assimilation of simulated satellite water vapor profiles and column cloud liquid water amounts

NASA Technical Reports Server (NTRS)

Wu, Xiaohua; Diak, George R.; Hayden, Cristopher M.; Young, John A.

1995-01-01

These observing system simulation experiments investigate the assimilation of satellite-observed water vapor and cloud liquid water data in the initialization of a limited-area primitive equations model with the goal of improving short-range precipitation forecasts. The assimilation procedure presented includes two aspects: specification of an initial cloud liquid water vertical distribution and diabatic initialization. The satellite data is simulated for the next generation of polar-orbiting satellite instruments, the Advanced Microwave Sounding Unit (AMSU) and the High-Resolution Infrared Sounder (HIRS), which are scheduled to be launched on the NOAA-K satellite in the mid-1990s. Based on cloud-top height and total column cloud liquid water amounts simulated for satellite data a diagnostic method is used to specify an initial cloud water vertical distribution and to modify the initial moisture distribution in cloudy areas. Using a diabatic initialization procedure, the associated latent heating profiles are directly assimilated into the numerical model. The initial heating is estimated by time averaging the latent heat release from convective and large-scale condensation during the early forecast stage after insertion of satellite-observed temperature, water vapor, and cloud water formation. The assimilation of satellite-observed moisture and cloud water, together withy three-mode diabatic initialization, significantly alleviates the model precipitation spinup problem, especially in the first 3 h of the forecast. Experimental forecasts indicate that the impact of satellite-observed temperature and water vapor profiles and cloud water alone in the initialization procedure shortens the spinup time for precipitation rates by 1-2 h and for regeneration of the areal coverage by 3 h. The diabatic initialization further reduces the precipitation spinup time (compared to adiabatic initialization) by 1 h.

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

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Mars topographic clouds: MAVEN/IUVS observations and LMD MGCM predictions

NASA Astrophysics Data System (ADS)

Schneider, Nicholas M.; Connour, Kyle; Forget, Francois; Deighan, Justin; Jain, Sonal; Vals, Margaux; Wolff, Michael J.; Chaffin, Michael S.; Crismani, Matteo; Stewart, A. Ian F.; McClintock, William E.; Holsclaw, Greg; Lefevre, Franck; Montmessin, Franck; Stiepen, Arnaud; Stevens, Michael H.; Evans, J. Scott; Yelle, Roger; Lo, Daniel; Clarke, John T.; Jakosky, Bruce

2017-10-01

The Imaging Ultraviolet Spectrograph (IUVS) instrument on the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft takes mid-UV spectral images of the Martian atmosphere. From these apoapse disk images, information about clouds and aerosols can be retrieved and comprise the only MAVEN observations of topographic clouds and cloud morphologies. Measuring local time variability of large-scale recurring cloud features is made possible with MAVEN’s ~4.5-hour elliptical orbit, something not possible with sun-synchronous orbits. We have run the LMD MGCM (Mars global circulation model) at 1° x 1° resolution to simulate water ice cloud formation with inputs consistent with observing parameters and Mars seasons. Topographic clouds are observed to form daily during the late mornings of northern hemisphere spring and this phenomenon recurs until late summer (Ls = 160°), after which topographic clouds wane in thickness. By northern fall, most topographic clouds cease to form except over Arsia Mons and Pavonis Mons, where clouds can still be observed. Our data show moderate cloud formation over these regions as late as Ls = 220°, something difficult for the model to replicate. Previous studies have shown that models have trouble simulating equatorial cloud thickness in combination with a realistic amount of water vapor and not-too-thick polar water ice clouds, implying aspects of the water cycle are not fully understood. We present data/model comparisons as well as further refinements on parameter inputs based on IUVS observations.

Mars topographic clouds: MAVEN/IUVS observations and LMD MGCM predictions

NASA Astrophysics Data System (ADS)

Connour, K.; Schneider, N.; Forget, F.; Deighan, J.; Jain, S.; Pottier, A.; Wolff, M. J.; Chaffin, M.; Crismani, M. M. J.; Stewart, I. F.; McClintock, B.; Holsclaw, G.; Lefèvre, F.; Montmessin, F.; Stiepen, A.; Stevens, M. H.; Evans, J. S.; Yelle, R. V.; Lo, D.; Clarke, J. T.; Jakosky, B. M.

2017-12-01

The Imaging Ultraviolet Spectrograph (IUVS) instrument on the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft takes mid-UV spectral images of the Martian atmosphere. From these apoapse disk images, information about clouds and aerosols can be retrieved and comprise the only MAVEN observations of topographic clouds and cloud morphologies. Measuring local time variability of large-scale recurring cloud features is made possible with MAVEN's 4.5-hour elliptical orbit, something not possible with sun-synchronous orbits. We have run the LMD MGCM (Mars global circulation model) at 1° x 1° resolution to simulate water ice cloud formation with inputs consistent with observing parameters and Mars seasons. Topographic clouds are observed to form daily during the late mornings of northern hemisphere spring and this phenomenon recurs until late summer (Ls = 160°), after which topographic clouds wane in thickness. By northern fall, most topographic clouds cease to form except over Arsia Mons and Pavonis Mons, where clouds can still be observed. Our data show moderate cloud formation over these regions as late as Ls = 220°, something difficult for the model to replicate. Previous studies have shown that models have trouble simulating equatorial cloud thickness in combination with a realistic amount of water vapor and not-too-thick polar water ice clouds, implying aspects of the water cycle are not fully understood. We present data/model comparisons as well as further refinements on parameter inputs based on IUVS observations.

Exploring Alternative Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.

2009-01-01

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. The combination of reliable cloud microphysics and radar reflectivity may constrain radiative transfer models used in satellite simulators during future missions, including EarthCARE and the NASA Global Precipitation Measurement. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a mid latitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Clearing clouds of uncertainty

NASA Astrophysics Data System (ADS)

Zelinka, Mark D.; Randall, David A.; Webb, Mark J.; Klein, Stephen A.

2017-10-01

Since 1990, the wide range in model-based estimates of equilibrium climate warming has been attributed to disparate cloud responses to warming. However, major progress in our ability to understand, observe, and simulate clouds has led to the conclusion that global cloud feedback is likely positive.

COSP: Satellite simulation software for model assessment

DOE PAGES

Bodas-Salcedo, A.; Webb, M. J.; Bony, S.; ...

2011-08-01

Errors in the simulation of clouds in general circulation models (GCMs) remain a long-standing issue in climate projections, as discussed in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. This highlights the need for developing new analysis techniques to improve our knowledge of the physical processes at the root of these errors. The Cloud Feedback Model Intercomparison Project (CFMIP) pursues this objective, and under that framework the CFMIP Observation Simulator Package (COSP) has been developed. COSP is a flexible software tool that enables the simulation of several satellite-borne active and passive sensor observations from model variables. The flexibilitymore » of COSP and a common interface for all sensors facilitates its use in any type of numerical model, from high-resolution cloud-resolving models to the coarser-resolution GCMs assessed by the IPCC, and the scales in between used in weather forecast and regional models. The diversity of model parameterization techniques makes the comparison between model and observations difficult, as some parameterized variables (e.g., cloud fraction) do not have the same meaning in all models. The approach followed in COSP permits models to be evaluated against observations and compared against each other in a more consistent manner. This thus permits a more detailed diagnosis of the physical processes that govern the behavior of clouds and precipitation in numerical models. The World Climate Research Programme (WCRP) Working Group on Coupled Modelling has recommended the use of COSP in a subset of climate experiments that will be assessed by the next IPCC report. Here we describe COSP, present some results from its application to numerical models, and discuss future work that will expand its capabilities.« less

Vertical transport by convective clouds: Comparisons of three modeling approaches

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.; Thompson, Anne M.; Tao, Wei-Kuo; Rood, Richard B.; Mcnamara, Donna P.; Molod, Andrea M.

1995-01-01

A preliminary comparison of the GEOS-1 (Goddard Earth Observing System) data assimilation system convective cloud mass fluxes with fluxes from a cloud-resolving model (the Goddard Cumulus Ensemble Model, GCE) is reported. A squall line case study (10-11 June 1985 Oklahoma PRESTORM episode) is the basis of the comparison. Regional (central U. S.) monthly total convective mass flux for June 1985 from GEOS-1 compares favorably with estimates from a statistical/dynamical approach using GCE simulations and satellite-derived cloud observations. The GEOS-1 convective mass fluxes produce reasonable estimates of monthly-averaged regional convective venting of CO from the boundary layer at least in an urban-influenced continental region, suggesting that they can be used in tracer transport simulations.

Lagrangian large eddy simulations of boundary layer clouds on ERA-Interim and ERA5 trajectories

NASA Astrophysics Data System (ADS)

Kazil, J.; Feingold, G.; Yamaguchi, T.

2017-12-01

This exploratory study examines Lagrangian large eddy simulations of boundary layer clouds along wind trajectories from the ERA-Interim and ERA5 reanalyses. The study is motivated by the need for statistically representative sets of high resolution simulations of cloud field evolution in realistic meteorological conditions. The study will serve as a foundation for the investigation of biomass burning effects on the transition from stratocumulus to shallow cumulus clouds in the South-East Atlantic. Trajectories that pass through a location with radiosonde data (St. Helena) and which exhibit a well-defined cloud structure and evolution were identified in satellite imagery, and sea surface temperature and atmospheric vertical profiles along the trajectories were extracted from the reanalysis data sets. The System for Atmospheric Modeling (SAM) simulated boundary layer turbulence and cloud properties along the trajectories. Mean temperature and moisture (in the free troposphere) and mean wind speed (at all levels) were nudged towards the reanalysis data. Atmospheric and cloud properties in the large eddy simulations were compared with those from the reanalysis products, and evaluated with satellite imagery and radiosonde data. Simulations using ERA-Interim data and the higher resolution ERA5 data are contrasted.

Comparisons of Cloud Properties over the Southern Ocean between In situ Observations and WRF Simulations

NASA Astrophysics Data System (ADS)

D'Alessandro, J.; Diao, M.; Wu, C.; Liu, X.

2017-12-01

Numerical weather models often struggle at representing clouds since small scale cloud processes must be parameterized. For example, models often utilize simple parameterizations for transitioning from liquid to ice, usually set as a function of temperature. However, supercooled liquid water (SLW) often persists at temperatures much lower than threshold values used in microphysics parameterizations. Previous observational studies of clouds over the Southern Ocean have found high frequencies of SLW (e.g., Morrison et al., 2011). Many of these studies have relied on satellite retrievals, which provide relatively low resolution observations and are often associated with large uncertainties due to assumptions of microphysical properties (e.g., particle size distributions). Recently, the NSF/NCAR O2/N2 Ratio and CO2 Airborne Southern Ocean Study (ORCAS) campaign took observations via the NSF/NCAR HIAPER research aircraft during January and February of 2016, providing in situ observations over the Southern Ocean (50°W to 92°W). We compare simulated results from the Weather Research and Forecasting (WRF) model with in situ observations from ORCAS. Differences between observations and simulations are evaluated via statistical analyses. Initial results from ORCAS reveal a high frequency of SLW at temperatures as low as -15°C, and the existence of SLW around -30°C. Recent studies have found that boundary layer clouds are underestimated by WRF in regions unaffected by cyclonic activity (Huang et al., 2014), suggesting a lack of low-level moisture due to local processes. To explore this, relative humidity distributions are examined and controlled by cloud microphysical characteristics (e.g., total water content) and relevant ambient properties (e.g., vertical velocity). A relatively low frequency of simulated SLW may in part explain the discrepancies in WRF, as cloud-top SLW results in stronger radiative cooling and turbulent motions conducive for long-lived cloud regimes. Results presented in this study will help improve our understanding of Southern Ocean clouds and the observed discrepancies seen in WRF simulations.

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

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

Evaluation of Cirrus Cloud Simulations Using ARM Data - Development of a Case Study Data Set

NASA Technical Reports Server (NTRS)

O'C.Starr, David; Demoz, Belay; Lare, Andrew; Poellot, Michael; Sassen, Kenneth; Heymsfield, Andrew; Brown, Philip; Mace, Jay; Einaudi, Franco (Technical Monitor)

2001-01-01

Cloud-resolving models (CRMs) provide an effective linkage in terms of parameters and scales between observations and the parametric treatments of clouds in global climate models (GCMs). They also represent the best understanding of the physical processes acting to determine cloud system lifecycle. The goal of this project is to improve state-of-the-art CRMs used for studies of cirrus clouds and to establish a relative calibration with GCMs through comparisons among CRMs, single column model (SCM) versions of the GCMs, and observations. This project will compare and evaluate a variety of CRMs and SCMs, under the auspices of the GEWEX Cloud Systems Study (GCSS) Working Group on Cirrus Cloud Systems (WG2), using ARM data acquired at the Southern Great Plains (SGP) site. This poster will report on progress in developing a suitable WG2 case study data set based on the September 26, 1996 ARM IOP case - the Hurricane Nora outflow case. The environmental data (input) will be described as well as the wealth of validating cloud observations. We plan to also show results of preliminary simulations. The science questions to be addressed derive significantly from results of the GCSS WG2 cloud model comparison projects, which will be briefly summarized.

D Modeling of Components of a Garden by Using Point Cloud Data

NASA Astrophysics Data System (ADS)

Kumazakia, R.; Kunii, Y.

2016-06-01

Laser measurement is currently applied to several tasks such as plumbing management, road investigation through mobile mapping systems, and elevation model utilization through airborne LiDAR. Effective laser measurement methods have been well-documented in civil engineering, but few attempts have been made to establish equally effective methods in landscape engineering. By using point cloud data acquired through laser measurement, the aesthetic landscaping of Japanese gardens can be enhanced. This study focuses on simple landscape simulations for pruning and rearranging trees as well as rearranging rocks, lanterns, and other garden features by using point cloud data. However, such simulations lack concreteness. Therefore, this study considers the construction of a library of garden features extracted from point cloud data. The library would serve as a resource for creating new gardens and simulating gardens prior to conducting repairs. Extracted garden features are imported as 3ds Max objects, and realistic 3D models are generated by using a material editor system. As further work toward the publication of a 3D model library, file formats for tree crowns and trunks should be adjusted. Moreover, reducing the size of created models is necessary. Models created using point cloud data are informative because simply shaped garden features such as trees are often seen in the 3D industry.

Modeling Aerosol Microphysical and Radiative Effects on Clouds and Implications for the Effects of Black and Brown Carbon on Clouds

NASA Astrophysics Data System (ADS)

Ten Hoeve, J. E.; Jacobson, M. Z.

2010-12-01

Satellite observational studies have found an increase in cloud fraction (CF) and cloud optical depth (COD) with increasing aerosol optical depth (AOD) followed by a decreasing CF/COD with increasing AOD at higher AODs over the Amazon Basin. The shape of this curve is similar to that of a boomerang, and thus the effect has been dubbed the "boomerang effect.” The increase in CF/COD with increasing AOD at low AODs is ascribed to the first and second indirect effects and is referred to as a microphysical effect of aerosols on clouds. The decrease in CF/COD at higher AODs is ascribed to enhanced warming of clouds due to absorbing aerosols, either as inclusions in drops or interstitially between drops. This is referred to as a radiative effect. To date, the interaction of the microphysical and radiative effects has not been simulated with a regional or global computer model. Here, we simulate the boomerang effect with the nested global-through-urban climate, air pollution, weather forecast model, GATOR-GCMOM, for the Amazon biomass burning season of 2006. We also compare the model with an extensive set of data, including satellite data from MODIS, TRMM, and CALIPSO, in situ surface observations, upper-air data, and AERONET data. Biomass burning emissions are obtained from the Global Fire Emissions Database (GFEDv2), and are combined with MODIS land cover data along with biomass burning emission factors. A high-resolution domain, nested within three increasingly coarser domains, is employed over the heaviest biomass burning region within the arc of deforestation. Modeled trends in cloud properties with aerosol loading compare well with MODIS observed trends, allowing causation of these observed correlations, including of the boomerang effect, to be determined by model results. The impact of aerosols on various cloud parameters, such as cloud optical thickness, cloud fraction, cloud liquid water/ice content, and precipitation, are shown through differences between simulations that include and exclude biomass burning emissions. This study suggests by cause and effect through numerical modeling that aerosol radiative effects counteract microphysical effects at high AODs, a result previously shown by correlation alone. As such, computer models that exclude treatment of cloud radiative effects are likely to overpredict the indirect effects of aerosols on clouds and underestimate the warming due to aerosols containing black carbon.

Meteorological and Aerosol effects on Marine Cloud Microphysical Properties

NASA Astrophysics Data System (ADS)

Sanchez, K. J.; Russell, L. M.; Modini, R. L.; Frossard, A. A.; Ahlm, L.; Roberts, G.; Hawkins, L. N.; Schroder, J. C.; Wang, Z.; Lee, A.; Abbatt, J.; Lin, J.; Nenes, A.; Wonaschuetz, A.; Sorooshian, A.; Noone, K.; Jonsson, H.; Albrecht, B. A.; Desiree, T. S.; Macdonald, A. M.; Seinfeld, J.; Zhao, R.

2015-12-01

Both meteorology and microphysics affect cloud formation and consequently their droplet distributions and shortwave reflectance. The Eastern Pacific Emitted Aerosol Cloud Experiment (EPEACE) and the Stratocumulus Observations of Los-Angeles Emissions Derived Aerosol-Droplets (SOLEDAD) studies provide detailed measurements in 6 case studies of both cloud thermodynamic properties and initial particle number distribution and composition, as well as the resulting cloud drop distribution and composition. This study uses simulations of a detailed chemical and microphysical aerosol-cloud parcel (ACP) model with explicit kinetic drop activation to reproduce the observed cloud droplet distribution and composition. Four of the cases examined had a sub-adiabatic lapse rate, which was shown to have fewer droplets due to decreased maximum supersaturation, lower LWC and higher cloud base height, consistent with previous findings. These detailed case studies provided measured thermodynamics and microphysics that constrained the simulated droplet size distribution sufficiently to match the droplet number within 6% and the size within 19% for 4 of the 6 cases, demonstrating "closure" or consistency of the measured composition with the measured CCN spectra and the inferred and modeled supersaturation. The contribution of organic components to droplet formation shows small effects on the droplet number and size in the 4 marine cases that had background aerosol conditions with varying amounts of coastal, ship or other non-biogenic sources. In contrast, the organic fraction and hygroscopicity increased the droplet number and size in the cases with generated smoke and cargo ship plumes that were freshly emitted and not yet internally mixed with the background particles. The simulation results show organic hygroscopicity causes small effects on cloud reflectivity (<0.7%) with the exception of the cargo ship plume and smoke plume which increased absolute cloud reflectivity fraction by 0.02 and 0.20 respectively. In addition, the ACP model simulations are compared to those from a numerical parameterization of cloud droplet activation that is suitable for GCMs and show droplet concentrations are comparable between the two methods.

Evidence for climate change in the satellite cloud record.

PubMed

Norris, Joel R; Allen, Robert J; Evan, Amato T; Zelinka, Mark D; O'Dell, Christopher W; Klein, Stephen A

2016-08-04

Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Evidence for climate change in the satellite cloud record

NASA Astrophysics Data System (ADS)

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; Zelinka, Mark D.; O'Dell, Christopher W.; Klein, Stephen A.

2016-08-01

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts. Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

Large-eddy Simulation of Stratocumulus-topped Atmospheric Boundary Layers with Dynamic Subgrid-scale Models

NASA Technical Reports Server (NTRS)

Senocak, Inane

2003-01-01

The objective of the present study is to evaluate the dynamic procedure in LES of stratocumulus topped atmospheric boundary layer and assess the relative importance of subgrid-scale modeling, cloud microphysics and radiation modeling on the predictions. The simulations will also be used to gain insight into the processes leading to cloud top entrainment instability and cloud breakup. In this report we document the governing equations, numerical schemes and physical models that are employed in the Goddard Cumulus Ensemble model (GCEM3D). We also present the subgrid-scale dynamic procedures that have been implemented in the GCEM3D code for the purpose of the present study.

Microwave and infrared simulations of an intense convective system and comparison with aircraft observations

NASA Technical Reports Server (NTRS)

Prasad, N.; Yeh, Hwa-Young M.; Adler, Robert F.; Tao, Wei-Kuo

1995-01-01

A three-dimensional cloud model, radiative transfer model-based simulation system is tested and validated against the aircraft-based radiance observations of an intense convective system in southeastern Virginia on 29 June 1986 during the Cooperative Huntsville Meteorological Experiment. NASA's ER-2, a high-altitude research aircraft with a complement of radiometers operating at 11-micrometer infrared channel and 18-, 37-, 92-, and 183-GHz microwave channels provided data for this study. The cloud model successfully simulated the cloud system with regard to aircraft- and radar-observed cloud-top heights and diameters and with regard to radar-observed reflectivity structure. For the simulation time found to correspond best with the aircraft- and radar-observed structure, brightness temperatures T(sub b) are simulated and compared with observations for all the microwave frequencies along with the 11-micrometer infrared channel. Radiance calculations at the various frequencies correspond well with the aircraft observations in the areas of deep convection. The clustering of 37-147-GHz T(sub b) observations and the isolation of the 18-GHz values over the convective cores are well simulated by the model. The radiative transfer model, in general, is able to simulate the observations reasonably well from 18 GHz through 174 GHz within all convective areas of the cloud system. When the aircraft-observed 18- and 37-GHz, and 90- and 174-GHz T(sub b) are plotted against each other, the relationships have a gradual difference in the slope due to the differences in the ice particle size in the convective and more stratiform areas of the cloud. The model is able to capture these differences observed by the aircraft. Brightness temperature-rain rate relationships compare reasonably well with the aircraft observations in terms of the slope of the relationship. The model calculations are also extended to select high-frequency channels at 220, 340, and 400 GHz to simulate the Millimeter-wave Imaging Radiometer aircraft instrument to be flown in the near future. All three of these frequencies are able to discriminate the convective and anvil portions of the system, providing useful information similar to that from the frequencies below 183 GHz but with potentially enhanced spatial resolution from a satellite platform. In thin clouds, the dominant effect of water vapor is seen at 174, 340, and 400 GHz. In thick cloudy areas, the scattering effect is dominant at 90 and 220 GHz, while the overlaying water vapor can attenuate at 174, 340, and 400 GHz. All frequencies (90-400 GHz) show strong signatures in the core.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Application of cellular automata approach for cloud simulation and rendering

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

Christopher Immanuel, W.; Paul Mary Deborrah, S.; Samuel Selvaraj, R.

Current techniques for creating clouds in games and other real time applications produce static, homogenous clouds. These clouds, while viable for real time applications, do not exhibit an organic feel that clouds in nature exhibit. These clouds, when viewed over a time period, were able to deform their initial shape and move in a more organic and dynamic way. With cloud shape technology we should be able in the future to extend to create even more cloud shapes in real time with more forces. Clouds are an essential part of any computer model of a landscape or an animation ofmore » an outdoor scene. A realistic animation of clouds is also important for creating scenes for flight simulators, movies, games, and other. Our goal was to create a realistic animation of clouds.« less

Responses of Mixed-Phase Cloud Condensates and Cloud Radiative Effects to Ice Nucleating Particle Concentrations in NCAR CAM5 and DOE ACME Climate Models

NASA Astrophysics Data System (ADS)

Liu, X.; Shi, Y.; Wu, M.; Zhang, K.

2017-12-01

Mixed-phase clouds frequently observed in the Arctic and mid-latitude storm tracks have the substantial impacts on the surface energy budget, precipitation and climate. In this study, we first implement the two empirical parameterizations (Niemand et al. 2012 and DeMott et al. 2015) of heterogeneous ice nucleation for mixed-phase clouds in the NCAR Community Atmosphere Model Version 5 (CAM5) and DOE Accelerated Climate Model for Energy Version 1 (ACME1). Model simulated ice nucleating particle (INP) concentrations based on Niemand et al. and DeMott et al. are compared with those from the default ice nucleation parameterization based on the classical nucleation theory (CNT) in CAM5 and ACME, and with in situ observations. Significantly higher INP concentrations (by up to a factor of 5) are simulated from Niemand et al. than DeMott et al. and CNT especially over the dust source regions in both CAM5 and ACME. Interestingly the ACME model simulates higher INP concentrations than CAM5, especially in the Polar regions. This is also the case when we nudge the two models' winds and temperature towards the same reanalysis, indicating more efficient transport of aerosols (dust) to the Polar regions in ACME. Next, we examine the responses of model simulated cloud liquid water and ice water contents to different INP concentrations from three ice nucleation parameterizations (Niemand et al., DeMott et al., and CNT) in CAM5 and ACME. Changes in liquid water path (LWP) reach as much as 20% in the Arctic regions in ACME between the three parameterizations while the LWP changes are smaller and limited in the Northern Hemispheric mid-latitudes in CAM5. Finally, the impacts on cloud radiative forcing and dust indirect effects on mixed-phase clouds are quantified with the three ice nucleation parameterizations in CAM5 and ACME.

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

NASA Technical Reports Server (NTRS)

Platnick, Steven; Zinner, Tobias; Ackerman, S.

2008-01-01

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

Clearing clouds of uncertainty

DOE PAGES

Zelinka, Mark D.; Randall, David A.; Webb, Mark J.; ...

2017-09-29

We report that since 1990, the wide range in model-based estimates of equilibrium climate warming has been attributed to disparate cloud responses to warming. However, major progress in our ability to understand, observe, and simulate clouds has led to the conclusion that global cloud feedback is likely positive.

Impact of Aerosols on Convective Clouds and Precipitation

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Chen, Jen-Ping; Li, Zhanqing; Wang, Chien; Zhang, Chidong

2011-01-01

Aerosols are a critical factor in the atmospheric hydrological cycle and radiation budget. As a major reason for clouds to form and a significant attenuator of solar radiation, aerosols affect climate in several ways. Current research suggests that aerosol effects on clouds could further extend to precipitation, both through the formation of cloud particles and by exerting persistent radiative forcing on the climate system that disturbs dynamics. However, the various mechanisms behind these effects, in particular the ones connected to precipitation, are not yet well understood. The atmospheric and climate communities have long been working to gain a better grasp of these critical effects and hence to reduce the significant uncertainties in climate prediction resulting from such a lack of adequate knowledge. The central theme of this paper is to review past efforts and summarize our current understanding of the effect of aerosols on precipitation processes from theoretical analysis of microphysics, observational evidence, and a range of numerical model simulations. In addition, the discrepancy between results simulated by models, as well as that between simulations and observations will be presented. Specifically, this paper will address the following topics: (1) fundamental theories of aerosol effects on microphysics and precipitation processes, (2) observational evidence of the effect of aerosols on precipitation processes, (3) signatures of the aerosol impact on precipitation from large-scale analyses, (4) results from cloud-resolving model simulations, and (5) results from large-scale numerical model simulations. Finally, several future research directions on aerosol - precipitation interactions are suggested.

Instantaneous Linkages between Clouds and Large-Scale Meteorology over the Southern Ocean in Observations and a Climate Model

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

Wall, Casey J.; Hartmann, Dennis L.; Ma, Po-Lun

Instantaneous, coincident, footprint-level satellite observations of cloud properties and radiation taken during austral summer over the Southern Ocean are used to study relationships between clouds and large-scale meteorology. Cloud properties are very sensitive to the strength of vertical motion in the middle-troposphere, and low-cloud properties are sensitive to estimated inversion strength, low-level temperature advection, and sea surface temperature. These relationships are quantified. An index for the meteorological anomalies associated with midlatitude cyclones is presented, and it is used to reveal the sensitivity of clouds to the meteorology within the warm- and cold-sector of cyclones. The observed relationships between clouds andmore » meteorology are compared to those in the Community Atmosphere Model version 5 (CAM5) using satellite simulators. Low-clouds simulated by CAM5 are too few, too bright, and contain too much ice, and low-clouds located in the cold-sector of cyclones are too sensitive to variations in the meteorology. The latter two biases are dramatically reduced when CAM5 is coupled with an updated boundary layer parameterization know as Cloud Layers Unified by Binormals (CLUBB). More generally, this study demonstrates that examining the instantaneous timescale is a powerful approach to understanding the physical processes that control clouds and how they are represented in climate models. Such an evaluation goes beyond the cloud climatology and exposes model bias under various meteorological conditions.« less

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

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

Xu, Kuan-Man; Cheng, Anning

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation andmore » stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.« less

Understanding the tropical cloud feedback from an analysis of the circulation and stability regimes simulated from an upgraded multiscale modeling framework

DOE PAGES

Xu, Kuan-Man; Cheng, Anning

2016-11-15

As revealed from studies using conventional general circulation models (GCMs), the thermodynamic contribution to the tropical cloud feedback dominates the dynamic contribution, but these models have difficulty in simulating the subsidence regimes in the tropics. In this study, we analyze the tropical cloud feedback from a 2 K sea surface temperature (SST) perturbation experiment performed with a multiscale modeling framework (MMF). The MMF explicitly represents cloud processes using 2-D cloud-resolving models with an advanced higher-order turbulence closure in each atmospheric column of the host GCM. We sort the monthly mean cloud properties and cloud radiative effects according to circulation andmore » stability regimes. Here, we find that the regime-sorted dynamic changes dominate the thermodynamic changes in terms of the absolute magnitude. The dynamic changes in the weak subsidence regimes exhibit strong negative cloud feedback due to increases in shallow cumulus and deep clouds while those in strongly convective and moderate-to-strong subsidence regimes have opposite signs, resulting in a small contribution to cloud feedback. On the other hand, the thermodynamic changes are large due to decreases in stratocumulus clouds in the moderate-to-strong subsidence regimes with small opposite changes in the weak subsidence and strongly convective regimes, resulting in a relatively large contribution to positive cloud feedback. The dynamic and thermodynamic changes contribute equally to positive cloud feedback and are relatively insensitive to stability in the moderate-to-strong subsidence regimes. But they are sensitive to stability changes from the SST increase in convective and weak subsidence regimes. Lastly, these results have implications for interpreting cloud feedback mechanisms.« less

Microphysics in the Multi-Scale Modeling Systems with Unified Physics

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Estimation of Cloud Fraction Profile in Shallow Convection Using a Scanning Cloud Radar

DOE PAGES

Oue, Mariko; Kollias, Pavlos; North, Kirk W.; ...

2016-10-18

Large spatial heterogeneities in shallow convection result in uncertainties in estimations of domain-averaged cloud fraction profiles (CFP). This issue is addressed using large eddy simulations of shallow convection over land coupled with a radar simulator. Results indicate that zenith profiling observations are inadequate to provide reliable CFP estimates. Use of Scanning Cloud Radar (SCR), performing a sequence of cross-wind horizon-to-horizon scans, is not straightforward due to the strong dependence of radar sensitivity to target distance. An objective method for estimating domain-averaged CFP is proposed that uses observed statistics of SCR hydrometeor detection with height to estimate optimum sampling regions. Thismore » method shows good agreement with the model CFP. Results indicate that CFP estimates require more than 35 min of SCR scans to converge on the model domain average. Lastly, the proposed technique is expected to improve our ability to compare model output with cloud radar observations in shallow cumulus cloud conditions.« less

Evaluating the feasibility of global climate models to simulate cloud cover effect controlled by Marine Stratocumulus regime transitions

NASA Astrophysics Data System (ADS)

Goren, Tom; Muelmenstaedt, Johannes; Rosenfeld, Daniel; Quaas, Johannes

2017-04-01

Marine stratocumulus clouds (MSC) occur in two main cloud regimes of open and closed cells that differ significantly by their cloud cover. Closed cells gradually get cleansed of high CCN concentrations in a process that involves initiation of drizzle that breaks the full cloud cover into open cells. The drizzle creates downdrafts that organize the convection along converging gust fronts, which in turn produce stronger updrafts that can sustain more cloud water that compensates the depletion of the cloud water by the rain. In addition, having stronger updrafts allow the clouds to grow relatively deep before rain starts to deplete its cloud water. Therefore, lower droplet concentrations and stronger rain would lead to lower cloud fraction, but not necessary also to lower liquid water path (LWP). The fundamental relationships between these key variables derived from global climate model (GCM) simulations are analyzed with respect to observations in order to determine whether the GCM parameterizations can represent well the governing physical mechanisms upon MSC regime transitions. The results are used to evaluate the feasibility of GCM's for estimating aerosol cloud-mediated radiative forcing upon MSC regime transitions, which are responsible for the largest aerosol cloud-mediated radiative forcing.

Origin of coronal mass ejection and magnetic cloud: Thermal or magnetic driven?

NASA Technical Reports Server (NTRS)

Zhang, Gong-Liang; Wang, Chi; He, Shuang-Hua

1995-01-01

A fundamental problem in Solar-Terrestrial Physics is the origin of the solar transient plasma output, which includes the coronal mass ejection and its interplanetary manifestation, e.g. the magnetic cloud. The traditional blast wave model resulted from solar thermal pressure impulse has faced with challenge during recent years. In the MHD numerical simulation study of CME, the authors find that the basic feature of the asymmetrical event on 18 August 1980 can be reproduced neither by a thermal pressure nor by a speed increment. Also, the thermal pressure model fails in simulating the interplanetary structure with low thermal pressure and strong magnetic field strength, representative of a typical magnetic cloud. Instead, the numerical simulation results are in favor of the magnetic field expansion as the likely mechanism for both the asymmetrical CME event and magnetic cloud.

Numerical Coupling and Simulation of Point-Mass System with the Turbulent Fluid Flow

NASA Astrophysics Data System (ADS)

Gao, Zheng

A computational framework that combines the Eulerian description of the turbulence field with a Lagrangian point-mass ensemble is proposed in this dissertation. Depending on the Reynolds number, the turbulence field is simulated using Direct Numerical Simulation (DNS) or eddy viscosity model. In the meanwhile, the particle system, such as spring-mass system and cloud droplets, are modeled using the ordinary differential system, which is stiff and hence poses a challenge to the stability of the entire system. This computational framework is applied to the numerical study of parachute deceleration and cloud microphysics. These two distinct problems can be uniformly modeled with Partial Differential Equations (PDEs) and Ordinary Differential Equations (ODEs), and numerically solved in the same framework. For the parachute simulation, a novel porosity model is proposed to simulate the porous effects of the parachute canopy. This model is easy to implement with the projection method and is able to reproduce Darcy's law observed in the experiment. Moreover, the impacts of using different versions of k-epsilon turbulence model in the parachute simulation have been investigated and conclude that the standard and Re-Normalisation Group (RNG) model may overestimate the turbulence effects when Reynolds number is small while the Realizable model has a consistent performance with both large and small Reynolds number. For another application, cloud microphysics, the cloud entrainment-mixing problem is studied in the same numerical framework. Three sets of DNS are carried out with both decaying and forced turbulence. The numerical result suggests a new way parameterize the cloud mixing degree using the dynamical measures. The numerical experiments also verify the negative relationship between the droplets number concentration and the vorticity field. The results imply that the gravity has fewer impacts on the forced turbulence than the decaying turbulence. In summary, the proposed framework can be used to solve a physics problem that involves turbulence field and point-mass system, and therefore has a broad application.

RACORO Extended-Term Aircraft Observations of Boundary-Layer Clouds

NASA Technical Reports Server (NTRS)

Vogelmann, Andrew M.; McFarquhar, Greg M.; Ogren, John A.; Turner, David D.; Comstock, Jennifer M.; Feingold, Graham; Long, Charles N.; Jonsson, Haflidi H.; Bucholtz, Anthony; Collins, Don R.;

Tropical Convective Responses to Microphysical and Radiative Processes: A Sensitivity Study With a 2D Cloud Resolving Model

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.

Updates on Modeling the Water Cycle with the NASA Ames Mars Global Climate Model

NASA Technical Reports Server (NTRS)

Kahre, M. A.; Haberle, R. M.; Hollingsworth, J. L.; Montmessin, F.; Brecht, A. S.; Urata, R.; Klassen, D. R.; Wolff, M. J.

2017-01-01

Global Circulation Models (GCMs) have made steady progress in simulating the current Mars water cycle. It is now widely recognized that clouds are a critical component that can significantly affect the nature of the simulated water cycle. Two processes in particular are key to implementing clouds in a GCM: the microphysical processes of formation and dissipation, and their radiative effects on heating/ cooling rates. Together, these processes alter the thermal structure, change the dynamics, and regulate inter-hemispheric transport. We have made considerable progress representing these processes in the NASA Ames GCM, particularly in the presence of radiatively active water ice clouds. We present the current state of our group's water cycle modeling efforts, show results from selected simulations, highlight some of the issues, and discuss avenues for further investigation.­

Application of Seasonal CRM Integrations to Develop Statistics and Improved GCM Parameterization of Subgrid Cloud-Radiation Interactions

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

Xiaoqing Wu; Xin-Zhong Liang; Sunwook Park

2007-01-23

The works supported by this ARM project lay the solid foundation for improving the parameterization of subgrid cloud-radiation interactions in the NCAR CCSM and the climate simulations. We have made a significant use of CRM simulations and concurrent ARM observations to produce long-term, consistent cloud and radiative property datasets at the cloud scale (Wu et al. 2006, 2007). With these datasets, we have investigated the mesoscale enhancement of cloud systems on surface heat fluxes (Wu and Guimond 2006), quantified the effects of cloud horizontal inhomogeneity and vertical overlap on the domain-averaged radiative fluxes (Wu and Liang 2005), and subsequently validatedmore » and improved the physically-based mosaic treatment of subgrid cloud-radiation interactions (Liang and Wu 2005). We have implemented the mosaic treatment into the CCM3. The 5-year (1979-1983) AMIP-type simulation showed significant impacts of subgrid cloud-radiation interaction on the climate simulations (Wu and Liang 2005). We have actively participated in CRM intercomparisons that foster the identification and physical understanding of common errors in cloud-scale modeling (Xie et al. 2005; Xu et al. 2005, Grabowski et al. 2005).« less

Sensitivity simulations of superparameterised convection in a general circulation model

NASA Astrophysics Data System (ADS)

Rybka, Harald; Tost, Holger

2015-04-01

Cloud Resolving Models (CRMs) covering a horizontal grid spacing from a few hundred meters up to a few kilometers have been used to explicitly resolve small-scale and mesoscale processes. Special attention has been paid to realistically represent cloud dynamics and cloud microphysics involving cloud droplets, ice crystals, graupel and aerosols. The entire variety of physical processes on the small-scale interacts with the larger-scale circulation and has to be parameterised on the coarse grid of a general circulation model (GCM). Since more than a decade an approach to connect these two types of models which act on different scales has been developed to resolve cloud processes and their interactions with the large-scale flow. The concept is to use an ensemble of CRM grid cells in a 2D or 3D configuration in each grid cell of the GCM to explicitly represent small-scale processes avoiding the use of convection and large-scale cloud parameterisations which are a major source for uncertainties regarding clouds. The idea is commonly known as superparameterisation or cloud-resolving convection parameterisation. This study presents different simulations of an adapted Earth System Model (ESM) connected to a CRM which acts as a superparameterisation. Simulations have been performed with the ECHAM/MESSy atmospheric chemistry (EMAC) model comparing conventional GCM runs (including convection and large-scale cloud parameterisations) with the improved superparameterised EMAC (SP-EMAC) modeling one year with prescribed sea surface temperatures and sea ice content. The sensitivity of atmospheric temperature, precipiation patterns, cloud amount and types is observed changing the embedded CRM represenation (orientation, width, no. of CRM cells, 2D vs. 3D). Additionally, we also evaluate the radiation balance with the new model configuration, and systematically analyse the impact of tunable parameters on the radiation budget and hydrological cycle. Furthermore, the subgrid variability (individual CRM cell output) is analysed in order to illustrate the importance of a highly varying atmospheric structure inside a single GCM grid box. Finally, the convective transport of Radon is observed comparing different transport procedures and their influence on the vertical tracer distribution.

Infrared Retrievals of Ice Cloud Properties and Uncertainties with an Optimal Estimation Retrieval Method

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.

2014-12-01

We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.

Aerosol indirect effects -- general circulation model intercomparison and evaluation with satellite data

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

Quaas, Johannes; Ming, Yi; Menon, Surabi

2009-04-10

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterizes aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (Ta) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found thatmore » the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between Ta and liquid water path is simulated much too strongly by the models. It is shown that this is partly related to the representation of the second aerosol indirect effect in terms of autoconversion. A positive relationship between total cloud fraction (fcld) and Ta as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld - Ta relationship, our results indicate that none can be identified as unique explanation. Relationships similar to the ones found in satellite data between Ta and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - Ta relationship show a strong positive correlation between Ta and fcld The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of Ta, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5+-0.5 Wm-2. An alternative estimate obtained by scaling the simulated clear- and cloudy-sky forcings with estimates of anthropogenic Ta and satellite-retrieved Nd - Ta regression slopes, respectively, yields a global annual mean clear-sky (aerosol direct effect) estimate of -0.4+-0.2 Wm-2 and a cloudy-sky (aerosol indirect effect) estimate of -0.7+-0.5 Wm-2, with a total estimate of -1.2+-0.4 Wm-2.« less

Implementation of warm-cloud processes in a source-oriented WRF/Chem model to study the effect of aerosol mixing state on fog formation in the Central Valley of California

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.

Validation of the large-scale Lagrangian cirrus model CLaMS-Ice by in-situ measurements

NASA Astrophysics Data System (ADS)

Costa, Anja; Rolf, Christian; Grooß, Jens-Uwe; Afchine, Armin; Spelten, Nicole; Dreiling, Volker; Zöger, Martin; Krämer, Martina

2015-04-01

Cirrus clouds are an element of uncertainty in the climate system and have received increasing attention since the last IPCC reports. The interaction of varying freezing meachanisms, sedimentation rates, temperature and updraft velocity fluctuations and other factors that lead to the formation of those clouds is still not fully understood. During the ML-Cirrus campaign 2014 (Germany), the new cirrus cloud model CLaMS-Ice (see Rolf et al., EGU 2015) has been used for flight planning to direct the research aircraft HALO into interesting cirrus cloud regions. Now, after the campaign, we use our in-situ aircraft measurements to validate and improve this model - with the long-term goal to enable it to simulate cirrus cloud cover globally, with reasonable computing times and sufficient accuracy. CLaMS-Ice consists of a two-moment bulk model established by Spichtinger and Gierens (2009a, 2009b), which simulates cirrus clouds along trajectories that the Lagrangian model CLaMS (McKenna et al., 2002 and Konopka et al. 2007) derived from ECMWF data. The model output covers temperature, pressure, relative humidity, ice water content (IWC), and ice crystal numbers (Nice). These parameters were measured on board of HALO by the following instruments: temperature and pressure by BAHAMAS, total and gas phase water by the hygrometers FISH and SHARC (see Meyer et al 2014, submitted to ACP), and Nice as well as ice crystal size distributions by the cloud spectrometer NIXE-CAPS (see also Krämer et al., EGU 2015). Comparisons of the model results with the measurements yield that cirrus clouds can be successfully simulated by CLaMS-Ice. However, there are sections in which the model's relative humidity and Nice deviate considerably from the measured values. This can be traced back to e.g. the initialization of total water from ECMWF data. The simulations are therefore reinitiated with the total water content measured by FISH. Other possible sources of uncertainties are investigated, as imposed temperature fluctuations, numbers and efficencies of heterogeneous ice nuclei or assumptions concerning the sedimentation rates. This contribution sums up the results of these investigations and outlines future work on CLaMS-Ice, that will lead to a tool helping to understand the cirrus clouds under the different environmental conditions during ML-Cirrus.

Modeling and simulation of dense cloud dispersion in urban areas by means of computational fluid dynamics.

PubMed

Scargiali, F; Grisafi, F; Busciglio, A; Brucato, A

2011-12-15

The formation of toxic heavy clouds as a result of sudden accidental releases from mobile containers, such as road tankers or railway tank cars, may occur inside urban areas so the problem arises of their consequences evaluation. Due to the semi-confined nature of the dispersion site simplified models may often be inappropriate. As an alternative, computational fluid dynamics (CFD) has the potential to provide realistic simulations even for geometrically complex scenarios since the heavy gas dispersion process is described by basic conservation equations with a reduced number of approximations. In the present work a commercial general purpose CFD code (CFX 4.4 by Ansys(®)) is employed for the simulation of dense cloud dispersion in urban areas. The simulation strategy proposed involves a stationary pre-release flow field simulation followed by a dynamic after-release flow and concentration field simulations. In order to try a generalization of results, the computational domain is modeled as a simple network of straight roads with regularly distributed blocks mimicking the buildings. Results show that the presence of buildings lower concentration maxima and enlarge the side spread of the cloud. Dispersion dynamics is also found to be strongly affected by the quantity of heavy-gas released. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

RACORO Continental Boundary Layer Cloud Investigations: 1. Case Study Development and Ensemble Large-Scale Forcings

NASA Technical Reports Server (NTRS)

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang;

RACORO continental boundary layer cloud investigations: 1. Case study development and ensemble large-scale forcings

NASA Astrophysics Data System (ADS)

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; Endo, Satoshi; Lin, Wuyin; Wang, Jian; Feng, Sha; Zhang, Yunyan; Turner, David D.; Liu, Yangang; Li, Zhijin; Xie, Shaocheng; Ackerman, Andrew S.; Zhang, Minghua; Khairoutdinov, Marat

2015-06-01

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60 h case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in situ measurements from the Routine AAF (Atmospheric Radiation Measurement (ARM) Aerial Facility) CLOWD (Clouds with Low Optical Water Depth) Optical Radiative Observations (RACORO) field campaign and remote sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functions for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be 0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing data sets are derived from the ARM variational analysis, European Centre for Medium-Range Weather Forecasts, and a multiscale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in "trial" large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.

Assessment of simulation of radiation in NCEP Climate Forecasting System (CFS V2)

NASA Astrophysics Data System (ADS)

Goswami, Tanmoy; Rao, Suryachandra A.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Dhakate, Ashish; Salunke, Kiran; Mahapatra, Somnath

2017-09-01

The objective of this study is to identify and document the radiation biases in the latest National Centers for Environment Prediction (NCEP), Climate Forecasting System (CFSv2) and to investigate the probable reasons for these biases. This analysis is made over global and Indian domain under all-sky and clear-sky conditions. The impact of increasing the horizontal resolution of the atmospheric model on these biases is also investigated by comparing results of two different horizontal resolution versions of CFSv2 namely T126 and T382. The difference between the top of the atmosphere and surface energy imbalance in T126 (T382) is 3.49 (2.78) W/m2. This reduction of bias in the high resolution model is achieved due to lesser low cloud cover, resulting more surface insolation, and due to more latent heat fluxes at the surface. Compared to clear sky simulations, all sky simulations exhibit larger biases suggesting that the cloud covers are not simulated well in the model. The annual mean high level cloud cover is over estimated over the global as well as the Indian domain. This overestimation over the Indian domain is also present during JJAS. There is also evidence that both of the models have insufficient water vapour in their atmosphere. This study suggests that in order to improve the model's mean radiation climatology, simulation of clouds in the model also needs to be improved, and future model development activities should focus on this aspect.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Comparisons of Mixed-Phase Icing Cloud Simulations with Experiments Conducted at the NASA Propulsion Systems Laboratory

NASA Technical Reports Server (NTRS)

Bartkus, Tadas; Tsao, Jen-Ching; Struk, Peter

2017-01-01

This paper builds on previous work that compares numerical simulations of mixed-phase icing clouds with experimental data. The model couples the thermal interaction between ice particles and water droplets of the icing cloud with the flowing air of an icing wind tunnel for simulation of NASA Glenn Research Centers (GRC) Propulsion Systems Laboratory (PSL). Measurements were taken during the Fundamentals of Ice Crystal Icing Physics Tests at the PSL tunnel in March 2016. The tests simulated ice-crystal and mixed-phase icing that relate to ice accretions within turbofan engines.

The Surface Energy Budget and Precipitation Efficiency for Convective Systems During TOGA, COARE, GATE, SCSMEX and ARM: Cloud-Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Shie, C.-L.; Johnson, D; Simpson, J.; Starr, David OC. (Technical Monitor)

2002-01-01

A two-dimensional version of the Goddard Cumulus Ensemble (GCE) Model is used to simulate convective systems that developed in various geographic locations. Observed large-scale advective tendencies for potential temperature, water vapor mixing ratio, and horizontal momentum derived from field campaigns are used as the main forcing. By examining the surface energy budgets, the model results show that the two largest terms are net condensation (heating/drying) and imposed large-scale forcing (cooling/moistening) for tropical oceanic cases. These two terms arc opposite in sign, however. The contributions by net radiation and latent heat flux to the net condensation vary in these tropical cases, however. For cloud systems that developed over the South China Sea and eastern Atlantic, net radiation (cooling) accounts for about 20% or more of the net condensation. However, short-wave heating and long-wave cooling are in balance with each other for cloud systems over the West Pacific region such that the net radiation is very small. This is due to the thick anvil clouds simulated in the cloud systems over the Pacific region. Large-scale cooling exceeds large-scale moistening in the Pacific and Atlantic cases. For cloud systems over the South China Sea, however, there is more large-scale moistening than cooling even though the cloud systems developed in a very moist environment. though For three cloud systems that developed over a mid-latitude continent, the net radiation and sensible and latent heat fluxes play a much more important role. This means the accurate measurement of surface fluxes and radiation is crucial for simulating these mid-latitude cases.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J. R.; Maslanik, J. A.

1988-01-01

The principal objectives of this project are: (1) to develop suitable validation data sets to evaluate the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; (2) to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers; and (3) to compare synoptic cloud data from a control run experiment of the GISS climate model II with typical observed synoptic cloud patterns.

Cirrus clouds. I - A cirrus cloud model. II - Numerical experiments on the formation and maintenance of cirrus

NASA Technical Reports Server (NTRS)

Starr, D. OC.; Cox, S. K.

1985-01-01

A simplified cirrus cloud model is presented which may be used to investigate the role of various physical processes in the life cycle of a cirrus cloud. The model is a two-dimensional, time-dependent, Eulerian numerical model where the focus is on cloud-scale processes. Parametrizations are developed to account for phase changes of water, radiative processes, and the effects of microphysical structure on the vertical flux of ice water. The results of a simulation of a thin cirrostratus cloud are given. The results of numerical experiments performed with the model are described in order to demonstrate the important role of cloud-scale processes in determining the cloud properties maintained in response to larger scale forcing. The effects of microphysical composition and radiative processes are considered, as well as their interaction with thermodynamic and dynamic processes within the cloud. It is shown that cirrus clouds operate in an entirely different manner than liquid phase stratiform clouds.

Role of Longwave Cloud-Radiation Feedback in the Simulation of the Madden-Julian Oscillation

NASA Technical Reports Server (NTRS)

Kim, Daehyun; Ahn, Min-Seop; Kang, In-Sik; Del Genio, Anthony D.

2015-01-01

The role of the cloud-radiation interaction in the simulation of the Madden-Julian oscillation (MJO) is investigated. A special focus is on the enhancement of column-integrated diabatic heating due to the greenhouse effects of clouds and moisture in the region of anomalous convection. The degree of this enhancement, the greenhouse enhancement factor (GEF), is measured at different precipitation anomaly regimes as the negative ratio of anomalous outgoing longwave radiation to anomalous precipitation. Observations show that the GEF varies significantly with precipitation anomaly and with the MJO cycle. The greenhouse enhancement is greater in weak precipitation anomaly regimes and its effectiveness decreases monotonically with increasing precipitation anomaly. The GEF also amplifies locally when convection is strengthened in association with the MJO, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). A robust statistical relationship is found among CMIP5 climate model simulations between the GEF and the MJO simulation fidelity. Models that simulate a stronger MJO also simulate a greater GEF, especially in the weak precipitation anomaly regime (less than 5 mm day(exp -1)). Models with a greater GEF in the strong precipitation anomaly regime (greater than 30 mm day(-1)) represent a slightly slower MJO propagation speed. Many models that lack the MJO underestimate the GEF in general and in particular in the weak precipitation anomaly regime. The results herein highlight that the cloud-radiation interaction is a crucial process for climate models to correctly represent the MJO.

Effects of Implementing Subgrid-Scale Cloud-Radiation Interactions in a Regional Climate Model

NASA Astrophysics Data System (ADS)

Herwehe, J. A.; Alapaty, K.; Otte, T.; Nolte, C. G.

2012-12-01

Interactions between atmospheric radiation, clouds, and aerosols are the most important processes that determine the climate and its variability. In regional scale models, when used at relatively coarse spatial resolutions (e.g., larger than 1 km), convective cumulus clouds need to be parameterized as subgrid-scale clouds. Like many groups, our regional climate modeling group at the EPA uses the Weather Research & Forecasting model (WRF) as a regional climate model (RCM). One of the findings from our RCM studies is that the summertime convective systems simulated by the WRF model are highly energetic, leading to excessive surface precipitation. We also found that the WRF model does not consider the interactions between convective clouds and radiation, thereby omitting an important process that drives the climate. Thus, the subgrid-scale cloudiness associated with convective clouds (from shallow cumuli to thunderstorms) does not exist and radiation passes through the atmosphere nearly unimpeded, potentially leading to overly energetic convection. This also has implications for air quality modeling systems that are dependent upon cloud properties from the WRF model, as the failure to account for subgrid-scale cloudiness can lead to problems such as the underrepresentation of aqueous chemistry processes within clouds and the overprediction of ozone from overactive photolysis. In an effort to advance the climate science of the cloud-aerosol-radiation (CAR) interactions in RCM systems, as a first step we have focused on linking the cumulus clouds with the radiation processes. To this end, our research group has implemented into WRF's Kain-Fritsch (KF) cumulus parameterization a cloudiness formulation that is widely used in global earth system models (e.g., CESM/CAM5). Estimated grid-scale cloudiness and associated condensate are adjusted to account for the subgrid clouds and then passed to WRF's Rapid Radiative Transfer Model - Global (RRTMG) radiation schemes to affect the shortwave and longwave radiative processes. To evaluate the effects of implementing the subgrid-scale cloud-radiation interactions on WRF regional climate simulations, a three-year study period (1988-1990) was simulated over the CONUS using two-way nested domains with 108 km and 36 km horizontal grid spacing, without and with the cumulus feedbacks to radiation, and without and with some form of four dimensional data assimilation (FDDA). Initial and lateral boundary conditions (as well as data for the FDDA, when enabled) were supplied from downscaled NCEP-NCAR Reanalysis II (R2) data sets. Evaluation of the simulation results will be presented comparing regional surface precipitation and temperature statistics with North American Regional Reanalysis (NARR) data and Climate Forecast System Reanalysis (CFSR) data, respectively, as well as comparison with available surface radiation (SURFRAD) and satellite (CERES) observations. This research supports improvements in the EPA's WRF-CMAQ modeling system, leading to better predictions of present and future air quality and climate interactions in order to protect human health and the environment.

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

PubMed

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

PubMed Central

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 role of global cloud climatologies in validating numerical models

NASA Technical Reports Server (NTRS)

HARSHVARDHAN

1991-01-01

The net upward longwave surface radiation is exceedingly difficult to measure from space. A hybrid method using General Circulation Model (GCM) simulations and satellite data from the Earth Radiation Budget Experiment (ERBE) and the International Satellite Cloud Climatology Project (ISCCP) was used to produce global maps of this quantity over oceanic areas. An advantage of this technique is that no independent knowledge or assumptions regarding cloud cover for a particular month are required. The only information required is a relationship between the cloud radiation forcing (CRF) at the top of the atmosphere and that at the surface, which is obtained from the GCM simulation. A flow diagram of the technique and results are given.

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Simulating Aerosol Indirect Effects with Improved Aerosol-Cloud- Precipitation Representations in a Coupled Regional Climate Model

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

Zhang, Yang; Leung, L. Ruby; Fan, Jiwen

This is a collaborative project among North Carolina State University, Pacific Northwest National Laboratory, and Scripps Institution of Oceanography, University of California at San Diego to address the critical need for an accurate representation of aerosol indirect effect in climate and Earth system models. In this project, we propose to develop and improve parameterizations of aerosol-cloud-precipitation feedbacks in climate models and apply them to study the effect of aerosols and clouds on radiation and hydrologic cycle. Our overall objective is to develop, improve, and evaluate parameterizations to enable more accurate simulations of these feedbacks in high resolution regional and globalmore » climate models.« less

Clouds in GEOS-5

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

Fine-scale application of WRF-CAM5 during a dust storm episode over East Asia: Sensitivity to grid resolutions and aerosol activation parameterizations

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.

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

DOE PAGES

Hagos, Samson; Feng, Zhe; Plant, Robert S.; ...

2018-02-20

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

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

A Stochastic Framework for Modeling the Population Dynamics of Convective Clouds

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

Hagos, Samson; Feng, Zhe; Plant, Robert S.

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

Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models

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

Robert A. Houze, Jr.

2013-11-13

We examined cloud radar data in monsoon climates, using cloud radars at Darwin in the Australian monsoon, on a ship in the Bay of Bengal in the South Asian monsoon, and at Niamey in the West African monsoon. We followed on with a more in-depth study of the continental MCSs over West Africa. We investigated whether the West African anvil clouds connected with squall line MCSs passing over the Niamey ARM site could be simulated in a numerical model by comparing the observed anvil clouds to anvil structures generated by the Weather Research and Forecasting (WRF) mesoscale model at highmore » resolution using six different ice-phase microphysical schemes. We carried out further simulations with a cloud-resolving model forced by sounding network budgets over the Niamey region and over the northern Australian region. We have devoted some of the effort of this project to examining how well satellite data can determine the global breadth of the anvil cloud measurements obtained at the ARM ground sites. We next considered whether satellite data could be objectively analyzed to so that their large global measurement sets can be systematically related to the ARM measurements. Further differences were detailed between the land and ocean MCS anvil clouds by examining the interior structure of the anvils with the satellite-detected the CloudSat Cloud Profiling Radar (CPR). The satellite survey of anvil clouds in the Indo-Pacific region was continued to determine the role of MCSs in producing the cloud pattern associated with the MJO.« less

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.

Investigating ice nucleation in cirrus clouds with an aerosol-enabled Multiscale Modeling Framework

DOE PAGES

Zhang, Chengzhu; Wang, Minghuai; Morrison, H.; ...

2014-11-06

In this study, an aerosol-dependent ice nucleation scheme [Liu and Penner, 2005] has been implemented in an aerosol-enabled multi-scale modeling framework (PNNL MMF) to study ice formation in upper troposphere cirrus clouds through both homogeneous and heterogeneous nucleation. The MMF model represents cloud scale processes by embedding a cloud-resolving model (CRM) within each vertical column of a GCM grid. By explicitly linking ice nucleation to aerosol number concentration, CRM-scale temperature, relative humidity and vertical velocity, the new MMF model simulates the persistent high ice supersaturation and low ice number concentration (10 to 100/L) at cirrus temperatures. The low ice numbermore » is attributed to the dominance of heterogeneous nucleation in ice formation. The new model simulates the observed shift of the ice supersaturation PDF towards higher values at low temperatures following homogeneous nucleation threshold. The MMF models predict a higher frequency of midlatitude supersaturation in the Southern hemisphere and winter hemisphere, which is consistent with previous satellite and in-situ observations. It is shown that compared to a conventional GCM, the MMF is a more powerful model to emulate parameters that evolve over short time scales such as supersaturation. Sensitivity tests suggest that the simulated global distribution of ice clouds is sensitive to the ice nucleation schemes and the distribution of sulfate and dust aerosols. Simulations are also performed to test empirical parameters related to auto-conversion of ice crystals to snow. Results show that with a value of 250 μm for the critical diameter, Dcs, that distinguishes ice crystals from snow, the model can produce good agreement to the satellite retrieved products in terms of cloud ice water path and ice water content, while the total ice water is not sensitive to the specification of Dcs value.« less

WRF Simulations of the 20-22 January 2007 Snow Events over Eastern Canada: Comparison with In-Situ and Satellite Observations

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.;

Multiyear applications of WRF/Chem over continental U.S.: Model evaluation, variation trend, and impacts of boundary conditions

NASA Astrophysics Data System (ADS)

Yahya, Khairunnisa; He, Jian; Zhang, Yang

2015-12-01

Multiyear applications of an online-coupled meteorology-chemistry model allow an assessment of the variation trends in simulated meteorology, air quality, and their interactions to changes in emissions and meteorology, as well as the impacts of initial and boundary conditions (ICONs/BCONs) on simulated aerosol-cloud-radiation interactions over a period of time. In this work, the Weather Research and Forecasting model with Chemistry version 3.4.1 (WRF/Chem v. 3.4.1) with the 2005 Carbon Bond mechanism coupled with the Volatility Basis Set module for secondary organic aerosol formation (WRF/Chem-CB05-VBS) is applied for multiple years (2001, 2006, and 2010) over continental U.S. This work also examines the changes in simulated air quality and meteorology due to changes in emissions and meteorology and the model's capability in reproducing the observed variation trends in species concentrations from 2001 to 2010. In addition, the impacts of the chemical ICONs/BCONs on model predictions are analyzed. ICONs/BCONs are downscaled from two global models, the modified Community Earth System Model/Community Atmosphere model version 5.1 (CESM/CAM v5.1) and the Monitoring Atmospheric Composition and Climate model (MACC). The evaluation of WRF/Chem-CB05-VBS simulations with the CESM ICONs/BCONs for 2001, 2006, and 2010 shows that temperature at 2 m (T2) is underpredicted for all three years likely due to inaccuracies in soil moisture and soil temperature, resulting in biases in surface relative humidity, wind speed, and precipitation. With the exception of cloud fraction, other aerosol-cloud variables including aerosol optical depth, cloud droplet number concentration, and cloud optical thickness are underpredicted for all three years, resulting in overpredictions of radiation variables. The model performs well for O3 and particulate matter with diameter less than or equal to 2.5 (PM2.5) for all three years comparable to other studies from literature. The model is able to reproduce observed annual average trends in O3 and PM2.5 concentrations from 2001 to 2006 and from 2006 to 2010 but is less skillful in simulating their observed seasonal trends. The 2006 and 2010 results using CESM and MACC ICONs/BCONs are compared to analyze the impact of ICONs/BCONs on model performance and their feedbacks to aerosol, clouds, and radiation. Comparing to the simulations with MACC ICONs/BCONs, the simulations with the CESM ICONs/BCONs improve the performance of O3 mixing ratios (e.g., the normalized mean bias for maximum 8 h O3 is reduced from -17% to -1% in 2010), PM2.5 in 2010, and sulfate in 2006 (despite a slightly larger normalized mean bias for PM2.5 in 2006). The impacts of different ICONs/BCONs on simulated aerosol-cloud-radiation variables are not negligible, with larger impacts in 2006 compared to 2010.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

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.

Large-scale simulations and in-situ observations of mid-latitude and Arctic cirrus clouds

NASA Astrophysics Data System (ADS)

Rolf, Christian; Grooß, Jens-Uwe; Spichtinger, Peter; Costa, Anja; Krämer, Martina

2017-04-01

Cirrus clouds play an important role by influencing the Earth's radiation budget and the global climate (Heintzenberg and Charlson, 2009). The formation and further evolution of cirrus clouds is determined by the interplay of temperature, ice nuclei (IN) properties, relative humidity, cooling rates and ice crystal sedimentation. Thus, for a realistic simulation of cirrus clouds, a Lagrangian approach using meteorological wind fields is the best way to represent complete cirrus systems as e.g. frontal cirrus. To this end, we coupled the two moment microphysical ice model of Spichtinger and Gierens (2009) with the 3D Lagrangian model CLaMS (McKenna et al., 2002). The new CLaMS-Ice module simulates cirrus formation by including heterogeneous and homogeneous freezing as well as ice crystal sedimentation. The boxmodel is operated along CLaMS trajectories and individually initialized with the ECMWF meteorological fields. From the CLaMS-Ice three dimensional large scale cirrus simulations, we are able to assign the formation mechanism - either heterogeneous or homogeneous freezing - to specific combinations of temperatures and ice water contents. First, we compare a large mid-latitude dataset of in-situ measured cirrus microphysical properties compiled from the ML-Cirrus aircraft campaign in 2014 to ClaMS-Ice model simulations. We investigate the number of ice crystals and the ice water content with respect to temperature in a climatological way and found a good and consistent agreement between measurement and simulations. We also found that most (67 %) of the cirrus cloud cover in mid-latitude is dominated by heterogeneously formed ice crystals. Second, CLaMS-Ice model simulations in the Arctic/Polar region are performed during the POLSTRACC aircraft campaign in 2016. Higher ice crystal number concentrations are found more frequently in the Arctic region in comparison to the mid-latitude dataset. This is caused by enhanced gravity wave activity over the mountainous terrain. References: Heintzenberg, J. and Charlson, R. J.: Clouds in the perturbed climate system - Their relationship to energy balance, atmospheric dynamics, and precipitation, MIT Press, Cambridge, UK, 58-72, 2009. McKenna, D. S., Konopka, P., Grooss, J. U., Günther, G., Müller, R., Spang, R., Offermann, D.,and Orsolini, Y.: A new Chemical Lagrangian Model of the Stratosphere (CLaMS) - 1. Formulation of advection and mixing, J. Geophys. Res., 107, 4309, doi:10.1029/2000JD000114, 2002. Spichtinger, P. and Gierens, K. M.: Modelling of cirrus clouds - Part 1a: Model description and validation, Atmospheric Chemistry and Physics, 9, 685-706, 2009.

The Rossby Centre Regional Atmospheric Climate Model part II: application to the Arctic climate.

PubMed

Jones, Colin G; Wyser, Klaus; Ullerstig, Anders; Willén, Ulrika

2004-06-01

The Rossby Centre regional climate model (RCA2) has been integrated over the Arctic Ocean as part of the international ARCMIP project. Results have been compared to observations derived from the SHEBA data set. The standard RCA2 model overpredicts cloud cover and downwelling longwave radiation, during the Arctic winter. This error was improved by introducing a new cloud parameterization, which significantly improves the annual cycle of cloud cover. Compensating biases between clear sky downwelling longwave radiation and longwave radiation emitted from cloud base were identified. Modifications have been introduced to the model radiation scheme that more accurately treat solar radiation interaction with ice crystals. This leads to a more realistic representation of cloud-solar radiation interaction. The clear sky portion of the model radiation code transmits too much solar radiation through the atmosphere, producing a positive bias at the top of the frequent boundary layer clouds. A realistic treatment of the temporally evolving albedo, of both sea-ice and snow, appears crucial for an accurate simulation of the net surface energy budget. Likewise, inclusion of a prognostic snow-surface temperature seems necessary, to accurately simulate near-surface thermodynamic processes in the Arctic.

Anthropogenic Sulfate, Clouds, and Climate Forcing

NASA Technical Reports Server (NTRS)

Ghan, Steven J.

1997-01-01

This research work is a joint effort between research groups at the Battelle Pacific Northwest Laboratory, Virginia Tech University, Georgia Institute of Technology, Brookhaven National Laboratory, and Texas A&M University. It has been jointly sponsored by the National Aeronautics and Space Administration, the U.S. Department of Energy, and the U.S. Environmental Protection Agency. In this research, a detailed tropospheric aerosol-chemistry model that predicts oxidant concentrations as well as concentrations of sulfur dioxide and sulfate aerosols has been coupled to a general circulation model that distinguishes between cloud water mass and cloud droplet number. The coupled model system has been first validated and then used to estimate the radiative impact of anthropogenic sulfur emissions. Both the direct radiative impact of the aerosols and their indirect impact through their influence on cloud droplet number are represented by distinguishing between sulfuric acid vapor and fresh and aged sulfate aerosols, and by parameterizing cloud droplet nucleation in terms of vertical velocity and the number concentration of aged sulfur aerosols. Natural sulfate aerosols, dust, and carbonaceous and nitrate aerosols and their influence on the radiative impact of anthropogenic sulfate aerosols, through competition as cloud condensation nuclei, will also be simulated. Parallel simulations with and without anthropogenic sulfur emissions are performed for a global domain. The objectives of the research are: To couple a state-of-the-art tropospheric aerosol-chemistry model with a global climate model. To use field and satellite measurements to evaluate the treatment of tropospheric chemistry and aerosol physics in the coupled model. To use the coupled model to simulate the radiative (and ultimately climatic) impacts of anthropogenic sulfur emissions.

Transitions of cloud-topped marine boundary layers characterized by AIRS, MODIS, and a large eddy simulation model

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

Yue, Qing; Kahn, Brian; Xiao, Heng

2013-08-16

Cloud top entrainment instability (CTEI) is a hypothesized positive feedback between entrainment mixing and evaporative cooling near the cloud top. Previous theoretical and numerical modeling studies have shown that the persistence or breakup of marine boundary layer (MBL) clouds may be sensitive to the CTEI parameter. Collocated thermodynamic profile and cloud observations obtained from the Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are used to quantify the relationship between the CTEI parameter and the cloud-topped MBL transition from stratocumulus to trade cumulus in the northeastern Pacific Ocean. Results derived from AIRS and MODIS are compared withmore » numerical results from the UCLA large eddy simulation (LES) model for both well-mixed and decoupled MBLs. The satellite and model results both demonstrate a clear correlation between the CTEI parameter and MBL cloud fraction. Despite fundamental differences between LES steady state results and the instantaneous snapshot type of observations from satellites, significant correlations for both the instantaneous pixel-scale observations and the long-term averaged spatial patterns between the CTEI parameter and MBL cloud fraction are found from the satellite observations and are consistent with LES results. This suggests the potential of using AIRS and MODIS to quantify global and temporal characteristics of the cloud-topped MBL transition.« less

Investigation of unsteadiness in Shock-particle cloud interaction: Fully resolved two-dimensional simulation and one-dimensional modeling

NASA Astrophysics Data System (ADS)

Hosseinzadeh-Nik, Zahra; Regele, Jonathan D.

2015-11-01

Dense compressible particle-laden flow, which has a complex nature, exists in various engineering applications. Shock waves impacting a particle cloud is a canonical problem to investigate this type of flow. It has been demonstrated that large flow unsteadiness is generated inside the particle cloud from the flow induced by the shock passage. It is desirable to develop models for the Reynolds stress to capture the energy contained in vortical structures so that volume-averaged models with point particles can be simulated accurately. However, the previous work used Euler equations, which makes the prediction of vorticity generation and propagation innacurate. In this work, a fully resolved two dimensional (2D) simulation using the compressible Navier-Stokes equations with a volume penalization method to model the particles has been performed with the parallel adaptive wavelet-collocation method. The results still show large unsteadiness inside and downstream of the particle cloud. A 1D model is created for the unclosed terms based upon these 2D results. The 1D model uses a two-phase simple low dissipation AUSM scheme (TSLAU) developed by coupled with the compressible two phase kinetic energy equation.

Far-Field Simulation of the Hawaiian Wake: Sea Surface Temperature and Orographic Effects(.

NASA Astrophysics Data System (ADS)

Hafner, Jan; Xie, Shang-Ping

2003-12-01

Recent satellite observations reveal far-reaching effects of the Hawaiian Islands on surface wind, cloud, ocean current, and sea surface temperature (SST) that extend leeward over an unusually long distance (>1000 km). A three-dimensional regional atmospheric model with full physics is used to investigate the cause of this long wake. While previous wind wake studies tend to focus on regions near the islands, the emphasis here is the far-field effects of SST and orography well away from the Hawaiian Islands. In response to an island-induced SST pattern, the model produces surface wind and cloud anomaly patterns that resemble those observed by satellites. In particular, anomalous surface winds are found to converge onto a zonal band of warmer water, with cloud liquid water content enhanced over it but reduced on the northern and southern sides. In the vertical, a two-cell meridional circulation develops of a baroclinic structure with the rising motion and thicker clouds over the warm water band. The model response in the wind and cloud fields supports the hypothesis that ocean atmosphere interaction is crucial for sustaining the island effects over a few thousand kilometers.Near Hawaii, mountains generate separate wind wakes in the model lee of individual islands as observed by satellites. Under orographic forcing, the model simulates the windward cloud line and the southwest-tilted cloud band leeward of the Big Island. In the far field, orographically induced wind perturbations are found to be in geostrophic balance with pressure anomalies, indicative of quasigeostrophic Rossby wave propagation. A shallow-water model is developed for disturbances trapped in the inversion-capped planetary boundary layer. The westward propagation of Rossby waves is found to increase the wake length significantly, consistent with the three-dimensional simulation.

Modeling the Hydrological Cycle in the Atmosphere of Mars: Influence of a Bimodal Size Distribution of Aerosol Nucleation Particles

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.

Clouds enhance Greenland ice sheet mass loss

NASA Astrophysics Data System (ADS)

Van Tricht, Kristof; Gorodetskaya, Irina V.; L'Ecuyer, Tristan; Lenaerts, Jan T. M.; Lhermitte, Stef; Noel, Brice; Turner, David D.; van den Broeke, Michiel R.; van Lipzig, Nicole P. M.

2015-04-01

Clouds have a profound influence on both the Arctic and global climate, while they still represent one of the key uncertainties in climate models, limiting the fidelity of future climate projections. The potentially important role of thin liquid-containing clouds over Greenland in enhancing ice sheet melt has recently gained interest, yet current research is spatially and temporally limited, focusing on particular events, and their large scale impact on the surface mass balance remains unknown. We used a combination of satellite remote sensing (CloudSat - CALIPSO), ground-based observations and climate model (RACMO) data to show that liquid-containing clouds warm the Greenland ice sheet 94% of the time. High surface reflectivity (albedo) for shortwave radiation reduces the cloud shortwave cooling effect on the absorbed fluxes, while not influencing the absorption of longwave radiation. Cloud warming over the ice sheet therefore dominates year-round. Only when albedo values drop below ~0.6 in the coastal areas during summer, the cooling effect starts to overcome the warming effect. The year-round excess of energy due to the presence of liquid-containing clouds has an extensive influence on the mass balance of the ice sheet. Simulations using the SNOWPACK snow model showed not only a strong influence of these liquid-containing clouds on melt increase, but also on the increased sublimation mass loss. Simulations with the Community Earth System Climate Model for the end of the 21st century (2080-2099) show that Greenland clouds contain more liquid water path and less ice water path. This implies that cloud radiative forcing will be further enhanced in the future. Our results therefore urge the need for improving cloud microphysics in climate models, to improve future projections of ice sheet mass balance and global sea level rise.

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

NASA Astrophysics Data System (ADS)

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

2003-04-01

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

Testing the Two-Layer Model for Correcting Clear Sky Reflectance near Clouds

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Evans, Frank; Varnai, Tamas; Levy, Rob

2015-01-01

A two-layer model (2LM) was developed in our earlier studies to estimate the clear sky reflectance enhancement due to cloud-molecular radiative interaction at MODIS at 0.47 micrometers. Recently, we extended the model to include cloud-surface and cloud-aerosol radiative interactions. We use the LES/SHDOM simulated 3D true radiation fields to test the 2LM for reflectance enhancement at 0.47 micrometers. We find: The simple model captures the viewing angle dependence of the reflectance enhancement near cloud, suggesting the physics of this model is correct; the cloud-molecular interaction alone accounts for 70 percent of the enhancement; the cloud-surface interaction accounts for 16 percent of the enhancement; the cloud-aerosol interaction accounts for an additional 13 percent of the enhancement. We conclude that the 2LM is simple to apply and unbiased.

Implementation of warm-cloud processes in a source-oriented WRF/Chem model to study the effect of aerosol mixing state on fog formation in the Central Valley of California

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.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Evidence for climate change in the satellite cloud record

DOE PAGES

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.; ...

2016-07-11

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

Evidence for climate change in the satellite cloud record

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

Norris, Joel R.; Allen, Robert J.; Evan, Amato T.

Clouds substantially affect Earth’s energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space 1. They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming 2, 3. This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts 4, 5. Here we show that several independent,more » empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. Here, these results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.« less

Application and Evaluation of an Explicit Prognostic Cloud-Cover Scheme in GRAPES Global Forecast System

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.

Comparison of aerosol optical properties above clouds between POLDER and AeroCom models over the South East Atlantic Ocean during the fire season

NASA Astrophysics Data System (ADS)

Peers, F.; Bellouin, N.; Waquet, F.; Ducos, F.; Goloub, P.; Mollard, J.; Myhre, G.; Skeie, R. B.; Takemura, T.; Tanré, D.; Thieuleux, F.; Zhang, K.

2016-04-01

Aerosol properties above clouds have been retrieved over the South East Atlantic Ocean during the fire season 2006 using satellite observations from POLDER (Polarization and Directionality of Earth Reflectances). From June to October, POLDER has observed a mean Above-Cloud Aerosol Optical Thickness (ACAOT) of 0.28 and a mean Above-Clouds Single Scattering Albedo (ACSSA) of 0.87 at 550 nm. These results have been used to evaluate the simulation of aerosols above clouds in five Aerosol Comparisons between Observations and Models (Goddard Chemistry Aerosol Radiation and Transport (GOCART), Hadley Centre Global Environmental Model 3 (HadGEM3), European Centre Hamburg Model 5-Hamburg Aerosol Module 2 (ECHAM5-HAM2), Oslo-Chemical Transport Model 2 (OsloCTM2), and Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS)). Most models do not reproduce the observed large aerosol load episodes. The comparison highlights the importance of the injection height and the vertical transport parameterizations to simulate the large ACAOT observed by POLDER. Furthermore, POLDER ACSSA is best reproduced by models with a high imaginary part of black carbon refractive index, in accordance with recent recommendations.

An efficient framework for modeling clouds from Landsat8 images

NASA Astrophysics Data System (ADS)

Yuan, Chunqiang; Guo, Jing

2015-03-01

Cloud plays an important role in creating realistic outdoor scenes for video game and flight simulation applications. Classic methods have been proposed for cumulus cloud modeling. However, these methods are not flexible for modeling large cloud scenes with hundreds of clouds in that the user must repeatedly model each cloud and adjust its various properties. This paper presents a meteorologically based method to reconstruct cumulus clouds from high resolution Landsat8 satellite images. From these input satellite images, the clouds are first segmented from the background. Then, the cloud top surface is estimated from the temperature of the infrared image. After that, under a mild assumption of flat base for cumulus cloud, the base height of each cloud is computed by averaging the top height for pixels on the cloud edge. Then, the extinction is generated from the visible image. Finally, we enrich the initial shapes of clouds using a fractal method and represent the recovered clouds as a particle system. The experimental results demonstrate our method can yield realistic cloud scenes resembling those in the satellite images.

The relationship between interannual and long-term cloud feedbacks

DOE PAGES

Zhou, Chen; Zelinka, Mark D.; Dessler, Andrew E.; ...

2015-12-11

The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual andmore » long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.« 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.

Continental Shallow Convection Cloud-Base Mass Flux from Doppler Lidar and LASSO Ensemble Large-Eddy Simulations

NASA Astrophysics Data System (ADS)

Vogelmann, A. M.; Zhang, D.; Kollias, P.; Endo, S.; Lamer, K.; Gustafson, W. I., Jr.; Romps, D. M.

2017-12-01

Continental boundary layer clouds are important to simulations of weather and climate because of their impact on surface budgets and vertical transports of energy and moisture; however, model-parameterized boundary layer clouds do not agree well with observations in part because small-scale turbulence and convection are not properly represented. To advance parameterization development and evaluation, observational constraints are needed on critical parameters such as cloud-base mass flux and its relationship to cloud cover and the sub-cloud boundary layer structure including vertical velocity variance and skewness. In this study, these constraints are derived from Doppler lidar observations and ensemble large-eddy simulations (LES) from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Facility Southern Great Plains (SGP) site in Oklahoma. The Doppler lidar analysis will extend the single-site, long-term analysis of Lamer and Kollias [2015] and augment this information with the short-term but unique 1-2 year period since five Doppler lidars began operation at the SGP, providing critical information on regional variability. These observations will be compared to the statistics obtained from ensemble, routine LES conducted by the LES ARM Symbiotic Simulation and Observation (LASSO) project (https://www.arm.gov/capabilities/modeling/lasso). An Observation System Simulation Experiment (OSSE) will be presented that uses the LASSO LES fields to determine criteria for which relationships from Doppler lidar observations are adequately sampled to yield convergence. Any systematic differences between the observed and simulated relationships will be examined to understand factors contributing to the differences. Lamer, K., and P. Kollias (2015), Observations of fair-weather cumuli over land: Dynamical factors controlling cloud size and cover, Geophys. Res. Lett., 42, 8693-8701, doi:10.1002/2015GL064534

How Difficult is it to Reduce Low-Level Cloud Biases With the Higher-Order Turbulence Closure Approach in Climate Models?

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2015-01-01

Low-level clouds cover nearly half of the Earth and play a critical role in regulating the energy and hydrological cycle. Despite the fact that a great effort has been put to advance the modeling and observational capability in recent years, low-level clouds remains one of the largest uncertainties in the projection of future climate change. Low-level cloud feedbacks dominate the uncertainty in the total cloud feedback in climate sensitivity and projection studies. These clouds are notoriously difficult to simulate in climate models due to its complicated interactions with aerosols, cloud microphysics, boundary-layer turbulence and cloud dynamics. The biases in both low cloud coverage/water content and cloud radiative effects (CREs) remain large. A simultaneous reduction in both cloud and CRE biases remains elusive. This presentation first reviews the effort of implementing the higher-order turbulence closure (HOC) approach to representing subgrid-scale turbulence and low-level cloud processes in climate models. There are two HOCs that have been implemented in climate models. They differ in how many three-order moments are used. The CLUBB are implemented in both CAM5 and GDFL models, which are compared with IPHOC that is implemented in CAM5 by our group. IPHOC uses three third-order moments while CLUBB only uses one third-order moment while both use a joint double-Gaussian distribution to represent the subgrid-scale variability. Despite that HOC is more physically consistent and produces more realistic low-cloud geographic distributions and transitions between cumulus and stratocumulus regimes, GCMs with traditional cloud parameterizations outperform in CREs because tuning of this type of models is more extensively performed than those with HOCs. We perform several tuning experiments with CAM5 implemented with IPHOC in an attempt to produce the nearly balanced global radiative budgets without deteriorating the low-cloud simulation. One of the issues in CAM5-IPHOC is that cloud water content is much higher than in CAM5, which is combined with higher low-cloud coverage to produce larger shortwave CREs in some low-cloud prevailing regions. Thus, the cloud-radiative feedbacks are exaggerated there. The turning exercise is focused on microphysical parameters, which are also commonly used for tuning in climate models. The results will be discussed in this presentation.

Comparing models for IMF variation across cosmological time in Milky Way-like galaxies

NASA Astrophysics Data System (ADS)

Guszejnov, Dávid; Hopkins, Philip F.; Ma, Xiangcheng

2017-12-01

One of the key observations regarding the stellar initial mass function (IMF) is its near-universality in the Milky Way (MW), which provides a powerful way to constrain different star formation models that predict the IMF. However, those models are almost universally 'cloud-scale' or smaller - they take as input or simulate single molecular clouds (GMCs), clumps or cores, and predict the resulting IMF as a function of the cloud properties. Without a model for the progenitor properties of all clouds that formed the stars at different locations in the MW (including ancient stellar populations formed in high redshift, likely gas-rich dwarf progenitor galaxies that looked little like the Galaxy today), the predictions cannot be fully explored nor safely applied to 'live' cosmological calculations of the IMF in different galaxies at different cosmological times. We therefore combine a suite of high-resolution cosmological simulations (from the Feedback In Realistic Environments project), which form MW-like galaxies with reasonable star formation properties and explicitly resolve massive GMCs, with various proposed cloud-scale IMF models. We apply the models independently to every star particle formed in the simulations to synthesize the predicted IMF in the present-day galaxy. We explore models where the IMF depends on Jeans mass, sonic or 'turbulent Bonnor-Ebert' mass, fragmentation with a polytropic equation of state, or where it is self-regulated by protostellar feedback. We show that all of these models, except the feedback-regulated ones, predict far more variation (∼0.6-1 dex 1σ scatter in the IMF turnover mass) in the simulations than is observed in the MW.

Assessing the CAM5 Physics Suite in the WRF-Chem Model: Implementation, Resolution Sensitivity, and a First Evaluation for a Regional Case Study

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

Ma, Po-Lun; Rasch, Philip J.; Fast, Jerome D.

A suite of physical parameterizations (deep and shallow convection, turbulent boundary layer, aerosols, cloud microphysics, and cloud fraction) from the global climate model Community Atmosphere Model version 5.1 (CAM5) has been implemented in the regional model Weather Research and Forecasting with chemistry (WRF-Chem). A downscaling modeling framework with consistent physics has also been established in which both global and regional simulations use the same emissions and surface fluxes. The WRF-Chem model with the CAM5 physics suite is run at multiple horizontal resolutions over a domain encompassing the northern Pacific Ocean, northeast Asia, and northwest North America for April 2008 whenmore » the ARCTAS, ARCPAC, and ISDAC field campaigns took place. These simulations are evaluated against field campaign measurements, satellite retrievals, and ground-based observations, and are compared with simulations that use a set of common WRF-Chem Parameterizations. This manuscript describes the implementation of the CAM5 physics suite in WRF-Chem provides an overview of the modeling framework and an initial evaluation of the simulated meteorology, clouds, and aerosols, and quantifies the resolution dependence of the cloud and aerosol parameterizations. We demonstrate that some of the CAM5 biases, such as high estimates of cloud susceptibility to aerosols and the underestimation of aerosol concentrations in the Arctic, can be reduced simply by increasing horizontal resolution. We also show that the CAM5 physics suite performs similarly to a set of parameterizations commonly used in WRF-Chem, but produces higher ice and liquid water condensate amounts and near-surface black carbon concentration. Further evaluations that use other mesoscale model parameterizations and perform other case studies are needed to infer whether one parameterization consistently produces results more consistent with observations.« less

Investigating the dependence of SCM simulated precipitation and clouds on the spatial scale of large-scale forcing at SGP [Investigating the scale dependence of SCM simulated precipitation and cloud by using gridded forcing data at SGP

DOE PAGES

Tang, Shuaiqi; Zhang, Minghua; Xie, Shaocheng

2017-08-05

Large-scale forcing data, such as vertical velocity and advective tendencies, are required to drive single-column models (SCMs), cloud-resolving models, and large-eddy simulations. Previous studies suggest that some errors of these model simulations could be attributed to the lack of spatial variability in the specified domain-mean large-scale forcing. This study investigates the spatial variability of the forcing and explores its impact on SCM simulated precipitation and clouds. A gridded large-scale forcing data during the March 2000 Cloud Intensive Operational Period at the Atmospheric Radiation Measurement program's Southern Great Plains site is used for analysis and to drive the single-column version ofmore » the Community Atmospheric Model Version 5 (SCAM5). When the gridded forcing data show large spatial variability, such as during a frontal passage, SCAM5 with the domain-mean forcing is not able to capture the convective systems that are partly located in the domain or that only occupy part of the domain. This problem has been largely reduced by using the gridded forcing data, which allows running SCAM5 in each subcolumn and then averaging the results within the domain. This is because the subcolumns have a better chance to capture the timing of the frontal propagation and the small-scale systems. As a result, other potential uses of the gridded forcing data, such as understanding and testing scale-aware parameterizations, are also discussed.« less

The relative importance of macrophysical and cloud albedo changes for aerosol-induced radiative effects in closed-cell stratocumulus: insight from the modelling of a case study

NASA Astrophysics Data System (ADS)

Grosvenor, Daniel P.; Field, Paul R.; Hill, Adrian A.; Shipway, Benjamin J.

2017-04-01

Aerosol-cloud interactions are explored using 1 km simulations of a case study of predominantly closed-cell SE Pacific stratocumulus clouds. The simulations include realistic meteorology along with newly implemented cloud microphysics and sub-grid cloud schemes. The model was critically assessed against observations of liquid water path (LWP), broadband fluxes, cloud fraction (fc), droplet number concentrations (Nd), thermodynamic profiles, and radar reflectivities.Aerosol loading sensitivity tests showed that at low aerosol loadings, changes to aerosol affected shortwave fluxes equally through changes to cloud macrophysical characteristics (LWP, fc) and cloud albedo changes due solely to Nd changes. However, at high aerosol loadings, only the Nd albedo change was important. Evidence was also provided to show that a treatment of sub-grid clouds is as important as order of magnitude changes in aerosol loading for the accurate simulation of stratocumulus at this grid resolution.Overall, the control model demonstrated a credible ability to reproduce observations, suggesting that many of the important physical processes for accurately simulating these clouds are represented within the model and giving some confidence in the predictions of the model concerning stratocumulus and the impact of aerosol. For example, the control run was able to reproduce the shape and magnitude of the observed diurnal cycle of domain mean LWP to within ˜ 10 g m-2 for the nighttime, but with an overestimate for the daytime of up to 30 g m-2. The latter was attributed to the uniform aerosol fields imposed on the model, which meant that the model failed to include the low-Nd mode that was observed further offshore, preventing the LWP removal through precipitation that likely occurred in reality. The boundary layer was too low by around 260 m, which was attributed to the driving global model analysis. The shapes and sizes of the observed bands of clouds and open-cell-like regions of low areal cloud cover were qualitatively captured. The daytime fc frequency distribution was reproduced to within Δfc = 0.04 for fc > ˜ 0.7 as was the domain mean nighttime fc (at a single time) to within Δfc = 0.02. Frequency distributions of shortwave top-of-the-atmosphere (TOA) fluxes from the satellite were well represented by the model, with only a slight underestimate of the mean by 15 %; this was attributed to near-shore aerosol concentrations that were too low for the particular times of the satellite overpasses. TOA long-wave flux distributions were close to those from the satellite with agreement of the mean value to within 0.4 %. From comparisons of Nd distributions to those from the satellite, it was found that the Nd mode from the model agreed with the higher of the two observed modes to within ˜ 15 %.

Diagnosing causes of cloud parameterization deficiencies using ARM measurements over SGP site

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

Wu, W.; Liu, Y.; Betts, A. K.

2010-03-15

Decade-long continuous surface-based measurements at Great Southern Plains (SGP) collected by the US Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility are first used to evaluate the three major reanalyses (i.e., ERA-Interim, NCEP/NCAR Reanalysis I and NCEP/DOE Reanalysis II) to identify model biases in simulating surface shortwave cloud forcing and total cloud fraction. The results show large systematic lower biases in the modeled surface shortwave cloud forcing and cloud fraction from all the three reanalysis datasets. Then we focus on diagnosing the causes of these model biases using the Active Remote Sensing of Clouds (ARSCL) products (e.g., verticalmore » distribution of cloud fraction, cloud-base and cloud-top heights, and cloud optical depth) and meteorological measurements (temperature, humidity and stability). Efforts are made to couple cloud properties with boundary processes in the diagnosis.« less

Factors Controlling the Properties of Multi-Phase Arctic Stratocumulus Clouds

NASA Technical Reports Server (NTRS)

Fridlind, Ann; Ackerman, Andrew; Menon, Surabi

2005-01-01

The 2004 Multi-Phase Arctic Cloud Experiment (M-PACE) IOP at the ARM NSA site focused on measuring the properties of autumn transition-season arctic stratus and the environmental conditions controlling them, including concentrations of heterogeneous ice nuclei. Our work aims to use a large-eddy simulation (LES) code with embedded size-resolved aerosol and cloud microphysics to identify factors controlling multi-phase arctic stratus. Our preliminary simulations of autumn transition-season clouds observed during the 1994 Beaufort and Arctic Seas Experiment (BASE) indicated that low concentrations of ice nuclei, which were not measured, may have significantly lowered liquid water content and thereby stabilized cloud evolution. However, cloud drop concentrations appeared to be virtually immune to changes in liquid water content, indicating an active Bergeron process with little effect of collection on drop number concentration. We will compare these results with preliminary simulations from October 8-13 during MPACE. The sensitivity of cloud properties to uncertainty in other factors, such as large-scale forcings and aerosol profiles, will also be investigated. Based on the LES simulations with M-PACE data, preliminary results from the NASA GlSS single-column model (SCM) will be used to examine the sensitivity of predicted cloud properties to changing cloud drop number concentrations for multi-phase arctic clouds. Present parametrizations assumed fixed cloud droplet number concentrations and these will be modified using M-PACE data.

Research of MPPT for photovoltaic generation based on two-dimensional cloud model

NASA Astrophysics Data System (ADS)

Liu, Shuping; Fan, Wei

2013-03-01

The cloud model is a mathematical representation to fuzziness and randomness in linguistic concepts. It represents a qualitative concept with expected value Ex, entropy En and hyper entropy He, and integrates the fuzziness and randomness of a linguistic concept in a unified way. This model is a new method for transformation between qualitative and quantitative in the knowledge. This paper is introduced MPPT (maximum power point tracking, MPPT) controller based two- dimensional cloud model through analysis of auto-optimization MPPT control of photovoltaic power system and combining theory of cloud model. Simulation result shows that the cloud controller is simple and easy, directly perceived through the senses, and has strong robustness, better control performance.

Evaluating the Influence of the Client Behavior in Cloud Computing.

PubMed

Souza Pardo, Mário Henrique; Centurion, Adriana Molina; Franco Eustáquio, Paulo Sérgio; Carlucci Santana, Regina Helena; Bruschi, Sarita Mazzini; Santana, Marcos José

2016-01-01

This paper proposes a novel approach for the implementation of simulation scenarios, providing a client entity for cloud computing systems. The client entity allows the creation of scenarios in which the client behavior has an influence on the simulation, making the results more realistic. The proposed client entity is based on several characteristics that affect the performance of a cloud computing system, including different modes of submission and their behavior when the waiting time between requests (think time) is considered. The proposed characterization of the client enables the sending of either individual requests or group of Web services to scenarios where the workload takes the form of bursts. The client entity is included in the CloudSim, a framework for modelling and simulation of cloud computing. Experimental results show the influence of the client behavior on the performance of the services executed in a cloud computing system.

Evaluating the Influence of the Client Behavior in Cloud Computing

PubMed Central

Centurion, Adriana Molina; Franco Eustáquio, Paulo Sérgio; Carlucci Santana, Regina Helena; Bruschi, Sarita Mazzini; Santana, Marcos José

2016-01-01

This paper proposes a novel approach for the implementation of simulation scenarios, providing a client entity for cloud computing systems. The client entity allows the creation of scenarios in which the client behavior has an influence on the simulation, making the results more realistic. The proposed client entity is based on several characteristics that affect the performance of a cloud computing system, including different modes of submission and their behavior when the waiting time between requests (think time) is considered. The proposed characterization of the client enables the sending of either individual requests or group of Web services to scenarios where the workload takes the form of bursts. The client entity is included in the CloudSim, a framework for modelling and simulation of cloud computing. Experimental results show the influence of the client behavior on the performance of the services executed in a cloud computing system. PMID:27441559

Numerical Simulation of an Industrial Cumulus Affected by Heat, Moisture, and CCN Released from an Oil Refinery.

NASA Astrophysics Data System (ADS)

Guan, S.; Reuter, G. W.

1996-08-01

Large oil refineries emit heat, vapor, and cloud condensation nuclei (CCN), all of which can affect the formation of cloud and precipitation. This study quantities the relative contributions of the three factors on cloud development in calm wind conditions using an axisymmetric cloud model. The factor separation technique is applied to isolate the net contributions of waste heat, vapor, and CCN on the rainfall of a cumulus developing in the industrial plume. The mutual-interactive contributions of two or three of the factors are also computed.The simulations for midlatitude and tropical conditions indicate that the sensible heat provides the major stimulus for cloud development and rain formation. The pure contribution of the industrial CCN is to enhance the condensation, causing an increase in the mass of total cloud water. The simulation results indicate that mutual interactions between waste heat and industrial CCN are large for both cases considered.

Tropical Oceanic Precipitation Processes Over Warm Pool: 2D and 3D Cloud Resolving Model Simulations

NASA Technical Reports Server (NTRS)

Tao, W.-K.; Johnson, D.; Simpson, J.; Einaudi, Franco (Technical Monitor)

2001-01-01

Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.

Top-down and bottom-up aerosol-cloud closure: towards understanding sources of uncertainty in deriving cloud shortwave radiative flux

NASA Astrophysics Data System (ADS)

Sanchez, Kevin J.; Roberts, Gregory C.; Calmer, Radiance; Nicoll, Keri; Hashimshoni, Eyal; Rosenfeld, Daniel; Ovadnevaite, Jurgita; Preissler, Jana; Ceburnis, Darius; O'Dowd, Colin; Russell, Lynn M.

2017-08-01

Top-down and bottom-up aerosol-cloud shortwave radiative flux closures were conducted at the Mace Head Atmospheric Research Station in Galway, Ireland, in August 2015. This study is part of the BACCHUS (Impact of Biogenic versus Anthropogenic emissions on Clouds and Climate: towards a Holistic UnderStanding) European collaborative project, with the goal of understanding key processes affecting aerosol-cloud shortwave radiative flux closures to improve future climate predictions and develop sustainable policies for Europe. Instrument platforms include ground-based unmanned aerial vehicles (UAVs)1 and satellite measurements of aerosols, clouds and meteorological variables. The ground-based and airborne measurements of aerosol size distributions and cloud condensation nuclei (CCN) concentration were used to initiate a 1-D microphysical aerosol-cloud parcel model (ACPM). UAVs were equipped for a specific science mission, with an optical particle counter for aerosol distribution profiles, a cloud sensor to measure cloud extinction or a five-hole probe for 3-D wind vectors. UAV cloud measurements are rare and have only become possible in recent years through the miniaturization of instrumentation. These are the first UAV measurements at Mace Head. ACPM simulations are compared to in situ cloud extinction measurements from UAVs to quantify closure in terms of cloud shortwave radiative flux. Two out of seven cases exhibit sub-adiabatic vertical temperature profiles within the cloud, which suggests that entrainment processes affect cloud microphysical properties and lead to an overestimate of simulated cloud shortwave radiative flux. Including an entrainment parameterization and explicitly calculating the entrainment fraction in the ACPM simulations both improved cloud-top radiative closure. Entrainment reduced the difference between simulated and observation-derived cloud-top shortwave radiative flux (δRF) by between 25 and 60 W m-2. After accounting for entrainment, satellite-derived cloud droplet number concentrations (CDNCs) were within 30 % of simulated CDNC. In cases with a well-mixed boundary layer, δRF is no greater than 20 W m-2 after accounting for cloud-top entrainment and up to 50 W m-2 when entrainment is not taken into account. In cases with a decoupled boundary layer, cloud microphysical properties are inconsistent with ground-based aerosol measurements, as expected, and δRF is as high as 88 W m-2, even high (> 30 W m-2) after accounting for cloud-top entrainment. This work demonstrates the need to take in situ measurements of aerosol properties for cases where the boundary layer is decoupled as well as consider cloud-top entrainment to accurately model stratocumulus cloud radiative flux. 1The regulatory term for UAV is remotely piloted aircraft (RPA).

Spatial and temporal variability of clouds and precipitation over Germany: multiscale simulations across the "gray zone"

NASA Astrophysics Data System (ADS)

Barthlott, C.; Hoose, C.

2015-11-01

This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling (COSMO) model. Six intensive observation periods of the HOPE (HD(CP)2 Observational Prototype Experiment) measurement campaign conducted in spring 2013 and 1 summer day of the same year are simulated. By means of a series of grid-refinement resolution tests (horizontal grid spacing 2.8, 1 km, 500, and 250 m), the applicability of the COSMO model to represent real weather events in the gray zone, i.e., the scale ranging between the mesoscale limit (no turbulence resolved) and the large-eddy simulation limit (energy-containing turbulence resolved), is tested. To the authors' knowledge, this paper presents the first non-idealized COSMO simulations in the peer-reviewed literature at the 250-500 m scale. It is found that the kinetic energy spectra derived from model output show the expected -5/3 slope, as well as a dependency on model resolution, and that the effective resolution lies between 6 and 7 times the nominal resolution. Although the representation of a number of processes is enhanced with resolution (e.g., boundary-layer thermals, low-level convergence zones, gravity waves), their influence on the temporal evolution of precipitation is rather weak. However, rain intensities vary with resolution, leading to differences in the total rain amount of up to +48 %. Furthermore, the location of rain is similar for the springtime cases with moderate and strong synoptic forcing, whereas significant differences are obtained for the summertime case with air mass convection. Domain-averaged liquid water paths and cloud condensate profiles are used to analyze the temporal and spatial variability of the simulated clouds. Finally, probability density functions of convection-related parameters are analyzed to investigate their dependance on model resolution and their impact on cloud formation and subsequent precipitation.

A hybrid approach to estimate the complex motions of clouds in sky images

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

Peng, Zhenzhou; Yu, Dantong; Huang, Dong

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

A hybrid approach to estimate the complex motions of clouds in sky images

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2016-09-14

Tracking the motion of clouds is essential to forecasting the weather and to predicting the short-term solar energy generation. Existing techniques mainly fall into two categories: variational optical flow, and block matching. In this article, we summarize recent advances in estimating cloud motion using ground-based sky imagers and quantitatively evaluate state-of-the-art approaches. Then we propose a hybrid tracking framework to incorporate the strength of both block matching and optical flow models. To validate the accuracy of the proposed approach, we introduce a series of synthetic images to simulate the cloud movement and deformation, and thereafter comprehensively compare our hybrid approachmore » with several representative tracking algorithms over both simulated and real images collected from various sites/imagers. The results show that our hybrid approach outperforms state-of-the-art models by reducing at least 30% motion estimation errors compared with the ground-truth motions in most of simulated image sequences. Furthermore, our hybrid model demonstrates its superior efficiency in several real cloud image datasets by lowering at least 15% Mean Absolute Error (MAE) between predicted images and ground-truth images.« less

An economical model for simulating droplet spectrum evolution in turbulent cloud chambers and wind tunnels

NASA Astrophysics Data System (ADS)

Krueger, Steven; Cantrell, W.; Niedermeier, D.; Shaw, R.; Stratmann, F.

2017-11-01

Although airborne instruments provide detailed information about the microphysical structure of clouds, the measurements provide only a few snapshots of each cloud. Deducing the droplet spectrum evolution from such measurements is next to impossible. We are using two alternative approaches: laboratory studies and numerical simulations. The former relies on a new turbulent cloud chamber (the Pi Chamber) at Michigan Technical University, as well as the first humid turbulent wind tunnel (LACIS-T) at the Leibniz Institute for Tropospheric Research. Both produce conditions for droplet growth (i.e., supersaturation) by mixing saturated vapor at different temperatures. The Pi Chamber produces turbulence by inducing Rayleigh-Bénard convection, while the wind tunnel generates turbulence with a grid. We are using the Explicit Mixing Parcel Model (EMPM) to numerically simulate droplet spectrum evolution in these flows. The EMPM explicitly links turbulent mixing and droplet spectrum evolution by representing a turbulent flow in a 1D domain with the linear eddy model. The EMPM can economically span scales from those of the smallest turbulent eddies to those of the largest. The EMPM grows or evaporates thousands of individual cloud droplets according to their local environments.

Initial studies of middle and upper tropospheric stratiform clouds

NASA Technical Reports Server (NTRS)

Cox, S. K.

1982-01-01

The spatial and temporal occurrence of cloud layers, the development of a physical-numerical model to simulate the life cycles of tropospheric cloud layers, and the design of an observational program to study the properties of these layers are described.

Model Intercomparison of CCN-Limited Arctic Clouds During ASCOS

NASA Astrophysics Data System (ADS)

Stevens, Robin; Dearden, Chris; Dimetrelos, Antonios; Eirund, Gesa; Possner, Anna; Raatikainen, Tomi; Loewe, Katharina; Hill, Adrian; Shipway, Ben; Connolly, Paul; Ekman, Annica; Hoose, Corinna; Laaksonen, Ari; de Leeuw, Gerrit; Kolmonen, Pekka; Saponaro, Giulia; Field, Paul; Carlsaw, Ken

2017-04-01

Future decreases in Arctic sea ice are expected to increase fluxes of aerosol and precursor gases from the open ocean surface within the Arctic. The resulting increase in cloud condensation nuclei (CCN) concentrations would be expected to result in increased cloud albedo (Struthers et al, 2011), leading to potentially large changes in radiative forcings. However, Browse et al. (2014) have shown that these increases in condensable material could also result in the growth of existing particles to sizes where they are more efficiently removed by wet deposition in drizzling stratocumulus clouds, ultimately decreasing CCN concentrations in the high Arctic. Their study was limited in that it did not simulate alterations of dynamics or cloud properties due to either changes in heat and moisture fluxes following sea­-ice loss or changing aerosol concentrations. Taken together, these results show that significant uncertainties remain in trying to quantify aerosol­-cloud processes in the Arctic system. The current representation of these processes in global climate models is most likely insufficient to realistically simulate long­-term changes. In order to better understand the microphysical processes currently governing Arctic clouds, we perform a model intercomparison of summertime high Arctic (>80N) clouds observed during the 2008 ASCOS campaign. The intercomparison includes results from three large eddy simulation models (UCLALES-SALSA, COSMO-LES, and MIMICA) and three numerical weather prediction models (COSMO-NWP, WRF, and UM-CASIM). The results of these experiments will be used as a basis for sensitivity studies on the impact of sea-ice loss on Arctic clouds through changes in aerosol and precursor emissions as well as changes in latent and sensible heat fluxes. Browse, J., et al., Atmos. Chem. Phys., 14(14), 7543-7557, doi:10.5194/acp-14-7543-2014, 2014. Struthers, H., et al., Atmos. Chem. Phys., 11(7), 3459-3477, doi:10.5194/acp-11-3459-2011, 2011.

Anvil Glaciation in a Deep Cumulus Updraught over Florida Simulated with the Explicit Microphysics Model. I: Impact of Various Nucleation Processes

NASA Technical Reports Server (NTRS)

Phillips, Vaughan T. J.; Andronache, Constantin; Sherwood, Steven C.; Bansemer, Aaron; Conant, William C.; Demott, Paul J.; Flagan, Richard C.; Heymsfield, Andy; Jonsson, Haflidi; Poellot, Micheal;

Confronting Models with Data: The GEWEX Cloud Systems Study

NASA Technical Reports Server (NTRS)

Randall, David; Curry, Judith; Duynkerke, Peter; Krueger, Steven; Moncrieff, Mitchell; Ryan, Brian; Starr, David OC.; Miller, Martin; Rossow, William; Tselioudis, George

2002-01-01

The GEWEX Cloud System Study (GCSS; GEWEX is the Global Energy and Water Cycle Experiment) was organized to promote development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. The strategy of GCSS is to use two distinct kinds of models to analyze and understand observations of the behavior of several different types of clouds systems. Cloud-system-resolving models (CSRMs) have high enough spatial and temporal resolutions to represent individual cloud elements, but cover a wide enough range of space and time scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the surgically extracted column physics of atmospheric general circulation models. SCMs are used to test cloud parameterizations in an un-coupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data is collected in various field programs and provided to the CSRM Community, which uses the data to "certify" the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM Community. We report here the results of a re-thinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, and an explicit recognition of the importance of data integration.

The implications of dust ice nuclei effect on cloud top temperature in a complex mesoscale convective system.

PubMed

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.

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

Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity Experiments

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.

Madden–Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer

PubMed Central

Miyakawa, Tomoki; Satoh, Masaki; Miura, Hiroaki; Tomita, Hirofumi; Yashiro, Hisashi; Noda, Akira T.; Yamada, Yohei; Kodama, Chihiro; Kimoto, Masahide; Yoneyama, Kunio

2014-01-01

Global cloud/cloud system-resolving models are perceived to perform well in the prediction of the Madden–Julian Oscillation (MJO), a huge eastward -propagating atmospheric pulse that dominates intraseasonal variation of the tropics and affects the entire globe. However, owing to model complexity, detailed analysis is limited by computational power. Here we carry out a simulation series using a recently developed supercomputer, which enables the statistical evaluation of the MJO prediction skill of a costly new-generation model in a manner similar to operational forecast models. We estimate the current MJO predictability of the model as 27 days by conducting simulations including all winter MJO cases identified during 2003–2012. The simulated precipitation patterns associated with different MJO phases compare well with observations. An MJO case captured in a recent intensive observation is also well reproduced. Our results reveal that the global cloud-resolving approach is effective in understanding the MJO and in providing month-long tropical forecasts. PMID:24801254

Madden-Julian Oscillation prediction skill of a new-generation global model demonstrated using a supercomputer.

PubMed

Miyakawa, Tomoki; Satoh, Masaki; Miura, Hiroaki; Tomita, Hirofumi; Yashiro, Hisashi; Noda, Akira T; Yamada, Yohei; Kodama, Chihiro; Kimoto, Masahide; Yoneyama, Kunio

2014-05-06

Global cloud/cloud system-resolving models are perceived to perform well in the prediction of the Madden-Julian Oscillation (MJO), a huge eastward -propagating atmospheric pulse that dominates intraseasonal variation of the tropics and affects the entire globe. However, owing to model complexity, detailed analysis is limited by computational power. Here we carry out a simulation series using a recently developed supercomputer, which enables the statistical evaluation of the MJO prediction skill of a costly new-generation model in a manner similar to operational forecast models. We estimate the current MJO predictability of the model as 27 days by conducting simulations including all winter MJO cases identified during 2003-2012. The simulated precipitation patterns associated with different MJO phases compare well with observations. An MJO case captured in a recent intensive observation is also well reproduced. Our results reveal that the global cloud-resolving approach is effective in understanding the MJO and in providing month-long tropical forecasts.

Electron-cloud updated simulation results for the PSR, and recent results for the SNS

NASA Astrophysics Data System (ADS)

Pivi, M.; Furman, M. A.

2002-05-01

Recent simulation results for the main features of the electron cloud in the storage ring of the Spallation Neutron Source (SNS) at Oak Ridge, and updated results for the Proton Storage Ring (PSR) at Los Alamos are presented in this paper. A refined model for the secondary emission process including the so called true secondary, rediffused and backscattered electrons has recently been included in the electron-cloud code.

Understanding the Microphysical Properties of Developing Cloud Clusters during TCS-08

DTIC Science & Technology

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

Methods for Quantitative Interpretation of Retarding Field Analyzer Data

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

Calvey, J.R.; Crittenden, J.A.; Dugan, G.F.

2011-03-28

Over the course of the CesrTA program at Cornell, over 30 Retarding Field Analyzers (RFAs) have been installed in the CESR storage ring, and a great deal of data has been taken with them. These devices measure the local electron cloud density and energy distribution, and can be used to evaluate the efficacy of different cloud mitigation techniques. Obtaining a quantitative understanding of RFA data requires use of cloud simulation programs, as well as a detailed model of the detector itself. In a drift region, the RFA can be modeled by postprocessing the output of a simulation code, and onemore » can obtain best fit values for important simulation parameters with a chi-square minimization method.« less

Comprehensive mapping and characteristic regimes of aerosol effects on the formation and evolution of pyro-convective clouds

DOE PAGES

Chang, D.; Cheng, Y.; Reutter, P.; ...

2015-09-21

Here, a recent parcel model study (Reutter et al., 2009) showed three deterministic regimes of initial cloud droplet formation, characterized by different ratios of aerosol concentrations ( N CN) to updraft velocities. This analysis, however, did not reveal how these regimes evolve during the subsequent cloud development. To address this issue, we employed the Active Tracer High Resolution Atmospheric Model (ATHAM) with full microphysics and extended the model simulation from the cloud base to the entire column of a single pyro-convective mixed-phase cloud. A series of 2-D simulations (over 1000) were performed over a wide range of N CN andmore » dynamic conditions. The integrated concentration of hydrometeors over the full spatial and temporal scales was used to evaluate the aerosol and dynamic effects. The results show the following. (1) The three regimes for cloud condensation nuclei (CCN) activation in the parcel model (namely aerosol-limited, updraft-limited, and transitional regimes) still exist within our simulations, but net production of raindrops and frozen particles occurs mostly within the updraft-limited regime. (2) Generally, elevated aerosols enhance the formation of cloud droplets and frozen particles. The response of raindrops and precipitation to aerosols is more complex and can be either positive or negative as a function of aerosol concentrations. The most negative effect was found for values of N CN of ~ 1000 to 3000 cm –3. (3) The nonlinear properties of aerosol–cloud interactions challenge the conclusions drawn from limited case studies in terms of their representativeness, and ensemble studies over a wide range of aerosol concentrations and other influencing factors are strongly recommended for a more robust assessment of the aerosol effects.« less

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.

The Goddard Cumulus Ensemble Model (GCE): Improvements and Applications for Studying Precipitation Processes

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Lang, Stephen E.; Zeng, Xiping; Li, Xiaowen; Matsui, Toshi; Mohr, Karen; Posselt, Derek; Chern, Jiundar; Peters-Lidard, Christa; Norris, Peter M.;

wFReDoW: A Cloud-Based Web Environment to Handle Molecular Docking Simulations of a Fully Flexible Receptor Model

PubMed Central

De Paris, Renata; Frantz, Fábio A.; Norberto de Souza, Osmar; Ruiz, Duncan D. A.

2013-01-01

Molecular docking simulations of fully flexible protein receptor (FFR) models are coming of age. In our studies, an FFR model is represented by a series of different conformations derived from a molecular dynamic simulation trajectory of the receptor. For each conformation in the FFR model, a docking simulation is executed and analyzed. An important challenge is to perform virtual screening of millions of ligands using an FFR model in a sequential mode since it can become computationally very demanding. In this paper, we propose a cloud-based web environment, called web Flexible Receptor Docking Workflow (wFReDoW), which reduces the CPU time in the molecular docking simulations of FFR models to small molecules. It is based on the new workflow data pattern called self-adaptive multiple instances (P-SaMIs) and on a middleware built on Amazon EC2 instances. P-SaMI reduces the number of molecular docking simulations while the middleware speeds up the docking experiments using a High Performance Computing (HPC) environment on the cloud. The experimental results show a reduction in the total elapsed time of docking experiments and the quality of the new reduced receptor models produced by discarding the nonpromising conformations from an FFR model ruled by the P-SaMI data pattern. PMID:23691504

Aerosol indirect effects - general circulation model intercomparison and evaluation with satellite data

NASA Astrophysics Data System (ADS)

Quaas, J.; Ming, Y.; Menon, S.; Takemura, T.; Wang, M.; Penner, J. E.; Gettelman, A.; Lohmann, U.; Bellouin, N.; Boucher, O.; Sayer, A. M.; Thomas, G. E.; McComiskey, A.; Feingold, G.; Hoose, C.; Kristjánsson, J. E.; Liu, X.; Balkanski, Y.; Donner, L. J.; Ginoux, P. A.; Stier, P.; Grandey, B.; Feichter, J.; Sednev, I.; Bauer, S. E.; Koch, D.; Grainger, R. G.; Kirkevåg, A.; Iversen, T.; Seland, Ø.; Easter, R.; Ghan, S. J.; Rasch, P. J.; Morrison, H.; Lamarque, J.-F.; Iacono, M. J.; Kinne, S.; Schulz, M.

2009-11-01

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (τa) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is found that the model-simulated influence of aerosols on cloud droplet number concentration (Nd) compares relatively well to the satellite data at least over the ocean. The relationship between τa and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and τa as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld-τa relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between τa and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR-τa relationship show a strong positive correlation between τa and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of τa, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5±0.5 Wm-2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic τa and satellite-retrieved Nd-τa regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of -0.4±0.2 Wm-2 and a cloudy-sky (aerosol indirect effect) estimate of -0.7±0.5 Wm-2, with a total estimate of -1.2±0.4 Wm-2.

Aerosol indirect effects ? general circulation model intercomparison and evaluation with satellite data

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

Quaas, Johannes; Ming, Yi; Menon, Surabi

2010-03-12

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth ({tau}{sub a}) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. It is foundmore » that the model-simulated influence of aerosols on cloud droplet number concentration (N{sub d}) compares relatively well to the satellite data at least over the ocean. The relationship between {tau}{sub a} and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (f{sub cld}) and {tau}{sub a} as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong f{sub cld} - {tau}{sub a} relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between {tau}{sub a} and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - {tau}{sub a} relationship show a strong positive correlation between {tau}{sub a} and f{sub cld} The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of {tau}{sub a}, and parameterization assumptions such as a lower bound on N{sub d}. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of -1.5 {+-} 0.5 Wm{sup -2}. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clear- and cloudy-sky forcings with estimates of anthropogenic {tau}{sub a} and satellite-retrieved Nd - {tau}{sub a} regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of -0.4 {+-} 0.2 Wm{sup -2} and a cloudy-sky (aerosol indirect effect) estimate of -0.7 {+-} 0.5 Wm{sup -2}, with a total estimate of -1.2 {+-} 0.4 Wm{sup -2}.« less

Use of cloud radar Doppler spectra to evaluate stratocumulus drizzle size distributions in large-eddy simulations with size-resolved microphysics

DOE PAGES

Remillard, J.; Fridlind, Ann M.; Ackerman, A. S.; ...

2017-09-20

Here, a case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated withmore » an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.« less

Use of cloud radar Doppler spectra to evaluate stratocumulus drizzle size distributions in large-eddy simulations with size-resolved microphysics

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

Remillard, J.; Fridlind, Ann M.; Ackerman, A. S.

Here, a case study of persistent stratocumulus over the Azores is simulated using two independent large-eddy simulation (LES) models with bin microphysics, and forward-simulated cloud radar Doppler moments and spectra are compared with observations. Neither model is able to reproduce the monotonic increase of downward mean Doppler velocity with increasing reflectivity that is observed under a variety of conditions, but for differing reasons. To a varying degree, both models also exhibit a tendency to produce too many of the largest droplets, leading to excessive skewness in Doppler velocity distributions, especially below cloud base. Excessive skewness appears to be associated withmore » an insufficiently sharp reduction in droplet number concentration at diameters larger than ~200 μm, where a pronounced shoulder is found for in situ observations and a sharp reduction in reflectivity size distribution is associated with relatively narrow observed Doppler spectra. Effectively using LES with bin microphysics to study drizzle formation and evolution in cloud Doppler radar data evidently requires reducing numerical diffusivity in the treatment of the stochastic collection equation; if that is accomplished sufficiently to reproduce typical spectra, progress toward understanding drizzle processes is likely.« less

A Comprehensive Analysis of Clouds, Radiation, and Precipitation in the North Pacific ITCZ in the NASA GISS ModelE GCM and Satellite Observations

NASA Astrophysics Data System (ADS)

Stanfield, Ryan Evan

Global circulation/climate models (GCMs) remain as an invaluable tool to predict future potential climate change. To best advise policy makers, assessing and increasing the accuracy of climate models is paramount. The treatment of clouds, radiation and precipitation in climate models and their associated feedbacks have long been one of the largest sources of uncertainty in predicting any potential future climate changes. Three versions of the NASA GISS ModelE GCM (the frozen CMIP5 version [C5], a post-CMIP5 version with modifications to cumulus and boundary layer turbulence parameterizations [P5], and the most recent version of the GCM which builds on the post-CMIP5 version with further modifications to convective cloud ice and cold pool parameterizations [E5]) have been compared with various satellite observations to analyze how recent modifications to the GCM has impacted cloud, radiation, and precipitation properties. In addition to global comparisons, two areas are showcased in regional analyses: the Eastern Pacific Northern ITCZ (EP-ITCZ), and Indonesia and the Western Pacific (INDO-WP). Changes to the cumulus and boundary layer turbulence parameterizations in the P5 version of the GCM have improved cloud and radiation estimations in areas of descending motion, such as the Southern Mid-Latitudes. Ice particle size and fall speed modifications in the E5 version of the GCM have decreased ice cloud water contents and cloud fractions globally while increasing precipitable water vapor in the model. Comparisons of IWC profiles show that the GCM simulated IWCs increase with height and peak in the upper portions of the atmosphere, while 2C-ICE observations peak in the lower levels of the atmosphere and decrease with height, effectively opposite of each other. Profiles of CF peak at lower heights in the E5 simulation, which will potentially increase outgoing longwave radiation due to higher cloud top temperatures, which will counterbalance the decrease in reflected shortwave associated with lower CFs and the thinner optical depths associated with decreased IWC and LWC in the E5 simulation. Vertical motion within the newest E5 simulation is greatly weakened over the EP-ITCZ region, potentially due to atmospheric loading from enhanced ice particle fall speeds. Comparatively, E5 simulated upward motion in the INDO-WP is stronger than its predecessors. Changes in the E5 simulation have resulted in stronger/weaker upward motion over the ocean/land in the INDO-WP region in comparison with both the C5 and P5 predecessors. Multimodel precipitation analysis shows that most of the GCMs tend to produce a wider ITCZ with stronger precipitation compared to GPCP and TRMM precipitation products. E5-simulated precipitation decreases and shifts Southward over the Easter Pacific ITCZ, which warrants further investigation into meridional heat transport and radiation fields.

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

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

Insights from modeling and observational evaluation of a precipitating continental cumulus event observed during the MC3E field campaign

DOE PAGES

Mechem, David B.; Giangrande, Scott E.; Wittman, Carly S.; ...

2015-03-13

A case of shallow cumulus and precipitating cumulus congestus sampled at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) supersite is analyzed using a multi-sensor observational approach and numerical simulation. Observations from a new radar suite surrounding the facility are used to characterize the evolving statistical behavior of the precipitating cloud system. This is accomplished using distributions of different measures of cloud geometry and precipitation properties. Large-eddy simulation (LES) with size-resolved (bin) microphysics is employed to determine the forcings most important in producing the salient aspects of the cloud system captured in the radar observations. Our emphasis ismore » on assessing the importance of time-varying vs. steady-state large-scale forcing on the model's ability to reproduce the evolutionary behavior of the cloud system. Additional consideration is given to how the characteristic spatial scale and homogeneity of the forcing imposed on the simulation influences the evolution of cloud system properties. Results indicate that several new scanning radar estimates such as distributions of cloud top are useful to differentiate the value of time-varying (or at least temporally well-matched) forcing on LES solution fidelity.« less

Cloud computing and validation of expandable in silico livers.

PubMed

Ropella, Glen E P; Hunt, C Anthony

2010-12-03

In Silico Livers (ISLs) are works in progress. They are used to challenge multilevel, multi-attribute, mechanistic hypotheses about the hepatic disposition of xenobiotics coupled with hepatic responses. To enhance ISL-to-liver mappings, we added discrete time metabolism, biliary elimination, and bolus dosing features to a previously validated ISL and initiated re-validated experiments that required scaling experiments to use more simulated lobules than previously, more than could be achieved using the local cluster technology. Rather than dramatically increasing the size of our local cluster we undertook the re-validation experiments using the Amazon EC2 cloud platform. So doing required demonstrating the efficacy of scaling a simulation to use more cluster nodes and assessing the scientific equivalence of local cluster validation experiments with those executed using the cloud platform. The local cluster technology was duplicated in the Amazon EC2 cloud platform. Synthetic modeling protocols were followed to identify a successful parameterization. Experiment sample sizes (number of simulated lobules) on both platforms were 49, 70, 84, and 152 (cloud only). Experimental indistinguishability was demonstrated for ISL outflow profiles of diltiazem using both platforms for experiments consisting of 84 or more samples. The process was analogous to demonstration of results equivalency from two different wet-labs. The results provide additional evidence that disposition simulations using ISLs can cover the behavior space of liver experiments in distinct experimental contexts (there is in silico-to-wet-lab phenotype similarity). The scientific value of experimenting with multiscale biomedical models has been limited to research groups with access to computer clusters. The availability of cloud technology coupled with the evidence of scientific equivalency has lowered the barrier and will greatly facilitate model sharing as well as provide straightforward tools for scaling simulations to encompass greater detail with no extra investment in hardware.

Sensitivity of CAM5-simulated Arctic clouds and radiation to ice nucleation parameterization

DOE PAGES

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

RACORO continental boundary layer cloud investigations. Part I: Case study development and ensemble large-scale forcings

DOE PAGES

Vogelmann, Andrew M.; Fridlind, Ann M.; Toto, Tami; ...

2015-06-19

Observation-based modeling case studies of continental boundary layer clouds have been developed to study cloudy boundary layers, aerosol influences upon them, and their representation in cloud- and global-scale models. Three 60-hour case study periods span the temporal evolution of cumulus, stratiform, and drizzling boundary layer cloud systems, representing mixed and transitional states rather than idealized or canonical cases. Based on in-situ measurements from the RACORO field campaign and remote-sensing observations, the cases are designed with a modular configuration to simplify use in large-eddy simulations (LES) and single-column models. Aircraft measurements of aerosol number size distribution are fit to lognormal functionsmore » for concise representation in models. Values of the aerosol hygroscopicity parameter, κ, are derived from observations to be ~0.10, which are lower than the 0.3 typical over continents and suggestive of a large aerosol organic fraction. Ensemble large-scale forcing datasets are derived from the ARM variational analysis, ECMWF forecasts, and a multi-scale data assimilation system. The forcings are assessed through comparison of measured bulk atmospheric and cloud properties to those computed in 'trial' large-eddy simulations, where more efficient run times are enabled through modest reductions in grid resolution and domain size compared to the full-sized LES grid. Simulations capture many of the general features observed, but the state-of-the-art forcings were limited at representing details of cloud onset, and tight gradients and high-resolution transients of importance. Methods for improving the initial conditions and forcings are discussed. The cases developed are available to the general modeling community for studying continental boundary clouds.« less

Assessment of biomass burning smoke influence on environmental conditions for multi-year tornado outbreaks by combining aerosol-aware microphysics and fire emission constraints.

PubMed

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.

Assessment of Biomass Burning Smoke Influence on Environmental Conditions for Multi-Year Tornado Outbreaks by Combining Aerosol-Aware Microphysics and Fire Emission Constraints

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.

The ENSO Effects on Tropical Clouds and Top-of-Atmosphere Cloud Radiative Effects in CMIP5 Models

NASA Technical Reports Server (NTRS)

Su, Wenying; Wang, Hailan

2015-01-01

The El Nino-Southern Oscillation (ENSO) effects on tropical clouds and top-of-atmosphere (TOA) cloud radiative effects (CREs) in Coupled Model Intercomparison Project Phase5 (CMIP5) models are evaluated using satellite-based observations and International Satellite Cloud Climatology Project satellite simulator output. Climatologically, most CMIP5 models produce considerably less total cloud amount with higher cloud top and notably larger reflectivity than observations in tropical Indo-Pacific (60 degrees East - 200 degrees East; 10 degrees South - 10 degrees North). During ENSO, most CMIP5 models considerably underestimate TOA CRE and cloud changes over western tropical Pacific. Over central tropical Pacific, while the multi-model mean resembles observations in TOA CRE and cloud amount anomalies, it notably overestimates cloud top pressure (CTP) decreases; there are also substantial inter-model variations. The relative effects of changes in cloud properties, temperature and humidity on TOA CRE anomalies during ENSO in the CMIP5 models are assessed using cloud radiative kernels. The CMIP5 models agree with observations in that their TOA shortwave CRE anomalies are primarily contributed by total cloud amount changes, and their TOA longwave CRE anomalies are mostly contributed by changes in both total cloud amount and CTP. The model biases in TOA CRE anomalies particularly the strong underestimations over western tropical Pacific are, however, mainly explained by model biases in CTP and cloud optical thickness (tau) changes. Despite the distinct model cloud biases particularly in tau regime, the TOA CRE anomalies from cloud amount changes are comparable between the CMIP5 models and observations, because of the strong compensations between model underestimation of TOA CRE anomalies from thin clouds and overestimation from medium and thick clouds.

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

The GCM-Oriented CALIPSO Cloud Product (CALIPSO-GOCCP)

NASA Astrophysics Data System (ADS)

Chepfer, H.; Bony, S.; Winker, D.; Cesana, G.; Dufresne, J. L.; Minnis, P.; Stubenrauch, C. J.; Zeng, S.

2010-01-01

This article presents the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Cloud Product (GOCCP) designed to evaluate the cloudiness simulated by general circulation models (GCMs). For this purpose, Cloud-Aerosol Lidar with Orthogonal Polarization L1 data are processed following the same steps as in a lidar simulator used to diagnose the model cloud cover that CALIPSO would observe from space if the satellite was flying above an atmosphere similar to that predicted by the GCM. Instantaneous profiles of the lidar scattering ratio (SR) are first computed at the highest horizontal resolution of the data but at the vertical resolution typical of current GCMs, and then cloud diagnostics are inferred from these profiles: vertical distribution of cloud fraction, horizontal distribution of low, middle, high, and total cloud fractions, instantaneous SR profiles, and SR histograms as a function of height. Results are presented for different seasons (January-March 2007-2008 and June-August 2006-2008), and their sensitivity to parameters of the lidar simulator is investigated. It is shown that the choice of the vertical resolution and of the SR threshold value used for cloud detection can modify the cloud fraction by up to 0.20, particularly in the shallow cumulus regions. The tropical marine low-level cloud fraction is larger during nighttime (by up to 0.15) than during daytime. The histograms of SR characterize the cloud types encountered in different regions. The GOCCP high-level cloud amount is similar to that from the TIROS Operational Vertical Sounder (TOVS) and the Atmospheric Infrared Sounder (AIRS). The low-level and middle-level cloud fractions are larger than those derived from passive remote sensing (International Satellite Cloud Climatology Project, Moderate-Resolution Imaging Spectroradiometer-Cloud and Earth Radiant Energy System Polarization and Directionality of Earth Reflectances, TOVS Path B, AIRS-Laboratoire de Météorologie Dynamique) because the latter only provide information on the uppermost cloud layer.

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

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

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.

Use of ARM observations and numerical models to determine radiative and latent heating profiles of mesoscale convective systems for general circulation models

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

Tao, Wei-Kuo; Houze, Robert, A., Jr.; Zeng, Xiping

This three-year project, in cooperation with Professor Bob Houze at University of Washington, has been successfully finished as planned. Both ARM (the Atmospheric Radiation Measurement Program) data and cloud-resolving model (CRM) simulations were used to identify the water budgets of clouds observed in two international field campaigns. The research results achieved shed light on several key processes of clouds in climate change (or general circulation models), which are summarized below. 1. Revealed the effect of mineral dust on mesoscale convective systems (MCSs) Two international field campaigns near a desert and a tropical coast provided unique data to drive and evaluatemore » CRM simulations, which are TWP-ICE (the Tropical Warm Pool International Cloud Experiment) and AMMA (the African Monsoon Multidisciplinary Analysis). Studies of the two campaign data were contrasted, revealing that much mineral dust can bring about large MCSs via ice nucleation and clouds. This result was reported as a PI presentation in the 3rd ASR Science Team meeting held in Arlington, Virginia in March 2012. A paper on the studies was published in the Journal of the Atmospheric Sciences (Zeng et al. 2013). 2. Identified the effect of convective downdrafts on ice crystal concentration Using the large-scale forcing data from TWP-ICE, ARM-SGP (the Southern Great Plains) and other field campaigns, Goddard CRM simulations were carried out in comparison with radar and satellite observations. The comparison between model and observations revealed that convective downdrafts could increase ice crystal concentration by up to three or four orders, which is a key to quantitatively represent the indirect effects of ice nuclei, a kind of aerosol, on clouds and radiation in the Tropics. This result was published in the Journal of the Atmospheric Sciences (Zeng et al. 2011) and summarized in the DOE/ASR Research Highlights Summaries (see http://www.arm.gov/science/highlights/RMjY5/view). 3. Used radar observations to evaluate model simulations In cooperation with Profs. Bob Houze at University of Washington and Steven Rutledge at Colorado State University, numerical model results were evaluated with observations from W- and C-band radars and CloudSat/TRMM satellites. These studies exhibited some shortcomings of current numerical models, such as too little of thin anvil clouds, directing the future improvement of cloud microphysics parameterization in CRMs. Two papers of Powell et al (2012) and Zeng et al. (2013), summarizing these studies, were published in the Journal of the Atmospheric Sciences. 4. Analyzed the water budgets of MCSs Using ARM data from TWP-ICE, ARM-SGP and other field campaigns, the Goddard CRM simulations were carried out to analyze the water budgets of clouds from TWP-ICE and AMMA. The simulations generated a set of datasets on clouds and radiation, which are available http://cloud.gsfc.nasa.gov/. The cloud datasets were available for modelers and other researchers aiming to improve the representation of cloud processes in multi-scale modeling frameworks, GCMs and climate models. Special datasets, such as 3D cloud distributions every six minutes for TWP-ICE, were requested and generated for ARM/ASR investigators. Data server records show that 86,206 datasets were downloaded by 120 users between April of 2010 and January of 2012. 5. MMF simulations The Goddard MMF (multi-scale modeling framework) has been improved by coupling with the Goddard Land Information System (LIS) and the Goddard Earth Observing System Model, Version 5 (GOES5). It has also been optimized on NASA HEC supercomputers and can be run over 4000 CPUs. The improved MMF with high horizontal resolution (1 x 1 degree) is currently being applied to cases covering 2005 and 2006. The results show that the spatial distribution pattern of precipitation rate is well simulated by the MMF through comparisons with satellite retrievals from the CMOPRH and GPCP data sets. In addition, the MMF results were compared with three reanalyses (MERRA, ERA-Interim and CFSR). Although the MMF tends to produce a higher precipitation rate over some topical regions, it actually well captures the variations in the zonal and meridional means. Among the three reanalyses, ERA-Interim seems to have values close to those of the satellite retrievals especially for GPCP. It is interesting to note that the MMF obtained the best results in the rain forest of Africa even better than those of CFSR and ERA-Interim, when compared to CMORPH. MERRA fails to capture the precipitation in this region. We are now collaborating with Steve Rutledge (CSU) to validate the model results for AMMA 6. MC3E and the diurnal variation of precipitation processes The Midlatitude Continental Convective Clouds Experiment (MC3E) was a joint field campaign between the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility and the NASA Global Precipitation Measurement (GPM) mission Ground Validation (GV) program. It took place in central Oklahoma during the period April 22 _ June 6, 2011. Some of its major objectives involve the use of CRMs in precipitation science such as: (1) testing the fidelity of CRM simulations via intensive statistical comparisons between simulated and observed cloud properties and latent heating fields for a variety of case types, (2) establishing the limits of CRM space-time integration capabilities for quantitative precipitation estimates, and (3) supporting the development and refinement of physically-based GMI, DPR, and DPR-GMI combined retrieval algorithms using ground-based GPM GV Ku-Ka band radar and CRM simulations. The NASA unified WRF model (nu-WRF) was used for real time forecasts during the field campaign, and ten precipitation events were selected for post mission simulations. These events include well-organized squall lines, scattered storms and quasi-linear storms. A paper focused on the diurnal variation of precipitation will be submitted in September 2012. The major highlights are as follows: a. The results indicate that NU-WRF model could capture observed diurnal variation of rainfall (composite not individual); b. NU-WRF model could simulate two different types (propagating and local type) of the diurnal variation of rainfall; c. NU-WRF model simulation show very good agreement with observation in terms of precipitation pattern (linear MCS), radar reflectivity (a second low peak shallow convection); d. NU-WRF model simulation indicates that the cool-pool dynamic is the main physical process for MCS propagation speed; e. Surface heat fluxes (including land surface model and initial surface condition) do not play a major role in phase of diurnal variation (change rainfall amount slightly); f. Terrain effect is important for initial stage of MCS (rainfall is increased and close to observation by increasing the terrain height that is also close to observed); g. Diurnal variation of radiation is not important for the simulated variation of rainfall. Publications: Zeng, X., W.-K. Tao, S. Powell, R. Houze, Jr., P. Ciesielski, N. Guy, H. Pierce and T. Matsui, 2012: A comparison of the water budgets between clouds from AMMA and TWP-ICE. J. Atmos. Sci., 70, 487-503. Powell, S. W., R. A. Houze, Jr., A. Kumar, and S. A. McFarlane, 2012: Comparison of simulated and observed continental tropical anvil clouds and their radiative heating profiles. J. Atmos. Sci., 69, 2662-2681. Zeng, X., W.-K. Tao, T. Matsui, S. Xie, S. Lang, M. Zhang, D. Starr, and X. Li, 2011: Estimating the Ice Crystal Enhancement Factor in the Tropics. J. Atmos. Sci., 68, 1424-1434. Conferences: Zeng, X., W.-K. Tao, S. Powell, R. Houze, Jr., P. Ciesielski, N. Guy, H. Pierce and T. Matsui, 2012: Comparison of water budget between AMMA and TWP-ICE clouds. The 3rd Annual ASR Science Team Meeting. Arlington, Virginia, Mar. 12-16, 2012. Zeng, X., W.-K. Tao, S. Powell, R. A. Houze Jr., and P. Ciesielski, 2011: Comparing the water budgets between AMMA and TWP-ICE clouds. Fall 2011 ASR Working Group Meeting. Annapolis, September 12-16, 2011. Zeng, X. et al., 2011: Introducing ice nuclei into turbulence parameterizations in CRMs. Fall 2011 ASR Working Group Meeting. Annapolis, September 12-16, 2011.« less

Colored thunderstorms.

PubMed

Gedzelman, Stanley David

2017-07-01

Three scenarios that produce colored thunderstorms are simulated. In Scenario #1, the thunderstorm's sunlit face exhibits a color gradient from white or yellow at top to red at base when the sun is near the horizon. It is simulated with a second-order scattering model as a combination of sunlight and skylight reflected from the cloud face that is attenuated and reddened by Rayleigh and Mie scattering over the long optical path near sunset that increases from cloud top to base. In Scenario #2, the base of the precipitation shaft appears luminous green-blue when surrounded by a much darker arcus cloud. It is simulated as multiply scattered light transmitted through the precipitation shaft using a Monte Carlo model that includes absorption by liquid water and ice. The color occurs over a wide range of solar zenith angles with large liquid water content, but the precipitation shaft is only bright when hydrometeors are large. Attenuation of the light by Rayleigh and Mie scattering outside the precipitation shaft shifts the spectrum to green when viewed from a distance of several kilometers. In Scenario #3, the shaded cloud face exhibits a "sickly" yellow-green color. It is simulated with a second-order scattering model as the result of distant skylight that originates in the sunlit region beyond an opaque anvil of order 40 km wide but is attenuated by Rayleigh and Mie scattering in its path to the cloud and observer.

The potential influence of multiple scattering on longwave flux and heating rate simulations with clouds

NASA Astrophysics Data System (ADS)

Kuo, C. P.; Yang, P.; Huang, X.; Feldman, D.; Flanner, M.; Kuo, C.; Mlawer, E. J.

2017-12-01

Clouds, which cover approximately 67% of the globe, serve as one of the major modulators in adjusting radiative energy on the Earth. Since rigorous radiative transfer computations including multiple scattering are costly, only absorption is considered in the longwave spectral bands in the radiation sub-models of the general circulation models (GCMs). Quantification of the effect of ignoring longwave scattering for flux and heating rate simulations is performed by using the GCM version of the Longwave Rapid Radiative Transfer Model (RRTMG_LW) with an implementation with the 16-stream Discrete Ordinates Radiative Transfer (DISORT) Program for a Multi-Layered Plane-Parallel Medium in conjunction with the 2010 CCCM products that merge satellite observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), the CloudSat, the Clouds and the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectrometer (MODIS). One-year global simulations show that neglecting longwave scattering overestimates upward flux at the top of the atmosphere (TOA) and underestimates downward flux at the surface by approximately 2.63 and 1.15 W/m2, respectively. Furthermore, when longwave scattering is included in the simulations, the tropopause is cooled by approximately 0.018 K/day and the surface is heated by approximately 0.028 K/day. As a result, the radiative effects of ignoring longwave scattering and doubling CO2 are comparable in magnitude.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

Zhou, Chen; Zelinka, Mark D.; Dessler, Andrew E.

The analyses of Coupled Model Intercomparison Project phase 5 simulations suggest that climate models with more positive cloud feedback in response to interannual climate fluctuations also have more positive cloud feedback in response to long-term global warming. Ensemble mean vertical profiles of cloud change in response to interannual and long-term surface warming are similar, and the ensemble mean cloud feedback is positive on both timescales. However, the average long-term cloud feedback is smaller than the interannual cloud feedback, likely due to differences in surface warming pattern on the two timescales. Low cloud cover (LCC) change in response to interannual andmore » long-term global surface warming is found to be well correlated across models and explains over half of the covariance between interannual and long-term cloud feedback. In conclusion, the intermodel correlation of LCC across timescales likely results from model-specific sensitivities of LCC to sea surface warming.« less

Catching the Drift: Simulating Dark Spots and Bright Companions on the Ice Giants

NASA Astrophysics Data System (ADS)

LeBeau, R. P., Jr.; Koutas, N.; Palotai, C. J.; Bhure, S.; Hadland, N.; Sankar, R.

2017-12-01

Starting with the original Great Dark Spot (GDS-89) observed by Voyager 2, roughly a half-dozen large geophysical vortices have been observed on the Ice Giants, the most recent in 2015 on Neptune (Wong et al., 2016). While the presumption is that these Dark Spots are similar in structure to the large vortices on Jupiter, in some cases the Dark Spots exhibit dynamical motions such as the shape oscillations and latitudinal drift of GDS-89 (Smith et al., 1989) or the possible vortex drift underlying the "Berg" cloud feature on Uranus (de Pater et al., 2011). Others, like NGDS-1998, have remained largely stable across years of observation (Sromovsky et al., 2002). In addition, several of the vortices are linked with Bright Companion clouds which are presumed to be orographic features formed as the atmosphere rises over the vortex. The numerical simulation of these features has evolved with each new observation. Prior simulations have captured the forms if not all the specifics of observed Dark Spot dynamics (LeBeau and Dowling, 1998; LeBeau and Deng, 2006); likewise, numerical models have demonstrated the potential for orographic companion clouds (Stratman et al., 2001). However, as more knowledge of the Ice Giant atmospheres has been obtained, it has proven challenging to generate consistent dynamical models that capture the details of the Dark Spot variations and are physically consistent with known observations. In particular, current simulations indicate that the addition of a companion cloud can alter the vortex dynamics, both in terms of drift and oscillations. Given the impact of these clouds, a new parametric simulation study uses an updated microphysics model, implemented in the Explicit Planetary Isentropic Coordinate (EPIC) general circulation model (Dowling et al., 1998, 2006), to account for the condensation of methane and hydrogen sulfide (Palotai et al., 2016). Simulations of dark spots with varying sizes, strengths, and locations are conducted with different microphysical parameters such as the deep abundance and ambient supersaturation. Simulations are evaluated in terms of vortex stability and drift rate along with companion cloud formation with the goal of improving our understanding of the underlying physics driving the varying behaviors of the observed Dark Spots.

The effect of mineral dust and soot aerosols on ice microphysics near the foothills of the Himalayas: A numerical investigation

NASA Astrophysics Data System (ADS)

Hazra, Anupam; Padmakumari, B.; Maheskumar, R. S.; Chen, Jen-Ping

2016-05-01

This study investigates the influence of different ice nuclei (IN) species and their number concentrations on cloud ice production. The numerical simulation with different species of ice nuclei is investigated using an explicit bulk-water microphysical scheme in a Mesoscale Meteorological Model version 5 (MM5). The species dependent ice nucleation parameterization that is based on the classical nucleation theory has been implemented into the model. The IN species considered include dust and soot with two different concentrations (Low and High). The simulated cloud microphysical properties like droplet number concentration and droplet effective radii as well as macro-properties (equivalent potential temperature and relative humidity) are comparable with aircraft observations. When higher dust IN concentrations are considered, the simulation results showed good agreement with the cloud ice and cloud water mixing ratio from aircraft measurements during Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) and Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. Relative importance of IN species is shown as compared to the homogeneous freezing nucleation process. The tendency of cloud ice production rates is also analyzed and found that dust IN is more efficient in producing cloud ice when compared to soot IN. The dust IN with high concentration can produce more surface precipitation than soot IN at the same concentration. This study highlights the need to improve the ice nucleation parameterization in numerical models.

Exploring Alternate Parameterizations for Snowfall with Validation from Satellite and Terrestrial Radars

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Petersen, Walter A.; Case, Jonathan L.; Dembek, Scott R.; Jedlovec, Gary J.

2009-01-01

Increases in computational resources have allowed operational forecast centers to pursue experimental, high resolution simulations that resolve the microphysical characteristics of clouds and precipitation. These experiments are motivated by a desire to improve the representation of weather and climate, but will also benefit current and future satellite campaigns, which often use forecast model output to guide the retrieval process. Aircraft, surface and radar data from the Canadian CloudSat/CALIPSO Validation Project are used to check the validity of size distribution and density characteristics for snowfall simulated by the NASA Goddard six-class, single-moment bulk water microphysics scheme, currently available within the Weather Research and Forecast (WRF) Model. Widespread snowfall developed across the region on January 22, 2007, forced by the passing of a midlatitude cyclone, and was observed by the dual-polarimetric, C-band radar King City, Ontario, as well as the NASA 94 GHz CloudSat Cloud Profiling Radar. Combined, these data sets provide key metrics for validating model output: estimates of size distribution parameters fit to the inverse-exponential equations prescribed within the model, bulk density and crystal habit characteristics sampled by the aircraft, and representation of size characteristics as inferred by the radar reflectivity at C- and W-band. Specified constants for distribution intercept and density differ significantly from observations throughout much of the cloud depth. Alternate parameterizations are explored, using column-integrated values of vapor excess to avoid problems encountered with temperature-based parameterizations in an environment where inversions and isothermal layers are present. Simulation of CloudSat reflectivity is performed by adopting the discrete-dipole parameterizations and databases provided in literature, and demonstrate an improved capability in simulating radar reflectivity at W-band versus Mie scattering assumptions.

Simulation of the Upper Clouds and Hazes of Venus Using a Microphysical Cloud Model

NASA Astrophysics Data System (ADS)

McGouldrick, K.

2012-12-01

Several different microphysical and chemical models of the clouds of Venus have been developed in attempts to reproduce the in situ observations of the Venus clouds made by Pioneer Venus, Venera, and Vega descent probes (Turco et al., 1983 (Icarus 53:18-25), James et al, 1997 (Icarus 129:147-171), Imamura and Hashimoto, 2001 (J. Atm. Sci. 58:3597-3612), and McGouldrick and Toon, 2007 (Icarus 191:1-24)). The model of McGouldrick and Toon has successfully reproduced observations within the condensational middle and lower cloud decks of Venus (between about 48 and 57 km altitude, experiencing conditions similar to Earth's troposphere) and it now being extended to also simulate the microphysics occurring in the upper cloud deck (between altitudes of about 57 km and 70 km, experiencing conditions similar to Earth's stratosphere). In the upper clouds, aerosols composed of a solution of sulfuric acid in water are generated from the reservoir of available water vapor and sulfuric acid vapor that is photochemically produced. The manner of particle creation (e.g., activation of cloud condensation nuclei, or homogeneous or heterogeneous nucleation) is still incompletely understood, and the atmospheric environment has been measured to be not inconsistent with frozen aerosol particles (either sulfuric acid monohydrate or water ice). The material phase, viscosity, and surface tension of the aerosols (which are strongly dependent up on the local temperature and water vapor concentration) can affect the coagulation efficiencies of the aerosol, leading to variations in the size distributions, and other microphysical and radiative properties. Here, I present recent work exploring the effects of nucleation rates and coalescence efficiencies on the simulated Venus upper clouds.

The effect of clouds on the earth's radiation balance

NASA Technical Reports Server (NTRS)

Herman, G. F.; Wu, M. L. C.; Johnson, W. T.

1979-01-01

The effect of global cloudiness on the radiation balance at the top of the atmosphere is studied in general circulation model experiments. Wintertime simulations were conducted with clouds that had realistic optical properties, and were compared with simulations in which the clouds were transparent to either solar or thermal radiation. Clouds increase the net balance by limiting longwave loss to space, but decrease it by reflecting solar radiation. It is found that the net result of cloudiness is to maintain net radiation which is less than would be realized under clear conditions: Clouds cause the net radiation at the top of the atmosphere to increase due to longwave absorption, but to decrease even more due to cloud reflectance of solar radiation.

Constraining the low-cloud optical depth feedback at middle and high latitudes using satellite observations

DOE PAGES

Terai, C. R.; Klein, S. A.; Zelinka, M. D.

2016-08-26

The increase in cloud optical depth with warming at middle and high latitudes is a robust cloud feedback response found across all climate models. This study builds on results that suggest the optical depth response to temperature is timescale invariant for low-level clouds. The timescale invariance allows one to use satellite observations to constrain the models' optical depth feedbacks. Three passive-sensor satellite retrievals are compared against simulations from eight models from the Atmosphere Model Intercomparison Project (AMIP) of the 5th Coupled Model Intercomparison Project (CMIP5). This study confirms that the low-cloud optical depth response is timescale invariant in the AMIPmore » simulations, generally at latitudes higher than 40°. Compared to satellite estimates, most models overestimate the increase in optical depth with warming at the monthly and interannual timescales. Many models also do not capture the increase in optical depth with estimated inversion strength that is found in all three satellite observations and in previous studies. The discrepancy between models and satellites exists in both hemispheres and in most months of the year. A simple replacement of the models' optical depth sensitivities with the satellites' sensitivities reduces the negative shortwave cloud feedback by at least 50% in the 40°–70°S latitude band and by at least 65% in the 40°–70°N latitude band. Furthermore, based on this analysis of satellite observations, we conclude that the low-cloud optical depth feedback at middle and high latitudes is likely too negative in climate models.« less

Constraining the low-cloud optical depth feedback at middle and high latitudes using satellite observations

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

Terai, C. R.; Klein, S. A.; Zelinka, M. D.

The increase in cloud optical depth with warming at middle and high latitudes is a robust cloud feedback response found across all climate models. This study builds on results that suggest the optical depth response to temperature is timescale invariant for low-level clouds. The timescale invariance allows one to use satellite observations to constrain the models' optical depth feedbacks. Three passive-sensor satellite retrievals are compared against simulations from eight models from the Atmosphere Model Intercomparison Project (AMIP) of the 5th Coupled Model Intercomparison Project (CMIP5). This study confirms that the low-cloud optical depth response is timescale invariant in the AMIPmore » simulations, generally at latitudes higher than 40°. Compared to satellite estimates, most models overestimate the increase in optical depth with warming at the monthly and interannual timescales. Many models also do not capture the increase in optical depth with estimated inversion strength that is found in all three satellite observations and in previous studies. The discrepancy between models and satellites exists in both hemispheres and in most months of the year. A simple replacement of the models' optical depth sensitivities with the satellites' sensitivities reduces the negative shortwave cloud feedback by at least 50% in the 40°–70°S latitude band and by at least 65% in the 40°–70°N latitude band. Furthermore, based on this analysis of satellite observations, we conclude that the low-cloud optical depth feedback at middle and high latitudes is likely too negative in climate models.« less

A numerical study of aerosol effects on the dynamics and microphysics of a deep convective cloud in a continental environment

NASA Astrophysics Data System (ADS)

Cui, Zhiqiang; Carslaw, Kenneth S.; Yin, Yan; Davies, Stewart

2006-03-01

The effects of aerosols on a deep convective cloud in a midlatitude continental environment are studied using an axisymmetric cloud model with a sectional treatment of aerosol and hydrometeor microphysical processes. Simulations are conducted using observations from the Cooperative Convective Precipitation Experiments (CCOPE). The isolated cloud occurred in an environment with low wind shear and with relatively dry air in the midtroposphere and upper troposphere. By varying the concentration of aerosol particles in the accumulation mode within realistic limits for a continental environment, the simulated cloud exhibited different properties. The overall impact as the aerosol concentration increased is that (1) the cloud development was inhibited; (2) the precipitation was suppressed; (3) the maximum values of liquid water content decreased, but the maximum values of droplet number concentration increased before the dissipating stage; (4) a clear tendency was found for ice crystals to be larger and less numerous in the anvil cloud; and (5) there was a significant reduction of the inflow in the lower 2 km of the atmosphere. In the relatively dry environment in the midtroposphere, the latent heat changes associated with the Wegener-Bergeron-Findeisen mechanism played an important role in the upper part of the cloud at altitudes below the homogeneous freezing level. In particular, immersion freezing and latent heat release were much more rapid in the base simulation than in the increased aerosol simulation. Less latent heat release and insufficient inflow together impeded the development of the cloud with the higher aerosol loading. Our simulations suggest that continental clouds existing below the homogeneous freezing level could show an opposite response of cloud top height and anvil crystal concentrations to changes in aerosol to what has previously been reported for clouds ascending to higher levels.

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

NASA Astrophysics Data System (ADS)

Grabowski, W.

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

Akyurek, Bengu Ozge

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

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.

Fast instability caused by electron cloud in combined function magnets

DOE PAGES

Antipov, S. A.; Adamson, P.; Burov, A.; ...

2017-04-10

One of the factors which may limit the intensity in the Fermilab Recycler is a fast transverse instability. It develops within a hundred turns and, in certain conditions, may lead to a beam loss. The high rate of the instability suggest that its cause is electron cloud. Here, we studied the phenomena by observing the dynamics of stable and unstable beam, simulating numerically the build-up of the electron cloud, and developed an analytical model of an electron cloud driven instability with the electrons trapped in combined function di-poles. We also found that beam motion can be stabilized by a clearingmore » bunch, which confirms the electron cloud nature of the instability. The clearing suggest electron cloud trapping in Recycler combined function mag-nets. Numerical simulations show that up to 1% of the particles can be trapped by the magnetic field. Since the process of electron cloud build-up is exponential, once trapped this amount of electrons significantly increases the density of the cloud on the next revolution. Furthermore, in a Recycler combined function dipole this multi-turn accumulation allows the electron cloud reaching final intensities orders of magnitude greater than in a pure dipole. The estimated resulting instability growth rate of about 30 revolutions and the mode fre-quency of 0.4 MHz are consistent with experimental observations and agree with the simulation in the PEI code. The created instability model allows investigating the beam stability for the future intensity upgrades.« less

Fast instability caused by electron cloud in combined function magnets

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

Antipov, S. A.; Adamson, P.; Burov, A.

One of the factors which may limit the intensity in the Fermilab Recycler is a fast transverse instability. It develops within a hundred turns and, in certain conditions, may lead to a beam loss. The high rate of the instability suggest that its cause is electron cloud. Here, we studied the phenomena by observing the dynamics of stable and unstable beam, simulating numerically the build-up of the electron cloud, and developed an analytical model of an electron cloud driven instability with the electrons trapped in combined function di-poles. We also found that beam motion can be stabilized by a clearingmore » bunch, which confirms the electron cloud nature of the instability. The clearing suggest electron cloud trapping in Recycler combined function mag-nets. Numerical simulations show that up to 1% of the particles can be trapped by the magnetic field. Since the process of electron cloud build-up is exponential, once trapped this amount of electrons significantly increases the density of the cloud on the next revolution. Furthermore, in a Recycler combined function dipole this multi-turn accumulation allows the electron cloud reaching final intensities orders of magnitude greater than in a pure dipole. The estimated resulting instability growth rate of about 30 revolutions and the mode fre-quency of 0.4 MHz are consistent with experimental observations and agree with the simulation in the PEI code. The created instability model allows investigating the beam stability for the future intensity upgrades.« less

A Multi-Model Analysis of the Cloud Phase Transition in 16 GCMs Using Satellite Observations (CALIPSO/GPCP) and Reanalysis Data (ECMWF/MERRA).

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.

Simulation of Boundary-Layer Cumulus and Stratocumulus Clouds using a Cloud-Resolving Model With Low- and Third-Order Turbulence Closures

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man; Cheng, Anning

2007-01-01

The effects of subgrid-scale condensation and transport become more important as the grid spacings increase from those typically used in large-eddy simulation (LES) to those typically used in cloud-resolving models (CRMs). Incorporation of these effects can be achieved by a joint probability density function approach that utilizes higher-order moments of thermodynamic and dynamic variables. This study examines how well shallow cumulus and stratocumulus clouds are simulated by two versions of a CRM that is implemented with low-order and third-order turbulence closures (LOC and TOC) when a typical CRM horizontal resolution is used and what roles the subgrid-scale and resolved-scale processes play as the horizontal grid spacing of the CRM becomes finer. Cumulus clouds were mostly produced through subgrid-scale transport processes while stratocumulus clouds were produced through both subgrid-scale and resolved-scale processes in the TOC version of the CRM when a typical CRM grid spacing is used. The LOC version of the CRM relied upon resolved-scale circulations to produce both cumulus and stratocumulus clouds, due to small subgrid-scale transports. The mean profiles of thermodynamic variables, cloud fraction and liquid water content exhibit significant differences between the two versions of the CRM, with the TOC results agreeing better with the LES than the LOC results. The characteristics, temporal evolution and mean profiles of shallow cumulus and stratocumulus clouds are weakly dependent upon the horizontal grid spacing used in the TOC CRM. However, the ratio of the subgrid-scale to resolved-scale fluxes becomes smaller as the horizontal grid spacing decreases. The subcloud-layer fluxes are mostly due to the resolved scales when a grid spacing less than or equal to 1 km is used. The overall results of the TOC simulations suggest that a 1-km grid spacing is a good choice for CRM simulation of shallow cumulus and stratocumulus.

The MJO Transition from Shallow to Deep Convection in CloudSat/CALIPSO Data and GISS GCM Simulations

NASA Technical Reports Server (NTRS)

DelGenio, Anthony G.; Chen, Yonghua; Kim, Daehyun; Yao, Mao-Sung

2013-01-01

The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden-Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10MJO events show the following anticipatedMJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for EarthObserving System (EOS) (AMSR-E) columnwater vapor (CWV) increases by;5 mmduring the shallow- deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between;46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow-deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV. 1.

On the potential influence of ice nuclei on surface-forced marine stratocumulus cloud dynamics

NASA Astrophysics Data System (ADS)

Harrington, Jerry Y.; Olsson, Peter Q.

2001-11-01

The mixed phase cloudy boundary layer that occurs during off-ice flow in the marine Arctic was simulated in an environment with a strong surface heat flux (nearly 800 W m-2). A two-dimensional, eddy-resolving model coupled to a detailed cloud microphysical model was used to study both liquid phase and mixed phase stratocumulus clouds and boundary layer (BL) dynamics in this environment. Since ice precipitation may be important to BL dynamics, and ice nuclei (IN) concentrations modulate ice precipitation rates, the role of IN in cloud and BL development was explored. The results of several simulations illustrate how mixed phase microphysical processes affect the evolution of the cloudy BL in this environment. In agreement with past studies, BLs with mixed phase clouds had weaker convection, shallower BL depths, and smaller cloud fractions than BLs with clouds restricted to the liquid phase only. It is shown that the weaker BL convection is due to strong ice precipitation. Ice precipitation reduces convective strength directly by stabilizing downdrafts and more indirectly by sensibly heating the BL and inhibiting vertical mixing of momentum thereby reducing surface heat fluxes by as much as 80 W m-2. This feedback between precipitation and surface fluxes was found to have a significant impact on cloud/BL morphology, producing oscillations in convective strength and cloud fraction that did not occur if surface fluxes were fixed at constant values. Increases in IN concentrations in mixed phase clouds caused a more rapid Bergeron-Findeisen process leading to larger precipitation fluxes, reduced convection and lower cloud fraction. When IN were removed from the BL through precipitation, fewer crystals were nucleated at later simulation times leading to progressively weaker precipitation rates, greater cloud fraction, and stronger convective BL eddies.

Fewer clouds in the Mediterranean: consistency of observations and climate simulations

PubMed Central

Sanchez-Lorenzo, Arturo; Enriquez-Alonso, Aaron; Calbó, Josep; González, Josep-Abel; Wild, Martin; Folini, Doris; Norris, Joel R.; Vicente-Serrano, Sergio M.

2017-01-01

Clouds play a major role in the climate system, but large uncertainties remain about their decadal variations. Here we report a widespread decrease in cloud cover since the 1970 s over the Mediterranean region, in particular during the 1970 s–1980 s, especially in the central and eastern areas and during springtime. Confidence in these findings is high due to the good agreement between the interannual variations of cloud cover provided by surface observations and several satellite-derived and reanalysis products, although some discrepancies exist in their trends. Climate model simulations of the historical experiment from the Coupled Model Intercomparison Project Phase 5 (CMIP5) also exhibit a decrease in cloud cover over the Mediterranean since the 1970 s, in agreement with surface observations, although the rate of decrease is slightly lower. The observed northward expansion of the Hadley cell is discussed as a possible cause of detected trends. PMID:28148960

Implementation of aerosol-cloud interactions in the regional atmosphere-aerosol model COSMO-MUSCAT(5.0) and evaluation using satellite data

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 %.

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.

The "Grey Zone" cold air outbreak global model intercomparison: A cross evaluation using large-eddy simulations

NASA Astrophysics Data System (ADS)

Tomassini, Lorenzo; Field, Paul R.; Honnert, Rachel; Malardel, Sylvie; McTaggart-Cowan, Ron; Saitou, Kei; Noda, Akira T.; Seifert, Axel

2017-03-01

A stratocumulus-to-cumulus transition as observed in a cold air outbreak over the North Atlantic Ocean is compared in global climate and numerical weather prediction models and a large-eddy simulation model as part of the Working Group on Numerical Experimentation "Grey Zone" project. The focus of the project is to investigate to what degree current convection and boundary layer parameterizations behave in a scale-adaptive manner in situations where the model resolution approaches the scale of convection. Global model simulations were performed at a wide range of resolutions, with convective parameterizations turned on and off. The models successfully simulate the transition between the observed boundary layer structures, from a well-mixed stratocumulus to a deeper, partly decoupled cumulus boundary layer. There are indications that surface fluxes are generally underestimated. The amount of both cloud liquid water and cloud ice, and likely precipitation, are under-predicted, suggesting deficiencies in the strength of vertical mixing in shear-dominated boundary layers. But also regulation by precipitation and mixed-phase cloud microphysical processes play an important role in the case. With convection parameterizations switched on, the profiles of atmospheric liquid water and cloud ice are essentially resolution-insensitive. This, however, does not imply that convection parameterizations are scale-aware. Even at the highest resolutions considered here, simulations with convective parameterizations do not converge toward the results of convection-off experiments. Convection and boundary layer parameterizations strongly interact, suggesting the need for a unified treatment of convective and turbulent mixing when addressing scale-adaptivity.

Kinetic and Structural Evolution of Self-gravitating, Magnetized Clouds: 2.5-dimensional Simulations of Decaying Turbulence

NASA Astrophysics Data System (ADS)

Ostriker, Eve C.; Gammie, Charles F.; Stone, James M.

1999-03-01

The molecular component of the Galaxy is comprised of turbulent, magnetized clouds, many of which are self-gravitating and form stars. To develop an understanding of how these clouds' kinetic and structural evolution may depend on their level of turbulence, mean magnetization, and degree of self-gravity, we perform a survey of direct numerical MHD simulations in which three parameters are independently varied. Our simulations consist of solutions to the time-dependent MHD equations on a two-dimensional grid with periodic boundary conditions; an additional ``half'' dimension is also incorporated as dependent variables in the third Cartesian direction. Two of our survey parameters, the mean magnetization parameter β≡c2sound/v2Alfven and the Jeans number nJ≡Lcloud/LJeans, allow us to model clouds that either meet or fail conditions for magneto-Jeans stability and magnetic criticality. Our third survey parameter, the sonic Mach number M≡σvelocity/csound, allows us to initiate turbulence of either sub- or super-Alfvénic amplitude; we employ an isothermal equation of state throughout. We evaluate the times for each cloud model to become gravitationally bound and measure each model's kinetic energy loss over the fluid-flow crossing time. We compare the evolution of density and magnetic field structural morphology and quantify the differences in the density contrast generated by internal stresses for models of differing mean magnetization. We find that the values of β and nJ, but not the initial Mach number M, determine the time for cloud gravitational binding and collapse: for mean cloud density nH2=100 cm-3, unmagnetized models collapse after ~5 Myr, and magnetically supercritical models generally collapse after 5-10 Myr (although the smallest magneto-Jeans stable clouds survive gravitational collapse until t~15 Myr), while magnetically subcritical clouds remain uncollapsed over the entire simulations; these cloud collapse times scale with the mean density as tg~n-1/2H2. We find, contrary to some previous expectations, less than a factor of 2 difference between turbulent decay times for models with varying magnetic field strength; the maximum decay time, for B~14 μG and nH2=100 cm-3, is 1.4 flow crossing times tcross=L/σvelocity (or 8 Myr for typical giant molecular cloud parameters). In all models we find turbulent amplification in the magnetic field strength up to at least the level βpert≡c2sound/δv2Alfven=0.1, with the turbulent magnetic energy between 25% and 60% of the turbulent kinetic energy after one flow crossing time. We find that for non-self-gravitating stages of evolution, when clouds have M=5-10, the mass-averaged density contrast magnitudes are in the range 0.2-0.5, with the contrast increasing both toward low and high β. Although our conclusions about density statistics may be affected by our isothermal assumption, we note that only the more strongly magnetized models appear to be consistent with estimates of clump/interclump density contrasts inferred in Galactic giant molecular clouds.